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Publication Number: FHWA-HRT-10-038
Date: October 2010

Balancing Safety and Capacity in an Adaptive Signal Control System — Phase 1

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Foreword

Virtually all previous research addressing intersection safety and capacity has dealt with the two issues independently. Over the past 20 years, advancements in real-time adaptive signal timing strategies for intersections and arterials have improved signal operations by improving traffic flow efficiency, but most optimization algorithms do not include performance measures for safety. At this time, little is known about the relationships between signal timing parameters (e.g., cycle time, offsets, phase sequence, etc.) and safety that can be of benefit to traffic engineering practitioners.

This research, comprising two phases, focuses on the development of real-time signal timing methodologies and algorithms that balance safety and efficiency. This report summarizes phase 1, which examines relationships between signal timing parameters and surrogate measures of safety such as rear-end, angle, and lane-change conflicts. These single variable relationship studies determine the parameters that are most likely to offer benefits in an adaptive, real-time strategy. Phase 1 also identifies an experimental design methodology to compute the effect of a change to signal timing parameters and develops both procedures for calculating performance and algorithms for improving the traffic system based on safety and existing principles of adaptive control used in the Federal Highway Administration (FHWA) Adaptive Control Systems (ACS) Lite system.

The ultimate objective of this research is to develop algorithms that can balance the performance of the traffic control system for both efficiency and safety and that can work with state-of-the-practice signal controllers.

Monique R. Evans

Director, Office of Safety

Research and Development

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document.

The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers' names appear in this report only because they are considered essential to the objective of the document.

Quality Assurance Statement

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Technical Report Documentation Page

1. Report No.

FHWA-HRT-10-038

2. Government Accession No. 3 Recipient's Catalog No.
4. Title and Subtitle

Balancing Safety and Capacity in an Adaptive Signal Control System—Phase 1

5. Report Date

October 2010

6. Performing Organization Code
7. Author(s)

Ziad A. Sabra, Douglas Gettman, R. David Henry, and Venkata Nallamothu

8. Performing Organization Report No.

 

9. Performing Organization Name and Address

Sabra, Wang & Associates, Inc.
1504 Joh Avenue, Suite 160
Baltimore, MD 21227

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

DTRT57-08-C-10061

12. Sponsoring Agency Name and Address

Federal Highway Administration
6300 Georgetown Pike
McLean, VA 22101-2296

13. Type of Report and Period Covered

Final Report:
September 2008–December 2009

14. Sponsoring Agency Code

 

15. Supplementary Notes

The FHWA Contracting Officer's Technical Representative (COTR) was Joe Bared. The project panel that reviewed progress of this report are Eddie Curtis, Raj Ghaman, David Gibson, John Halkias, and Wei Zhang.

16. Abstract

This research focuses on the development of real-time signal timing methodologies and algorithms that balance safety and efficiency. The research consists of two phases, and this report summarizes the findings of phase 1. First, it examines the relationships between signal timing and surrogate measures of safety: frequency of rear-end, angle, and lane-change conflicts. The Federal Highway Administration (FHWA) Surrogate Safety Assessment Methodology (SSAM) was used to evaluate simulated scenarios to test the relationships between signal timing parameters and the occurrence of traffic conflicts. A single intersection and a three-intersection arterial were examined, and each parameter was tested independently. The analysis effort indicated the following results:

  • The ratio of demand to capacity (i.e., the length of the split) is a factor that influences the total number of conflicts. There is an inverse linear relationship between splits and total conflicts.
  • Cycle length has the most significant impact on the total number of conflicts. Increasing the cycle length beyond its optimum value on an arterial system has a significant effect in reducing all types of conflicts.
  • Detector extension times have only a minor impact on changes to conflict rates.
  • The phase-change interval has a marginal effect on the total number of conflicts.
  • Left-turn phasing (protected/permitted) has a significant effect on the total number of conflicts.
  • An offset has an insignificant effect on conflicts until the change is more than ±10 percent of the cycle length.
  • Phase sequence has a significant effect on the total number of conflicts on an arterial.

These results were obtained by modifying each variable independently for specific geometric and volume conditions. As such, these results provide evidence that certain parameters have a positive correlation to changes in surrogate measures of safety, but they do not provide metrics that can be used for real-time signal timing optimization. This report also discusses a methodology based on design of experiments to calculate a safety performance function that can be used for estimating the effect of changes to signal timing parameters in tandem. The report concludes with the development of a multiobjective optimization methodology and the five principle algorithms that constitute the proposed adaptive system for tuning the cycle length, splits, offsets, left-turn phase protection treatment, and left-turn phase sequence of a set of intersections.

17. Key Words

Surrogate measures of safety, Adaptive traffic control, Traffic signal timing, Traffic conflicts, Microsimulation traffic models, ACS Lite, Multiobjective optimization, Design of experiments

18. Distribution Statement

No restrictions. This document is available through the National Technical Information Service, Springfield, VA 22161.

19. Security Classification
(of this report)

Unclassified

20. Security Classification
(of this page)

Unclassified

21. No. of Pages

106

22. Price

N/A

Form DOT F 1700.7 Reproduction of completed page authorized

SI* (Modern Metric) Conversion Factors

TABLE OF CONTENTS

1.0 INTRODUCTION

2.0 SIGNAL TIMING AND SAFETY

3.0 ANALYSIS AND SIMULATION METHODOLOGIES

4.0 STUDY SCENARIOS AND SURROGATE MEASURES OF SAFETY

5.0 FINDINGS FROM THE SIMULATION ANALYSIS

6.0 PHASE 2 RESEARCH AND DEVELOPMENT

REFERENCES

LIST OF FIGURES

Figure 1. Screenshot. SSAM's color-coded conflicts

Figure 2. Chart. Operational concept of SSAM

Figure 3. Illustration. SSAM's zone grid

Figure 4. Illustration. Vehicle path

Figure 5. Illustration. DIS1 and DIS2

Figure 6. Illustration. Checking a conflict between two vehicles at MaxTTC

Figure 7. Illustration. Checking a conflict between two vehicles at TTC = 1.3 s (vehicles no longer in conflict)

Figure 8. Illustration. Conflict types by angle

Figure 9. Illustration. Lane-change conflict

Figure 10. Illustration. Conflict angle

Figure 11. Illustration. Clock angle

Figure 12. Illustration. Intersection configuration used in simulation tests

Figure 13. Illustration. Arterial configuration used in simulation tests

Figure 14. Illustration. Typical intersection layout

Figure 15. Illustration. Intersection traffic volumes

Figure 16. Illustration. Three-intersection arterial

Figure 17. Illustration. Detail of intersection in three-intersection arterial

Figure 18. Illustration. Demand volumes for 50-s cycle (vehicles per hour)

Figure 19. Illustration. Demand volumes for 105-s cycle (vehicles per hour)

Figure 20. Screenshot. Synchro™s representation of flows impacted by offset changes

Figure 21. Screenshot. Typical summary of statistical distribution data

Figure 22. Screenshot. An excerpt of t-test statistical output from SSAM

Figure 23. Chart. Generic cycle time tuning algorithm to keep all intersections below 90 percent degree of saturation

Figure 24. Chart. Flow chart of cycle time tuning algorithm

Figure 25. Illustration. Typical flow profile detector locations on coordinated approaches

Figure 26. Illustration. Example of volume and occupancy data from a typical advance detector

Figure 27. Illustration. Example of phase timing for each of the last several cycles

Figure 28. Illustration. Example of cyclic volume and occupancy profiles averaged over the last several cycles

Figure 29. Chart. Offset adjustment algorithm flow chart

Figure 30. Diagram. Ring diagram with barriers denoted by bold vertical lines

Figure 31. Screenshot. A complete utilization-detector layout for ACS Lite

Figure 32. Illustration. Measuring phase utilization for coordinated-actuated controllers

Figure 33. Graph. Utilization of phases before split adjustment

Figure 34. Graph. Utilization of phases after split adjustment

Figure 35. Chart. Flow chart of the split optimization process including safety analysis

Figure 36. Chart. Flow chart of algorithms execution sequence

LIST OF TABLES

Table 1. Potential relationships between signal timing parameters and conflict types

Table 2. Measures of conflict severity

Table 3. Single intersection base condition

Table 4. Effects of changes in traffic demand under a fixed cycle length

Table 5. Effects of changes in splits

Table 6. Effects of changes in cycle length

Table 7. Effects of changes in the main street detector extension setting

Table 8. Effect of changes in the side street detector extension setting

Table 9. Effects of changes in left-turn phasing from protected only to protected/permissive

Table 10. Effects of changes in left-turn phasing from protected to permissive left-turn only

Table 11. Effects of changes in the phase-change interval

Table 12. Arterial base condition with arterial traffic demand of V/C = 0.85

Table 13. Arterial base condition with changes in arterial traffic demand to V/C = 1.0

Table 14. Effects of changes in offsets with cycle length of 50 s

Table 15. Effects of changes in offsets with cycle length of 105 s

Table 16. Effects of changes in left-turn phase sequence to lead-lag, 50-s cycle length

Table 17. Effects of changes in left-turn phase sequence to lead-lag, 105-s cycle length

Table 18. Summary of conflict data for the intersection baseline analysis

Table 19. Average conflicts under different demand conditions

Table 20. Ratio of conflicts to V/C

Table 21. Conflicts under different split conditions

Table 22. Ratio of conflicts to changes per hour (various split conditions)

Table 23. Conflicts with main street split adjustments

Table 24. Conflicts with side street split adjustments

Table 25. Conflicts under different cycle lengths

Table 26. Ratio of conflicts to changes per hour (various demand conditions)

Table 27. Conflicts under different main street detector extension times

Table 28. Conflicts under different side street extension times

Table 29. Total conflicts with protected/permissive phasing versus protected-only phasing

Table 30. Conflict by type for protected only and protected-permissive

Table 31. Conflicts with permissive left-turn phasing (unprotected left turn)

Table 32. Total conflicts with protected/permissive phasing versus protected-only phasing

Table 33. Total conflicts with different Y+AR times

Table 34. Arterial conflicts by type

Table 35. Conflicts under different offset conditions (50-s cycle length)

Table 36. Conflicts under different offset conditions (105-s cycle length)

Table 37. Arterial conflicts with lead-lag left-turn phasing (50-s cycle, V/C = 0.85)

Table 38. Arterial conflicts with lead-lag left-turn phasing (105-s cycle, V/C=1.0)

Table 39. Parameter-conflict association

Table 40. Fractional factorial design approach using linear regression models

Table 41. CCD approach using nonlinear regression models

Table 42. Example utilization of phases before and after split adjustment

Table 43. Rules to evaluate to consider changing phase sequence

Table 44. Rules to evaluate when considering changing left-turn treatment

LIST OF ACRONYMS AND ABBREVIATIONS

AADTAverage annual daily traffic
ACSAdaptive control system
ADTAverage daily traffic
AimsunAdvanced Interactive Microscopic Simulator for Urban and Non-urban Networks
ASC MIBActuated signal controller management information base
ATMSAdvanced Traffic Management Systems
CCDCentral composite design
CEPConflict ending point
CICASCooperative Intersection Collision Avoidance System
CMFCrash modification factor
CORSIMCorridor Simulation
CSPConflict starting point
DCSDetection Control System
DeltaSMaximum speed differential
DeltaVChange between conflict velocity
DRDeceleration rate
FHWAFederal Highway Administration
FRESIMIntegrated Traffic Simulator
HUTSIMHelsinki Urban Traffic Simulation
ITEInstitute of Technical Engineers
MaxDMaximum deceleration rate
MaxSMaximum speed of vehicle
MDSHAMaryland State Highway Administration
OPACOptimization Policies for Adaptive Control
PETPostenchroachment time
PHFPeak-hour factor
PIPerformance Index
RHODESReal Time Hierarchical Optimized Distributed Effective System
SCATS®Sydney Coordinated Adaptive Traffic System
SCOOTSplit Cycle Offset Optimization Technique
SPUISingle-point urban interchanges
SSAMSurrogate Safety Analysis Model
TEXASTraffic Experimental Analytical Simulation
TODTime of day
TRANSIMSTransportation Analysis and Simulation System
TTCTime to collision
V/CVolume to capacity
Y+ARYellow plus all red
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