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Publication Number:  FHWA-HRT-15-082    Date:  December 2015
Publication Number: FHWA-HRT-15-082
Date: December 2015

 

Exploratory Advanced Research Program

VASTO - Evolutionary Agent System for Transportation Outlook

Agent-Based Modeling and Simulation in The Dilemma Zone

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FOREWORD

Gaining an indepth understanding of drivers’ decisions and behaviors in dilemma zone situations will help State, county, and city transportation agencies to develop and deploy effective countermeasures to improve safety and reduce potential crashes at signalized intersections. This study’s objective is to develop a dilemma zone behavior model that considers the effects on drivers of certain factors found at signalized intersections, such as the presence of a pedestrian countdown signal, the presence of a red-light photo enforcement camera, and the actions of an adjacent vehicle. Federal Highway Administration’s (FHWA’s) Highway Driving Simulator was used to collect drivers’ responses as a function of speed limit and whether the driver was in a hurry. A dilemma zone behavior model was developed based on data collected in the driving simulation experiments via agent-based modeling and simulation. Results from the experiments suggested that sufficient external information, such as the presence of a red-light photo enforcement camera, can accurately predict the drivers’ decisions when they were confronted with the dilemma zone. The dilemma zone behavior model also takes into account the interactions between vehicles and provides realistic predictions of driver behaviors under various traffic conditions.

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.

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Technical Report Documentation Page

1. Report No.

FHWA-HRT-15-082

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

Agent-Based Modeling and Simulation in the Dilemma Zone

5. Report Date

December 2015

6. Performing Organization Code
7. Author(s)

Sojung Kim, Young-Jun Son, Mary Anne Jeffers, Jason Williams, Yi-Chang Chiu

8. Performing Organization Report No.

 

9. Performing Organization Name and Address

University of Arizona, Tucson, AZ 85721
George Mason University, Fairfax, VA 22030
Leidos, Reston, VA 20190
Textron Systems/AAI Corporation, Hunt Valley, MD, 21030

10. Work Unit No. (TRAIS)

11. Contract or Grant No.
12. Sponsoring Agency Name and Address

Federal Highway Administration
Office of Safety Research and Development
6300 Georgetown Pike
McLean, VA 22101

13. Type of Report and Period Covered

Final Report

14. Sponsoring Agency Code

HRDS-30

15. Supplementary Notes

FHWA Contracting Officer's Representative (COR): Dr. C. Y. David Yang

16. Abstract

The goal of this study is to develop a realistic dilemma zone (DZ) model that considers the effects of factors surrounding vehicles at an intersection, particularly focusing on driver decisionmaking behavior, such as the presence of a pedestrian countdown signal, a red-light photo enforcement camera, and the actions of an adjacent vehicle. The Federal Highway Administration’s Highway Driving Simulator (HDS) was used to collect drivers’ responses as a function of facility speed limit and whether the driver was in a hurry. From these responses, a DZ model was developed via agent-based modeling and simulation (ABMS) under the extended belief-desire-intention (E-BDI) framework. This framework represents uncertain perception and decision behaviors of humans in a probabilistic manner. To demonstrate and validate the proposed approach, the drivers’ actions under two circumstances were compared: (1) drivers only knew the approach speed and distance to the stop (i.e., internal information); and (2) drivers knew the internal information as well as external information, such as presence of a pedestrian countdown signal or presence of a red-light photo enforcement camera, and the behavior of an adjacent vehicle. The experiments indicate that sufficient external information could accurately predict the decisions of drivers and thus reduce the number of red-light violations that could potentially cause accidents at an intersection. In addition, the proposed E-BDI-based DZ model allowed us to consider the physical interactions between vehicles such that it provides realistic prediction results of drivers under various traffic conditions.

17. Key Words

dilemma zone, driving simulator, time pressure, driving in a hurry, red light photo enforcement camera, pedestrian countdown signal, adjacent vehicle, red-light running

18. Distribution Statement

No restrictions. This document is available to the public 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

48

22. Price

N/A

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized

SI* (Modern Metric) Conversion Factors

Table of Contents

1 Executive Summary

2 Introduction

3 Overview of Research Methodology

4 DZ Data Collection Using a Highway Driving Simulator

5 Analysis Results

6 Concluding Remarks

7 References

Appendix A. Post-Participation Survey

List of Figures

List of Tables

List of Abbreviations and Symbols

ABMS Agent-based Modeling and Simulation
BBNBayesian Belief Network
CD/M2Candela per Square Meter
CIConfidence Interval
DZ Dilemma Zone
E-BDI Extended Belief-Desire Intention
EDFT Extended Decision Field Theory
fLFoot-lambert
GEE Generalized Estimating Equations
HDS Highway Driving Simulator
ITEInstitute of Traffic Engineers
KM/H Kilometers per Hour
MI/H Miles per Hour
NHTSA National Highway Traffic Safety Administration
PRTPerception-Reaction Time
SEM Structural Equation Modeling
S-D Speed-Distance

 

 

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