Operating performance of diverging diamond interchanges

GEORGIA DOT RESEARCH PROJECT 12-28
FINAL REPORT
OPERATING PERFORMANCE OF DIVERGING DIAMOND INTERCHANGES
OFFICE OF PERFORMANCE-BASED MANAGEMENT AND RESEARCH 15 KENNEDY DRIVE FOREST PARK GA 30297-2534

GDOT Research Project 12-28
Final Report
OPERATING PERFORMANCE OF DIVERGING DIAMOND INTERCHANGES
By Angshuman Guin Ph.D. Principal Investigator Michael Hunter Ph.D. co-Principal Investigator
Michael Rodgers Ph.D. Investigator James Anderson Graduate Research Assistant Sung Jun Park Graduate Research Assistant
School of Civil and Environmental Engineering Georgia Institute of Technology
Contract with Georgia Department of Transportation
In cooperation with U.S. Department of Transportation Federal Highway Administration
August 2018
The contents of this report reflect the views of the authors who are responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Georgia Department of Transportation or the Federal Highway Administration. This report does not constitute a standard specification or regulation.

Technical Report Documentation Page

1. Report No.
FHWA-GA-18-1228

2. Government Accession No.

4. Title and Subtitle

Operating Performance of Diverging Diamond Interchanges

3. Recipient s Catalog No.
5. Report Date
August 2018
6. Performing Organization Code

7. Author(s)
Angshuman Guin Ph.D. Michael Hunter Ph.D. Michael Rodgers Ph.D. James Anderson Sung Jun Park

8. Performing Organization Report No.
2006U97

9. Performing Organization Name and Address
Georgia Institute of Technology School of Civil and Environmental Engineering Atlanta GA 30332-0355
12. Sponsoring Organization Name and Address
Georgia Department of Transportation Office of Performance-based Management and Research 15 Kennedy Drive Forest Park GA 30297-2534

10. Work Unit No.
11. Contract or Grant No.
0011746
13. Type of Report & Period Covered
Final August 2013 February 2018
14. Sponsoring Agency Code

15. Supplementary Notes
Prepared in cooperation with the U.S. Department of Transportation Federal Highway Administration.

16. Abstract
As the result of changing traffic patterns many conventional intersections and interchanges can no longer accommodate growing traffic volumes and heavy turning movements. In response there are various innovative intersection and interchange designs proposed and implemented to better accommodate these changes and the diverging diamond interchange (DDI) is one of these alternatives. This effort conducts a sensitivity analysis of conventional diamond interchange (CDI) and DDI operational performance under various interchange lane configurations including the selected study area of the Jimmy Carter Blvd. and I-85 interchange in Norcross Georgia under varying traffic demands and turn-movement ratios. The sensitivity analysis explores the detailed conditions in which one interchange configuration provides superior performance over the other. The sensitivity analysis is structured into a two-step process with a critical lane volume (CLV) analysis as the first step followed by a VISSIM microscopic simulation study as the second step. Overall the study found that a CDI is likely the preferred option at locations with traffic volumes well below capacity and cross-street left-turn traffic proportions below 30% of the total cross-street demand and a DDI is likely preferred at locations with traffic volumes near capacity and cross-street left-turn proportions exceeding 50% of the total cross-street demand.

17. Key Words
Diverging Diamond Interchange Operational Evaluation

19. Security Class (This Report) 20. Security Class (This Page)

Unclassified

Unclassified

18. Distribution Statement

21. No of Pages 71

22. Price

Form DOT F 1700.7 (8/72) Reproduction of form and completed page is authorized

Operating Performance of Diverging Diamond Interchanges

TABLE OF CONTENTS

LIST OF TABLES

viii

LIST OF FIGURES

ix

LIST OF SYMBOLS AND ABBREVIATIONS

xii

EXECUTIVE SUMMARY

xv

CHAPTER 1. INTRODUCTION

1

1.1 Background

2

1.2 Project Goals and Scope

3

1.3 Report Organization

4

CHAPTER 2. LITERATURE REVIEW

5

2.1 Diverging Diamond Interchange Design

5

2.2 Diverging Diamond Interchange Costs and Benefits

7

2.2.1 Operational Performance of DDI vs. Other Interchange Designs

7

2.2.2 Other Benefits and Costs

12

2.3 Methodologies in Diverging Diamond Interchange Studies

15

2.3.1 Microscopic Simulation Study

15

2.3.2 Critical Lane Volume Method

16

2.3.3 Other Methodologies

18

2.3.4 Traffic Scenario Selection Methodologies

18

2.3.5 Balanced and Unbalanced Traffic Volume

19

CHAPTER 3. METHODOLOGY

21

3.1 Overview Flow Chart of the Study Procedure

21

3.2 Lane Configuration Selection

23

3.3 Sensitivity Analysis of DDI and CDI

26

3.3.1 Sensitivity Analysis Structure and Assumptions

28

3.3.2 Traffic Scenarios Selection

28

3.3.3 Synchro Signal Optimization

30

3.3.4 Critical Lane Volume Analysis

32

3.3.5 Microscopic Simulation Study

40

3.4 Implementation

44

3.4.1 Synchro Signal Optimization

44

3.4.2 CLV Study and Comparative Analysis

45

3.4.3 VISSIM Simulation Analysis

47

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Operating Performance of Diverging Diamond Interchanges

CHAPTER 4. RESULTS AND DISCUSSION

49

4.1 CLV Analysis Results

49

4.2 Microscopic Simulation Study Results

52

4.2.1 Lane Configuration 1 (LC1)

52

4.2.2 Lane Configuration 2 (LC2)

55

4.2.3 Lane Configuration 3 (LC3)

58

4.3 Discussion and Evaluation of the Results

60

CHAPTER 5. CONCLUSIONS AND Recommendations

63

5.1 Conclusions

63

5.2 Recommendations

64

5.3 Limitations in the Study

65

CHAPTER 6. REFERENCES

69

APPENDIX A. PRE-DEPLOYMENT DATA COLLECTION AND ANALYSIS
A.1 Data Source Collection Sites and Routes
A.1.1 Bluetooth Characteristics Affecting Travel Times
A.2 Previous Research A.3 Multiple Travel-time Distribution Separation A.4 Multiple LOS Rating Assignment A.5 Results A.6 Analysis and Discussion A.7 Limitations and Future Applications
A.7.1 Scenario One Uniform Sampling Rate Over All Road User Subgroups
A.7.2 Scenario Two Cannot Assume Uniform Sampling Rate Over All Road User Sub Groups
A.8 Conclusions A.9 References

A-1
A-3 A-8
A-11 A-14 A-20 A-21 A-25 A-28
A-28
A-29
A-30 A-32

APPENDIX B. COST OF CONSTRUCTION OF DIVERGING DIAMOND

INTERCHANGES AND ALTERNATIVE DESIGNS AT FOUR

LOCATIONS

B-1

APPENDIX C. EXCEL MACRO VISUAL BASIC SCRIPTS

C-1

C.1 Optimized Signal Timing Relocation

C-1

C.2 Volume-to-Capacity Ratio Calculation and Redistribution

C-2

C.2.1 DDI_CLV script

C-2

C.2.2 CDI_CLV script

C-3

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Operating Performance of Diverging Diamond Interchanges

APPENDIX D. MICROSOFT VISUAL STUDIO VISUAL BASIC SCRIPTS D-1

APPENDIX E. CRITICAL LANE VOLUME ANALYSIS RESULTS

E-1

E.1 Lane Configuration 1

E-6

E.1.1 Color-Coded Tables of CDI and DDI v/c Ratios

E-6

E.1.2 Plots of Difference between CDI and DDI v/c Ratios

E-12

E.2 Lane Configuration 2

E-17

E.2.1 Color-Coded Tables of v/c Ratios of CDIs and DDIs

E-17

E.2.2 Plots of Difference between CDI and DDI v/c Ratios

E-23

E.3 Lane Configuration 3

E-28

E.3.1 Color-Coded Tables of v/c Ratios of CDIs and DDIs

E-28

E.3.2 Plots of Difference between CDI and DDI v/c Ratios

E-34

APPENDIX F. MICROSCOPIC SIMULATION STUDY RESULTS

F-1

F.1 Lane Configuration 1

F-9

F.1.1 Cross-Street Demand 1500 vph

F-9

F.1.2 Cross-Street Demand 2100 vph

F-13

F.1.3 Cross-Street Demand 2500 vph

F-17

F.2 Lane Configuration 2

F-21

F.2.1 Cross-Street Demand 1500 vph

F-21

F.2.2 Cross-Street Demand 2100 vph

F-25

F.2.3 Cross-Street Demand 2500 vph

F-29

F.3 Lane Configuration 3

F-33

F.3.1 Cross-Street Demand 1500 vph

F-33

F.3.2 Cross-Street Demand 2100 vph

F-37

F.3.3 Cross-Street Demand 2500 vph

F-41

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Operating Performance of Diverging Diamond Interchanges
LIST OF TABLES
Table 1 Balanced and unbalanced volumes ..................................................................... 20 Table 2 Vehicle volumes tested in the study ................................................................... 29 Table 3 Turn-movement ratios tested in the study .......................................................... 29 Table 4 DDI and CDI critical movements ....................................................................... 33 Table 5 Lane utilization factor calculation ...................................................................... 36 Table 6 Color schematics of color-coded spreadsheet for v/c ratios ............................... 39 Table 7 Selected demand scenarios for the simulation study .......................................... 40 Table 8 Selected through/left proportions for the simulation study ................................ 41
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Operating Performance of Diverging Diamond Interchanges
LIST OF FIGURES
Figure 1 Layout of a diverging diamond interchange........................................................ 6 Figure 2 Six types of partial cloverleaf............................................................................ 11 Figure 3 Conflict diagram of (a) DDI (b) CDI and (c) SPUI ........................................ 13 Figure 4 Flow chart of the study procedure ..................................................................... 22 Figure 5 Before configuration of the conventional diamond interchange at Jimmy Carter
Blvd. and I-85 in Norcross GA ................................................................................ 24 Figure 6 After configuration of the diverging diamond interchange at Jimmy Carter
Blvd. and I-85 in Norcross GA ................................................................................ 25 Figure 7 CDI (left) and DDI (right) in lane configuration 1............................................ 25 Figure 8 CDI (left) and DDI (right) in lane configuration 2............................................ 26 Figure 9 CDI (left) and DDI (right) in lane configuration 3............................................ 26 Figure 10 Sample dual ring diagram of the diverging diamond interchange .................. 32 Figure 11 Sample dual ring diagram of the conventional diamond interchange ............. 32 Figure 12 Turning movement schematic of the conventional diamond interchange....... 33 Figure 13 Turning movement schematic of the diverging diamond interchange ............ 34 Figure 14 VISSIM model for the conventional diamond interchange (LC1).................. 42 Figure 15 VISSIM model for the diverging diamond interchange (LC1) ....................... 42 Figure 16 Optimized signal timings exported to a CSV file............................................ 45 Figure 17 Signal plans reorganized in the CLV spreadsheet........................................... 45 Figure 18 Spreadsheet for v/c ratio calculation for the CLV analysis............................. 46
ix

Operating Performance of Diverging Diamond Interchanges Figure 19 Difference in v/c ratios between CDI and DDI for LC1 at different traffic
demands and through/left proportions ...................................................................... 51 Figure 20 Difference in v/c ratios between CDI and DDI for LC2 at different traffic
demands and through/left proportions ...................................................................... 51 Figure 21 Difference in v/c ratios between CDI and DDI for LC3 at different traffic
demands and through/left proportions ...................................................................... 52 Figure 22 DDI and CDI average delay per vehicle and interchange throughput with
cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC1 .................................................................................................. 54 Figure 23 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC1 .................................................................................................. 54 Figure 24 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1 .................................................................................................. 55 Figure 25 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2 .................................................................................................. 56 Figure 26 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2 .................................................................................................. 57
x

Operating Performance of Diverging Diamond Interchanges Figure 27 DDI and CDI average delay per vehicle and interchange throughput with
cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2 .................................................................................................. 57 Figure 28 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3 .................................................................................................. 59 Figure 29 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3 .................................................................................................. 59 Figure 30 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3 .................................................................................................. 60
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Operating Performance of Diverging Diamond Interchanges

CAP-X CDI CLV DCD DDI DLT DOT DXI FHWA HCM LC LUF MoDOT MOE mph MUT ParClo ROW SPUI USC v/c

LIST OF SYMBOLS AND ABBREVIATIONS
Capacity Analysis for Planning of Junctions Conventional Diamond Interchange Critical Lane Volume Double Crossover Diamond Interchange Diverging Diamond Interchange Displaced Left-Turn Intersection Department of Transportation Double Crossover Interchange Federal Highway Administration Highway Capacity Manual Lane Configuration Lane Utilization Factor Missouri Department of Transportation Measure of Effectiveness Miles per Hour Median U-Turn Partial Cloverleaf Right-of-Way Single-Point Urban Interchange Upstream Signalized Crossover Volume-to-Capacity

xii

VB vph vphrpln XDL

Operating Performance of Diverging Diamond Interchanges
Visual Basic Vehicle per Hour Vehicle per Hour per Lane Crossover Displaced Left-Turn

xiii

Operating Performance of Diverging Diamond Interchanges
EXECUTIVE SUMMARY
Due to changing traffic patterns many conventional intersections and interchanges can no longer accommodate growing traffic volumes and heavy turning movements. In response there are various innovative intersection and interchange designs proposed and implemented to better accommodate these changes and the diverging diamond interchange (DDI) is one of these alternatives. The DDI is designed to better accommodate heavy leftturn movements and it provides simplified signal operations with fewer phases and reduced lost times compared to a conventional diamond interchange (CDI). Previous studies have also found safety and cost benefits of the DDI in comparison to conventional interchange designs.
To contribute to these studies this effort aims to conduct a sensitivity analysis of CDI and DDI operational performance under various interchange lane configurations including the selected study area of the Jimmy Carter Blvd. and I-85 interchange in Norcross Georgia under varying traffic demands and turn-movement ratios. The sensitivity analysis explores the detailed conditions in which one interchange configuration provides superior performance over the other. A literature review is conducted on the DDI background and concepts the benefits and costs of a DDI in comparison to the CDI and other unconventional interchange designs and the methodologies used in previous studies on CDI and DDI operational performance analysis.
The sensitivity analysis is structured into a two-step process. First a critical lane volume (CLV) method calculates the volume-to-capacity (v/c) ratio of each interchange design using the capacity and volume equations from the Highway Capacity Manual (HCM
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Operating Performance of Diverging Diamond Interchanges
2010). This CLV method allows for a quick analysis of a large number of traffic scenarios. The second part of the analysis is a VISSIM microscopic simulation study. The simulation study is conducted for a subset of the demand scenarios to confirm the comparative performance findings of the CLV analysis. VISSIM allows users to control multiple traffic parameters and allows for more detailed analysis of the network operational performance with various operational measures such as average delay per vehicles throughput queue length and average number of stops per vehicle for individual turning movements as well as for the entire interchange.
From the CLV analysis the CDI is found to perform better or similar to the DDI when the cross-street left-turn proportion onto the freeway entrance ramp is below 30% of the total cross-street demand and in most cases the DDI outperforms the CDI at left-turn proportions exceeding 50%. The CDIs and DDIs were found to have similar performance in the through/left-turn proportion ranges of 70/30 and 50/50 often dependent on cross street cross sections. As the number of cross-street lanes increases especially left-turn lanes the left-turn proportion required for the DDI to provide favorable performance increases. Similar results are found in the VISSIM simulation study based on the average delay per vehicle and average throughput of the CDI and DDI configurations over different through/left-turn proportions. The CDI configuration is also found to have better performance at low cross-street demands at given through/left-turn proportion although the CDI operational performance degrades more rapidly than that of the DDI at high crossstreet demands. The impact of freeway off-ramp demands on the operational performance is inconclusive.
xvi

Operating Performance of Diverging Diamond Interchanges Overall the study found that a CDI is likely the preferred option at locations with traffic volumes well below capacity and cross-street left-turn traffic proportions below 30% of the total cross-street demand and a DDI is likely preferred at locations with traffic volumes near capacity and cross-street left-turn proportions exceeding 50% of the total cross-street demand. Findings from this study can support planning and decision-making processes associated with the implementation of DDIs.
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Operating Performance of Diverging Diamond Interchanges
CHAPTER 1. INTRODUCTION
Rapidly growing traffic demand and changing traffic patterns have led to the operational failure of many segments of the existing transportation infrastructure (Chlewicki 2003). According to the 2015 Urban Mobility Scorecard the national yearly average delay per commuter in 2014 was 42 hours and the total cost of congestion was $160 billion. In the same year Atlanta Georgia recorded a yearly delay per commuter of 52 hours which ranked twelfth among large urban areas with population over 3 million and had a congestion cost of $1 130 per commuter. However conventional solutions to these problems e.g. adding more lanes and building more infrastructure are becoming increasingly difficult to implement. It is becoming more problematic to find sufficient funding and right-of-way to expand roadways. Consequently traffic engineers are seeking innovative intersection and interchange designs to better accommodate these challenges. The diverging diamond interchange (DDI) is one such innovative intersection that is receiving increasing interest in the United States.
A DDI is an unconventional interchange design that eliminates the left-turn opposing through vehicle conflict from the conventional diamond interchange (CDI). Its design may offer additional benefits compared to conventional diamond interchanges. In a DDI the cross-street traffic is diverted to travel on the left side (as opposed to all traffic on the right) of the bridge. The changeover of sides of travel is facilitated at the bridge ends. A DDI reduces total conflict points from 30 within a traditional diamond interchange to 18 provides free-flow travel to the left-turning traffic as well as reduces the signal to two
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Operating Performance of Diverging Diamond Interchanges
phases. A DDI provides superior operational performance to a traditional diamond interchange under high left-turn movements onto and off a freeway.
Georgia s first diverging diamond interchange Ashford Dunwoody DDI at I-285 opened to drivers in June 2012. Shortly afterward two more DDIs were built on Pleasant Hill Road at I-85 and on Jimmy Carter Blvd. at I-85. This current project was undertaken during the planning stage of the Jimmy Carter Blvd. interchange to enable performance evaluation at that site to determine how operational efficiency has improved under Georgia driving conditions to determine under what conditions a DDI may provide superior performance to a traditional diamond interchange and to allow for potential improvements in future proposed DDIs.
1.1 Background
The DDI also called a double crossover diamond interchange (DCD) was first introduced in the United States by Gilbert Chlewicki in 2003. A DDI has crossovers on each side of an interchange to move traffic onto the left side of the road which is opposite to conventional traffic movement. A DDI eliminates left-turn vehicle conflicts with other movements allowing for free-flow left-turn operation. Many studies have suggested that a DDI improves the operation of turning movements and significantly reduces the number of vehicle-to-vehicle conflict points compared to a conventional diamond interchange.
Since the first DDI opened at I-44 and MO-13 in Springfield Missouri on June 21 2009 89 DDIs have been built in the United States (as of July 2017) with many more being planned (Chlewicki 2014). There are five DDIs currently in operation in the state of Georgia.
2

Operating Performance of Diverging Diamond Interchanges 1.2 Project Goals and Scope
Although previous studies have examined the operational performance of a DDI and compared it to other interchange designs there currently are no guidance or criteria that specify conditions that justify the conversion of a CDI into a DDI. Therefore the primary objective of this study is to evaluate the comparative operational performance of CDI and DDI configurations across a range of traffic demands and turn-movement ratios. To achieve this goal a sensitivity analysis of the operational performance under CDIs and DDIs is conducted for three different lane configurations including the beforeafter lane configuration at the selected Jimmy Carter Blvd. and I-85 interchange in Norcross Georgia.
Independent variables tested in the sensitivity analysis are traffic demand and turnmovement ratio which are two critical variables in the operation of an interchange. These independent variables are tested among different interchange lane configurations to increase the applicability of the findings. The sensitivity analysis is conducted in a twostep process (1) a critical lane volume (CLV) analysis and (2) a VISSIM simulation study. Primary measures of effectiveness (MOEs) collected in the study are volume-to-capacity (v/c) ratio and average delay per vehicle with additional measures of travel time queue length and average number of stops per vehicle collected. The scope of the study is limited to the interchange including off- and on-ramps bridge segment and cross streets entering the bridge and does not include adjacent intersections. This scope limits the number of confounding variables enhancing the ability to conduct the analysis in a reasonable timeframe and interpret the results.
3

Operating Performance of Diverging Diamond Interchanges 1.3 Report Organization
This report is organized in the following manner. CHAPTER 2 presents a literature review on the DDI background and concepts benefits and costs of a DDI in comparison to a CDI and other unconventional interchange designs and methodologies used in previous studies on DDI operational performance. CHAPTER 3 presents the methodology performance measures and analysis techniques used in this study. CHAPTER 4 highlights and evaluates the results of the sensitivity analysis using the CLV method and the VISSIM simulation study. CHAPTER 5 concludes with a results summary study limitations and potential future research. Operational performancerelated data were collected at the beginning of the study and analysis of the pre-deployment traffic patterns was performed. However the study focused on providing guidance on when DDIs are more advantageous than CDIs hence a beforeafter evaluation based on field data was not performed. The pre-deployment field data analysis is provided in Appendix A.
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Operating Performance of Diverging Diamond Interchanges
CHAPTER 2. LITERATURE REVIEW
This literature review provides an overview and background for the diverging diamond interchange layout and operation analyses and methodologies as well as published operational performance comparisons of DDIs with conventional diamond interchanges.
2.1 Diverging Diamond Interchange Design
The DDI is an innovative interchange design first introduced in the United States by Gilbert Chlewicki in 2003 at the 2nd Urban Street Symposium in Anaheim California (Chlewicki 2003). Figure 1 shows the vehicle movement layout of a DDI. The freeway access and egress are the same for a CDI and a DDI however in a DDI through and leftturn traffic on the cross streets traverse over to the opposite side (left side) of the roadway between ramp terminals (Bared et al. 2005). In this configuration the cross-street traffic enters the freeway on-ramps uninterrupted i.e. without a conflict point eliminating the need for dedicated left-turn phasing from the cross street to the freeway ramp. Thus a DDI may accommodate heavier left-turn demand than a CDI. As illustrated in Figure 1 a DDI has two traffic signalcontrolled conflict points one at each crossover. A two-phased timing plan is implemented at each crossing point with the freeway off-ramp phase simultaneous with the non-conflicting cross-street direction of traffic. As a result of the crossovers through movements in each direction follow a split-phased timing pattern unlike those in a CDI where through movements typically receive concurrent green indications.
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Operating Performance of Diverging Diamond Interchanges
Figure 1 Layout of a diverging diamond interchange (Chlewicki 2003) Prior to Chlewicki s introduction of the concept in the United States in 2003 the DDI configuration existed in Versailles France at Autoroute de Normandie and Blvd. de Jardy (Chlewicki 2014). The first DDI in the United States opened in June 2009 at the I44 and SR-13 interchange in Springfield Missouri. Currently there are 89 DDIs in operation in the United States with the number planned for construction increasing every year (Chlewicki 2014). DDIs are seeing increasing interest in the United States due to their low construction costs and right-of-way (ROW) needs as well as reasonable traffic operations and safety improvements (Chlewicki 2003 Bared et al. 2005 Edara et al. 2005 Sharma and Chatterjee 2007 Speth 2008 Missouri Department of Transportation 2010 Chilukuri et al. 2011 Chlewicki 2011 Galletebeitia 2011 Khan and Anderson 2016). The following section discusses DDI benefits and costs in more detail.
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Operating Performance of Diverging Diamond Interchanges
2.2 Diverging Diamond Interchange Costs and Benefits
Various cost/benefit studies have explored DDI performance related to operations safety construction costs etc. This section summarizes several of those studies as well as prior research comparing DDIs to CDIs and other unconventional interchange designs.
2.2.1 Operational Performance of DDI vs. Other Interchange Designs
2.2.1.1 DDI vs. CDI Chlewicki s first DDI study (2003) compared the original design of the interchange
at I-695 and MD 140 in Baltimore County Maryland to a DDI with the same lane configurations and traffic volumes. Chlewicki found that the total number of stops total delay and stop delay at the CDI were two- three- and four-fold respectively that of the DDI.
Edara et al. (2005) compared DDIs having two different lane configurations (fourand six-lane) and a CDI (six-lane) for four different traffic scenarios. The study found similar performance of both DDIs and the CDI design at low-to-medium volumes but the DDIs outperformed the CDI in all performance measures at high volumes. The DDIs also had a higher maximum off-ramp capacity of 700 vehicles per hour per lane (vphrpln) compared to the CDI with 390 vphrpln. For both DDI lane configurations tested the capacity of the cross-street left turn to the freeway on-ramp was twice that of the CDI a benefit of the left movement being uninterrupted (i.e. moving throughout the cycle).
Other studies conducted by Bared et al. (2005) Sharma and Chatterjee (2007) and Speth (2008) concluded that DDIs outperformed CDIs in most tested traffic scenarios and the difference in performance was larger at high flow levels and heavy left-turn movements.
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Operating Performance of Diverging Diamond Interchanges
All these studies showed that DDIs operated better than CDIs despite fewer lanes on the bridge segment. Bared et al. (2005) also found that capacities of all signalized movements were higher for the DDI and that the DDI cross-street to on-ramp left-turn movement capacity was twice that of the CDI.
Chilukuri et al. (2011) conducted a before-and-after analysis of the DDI at I-44 and Route 13 in Springfield Missouri and concluded that overall traffic flow through the DDI improved relative to the former CDI. Despite the increase in traffic volumes after DDI implementation the DDI had significantly lower delay and queuing for left-turn movements than the CDI. The DDI had a slight increase in the through-movement travel time due to slower speeds through the crossover intersections during off-peak periods. Chilukuri et al. also highlighted that oversized loads up to 18 ft wide and 200 ft long successfully moved through the DDI.
In addition to higher left-turn movement capacity the DDI s operational benefits also come from its ability to combine phases that conflict in the CDI configuration. For instance freeway on- and off-ramp phases can be combined with mainline through movements. Also the reduction of a phase compared to a CDI reduces lost time in a cycle and thus reduces delay (Chlewicki 2003). Similar findings were observed in a Missouri Department of Transportation (MoDOT) report based on MoDOT s experience with DDIs (2010). MoDOT found that signal operations were improved by converting from a CDI to a DDI having fewer phases a shorter cycle length and lower lost time.
Even with those documented benefits a DDI is not the solution for all traffic conditions. Khan and Anderson (2016) evaluated DDIs as a possible solution for existing interchanges in Athens Alabama by testing 83 traffic scenarios. Their results show that
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Operating Performance of Diverging Diamond Interchanges
only four scenarios had lower delay for the DDI likely due to relatively low turning movements relative to the through movements. Chlewicki (2011) suggested that while DDI is not the best option in each case there is sufficient evidence to suggest that a DDI should always be considered in an interchange improvement analysis. The results from that experiment with 15 626 volume combinations show that the DDI has superior operations to the CDI when costs are similar and the DDI is the better option if an interchange requires more lanes to accommodate higher traffic volumes.
2.2.1.2 Comparison with Other Interchange Design Alternatives
Additional studies have explored DDI performance in comparison to other unconventional interchange design alternatives. Speth (2008) was one of the first to compare the operational performance of a DDI to a single-point urban interchange (SPUI). The study found that the SPUI performs slightly better than the DDI at low-volume scenarios but the DDI outperforms the SPUI in all other scenarios in vehicle throughput average delay per vehicle and average number of stops per vehicle and it requires fewer lanes in the bridge section.
Galletebeitia (2011) conducted a study to compare and evaluate the operational performance between a DDI and partial cloverleaf (ParClo) interchanges using the microscopic simulation platform AIMSUN. Of all U.S. interchanges 16% are a ParClo configuration. ParClo interchanges are often selected for their accommodation of heavy left-turn movements similar to a DDI. There are several ParClo interchange configurations categorized as ParClo A (indicating a cloverleaf configuration on an on-ramp) ParClo B (cloverleaf configuration on an off-ramp) and ParClo AB (cloverleaf configuration on both the on- and off-ramps). In addition a ParClo configuration may utilize from one to four
9

Operating Performance of Diverging Diamond Interchanges quadrants for the interchange. Figure 2 shows six types of ParClo interchange (Zhang and Zong 2010). Zhang and Zong conducted a study focused on evaluating ParClo A4 and ParClo B4 interchanges and four-lane and six-lane DDIs (DDI-4 DDI-6). The study tested 10 volume scenarios in balanced and unbalanced conditions and found that the DDI and ParClo interchange performances are similar at low-to-medium volumes in both balanced and unbalanced conditions. In the balanced condition ParClo interchanges experienced lower delays stop times and number of stops compared to the DDIs although the difference in delay between DDI-6 and ParClo B4 decreased as the traffic flow increased. The ParClo B4 resulted in the longest maximum queue as the flow increased. In the unbalanced condition ParClo B4 showed the best results in all measures at low-to-medium volumes but both DDI-4 and DDI-6 resulted in better performance than the ParClo interchanges as the flow increased. The study concluded that ParClo interchanges perform better in balanced conditions with low-to-medium traffic flow and DDIs perform better in unbalanced conditions at high flow.
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Operating Performance of Diverging Diamond Interchanges
Figure 2 Six types of partial cloverleaf (Zhang and Zong 2010) Autey et al. (2012) conducted a study to compare the operational performance of four unconventional intersection designs--crossover displaced left-turn (XDL) upstream signalized crossover (USC) double crossover intersection (DXI) and median U-turn (MUT)--as well as a conventional intersection with equal lane configurations in balanced and unbalanced volume conditions. The DXI may intuitively be thought of as the intersection form of the DDI with mainline traffic passing through the intersection with left-hand side travel resulting in free flow left turn movement from the mainline. The results showed that all the tested unconventional designs performed better than the conventional intersection in most cases and the improvements became more significant at high traffic volumes. Among the tested unconventional designs the XDL consistently
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Operating Performance of Diverging Diamond Interchanges
outperformed other designs under both balanced and unbalanced volume conditions especially at high volumes. In balanced traffic volumes XDL USC and DXI performed equally well for moderate approach volumes (11001500 veh/hr) but for approach volumes higher than 1500 veh/hr the XDL outperformed the other intersections. In unbalanced conditions the XDL outperformed other intersection designs in all volume scenarios. The DXI performed better than the USC in most unbalanced conditions (i.e. ratio between the minor and the major street volumes less than 70%). The MUT resulted in the highest average delay per vehicle especially with high approach volumes and heavy left-turning ratios. However the XDL and the MUT designs require greater right-of-way to accommodate their designs and hence may not be appropriate alternatives to a conventional intersection in many cases.
2.2.2 Other Benefits and Costs Numerous studies suggest that the DDI has several safety benefits over other
interchange designs. Its unique design eliminates left-turn movement conflicts. With 24 and 30 conflict points respectively both the SPUI and the CDI have more conflict points than a DDI which has 18 (Chlewicki 2003 Cogan 2008 MoDOT 2010 Ressel 2012). Figure 3 shows the conflict diagrams of a CDI a DDI and a SPUI.
A DDI also provides for easier U-turn movements on a limited-access highway allowing a vehicle to return to a missed exit (MoDOT 2010). In a CDI drivers must go through two signalized left turns to re-enter the highway whereas for a DDI a returning vehicle must pass through only one signal as the on-ramp left-turn is uninterrupted. A DDI also eliminates wrong-way movements to and from ramps. However in the DDI
12

Operating Performance of Diverging Diamond Interchanges interchange configuration the intersection crossover prohibits a vehicle s through movement from an off-ramp to an on-ramp to re-enter the highway.

(a)

(b)

(c)

Figure 3 Conflict diagram of (a) DDI (b) CDI and (c) SPUI (MoDOT 2010)

A concern related to the DDI configuration is the potential for confusion given the unfamiliarity of drivers with the crossover intersections and driving on the left side of the road. However this disadvantage can be mitigated through an aggressive public information campaign and appropriate education by states and cities (Chlewicki 2003 MoDOT 2010). According to an online and telephone survey conducted by Chilukuri (2011) on the DDI at I-44 and Route 13 91% of participants expressed a good understanding of the operation of the DDI and more than 80% stated that the traffic flow had improved and delay had decreased with the DDI conversion. Several studies argued against the crossover intersection concern stating that the driver unfamiliarity has a calming effect by

13

Operating Performance of Diverging Diamond Interchanges encouraging slower speeds while approaching and crossing the interchange thus serving as a potential safety benefit (MoDOT 2010 Ressel 2012). According to the MoDOT survey 97% of drivers said they feel safer in the DDI than the previous CDI. A five-month comparison of crash data for the DDI in Springfield Missouri shows a 60% reduction over the previous diamond interchange (MoDOT 2010). The crash data review by Chilukuri (2011) also shows a 46% decrease in total crashes in the first year of operation of the DDI elimination of left-turn crashes and a decrease in angle and rear-end crashes.
A DDI is also known to have lower construction cost compared to other interchange alternatives. In many cases an existing bridge can be used for the DDI conversion though the DDI may require additional right-of-way compared to a CDI to allow median and ramp terminals to bend into the road. Hughes et al. (2010) found that a four-lane DDI performs at a similar level as a six-lane CDI and a six-lane DDI performs similar to an eight-lane CDI. This reduction in lanes indicates that a DDI in many cases may provide a similar or better level of operation with little or no additional right-of-way from the existing CDI. A DDI also requires less right-of-way than a SPUI or displaced left-turn intersection (DLT) and similar right-of-way but higher capacity than a ParClo interchange (Chlewicki 2003 Stanek 2007 Hughes et al. 2010 Chlewicki 2011 Ressel 2012). The comparison of construction costs among DDIs in four locations in the United States and alternative designs presented in Appendix B shows that there are up to 75% cost savings from constructing DDIs over other alternatives (Chlewicki 2014).
14

Operating Performance of Diverging Diamond Interchanges
2.3 Methodologies in Diverging Diamond Interchange Studies
The studies discussed in the previous sections used several different methodologies to evaluate and compare the operational performance of DDIs and other interchange designs. Two major methodologies are reviewed microscopic simulation and critical lane volume method.
2.3.1 Microscopic Simulation Study Microscopic simulation is the most popular tool used in DDI studies. While
Chlewicki (2003) used Synchro (an analytic tool) to analyze the operational performance of a CDI and a DDI in his first DDI paper many other studies have since relied on microscopic simulation including VISSIM AIMSUN TSIS-CORSIMTM and Synchro with SimTraffic to measure and compare the performance of DDIs and CDIs. These studies include Bared et al (2005) Edara et al. (2005) Schroeder et al. (2006) Sharma and Chatterjee (2007) Speth (2008) Chlewicki (2011) Chilukuri et al. (2011) Galletebeitia (2011) Ressel (2012) Yeom et al. (2014) and Khan and Anderson (2016). Microscopic simulation software has the capability to analyze the operational performance of an interchange at various traffic conditions with varying traffic volumes and turn-movement ratios a range of vehicle types and alternative geometric configurations. Xiao et al. (2005) and Schroeder et al. (2006) concluded in their papers that microscopic simulation tools are capable of replicating observed vehicle behaviors and meeting most of the standard traffic modeling requirements with careful calibration and validation.
The use of VISSIM is widespread among interchange operational performance studies. VISSIM is a microscopic simulation program that has the capability to replicate
15

Operating Performance of Diverging Diamond Interchanges
driver behavior geometry and traffic controls accurately for various roadway designs (Ressel 2012). What distinguishes VISSIM from other microscopic simulation tools is the ability to calibrate the driver behavior modeling. Other popular tools such as Synchro with SimTraffic have deterministic arrival patterns lane change behaviors and look-back distances. All of these parameters can be controlled in VISSIM as well which adds reliability and accuracy to the model and its outcomes (Ressel 2012).
According to Schroeder et al. (2006) and Woody (2006) calibration and field validation are essential to developing accurate VISSIM models. Schroeder et al. (2006) stated that important VISSIM model calibration factors include origindestination volumes route decision look-back distances field-measured free-flow speeds and fieldimplemented signal-timing schemes. Validation parameters include travel time through the network and each route as well as average 95th and maximum queue lengths on a percycle basis. Woody (2006) provided a guideline for the calibration of VISSIM models and suggested the importance of the car-following behaviors lane-changing behavior and standstill distance for operational calibration and study area size analysis period volume route choice traffic control network speed and roadway geometry for system calibration.
2.3.2 Critical Lane Volume Method
A limitation of a microscopic simulation study is that it can be costly and timeconsuming depending on the length and the number of simulation inputs and thus only a limited number of traffic scenarios may be analyzed. As an alternative Chlewicki (2011) and Maji et al. (2013) used the critical lane volume method. CLV uses mathematical equations from the Highway Capacity Manual (HCM) to calculate the capacity per lane of critical movements and then compares these capacities to the demand and estimates a level
16

Operating Performance of Diverging Diamond Interchanges
of service (LOS) for the DDI (Transportation Research Board 2010). The CLV method is straightforward and less time-consuming than microscopic simulation allowing for the analysis of a large number of alternatives in a relatively short time with reasonable reliability.
Using the CLV method Chlewicki (2011) analyzed 15 626 volume combinations to compare the operations of a DDI and a CDI. Maji et al. (2013) found that the CLV method could provide reliable and accurate outcomes for DDI operational performance in comparison to VISSIM and Synchro. The Federal Highway Administration (FHWA) introduced the Capacity Analysis for Planning of Junctions (CAP-X) in the Diverging Diamond Interchange Information Guide (Bastian et al. 2014) as a principal planning-level tool to analyze and compare the operational performance of several interchange designs including a DDI using the CLV method. CAP-X uses inputs of turning-movement counts heavy-vehicle percentages and number of lanes on each approach to estimate v/c ratios at each crossing point of different junction designs.
However Chlewicki (2011) pointed out several limitations of the CLV method. First the CLV method is only capable of analyzing individual intersections. It cannot determine how signals or intersections will synchronize which is an issue for interchanges as they typically have two or more intersections. Second the CLV method is likely to ignore issues associated with a CDI and thus overestimate CDI performance relative to other alternatives. For instance A CLV analysis may assume the same capacity for all interchange intersections regardless of interchange form. However a DDI crossover intersection likely has a higher per-lane capacity than a CDI intersection as the DDI has one less phase and thus less lost time per hour. Chlewicki also pointed out that the CLV
17

Operating Performance of Diverging Diamond Interchanges
method requires careful selection of lane adjustment factors for accurate results. Maji et al. (2013) concluded that it is better to use microscopic simulation tools for detailed operational performance analysis of interchanges as the CLV method utilizes limited parameters. For instance CAP-X does not use phase timings or saturation flow to calculate the capacity but instead requires users to input the junction capacity. Also by considering intersections in isolation CAP-X does not capture the reduction in demand on a downstream approach as the result of upstream operational failure.
2.3.3 Other Methodologies In addition to the microscopic simulation and the CLV method Chilukuri et al.
(2011) conducted travel-time runs video recording peak hour traffic volume data crash data review and online surveys to measure DDI operation performance. These methodologies were utilized in part to check the accuracy and reliability of the simulation results.
2.3.4 Traffic Scenario Selection Methodologies Although many studies used similar tools for the analysis there are differences in
how each developed volume and route decision scenarios to test the operational performance of DDIs and CDIs.
2.3.4.1 Existing Volumes vs. Hypothetical Volumes The operational performance of a DDI and a CDI can be analyzed using either
existing volume data from the study area or hypothetical volumes developed by researchers. For example Chlewicki (2003) evaluated CDI and DDI operational performance using the existing traffic volumes and turning-movement distributions for the interchange at I-695
18

Operating Performance of Diverging Diamond Interchanges
and MD 140 in Baltimore County Maryland. Chilukuri et al. (2011) Ressel (2012) and Maji et al. (2013) also used existing volume data for their study interchanges and projected 2035 traffic volumes based on the existing data to evaluate DDI performance. Schroeder et al. (2006) also used existing traffic volumes of four DDIs in Tennessee and Missouri to present an approach for calibrating and validating DDI models using VISSIM. Khan and Anderson (2016) developed 83 volume scenarios based on the existing volumes at a CDI in Athens Alabama with volume increases of 0% 50% 100% 150% and 200% of the existing.
Bared et al. (2005) Edara et al. (2005) Sharma and Chatterjee (2007) Speth (2008) Galletebeitia (2011) and Autey et al. (2012) used hypothetical combinations of volumes and turning movements to test the operational performance of interchanges. Chlewicki (2011) tested 15 626 volume combinations based on the permutation of five left-turn and through movements. Bared et al. (2005) Sharma and Chatterjee (2007) and Galletebeitia (2011) categorized the traffic volumes in peak high medium and low flow rates.
2.3.5 Balanced and Unbalanced Traffic Volume
Another variable in traffic scenario selection is balanced and unbalanced traffic. Balanced traffic refers to opposing approaches (e.g. east- and westbound or north- and southbound) having equal traffic volumes and/or turning movement distributions. Unbalanced traffic refers to opposing approaches having different traffic volumes and/or turning-movement distributions. Examples of balanced and unbalanced volume conditions are illustrated in Table 1. Chlewicki (2003) Bared et al. (2005) Edara et al (2005) and Chilukuri et al. (2011) studied the operational performance of DDIs under balanced volume conditions only. Ressel (2012) and Maji et al. (2013) tested DDIs under unbalanced
19

Operating Performance of Diverging Diamond Interchanges
conditions only. Sharma and Chatterjee (2007) Speth (2008) Chlewicki (2011) Galletebeitia (2011) Autey et al. (2012) and Khan and Anderson (2016) analyzed the operations of DDIs and CDIs under both balanced and unbalanced traffic volumes. Chlewicki (2011) and Autey et al. (2012) also analyzed DDIs at different left-turn ratios to evaluate the impact of left-turn proportions on the operation of DDIs.

Table 1 Balanced and unbalanced volumes (Speth 2008)

Balanced

Northbound

L

R

200 200

Southbound

L

R

200 200

Eastbound LTR 700 500 100

Westbound LTR 700 500 100

Unbalanced 500 200 260 70 160 400 700 330 470 300

* L Left-turn R Right-turn T Through

20

Operating Performance of Diverging Diamond Interchanges
CHAPTER 3. METHODOLOGY
The DDI and CDI sensitivity analysis in this study is based on the operational performance studies discussed in the literature review. The following sections describe in detail the analysis methodology including lane configuration and traffic scenario selection network designs and sensitivity analysis steps and inputs. 3.1 Overview Flow Chart of the Study Procedure
The following flow chart (Figure 4) provides an overview of the step-by-step procedure of the analysis conducted in this study. Detailed descriptions of each step in the flow chart are provided in the following sections of this chapter. The study starts with a selection of CDI and DDI configurations along with a range of demand scenarios. For each configuration and demand scenario optimal signal-timing plans are determined using the optimization tool Synchro. A CLV analysis is then conducted for each configuration and demand scenario allowing for a comparison of DDI and CDI performance under a wide variety of conditions. A more in-depth analysis of a subset of the scenarios is then undertaken using the VISSIM microscopic simulation tool. The CLV and VISSIM findings are then summarized to help inform the selection of a DDI or a CDI configuration in the design planning stage of a project.
21

Operating Performance of Diverging Diamond Interchanges
Figure 4 Flow chart of the study procedure 22

Operating Performance of Diverging Diamond Interchanges
3.2 Lane Configuration Selection
The first step in the analysis is to select the interchange lane configurations to be tested. Analysis of various lane configurations allows for a broad application of the study findings.
The initial CDI and DDI configurations in this study are based on the before and after interchange designs at Jimmy Carter Blvd. and I-85 in Norcross Georgia. Figure 5 and Figure 6 show aerial pictures of before-and-after configurations of the selected site. This interchange was converted to a DDI in 2015 in response to severe traffic congestion. For this report the cross street Jimmy Carter Blvd. is designated as northsouth and the freeway I-85 as eastwest. Before the conversion the northbound interchange approach had four through lanes with a right-turn-only lane and the southbound approach had three through lanes with a right-turn-only lane. On the bridge there were two through lanes and two left-turn lanes northbound and two through lanes and one left-turn lane southbound. Both I-85 off-ramps (eastbound and westbound) to Jimmy Carter Blvd. had two left-turn lanes and one right-turn lane. After the DDI conversion the interchange has three through lanes and one right-turn lane on both the northbound and southbound approaches and one through-only lane one through-plus-left shared lane and one left-turn-only lane northbound and southbound on the bridge (see Figure 7). The after off-ramp lane configurations are the same as in the before configuration. The before and after lane configurations are indicated as LC1 (Lane-Configuration-1) in subsequent analyses.
Two other CDI versus DDI lane configurations were also modeled (1) three entering lanes on cross streets with two through lanes and one left-turn lane on the bridge in the northbound and southbound directions (indicated as LC2) as shown in Figure 8 and
23

Operating Performance of Diverging Diamond Interchanges (2) four entering lanes on cross streets two through lanes and two dedicated left-turn lanes on the bridge in the northbound and southbound directions (indicated as LC3) as shown in Figure 9. The off- and on-ramps remain the same for all configurations. Unlike the first lane configuration tested the other two lane configurations have an equal number of lanes on both the CDI and DDI southbound and northbound approaches.
N
Figure 5 Before configuration of the conventional diamond interchange at Jimmy Carter Blvd. and I-85 in Norcross GA (Google Earth accessed 11/28/2017)
24

Operating Performance of Diverging Diamond Interchanges
N
Figure 6 After configuration of the diverging diamond interchange at Jimmy Carter Blvd. and I-85 in Norcross GA (Google Earth accessed 11/28/2017)
Figure 7 CDI (left) and DDI (right) in lane configuration 1 25

Operating Performance of Diverging Diamond Interchanges
Figure 8 CDI (left) and DDI (right) in lane configuration 2
Figure 9 CDI (left) and DDI (right) in lane configuration 3 3.3 Sensitivity Analysis of DDI and CDI
Sensitivity analysis is "a technique used to determine how different values of an independent variable impact a particular dependent variable under a given set of assumptions" (Investopedia 2017). In this study independent variables examined in the analysis are traffic demand defined by number of vehicles per hour entering the network and turn-movement ratio defined by the proportion between through and left-turn
26

Operating Performance of Diverging Diamond Interchanges movements of vehicles coming into the interchange from the cross street of Jimmy Carter Blvd.. The following subsections describe in detail the steps and parameter settings selected to perform the DDI and CDI operational performance sensitivity analysis.
27

Operating Performance of Diverging Diamond Interchanges
3.3.1 Sensitivity Analysis Structure and Assumptions The sensitivity analysis in this study is structured as a two-step process a CLV
analysis and a microscopic simulation study. The CLV analysis calculates and compares v/c ratios of the DDIs and CDIs for all the traffic scenarios under consideration. The CLV analysis allows for a relatively quick comparison of DDI and CDI operational performance across a large number of demand scenarios. A VISSIM simulation (a common microscopic simulation tool see section 2.3.1) study is then conducted to confirm the comparative performance findings of the CLV analysis. Microscopic simulation allows a researcher to control various traffic elements including vehicle volume speed car-following model route decision vehicle composition and lane-change behavior. It also allows for a more detailed analysis of interchange operations compared to the CLV analysis through various operational measures such as travel time delay number of stops throughput and queue length. As stated in CHAPTER 2 the drawback of microscopic simulation is that it is much more time consuming and labor intensive than CLV and thus the VISSIM analysis focuses on a subset of the demand scenarios.
3.3.2 Traffic Scenarios Selection Traffic scenarios consist of hourly traffic demand and turn-movement ratios. As the
objective of this study is to compare interchange configurations under various demand scenarios a large number of volumeproportion combinations are needed. Table 2 and Table 3 list all volumes and turn-movement ratios tested in this study. Each demand scenario is tested for all through/left proportions listed. These volume and turn-movement ratios result in 161 different traffic scenarios. In this study only balanced volume
28

Operating Performance of Diverging Diamond Interchanges conditions were tested where northboundsouthbound and eastboundwestbound approaches have equal volumes and turn-movement ratios.

Table 2 Vehicle volumes tested in the study

Cross-Street Volume

(vph)

Low

1000

200

Off-Ramp Volume (vph)

Medium

High

500

800

1500

500

1100

1800

1800

500

1100

1800

2100

500

1100

1800

2300

500

1100

1800

2500

500

1100

1800

2700

500

1100

1800

High-2
2100 2100

Table 3 Turn-movement ratios tested in the study

Through/Left Proportions

Through

Left

1

0

0.9

0.1

0.7

0.3

0.5

0.5

0.3

0.7

0.1

0.9

0

1

29

Operating Performance of Diverging Diamond Interchanges Several assumptions are included in the demand scenarios. First vehicles exiting
the freeway do not return to the freeway that is no vehicle from an off-ramp uses the on-ramp back to the interstate. This implies that all vehicles entering the bridge from an off-ramp make a through movement at the exiting crossover intersection. Second the through/left proportion applies only to vehicles that enter the bridge from the cross street vehicles from the off-ramp are not considered in the through/left volume proportion calculation. For example the through/left proportion of 70/30 indicates 70% of vehicles entering the bridge from the cross street make a through movement at the exiting crossover intersection while the remaining 30% turn left onto the freeway on-ramp. Third the freeway off-ramp vehicles are evenly split between left and right turns at the cross-street intersection. Finally 20% of the arriving cross-street vehicles turn right to the freeway on-ramps indicating 80% of vehicles enter the bridge.
3.3.3 Synchro Signal Optimization As part of the sensitivity analysis optimal signal timing plans for each lane
configuration and traffic demand scenarios were determined. For this effort Synchro was used to optimize both the CDI and DDI signal-timing plans.
Synchro models of the DDIs and CDIs were developed based on Jimmy Carter Blvd. and I-85 aerial maps from Bing. Synchro models for both interchange configurations include the off- and on-ramps bridge segment and cross streets entering the bridge. The models excluded the adjacent intersections from the analysis to simplify the signal optimization.
30

Operating Performance of Diverging Diamond Interchanges DDI models were optimized with a pretimed setting and CDI models were optimized with an actuated-coordinated setting with loop detectors on left-turn lanes. Cycle lengths of both interchange designs were optimized within the range of 50 seconds and 180 seconds and the offset was referenced to the beginning of green of the northbound through (NBT) phase. These decisions were based on the existing signal implementations at the selected site provided by Gwinnett County DOT. The basic dual ring diagrams of the DDI and CDI models were developed based on the existing timing plans from Gwinnet County DOT. Sample dual ring diagrams of the DDI and the CDI are shown in Figure 10 and Figure 11. The DDI has a split-phase configuration of the cross-street through movements with no phase for the left-turn movements from the cross street to the on-ramps as these are uninterrupted movements in the DDI configuration. The CDI has protected left-turn movements from the cross street to the freeway on-ramp at both bridge intersections. Based on these phase diagrams the DDIs are expected to benefit from both free-flow left-turn movements and reduced lost time per cycle although the DDI may have reduced cross-street capacity given the through movement split-phase timing configuration. From the signal timing optimization using Synchro the phase lengths cycle lengths and offsets on each intersection are collected.
31

Operating Performance of Diverging Diamond Interchanges
Figure 10 Sample dual ring diagram of the diverging diamond interchange
Figure 11 Sample dual ring diagram of the conventional diamond interchange 3.3.4 Critical Lane Volume Analysis
The first part of the sensitivity analysis is the CLV analysis comparing DDI and CDI critical movement v/c ratios. A critical movement (or movement pair) is defined as the movement(s) with the highest per lane demand (v/c) on each side of the ring barrier. The critical path consists of the critical movements from both sides of the dual ring diagram. Movements considered in the CLV analysis of the CDI and the DDI defined in this study are listed in Table 4. Figure 12 and Figure 13 illustrate the turning movement schematics of the CDI and the DDI. For the CLV analysis the movements EBR1 NBR1 SBR2 and WBR2 are not considered as they are uninterrupted movements and unlikely to be capacity constrained. SBL1 and NBL2 are considered in the analysis as these are phase controlled in the CDI configuration and may be capacity constrained however in the DDI these movements are uninterrupted.
32

Operating Performance of Diverging Diamond Interchanges

Table 4 DDI and CDI critical movements

Intersections

Critical Movements NBT1

Node 1

SBT1 SBL1

EBL1

NBT2

Node 2

NBL2 SBT2

WBL2

Figure 12 Turning movement schematic of the conventional diamond interchange 33

Operating Performance of Diverging Diamond Interchanges
Figure 13 Turning movement schematic of the diverging diamond interchange 3.3.4.1 Volume-to-Capacity Calculations
CAP-X from FHWA is not used in this study for v/c ratio calculation as capacity must be manually set. In addition CAP-X does not capture the reduction in demand on a downstream approach resulting from an upstream capacity constraint. Instead v/c ratios of CDIs and DDIs are calculated using simplified HCM 2010 methods. Equation 1 below calculates the capacity per lane for each turning movement within the interchange. Phase lengths and cycle lengths used in the CLV analysis are from Synchro signal optimization. As the CLV analysis is a planning-level analysis and thus intended as an approximation saturation flow is set to be 2000 vphrpln based on VISSIM results. In addition a 4-second lost time per phase is assumed. However in a future iteration of the CLV analysis these values could be adjusted to reflect specific field conditions for increasingly fine-tuned results.
34

Operating Performance of Diverging Diamond Interchanges

c

s



(1)

capacity per lane (vphrpln) saturation flow assumed as 2000 vphrpln effective green time calculated as phase time minus lost time of 4 seconds cycle length of the intersection in seconds

Equation 2 calculates the demand per lane for each movement using the assigned (i.e. scenario) traffic flows and lane utilization factors.



(2)

volume per lane (vphrpln) assigned movement traffic flow on each movement (vph) lane utilization factor

Table 5 shows the calculation for the LUF for the various lane groupings. The LUFs are developed with consideration of lane assignments (left only through only or shared left-through) the number of lanes and the relationship between upstream and downstream intersections. LUFs are assumed to be maximum lane utilization (i.e. distribution of vehicles across lanes) with the exception that weaving on the bridge is minimized. That is a vehicle will not pre-position in an upstream lane that does not lead to a downstream lane allowing that movement (exclusive or shared). These assumptions tend to lead to a conservation allocation of vehicles particularly on a DDI with a shared through-left lane likely underutilizing the left-turn-only free-flow lane. However as this is a planning-level

35

Operating Performance of Diverging Diamond Interchanges analysis the more conservative assignment was selected. Future efforts should seek to inform the selection of LUFs based on numerous DDI and CDI field observations.

Table 5 Lane utilization factor calculation* **

Turning Movements

Scenarios

Lane Utilization Factor (LUF) Calculations
For the lanes utilized by vehicles pre-positioning to make through movement at the downstream approach

LC1 (CDI) LC2 LC3



all lanes

For the lanes utilized by vehicles pre-positioning to make left turn at the downstream approach

Upstream Approaches
NBT1 / SBT2

LC1-DDI with shared lanes (3 lanes)



all lanes

Let

1 2

If 1 then 1 for lane 1

0 for lane 2

If 1 2 then 1/ for lane 1

1 / for lane 2

If 2 then 0.5 for both lanes

Let

1 2

If 1 then 0 for lane 2

1 for lane 3

If 1 2 then 1 / for lane 2

1/ for lane 3

If 2 then 0.5 for both lanes

* Lanes are numbered from centerline to outside edge of roadway ** Table 5 continues on the next page

36

Operating Performance of Diverging Diamond Interchanges

Table 5 Lane utilization factor calculation (continued)*

LC1 (CDI) LC2 LC3



1 1 2


Downstream Approaches SBL1 / NBL2

LC1-DDI with shared lanes (3 lanes)
LC1 (CDI) LC2 LC3

For vehicles coming from cross street (SBT1 or NBT2)


For vehicles coming from off-ramps (EBL1 or WBL2)



1 1 2



1 1 2

LC1-DDI For vehicles coming from cross street (SBT1 or

with shared NBT2)

lanes (3 lanes)



For vehicles coming from off-ramps (EBL1 or WBL2)



1 1 2

* Lanes are numbered from centerline to outside edge of roadway

In the determination of the arriving traffic volume at an approach potential upstream capacity constraints are considered. However traffic volumes on downstream movements (SBT1 SBL1 NBT2 and NBL2) receive the throughputs of upstream movements (NBT1 EBL1 SBT2 and WBL2). Where the upstream intersection movement cannot process all the assigned traffic or when v/c ratios of upstream movements exceed 1 the downstream arriving volume is adjusted. It is assumed that the maximum throughput processed by the upstream approach is 95% of the capacity and thus the volume of downstream movements is adjusted as shown in Equation 3.

37

Operating Performance of Diverging Diamond Interchanges

/ 0. 95 0.95

(3)

/ v/c ratio of an upstream movement demand per lane of a downstream movement (vphrpln)

An interchange intersection v/c ratio is calculated based on the sum of the critical lane volumes in the critical path and the critical path capacity. Equation 4 calculates the critical lane volume of an intersection by summing the demand per lane of critical path phases.





(4)

selected intersection within the interchange volume per lane of each movement within the critical path of the intersection (vphrpln) number of phases within the critical path of the intersection

The intersection critical path capacity is calculated using Equation 5 based on the cycle length and total lost time per cycle. The DDI has two phases in a cycle critical path and the CDI has either two or three phases in a cycle critical path depending on the phase demands.



3600

3600







(5)



capacity per lane of the selected intersection (vphrpln)

cycle length of the intersection (seconds)

total lost time per phase assumed as 4 seconds

number of phases in a cycle

38

Operating Performance of Diverging Diamond Interchanges saturation headway assumed as 1.8 s/veh (i.e. saturation flow of 2000 veh/hr/ln)
The intersection v/c ratio may then be calculated using the critical path volume and the critical path capacity. For this analysis the interchange v/c ratio is set as the larger v/c ratio of two interchange intersections as shown in Equation 6.

/

/

/

(6)

3.3.4.2 Comparative Study
Calculated v/c movement and interchange ratios are populated into a tabular format and color-coded to present the difference in v/c ratios between the CDI and DDI scenarios using Microsoft Excel with Visual Basic (VB) scripts (Appendix C). The color schematics of the color-coded spreadsheet for v/c ratios are presented in Table 6. The v/c ratios are then plotted to help visualize the differences between the CDI and DDI performance over different demand and through/left proportions. Using these tables and plots patterns in the v/c ratios and relative performance between the interchange configurations are explored.

Table 6 Color schematics of color-coded spreadsheet for v/c ratios

Cell Color Green

Meaning Lower v/c ratio with difference 0.2

Yellow

Greater v/c ratio with difference 0.2

Red

v/c ratio 0.95

39

Operating Performance of Diverging Diamond Interchanges
3.3.5 Microscopic Simulation Study
The second step in the sensitivity analysis is the microscopic simulation study using VISSIM for selected combinations of traffic volumes and through/left proportions to confirm the observations from the CLV analysis. The CLV study alone is insufficient to evaluate the CDI and DDI operational performance as the v/c ratio does not present a complete operational picture as discussed in the literature review. Therefore the VISSIM simulation study which allows for the estimation of numerous operational parameters is used to complement the CLV study. Similar to the CLV analysis the signal timing plans are optimized using Synchro and are used in the VISSIM simulation network. As the simulation study is more time-consuming than the CLV analysis only selected case studies are tested using VISSIM. Table 7 and Table 8 list the selected demand scenarios and through/left proportions tested in this microscopic simulation study for all tested lane configurations. These scenarios were selected to represent a cross section of the scenarios in the CLV study.

Table 7 Selected demand scenarios for the simulation study

Cross-Street Volume (vph)

Off-Ramp Volume (vph)

Low

Medium

High

1500

500

1100

1800

2100

500

1100

1800

2500

500

1100

1800

40

Operating Performance of Diverging Diamond Interchanges

Table 8 Selected through/left proportions for the simulation study

Through/Left Proportions

Through

Left

1

0

0.9

0.1

0.7

0.3

0.5

0.5

0.3

0.7

0.1

0.9

0

1

3.3.5.1 VISSIM Model
As with the CLV analysis the CDI and DDI VISSIM lane configurations and geometric designs are developed based on the Jimmy Carter Blvd. and I-85 interchange. Cross-street grades are assumed as zero and grades on off-ramps are as measured from the field (1.5% within 300 ft of the cross-street signal and 5.0% for the rest of the segment). Single vehicle input defined as number of vehicles input into the network per hour (vph) is used for each simulation period to minimize the variability in the data from changing traffic demands over time. Again as with CLV analysis the study area covers the interchange segment including off- and on-ramps bridge segment and the cross-street approaches to the interchange. Figure 14 and Figure 15 show sample CDI and DDI VISSIM models with the existing lane configuration (LC1). As seen the primary difference between the two models is the bridge segment where the DDI model has crossovers at the two

41

Operating Performance of Diverging Diamond Interchanges intersections. The LC2 and LC3 configurations as discussed in the CLV section are based on these initial VISSIM models.
Figure 14 VISSIM model for the conventional diamond interchange (LC1)
Figure 15 VISSIM model for the diverging diamond interchange (LC1) 42

Operating Performance of Diverging Diamond Interchanges The study uses the default VISSIM vehicle composition with 5% heavy vehicle. With the assumption of approximate turning speed of 25 mph reduced speed zones are implemented at turning links with a speed range of 20 to 30 mph. Priority rules are implemented at the intersections to prevent vehicles from driving through other vehicles blocking the intersection. The simulation time of the VISSIM models for each traffic scenario is 4500 seconds. The first 900 seconds of the simulation is allotted to allow the model to fill and reach steady state (if possible). Performance metrics from the fill time are not included in the analysis. Therefore data are collected for 3600 seconds with 300-second bin aggregations. Ten simulation replications are conducted for each traffic scenario with different seeds to provide variation in arrival patterns and network traffic flow. The simulation runs and data collection are automated using Microsoft Visual Studio with VB scripts (Appendix D). Performance measures collected from the simulation study are average delay per vehicle average travel time per vehicle average number of stops per vehicle queue length and throughput on each approach and x- and y-coordinates of individual vehicles processed. R scripts are used to organize and summarize collected performance measures. The average delay per vehicle for each approach and the entire route are populated in Excel spreadsheets enabling the comparisons between interchange configurations and demand scenarios.
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Operating Performance of Diverging Diamond Interchanges 3.4 Implementation
This section describes the sensitivity analysis implementation process providing additional detail regarding inputs spreadsheets and software utilized to analyze the operational performance of the interchange configurations. 3.4.1 Synchro Signal Optimization
For each scenario of traffic demand through/left proportion and lane configuration an optimal signal timing plan is determined using Synchro. Synchro exports the signaltiming parameters to a comma-separated value (CSV) file. Separate CSV files ae created for each lane configuration tested. Each timing plan of each subsequent Synchro scenario run is appended to the end of the CSV file. A screen capture of an exported signal plan in a CSV file format is shown in Figure 16. Each signal plan (PLANID) is named after the combination of cross-street and off-ramp volumes and the left-turn proportion. For example the PLANID of 100020050 represents a 1000-vph cross-street volume 200-vph off-ramp volume and 50% left-turn proportion. After all the optimized signal timings are exported to CSV files signal plans in the CSV files are exported to the CLV spreadsheet under the "Signal Timing" tab into a format suitable for the analysis using a VB script (Appendix C). Figure 17 shows the screen capture of the signal plans reorganized in the CLV spreadsheet.
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Operating Performance of Diverging Diamond Interchanges
Figure 16 Optimized signal timings exported to a CSV file
Figure 17 Signal plans reorganized in the CLV spreadsheet 3.4.2 CLV Study and Comparative Analysis
After importing the DDI and CDI interchange signal plans for all volume proportion combinations and lane configurations in the "Signal Timing" tab of the CLV spreadsheet (each lane configuration has a separate CLV workbook) CLV analysis is conducted to calculate v/c ratios for each scenario. The v/c ratio for each volume proportion combination is calculated in "DDI_CLV" and "CDI_CLV" worksheets in the workbook. Each sheet consists of vehicle input through/left proportion route decision
45

Operating Performance of Diverging Diamond Interchanges phase diagram proportional phase timing volume set for Synchro traffic demand and lane numbers on each approach optimized timing from Synchro approach capacity and v/c ratio calculation. Cells in the right-top corner of the spreadsheet contain selected crossstreet and off-ramp volumes and through/left proportions to be tested. Figure 18 below shows a screen capture of the "DDI_CLV" worksheet. A VB script (Appendix C) automatically inputs cross-street and off-ramp volumes and through/left proportions into the cells and exports calculated v/c ratios into the "Color Coded" worksheet which contains color-coded tables and plots of the CDI and DDI v/c ratios utilizing the color schematics described in Table 6. These tables and plots are used to analyze the conditions in which one interchange design outperforms the other.
Figure 18 Spreadsheet for v/c ratio calculation for the CLV analysis
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Operating Performance of Diverging Diamond Interchanges
3.4.3 VISSIM Simulation Analysis
After completion of the CLV analysis the VISSIM microscopic simulation study is undertaken. Based on the CLV findings cross-street and off-ramp volumes representing low medium and high traffic-demand scenarios are selected for the simulation case study.
As stated previously CDI and DDI VISSIM models are created based on the geometry from a Google Maps aerial of the Jimmy Carter Blvd. and I-85 interchange. Signal timing files (Ring Barrier Control or RBC files) are manually created for each traffic scenario using the signal plans from Synchro. The developed Microsoft Visual Studio VB script (see Appendix D) automates the process to call input and run VISSIM models and to collect performance measures including delay travel time throughput queue length and x- and y-coordinates of individual vehicles. Ten simulation runs are conducted for each volumeproportion set and average delay per vehicle data are calculated based on the weighted average of these ten simulation runs using the R script as shown in Equation 7.





(7)

number of simulation runs conducted (10 runs) delay per vehicle at nth simulation run throughput on an approach at nth simulation run
Average delay per vehicle and average throughput data for each lane configuration are organized in the "VISSIM Output Analysis" worksheet and plotted for each turning movement to enable the comparison of CDI and DDI operational performance across the
47

Operating Performance of Diverging Diamond Interchanges various scenarios. Each worksheet in the LC1 LC2 and LC3 workbooks contains the delay and throughput data from the simulation study of the respective configuration.
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Operating Performance of Diverging Diamond Interchanges
CHAPTER 4. RESULTS AND DISCUSSION
This chapter summarizes compares and evaluates results from the CLV analysis and the VISSIM simulation study.
4.1 CLV Analysis Results
The CLV study calculates CDI and DDI v/c ratios at different traffic demands and turn-movement ratios. Calculated v/c ratios are populated into color-coded spreadsheets and plots to present the CDI and DDI operational performance. Figure 19 Figure 20 and Figure 21 plot the difference between the CDI v/c ratio and the DDI v/c ratio for each laneconfiguration (LC1 LC2 and LC3) and traffic-demand scenario. Values in the legend represent cross-street and off-ramp demands i.e. 2100/500 is interpreted as a cross-street demand of 2100 vph and an off-ramp demand of 500 vph. See Appendix E for all detailed results of color-coded tables and plots developed using the CLV method.
For the existing lane configuration (LC1) the CDI is favored over the DDI (i.e. v/c ratios of the CDI are lower than those of the DDI thus the difference in v/c ratios is negative) when the cross-street left-turn proportion is below 30%. The two interchange configurations experience similar v/c ratios at the proportion of 70/30 and the DDI outperforms the CDI at left-turn proportions exceeding 50% of total demand. Also for a given through/left proportion the v/c ratio difference consistently increases as the demands increase supporting that there are benefits of the DDI under higher demands. Thus at the lower left-turn proportions while the CDI may have lower v/c ratios the relative advantage over DDI decreases as demands increase likewise at higher left-turn proportions the
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Operating Performance of Diverging Diamond Interchanges
advantage of the DDI is amplified at higher demands. For the LC2 scenario (i.e. fewer lanes than LC1) the DDI and CDI have a similar performance as that for LC1. The CDI again has superior operational performance to the DDI until the left-turn proportion reaches 30% of total demand at which point performance is similar. At left-turn percentages of 50% and above the DDI outperforms the CDI although the magnitude of the difference is not as large. The LC3 plot the largest bridge cross section (8 lanes) tested in this study shows a slight shift with the CDI and DDI having similar performance at the through/left ratio of 50/50 with the CDI generally providing better service at lower left-turn proportions and the DDI at higher left-turn proportions. This change is expected as the CDI capacity is more sensitive to the number of lanes thus when the number of lanes increases the CDI operational performance will see greater improvements than the DDI (Hughes et al. 2010).
From the color-coded tables comparing the CDI and DDI v/c ratios by individual turning movement (see Appendix E) SBT1 and NBT2 the through movements exiting the bridge as expected experience better operations (lower v/c ratios) on the CDI than on the DDI in most traffic scenarios. This is primarily due to the CDI through movement having concurrent signal timing whereas these movements operate in a split-phase pattern on the DDI. However the DDI provides superior service to the left-turn movements from the cross streets to the on-ramps and the left turns from the off-ramps to the bridge (SBL1 NBL2 EBL1 and WBL2) in most traffic scenarios. This derives from the DDI free-flow left-turn movements an overall reduction in lost time and the off-ramp movements in the DDI running concurrent with cross-street through movements often resulting in a higher effective green for this movement than in the CDI. Overall as expected the CDI has a tendency to favor cross-street through movements while a DDI favors left-turn movements.
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Operating Performance of Diverging Diamond Interchanges
Figure 19 Difference in v/c ratios between CDI and DDI for LC1 at different traffic demands and through/left proportions
Figure 20 Difference in v/c ratios between CDI and DDI for LC2 at different traffic demands and through/left proportions 51

Operating Performance of Diverging Diamond Interchanges
(%)
Figure 21 Difference in v/c ratios between CDI and DDI for LC3 at different traffic demands and through/left proportions
4.2 Microscopic Simulation Study Results As part of the VISSIM simulation portion of this study various performance
measures were collected including delay throughput volume number of stops and queue length on each approach. In this section the primary performance measures discussed are the average delay per vehicle in the interchange aggregated over all movements and the interchange throughput as these were found to provide the best representation of overall performance. Appendix F provides all detailed results of CDI and DDI average delay per vehicle and throughput data on individual turning movements. 4.2.1 Lane Configuration 1 (LC1)
The first lane configuration tested in this study LC1 is the before-and-after models of the Jimmy Carter Blvd. and I-85 interchange. Figure 22 Figure 23 and Figure 24 plot
52

Operating Performance of Diverging Diamond Interchanges
the average delay per vehicle and the throughput of the CDI and the DDI for the studied traffic volumes and turn-movement ratios. Values in the legend represent the off-ramp demands tested for the cross-street demand.
From these plots the CDI generally performs better or at a similar level to the DDI at left-turn proportions below 30% of total traffic demand and the DDI outperforms the CDI when the left-turn proportion is 50% or greater. These results are similar to the CLV findings although at the higher left-turn proportions the CDI delays are significantly higher than those in any through/left proportion on the DDI. These patterns are also noted in the throughput data. At the lower left-turn proportions the CDI tends to satisfy demand whereas the DDI is less likely to satisfy demand particularly at higher overall demands. When the left-turn proportion exceeds 50% the CDI is often unable to process the demand failing to serve a significant portion of the demand at the higher volume levels whereas the DDI reliably processes the full demand.
The relative difference in performance between the CDI and the DDI at the through/left proportions of 50/50 or more is greater in the simulation study than those found in the CLV analysis especially at higher cross-street demands. This is because the CLV method does not reflect the synchronization of intersections in the interchange or the complex lane utilizations seen in the VISSIM simulations. These differences are particularly exhibited on the SBT1 and NBT2 approaches i.e. the through movements exiting the bridge. These movements tend to favor CDIs in the CLV analysis but are found to be similar between the CDI and the DDI in the simulation study. Additionally in the simulation plots the left-turn proportion at which the DDI becomes the favored alternative is higher for lower cross-street demands.
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Operating Performance of Diverging Diamond Interchanges
(%)
Figure 22 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC1
(%)
Figure 23 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC1 54

Operating Performance of Diverging Diamond Interchanges
(%)
Figure 24 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1
4.2.2 Lane Configuration 2 (LC2) The second lane configuration tested LC2 has three entering lanes on the cross-
street approaches and one left-turn and two through lanes on each direction of the bridge. Figure 25 Figure 26 and Figure 27 plot the average delay per vehicle and the CDI and DDI throughput at different traffic demands and turn-movement ratios. For all three crossstreet demands tested the CDI only clearly outperforms the DDI in the 10% left-turn case and the average delay per vehicle of the CDI starts to exceed that of the DDI at the leftturn proportion of 30%. This trend is the same as that found in the CLV analysis where the difference in CDI and DDI v/c ratios starts to turn positive (i.e. v/c ratios of CDIs are higher than that of DDIs) at through/left proportion of 70/30. As with LC1 in the simulation plots the left-turn proportion at which the DDI becomes the favored alternative is higher for lower cross-street demands.
55

Operating Performance of Diverging Diamond Interchanges Unlike the results found in the CLV analysis where the magnitude of difference in
v/c ratios between the CDI and DDI configuration is smaller for LC2 than LC1 the results from the simulation study show no meaningful change in differences in average delay per vehicle between the LC1 and LC2 interchange configuration.
(%)
Figure 25 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2
56

Operating Performance of Diverging Diamond Interchanges
(%)
Figure 26 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2
(%)
Figure 27 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2 57

Operating Performance of Diverging Diamond Interchanges 4.2.3 Lane Configuration 3 (LC3)
The third lane configuration tested LC3 has the most lanes with four entering lanes on the cross-street approaches and two left-turn and two through lanes on the bridge. Figure 28 Figure 29 and Figure 30 plot the average delay per vehicle and the interchange throughput at different traffic volumes and turn-movement ratios. The CDI performs better or at a similar level to the DDI until the left-turn proportion reaches 50%. The DDI starts to outperform the CDI at a left-turn proportion of 70%. Similar to the CLV results the simulation results show that the CDI and DDI v/c ratios are similar at the 50/50 through/left proportion. LC3 has the highest left-turn proportion at which the DDI becomes the favored alternative aligning with the CLV finding that the relative operational performance of CDI and DDI are partially dependent on the total available cross section. Again as with LC1 and LC2 in the simulation plots the left-turn proportion at which the DDI becomes the favored alternative is higher for lower cross-street demands indicating that the CDI performs better at lower traffic volume.
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Operating Performance of Diverging Diamond Interchanges
(%)
Figure 28 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3
(%)
Figure 29 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3 59

Operating Performance of Diverging Diamond Interchanges
(%)
Figure 30 DDI and CDI average delay per vehicle and interchange throughput with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3
4.3 Discussion and Evaluation of the Results Based on the results from the CLV analysis and VISSIM simulation study CDIs
have better operational performance than DDIs at higher through and lower left-turn proportions while DDIs perform better in the opposite condition. The through/left proportion at which the CDI and DDI configurations had similar performance is dependent on cross-street cross sections and total demand. As the number of lanes on the cross street increases especially left-turn lanes the left-turn proportion required for the DDI to provide favorable performance increases. For the lane configurations tested in this study the CDIs and DDIs were found to have similar performance in the through/left proportion range of 70/30 to 50/50. Where the left-turn proportion was below 30% the CDI tended to offer better performance and where the left-turn proportion exceeded 50% of the total traffic
60

Operating Performance of Diverging Diamond Interchanges demand the DDI tended to offer better performance. The most significant operational benefits of DDI configuration are found on the cross street to on-ramp left-turn movements and freeway off-ramps onto the cross-street bridge. CDI configurations tended to provide better through movement operations.
The CDI configuration also was found to perform better at lower cross-street demands at a given through/left proportion while the operational performance of the CDI degrades faster than that of the DDI at higher cross-street demands. These results align well with findings from previous studies that the CDI performs better or similar to the DDI at low-to-medium volumes and the DDI outperforms the CDI at higher traffic volumes (Bared et al. 2005 Edara et al. 2005 Sharma and Chatterjee 2007 Speth 2008). However the impact of off-ramp demands on the operational performance of CDIs and DDIs is inconclusive due to the mixed results found in this study.
The overall comparative CDI and DDI operational performance trends observed are similar in both the CLV and simulation methodologies with some difference in the observed performance-difference magnitudes and at the individual movement level. In the CLV analysis the CDI configuration is found to have better performance on the SBT1 and NBT2 movements in most traffic scenarios. However these movements have no meaningful operational difference in the simulation study. This is primarily due to the CLV method s inability to capture the effect of synchronization between intersections and the difference in lane utilizations between the two methods.
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Operating Performance of Diverging Diamond Interchanges

CHAPTER 5. CONCLUSIONS AND RECOMMENDATIONS

5.1

Conclusions

This project focused on determining the general traffic operating conditions under which a DDI is more appropriate than a CDI and vice versa using traffic simulation and CLV analysis. While the Jimmy Carter Interchange is utilized as the base case the simulation was not specifically calibrated to all site geometric conditions instead constructed to provide a reasonable representation of a DDI and conventional interchange to allow for application of the results to other locations. Reflection of the specific site conditions in the model would limit the ability to apply the result more generally however it is recoginzied that it is critical that a designer consider the specifics of their site when considering any interchange design.
Given the preceding the operational performance curves developed in this study for CDI and DDI interchange configurations are able to support planning and decisionmaking procedures for interchange improvement projects and should contribute to the development of criteria for the selection planning and design of CDI to DDI interchange conversions. From the sensitivity analysis of the CDI and DDI interchange configurations using both critical lane volume and microscopic simulation the two configurations were found to provide similar performance (or alternate configuration which provided better service) at left-turn proportions between 30% and 50% of the total traffic demand dependent on the interchange lane configuration and total demand. For instance the leftturn proportion at which a DDI configuration outperforms the CDI configuration increases as the number of lanes on the cross-street cross section increases. The CDI also performs

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Operating Performance of Diverging Diamond Interchanges better at lower cross-street demands although its operation degrades faster than that of the DDI at high cross-street demands. In the current study the impact of off-ramp demands on the CDI and DDI operational performance is inconclusive.
5.2 Recommendations
It is recommendated that a CDI is likely the preferred alternative at locations with low traffic volumes and left-turn traffic proportions below 30% of the total traffic demand and a DDI is likely the preferred alternative at locations with higher traffic volumes and left-turn proportions exceeding 50% of the total demand. Volumes sets that fall between these ranges will required modeling of the specific case to determine the superior alternative.
In addition this study provides a foundation for developing more detailed standards and guidelines for the implementation of a DDI based on various lane configurations and traffic conditions. However for a more thorough analysis the researchers recommend that future studies conduct the simulation study for both balanced and unbalanced traffic conditions and expand the study area to include adjacent intersections.
It is also recommended to study the operational impact of large trucks (exceeding 50 ft in length) with a turning radius that would require multiple lanes to enter the bridge. This will provide a better understanding of the impact of DDI geometrics in accommodating heavy trucks. Inaddition adding ramp meters into simulation models will capture the impact of spillback from on-ramps to the bridge. This will provide more reliable performance data where freeway congestion may impact the cross-street operations.
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Operating Performance of Diverging Diamond Interchanges
Finally it is recommended to develop inproved lane utilization factors. Improved lane utilization factors in addition to left-turn and heavy-vehicle adjustment factors will allow the CLV analysis to better replicate the potential variations in field conditions. These additions to future study will provide more reliable and accurate data in analyzing the DDI operational performance.

5.3

Limitations in the Study

There are a few limitations in this study that can be improved in future research efforts. First as noted by Chlewicki (2011) and Schroeder et al. (2014) the CLV method oversimplifies the operational performance of an interchange and an intersection. It tends to overestimate the performance of the CDI due to its inability to account for intersection signal synchronization. As a result some discrepancies in results between the CLV analysis and the simulation study were found especially on the through movements exiting the bridge (i.e. SBT1 and NBT2). In both the CDI and DDI configurations the VISSIM simulations show relatively constant low delays on the through movements exiting the bridge with good signal coordination between the intersections. However the CLV method does not reflect this intersection synchronization resulting in higher v/c ratios for the same movements on DDIs.
In addition the CLV analysis does not capture the impact of significant queuing or spillback. For instance on the DDI configuration the freeway on-ramp from the cross street is assumed to be uninterrupted and thus free flow. However it is possible the free-flow traffic could lead to downstream congestion on the ramp either when merging with rightturning vehicles from the cross street or merging onto the freeway. Spillback potentially

65

Operating Performance of Diverging Diamond Interchanges
to the bridge is not reflected by the CLV method. This problem was observed during peak hours at the interchange of Jimmy Carter Boulevard and I-85. Therefore it is important for engineers and planners to understand the potential broader impact of the improved DDI left-turn accommodation and that bottlenecks may not be eliminated only moved to new locations. This study also did not take into account adjacent intersections. Adjacent intersections may have significant impacts on the interchange operation. However adjacent intersections were neglected in this study to minimize the number of confounding variables in the operational analysis.
During the field observation at the study interchange it was observed that a large truck exceeding 50 ft in length occupied both off-ramp lanes while turning onto the bridge. This behavior is not replicated in the current CLV analysis or VISSIM simulation. However when designing the interchange consideration must be given to the potential reduction in capacity due to tight curve radii. Future efforts may expand the current VISSIM model to explore this impact.
This study only examined balanced volume conditions i.e. similar demand from both cross-street approaches. It is desirable to expand the analysis to explore the impact of unbalanced volumes.
Lastly this study did not consider conditions unique to the Jimmy Carter interchange. For instance the selected 2000 (vphrpln) saturation flow is likely not realistic for the I-85 northbound off-ramp to Jimmy Carter Blvd. as the ramp approach curvature at Jimmy Carter Blvd. likely results in reduce saturation flow and performance. In addition the opening of the shoulder usage lane added some confounding variables in the before after analysis. However this study has gathered the pre- and post-deployment travel-time
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Operating Performance of Diverging Diamond Interchanges data and a beforeafter analysis should still be considered in a follow-on study to understand how traffic operations were affected at this interchange with the combination of changes that occurred.
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Operating Performance of Diverging Diamond Interchanges
CHAPTER 6. REFERENCES
Autey J. T. Sayed and M. El Esawey (2012). "Operational Performance Comparison of Four Unconventional Intersection Designs Using Micro-simulation." Journal of Advanced Transportation 47(5) 17.
Bared J. P.K. Edara and R. Jagannathan. (2005). "Design and Operational Performance of Double Crossover Intersection and Diverging Diamond Interchange." In Transportation Research Record Journal of the Transportation Research Board No. 1912 3138.
Chlewicki G. (2003). "New Interchange and Intersection Designs The Synchronized Split-Phasing Intersection and the Diverging Diamond Interchange." Presented at 2nd Urban Street Symposium Anaheim Calif.
Chlewicki G. (2011). "Should the Diverging Diamond Interchange Always Be Considered a Diamond Interchange Form " In Transportation Research Record Journal of the Transportation Research Board No. 2223 8895.
Chlewicki G. (2014). "The Diverging Diamond Interchange Website." History. Retrieved August 18 2017. http //www.divergingdiamond.com/index.html.
Chilukuri V. S. Siromaskul M. Trueblood and T. Ryan. (2011). "Diverging Diamond Interchange Performance Evaluation (I-44 and Route 13)." National Technical Information Service HDR Engineering Missouri Department of Transportation Federal Highway Administration 62.
Cogan C.A. (2008). "The Design and Operations of Diverging Diamond Interchange A Case Study in Kansas City Missouri." Civil Engineering. University of Missouri Master in Science 60.
Edara P.K. J.G. Bared and R. Jagannathan. (2005). "Diverging Diamond Interchange and Double Crossover Intersection--Vehicle and Pedestrian Performance." The 3rd International Symposium on Highway Geometric Design Chicago Illinois.
Bastian S. C. Cunningham B. Ray A. Daleiden P. Jenior and J. Knudsen. (2014). "Diverging Diamond Interchange Informational Guide" Publication FHWA-SA14-067. FHWA U.S. Department of Transportation.
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Galletebeitia B. (2011). "Comparative Analysis Between the Diverging Diamond Interchange and Partial Cloverleaf Interchange Using Microsimulation Modeling." Civil Engineering. ProQuest LLC Florida Atlantic University. Master s 1199.
Hughes W. R. Jagannathan D. Sengupta and J. Hummer. (2010). "Alternative Intersections/Interchanges Informational Report (AIIR)." Publication FHWA HRT-09-060. FHWA U.S. Department of Transportation.
Investopedia. (2017). "Terms." Sensitivity Analysis. Retrieved August 31 2017. http //www.investopedia.com/terms/s/sensitivityanalysis.asp.
Khan T. and A. Michael. (2016). "Evaluating the Application of Diverging Diamond Interchange in Athens Alabama." International Journal for Traffic and Transport Engineering 6(1) 3850.
Maji A. S. Mishra and M.K. Jha. (2013). "Critical Lane Volume-based Capacity and Level of Service Analyses for Diverging Diamond Interchange." 92nd Annual Meeting of the Transportation Research Board Washington D.C.
Missouri Department of Transportation. (2010). "Missouri s Experience with a Diverging Diamond Interchange--Lessons Learned." Missouri Department of Transportation.
Ressel N.R. (2012). "Insights into the First Three Diverging Diamond Interchanges in Missouri." Civil Engineering. University of Missouri Master in Science 97.
Schroeder B.J. K. Salamati and J. Hummer. (2006). "Calibration and Field Validation of Four Double-Crossover Diamond Interchanges in VISSIM Microsimulation." In Transportation Research Record Journal of the Transportation Research Board No. 2404 4958.
Schroeder B. C. Cunningham B. Ray A. Daleiden P. Jenior. and J. Knudsen. (2014). "Diverging Diamond Interchange Informational Guide." Publication FHWA-SA14-067. FHWA U.S. Department of Transportation.
Sharma S. and I. Chatterjee. (2007). "Performance Evaluation of the Diverging Diamond Interchange in Comparison with the Conventional Diamond Interchange." Department of Civil and Environmental Engineering University of Missouri-Columbia 13.
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Operating Performance of Diverging Diamond Interchanges Speth S.B. (2008). "A Comparative Analysis of Diverging Diamond Interchange
Operations." ITE 2008 Annual Meeting and Exhibit Washington D.C. HDR Engineering.
Stanek D. (2007). "Innovative Diamond Interchange Designs How to Increase Capacity and Minimize Cost." Institute of Transportation Engineers Annual Meeting Pittsburgh.
Transportation Research Board. (2010). Highway Capacity Manual. Transportation Research Board of the National Academies Washington D.C. Print.
Woody T. (2006). "Calibrating Freeway Simulation Models in VISSIM." Civil Engineering. University of Washington Master s 20.
Xiao H. R. Ambadipudi J. Hourdakis and P. Michalopoulos. (2005). "Methodology for Selecting Microscopic Simulators Comparative Evaluation of AIMSUN and VISSIM." Intelligent Transportation Systems Institute University of Minnesota. May.
Yeom C. B. Schroeder C. Cunningham C. Vaughan N. Rouphail and J. Hummer. (2014). "Lane Utilization at Two-Lane Arterial Approaches to Double Crossover Diamond Interchanges." In Transportation Research Record Journal of the Transportaton Research Board No. 2461(13) 103112.
Zhang Z. and T. Zong. (2010). "Signal Control of Dual T-intersections and Partial Cloverleaf Interchanges with One Controller." Presented at the Technical Session of 2010 ITE Western District Conference San Francisco.
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APPENDIX A. PRE-DEPLOYMENT DATA COLLECTION AND ANALYSIS
List of Figures
Figure A - 1 Location of Jimmy Carter Blvd. in Metro Atlanta GA ............................ A-4 Figure A - 2 Jimmy Carter Blvd. Bluetooth detector unit locations........................... A-5 Figure A - 3 The 10 Travel-time routes used for multiple distribution analysis
(a) northbound (NB) and southbound (SB) routes through the interchange (b) NB and SB right turn onto I-85 (c) NB and SB left turn onto I-85 (d) right turns originating from I-85 and (e) left turns originating from the interchange ............. A-6 Figure A - 4 Bluetooth raw matches Bluetooth filtered matches and ALPR traveltime comparison...................................................................................................... A-9 Figure A - 5 Mixed Tuesday raw data plot from 3 PM to 7 PM for the SB through route ............................................................................................................................... A-10 Figure A - 6 Travel times for through movements along the study corridor (a) southbound travel times (AM peak) (b) northbound travel times (AM Peak) A-17 Figure A - 7 Travel-time histogram of data in Figure 2 (a) southbound histogram (b) northbound histogram ........................................................................................... A-18 Figure A - 8 Southbound travel-time data with a 6-curve fit....................................... A-20 Figure A - 9 Data separated by distribution southbound direction (PM) ................... A-23 Figure A - 10 Data separated by distribution northbound direction (AM)................. A-24
A-1

Operating Performance of Diverging Diamond Interchanges
List of Tables
Table A - 1 Percentile ranges for facility LOS ratings (TRB 2010)............................ A-21 Table A - 2 Facility LOS ratings for AM lowest mean speed hour on Jimmy Carter Blvd.
............................................................................................................................... A-22
A-2

Operating Performance of Diverging Diamond Interchanges

This project focused on determining the general traffic operating conditions under which a DDI is more appropriate than a CDI and vice versa using traffic simulation and CLV analysis. However as part of the study traffic operations performance data were collected at the interchange and the adjacent area. Vehicle travel-time data were collected for both the pre-deployment and post-deployment period. The following sections provide the details of the data collection and an analysis of the pre-deployment data.

A.1

Data Source Collection Sites and Routes

The traffic operations performance data were collected using commercial "offtheshelf" Bluetooth travel-time detection equipment. A total of six Bluetooth detectors were deployed in the field by the Georgia Department of Transportation (GDOT) over the study area. These detectors recorded Bluetooth media access control (MAC) addresses of Bluetooth-equipped devices (in discoverable mode) within vehicles traversing the study location. MAC addresses are assigned under a scheme designed to reduce the likelihood that any two devices will have the same MAC address. Under this scheme 48-bit MAC addresses are comprised of six sets of two alphanumeric pairs. The first three pairs are assigned to a specific hardware manufacturer while the last three are generated by the manufacturer to be unique among all devices they manufacture (Barcel et al. 2010). Since MAC addresses are expected to be unique among all digital devices Bluetooth detectors can match the MAC addresses detected at different locations to generate travel times between these locations. For the before-and-after DDI analysis 20 unique routes were defined for MAC address matching however only 10 of the routes were used for the analysis. The 10 routes chosen for analysis overlap the other 10 routes that were defined and cover a longer route. This serves two purposes. First these 10 routes cover the entire

A-3

Operating Performance of Diverging Diamond Interchanges coordinated signal corridor allowing evaluation of the corridor as a whole. Second the origins and destinations on these routes are farther from each other thereby reducing the impact of error from uncertainties in detection location of the Bluetooth system (Colberg et al. 2014). Figure A - 1 shows the location of Jimmy Carter Blvd. with respect to Atlanta Georgia. Figure A - 2 shows the Bluetooth device locations in the corridor. Figure A - 3 shows five maps outlining the 10 routes through the interchange for which Bluetooth travel times were collected for this analysis.
Jimmy Carter Blvd. and I-85
Figure A - 1 Location of Jimmy Carter Blvd. in Metro Atlanta GA
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Operating Performance of Diverging Diamond Interchanges

Bluetooth

Start (Southbound) End (Northbound) Best Friend Road

Start (Northbound) End (Southbound) Rockbridge Road
Figure A - 2 Jimmy Carter Blvd. Bluetooth detector unit locations

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Operating Performance of Diverging Diamond Interchanges

Bluetooth Detector
(a)

Bluetooth Detector
(b)

Bluetooth Detector
(c)

Bluetooth Detector

Bluetooth Detector

(d)

(e)

Figure A - 3 The 10 Travel-time routes used for multiple distribution analysis (a) northbound (NB) and southbound (SB) routes through the interchange (b) NB
and SB right turn onto I-85 (c) NB and SB left turn onto I-85 (d) right turns originating from I-85 and (e) left turns originating from the interchange

The 10 routes shown in Figure A - 3 are the 10 possible paths that can be taken through the interchange. The routes are shown in green or red lines/arrows and Bluetooth

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Operating Performance of Diverging Diamond Interchanges
detectors are shown as blue circles. Figure A - 3(a) shows the northbound (NB) and southbound (SB) routes through the interchange that originate and terminate at the northernmost and southernmost Bluetooth detectors. Figure A - 3(b) shows the two routes originating at the northernmost and southernmost Bluetooth detectors making a right turn onto I-85 and terminating at the Bluetooth detectors located at the interchange ramps. Figure A - 3(c) shows the two routes originating at the northernmost and southernmost Bluetooth detectors making a left turn onto I-85 and terminating at the Bluetooth detectors located at the interchange ramps. Figure A - 3(d) shows the two routes originating from the I-85 exit ramps turning right onto Jimmy Carter Blvd. and terminating at the northernmost and southernmost Bluetooth detectors. Finally Figure A - 3(e) shows the two routes originating from the I-85 exit ramps turning left onto Jimmy Carter Blvd. and terminating at the northernmost and southernmost Bluetooth detectors.
As illustrated in Figure A - 3 only one detector was being used at each origin and destination to detect both directions of travel. At each of these locations the detector was mounted on various roadside objects such as utility poles signal support poles or road sign gantry supports. At the interchange ramp locations the detectors were detecting vehicles not only at the adjacent ramp but also at the ramp located on the far side of I-85 across from the detector. This large distance (approximately 220 ft at the NB on-ramp and 250 ft at the SB on-ramp) is within the 1000-ft range of the commercial Bluetooth detectors. However due to the larger distances it is expected that the detection rate of routes originating at the I-85 exit ramps would be lower than that of other routes originating and terminating at locations closer to the detectors. Besides distance from the detector several
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Operating Performance of Diverging Diamond Interchanges

other factors can also affect the detection rate of Bluetooth devices as described in the following subsection.

A.1.1

Bluetooth Characteristics Affecting Travel Times

Bluetooth is a method of wireless communications operating in the 2.4 Gigahertz (GHz) to 2.483 GHz frequencies. The connection process between two Bluetooth devices can take up to 10.24 seconds. Some studies have found that most devices take between 5.12 and 5.76 seconds to establish a connection (Chakraborty et al. 2006 Peterson et al. 2006). Due to the variance in delay of a connection between devices and the detector as well as device signal strength and sensitivity different devices may be detected at different distances from the detector. Furthermore once a device is detected it is typically redetected several times before the device leaves the detection zone. The detectors used in this study are proprietary and specifications of the detectors as well as their filtering processes for multiple detections are not readily available. Therefore the exact location where each Bluetooth device was detected is unknown which adds some variability to the travel times used in this study.

For data verification purposes license plate data were recorded along this corridor via automated license plate recognition (ALPR) cameras at locations approximately matching the locations of the Bluetooth sensors detection areas. The license plates were matched using a Visual Basic script and travel times were derived by subtracting the time stamps of the license plate records across locations. The travel times from the ALPR system and the Bluetooth system were then compared visually. The Bluetooth travel times and the ALPR travel times are plotted in Figure A - 4. The blue triangles are Bluetooth data that have been filtered via the commercial Bluetooth systems filters the green plus signs

A-8

Operating Performance of Diverging Diamond Interchanges are the Bluetooth raw matches and the red circles are the ALPR travel times. Figure A 4 shows that although ALPR generates more travel-time data both the filtered and unfiltered Bluetooth travel times closely match the ALPR travel-time data. Furthermore both systems show similarities in outlying data points. Finally this comparison also shows that with enough data points collected on a single day the multiple distribution tendency is prominent. In the ALPR data two prominent bands are observed between 2 00 PM and 4 15 PM. As congestion sets in after 4 15 PM the lower band begins to diminish but does not completely disappear.
Figure A - 4 Bluetooth raw matches Bluetooth filtered matches and ALPR travel-time comparison
Besides the variability in detection location affecting travel times previous studies of Bluetooth travel-time technology have found detection rates ranging from 5 to 10 percent (Day et al. 2010 Brennan et al. 2010 Tarnoff et al. 2009 Wang et al. 2010). These detection rates are calculated as the number of unique MAC address detections divided by the total volume passing the detector. Due to the low detection rate of
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Operating Performance of Diverging Diamond Interchanges Bluetooth detectors (Zinner 2012 Box 2011) it is difficult to perform analyses and identify patterns over short (e.g. one-hour) intervals and successful analysis often requires combining data from multiple days. For this study data were segregated into five data sets one for each day of the week. The individual datasets comprised 14 days of data collected over a 16-week period between Monday August 5 2013 and Friday November 22 2013 and excludes data collected during the week of a major U.S. holiday (i.e. Labor Day-- Monday September 2 2013). Due to an outage in the Bluetooth system data were also not collected from September 13 2013 to September 25 2013.
The individual data points of the data across multiple days were plotted with a different color symbol for each unique day within the data set to check whether any of the days displayed drastically different traffic patterns. A sample plot using the data for Tuesdays is provided in Figure A - 5.
Figure A - 5 Mixed Tuesday raw data plot from 3 PM to 7 PM for the SB through route A-10

Operating Performance of Diverging Diamond Interchanges

A.2

Previous Research

As observed in Figure A - 4 the travel-time data from the study site displayed multiple bands in the data indicating the presence of multiple distributions in the dataset. Bimodal and multimodal distributions of travel time have been previously observed in a number of settings. These include arterials (Ji and Zhang 2013 Yang et al. 2014) due to the presence of signalized intersections and freeways (Park et al. 2010 Chalumuri and Asakura 2012 Colberg et al. 2014) when there are lane closures during construction periods or more generally when both congested and uncongested travel is present. These multimodal distributions reflect different subgroups of traffic that may experience different service quality along the same roadway. Previous studies have used expectationmaximization (EM) and hierarchical Bayesian mixture models to separate these distributions in order to develop travel-time reliability indices (Ji and Zhang 2013 Yang et al. 2014 Park et al. 2010 Chalumuri and Asakura 2012).

In this study an expectationmaximization algorithm (Benaglia et al. 2010) is utilized to separate multimodal travel-time data collected on a major arterial (Jimmy Carter Blvd.) in the metropolitan Atlanta area and assign a separate corridor-level LOS rating to each distribution. This multiple LOS rating method is not intended to replace the HCM 2010 facility LOS method (TRB 2010) instead it is being developed as a supplementary tool to provide more detailed LOS information. For example the impact of roadway improvements (e.g. signal timing geometric changes etc.) on the different road user subgroups may be directly evaluated by providing a more detailed view that captures the underlying performance of each subgroup rather than a single aggregate LOS measure. This type of analysis is becoming available by the growing availability of disaggregate

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Operating Performance of Diverging Diamond Interchanges
travel-time data by continuous data collection systems such as Bluetooth cell phone tracking etc. The advantages and drawbacks of this approach are discussed later in the text.
As mentioned earlier bimodal/multimodal travel-time distributions have been encountered on multiple roadway types (Park et al. 2010 Chalumuri and Asakura 2012 Ji and Zhang 2013 Colberg et al. 2014 Yang et al. 2014). Typically these distributions have been studied in association with research on travel-time reliability and/or congestion detection. For example two previous studies aimed to develop congestion detection algorithms for arterial roadways (Ji and Zhang 2013 Yang et al. 2014). Ji and Zhang successfully used bus probe data to collect travel times along an arterial roadway on the Ohio State University campus by recording from the campus bus automatic vehicle location (AVL) system. In that study location data near bus stops were omitted in order to collect travel-time data on segments that included either one signal or no traffic signal and did not include delay from boarding and alighting. It was found that the segments with one signal consistently showed bimodality in travel times while a segment without a signal had only a single mode. Curves were fit to the resulting data using a Bayesian mixture model assuming either a single or bimodal distribution and then congestion-detection algorithms were applied. In the segments with a signalized intersection the developed congestion-detection algorithms detected congestion more accurately with the mixed models than the single-mode models (Ji and Zhang 2013).
In a second study by Yang et al. similar data were collected on multiple corridors in the downtown area of Nanjing China. The selected links were similar to Ji and Zhang s study in that each link only contained one signal. Similarly bimodal distributions were found and an EM algorithm was used to separate the data. In this study a combination of
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Operating Performance of Diverging Diamond Interchanges
six distribution types were tested on each data set and the best fit for each distribution was found based on the resulting R-squared values. Subsequently the resulting distributions were applied to two methods of detecting congestion in bimodal travel-time distributions the expected-travel-time and RATIO indices (Yang et al. 2014). Additionally Henclewood et al. suggested that although first moment values such as average travel time may be sufficient to evaluate general traffic performance at an aggregated level considering travel times at the distribution level allows for a better representation of traffic performance at an individual vehicle level (Henclewood et al. 2013).
Freeway studies have also found bimodal travel-time distributions (Park et al. 2010 Chalumuri and Asakura 2012). Park et al. created a model to predict congested and uncongested freeway travel times similar to weather forecasting. In that study simulated data were used from a model of I-66 outside of Washington D.C. Using this model congested and uncongested conditions were simulated separately and data from the different simulation runs intentionally were mixed. Here varying ratios of congested travel-time data and uncongested travel-time data were mixed and separated using EM algorithms. Travel-time data for all vehicles completing the route were available so the ratio of congested to uncongested data was known before bimodal curve fitting. After separating the data the output ratios from the EM algorithm were found to be very similar to the known input conditions. Their conclusion was that if a sufficiently high sampling rate could be attained on freeways the ratio of congested to uncongested travel times during periods of the day could be accurately estimated. Therefore these ratios developed using historical data could be used to give drivers the probability of encountering congestion during a given time on a given route and provide an estimate of congested and
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Operating Performance of Diverging Diamond Interchanges

uncongested travel times (Park et al. 2010). These multimodal distributions have also been determined by Colberg et al. (2014) to occur on freeways in work zones when lane closures are present. They found that drivers in the left lanes of the study corridor (the location of the lane closures) experienced significantly shorter travel times than those in the right lanes of the same freeway. The researchers believed that vehicles in the right lanes experienced higher delays due to queue formation in the right lanes and that slower moving trucks were not permitted to travel in the left lanes (Colberg et al. 2014).

A.3

Multiple Travel-time Distribution Separation

Arterial roadway travel times often exhibit multiple travel-time distributions within the same time period. This is typically caused by the signal systems in place along these corridors (Ji and Zhang 2013 Yang et al. 2014). It is well known that coordinated signal systems may systematically enforce groupings of vehicles into different travel-time bands. For example one group of vehicles may be able to traverse the entire corridor stopping only once due to a red signal while another vehicle group may traverse the same corridor and encounter multiple red signals. In this scenario the vehicles that stop multiple times will have more delay and a longer travel time than vehicles that stop only once. Furthermore as congestion builds along signalized corridors and queueing spills back from one intersection to the next it becomes more likely that drivers will be delayed at more than one intersection pushing more drivers into higher travel-time bands. Another source of these multiple distributions may be congestion and delays due to lane-specific conditions. For example spillback from left-turn lanes into through lanes may cause added delay to through vehicles traveling in the lanes adjacent to the left-turn lanes. For instance in the corridor studied for the current research left-turn lane spillbacks have been witnessed by

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Operating Performance of Diverging Diamond Interchanges
the research group along the study corridor during congested periods. Additional potential causes for multiple travel-time distributions exist such as high driveway densities lane additions and drops etc.
For this multiple distribution data deconvolution analysis the paths of interest are from (1) the north end to the south end of the Jimmy Carter Blvd. corridor a distance of 2.4 miles (4 km) and (2) the reverse path. Figure A - 6 illustrates the observed travel times over the study period for the southbound (Tuesday 5 00 PM to 6 30 PM) and northbound (Tuesday 5 00 PM to 6 30 PM) through movements respectively. In this figure datapoints represent a single paired (origindestination) observed travel time with the varying colors representing different measurement days. The time periods analyzed in this research were derived from the signal timing plan periods (e.g. before and after the 5 PM to 6 30 PM period different signal plans are implemented). These analysis periods were chosen to eliminate the possibility of multiple travel-time distributions occurring due to signal plan changes within the analysis periods. These data sets have been pre-processed with two filters. The first filter is a "20 minute" filter that removes any travel-time observation greater than 20 minutes. The second filter is a "60 miles per hour" filter that acts to remove any observed travel time that when converted to a speed is greater than 60 mph. These filters removed data likely resulting from well-known issues associated with travel-time data collected using Bluetooth technology (Wasson et al. 2010 Colberg 2013 Colberg et al. 2014) and are considered well outside the reasonable travel-time range for this corridor. In all cases the number of removed data points was minimal.
Observing Figure A - 6(a) travel-time "bands" are discernable at approximately 6 8 and 10 minutes. Furthermore in Figure A - 6(b) it is difficult to visually distinguish
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Operating Performance of Diverging Diamond Interchanges any obvious banding of travel times. However in the histograms for these data shown in Figure A - 7 for the southbound direction there are possibly up to five discernable traveltime bands the first centered at slightly less than 6 minutes the second at slightly less than 8 minutes the third (and fourth) at greater than 8 minutes and a possible fifth band capturing data over 14 minutes. For the northbound direction there also may be up to five distributions however these distributions appear to be closer together suggesting that there is possibly less congestion. These multiple distributions do appear to be centered at approximately 5.5 6.5 8 and 9 minutes as well as a fifth distribution encompassing data from 10 minutes onward.
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Operating Performance of Diverging Diamond Interchanges
(a)
(b) Figure A - 6 Travel times for through movements along the study corridor (a) southbound travel times (AM peak) (b) northbound travel times (AM Peak)
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Operating Performance of Diverging Diamond Interchanges

(a)

(b)

Figure A - 7 Travel-time histogram of data in Figure 2 (a) southbound histogram (b) northbound histogram

The multiple peaks (modes) displayed in the histograms provide strong evidence for the existence of multiple travel-time distributions. To identify the characteristics of these individual distributions multiple gamma curves were fit to the observations. To accomplish this an EM algorithm for multiple gamma curve fitting was used. This algorithm named the gammamixEM function is part of the "mixtools" package that was developed and implemented in R by Bengalia et al. (2009). This function uses the expectationmaximization iterative process to fit multiple gamma curves and provides an a posteriori probability for each data point (i.e. the estimated probability that the point belongs to a particular distribution). These probabilities were used in conjunction with a random number generated between 0 and 1 to assign individual data points to a particular distribution. It should be noted that since multiple distributions were fit multiple posterior probabilities were generated for each data point the sum of which equals 1. Finally Figure A - 8 shows the fitted gamma curves for each travel-time band and the histograms of the data assigned to each distribution for the southbound direction. Six distributions were fit

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Operating Performance of Diverging Diamond Interchanges for the southbound direction. This number of underlying distributions was chosen using an R-square value in conjunction with an Akaike information criterion (AIC) number.
In this process multiple distributions were fit (1 to 7 distributions). To ensure that each distribution fit was an optimum fit the multiple distribution function was run 100 times for each number of distributions and the fit with the highest R-squared value was taken to compare between number of distributions. To compare between the number of distributions the AIC value was used. The AIC value uses the log likelihood of the fit with a modification factor for the number of parameters used in the fit. This allows a comparison between different number of fits while accounting for information lost due to increased complexity of the model.
In general multi-distributional fit provided a meaningful improvement in information over a single distribution fit as witnessed by the AIC values. However based on this process some time periods did show a better fit with only a single distribution rather than multiple distributions for the northbound route. For example for the 7 45 AM to 8 45 AM and the 3 00 PM to 5 00 PM time periods the AIC values were lowest for a single distribution. For the data shown in Figure A - 8 a six-distribution fit was chosen. This fit s AIC value was 2188 while its respective single-distribution fit AIC value was 2295. Because the AIC value for the six-distribution fit was lower it provides a meaningful improvement in information content.
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Operating Performance of Diverging Diamond Interchanges

Figure A - 8 Southbound travel-time data with a 6-curve fit.

A.4

Multiple LOS Rating Assignment

After assigning multiple gamma functions to the data sets and separating the data by distribution an LOS rating was assigned to each distribution. In order to assign an LOS rating for each distribution a base free-flow speed for each direction was first determined. The HCM methodology for determining the facility LOS rating was followed when determining the base free-flow speed (TRB 2010). A base free-flow speed was not field measured as the given Bluetooth data include control delays and do not allow for distinguishing free-flow speeds on a corridor (TRB 2010).

Travel speed through the corridor was derived from the travel-time data distributions. For each distribution created through the curve-fitting procedure the average travel time was converted into a speed in miles per hour. The final step in determining facility LOS was to calculate the percent reduction of free-flow speed for each individual mode and determine which speed-reduction range included the observed reduction.

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Operating Performance of Diverging Diamond Interchanges
Table A - 1 shows the percentile ranges for each LOS rating according to the 2010 HCM. The multiple-facility LOS ratings for the lowest speed hour for the AM and PM periods can be found in the results section in Table A - 2. In the HCM method of analysis a v/c ratio greater than 1.0 automatically warrants an LOS of F as shown in Table A - 1. In this study volume counts corresponding to the travel-time data were not available. Thus for this analysis v/c ratio was not considered when determining LOS ratings.

Table A - 1 Percentile ranges for facility LOS ratings (TRB 2010)

Travel Speed as a Percentage of Base Free-Flow Speed (%)
85
6785
5067
4050
3040
30

LOS by Critical Volume-to-Capacity Ratio

1.0

1.0

A

F

B

F

C

F

D

F

E

F

F

F

A.5

Results

For brevity one day of results from the combined Tuesday dataset is shown here. Table A - 2 presents the LOS and mean speed for each modal distribution and the overall

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Operating Performance of Diverging Diamond Interchanges
corresponding signal timing period of the day and direction along the corridor for the Tuesday data. LOS ratings are generally lower for the PM time periods than for the AM. Figure A - 9 and Figure A - 10 provide temporal plots and histograms for the complete data set and each of the three modal distributions (Mode 1 slowest) determined by the fitting procedures for the southbound and northbound routes respectively.

Table A - 2 Facility LOS ratings for AM lowest mean speed hour on Jimmy Carter Blvd.

Direction Time SB 6 00 - 7 45 SB 7 45 - 8 45 SB 8 45 - 9 30 SB 9 30 - 15 00 SB 15 00 - 17 00 SB 17 00 - 18 30 SB 18 30 - 19 00 NB 6 00 - 7 45 NB 7 45 - 8 45 NB 8 45 - 9 30 NB 9 30 - 15 00 NB 15 00 - 17 00 NB 17 00 - 18 30 NB 18 30 - 19 00

Mean Speed 1234567
19.2 26.2 14.8 11.5 8.33 -- -- 25.6 18.9 13.1 8.11 -- -- -- 25.2 18.7 14.5 11.8 9.25 -- -- 28.2 20.9 16.2 12 9.05 -- -- 25.2 39.4 18.4 14.1 10.8 8.25 -- 22.8 17.2 13.3 10.7 8.93 7.71 -- 24.8 17.7 13.4 10.9 8.18 -- -- 22.3 11.5 -- -- -- -- -- 16.4 -- -- -- -- -- -- 26.9 15.5 -- -- -- -- -- 22.4 20.8 9.7 -- -- -- -- 15.7 -- -- -- -- -- -- 17.1 7.77 -- -- -- -- -- 19.7 10.7 -- -- -- -- --

Level of Service 1234567
D C E F F -- -- C D E F -- -- -- C D E F F -- -- C D E F F -- -- C A D E F F -- C D E F F F -- C D E F F -- -- C F -- -- -- -- -- E -- -- -- -- -- -- C E -- -- -- -- -- C D F -- -- -- -- E -- -- -- -- -- -- E F -- -- -- -- -- D F -- -- -- -- --

Avg Avg Speed LOS 18.6373 D 17.0666 E 16.5644 E 20.991 D 19.4232 D 12.2724 F 15.0686 E 20.4726 D 16.3952 E 24.8433 C 20.3692 D 15.6655 E 16.6385 E 18.3045 D

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Operating Performance of Diverging Diamond Interchanges
Figure A - 9 Data separated by distribution southbound direction (PM) A-23

Operating Performance of Diverging Diamond Interchanges
Figure A - 10 Data separated by distribution northbound direction (AM) A-24

Operating Performance of Diverging Diamond Interchanges

A.6

Analysis and Discussion

For the Tuesday data (Table A - 2) the lowest mean speeds were observed during the 5 00 PM to 6 30 PM time periods for the southbound direction and from 3 00 PM to 5 00 PM for the northbound direction. In the southbound direction the observed number of distributions ranged from four to six distributions. The first distribution typically received an LOS of C in the southbound direction except the 6 00 AM to 7 45 AM time period. Interestingly the second time period in some instances contained a higher LOS than the first distribution for the southbound direction. Typically the LOS in the second distribution here was D except in the case of the 6 00 AM to 7 45 AM period and the 3 00 PM to 5 00 PM period where the LOS was C and A respectively for the southbound direction. This may be due to higher travel times contained in a broader first distribution for these time periods. The third distribution typically was assigned an LOS of E except during the 3 00 PM to 5 00 PM time period where it received an LOS of D for the southbound direction. The fourth distribution typically contained an LOS of F except in the 3 00 PM to 5 00 PM time period when it received an LOS of E for the southbound direction. Finally the fifth and sixth distributions received an LOS of F for the southbound direction.

For the northbound direction the number of distributions that were determined to exist ranged from one to three. Since a lower number of distributions was fit for this direction the LOS ratings assigned to each distribution were more mixed than for the southbound direction. Here the first distribution was assigned an LOS of C E or D the second distribution was assigned an LOS of F E or D and the third distribution existing from 9 30 AM to 3 00 PM received an LOS of F.

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Operating Performance of Diverging Diamond Interchanges
Where multiple distributions were observed drivers in the slowest groups experienced average speeds ranging from 7.71 mph to 9.25 mph for the southbound direction. For the northbound direction drivers in the slowest groups experienced average speeds ranging from 7.77 mph to 15.5 mph. From Figure A - 9 and Figure A - 10 it can be seen that there are a number of vehicles in this slowest distribution. During peak periods it is plausible that many of these are actual travel times from vehicles that do not stop along the corridor but experience severe congestion pushing them into the slowest distribution. However during non-congested periods of the day the slowest distributions carry fewer data points but do not disappear. There are 98 driveways and 12 signalized intersections from which a driver may access many businesses ranging from office complexes to restaurants. Due to the high number of destinations along the corridor it is possible that members of the slowest distributions may also have stopped for a few minutes along the corridor.
Despite this potential mix of vehicles in the slowest groups these data remain informative. When short stops (e.g. to refuel) are the primary reason for the long travel times which is likely during uncongested traffic one would expect similar behavior in a beforeafter analysis allowing for separation of this group in any improvement analysis. Thus for example where only signal timing has changed these vehicles should not be considered when using Bluetooth data to compare beforeafter results as their behavior is likely not a function of the signal timing. During congested conditions this mode may contain a mix of vehicles that experience high delays and vehicles with short stops. Where improvements are not anticipated to impact the number of vehicles making stops changes in these vehicles distribution will partially reflect the impact of improvements on highly
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Operating Performance of Diverging Diamond Interchanges
delayed vehicles. In addition fewer samples in the mode in the post-deployment data will indicate fewer highly delayed vehicles.
The researchers believe that where the data had multiple distributions the fastest group (group 1 or 2) and the middle group (group 3 or 4) of drivers likely drove the corridor continuously without stopping except where instructed to do so by traffic control devices. As seen in Figure A - 9 and Figure A - 10 approximately 73% to 78% of the data points lie within these first distributions. Although a uniform sampling rate over all road user subgroups cannot be assumed (discussed below) it can be assumed that a proportion of vehicles traversing the corridor fall into these two distributions. For the southbound PM direction shown in Figure A - 9 these distributions are separated by a little over 2 minutes or 120 seconds. For the northbound AM direction shown in Figure A - 10 these distributions are separated by approximately 1 minute or 60 seconds. During the time period shown in Figure A - 9 the signal-timing cycle length along the corridor is 160 seconds and for the time period shown in Figure A - 10 the signal-timing cycle length along the corridor is 140 seconds. These differences are likely related to different paths through the timespace diagram as a function of signal offsets vehicle arrival times and congestion (potentially lane specific). For example significant lane-specific delays were observed in the field during the peak periods as left-turning vehicles at some signalized intersections especially near the I-85 interchange spill back out of the left-turn lanes into adjacent left-most through lanes. While this analysis does not conclusively determine the reason for the different behaviors it does highlight that different road user subgroups are experiencing different LOS. Improved analysis and evaluations (e.g. beforeafter
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Operating Performance of Diverging Diamond Interchanges

comparisons) may be obtained by considering these groups separately rather than as a single aggregate collection of road users.

A.7

Limitations and Future Applications

The concept of multiple LOS rating assignment can be used to give a more detailed description of traffic conditions. There are two scenarios that affect how the multiple LOS ratings can ultimately be used for public reporting. Under the first assumption there is a uniform travel-time sampling rate over all road user subgroups of the corridor of interest and under the second assumption a uniform sampling rate cannot be reasonably assumed (e.g. the first assumption cannot be proven). These two situations and their future exploration are discussed in the next two subsections.

A.7.1

Scenario One Uniform Sampling Rate Over All Road User Subgroups

This approach implicitly assumes that the sample data were collected uniformly across all road user subgroups (that is each of the underlying gamma curves is sampled at the same rate). In the case where a uniform sampling rate across all subgroups can be assumed proportions of vehicles in each distribution can be accurately estimated and presented along with the LOS for that distribution. Thus the multiple LOS rating information will become more robust in describing traffic patterns and situations. Furthermore if using the multiple LOS method as a performance measurement tool for before and after project implementations one can see clearly not only the shifts and changes in distributions on a statistical level but a shift in the percentage of drivers belonging to each distribution.

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Operating Performance of Diverging Diamond Interchanges

A.7.2

Scenario Two Cannot Assume Uniform Sampling Rate Over All Road User Sub Groups

When it cannot be reasonably assumed that there is a uniform sampling rate over all road user subgroups the multiple LOS method is not as robust as the percentages of drivers in each distribution cannot be assumed to be the same as the sampling proportions. In this situation it can only be assumed that the different distributions exist within the data set and that there are certain unknown proportions of vehicles experiencing different levels of service depending on combinations of red or green signals encountered while traversing the corridor. In the case of the data set used for this research project a uniform sampling rate across road user subgroups cannot be safely assumed as the likelihood of a Bluetooth data point is related to vehicle speed and distance from the detector as well as other factors (Colberg 2013 Colberg et al. 2014). When using multiple LOS ratings as performance measures for before and after analyses analysts can use the separated data sets as individual distributions and run robust statistical tests to determine if changes in the distributions are statistically significant (e.g. using t-tests chi-squared tests etc.). Typically statistical tests apply only to a certain distribution type assumed by the analyst. When these tests are applied to data that clearly have multiple distributions the test results cannot be taken as accurate as would be the case with the aggregated travel-time distributions. Using these data-separation techniques researchers can test the significance of shifts in the separated distributions. Such a test can also be useful while a change may not affect the LOS ratings the statistical tests may show statistically significant changes in the distribution proving that an improvement did occur due to changes made in the corridor.

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Operating Performance of Diverging Diamond Interchanges

A.8

Conclusions

Separation of the mixed distributions allows for robust statistical testing of the separated data. However under the conditions that a uniform sampling rate can be assumed proportions of vehicles in each distribution can be accurately estimated and shown along with the corresponding LOS ratings to give a more comprehensive picture of traffic conditions to nontransportation professionals. In the case of Jimmy Carter Blvd. in northeast Atlanta Georgia researchers learned that when multiple distributions were found to exist the highest speed distribution in the southbound direction exhibited a typical LOS C or D rating while the northbound highest speed distribution exhibited LOS C D or E ratings. The second distribution in the southbound direction exhibited LOS ratings C D or A while in the northbound direction D E and F LOS ratings were experienced. Time periods that experienced three to six distributions exhibited an LOS of D E or F in these distributions. During the peak periods a significant portion of travel times fell into the fourth or fifth (slowest) distribution. It is plausible that this distribution during the peak periods is composed of a portion of travel times where drivers did not make any stops in the corridor but were pushed into this distribution by severe congestion. The fourth or fifth distribution however is mixed with outlying data points where drivers may have stopped as there are ample opportunities (98 total driveways) for drivers to stop along the corridor. During off-peak periods the fifth distribution contains a much smaller proportion of the travel times suggesting that these are mostly composed of travel times where drivers stopped at a destination along the corridor for a short period of time.

Multiple curves were fit to the travel-time data sets in this study using an EM algorithm for gamma curves. The data were separated using the posterior probabilities

A-30

Operating Performance of Diverging Diamond Interchanges calculated by the R statistical package "mixtools" using the "gammamixEM" function (Benaglia et al. 2010). LOS ratings were assigned using a method based on the HCM 2010 manual (TRB 2010). In this method the base free-flow speed was calculated according to the HCM 2010 manual (TRB 2010) and average travel times for each distribution were calculated and converted to a speed to use as the travel speed in determining the multiple LOS ratings. The HCM-recommended percentile thresholds for facility LOS ratings were used to assign each distribution an LOS (TRB 2010).
Previous studies have found usefulness in separating multiple distributions for research in travel-time reliability indices (Park et al. 2010 Chalumuri and Asakura 2012 Ji and Zhang 2013 Yang et al. 2014). This study found it useful to separate the travel-time data to assign multiple LOS ratings to the different distributions. From the analysis it was clear that different subgroups of vehicles can experience different LOS ratings on the same roadway facility during the same time period. By separating the travel times into their underlying distributions it becomes possible to consider each of these subgroups separately. Separating these distributions will allow for more robust statistical tests to be used to detect changes in the before-and-after study for the Jimmy Carter Blvd. interchange.
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Operating Performance of Diverging Diamond Interchanges

A.9

References

Barcel J. L. Montero Laura Marqus and C. Carmona. (2010). "Travel Time Forecasting and Dynamic OriginDestination Estimation for Freeways Based on Bluetooth Traffic Monitoring." In Transportation Research Record Journal of the Transportaton Research Board No. 2175 Accessed from http //trb.metapress.com/content/17x1v88n6p8363p1/fulltext.pdf.

Benaglia T. D. Chauveau D. Hunter and D. Young. (2010). "mixtools An R Package for Analyzing Mixture Models." In Journal of Statistical Software Oct. 32(6).

Box S. (2011). "Arterial Travel Time Data Collection Using Bluetooth Technology." Master s Thesis Georgia Institute of Technology.

Brennan T. J. Ernst C. Day D. Bullock J. Krogmeier and M. Martchouk. (2010). "Influence of Vertical Sensor Placement on Data Collection Efficiency from Bluetooth MAC Address Collection Devices." Journal of Transportation Engineering Dec. 136 11041109.

Chakraborty D. G. Chakraborty S. Naik and N. Shiratori. (2006). "Discovery and Delay Analysis of Bluetooth Devices." 7th International Conference on Mobile Data Management Accessed from http //ieeexplore.ieee.org/stamp/stamp.jsp tp &arnumber 1630650.

Chalumuri R.S. and Y. Asakura. (2012). "Modelling Travel Time Distribution Under Various Uncertainties on Hanshin Expressway of Japan." European Transport Research Review. 6 8592.

Colberg K. (2013). "Investigating the Ability of Automated License Plate Recognition Camera Systems to Measure Travel Times in Work Zones." Master s Thesis Georgia Institute of Technology.

Colberg K. W. Suh J. Anderson S. Zinner A. Guin M. Hunter and R. Guensler. (2014). "Lane Bias Issues in Work Zone Travel Time Measurement and Reporting." In Transportation Research Record Journal of the Transportation Research Board No. 2458 7887.

Day C.M. R. Haseman H. Premachandra T.M. Brennan J. Wasson J. Sturdevant and D. Bullock. (2010). "Evaluation of Arterial Signal Coordination Methodologies for Visualizing High-Resolution Event Data and Measuring Travel Time." In

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Operating Performance of Diverging Diamond Interchanges
Transportation Research Record Journal of the Transportation Research Board No. 2192 3749 December 1 2010.
Henclewood D. W. Suh M. Rodgers and M. Hunter. (2013). "Statistical Calibration for Data-Driven Microscopic Simulation Model." In Transportation Research Board 92nd Annual Meeting Transportation Research Board of the National Academies Washington D.C.
Ji Y. and H.M. Zhang. (2013). "Travel Time Distributions on Urban Streets Their Estimation with a Hierarchical Bayesian Mixture Model and Application to Traffic Analysis Using High-Resolution Bus Probe Data." In Transportation Research Board 92nd Annual Meeting Transportation Research Board of the National Academies Washington D.C.
Park S. H. Rakha and F. Guo. (2010). "Calibration Issues for Multistate Model of Travel Time Reliability." In Transportation Research Record Journal of the Transportation Research Board No. 2188 7484.
Peterson B. R. Baldwin and J. Kharoufeh. (2006). "Bluetooth Inquiry Time Characterization and Selection." IEEE Transactions on Mobile Computing 5(9) Accessed from http //ieeexplore.ieee.org/stamp/stamp.jsp tp &arnumber 1661527.
Tarnoff P.J. D. Bullock S. Young J. Wasson N. Ganig and J. Sturdevant. (2009). "Continuing Evolution of Travel Time Data Information Collection and Processing." In Transportation Research Board 88th Annual Meeting Transportation Research Board of the National Academies Washington D.C. 14.
Transportation Research Board. (2010). Highway Capacity Manual. Transportation Research Board of the National Academies Washington D.C.
Wang Y. Y. Malinovskiy Y. Wu U. Lee T. Bailey and M. Neely. (2010). "Field Experiments with Bluetooth Sensors." Accessed from http //www.westernstatesforum.org/Documents/2010/UW_FINAL_Bluetooth_W SRTF_6-17-10.pdf
Wasson J. R. Haseman and D. Bullock. (2010). "Real-Time Measurement of Work Zone Travel Time Delay and Evaluation Metrics Using Bluetooth Probe Tracking." In Transportation Research Board 89th Annual Meeting Transportation Research Board of the National Academies Washington D.C.
A-33

Operating Performance of Diverging Diamond Interchanges Yang F. M. Yun and X. Yang. (2014). "Travel Time Distributions under Interrupted
Flow and Its Application to Travel Time Reliability." In Transportation Research Board 93rd Annual Meeting Transportation Research Board of the National Academies Washington D.C. Zinner S. (2012). "A Methodology for Using Bluetooth to Measure Real-time Work Zone Travel Time." Master s Thesis Georgia Institute of Technology.
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APPENDIX B. COST OF CONSTRUCTION OF DIVERGING DIAMOND INTERCHANGES AND ALTERNATIVE DESIGNS AT FOUR LOCATIONS
Table B - 1 compares the construction costs of DDIs and other alternative designs
at four locations in the United States (Chlewicki 2014). This table shows large cost savings
in constructing DDIs over other alternatives in many cases.

Table B - 1 Cost of construction of diverging diamond interchanges and alternative designs at four locations

Interchange Location

I-44 Route 13

Springfield MO

I-435 Front Kansas City

Street

MO

SR_265 SR62

Utica IN

I-590 Winton Brighton

Road

NY

DDI Cost (real or estimated
$Million) 3.2
6.7
52
3 4

Alternative Design Cost ($Million)
10
CDI 11. 4 SPUI 25
118
SPUI 10 Triple Left Diamond 13.6

Cost Saving
(%) 70
75
55
75

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APPENDIX C. EXCEL MACRO VISUAL BASIC SCRIPTS

This appendix provides Visual Basic scripts used in the Macro functions of Microsoft Excel to automate the data analysis and organization processes for the CLV analysis.

C.1

Optimized Signal Timing Relocation

The following VB script relocates the optimized signal timing plans from Synchro to the "Signal Timing" worksheet under the CLV workbook into a format that is suitable for v/c ratio calculations.

Sub SynchroCDITimingFill()
Dim CLVwbk As Workbook Dim CLVSheet As Worksheet Dim Timingwbk As Workbook Dim TimingSheet As Worksheet Dim testval
Set TimingSheet Sheets("Timing") Set CLVwbk Workbooks. Open("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final CLV Method CLV Spreadsheet LC2. xlsm") Set CLVSheet CLVwbk. Sheets("Signal Timing") Dim rownumber As Long
rownumber (TimingSheet. Range("A1" TimingSheet. Range("A1"). End(xlDown)). Rows. Count) - 2 Planrow 1 count for rows of each signal plan
For PlanID 1 To rownumber
ICode Cells(2 PlanID 1) IntID Cells(2 PlanID 2)
If IntID 4 Then NB intersection Phase1 Cells(2 PlanID 3) SBL1 Phase2 Cells(2 PlanID 4) NBT1 Phase6 Cells(2 PlanID 8) SBT1 Phase8 Cells(2 PlanID 10) EBL1 CL Cells(2 PlanID 11) cycle length Offset Cells(2 PlanID 12) CLVSheet. Cells(2 Planrow 15) ICode CLVSheet. Cells(2 Planrow 16) Phase2 CLVSheet. Cells(2 Planrow 17) Phase1 CLVSheet. Cells(2 Planrow 18) Phase6 CLVSheet. Cells(2 Planrow 19) Phase8 CLVSheet. Cells(2 Planrow 24) CL

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Operating Performance of Diverging Diamond Interchanges
CLVSheet. Cells(2 Planrow 25) Offset
ElseIf IntID 6 Then SB intersection Phase2 Cells(2 PlanID 4) NBT2 Phase4 Cells(2 PlanID 6) WBL2 Phase5 Cells(2 PlanID 7) NBL2 Phase6 Cells(2 PlanID 8) SBT2 Offset Cells(2 PlanID 12) CLVSheet. Cells(2 Planrow 20) Phase2 CLVSheet. Cells(2 Planrow 21) Phase4 CLVSheet. Cells(2 Planrow 22) Phase5 CLVSheet. Cells(2 Planrow 23) Phase6 CLVSheet. Cells(2 Planrow 26) Offset Planrow Planrow 1 add 1 to Planrow if IntID 6
End If
Next PlanID
End Sub

C.2

Volume-to-Capacity Ratio Calculation and Redistribution

The following VB scripts automatically input traffic demands and turn-movement ratios into the "DDI_CLV" and "CDI_CLV" worksheets in the CLV workbook and relocate calculated v/c ratios to "Color Coded" worksheets where calculated DDI and CDI v/c ratios are color-coded and plotted for comparison.

C.2.1

DDI_CLV script

Sub CLVTableFillDDI()
Dim JCEnterVol As Integer Dim I85OffVol As Integer For VolumeCase 1 To 7
JCEnterVol Cells(3 VolumeCase 30)
For RampCase 1 To 4 I85OffVol Cells(3 VolumeCase 30 RampCase)
If I85OffVol 1 Then
For PropLeft 1 To 7 Prop Cells(3 PropLeft 37) Cells(3 2) JCEnterVol Cells(4 2) I85OffVol Cells(5 7) Prop VCNBT1 Cells(56 3) VCSBT1 Cells(57 3)

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Operating Performance of Diverging Diamond Interchanges

VCSBL1 Cells(58 3) VCEBL1 Cells(59 3) VCNBT2 Cells(54 6) VCNBL2 Cells(55 6) VCSBT2 Cells(58 6) VCWBL2 Cells(59 6) Intvc Cells(59 10) Sheets("Color Coded"). Cells(7 PropLeft 2 (((VolumeCase - 1) * 11) (RampCase * 2))) VCNBT1 Sheets("Color Coded"). Cells(14 PropLeft 2 (((VolumeCase - 1) * 11) (RampCase * 2))) VCSBT1 Sheets("Color Coded"). Cells(21 PropLeft 2 (((VolumeCase - 1) * 11) (RampCase * 2))) VCSBL1 Sheets("Color Coded"). Cells(28 PropLeft 2 (((VolumeCase - 1) * 11) (RampCase * 2))) VCEBL1 Sheets("Color Coded"). Cells(35 PropLeft 2 (((VolumeCase - 1) * 11) (RampCase * 2))) VCNBT2 Sheets("Color Coded"). Cells(42 PropLeft 2 (((VolumeCase - 1) * 11) (RampCase * 2))) VCNBL2 Sheets("Color Coded"). Cells(49 PropLeft 2 (((VolumeCase - 1) * 11) (RampCase * 2))) VCSBT2 Sheets("Color Coded"). Cells(56 PropLeft 2 (((VolumeCase - 1) * 11) (RampCase * 2))) VCWBL2 Sheets("Color Coded"). Cells(63 PropLeft 2 (((VolumeCase - 1) * 11) (RampCase * 2))) Intvc
Next PropLeft
End If
Next RampCase
Next VolumeCase
End Sub

C.2.2

CDI_CLV script

Sub CLVTableFillCDI()
Dim JCEnterVol As Integer Dim I85OffVol As Integer
For VolumeCase 1 To 7 JCEnterVol Cells(3 VolumeCase 30)
For RampCase 1 To 4 I85OffVol Cells(3 VolumeCase 30 RampCase)
If I85OffVol 1 Then
For PropLeft 1 To 7 Can be up to 7 Prop Cells(3 PropLeft 37) Enter Volumes to be test into calculator Cells(3 2) JCEnterVol Cells(4 2) I85OffVol

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Operating Performance of Diverging Diamond Interchanges
Cells(5 7) Prop VCNBT1 Cells(56 3) VCSBT1 Cells(57 3) VCSBL1 Cells(58 3) VCEBL1 Cells(59 3) VCNBT2 Cells(54 6) VCNBL2 Cells(55 6) VCSBT2 Cells(58 6) VCWBL2 Cells(59 6) Intvc Cells(59 10) Sheets("Color Coded"). Cells(7 PropLeft 1 (((VolumeCase - 1) * 11) (RampCase * 2))) VCNBT1 Sheets("Color Coded"). Cells(14 PropLeft 1 (((VolumeCase - 1) * 11) (RampCase * 2))) VCSBT1 Sheets("Color Coded"). Cells(21 PropLeft 1 (((VolumeCase - 1) * 11) (RampCase * 2))) VCSBL1 Sheets("Color Coded"). Cells(28 PropLeft 1 (((VolumeCase - 1) * 11) (RampCase * 2))) VCEBL1 Sheets("Color Coded"). Cells(35 PropLeft 1 (((VolumeCase - 1) * 11) (RampCase * 2))) VCNBT2 Sheets("Color Coded"). Cells(42 PropLeft 1 (((VolumeCase - 1) * 11) (RampCase * 2))) VCNBL2 Sheets("Color Coded"). Cells(49 PropLeft 1 (((VolumeCase - 1) * 11) (RampCase * 2))) VCSBT2 Sheets("Color Coded"). Cells(56 PropLeft 1 (((VolumeCase - 1) * 11) (RampCase * 2))) VCWBL2 Sheets("Color Coded"). Cells(63 PropLeft 1 (((VolumeCase - 1) * 11) (RampCase * 2))) Intvc Next PropLeft End If Next RampCase Next VolumeCase End Sub
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Operating Performance of Diverging Diamond Interchanges
APPENDIX D. MICROSOFT VISUAL STUDIO VISUAL BASIC SCRIPTS
This appendix provides the VB script in Microsoft Visual Studio that automates the
procedure for inputting and assigning variables and collecting and relocating output files
from the VISSIM simulation study. This script allows the user to collect the necessary
output files from the VISSIM simulation with varying traffic scenarios and lane
configurations without having to manually open and run individual input files.
Imports System. Text Imports System. Convert Imports System. Math Imports System Imports System. IO Imports System. Threading
Imports VISSIM_COMSERVERLib Module Module1
Dim vissim As Vissim Dim net As Net Dim simulation As Simulation Dim vehicles As Vehicles Dim vehicle As Vehicle Dim links As Links Dim link As Link Dim evaluation As Evaluation Dim vehinps As VehicleInputs Dim decisions As RoutingDecisions Dim decision As RoutingDecision Dim JC As Integer Dim Off As Integer Dim m As Integer Dim simtime 4500 Dim resolution 10 Sub Main()
set groups of arrays that contain vehicle inputs Dim vehinp1() As Integer New Integer() 1500 2100 2500 Jimmy Carter NB1 Dim vehinp2() As Integer New Integer() 1500 2100 2500 Jimmy Carter SB2 Dim vehinp3() As Integer New Integer() 500 1100 1800 I-85 off-ramp NB Dim vehinp4() As Integer New Integer() 500 1100 1800 I-85 off-ramp SB
set groups of arrays that contain different route decisions Dim decision1_1() As Double New Double() 0. 8 0. 72 0. 56 0. 4 0. 24 0. 08 0 NBT2
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Operating Performance of Diverging Diamond Interchanges

Dim decision1_2() As Double New Double() 0 0. 08 0. 24 0. 4 0. 56 0. 72 0. 8 NBL2
Dim decision1_3() As Double New Double() 0. 2 NBR1 Dim decision2_1() As Double New Double() 0. 8 0. 72 0. 56 0. 4 0. 24 0. 08 0 SBT1 Dim decision2_2() As Double New Double() 0 0. 08 0. 24 0. 4 0. 56 0. 72 0. 8 SBL1 Dim decision2_3() As Double New Double() 0. 2 SBR2 Dim decision3_1() As Double New Double() 0. 5 EBL1 Dim decision3_2() As Double New Double() 0. 5 EBR1 Dim decision4_1() As Double New Double() 0. 5 WBL2 Dim decision4_2() As Double New Double() 0. 5 WBR2

For l As Integer 1 To 3 For loop for lane configuration

For-loop to insert desired routing decision into the model JC 0 counter for Jimmy Carter volumes

ratios 3 2500)

For-loop to run through different traffic volumes and turn movement For i As Integer 1 To 3 For loop for JC volumes (1 1500 2 2100

Off 0 counter for Off-ramp volumes

For j As Integer 1 To 3 For loop for Off-ramp volumes (1 500 2 1100 3 1800)

m 0 counter for route decisions

For k As Integer 1 To 7 7 different turning movement proportions (1 100/0 2 90/10 3 70/30 4 50/50 5 30/70 6 10/90 7 0 100)

For n As Integer 1 To 2

Initializing a new instance of Vissim vissim New Vissim

If n 1 Then running DDI models loading Vissim network model ". inp" file and ".
ini" file for offset test this is to call DDI files vissim. LoadNet("C Users spark365 Documents Sung
Jun Park Research DDI After DDI Final VISSIM LC" & l & " After " & i & "_" & j & " DDI_PM_" & k & ". inp")
vissim. LoadLayout("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " After " & i & "_" & j & " vissim. ini")

you may minimize the VISSIM window if you want vissim. ShowMinimized()

variable

initiate route decision and vehicle input
Dim vehinps vissim. Net. VehicleInputs Dim decisions vissim. Net. RoutingDecisions

initiate vehicle nput for each approach

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Operating Performance of Diverging Diamond Interchanges

Dim vehinpNB vissim. Net. VehicleInputs. GetVehicleInputByNumber(26) number in the bracket is link/connector number in VISSIM
Dim vehinpSB vissim. Net. VehicleInputs. GetVehicleInputByNumber(1)
Dim vehinpNBRamp vissim. Net. VehicleInputs. GetVehicleInputByNumber(10)
Dim vehinpSBRamp vissim. Net. VehicleInputs. GetVehicleInputByNumber(24)

initiate route decisions for each approach Dim decisionNB decisions. GetRoutingDecisionByNumber(1) number in the bracket is route decision number in VISSIM Dim decisionSB decisions. GetRoutingDecisionByNumber(2) Dim decisionNBR decisions. GetRoutingDecisionByNumber(3) Dim decisionSBR decisions. GetRoutingDecisionByNumber(4)

add vehicle input from desired vehicle input group for each time frame
vehinpNB vehinps. AddVehicleInput(26 0 4500) vehinps. AddVehincleInput(link/connector start time end time)
vehinpNB. AttValue("Volume") vehinp1(JC) this calls the first number from the array of vehinp1 (the first number in the array is 0th position)
vehinpNB. AttValue("TrafficComposition") 1 1 for Default 2 for DDI (currently no difference between the two)

vehinpSB vehinps. AddVehicleInput(1 0 4500) vehinpSB. AttValue("Volume") vehinp2(JC) vehinpSB. AttValue("TrafficComposition") 1

4500)

vehinpNBRamp vehinps. AddVehicleInput(10 0
vehinpNBRamp. AttValue("Volume") vehinp3(Off) vehinpNBRamp. AttValue("TrafficComposition") 1

4500)

vehinpSBRamp vehinps. AddVehicleInput(24 0
vehinpSBRamp. AttValue("Volume") vehinp4(Off) vehinpSBRamp. AttValue("TrafficComposition") 1

add route decision from desired route decision group for each time frame
DDI NB decisionNB. AttValue2("RelativeFlow" 1 4500) decision1_1(m) decisionX. AttValue2("RelativeFlow Decision end time) decision1_X(position of proportion that you want to call) decisionNB. AttValue2("RelativeFlow" 2 4500) decision1_2(m) decisionNB. AttValue2("RelativeFlow" 3 4500) decision1_3(0) DDI SB decisionSB. AttValue2("RelativeFlow" 1 4500) decision2_1(m)

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Operating Performance of Diverging Diamond Interchanges

decision2_2(m) decision2_3(0)
decision3_1(0) decision3_2(0)
decision4_1(0) decision4_2(0)

decisionSB. AttValue2("RelativeFlow" 2 4500)
decisionSB. AttValue2("RelativeFlow" 3 4500)
NB Ramp decisionNBR. AttValue2("RelativeFlow" 1 4500)
decisionNBR. AttValue2("RelativeFlow" 2 4500)
SB Ramp decisionSBR. AttValue2("RelativeFlow" 1 4500)
decisionSBR. AttValue2("RelativeFlow" 2 4500)

Dim randseed 1 this allows you to change random seed in VISSIM in each run and thus you get some variable flows in each run

For randcount 1 To 10 number of runs for a particular traffic volume and route decision combinations with different seeds in each run

activating evaluation tools in the file evaluation vissim. Evaluation evaluation. AttValue("traveltime") True evaluation. AttValue("delay") True evaluation. AttValue("datacollection") True evaluation. AttValue("queuecounter") True evaluation. AttValue("vehiclerecord") True

assigning simulation propoerties simulation vissim. Simulation simulation. Period simtime simulation. Resolution resolution simulation. RandomSeed randseed simulation. RunContinuous()

Thread. Sleep(5000)

rename and move output files into separate folder
relocate output file - Data Collection Raw(. mer) Data Collection Compiled(. mes) Delay Raw(. vlr) Delay Compiled(. vlz) Travel Time Raw(. rsr) Travel Time Compiled(. rsz) and Error files(. err)
for DDI model My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " After " & i & "_" & j & " DDI_PM_" & k & ". mer" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " After dc raw volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True) My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " After " & i & "_" & j & " DDI_PM_" & k & ". mes" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " After dc comp volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)

D-4

Operating Performance of Diverging Diamond Interchanges

My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " After " & i & "_" & j & " DDI_PM_" & k & ". vlr" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " After delay raw volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " After " & i & "_" & j & " DDI_PM_" & k & ". vlz" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " After delay comp volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " After " & i & "_" & j & " DDI_PM_" & k & ". rsr" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " After tt raw volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " After " & i & "_" & j & " DDI_PM_" & k & ". rsz" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " After tt comp volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " After " & i & "_" & j & " DDI_PM_" & k & ". stz" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " After queue volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " After " & i & "_" & j & " DDI_PM_" & k & ". fzp" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " After vr volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)

seed after each run

randseed randseed 11 add 11 to random

Next vissim. Exit() exit currently opened VISSIM file

ElseIf n 2 Then running CDI models this is to call CDI files vissim. LoadNet("C Users spark365 Documents Sung
Jun Park Research DDI After DDI Final VISSIM LC" & l & " Before " & i & "_" & j & " Before_PM_" & k & ". inp")
vissim. LoadLayout("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " Before " & i & "_" & j & " vissim. ini")

you may minimize the VISSIM window if you want vissim. ShowMinimized()

variable

initiate route decision and vehicle input Dim vehinps vissim. Net. VehicleInputs

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Operating Performance of Diverging Diamond Interchanges

Dim decisions vissim. Net. RoutingDecisions

initiate vehicle nput for each approach Dim vehinpNB vissim. Net. VehicleInputs. GetVehicleInputByNumber(26) number in the bracket is link/connector number in VISSIM Dim vehinpSB vissim. Net. VehicleInputs. GetVehicleInputByNumber(1) Dim vehinpNBRamp vissim. Net. VehicleInputs. GetVehicleInputByNumber(10) Dim vehinpSBRamp vissim. Net. VehicleInputs. GetVehicleInputByNumber(24)

initiate route decisions for each approach Dim decisionNB decisions. GetRoutingDecisionByNumber(1) number in the bracket is route decision number in VISSIM Dim decisionSB decisions. GetRoutingDecisionByNumber(2) Dim decisionNBR decisions. GetRoutingDecisionByNumber(3) Dim decisionSBR decisions. GetRoutingDecisionByNumber(4)

add vehicle input from desired vehicle input group for each time frame
vehinpNB vehinps. AddVehicleInput(26 0 4500) vehinps. AddVehincleInput(link/connector start time end time)
vehinpNB. AttValue("Volume") vehinp1(JC) this calls the first number from the array of vehinp1 (the first number in the array is 0th position)
vehinpNB. AttValue("TrafficComposition") 1 1 for Default 2 for DDI (currently no difference between the two)

vehinpSB vehinps. AddVehicleInput(1 0 4500) vehinpSB. AttValue("Volume") vehinp2(JC) vehinpSB. AttValue("TrafficComposition") 1

4500)

vehinpNBRamp vehinps. AddVehicleInput(10 0
vehinpNBRamp. AttValue("Volume") vehinp3(Off) vehinpNBRamp. AttValue("TrafficComposition") 1

4500)

vehinpSBRamp vehinps. AddVehicleInput(24 0
vehinpSBRamp. AttValue("Volume") vehinp4(Off) vehinpSBRamp. AttValue("TrafficComposition") 1

add route decision from desired route decision group for each time frame
DDI NB decisionNB. AttValue2("RelativeFlow" 1 4500) decision1_1(m) decisionX. AttValue2("RelativeFlow Decision end time) decision1_X(position of proportion that you want to call) decisionNB. AttValue2("RelativeFlow" 2 4500) decision1_2(m) decisionNB. AttValue2("RelativeFlow" 3 4500) decision1_3(0)

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Operating Performance of Diverging Diamond Interchanges

decision2_1(m) decision2_2(m) decision2_3(0)
decision3_1(0) decision3_2(0)
decision4_1(0) decision4_2(0)

DDI SB decisionSB. AttValue2("RelativeFlow" 1 4500)
decisionSB. AttValue2("RelativeFlow" 2 4500)
decisionSB. AttValue2("RelativeFlow" 3 4500)
NB Ramp decisionNBR. AttValue2("RelativeFlow" 1 4500)
decisionNBR. AttValue2("RelativeFlow" 2 4500)
SB Ramp decisionSBR. AttValue2("RelativeFlow" 1 4500)
decisionSBR. AttValue2("RelativeFlow" 2 4500)

Dim randseed 1 this allows you to change random seed in VISSIM in each run and thus you get some variable flows in each run

For randcount 1 To 10 number of runs for a particular traffic volume and route decision combinations with different seeds in each run

activating evaluation tools in the file evaluation vissim. Evaluation evaluation. AttValue("traveltime") True evaluation. AttValue("delay") True evaluation. AttValue("datacollection") True evaluation. AttValue("queuecounter") True evaluation. AttValue("vehiclerecord") True

assigning simulation propoerties simulation vissim. Simulation simulation. Period simtime simulation. Resolution resolution simulation. RandomSeed randseed simulation. RunContinuous()

Thread. Sleep(5000)

rename and move output files into separate folder
relocate output file - Data Collection Raw(. mer) Data Collection Compiled(. mes) Delay Raw(. vlr) Delay Compiled(. vlz) Travel Time Raw(. rsr) Travel Time Compiled(. rsz) and Error files(. err)
for CDI model My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " Before " & i & "_" & j & " Before_PM_" & k & ". mer" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " Before dc raw volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True) My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " Before " & i & "_" & j & " Before_PM_" & k & ". mes" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" &

D-7

Operating Performance of Diverging Diamond Interchanges

l & " Before dc comp volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " Before " & i & "_" & j & " Before_PM_" & k & ". vlr" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " Before delay raw volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " Before " & i & "_" & j & " Before_PM_" & k & ". vlz" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " Before delay comp volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " Before " & i & "_" & j & " Before_PM_" & k & ". rsr" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " Before tt raw volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " Before " & i & "_" & j & " Before_PM_" & k & ". rsz" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " Before tt comp volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " Before " & i & "_" & j & " Before_PM_" & k & ". stz" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " Before queue volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)
My. Computer. FileSystem. CopyFile("C Users spark365 Documents Sung Jun Park Research DDI After DDI Final VISSIM LC" & l & " Before " & i & "_" & j & " Before_PM_" & k & ". fzp" "C Users spark365 Documents Sung Jun Park Research DDI After DDI Final Data LC" & l & " Before vr volume" & i & "_" & j & " proportion" & k & " run" & randcount & ". txt" True)

seed after each run

randseed randseed 11 add 11 to random

Next vissim. Exit() exit currently opened VISSIM file

End If

Next m m 1 add 1 to move to next routing proportion

Next Off Off 1 add 1 to move to next off-ramp volume

Next JC JC 1 add 1 to move to next JC volume

Next

D-8

Next End Sub
End Module

Operating Performance of Diverging Diamond Interchanges

D-9

Operating Performance of Diverging Diamond Interchanges
APPENDIX E. CRITICAL LANE VOLUME ANALYSIS RESULTS List of Tables
Table E - 1 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1000 vph and (b) cross-street demand of 1500 vph with different off-ramp demands and through/left proportions for LC1 .E-7
Table E - 2 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1800 vph and (b) cross-street demand of 2100 vph with different off-ramp demands and through/left proportions for LC1 .E-8
Table E - 3 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2300 vph with different off-ramp demands and through/left proportions for LC1 .............................................................................E-9
Table E - 4 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2500 vph with different off-ramp demands and through/left proportions for LC1 ...........................................................................E-10
Table E - 5 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street volume of 2700 vph with different off-ramp demands and through/left proportions for LC1 ...........................................................................E-11
Table E - 6 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1000 vph and (b) cross-street demand of 1500 vph with different off-ramp demands and through/left proportions for LC2E-18
E-1

Operating Performance of Diverging Diamond Interchanges Table E - 7 Color-coded tables of the CDI and DDI turning movement and interchange
v/c ratios at (a) cross-street demand of 1800 vph and (b) cross-street demand of 2100 vph with different off-ramp demands and through/left proportions for LC2E-19 Table E - 8 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2300 vph with different off-ramp demands and through/left proportions for LC2 ...........................................................................E-20 Table E - 9 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2500 vph with different off-ramp demands and through/left proportions for LC2 ...........................................................................E-21 Table E - 10 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2700 vph with different off-ramp demands and through/left proportions for LC2 ...........................................................................E-22 Table E - 11 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1000 vph and (b) cross-street demand of 1500 vph with different off-ramp demands and through/left proportions for LC3E-29 Table E - 12 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1800 vph and (b) cross-street demand of 2100 vph with different off-ramp demands and through/left proportions for LC3E-30 Table E - 13 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2300 vph with different off-ramp demands and through/left proportions for LC3 ...........................................................................E-31
E-2

Operating Performance of Diverging Diamond Interchanges Table E - 14 Color-coded tables of the CDI and DDI turning movement and interchange
v/c ratios at cross-street demand of 2500 vph with different off-ramp demands and through/left proportions for LC3 ...........................................................................E-32 Table E - 15 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2700 vph with different off-ramp demands and through/left proportions for LC3 ...........................................................................E-33
List of Figures
Figure E - 1 Difference in v/c ratios between CDI and DDI on NBT1 at different traffic demands and through/left proportions for LC1 .....................................................E-12
Figure E - 2 Difference in v/c ratios between CDI and DDI on SBT1 at different traffic demands and through/left proportions for LC1 .....................................................E-13
Figure E - 3 Difference in v/c ratios between CDI and DDI on SBL1 at different traffic demands and through/left proportions for LC1 .....................................................E-13
Figure E - 4 Difference in v/c ratios between CDI and DDI on EBL1 at different traffic demands and through/left proportions for LC1 .....................................................E-14
Figure E - 5 Difference in v/c ratios between CDI and DDI on NBT2 at different traffic demands and through/left proportions for LC1 .....................................................E-14
Figure E - 6 Difference in v/c ratios between CDI and DDI on NBL2 at different traffic demands and through/left proportions for LC1 .....................................................E-15
Figure E - 7 Difference in v/c ratios between CDI and DDI on SBT2 at different traffic demands and through/left proportions for LC1 .....................................................E-15 E-3

Operating Performance of Diverging Diamond Interchanges
Figure E - 8 Difference in v/c ratios between CDI and DDI on WBL2 at different traffic demands and through/left proportions for LC1 .....................................................E-16
Figure E - 9 Difference in v/c ratios between CDI and DDI on NBT1 at different traffic demands and through/left proportions for LC2 .....................................................E-23
Figure E - 10 Difference in v/c ratios between CDI and DDI on SBT1 at different traffic demands and through/left proportions for LC2 .....................................................E-24
Figure E - 11 Difference in v/c ratios between CDI and DDI on SBL1 at different traffic demands and through/left proportions for LC2 .....................................................E-24
Figure E - 12 Difference in v/c ratios between CDI and DDI on EBL1 at different traffic demands and through/left proportions for LC2 .....................................................E-25
Figure E - 13 Difference in v/c ratios between CDI and DDI on NBT2 at different traffic demands and through/left proportions for LC2 .....................................................E-25
Figure E - 14 Difference in v/c ratios between CDI and DDI on NBL2 at different traffic demands and through/left proportions for LC2 .....................................................E-26
Figure E - 15 Difference in v/c ratios between CDI and DDI on SBT2 at different traffic demands and through/left proportions for LC2 .....................................................E-26
Figure E - 16 Difference in v/c ratios between CDI and DDI on WBL2 at different traffic demands and through/left proportions for LC2 .....................................................E-27
Figure E - 17 Difference in v/c ratios between CDI and DDI on NBT1 at different traffic demands and through/left proportions for LC3 .....................................................E-34
Figure E - 18 Difference in v/c ratios between CDI and DDI on SBT1 at different traffic demands and through/left proportions for LC3 .....................................................E-35
E-4

Operating Performance of Diverging Diamond Interchanges Figure E - 19 Difference in v/c ratios between CDI and DDI on SBL1 at different traffic
demands and through/left proportions for LC3 .....................................................E-35 Figure E - 20 Difference in v/c ratios between CDI and DDI on EBL1 at different traffic
demands and through/left proportions for LC3 .....................................................E-36 Figure E - 21 Difference in v/c ratios between CDI and DDI on NBT2 at different traffic
demands and through/left proportions for LC3 .....................................................E-36 Figure E - 22 Difference in v/c ratios between CDI and DDI on NBL2 at different traffic
demands and through/left proportions for LC3 .....................................................E-37 Figure E - 23 Difference in v/c ratios between CDI and DDI on SBT2 at different traffic
demands and through/left proportions for LC3 .....................................................E-37 Figure E - 24 Difference in v/c ratios between CDI and DDI on WBL2 at different traffic
demands and through/left proportions for LC3 .....................................................E-38
E-5

Operating Performance of Diverging Diamond Interchanges

This appendix provides the resultant color-coded tables and plots showing the difference in the CDI and DDI v/c ratios at different through/left proportions traffic demands and lane configurations.

E.1 E.1.1

Lane Configuration 1 Color-Coded Tables of CDI and DDI v/c Ratios

The following color-coded tables show the comparison of the CDI and DDI v/c ratios calculated using the CLV method for LC1. The color schematics of these tables are described in Table 6 in Chapter 3.

E-6

Operating Performance of Diverging Diamond Interchanges

Table E - 1 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1000 vph and (b) cross-street demand of 1500 vph with different off-ramp demands and through/left proportions
for LC1

(a)

(b)

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 1000 vph

CDI DDI CDI DDI

200 vph

500 vph

0.28 0.56 0.33 0.60

0.50 0.49 0.51 0.54

0.50 0.35 0.50 0.39

0.37 0.32 0.41 0.35

0.65 0.30 0.60 0.33

0.84 0.36 0.90 0.39

1.00 0.38 1.07 0.42

0.32 0.44 0.44 0.51

0.31 0.42 0.39 0.47

0.24 0.37 0.31 0.44

0.16 0.31 0.23 0.37

0.11 0.24 0.17 0.31

0.06 0.14 0.11 0.23

0.03 0.08 0.08 0.18

0.00 0.00 0.00 0.00

0.18 0.02 0.20 0.02

0.35 0.06 0.40 0.06

0.45 0.10 0.48 0.10

0.58 0.14 0.65 0.14

0.55 0.18 0.53 0.18

0.52 0.20 0.50 0.20

0.13 0.05 0.26 0.12

0.14 0.05 0.25 0.12

0.18 0.06 0.35 0.14

0.22 0.06 0.36 0.14

0.25 0.07 0.47 0.16

0.35 0.08 0.55 0.17

0.33 0.08 0.56 0.18

0.32 0.43 0.44 0.49

0.31 0.41 0.39 0.47

0.24 0.35 0.32 0.42

0.17 0.30 0.24 0.35

0.11 0.22 0.18 0.29

0.06 0.13 0.12 0.22

0.03 0.08 0.08 0.17

0.00 0.00 0.00 0.00

0.13 0.02 0.13 0.02

0.25 0.06 0.27 0.06

0.32 0.10 0.35 0.10

0.40 0.14 0.42 0.14

0.45 0.18 0.48 0.18

0.43 0.20 0.45 0.20

0.28 0.58 0.33 0.63

0.43 0.51 0.45 0.54

0.37 0.37 0.41 0.41

0.54 0.33 0.58 0.37

0.84 0.32 0.99 0.35

1.15 0.38 1.26 0.41

1.28 0.40 1.39 0.43

0.13 0.05 0.26 0.12

0.14 0.05 0.25 0.12

0.18 0.05 0.31 0.13

0.18 0.06 0.31 0.16

0.21 0.07 0.34 0.15

0.22 0.07 0.36 0.14

0.25 0.08 0.38 0.17

0.28 0.48 0.39 0.53

0.32 0.44 0.35 0.49

0.38 0.35 0.42 0.41

0.39 0.31 0.44 0.35

0.56 0.27 0.60 0.31

0.68 0.27 0.73 0.31

0.72 0.27 0.75 0.31

CDI DDI 800 vph
0.34 0.63 0.56 0.57 0.54 0.41 0.43 0.37 0.70 0.37 1.05 0.43 1.07 0.45 0.52 0.56 0.48 0.53 0.39 0.50 0.30 0.43 0.23 0.36 0.17 0.30 0.13 0.26 0.00 0.00 0.22 0.02 0.43 0.06 0.55 0.10 0.63 0.14 0.53 0.18 0.49 0.20 0.38 0.19 0.38 0.19 0.45 0.21 0.50 0.22 0.54 0.23 0.58 0.25 0.67 0.26 0.52 0.55 0.48 0.51 0.40 0.48 0.32 0.42 0.24 0.35 0.18 0.29 0.15 0.24 0.00 0.00 0.17 0.02 0.30 0.06 0.40 0.10 0.45 0.14 0.48 0.18 0.48 0.20 0.34 0.67 0.47 0.60 0.44 0.44 0.67 0.39 0.98 0.39 1.33 0.45 1.52 0.50 0.38 0.18 0.38 0.18 0.42 0.20 0.40 0.21 0.44 0.22 0.47 0.24 0.47 0.24 0.48 0.58 0.45 0.53 0.47 0.45 0.50 0.40 0.63 0.36 0.75 0.36 0.80 0.36

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 1500 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.44

0.88

0.47 0.97

0.70

0.76

0.77 0.84

0.70

0.54

0.74 0.62

0.55

0.48

0.62 0.55

0.90

0.48

0.95 0.55

1.25

0.56

1.35 0.64

1.50

0.60

1.60 0.68

0.53

0.69

0.69 0.70

0.50

0.65

0.66 0.66

0.39

0.56

0.55 0.63

0.28

0.49

0.42 0.59

0.19

0.40

0.31 0.52

0.11

0.27

0.21 0.42

0.07

0.20

0.17 0.36

0.00

0.00

0.00 0.00

0.28

0.03

0.30 0.03

0.56

0.09

0.64 0.09

0.70

0.15

0.78 0.15

0.65

0.21

0.63 0.21

0.53

0.27

0.51 0.27

0.49

0.30

0.48 0.30

0.34

0.12

0.59 0.23

0.31

0.12

0.55 0.22

0.45

0.13

0.59 0.25

0.49

0.14

0.69 0.28

0.56

0.16

0.76 0.31

0.74

0.18

0.88 0.34

0.74

0.20

0.92 0.36

0.53

0.67

0.69 0.72

0.50

0.63

0.66 0.66

0.40

0.55

0.56 0.63

0.29

0.47

0.44 0.58

0.20

0.38

0.33 0.52

0.11

0.26

0.23 0.40

0.08

0.18

0.18 0.34

0.00

0.00

0.00 0.00

0.20

0.03

0.23 0.03

0.41

0.09

0.45 0.09

0.50

0.15

0.58 0.15

0.57

0.21

0.64 0.21

0.47

0.27

0.48 0.27

0.41

0.30

0.42 0.30

0.44

0.91

0.47 1.00

0.60

0.79

0.65 0.84

0.55

0.57

0.60 0.62

0.81

0.50

0.88 0.57

1.18

0.50

1.31 0.55

1.60

0.59

1.80 0.68

1.86

0.63

2.04 0.71

0.34

0.12

0.59 0.23

0.31

0.12

0.55 0.22

0.39

0.13

0.55 0.25

0.40

0.14

0.60 0.28

0.43

0.16

0.60 0.31

0.48

0.17

0.64 0.33

0.51

0.18

0.67 0.34

0.49

0.75

0.66 0.80

0.46

0.68

0.63 0.72

0.60

0.54

0.66 0.62

0.62

0.48

0.71 0.56

0.80

0.43

0.87 0.52

0.89

0.43

0.95 0.52

0.94

0.43

0.99 0.52

CDI

DDI

1800 vph

0.48 1.06

0.68 0.92

0.80 0.66

0.68 0.64

1.05 0.57

1.48 0.70

1.76 0.72

0.83 0.75

0.81 0.78

0.76 0.69

0.60 0.67

0.47 0.63

0.35 0.55

0.31 0.49

0.00 0.00

0.36 0.03

0.69 0.09

0.81 0.15

0.61 0.21

0.51 0.27

0.45 0.30

0.78 0.35

0.75 0.35

0.69 0.36

0.78 0.40

0.88 0.45

0.98 0.48

1.03 0.49

0.83 0.75

0.81 0.76

0.76 0.68

0.64 0.67

0.51 0.60

0.39 0.53

0.31 0.45

0.00 0.00

0.27 0.03

0.51 0.09

0.63 0.15

0.63 0.21

0.48 0.27

0.42 0.30

0.48 1.13

0.59 0.98

0.60 0.69

0.97 0.64

1.49 0.61

1.95 0.74

2.32 0.81

0.78 0.34

0.75 0.34

0.69 0.35

0.68 0.40

0.73 0.43

0.77 0.47

0.78 0.45

0.82 0.85

0.79 0.82

0.73 0.68

0.77 0.65

0.94 0.59

1.01 0.61

1.06 0.59

E-7

Operating Performance of Diverging Diamond Interchanges

Table E - 2 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1800 vph and (b) cross-street demand of 2100 vph with different off-ramp demands and through/left proportions
for LC1

(a)

(b)

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 1800 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.51 1.03

0.52

1.11

0.85 0.91

0.84

0.97

0.76 0.63

0.84

0.70

0.65 0.56

0.68

0.62

0.99 0.54

1.08

0.60

1.47 0.65

1.62

0.72

1.75 0.69

1.87

0.77

0.60 0.67

0.72

0.72

0.57 0.71

0.70

0.78

0.43 0.63

0.58

0.71

0.30 0.55

0.43

0.62

0.20 0.44

0.31

0.57

0.11 0.31

0.22

0.43

0.07 0.21

0.17

0.36

0.00 0.00

0.00

0.00

0.31 0.04

0.34

0.04

0.65 0.11

0.69

0.11

0.75 0.18

0.85

0.18

0.64 0.25

0.64

0.25

0.54 0.32

0.52

0.32

0.49 0.36

0.48

0.36

0.38 0.11

0.65

0.23

0.34 0.11

0.60

0.24

0.47 0.13

0.64

0.25

0.56 0.14

0.77

0.27

0.74 0.16

0.86

0.32

0.85 0.20

0.98

0.34

0.91 0.21

1.07

0.36

0.60 0.68

0.72

0.72

0.57 0.71

0.70

0.80

0.44 0.62

0.59

0.70

0.31 0.53

0.45

0.62

0.21 0.43

0.33

0.55

0.12 0.29

0.23

0.42

0.07 0.20

0.16

0.34

0.00 0.00

0.00

0.00

0.24 0.04

0.25

0.04

0.46 0.11

0.54

0.11

0.56 0.18

0.65

0.18

0.63 0.25

0.62

0.25

0.45 0.32

0.46

0.32

0.40 0.36

0.42

0.36

0.51 1.05

0.52

1.14

0.69 0.91

0.71

1.01

0.60 0.65

0.63

0.72

0.88 0.58

0.95

0.62

1.31 0.56

1.43

0.63

1.83 0.68

2.03

0.75

2.13 0.72

2.40

0.80

0.38 0.11

0.65

0.22

0.34 0.11

0.60

0.24

0.42 0.12

0.60

0.25

0.47 0.14

0.65

0.27

0.51 0.16

0.67

0.31

0.59 0.18

0.74

0.33

0.63 0.20

0.77

0.34

0.56 0.81

0.71

0.86

0.57 0.78

0.68

0.86

0.66 0.62

0.73

0.70

0.70 0.54

0.78

0.61

0.90 0.49

0.94

0.57

1.00 0.50

1.06

0.57

1.06 0.50

1.14

0.57

CDI

DDI

1800 vph

0.54 1.25

0.77 1.08

0.91 0.78

0.76 0.70

1.17 0.67

1.72 0.78

2.03 0.84

0.87 0.75

0.86 0.78

0.78 0.80

0.61 0.73

0.47 0.65

0.35 0.57

0.29 0.51

0.00 0.00

0.40 0.04

0.75 0.11

0.82 0.18

0.64 0.25

0.52 0.32

0.48 0.36

0.84 0.34

0.80 0.35

0.75 0.38

0.85 0.41

1.01 0.44

1.13 0.49

1.19 0.51

0.87 0.75

0.86 0.78

0.78 0.78

0.65 0.73

0.48 0.63

0.33 0.54

0.25 0.48

0.00 0.00

0.30 0.04

0.61 0.11

0.71 0.18

0.65 0.25

0.48 0.32

0.42 0.36

0.54 1.27

0.68 1.10

0.65 0.80

1.07 0.70

1.60 0.70

2.20 0.84

2.54 0.90

0.84 0.34

0.80 0.35

0.75 0.37

0.75 0.41

0.81 0.43

0.87 0.46

0.90 0.48

0.86 0.90

0.84 0.88

0.77 0.78

0.86 0.71

1.03 0.65

1.13 0.66

1.19 0.66

Proportion Approach

100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2100 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.57

1.20 0.58 1.26

0.95

1.01 0.85 1.09

0.84

0.72 0.91 0.80

0.72

0.63 0.75 0.70

1.15

0.61 1.25 0.69

1.72

0.73 1.84 0.81

2.04

0.78 2.22 0.84

0.65

0.67 0.77 0.73

0.65

0.75 0.75 0.77

0.46

0.69 0.61 0.77

0.33

0.60 0.45 0.71

0.22

0.49 0.33 0.60

0.12

0.35 0.22 0.47

0.07

0.22 0.16 0.39

0.00

0.00 0.00 0.00

0.42

0.04 0.45 0.04

0.67

0.13 0.73 0.13

0.84

0.21 0.82 0.21

0.64

0.29 0.65 0.29

0.55

0.38 0.52 0.38

0.49

0.42 0.49 0.42

0.44

0.11 0.69 0.22

0.39

0.11 0.69 0.23

0.50

0.12 0.69 0.24

0.63

0.14 0.83 0.28

0.83

0.16 0.96 0.31

0.94

0.21 1.13 0.36

1.02

0.22 1.18 0.39

0.65

0.67 0.77 0.73

0.65

0.75 0.77 0.77

0.47

0.68 0.63 0.76

0.34

0.60 0.47 0.70

0.22

0.47 0.34 0.60

0.12

0.33 0.20 0.45

0.07

0.21 0.14 0.38

0.00

0.00 0.00 0.00

0.30

0.04 0.37 0.04

0.50

0.13 0.60 0.13

0.62

0.21 0.68 0.21

0.58

0.29 0.60 0.29

0.45

0.38 0.45 0.38

0.39

0.42 0.39 0.42

0.57

1.20 0.58 1.28

0.82

1.03 0.76 1.11

0.64

0.74 0.68 0.81

0.96

0.63 1.03 0.72

1.47

0.62 1.61 0.69

2.06

0.76 2.27 0.84

2.44

0.81 2.61 0.87

0.44

0.11 0.69 0.22

0.39

0.11 0.64 0.23

0.45

0.12 0.62 0.24

0.53

0.14 0.67 0.28

0.59

0.16 0.77 0.31

0.72

0.20 0.83 0.34

0.70

0.21 0.88 0.38

0.62

0.86 0.75 0.91

0.69

0.85 0.74 0.89

0.72

0.70 0.79 0.77

0.78

0.61 0.83 0.70

0.97

0.54 1.04 0.63

1.12

0.57 1.17 0.64

1.18

0.57 1.24 0.64

CDI

DDI

1800 vph

0.60 1.37

0.81 1.19

0.98 0.87

0.81 0.76

1.32 0.74

2.00 0.86

2.36 0.93

0.92 0.79

0.89 0.82

0.80 0.85

0.61 0.78

0.47 0.68

0.35 0.59

0.29 0.51

0.00 0.00

0.45 0.04

0.82 0.13

0.81 0.21

0.63 0.29

0.51 0.38

0.47 0.42

0.88 0.35

0.84 0.36

0.80 0.37

0.93 0.40

1.09 0.43

1.23 0.50

1.31 0.51

0.92 0.79

0.89 0.82

0.82 0.84

0.65 0.77

0.46 0.67

0.30 0.58

0.22 0.51

0.00 0.00

0.39 0.04

0.66 0.13

0.76 0.21

0.62 0.29

0.45 0.38

0.41 0.42

0.60 1.40

0.69 1.22

0.72 0.88

1.15 0.78

1.76 0.75

2.52 0.89

2.91 0.93

0.88 0.35

0.84 0.35

0.77 0.36

0.78 0.40

0.86 0.43

0.94 0.49

0.99 0.51

0.91 0.98

0.87 0.95

0.87 0.85

0.92 0.77

1.10 0.70

1.24 0.72

1.32 0.72

E-8

Operating Performance of Diverging Diamond Interchanges

Table E - 3 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2300 vph with different off-ramp
demands and through/left proportions for LC1

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2300 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.59 1.27 0.62 1.38

0.88 1.10 0.86 1.18

0.89 0.78 0.95 0.84

0.75 0.67 0.81 0.75

1.24 0.66 1.35 0.71

1.86 0.78 2.01 0.83

2.18 0.82 2.30 0.89

0.67 0.68 0.81 0.73

0.64 0.73 0.76 0.77

0.49 0.75 0.63 0.81

0.34 0.63 0.47 0.74

0.23 0.52 0.34 0.62

0.12 0.34 0.22 0.49

0.07 0.24 0.16 0.39

0.00 0.00 0.00 0.00

0.43 0.05 0.44 0.05

0.74 0.14 0.79 0.14

0.82 0.23 0.84 0.23

0.65 0.32 0.63 0.32

0.54 0.41 0.53 0.41

0.50 0.46 0.49 0.46

0.47 0.11 0.72 0.22

0.44 0.11 0.69 0.23

0.56 0.12 0.72 0.24

0.74 0.13 0.89 0.28

0.89 0.16 1.03 0.31

1.02 0.20 1.18 0.37

1.02 0.24 1.24 0.39

0.67 0.68 0.81 0.73

0.64 0.73 0.76 0.78

0.50 0.74 0.65 0.81

0.36 0.62 0.49 0.72

0.23 0.50 0.34 0.60

0.12 0.33 0.20 0.48

0.07 0.22 0.13 0.39

0.00 0.00 0.00 0.00

0.36 0.05 0.36 0.05

0.55 0.14 0.63 0.14

0.66 0.23 0.75 0.23

0.58 0.32 0.58 0.32

0.44 0.41 0.44 0.41

0.40 0.46 0.41 0.46

0.59 1.29 0.62 1.40

0.74 1.12 0.73 1.20

0.70 0.79 0.72 0.86

1.03 0.69 1.11 0.77

1.56 0.68 1.73 0.72

2.26 0.80 2.44 0.85

2.63 0.85 2.86 0.89

0.47 0.11 0.72 0.22

0.44 0.11 0.69 0.23

0.45 0.12 0.65 0.24

0.54 0.13 0.74 0.27

0.66 0.16 0.80 0.30

0.75 0.19 0.88 0.36

0.80 0.22 0.95 0.39

0.64 0.91 0.79 0.96

0.69 0.88 0.74 0.93

0.78 0.75 0.84 0.82

0.83 0.65 0.91 0.73

1.02 0.59 1.08 0.66

1.18 0.60 1.24 0.67

1.27 0.62 1.34 0.67

CDI

DDI

1800 vph

0.65 1.24

0.87 0.99

1.04 0.93

0.88 0.84

1.45 0.79

2.13 0.91

2.51 0.96

0.96 0.88

0.92 0.98

0.83 0.90

0.63 0.78

0.48 0.73

0.33 0.61

0.25 0.53

0.00 0.00

0.47 0.05

0.87 0.14

0.81 0.23

0.62 0.32

0.52 0.41

0.48 0.46

0.92 0.39

0.88 0.42

0.82 0.37

0.99 0.39

1.16 0.45

1.35 0.51

1.35 0.53

0.96 0.89

0.92 1.00

0.80 0.90

0.67 0.77

0.45 0.71

0.28 0.59

0.21 0.52

0.00 0.00

0.41 0.05

0.72 0.14

0.81 0.23

0.60 0.32

0.46 0.41

0.41 0.46

0.65 1.53

0.74 1.33

0.77 0.95

1.22 0.85

1.90 0.81

2.66 0.93

3.12 0.99

0.92 0.35

0.88 0.35

0.79 0.37

0.83 0.38

0.92 0.44

1.01 0.49

1.07 0.52

0.95 1.09

0.91 1.10

0.91 0.91

0.98 0.80

1.16 0.74

1.33 0.75

1.41 0.75

CDI DDI 2100 vph
0.67 1.56 0.89 1.35 1.03 0.97 0.91 0.84 1.49 0.82 2.18 0.95 2.44 1.01 1.05 0.82 1.00 0.85 0.90 0.95 0.70 0.85 0.54 0.75 0.36 0.64 0.29 0.57 0.00 0.00 0.49 0.05 0.90 0.14 0.80 0.23 0.62 0.32 0.52 0.41 0.49 0.42 0.98 0.40 0.95 0.41 0.88 0.43 1.04 0.45 1.21 0.49 1.38 0.54 1.44 0.57 1.05 0.82 0.99 0.85 0.87 0.94 0.72 0.84 0.50 0.75 0.32 0.63 0.24 0.56 0.00 0.00 0.44 0.05 0.74 0.14 0.85 0.23 0.62 0.32 0.46 0.41 0.44 0.43 0.67 1.59 0.75 1.38 0.74 0.98 1.28 0.85 1.96 0.82 2.74 0.97 3.19 1.03 0.98 0.40 0.96 0.40 0.88 0.42 0.88 0.45 0.96 0.49 1.07 0.53 1.12 0.56 1.03 1.05 0.98 1.01 0.94 0.95 1.02 0.84 1.19 0.77 1.36 0.78 1.46 0.78

E-9

Operating Performance of Diverging Diamond Interchanges

Table E - 4 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2500 vph with different off-ramp
demands and through/left proportions for LC1

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2500 vph

CDI

DDI CDI

DDI

500 vph

1100 vph

0.64 1.38 0.66 1.48

0.90 1.17 0.92 1.29

0.95 0.83 1.01 0.90

0.80 0.71 0.88 0.78

1.35 0.70 1.47 0.77

2.03 0.84 2.13 0.90

2.25 0.86 2.37 0.95

0.72 0.69 0.84 0.74

0.67 0.74 0.81 0.78

0.51 0.79 0.65 0.87

0.36 0.66 0.49 0.78

0.24 0.57 0.35 0.65

0.13 0.36 0.22 0.50

0.07 0.23 0.16 0.40

0.00 0.00 0.00 0.00

0.47 0.05 0.53 0.05

0.75 0.15 0.83 0.15

0.85 0.25 0.84 0.25

0.65 0.35 0.64 0.35

0.54 0.45 0.54 0.45

0.52 0.50 0.50 0.50

0.47 0.11 0.78 0.23

0.45 0.11 0.73 0.23

0.57 0.12 0.76 0.25

0.80 0.13 0.92 0.28

0.94 0.17 1.08 0.31

1.02 0.20 1.24 0.37

1.02 0.23 1.24 0.40

0.72 0.69 0.84 0.75

0.67 0.75 0.83 0.78

0.52 0.78 0.64 0.86

0.37 0.65 0.51 0.76

0.25 0.55 0.34 0.65

0.12 0.36 0.19 0.50

0.07 0.22 0.13 0.40

0.00 0.00 0.00 0.00

0.40 0.05 0.45 0.05

0.60 0.15 0.69 0.15

0.71 0.25 0.80 0.25

0.59 0.35 0.58 0.35

0.44 0.45 0.45 0.45

0.42 0.50 0.42 0.50

0.64 1.38 0.66 1.50

0.77 1.19 0.81 1.29

0.69 0.84 0.74 0.91

1.08 0.72 1.19 0.80

1.72 0.72 1.83 0.77

2.42 0.84 2.61 0.90

2.81 0.88 3.10 0.95

0.47 0.11 0.78 0.22

0.45 0.11 0.69 0.23

0.52 0.12 0.69 0.24

0.63 0.13 0.77 0.27

0.72 0.16 0.85 0.31

0.80 0.20 0.95 0.37

0.87 0.22 0.99 0.40

0.69 0.95 0.83 1.00

0.72 0.92 0.80 0.96

0.81 0.80 0.88 0.88

0.89 0.68 0.97 0.77

1.10 0.64 1.14 0.70

1.26 0.65 1.33 0.72

1.36 0.65 1.43 0.72

CDI

DDI

1800 vph

0.70 1.61

0.93 1.40

1.11 0.98

0.94 0.86

1.58 0.82

2.25 0.97

2.50 1.02

1.01 0.81

0.96 0.84

0.85 0.94

0.64 0.85

0.49 0.75

0.32 0.61

0.24 0.54

0.00 0.00

0.50 0.05

0.92 0.15

0.82 0.25

0.63 0.35

0.52 0.45

0.50 0.46

0.94 0.35

0.91 0.36

0.87 0.38

1.04 0.40

1.23 0.45

1.40 0.50

1.40 0.54

1.01 0.81

0.96 0.84

0.80 0.96

0.65 0.84

0.45 0.74

0.27 0.61

0.20 0.52

0.00 0.00

0.43 0.05

0.75 0.15

0.87 0.25

0.59 0.35

0.46 0.45

0.44 0.47

0.70 1.64

0.80 1.42

0.82 1.00

1.29 0.87

2.00 0.84

2.89 0.97

3.33 1.04

0.94 0.35

0.91 0.36

0.82 0.38

0.88 0.40

0.99 0.44

1.07 0.50

1.13 0.52

0.99 1.07

0.94 1.03

0.97 0.97

1.04 0.85

1.22 0.78

1.41 0.78

1.52 0.79

CDI

DDI

2100 vph

0.71 1.67

0.96 1.42

1.14 1.03

0.98 0.90

1.62 0.86

2.31 1.00

2.57 1.05

1.06 0.83

1.03 0.88

0.93 0.95

0.72 0.89

0.52 0.77

0.35 0.66

0.27 0.58

0.00 0.00

0.50 0.05

0.93 0.15

0.81 0.25

0.62 0.35

0.52 0.42

0.50 0.44

1.03 0.40

0.98 0.41

0.92 0.43

1.10 0.45

1.28 0.49

1.43 0.55

1.43 0.58

1.06 0.84

1.03 0.88

0.85 0.95

0.71 0.88

0.49 0.76

0.31 0.65

0.24 0.57

0.00 0.00

0.45 0.05

0.78 0.15

0.90 0.25

0.60 0.35

0.47 0.43

0.44 0.45

0.71 1.70

0.81 1.45

0.82 1.05

1.34 0.91

2.10 0.88

2.95 1.02

3.40 1.07

1.03 0.40

0.98 0.41

0.90 0.43

0.93 0.45

1.03 0.49

1.13 0.54

1.18 0.57

1.05 1.10

1.02 1.06

1.00 0.98

1.08 0.89

1.25 0.81

1.44 0.82

1.55 0.82

E-10

Operating Performance of Diverging Diamond Interchanges

Table E - 5 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street volume of 2700 vph with different off-ramp
demands and through/left proportions for LC1

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2700 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.67 1.47

0.70

1.59

0.91 1.27

0.94

1.37

0.99 0.90

1.07

0.97

0.86 0.78

0.92

0.83

1.45 0.74

1.55

0.80

2.08 0.87

2.19

0.91

2.31 0.88

2.43

0.96

0.74 0.70

0.88

0.74

0.71 0.74

0.84

0.79

0.53 0.83

0.68

0.92

0.38 0.74

0.50

0.80

0.25 0.60

0.36

0.68

0.13 0.37

0.21

0.52

0.07 0.24

0.14

0.42

0.00 0.00

0.00

0.00

0.54 0.05

0.57

0.05

0.79 0.16

0.89

0.16

0.84 0.27

0.83

0.27

0.66 0.38

0.65

0.38

0.55 0.49

0.55

0.49

0.53 0.54

0.53

0.54

0.57 0.11

0.79

0.23

0.47 0.11

0.76

0.23

0.63 0.12

0.80

0.25

0.83 0.14

1.00

0.27

1.02 0.17

1.18

0.31

1.02 0.20

1.24

0.38

1.02 0.24

1.24

0.42

0.74 0.70

0.88

0.75

0.71 0.75

0.84

0.79

0.54 0.83

0.64

0.92

0.39 0.72

0.51

0.79

0.25 0.58

0.34

0.67

0.13 0.39

0.19

0.51

0.07 0.23

0.13

0.41

0.00 0.00

0.00

0.00

0.44 0.05

0.46

0.05

0.64 0.16

0.71

0.16

0.76 0.27

0.83

0.27

0.57 0.38

0.59

0.38

0.45 0.49

0.47

0.49

0.43 0.54

0.45

0.54

0.67 1.50

0.70

1.62

0.80 1.29

0.82

1.39

0.72 0.90

0.80

0.97

1.14 0.80

1.25

0.84

1.79 0.76

1.94

0.82

2.61 0.85

2.78

0.93

3.04 0.90

3.24

0.98

0.57 0.11

0.79

0.22

0.47 0.11

0.76

0.23

0.57 0.12

0.72

0.25

0.67 0.14

0.81

0.27

0.80 0.16

0.92

0.31

0.87 0.21

1.03

0.36

0.94 0.23

1.08

0.41

0.72 1.00

0.86

1.05

0.76 0.96

0.82

1.01

0.86 0.86

0.94

0.94

0.94 0.75

1.02

0.81

1.14 0.67

1.21

0.74

1.35 0.68

1.41

0.74

1.46 0.68

1.53

0.75

CDI

DDI

1800 vph

0.74 1.71

1.01 1.48

1.13 1.05

1.01 0.91

1.66 0.86

2.30 1.01

2.56 1.05

1.05 0.82

0.99 0.85

0.86 0.96

0.66 0.89

0.47

0.76

0.30

0.63

0.23

0.55

0.00

0.00

0.51

0.05

0.95

0.16

0.81

0.27

0.63

0.38

0.55

0.45

0.52

0.48

0.99

0.36

0.94

0.36

0.91

0.38

1.09

0.41

1.31

0.44

1.40

0.51

1.40

0.55

1.05

0.82

0.95

0.85

0.80

0.96

0.63

0.88

0.44

0.76

0.27

0.62

0.20

0.54

0.00

0.00

0.44

0.05

0.81

0.16

0.86

0.27

0.60

0.38

0.48

0.46

0.46 0.49

0.74 1.74

0.85 1.51

0.83 1.06

1.37 0.93

2.13 0.88

3.02 1.02

3.53 1.06

0.99 0.35

0.94 0.36

0.84 0.38

0.92 0.40

1.04 0.44

1.16 0.50

1.19 0.54

1.04 1.12

0.98 1.07

1.01 0.99

1.09 0.89

1.28 0.81

1.50 0.82

1.61 0.82

E-11

Operating Performance of Diverging Diamond Interchanges

E.1.2

Plots of Difference between CDI and DDI v/c Ratios

The following plots present the difference in the CDI and DDI v/c ratios on different turning movements traffic demands and through/left proportions for LC1. The numbers in the legend represent different cross-street and off-ramp volumes i.e. 2300/1100 means cross-street demand of 2300 vph and off-ramp volume of 1100 vph.

Figure E - 1 Difference in v/c ratios between CDI and DDI on NBT1 at different traffic demands and through/left proportions for LC1
E-12

Operating Performance of Diverging Diamond Interchanges
Figure E - 2 Difference in v/c ratios between CDI and DDI on SBT1 at different traffic demands and through/left proportions for LC1
Figure E - 3 Difference in v/c ratios between CDI and DDI on SBL1 at different traffic demands and through/left proportions for LC1 E-13

Operating Performance of Diverging Diamond Interchanges
Figure E - 4 Difference in v/c ratios between CDI and DDI on EBL1 at different traffic demands and through/left proportions for LC1
Figure E - 5 Difference in v/c ratios between CDI and DDI on NBT2 at different traffic demands and through/left proportions for LC1 E-14

Operating Performance of Diverging Diamond Interchanges
Figure E - 6 Difference in v/c ratios between CDI and DDI on NBL2 at different traffic demands and through/left proportions for LC1
Figure E - 7 Difference in v/c ratios between CDI and DDI on SBT2 at different traffic demands and through/left proportions for LC1 E-15

Operating Performance of Diverging Diamond Interchanges
(%)
Figure E - 8 Difference in v/c ratios between CDI and DDI on WBL2 at different traffic demands and through/left proportions for LC1
E-16

Operating Performance of Diverging Diamond Interchanges

E.2

Lane Configuration 2

The following tables and plots present the difference in the CDI and DDI v/c ratios on different turning movements traffic demands and through/left proportions for LC2.

E.2.1

Color-Coded Tables of v/c Ratios of CDIs and DDIs

E-17

Operating Performance of Diverging Diamond Interchanges

Table E - 6 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1000 vph and (b) cross-street demand of 1500 vph with different off-ramp demands and through/left proportions
for LC2

(a)

(b)

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 1000 vph

CDI DDI CDI DDI

200 vph

500 vph

0.28 0.54 0.33 0.60

0.45 0.47 0.50 0.51

0.42 0.35 0.47 0.39

0.67 0.45 0.71 0.50

1.03 0.58 1.15 0.64

1.55 0.67 1.61 0.75

1.78 0.69 1.92 0.80

0.32 0.45 0.44 0.51

0.30 0.44 0.39 0.49

0.23 0.39 0.31 0.44

0.16 0.33 0.23 0.39

0.11 0.25 0.16 0.32

0.06 0.16 0.11 0.24

0.03 0.09 0.08 0.20

0.00 0.00 0.00 0.00

0.20 0.04 0.22 0.04

0.36 0.12 0.43 0.12

0.50 0.20 0.55 0.20

0.52 0.28 0.50 0.28

0.43 0.36 0.43 0.36

0.40 0.40 0.39 0.40

0.13 0.05 0.26 0.12

0.16 0.05 0.28 0.13

0.19 0.06 0.35 0.14

0.25 0.07 0.42 0.15

0.29 0.07 0.45 0.16

0.32 0.09 0.53 0.18

0.33 0.09 0.55 0.20

0.32 0.44 0.44 0.49

0.30 0.42 0.39 0.47

0.22 0.38 0.30 0.42

0.16 0.31 0.23 0.37

0.11 0.24 0.16 0.31

0.06 0.15 0.11 0.23

0.03 0.09 0.08 0.17

0.00 0.00 0.00 0.00

0.18 0.04 0.20 0.04

0.36 0.12 0.40 0.12

0.48 0.20 0.52 0.20

0.53 0.28 0.51 0.28

0.44 0.36 0.43 0.36

0.41 0.40 0.38 0.40

0.28 0.56 0.33 0.63

0.47 0.49 0.53 0.54

0.40 0.37 0.47 0.41

0.71 0.48 0.75 0.53

1.09 0.61 1.19 0.67

1.61 0.69 1.65 0.78

1.90 0.71 1.86 0.87

0.13 0.05 0.26 0.12

0.16 0.05 0.28 0.12

0.21 0.06 0.39 0.13

0.25 0.06 0.42 0.14

0.29 0.07 0.46 0.16

0.33 0.08 0.53 0.17

0.34 0.09 0.57 0.17

0.28 0.48 0.39 0.53

0.32 0.44 0.36 0.49

0.36 0.36 0.42 0.41

0.53 0.39 0.58 0.43

0.68 0.43 0.69 0.48

0.76 0.48 0.77 0.53

0.80 0.49 0.78 0.55

CDI DDI 800 vph
0.35 0.63 0.56 0.56 0.50 0.41 0.79 0.53 1.15 0.70 1.71 0.82 1.96 0.91 0.52 0.56 0.49 0.53 0.39 0.50 0.30 0.45 0.22 0.38 0.16 0.32 0.13 0.26 0.00 0.00 0.23 0.04 0.46 0.12 0.58 0.20 0.56 0.28 0.42 0.36 0.38 0.38 0.38 0.19 0.38 0.19 0.45 0.21 0.50 0.23 0.58 0.24 0.62 0.26 0.66 0.26 0.52 0.55 0.48 0.53 0.38 0.49 0.30 0.43 0.22 0.36 0.16 0.29 0.13 0.24 0.00 0.00 0.22 0.04 0.45 0.12 0.56 0.20 0.56 0.28 0.42 0.36 0.38 0.40 0.35 0.67 0.57 0.57 0.50 0.43 0.82 0.56 1.15 0.74 1.69 0.90 1.95 1.00 0.38 0.18 0.38 0.19 0.47 0.20 0.50 0.22 0.58 0.23 0.63 0.24 0.67 0.24 0.48 0.58 0.45 0.53 0.47 0.45 0.63 0.48 0.74 0.52 0.78 0.57 0.80 0.60

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 1500 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.45

0.86

0.47 0.94

0.68

0.74

0.63 0.81

0.59

0.53

0.67 0.60

0.96

0.71

1.06 0.78

1.50

0.91

1.67 1.05

2.19

1.04

2.37 1.23

2.55

1.06

2.77 1.36

0.55

0.67

0.69 0.74

0.50

0.63

0.65 0.72

0.37

0.58

0.53 0.67

0.27

0.50

0.41 0.62

0.19

0.42

0.30 0.54

0.11

0.31

0.21 0.44

0.07

0.22

0.17 0.36

0.00

0.00

0.00 0.00

0.33

0.06

0.41 0.06

0.55

0.18

0.63 0.18

0.71

0.30

0.72 0.30

0.51

0.42

0.49 0.36

0.41

0.48

0.40 0.40

0.36

0.51

0.36 0.40

0.35

0.12

0.59 0.23

0.35

0.12

0.53 0.24

0.44

0.13

0.60 0.26

0.55

0.15

0.72 0.29

0.63

0.17

0.78 0.33

0.74

0.21

0.88 0.36

0.82

0.22

0.95 0.36

0.55

0.66

0.69 0.73

0.49

0.62

0.65 0.71

0.37

0.56

0.52 0.66

0.27

0.49

0.40 0.59

0.19

0.40

0.30 0.52

0.11

0.29

0.21 0.42

0.07

0.20

0.17 0.34

0.00

0.00

0.00 0.00

0.30

0.06

0.35 0.06

0.55

0.18

0.63 0.18

0.71

0.30

0.72 0.30

0.52

0.42

0.49 0.38

0.41

0.49

0.39 0.42

0.36

0.54

0.36 0.42

0.45

0.89

0.47 0.97

0.68

0.77

0.68 0.84

0.59

0.54

0.64 0.61

0.96

0.72

1.05 0.82

1.56

0.95

1.68 1.11

2.19

1.08

2.31 1.29

2.55

1.13

2.77 1.43

0.35

0.11

0.59 0.23

0.39

0.12

0.53 0.24

0.44

0.13

0.64 0.26

0.56

0.14

0.72 0.28

0.63

0.16

0.78 0.31

0.74

0.20

0.92 0.34

0.82

0.20

0.95 0.34

0.51

0.74

0.66 0.80

0.47

0.67

0.62 0.74

0.55

0.54

0.64 0.63

0.78

0.59

0.83 0.68

0.85

0.68

0.87 0.77

0.92

0.75

0.96 0.84

0.95

0.76

1.01 0.88

CDI

DDI

1800 vph

0.48 1.07

0.64 0.90

0.68 0.64

1.15 0.90

1.76 1.09

2.56 1.30

3.00 1.44

0.83 0.79

0.81 0.83

0.72 0.70

0.57 0.73

0.45 0.65

0.33 0.56

0.27 0.52

0.00 0.00

0.43 0.06

0.68 0.18

0.69 0.30

0.50 0.34

0.39 0.35

0.35 0.35

0.78 0.36

0.77 0.38

0.69 0.36

0.80 0.44

0.90 0.46

1.01 0.49

1.07 0.52

0.83 0.79

0.81 0.81

0.72 0.69

0.57 0.72

0.45 0.61

0.33 0.51

0.27 0.47

0.00 0.00

0.42 0.06

0.65 0.18

0.69 0.30

0.50 0.37

0.40 0.39

0.36 0.40

0.48 1.07

0.65 0.93

0.70 0.66

1.15 0.91

1.80 1.18

2.63 1.45

3.09 1.64

0.78 0.36

0.78 0.37

0.69 0.36

0.81 0.43

0.90 0.44

1.01 0.45

1.07 0.47

0.82 0.87

0.80 0.84

0.71 0.68

0.86 0.78

0.93 0.83

1.03 0.90

1.09 0.95

E-18

Operating Performance of Diverging Diamond Interchanges

Table E - 7 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1800 vph and (b) cross-street demand of 2100 vph with different off-ramp demands and through/left proportions
for LC2

(a)

(b)

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 1800 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.51 1.01

0.52

1.11

0.77 0.86

0.70

0.95

0.68 0.61

0.71

0.69

1.05 0.81

1.17

0.90

1.72 1.05

1.85

1.16

2.56 1.20

2.78

1.35

3.01 1.24

3.22

1.49

0.60 0.71

0.72

0.75

0.57 0.74

0.70

0.79

0.42 0.64

0.56

0.73

0.29 0.57

0.42

0.65

0.20 0.50

0.30

0.59

0.11 0.35

0.20

0.47

0.07 0.26

0.14

0.38

0.00 0.00

0.00

0.00

0.40 0.07

0.48

0.07

0.66 0.22

0.72

0.22

0.69 0.36

0.70

0.36

0.51 0.44

0.51

0.40

0.40 0.49

0.39

0.44

0.35 0.51

0.36

0.44

0.38 0.11

0.65

0.23

0.39 0.12

0.58

0.24

0.49 0.13

0.65

0.26

0.63 0.15

0.79

0.28

0.78 0.18

0.92

0.33

0.89 0.22

1.03

0.37

0.94 0.26

1.11

0.38

0.60 0.72

0.72

0.75

0.57 0.72

0.70

0.78

0.41 0.63

0.55

0.72

0.29 0.55

0.42

0.65

0.20 0.47

0.30

0.57

0.11 0.33

0.20

0.45

0.07 0.22

0.14

0.36

0.00 0.00

0.00

0.00

0.38 0.07

0.45

0.07

0.66 0.22

0.69

0.22

0.70 0.36

0.70

0.36

0.51 0.46

0.51

0.41

0.40 0.51

0.39

0.46

0.36 0.55

0.36

0.46

0.51 1.03

0.52

1.13

0.79 0.88

0.71

0.97

0.66 0.63

0.72

0.71

1.08 0.84

1.17

0.90

1.72 1.10

1.85

1.21

2.56 1.25

2.78

1.39

3.09 1.33

3.22

1.54

0.38 0.11

0.65

0.23

0.39 0.12

0.58

0.23

0.53 0.13

0.67

0.25

0.63 0.14

0.79

0.28

0.78 0.17

0.92

0.32

0.89 0.21

1.03

0.36

0.94 0.22

1.11

0.36

0.56 0.83

0.71

0.88

0.60 0.78

0.67

0.84

0.64 0.62

0.70

0.70

0.83 0.68

0.88

0.75

0.92 0.80

0.96

0.86

1.02 0.89

1.08

0.95

1.08 0.93

1.15

0.99

CDI DDI 1800 vph
0.54 1.20 0.78 1.04 0.79 0.76 1.28 0.99 2.06 1.26 2.99 1.51 3.50 1.68 0.87 0.78 0.86 0.82 0.76 0.82 0.58 0.75 0.44 0.71 0.29 0.59 0.23 0.51 0.00 0.00 0.39 0.07 0.80 0.22 0.70 0.34 0.50 0.37 0.39 0.38 0.36 0.38 0.83 0.35 0.79 0.36 0.78 0.39 0.88 0.42 1.01 0.48 1.16 0.51 1.23 0.51 0.88 0.78 0.86 0.82 0.75 0.81 0.58 0.74 0.44 0.69 0.29 0.56 0.23 0.48 0.00 0.00 0.49 0.07 0.79 0.22 0.69 0.36 0.50 0.38 0.39 0.41 0.36 0.41 0.54 1.22 0.72 1.06 0.78 0.79 1.25 1.01 2.06 1.31 2.99 1.61 3.50 1.79 0.82 0.34 0.80 0.35 0.80 0.38 0.90 0.41 1.01 0.46 1.16 0.48 1.23 0.48 0.86 0.91 0.84 0.89 0.76 0.79 0.93 0.84 1.03 0.95 1.16 1.03 1.22 1.07

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2100 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.57

1.16 0.58 1.24

0.78

0.98 0.77 1.07

0.72

0.69 0.80 0.77

1.20

0.91 1.30 1.01

1.96

1.18 2.12 1.29

3.02

1.35 3.16 1.46

3.52

1.45 3.69 1.63

0.65

0.70 0.77 0.74

0.59

0.77 0.74 0.80

0.44

0.73 0.60 0.81

0.32

0.64 0.44 0.74

0.21

0.59 0.31 0.63

0.11

0.40 0.18 0.54

0.06

0.26 0.13 0.41

0.00

0.00 0.00 0.00

0.42

0.08 0.51 0.08

0.70

0.25 0.81 0.25

0.69

0.42 0.69 0.39

0.50

0.46 0.50 0.43

0.39

0.51 0.39 0.48

0.35

0.53 0.36 0.48

0.44

0.11 0.69 0.23

0.44

0.11 0.65 0.23

0.57

0.13 0.73 0.26

0.73

0.15 0.87 0.29

0.89

0.20 1.03 0.33

0.94

0.24 1.18 0.41

1.02

0.26 1.24 0.41

0.65

0.71 0.77 0.75

0.59

0.80 0.74 0.80

0.44

0.71 0.60 0.80

0.32

0.62 0.44 0.73

0.21

0.55 0.31 0.64

0.12

0.37 0.18 0.51

0.06

0.24 0.13 0.39

0.00

0.00 0.00 0.00

0.39

0.08 0.49 0.08

0.70

0.25 0.79 0.25

0.69

0.42 0.69 0.39

0.50

0.48 0.50 0.43

0.39

0.53 0.39 0.49

0.36

0.55 0.36 0.49

0.57

1.18 0.58 1.26

0.80

1.00 0.78 1.09

0.72

0.70 0.81 0.79

1.20

0.93 1.30 1.02

2.00

1.23 2.16 1.29

2.96

1.40 3.16 1.51

3.60

1.50 3.78 1.68

0.44

0.11 0.69 0.22

0.44

0.11 0.65 0.23

0.57

0.13 0.74 0.25

0.73

0.14 0.87 0.29

0.89

0.18 1.03 0.33

1.02

0.22 1.18 0.39

1.02

0.24 1.24 0.39

0.62

0.88 0.75 0.92

0.63

0.87 0.72 0.90

0.69

0.70 0.79 0.79

0.89

0.77 0.93 0.85

1.01

0.92 1.06 0.96

1.14

1.02 1.20 1.08

1.21

1.07 1.28 1.13

CDI

DDI

1800 vph

0.60 1.35

0.79 1.15

0.84 0.84

1.40 1.11

2.35 1.43

3.32 1.65

3.88 1.84

0.92 0.81

0.89 0.85

0.77 0.87

0.60 0.83

0.41 0.74

0.26 0.64

0.19 0.54

0.00 0.00

0.47 0.08

0.86 0.25

0.69 0.35

0.50 0.39

0.40 0.41

0.36 0.41

0.88 0.35

0.84 0.36

0.83 0.38

0.99 0.43

1.13 0.47

1.31 0.54

1.40 0.54

0.92 0.81

0.89 0.85

0.77 0.87

0.60 0.82

0.42 0.74

0.26 0.60

0.19 0.51

0.00 0.00

0.46 0.08

0.84 0.25

0.69 0.36

0.49 0.39

0.40 0.43

0.37 0.43

0.60 1.35

0.80 1.17

0.86 0.86

1.43 1.13

2.30 1.43

3.40 1.76

3.98 1.96

0.88 0.35

0.84 0.36

0.83 0.38

0.99 0.43

1.16 0.47

1.31 0.51

1.40 0.51

0.91 0.98

0.87 0.96

0.84 0.86

1.00 0.94

1.13 1.04

1.28 1.16

1.36 1.20

E-19

Operating Performance of Diverging Diamond Interchanges

Table E - 8 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2300 vph with different off-ramp
demands and through/left proportions for LC2

Proportion Approach

100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2300 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.59 1.24 0.62 1.34

0.81 1.07 0.83 1.15

0.74 0.74 0.83 0.82

1.27 0.96 1.40 1.11

2.15 1.28 2.32 1.37

3.24 1.43 3.47 1.57

3.68 1.53 3.94 1.67

0.67 0.71 0.81 0.76

0.62 0.77 0.79 0.81

0.46 0.76 0.61 0.85

0.33 0.69 0.46 0.80

0.23 0.58 0.31 0.69

0.12 0.40 0.18 0.57

0.06 0.28 0.12 0.46

0.00 0.00 0.00 0.00

0.46 0.09 0.62 0.09

0.75 0.28 0.86 0.28

0.68 0.46 0.68 0.39

0.49 0.48 0.49 0.43

0.39 0.54 0.39 0.49

0.38 0.55 0.37 0.49

0.47 0.11 0.72 0.23

0.45 0.11 0.69 0.23

0.62 0.12 0.81 0.25

0.80 0.15 0.92 0.30

0.94 0.18 1.08 0.34

1.02 0.23 1.24 0.43

1.13 0.28 1.30 0.46

0.67 0.71 0.81 0.76

0.62 0.77 0.79 0.81

0.46 0.75 0.61 0.84

0.33 0.68 0.46 0.81

0.23 0.58 0.31 0.67

0.12 0.39 0.18 0.55

0.06 0.26 0.12 0.41

0.00 0.00 0.00 0.00

0.46 0.09 0.59 0.09

0.73 0.28 0.84 0.28

0.69 0.46 0.68 0.39

0.50 0.48 0.49 0.45

0.39 0.55 0.39 0.50

0.38 0.57 0.37 0.52

0.59 1.25 0.62 1.36

0.81 1.09 0.84 1.16

0.75 0.75 0.85 0.83

1.29 0.99 1.40 1.11

2.19 1.28 2.37 1.41

3.31 1.44 3.47 1.60

3.68 1.59 3.94 1.78

0.47 0.11 0.72 0.23

0.45 0.11 0.69 0.23

0.63 0.12 0.81 0.25

0.80 0.14 0.92 0.30

0.94 0.18 1.08 0.33

1.02 0.23 1.24 0.41

1.13 0.26 1.30 0.41

0.64 0.92 0.79 0.97

0.67 0.89 0.77 0.94

0.73 0.75 0.84 0.83

0.93 0.83 0.97 0.93

1.06 0.97 1.12 1.04

1.21 1.08 1.28 1.17

1.31 1.17 1.37 1.22

CDI

DDI

1800 vph

0.65 1.45

0.80 1.26

0.88 0.89

1.53 1.20

2.49 1.49

3.64 1.74

4.14 1.89

0.96 0.82

0.92 0.85

0.79 0.93

0.59 0.83

0.40 0.78

0.25 0.66

0.18 0.56

0.00 0.00

0.60 0.09

0.90 0.28

0.68 0.36

0.50 0.40

0.40 0.44

0.38 0.44

0.92 0.36

0.88 0.36

0.87 0.38

1.04 0.41

1.23 0.48

1.40 0.55

1.45 0.56

0.96 0.82

0.92 0.85

0.79 0.92

0.59 0.82

0.40 0.76

0.25 0.64

0.18 0.53

0.00 0.00

0.58 0.09

0.89 0.28

0.68 0.37

0.50 0.41

0.40 0.45

0.38 0.46

0.65 1.48

0.81 1.28

0.90 0.91

1.53 1.22

2.49 1.53

3.64 1.79

4.14 1.99

0.92 0.35

0.88 0.36

0.87 0.38

1.04 0.41

1.23 0.47

1.40 0.53

1.45 0.53

0.95 1.03

0.91 0.99

0.89 0.91

1.04 0.98

1.20 1.11

1.36 1.22

1.45 1.27

CDI DDI 2100 vph
0.67 1.51 0.82 1.31 0.93 0.92 1.56 1.21 2.58 1.53 3.73 1.80 4.25 2.00 1.05 0.85 1.00 0.88 0.88 0.97 0.64 0.88 0.44 0.82 0.29 0.69 0.22 0.58 0.00 0.00 0.61 0.09 0.94 0.28 0.69 0.35 0.50 0.39 0.39 0.42 0.37 0.42 0.98 0.41 0.95 0.41 0.91 0.44 1.10 0.47 1.28 0.54 1.43 0.58 1.48 0.58 1.05 0.85 0.99 0.88 0.88 0.97 0.64 0.87 0.44 0.80 0.29 0.66 0.22 0.56 0.00 0.00 0.60 0.09 0.94 0.28 0.69 0.36 0.50 0.40 0.40 0.44 0.38 0.44 0.67 1.53 0.82 1.33 0.93 0.93 1.59 1.23 2.58 1.57 3.82 1.88 4.36 2.09 0.98 0.40 0.96 0.41 0.91 0.43 1.10 0.46 1.28 0.53 1.43 0.56 1.48 0.56 1.03 1.06 0.98 1.02 0.93 0.95 1.07 1.01 1.23 1.14 1.39 1.24 1.49 1.29

E-20

Operating Performance of Diverging Diamond Interchanges

Table E - 9 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2500 vph with different off-ramp
demands and through/left proportions for LC2

Proportion Approach

100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2500 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.65 1.34 0.65 1.45

0.88 1.14 0.86 1.25

0.78 0.80 0.88 0.88

1.41 1.06 1.50 1.16

2.38 1.35 2.47 1.44

3.45 1.50 3.60 1.66

3.83 1.61 4.00 1.75

0.73 0.71 0.83 0.76

0.68 0.78 0.81 0.82

0.48 0.81 0.63 0.89

0.36 0.78 0.47 0.83

0.23 0.64 0.31 0.72

0.11 0.45 0.18 0.57

0.06 0.31 0.12 0.46

0.00 0.00 0.00 0.00

0.54 0.10 0.65 0.10

0.79 0.30 0.88 0.30

0.69 0.43 0.69 0.41

0.50 0.48 0.49 0.46

0.40 0.55 0.40 0.50

0.40 0.55 0.40 0.52

0.50 0.11 0.77 0.23

0.49 0.11 0.73 0.23

0.66 0.12 0.80 0.25

0.80 0.16 0.99 0.29

0.94 0.19 1.18 0.34

1.13 0.25 1.30 0.42

1.13 0.31 1.30 0.46

0.73 0.71 0.83 0.76

0.68 0.78 0.82 0.82

0.48 0.81 0.63 0.89

0.35 0.75 0.47 0.83

0.24 0.61 0.31 0.71

0.11 0.42 0.18 0.55

0.06 0.26 0.12 0.42

0.00 0.00 0.00 0.00

0.54 0.10 0.62 0.10

0.79 0.30 0.88 0.30

0.68 0.45 0.69 0.41

0.49 0.49 0.50 0.46

0.40 0.57 0.41 0.52

0.40 0.59 0.41 0.54

0.65 1.36 0.65 1.48

0.88 1.16 0.88 1.25

0.78 0.80 0.88 0.88

1.38 1.09 1.50 1.16

2.33 1.40 2.52 1.45

3.45 1.54 3.68 1.70

3.83 1.72 4.09 1.84

0.50 0.11 0.77 0.23

0.49 0.11 0.70 0.23

0.67 0.12 0.80 0.25

0.87 0.15 0.99 0.29

1.02 0.18 1.18 0.34

1.13 0.23 1.30 0.40

1.13 0.26 1.30 0.42

0.69 0.96 0.82 1.01

0.74 0.93 0.80 0.97

0.77 0.80 0.86 0.88

0.97 0.92 1.02 0.97

1.12 1.05 1.19 1.10

1.30 1.17 1.37 1.23

1.40 1.26 1.47 1.28

CDI DDI 1800 vph
0.70 1.55 0.87 1.35 0.94 0.95 1.64 1.23 2.68 1.56 3.86 1.80 4.29 2.00 1.01 0.84 0.96 0.87 0.81 0.99 0.59 0.91 0.40 0.82 0.25 0.69 0.18 0.56 0.00 0.00 0.61 0.10 0.95 0.30 0.69 0.38 0.50 0.42 0.41 0.46 0.41 0.46 0.94 0.36 0.91 0.36 0.92 0.39 1.09 0.43 1.31 0.49 1.45 0.56 1.45 0.56 1.01 0.84 0.96 0.87 0.81 0.98 0.59 0.89 0.40 0.80 0.25 0.67 0.18 0.55 0.00 0.00 0.60 0.10 0.95 0.30 0.68 0.39 0.50 0.43 0.41 0.48 0.41 0.48 0.70 1.58 0.87 1.37 0.94 0.97 1.64 1.25 2.68 1.59 3.86 1.84 4.29 2.05 0.94 0.36 0.91 0.36 0.92 0.38 1.13 0.42 1.31 0.48 1.45 0.55 1.45 0.55 0.99 1.08 0.94 1.04 0.94 0.97 1.09 1.04 1.26 1.17 1.44 1.29 1.55 1.34

CDI

DDI

2100 vph

0.71 1.61

0.89 1.40

0.97 0.98

1.70 1.27

2.74 1.62

3.95 1.86

4.39 2.08

1.06 0.87

1.03 0.90

0.90 1.00

0.64 0.93

0.44 0.84

0.27 0.71

0.21 0.60

0.00 0.00

0.62 0.10

1.00 0.30

0.68 0.37

0.50 0.40

0.41 0.44

0.41 0.44

1.03 0.41

0.98 0.42

0.96 0.44

1.15 0.48

1.35 0.53

1.52 0.59

1.52 0.60

1.06 0.87

1.03 0.90

0.90 1.02

0.64 0.92

0.44 0.83

0.27 0.68

0.21 0.58

0.00 0.00

0.61 0.10

0.98 0.30

0.68 0.37

0.50 0.41

0.41 0.46

0.41 0.46

0.71 1.64

0.90 1.42

0.98 1.00

1.70 1.29

2.74 1.65

3.95 1.93

4.39 2.14

1.03 0.41

0.98 0.41

0.96 0.44

1.15 0.47

1.35 0.53

1.52 0.57

1.52 0.58

1.05 1.11

1.02 1.07

0.98 1.01

1.12 1.07

1.29 1.19

1.48 1.30

1.58 1.36

E-21

Operating Performance of Diverging Diamond Interchanges

Table E - 10 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2700 vph with different off-ramp
demands and through/left proportions for LC2

Proportion Approach

100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2700 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.67 1.45

0.70

1.54

0.90 1.23

0.88

1.33

0.86 0.86

0.91

0.92

1.50 1.10

1.62

1.20

2.52 1.39

2.67

1.54

3.50 1.58

3.72

1.69

3.89 1.69

4.14

1.84

0.74 0.71

0.88

0.77

0.71 0.78

0.82

0.82

0.52 0.87

0.65

0.96

0.38 0.81

0.48

0.86

0.25 0.68

0.32

0.76

0.12 0.45

0.18

0.61

0.06 0.35

0.11

0.46

0.00 0.00

0.00

0.00

0.58 0.11

0.61

0.11

0.88 0.32

0.91

0.32

0.68 0.45

0.69

0.42

0.49 0.50

0.50

0.47

0.43 0.58

0.44

0.53

0.43 0.57

0.44

0.55

0.57 0.11

0.78

0.23

0.50 0.11

0.74

0.24

0.68 0.12

0.85

0.26

0.87 0.15

1.03

0.29

1.02 0.19

1.24

0.35

1.13 0.24

1.30

0.44

1.13 0.35

1.30

0.46

0.74 0.71

0.88

0.78

0.71 0.78

0.82

0.83

0.52 0.86

0.65

0.95

0.38 0.79

0.48

0.84

0.25 0.65

0.32

0.76

0.12 0.45

0.18

0.59

0.06 0.28

0.12

0.44

0.00 0.00

0.00

0.00

0.58 0.11

0.59

0.11

0.86 0.32

0.91

0.32

0.68 0.46

0.68

0.43

0.49 0.52

0.50

0.47

0.44 0.58

0.43

0.55

0.44 0.61

0.43

0.56

0.67 1.47

0.70

1.57

0.90 1.25

0.88

1.35

0.87 0.86

0.91

0.93

1.52 1.13

1.59

1.22

2.57 1.43

2.67

1.54

3.57 1.58

3.72

1.73

3.97 1.80

4.14

1.88

0.57 0.11

0.79

0.23

0.50 0.11

0.75

0.23

0.68 0.12

0.85

0.25

0.87 0.15

1.08

0.28

1.02 0.18

1.24

0.35

1.13 0.24

1.38

0.42

1.13 0.28

1.38

0.44

0.72 1.00

0.86

1.06

0.77 0.97

0.80

1.02

0.85 0.86

0.90

0.94

1.01 0.96

1.07

1.02

1.18 1.11

1.25

1.17

1.39 1.23

1.45

1.29

1.51 1.36

1.57

1.35

CDI

DDI

1800 vph

0.74 1.68

0.93 1.43

0.99 1.02

1.74 1.29

2.84 1.65

3.89 1.87

4.32 2.04

1.05 0.85

0.99 0.89

0.81 0.99

0.59 0.94

0.40 0.84

0.24

0.72

0.18

0.59

0.00

0.00

0.63

0.11

1.02

0.32

0.69

0.39

0.50

0.43

0.45

0.48

0.45

0.48

0.99

0.36

0.94

0.37

0.98

0.39

1.16

0.43

1.40

0.49

1.50

0.58

1.50

0.59

1.05

0.85

0.99

0.89

0.83

0.99

0.59

0.93

0.40

0.83

0.24

0.70

0.18

0.56

0.00

0.00

0.61

0.11

1.00

0.32

0.68

0.40

0.50

0.43

0.45

0.49

0.45 0.50

0.74 1.68

0.94 1.46

1.00 1.03

1.74 1.31

2.84 1.66

3.89 1.91

4.32 2.12

0.99 0.36

0.94 0.36

0.98 0.39

1.19 0.42

1.40 0.49

1.50 0.56

1.50 0.56

1.04 1.12

0.98 1.08

1.00 1.00

1.14 1.09

1.32 1.23

1.54 1.36

1.65 1.42

E-22

E.2.2

Operating Performance of Diverging Diamond Interchanges Plots of Difference between CDI and DDI v/c Ratios

Figure E - 9 Difference in v/c ratios between CDI and DDI on NBT1 at different traffic demands and through/left proportions for LC2

E-23

Operating Performance of Diverging Diamond Interchanges
Figure E - 10 Difference in v/c ratios between CDI and DDI on SBT1 at different traffic demands and through/left proportions for LC2
Figure E - 11 Difference in v/c ratios between CDI and DDI on SBL1 at different traffic demands and through/left proportions for LC2 E-24

Operating Performance of Diverging Diamond Interchanges
Figure E - 12 Difference in v/c ratios between CDI and DDI on EBL1 at different traffic demands and through/left proportions for LC2
Figure E - 13 Difference in v/c ratios between CDI and DDI on NBT2 at different traffic demands and through/left proportions for LC2 E-25

Operating Performance of Diverging Diamond Interchanges
Figure E - 14 Difference in v/c ratios between CDI and DDI on NBL2 at different traffic demands and through/left proportions for LC2
Figure E - 15 Difference in v/c ratios between CDI and DDI on SBT2 at different traffic demands and through/left proportions for LC2 E-26

Operating Performance of Diverging Diamond Interchanges
Figure E - 16 Difference in v/c ratios between CDI and DDI on WBL2 at different traffic demands and through/left proportions for LC2
E-27

Operating Performance of Diverging Diamond Interchanges

E.3

Lane Configuration 3

The following tables and plots present the difference in the CDI and DDI v/c ratios on different turning movements traffic demands and through/left proportions for LC3.

E.3.1

Color-Coded Tables of v/c Ratios of CDIs and DDIs

E-28

Operating Performance of Diverging Diamond Interchanges

Table E - 11 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1000 vph and (b) cross-street demand of 1500 vph with different off-ramp demands and through/left proportions
for LC3

(a)

(b)

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 1000 vph

CDI DDI CDI DDI

200 vph

500 vph

0.28 0.60 0.33 0.67

0.39 0.51 0.47 0.57

0.39 0.39 0.44 0.41

0.31 0.25 0.34 0.28

0.50 0.32 0.50 0.35

0.64 0.36 0.72 0.39

0.75 0.35 0.80 0.43

0.32 0.44 0.44 0.48

0.29 0.41 0.40 0.45

0.24 0.36 0.33 0.42

0.18 0.30 0.25 0.35

0.12 0.22 0.19 0.29

0.06 0.14 0.12 0.23

0.03 0.09 0.09 0.17

0.00 0.00 0.00 0.00

0.11 0.02 0.14 0.02

0.25 0.06 0.27 0.06

0.33 0.10 0.38 0.10

0.41 0.14 0.47 0.14

0.45 0.18 0.49 0.18

0.48 0.20 0.52 0.20

0.13 0.05 0.26 0.11

0.13 0.05 0.26 0.12

0.16 0.05 0.28 0.13

0.18 0.06 0.31 0.14

0.18 0.07 0.35 0.15

0.21 0.08 0.34 0.17

0.21 0.09 0.38 0.17

0.32 0.42 0.44 0.46

0.29 0.40 0.40 0.44

0.24 0.34 0.33 0.41

0.18 0.28 0.25 0.34

0.12 0.22 0.19 0.28

0.06 0.13 0.12 0.21

0.03 0.08 0.09 0.16

0.00 0.00 0.00 0.00

0.10 0.02 0.13 0.02

0.23 0.06 0.25 0.06

0.33 0.10 0.36 0.10

0.41 0.14 0.44 0.14

0.45 0.18 0.49 0.18

0.46 0.20 0.52 0.20

0.28 0.63 0.33 0.71

0.40 0.54 0.50 0.60

0.41 0.41 0.47 0.44

0.31 0.26 0.36 0.29

0.49 0.32 0.54 0.37

0.64 0.38 0.68 0.43

0.80 0.38 0.80 0.48

0.13 0.05 0.26 0.11

0.13 0.05 0.26 0.11

0.16 0.05 0.28 0.13

0.18 0.06 0.31 0.13

0.19 0.07 0.35 0.14

0.21 0.07 0.38 0.16

0.21 0.08 0.38 0.16

0.28 0.49 0.39 0.53

0.26 0.44 0.36 0.49

0.30 0.36 0.32 0.41

0.30 0.27 0.35 0.31

0.40 0.27 0.45 0.31

0.48 0.27 0.53 0.31

0.53 0.26 0.58 0.31

CDI DDI 800 vph
0.35 0.68 0.48 0.57 0.48 0.44 0.36 0.28 0.54 0.37 0.72 0.41 0.80 0.45 0.52 0.54 0.49 0.53 0.42 0.48 0.33 0.43 0.26 0.36 0.18 0.32 0.15 0.26 0.00 0.00 0.17 0.02 0.30 0.06 0.42 0.10 0.50 0.14 0.54 0.18 0.57 0.20 0.38 0.18 0.38 0.19 0.38 0.20 0.42 0.22 0.45 0.23 0.46 0.26 0.50 0.26 0.52 0.51 0.48 0.49 0.42 0.46 0.33 0.40 0.26 0.33 0.18 0.27 0.15 0.23 0.00 0.00 0.16 0.02 0.27 0.06 0.38 0.10 0.47 0.14 0.51 0.18 0.55 0.20 0.35 0.75 0.49 0.64 0.50 0.47 0.38 0.31 0.58 0.41 0.77 0.47 0.86 0.53 0.38 0.17 0.38 0.18 0.38 0.19 0.42 0.20 0.45 0.21 0.46 0.23 0.50 0.23 0.48 0.58 0.45 0.53 0.40 0.45 0.36 0.36 0.50 0.36 0.58 0.36 0.63 0.36

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 1500 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.44

0.95

0.47 1.06

0.65

0.86

0.64 0.92

0.58

0.60

0.71 0.67

0.45

0.41

0.53 0.43

0.71

0.50

0.77 0.55

0.95

0.56

1.08 0.64

1.17

0.60

1.20 0.68

0.53

0.62

0.69 0.62

0.52

0.60

0.67 0.69

0.41

0.55

0.61 0.65

0.30

0.47

0.47 0.58

0.21

0.38

0.35 0.52

0.12

0.27

0.24 0.42

0.08

0.20

0.20 0.36

0.00

0.00

0.00 0.00

0.21

0.03

0.24 0.03

0.41

0.09

0.45 0.09

0.50

0.15

0.56 0.15

0.59

0.21

0.64 0.21

0.65

0.27

0.61 0.27

0.58

0.30

0.56 0.30

0.33

0.11

0.59 0.22

0.31

0.11

0.54 0.23

0.35

0.13

0.52 0.26

0.38

0.14

0.55 0.28

0.42

0.16

0.60 0.31

0.49

0.18

0.65 0.34

0.49

0.20

0.69 0.36

0.53

0.63

0.69 0.63

0.52

0.60

0.66 0.67

0.41

0.53

0.60 0.64

0.30

0.47

0.45 0.56

0.21

0.36

0.35 0.49

0.12

0.26

0.24 0.38

0.08

0.18

0.20 0.31

0.00

0.00

0.00 0.00

0.19

0.03

0.22 0.03

0.38

0.09

0.44 0.09

0.47

0.15

0.56 0.15

0.57

0.21

0.64 0.21

0.63

0.27

0.61 0.27

0.55

0.30

0.58 0.30

0.44

1.00

0.47 1.10

0.67

0.86

0.66 0.96

0.62

0.63

0.72 0.69

0.47

0.41

0.50 0.45

0.73

0.53

0.77 0.58

0.99

0.59

1.08 0.71

1.12

0.63

1.26 0.79

0.34

0.11

0.59 0.21

0.31

0.11

0.54 0.23

0.35

0.12

0.52 0.25

0.38

0.14

0.59 0.27

0.43

0.15

0.60 0.30

0.49

0.17

0.65 0.31

0.53

0.18

0.69 0.31

0.49

0.75

0.66 0.76

0.47

0.68

0.63 0.75

0.48

0.56

0.58 0.64

0.45

0.43

0.55 0.50

0.60

0.43

0.67 0.52

0.73

0.43

0.76 0.52

0.75

0.43

0.79 0.52

CDI

DDI

1800 vph

0.48 1.14

0.60 1.01

0.63 0.72

0.55 0.47

0.86 0.60

1.16 0.68

1.35 0.75

0.83 0.73

0.81 0.70

0.76 0.68

0.67 0.70

0.53 0.63

0.41 0.57

0.36 0.50

0.00 0.00

0.27 0.03

0.50 0.09

0.63 0.15

0.70 0.21

0.64 0.27

0.58 0.30

0.78 0.36

0.77 0.34

0.72 0.35

0.67 0.42

0.70 0.45

0.78 0.50

0.81 0.50

0.83 0.73

0.81 0.71

0.76 0.67

0.67 0.66

0.53 0.59

0.41 0.49

0.36 0.44

0.00 0.00

0.26 0.03

0.48 0.09

0.60 0.15

0.69 0.21

0.64 0.27

0.58 0.30

0.48 1.24

0.61 1.08

0.64 0.76

0.57 0.53

0.85 0.66

1.17 0.81

1.35 0.90

0.78 0.35

0.78 0.33

0.72 0.34

0.67 0.40

0.72 0.42

0.78 0.44

0.81 0.44

0.82 0.86

0.80 0.80

0.75 0.69

0.67 0.61

0.74 0.61

0.83 0.61

0.85 0.61

E-29

Operating Performance of Diverging Diamond Interchanges

Table E - 12 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at (a) cross-street demand of 1800 vph and (b) cross-street demand of 2100 vph with different off-ramp demands and through/left proportions
for LC3

(a)

(b)

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 1800 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.51 1.15

0.52

1.25

0.75 1.01

0.69

1.10

0.70 0.71

0.77

0.77

0.54 0.45

0.57

0.50

0.80 0.58

0.88

0.66

1.08 0.65

1.19

0.75

1.28 0.67

1.37

0.82

0.60 0.60

0.72

0.66

0.59 0.65

0.70

0.68

0.46 0.61

0.64

0.72

0.34 0.54

0.48

0.62

0.22 0.44

0.36

0.56

0.12 0.31

0.24

0.44

0.08 0.22

0.18

0.36

0.00 0.00

0.00

0.00

0.24 0.04

0.28

0.04

0.45 0.11

0.50

0.11

0.57 0.18

0.63

0.18

0.63 0.25

0.71

0.25

0.63 0.32

0.61

0.32

0.56 0.36

0.56

0.36

0.38 0.11

0.65

0.23

0.35 0.11

0.60

0.23

0.39 0.12

0.54

0.25

0.42 0.14

0.60

0.27

0.46 0.16

0.66

0.31

0.56 0.20

0.72

0.35

0.59 0.22

0.76

0.36

0.60 0.61

0.72

0.67

0.59 0.65

0.70

0.68

0.46 0.60

0.64

0.70

0.34 0.52

0.48

0.60

0.22 0.43

0.35

0.54

0.12 0.29

0.24

0.43

0.08 0.20

0.18

0.34

0.00 0.00

0.00

0.00

0.26 0.04

0.26

0.04

0.45 0.11

0.48

0.11

0.55 0.18

0.63

0.18

0.63 0.25

0.70

0.25

0.63 0.32

0.61

0.32

0.56 0.36

0.56

0.36

0.51 1.20

0.52

1.31

0.74 1.00

0.70

1.11

0.70 0.74

0.78

0.80

0.55 0.47

0.57

0.53

0.80 0.60

0.90

0.70

1.08 0.68

1.19

0.78

1.27 0.72

1.37

0.87

0.38 0.11

0.65

0.22

0.35 0.11

0.60

0.23

0.39 0.12

0.54

0.25

0.43 0.13

0.60

0.26

0.47 0.16

0.66

0.30

0.56 0.18

0.72

0.34

0.59 0.20

0.76

0.34

0.56 0.80

0.71

0.86

0.53 0.77

0.68

0.81

0.56 0.64

0.61

0.72

0.53 0.49

0.60

0.56

0.67 0.50

0.75

0.59

0.77 0.50

0.81

0.59

0.80 0.50

0.84

0.59

CDI DDI 1800 vph
0.54 1.35 0.64 1.19 0.72 0.86 0.62 0.56 0.99 0.71 1.28 0.81 1.53 0.90 0.87 0.70 0.85 0.74 0.81 0.83 0.68 0.74 0.54 0.65 0.39 0.58 0.33 0.50 0.00 0.00 0.34 0.04 0.60 0.11 0.69 0.18 0.78 0.25 0.61 0.32 0.54 0.33 0.83 0.34 0.80 0.35 0.75 0.39 0.71 0.41 0.78 0.44 0.84 0.50 0.85 0.50 0.88 0.71 0.85 0.74 0.81 0.81 0.68 0.72 0.53 0.63 0.39 0.52 0.33 0.45 0.00 0.00 0.32 0.04 0.58 0.11 0.68 0.18 0.77 0.25 0.61 0.32 0.54 0.36 0.54 1.44 0.65 1.23 0.74 0.89 0.63 0.58 0.99 0.74 1.32 0.93 1.53 1.03 0.82 0.33 0.80 0.34 0.75 0.38 0.72 0.40 0.78 0.43 0.84 0.45 0.85 0.45 0.86 0.90 0.83 0.87 0.79 0.82 0.69 0.66 0.84 0.66 0.87 0.68 0.88 0.68

Proportion Approach

100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2100 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.57

1.33 0.58 1.44

0.72

1.15 0.75 1.22

0.77

0.78 0.82 0.87

0.57

0.51 0.63 0.57

0.85

0.65 0.93 0.71

1.23

0.73 1.30 0.82

1.42

0.74 1.53 0.91

0.65

0.60 0.77 0.64

0.60

0.65 0.75 0.69

0.51

0.70 0.67 0.78

0.36

0.60 0.51 0.67

0.24

0.47 0.36 0.61

0.13

0.35 0.23 0.50

0.07

0.22 0.18 0.38

0.00

0.00 0.00 0.00

0.29

0.04 0.32 0.04

0.53

0.13 0.55 0.13

0.64

0.21 0.69 0.21

0.72

0.29 0.75 0.29

0.60

0.38 0.60 0.38

0.54

0.42 0.53 0.42

0.44

0.11 0.69 0.22

0.40

0.11 0.65 0.23

0.45

0.12 0.57 0.25

0.49

0.14 0.65 0.27

0.56

0.16 0.72 0.32

0.63

0.21 0.78 0.38

0.66

0.22 0.81 0.38

0.65

0.60 0.77 0.64

0.60

0.65 0.75 0.70

0.51

0.68 0.66 0.77

0.36

0.58 0.50 0.67

0.24

0.46 0.36 0.59

0.13

0.33 0.23 0.47

0.07

0.21 0.18 0.36

0.00

0.00 0.00 0.00

0.28

0.04 0.30 0.04

0.53

0.13 0.55 0.13

0.61

0.21 0.67 0.21

0.70

0.29 0.75 0.29

0.60

0.38 0.60 0.38

0.55

0.42 0.54 0.42

0.57

1.35 0.58 1.48

0.73

1.15 0.76 1.26

0.77

0.81 0.79 0.90

0.59

0.53 0.64 0.57

0.88

0.67 0.93 0.74

1.22

0.76 1.32 0.86

1.45

0.76 1.56 0.95

0.44

0.10 0.69 0.21

0.40

0.11 0.65 0.22

0.45

0.12 0.60 0.24

0.49

0.13 0.66 0.26

0.56

0.15 0.72 0.31

0.64

0.20 0.79 0.36

0.66

0.21 0.81 0.36

0.62

0.85 0.75 0.89

0.57

0.82 0.73 0.87

0.63

0.72 0.64 0.81

0.58

0.54 0.66 0.62

0.75

0.56 0.81 0.64

0.82

0.57 0.86 0.66

0.85

0.56 0.89 0.66

CDI

DDI

1800 vph

0.60 1.52

0.69 1.31

0.82 0.93

0.69 0.63

1.03 0.76

1.45 0.91

1.68 1.01

0.92 0.71

0.89 0.74

0.83 0.84

0.69 0.79

0.52 0.72

0.38 0.58

0.32 0.52

0.00 0.00

0.40 0.04

0.58 0.13

0.75 0.21

0.76 0.29

0.61 0.38

0.54 0.37

0.88 0.34

0.84 0.34

0.78 0.37

0.77 0.41

0.84 0.46

0.88 0.49

0.92 0.52

0.92 0.71

0.89 0.74

0.83 0.82

0.69 0.77

0.52 0.68

0.38 0.55

0.31 0.49

0.00 0.00

0.39 0.04

0.63 0.13

0.75 0.21

0.76 0.29

0.60 0.38

0.53 0.40

0.60 1.59

0.69 1.37

0.78 0.98

0.68 0.65

1.03 0.82

1.42 0.98

1.68 1.08

0.88 0.33

0.84 0.34

0.78 0.36

0.78 0.40

0.84 0.44

0.90 0.46

0.94 0.49

0.91 0.95

0.87 0.92

0.82 0.87

0.72 0.72

0.87 0.73

0.92 0.73

0.95 0.74

E-30

Operating Performance of Diverging Diamond Interchanges

Table E - 13 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2300 vph with different off-ramp
demands and through/left proportions for LC3

Proportion Approach

100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2300 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.59 1.45 0.62 1.56

0.73 1.22 0.77 1.32

0.82 0.85 0.87 0.92

0.61 0.54 0.65 0.59

0.91 0.69 1.02 0.77

1.32 0.75 1.41 0.90

1.53 0.79 1.62 0.95

0.67 0.60 0.81 0.64

0.64 0.66 0.78 0.68

0.54 0.74 0.70 0.80

0.38 0.63 0.52 0.72

0.24 0.52 0.37 0.64

0.13 0.36 0.23 0.51

0.07 0.26 0.17 0.38

0.00 0.00 0.00 0.00

0.34 0.05 0.35 0.05

0.54 0.14 0.60 0.14

0.66 0.23 0.74 0.23

0.73 0.32 0.75 0.32

0.60 0.41 0.59 0.41

0.52 0.46 0.53 0.46

0.47 0.10 0.72 0.21

0.42 0.11 0.69 0.22

0.42 0.12 0.60 0.24

0.50 0.14 0.69 0.27

0.60 0.16 0.75 0.32

0.67 0.21 0.83 0.38

0.71 0.26 0.88 0.38

0.67 0.60 0.81 0.64

0.64 0.66 0.78 0.69

0.52 0.72 0.68 0.79

0.38 0.62 0.52 0.70

0.24 0.50 0.37 0.61

0.13 0.34 0.23 0.48

0.07 0.22 0.17 0.36

0.00 0.00 0.00 0.00

0.32 0.05 0.33 0.05

0.55 0.14 0.60 0.14

0.66 0.23 0.71 0.23

0.73 0.32 0.75 0.32

0.60 0.41 0.59 0.41

0.52 0.46 0.54 0.46

0.59 1.45 0.62 1.56

0.74 1.25 0.78 1.35

0.77 0.88 0.83 0.94

0.61 0.56 0.67 0.61

0.90 0.72 1.02 0.81

1.31 0.78 1.41 0.94

1.55 0.85 1.66 0.99

0.47 0.10 0.72 0.21

0.42 0.11 0.69 0.22

0.47 0.12 0.64 0.24

0.50 0.13 0.69 0.26

0.61 0.16 0.75 0.31

0.68 0.20 0.83 0.36

0.72 0.22 0.88 0.36

0.64 0.88 0.79 0.92

0.60 0.87 0.76 0.90

0.65 0.78 0.72 0.84

0.61 0.58 0.69 0.66

0.79 0.60 0.84 0.69

0.86 0.60 0.89 0.71

0.87 0.62 0.93 0.69

CDI

DDI

1800 vph

0.65 1.38

0.74 1.08

0.82 1.03

0.71 0.68

1.10 0.86

1.55 0.97

1.80 1.07

0.96 0.78

0.92 0.86

0.86 0.83

0.71 0.78

0.53 0.73

0.38 0.61

0.31 0.51

0.00 0.00

0.43 0.05

0.68 0.14

0.83 0.23

0.76 0.32

0.59 0.38

0.53 0.38

0.92 0.36

0.88 0.40

0.79 0.36

0.84 0.39

0.86 0.45

0.94 0.51

0.99 0.51

0.96 0.79

0.92 0.88

0.86 0.83

0.71 0.77

0.53 0.73

0.38 0.58

0.31 0.48

0.00 0.00

0.41 0.05

0.66 0.14

0.80 0.23

0.76 0.32

0.59 0.41

0.53 0.41

0.65 1.73

0.74 1.49

0.83 1.04

0.74 0.70

1.10 0.86

1.55 1.03

1.84 1.14

0.92 0.33

0.88 0.33

0.80 0.36

0.84 0.38

0.86 0.45

0.94 0.48

0.99 0.48

0.95 1.05

0.91 1.05

0.84 0.89

0.79 0.74

0.89 0.77

0.96 0.77

0.99 0.77

CDI DDI 2100 vph
0.67 1.73 0.75 1.49 0.80 1.05 0.74 0.70 1.12 0.88 1.62 1.00 1.84 1.12 1.05 0.74 1.00 0.77 0.90 0.84 0.80 0.85 0.60 0.75 0.43 0.65 0.34 0.55 0.00 0.00 0.44 0.05 0.64 0.14 0.84 0.23 0.76 0.32 0.60 0.37 0.54 0.37 0.98 0.38 0.95 0.39 0.88 0.41 0.85 0.45 0.91 0.49 0.98 0.55 1.05 0.55 1.05 0.74 0.99 0.77 0.90 0.84 0.80 0.84 0.60 0.74 0.44 0.62 0.34 0.53 0.00 0.00 0.43 0.05 0.63 0.14 0.82 0.23 0.76 0.32 0.59 0.39 0.54 0.39 0.67 1.80 0.75 1.55 0.80 1.09 0.77 0.71 1.14 0.89 1.59 1.07 1.88 1.19 0.98 0.38 0.96 0.38 0.88 0.40 0.85 0.45 0.91 0.49 1.01 0.53 1.05 0.53 1.03 1.02 0.98 0.98 0.89 0.92 0.81 0.79 0.92 0.79 0.99 0.80 1.03 0.80

E-31

Operating Performance of Diverging Diamond Interchanges

Table E - 14 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2500 vph with different off-ramp
demands and through/left proportions for LC3

Proportion
100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

Approach NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2500 vph

CDI

DDI CDI

DDI

500 vph

1100 vph

0.64 1.55 0.66 1.67

0.74 1.33 0.81 1.42

0.84 0.92 0.88 1.00

0.63 0.58 0.70 0.64

0.97 0.72 1.07 0.82

1.41 0.86 1.50 0.93

1.61 0.86 1.73 1.00

0.72 0.59 0.84 0.64

0.66 0.64 0.81 0.68

0.56 0.77 0.71 0.80

0.39 0.67 0.54 0.75

0.25 0.55 0.37 0.65

0.13 0.38 0.23 0.51

0.07 0.26 0.17 0.39

0.00 0.00 0.00 0.00

0.38 0.05 0.38 0.05

0.60 0.15 0.63 0.15

0.70 0.25 0.78 0.25

0.77 0.35 0.75 0.35

0.59 0.45 0.60 0.45

0.53 0.50 0.54 0.46

0.48 0.10 0.77 0.21

0.45 0.11 0.71 0.22

0.47 0.12 0.65 0.24

0.56 0.13 0.73 0.26

0.66 0.16 0.80 0.31

0.72 0.21 0.90 0.38

0.80 0.26 0.95 0.39

0.72 0.59 0.84 0.64

0.66 0.64 0.81 0.69

0.56 0.76 0.71 0.81

0.39 0.65 0.54 0.73

0.25 0.53 0.37 0.65

0.13 0.38 0.23 0.49

0.07 0.22 0.17 0.38

0.00 0.00 0.00 0.00

0.36 0.05 0.36 0.05

0.60 0.15 0.63 0.15

0.68 0.25 0.77 0.25

0.77 0.35 0.75 0.35

0.59 0.45 0.60 0.45

0.54 0.50 0.54 0.48

0.64 1.55 0.66 1.70

0.75 1.36 0.82 1.45

0.84 0.93 0.88 1.02

0.64 0.59 0.71 0.65

0.96 0.74 1.07 0.82

1.41 0.86 1.50 0.96

1.64 0.93 1.76 1.03

0.49 0.10 0.77 0.21

0.45 0.10 0.72 0.22

0.47 0.12 0.65 0.24

0.56 0.13 0.73 0.26

0.66 0.16 0.80 0.31

0.72 0.21 0.90 0.36

0.80 0.22 0.95 0.38

0.69 0.91 0.83 0.97

0.63 0.89 0.79 0.93

0.70 0.82 0.75 0.88

0.65 0.62 0.74 0.69

0.83 0.64 0.87 0.72

0.89 0.67 0.94 0.74

0.92 0.67 0.98 0.74

CDI

DDI

1800 vph

0.70 1.80

0.79 1.56

0.85 1.09

0.76 0.71

1.14 0.88

1.62 1.02

1.91 1.13

1.01 0.72

0.96 0.75

0.87 0.84

0.71 0.84

0.53 0.75

0.36 0.64

0.27 0.53

0.00 0.00

0.45 0.05

0.70 0.15

0.81 0.25

0.76 0.35

0.60 0.39

0.54 0.39

0.94 0.33

0.91 0.34

0.82 0.36

0.81 0.40

0.91 0.45

1.01 0.52

1.07 0.53

1.01 0.72

0.96 0.75

0.87 0.84

0.71 0.83

0.53 0.73

0.36 0.60

0.27 0.49

0.00 0.00

0.43 0.05

0.68 0.15

0.81 0.25

0.76 0.35

0.60 0.42

0.54 0.42

0.70 1.84

0.79 1.59

0.86 1.11

0.76 0.72

1.17 0.90

1.65 1.09

1.91 1.21

0.94 0.33

0.91 0.34

0.82 0.36

0.82 0.39

0.91 0.44

1.01 0.49

1.07 0.49

0.99 1.03

0.94 0.99

0.86 0.92

0.79 0.78

0.93 0.80

1.01 0.82

1.04 0.82

CDI

DDI

2100 vph

0.71 1.84

0.81 1.59

0.89 1.13

0.78 0.73

1.21 0.90

1.72 1.04

2.00 1.14

1.06 0.75

1.03 0.78

0.94 0.87

0.80 0.86

0.61 0.79

0.41 0.67

0.32 0.58

0.00 0.00

0.45 0.05

0.65 0.15

0.85 0.25

0.75 0.35

0.59 0.39

0.53 0.38

1.03 0.39

0.98 0.39

0.89 0.41

0.86 0.44

0.95 0.50

1.05 0.56

1.10 0.58

1.06 0.76

1.03 0.78

0.94 0.87

0.80 0.85

0.61 0.76

0.41 0.64

0.32 0.54

0.00 0.00

0.44 0.05

0.64 0.15

0.85 0.25

0.75 0.35

0.59 0.41

0.53 0.42

0.71 1.91

0.81 1.65

0.89 1.15

0.78 0.74

1.21 0.95

1.72 1.09

2.00 1.25

1.03 0.38

0.98 0.39

0.89 0.41

0.86 0.44

0.95 0.49

1.05 0.54

1.10 0.54

1.05 1.07

1.02 1.03

0.92 0.95

0.82 0.81

0.95 0.83

1.03 0.84

1.07 0.85

E-32

Operating Performance of Diverging Diamond Interchanges

Table E - 15 Color-coded tables of the CDI and DDI turning movement and interchange v/c ratios at cross-street demand of 2700 vph with different off-ramp
demands and through/left proportions for LC3

Proportion Approach

100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100 100 0 90 10 70 30 50 50 30 70 10 90 0 100

NBT1 SBT1 SBL1 EBL1 NBT2 NBL2 SBT2 WBL2 Int v/c

JC Volume 2700 vph

CDI

DDI

CDI

DDI

500 vph

1100 vph

0.67 1.65

0.70

1.77

0.77 1.40

0.85

1.51

0.85 0.96

0.90

1.05

0.66 0.61

0.70

0.68

1.02 0.80

1.12

0.85

1.48 0.90

1.59

0.97

1.74 0.93

1.87

1.04

0.74 0.59

0.88

0.66

0.69 0.64

0.84

0.70

0.58 0.80

0.73

0.81

0.41 0.71

0.53

0.79

0.26 0.60

0.38

0.70

0.13 0.42

0.24

0.55

0.07 0.26

0.17

0.46

0.00 0.00

0.00

0.00

0.40 0.05

0.40

0.05

0.63 0.16

0.65

0.16

0.72 0.27

0.77

0.27

0.75 0.38

0.75

0.38

0.60 0.49

0.59

0.46

0.54 0.54

0.53

0.47

0.57 0.10

0.80

0.21

0.49 0.10

0.76

0.22

0.49 0.11

0.65

0.23

0.57 0.13

0.73

0.27

0.69 0.17

0.83

0.32

0.82 0.22

0.95

0.39

0.87 0.26

0.99

0.46

0.74 0.60

0.88

0.66

0.69 0.65

0.84

0.70

0.58 0.79

0.73

0.81

0.40 0.69

0.53

0.77

0.26 0.60

0.38

0.68

0.13 0.39

0.24

0.52

0.07 0.24

0.17

0.42

0.00 0.00

0.00

0.00

0.39 0.05

0.39

0.05

0.60 0.16

0.65

0.16

0.71 0.27

0.76

0.27

0.75 0.38

0.74

0.38

0.60 0.49

0.59

0.49

0.54 0.54

0.54

0.49

0.67 1.68

0.70

1.80

0.78 1.42

0.85

1.53

0.88 0.98

0.90

1.06

0.67 0.63

0.71

0.69

1.04 0.80

1.12

0.88

1.48 0.93

1.62

1.01

1.74 0.96

1.91

1.10

0.57 0.10

0.80

0.21

0.49 0.10

0.76

0.22

0.49 0.11

0.65

0.23

0.60 0.13

0.73

0.26

0.70 0.17

0.85

0.31

0.82 0.21

0.95

0.38

0.87 0.24

0.99

0.42

0.72 0.96

0.86

1.01

0.66 0.92

0.82

0.97

0.73 0.86

0.77

0.90

0.68 0.65

0.73

0.73

0.86 0.70

0.90

0.76

0.93 0.72

0.98

0.78

0.96 0.72

1.02

0.81

CDI

DDI

1800 vph

0.74 1.91

0.84 1.65

0.89 1.15

0.78 0.74

1.24 0.93

1.75 1.06

2.03 1.18

1.05 0.73

0.99 0.76

0.89 0.85

0.72 0.86

0.54 0.79

0.34 0.67

0.25 0.54

0.00 0.00

0.46 0.05

0.72 0.16

0.86 0.27

0.76 0.38

0.59 0.42

0.54 0.42

0.99 0.34

0.94 0.34

0.85 0.36

0.87 0.39

0.94 0.46

1.07 0.54

1.13 0.54

1.05 0.74

0.99 0.76

0.89 0.85

0.72 0.86

0.54 0.77

0.34 0.65

0.25 0.53

0.00 0.00

0.45 0.05

0.70 0.16

0.86 0.27

0.75 0.38

0.59

0.43

0.54

0.43

0.74

1.94

0.85

1.68

0.90

1.17

0.78

0.75

1.22

0.95

1.75

1.10

2.03

1.22

0.99

0.33

0.94

0.34

0.85

0.36

0.87

0.39

0.96

0.45

1.07

0.53

1.13

0.53

1.04

1.08

0.98

1.04

0.88

0.96

0.83

0.81

0.96

0.84

1.04

0.86

1.09

0.86

E-33

Operating Performance of Diverging Diamond Interchanges

E.3.2

Plots of Difference between CDI and DDI v/c Ratios

Figure E - 17 Difference in v/c ratios between CDI and DDI on NBT1 at different traffic demands and through/left proportions for LC3

E-34

Operating Performance of Diverging Diamond Interchanges
Figure E - 18 Difference in v/c ratios between CDI and DDI on SBT1 at different traffic demands and through/left proportions for LC3
Figure E - 19 Difference in v/c ratios between CDI and DDI on SBL1 at different traffic demands and through/left proportions for LC3 E-35

Operating Performance of Diverging Diamond Interchanges
Figure E - 20 Difference in v/c ratios between CDI and DDI on EBL1 at different traffic demands and through/left proportions for LC3
Figure E - 21 Difference in v/c ratios between CDI and DDI on NBT2 at different traffic demands and through/left proportions for LC3 E-36

Operating Performance of Diverging Diamond Interchanges
Figure E - 22 Difference in v/c ratios between CDI and DDI on NBL2 at different traffic demands and through/left proportions for LC3
Figure E - 23 Difference in v/c ratios between CDI and DDI on SBT2 at different traffic demands and through/left proportions for LC3 E-37

Operating Performance of Diverging Diamond Interchanges
Figure E - 24 Difference in v/c ratios between CDI and DDI on WBL2 at different traffic demands and through/left proportions for LC3
E-38

Operating Performance of Diverging Diamond Interchanges
APPENDIX F. MICROSCOPIC SIMULATION STUDY RESULTS List of Figures
Figure F - 1 DDI and CDI average delay per vehicle and throughput on NBT with crossstreet demand of 1500 vph at different off-ramp demands and through/left proportions for LC1 .................................................................................................F-9
Figure F - 2 DDI and CDI average delay per vehicle and throughput on EBL with crossstreet demand of 1500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-10
Figure F - 3 DDI and CDI average delay per vehicle and throughput on NBL with crossstreet demand of 1500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-10
Figure F - 4 DDI and CDI average delay per vehicle and throughput on SBT with crossstreet demand of 1500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-11
Figure F - 5 DDI and CDI average delay per vehicle and throughput on WBL with crossstreet demand of 1500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-11
Figure F - 6 DDI and CDI average delay per vehicle and throughput on SBL with crossstreet demand of 1500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-12
F-1

Operating Performance of Diverging Diamond Interchanges Figure F - 7 DDI and CDI average delay per vehicle and throughput on NBT with cross-
street demand of 2100 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-13 Figure F - 8 DDI and CDI average delay per vehicle and throughput on EBL with crossstreet demand of 2100 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-14 Figure F - 9 DDI and CDI average delay per vehicle and throughput on NBL with crossstreet demand of 2100 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-14 Figure F - 10 DDI and CDI average delay per vehicle and throughput on SBT with crossstreet demand of 2100 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-15 Figure F - 11 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-15 Figure F - 12 DDI and CDI average delay per vehicle and throughput on SBL with crossstreet demand of 2100 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-16 Figure F - 13 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-17
F-2

Operating Performance of Diverging Diamond Interchanges Figure F - 14 DDI and CDI average delay per vehicle and throughput on EBL with
cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-18 Figure F - 15 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-18 Figure F - 16 DDI and CDI average delay per vehicle and throughput on SBT with crossstreet demand of 2500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-19 Figure F - 17 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-19 Figure F - 18 DDI and CDI average delay per vehicle and throughput on SBL with crossstreet demand of 2500 vph at different off-ramp demands and through/left proportions for LC1 ...............................................................................................F-20 Figure F - 19 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-21 Figure F - 20 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-22
F-3

Operating Performance of Diverging Diamond Interchanges Figure F - 21 DDI and CDI average delay per vehicle and throughput on NBL with
cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-22 Figure F - 22 DDI and CDI average delay per vehicle and throughput on SBT with crossstreet demand of 1500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-23 Figure F - 23 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-23 Figure F - 24 DDI and CDI average delay per vehicle and throughput on SBL with crossstreet demand of 1500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-24 Figure F - 25 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-25 Figure F - 26 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-26 Figure F - 27 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-26
F-4

Operating Performance of Diverging Diamond Interchanges Figure F - 28 DDI and CDI average delay per vehicle and throughput on SBT with cross-
street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-27 Figure F - 29 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-27 Figure F - 30 DDI and CDI average delay per vehicle and throughput on SBL with crossstreet demand of 2100 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-28 Figure F - 31 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-29 Figure F - 32 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-30 Figure F - 33 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-30 Figure F - 34 DDI and CDI average delay per vehicle and throughput on SBT with crossstreet demand of 2500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-31
F-5

Operating Performance of Diverging Diamond Interchanges Figure F - 35 DDI and CDI average delay per vehicle and throughput on WBL with
cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-31 Figure F - 36 DDI and CDI average delay per vehicle and throughput on SBL with crossstreet demand of 2500 vph at different off-ramp demands and through/left proportions for LC2 ...............................................................................................F-32 Figure F - 37 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-33 Figure F - 38 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-34 Figure F - 39 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-34 Figure F - 40 DDI and CDI average delay per vehicle and throughput on SBT with crossstreet demand of 1500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-35 Figure F - 41 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-35
F-6

Operating Performance of Diverging Diamond Interchanges Figure F - 42 DDI and CDI average delay per vehicle and throughput on SBL with cross-
street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-36 Figure F - 43 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-37 Figure F - 44 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-38 Figure F - 45 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-38 Figure F - 46 DDI and CDI average delay per vehicle and throughput on SBT with crossstreet demand of 2100 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-39 Figure F - 47 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-39 Figure F - 48 DDI and CDI average delay per vehicle and throughput on SBL with crossstreet demand of 2100 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-40
F-7

Operating Performance of Diverging Diamond Interchanges Figure F - 49 DDI and CDI average delay per vehicle and throughput on NBT with
cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-41 Figure F - 50 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-42 Figure F - 51 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-42 Figure F - 52 DDI and CDI average delay per vehicle and throughput on SBT with crossstreet demand of 2500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-43 Figure F - 53 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-43 Figure F - 54 DDI and CDI average delay per vehicle and throughput on SBL with crossstreet demand of 2500 vph at different off-ramp demands and through/left proportions for LC3 ...............................................................................................F-44
F-8

Operating Performance of Diverging Diamond Interchanges

This appendix provides resultant plots of average delay per vehicle and throughput at different through/left proportions from the VISSIM simulation study. Each plot illustrates the performance measures of individual turning movements. Numbers in the legend represent different off-ramp demands tested in the simulation.

F.1 F.1.1

Lane Configuration 1 Cross-Street Demand 1500 vph

Figure F - 1 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 1500 vph at different off-ramp demands and through/left
proportions for LC1
F-9

Operating Performance of Diverging Diamond Interchanges
Figure F - 2 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 1500 vph at different off-ramp demands and through/left
proportions for LC1
Figure F - 3 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 1500 vph at different off-ramp demands and through/left
proportions for LC1 F-10

Operating Performance of Diverging Diamond Interchanges
Figure F - 4 DDI and CDI average delay per vehicle and throughput on SBT with cross-street demand of 1500 vph at different off-ramp demands and through/left
proportions for LC1
Figure F - 5 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC1 F-11

Operating Performance of Diverging Diamond Interchanges
Figure F - 6 DDI and CDI average delay per vehicle and throughput on SBL with cross-street demand of 1500 vph at different off-ramp demands and through/left
proportions for LC1
F-12

F.1.2

Operating Performance of Diverging Diamond Interchanges Cross-Street Demand 2100 vph

(%)
Figure F - 7 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 2100 vph at different off-ramp demands and through/left
proportions for LC1

F-13

Operating Performance of Diverging Diamond Interchanges
Figure F - 8 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 2100 vph at different off-ramp demands and through/left
proportions for LC1
Figure F - 9 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2100 vph at different off-ramp demands and through/left
proportions for LC1 F-14

Operating Performance of Diverging Diamond Interchanges
Figure F - 10 DDI and CDI average delay per vehicle and throughput on SBT with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC1
Figure F - 11 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC1 F-15

Operating Performance of Diverging Diamond Interchanges
Figure F - 12 DDI and CDI average delay per vehicle and throughput on SBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC1
F-16

F.1.3

Operating Performance of Diverging Diamond Interchanges Cross-Street Demand 2500 vph

Figure F - 13 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1

F-17

Operating Performance of Diverging Diamond Interchanges
Figure F - 14 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1
Figure F - 15 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1 F-18

Operating Performance of Diverging Diamond Interchanges
Figure F - 16 DDI and CDI average delay per vehicle and throughput on SBT with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1
Figure F - 17 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1 F-19

Operating Performance of Diverging Diamond Interchanges
Figure F - 18 DDI and CDI average delay per vehicle and throughput on SBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC1
F-20

F.2 F.2.1

Operating Performance of Diverging Diamond Interchanges Lane Configuration 2
Cross-Street Demand 1500 vph

Figure F - 19 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2
F-21

Operating Performance of Diverging Diamond Interchanges
Figure F - 20 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2
Figure F - 21 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2 F-22

Operating Performance of Diverging Diamond Interchanges
Figure F - 22 DDI and CDI average delay per vehicle and throughput on SBT with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2
Figure F - 23 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2 F-23

Operating Performance of Diverging Diamond Interchanges
Figure F - 24 DDI and CDI average delay per vehicle and throughput on SBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC2
F-24

F.2.2

Operating Performance of Diverging Diamond Interchanges Cross-Street Demand 2100 vph

Figure F - 25 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2

F-25

Operating Performance of Diverging Diamond Interchanges
(%)
Figure F - 26 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2
Figure F - 27 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2 F-26

Operating Performance of Diverging Diamond Interchanges
Figure F - 28 DDI and CDI average delay per vehicle and throughput on SBT with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2
Figure F - 29 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2 F-27

Operating Performance of Diverging Diamond Interchanges
Figure F - 30 DDI and CDI average delay per vehicle and throughput on SBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC2
F-28

F.2.3

Operating Performance of Diverging Diamond Interchanges Cross-Street Demand 2500 vph

Figure F - 31 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2

F-29

Operating Performance of Diverging Diamond Interchanges
Figure F - 32 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2
Figure F - 33 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2 F-30

Operating Performance of Diverging Diamond Interchanges
Figure F - 34 DDI and CDI average delay per vehicle and throughput on SBT with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2
Figure F - 35 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2 F-31

Operating Performance of Diverging Diamond Interchanges
Figure F - 36 DDI and CDI average delay per vehicle and throughput on SBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC2
F-32

F.3 F.3.1

Operating Performance of Diverging Diamond Interchanges Lane Configuration 3
Cross-Street Demand 1500 vph

Figure F - 37 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3
F-33

Operating Performance of Diverging Diamond Interchanges
Figure F - 38 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3
Figure F - 39 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3 F-34

Operating Performance of Diverging Diamond Interchanges
Figure F - 40 DDI and CDI average delay per vehicle and throughput on SBT with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3
(%)
Figure F - 41 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3 F-35

Operating Performance of Diverging Diamond Interchanges
(%)
Figure F - 42 DDI and CDI average delay per vehicle and throughput on SBL with cross-street demand of 1500 vph at different off-ramp demands and through/left proportions for LC3
F-36

F.3.2

Operating Performance of Diverging Diamond Interchanges Cross-Street Demand 2100 vph

Figure F - 43 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3

F-37

Operating Performance of Diverging Diamond Interchanges
Figure F - 44 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3
Figure F - 45 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3 F-38

Operating Performance of Diverging Diamond Interchanges
Figure F - 46 DDI and CDI average delay per vehicle and throughput on SBT with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3
Figure F - 47 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3 F-39

Operating Performance of Diverging Diamond Interchanges
Figure F - 48 DDI and CDI average delay per vehicle and throughput on SBL with cross-street demand of 2100 vph at different off-ramp demands and through/left proportions for LC3
F-40

F.3.3

Operating Performance of Diverging Diamond Interchanges Cross-Street Demand 2500 vph

Figure F - 49 DDI and CDI average delay per vehicle and throughput on NBT with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3

F-41

Operating Performance of Diverging Diamond Interchanges
Figure F - 50 DDI and CDI average delay per vehicle and throughput on EBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3
Figure F - 51 DDI and CDI average delay per vehicle and throughput on NBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3 F-42

Operating Performance of Diverging Diamond Interchanges
Figure F - 52 DDI and CDI average delay per vehicle and throughput on SBT with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3
Figure F - 53 DDI and CDI average delay per vehicle and throughput on WBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3 F-43

Operating Performance of Diverging Diamond Interchanges
Figure F - 54 DDI and CDI average delay per vehicle and throughput on SBL with cross-street demand of 2500 vph at different off-ramp demands and through/left proportions for LC3
F-44