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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations

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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

6 Concluding Remarks

This report provided details about the work on developing a novel DZ model based on ABMS. In order to develop a realistic driver's behavior model regarding the uncertainty of a driver's perception and decision, the E-BDI framework was adopted. In the E-BDI framework, internal information (i.e., vehicle's approaching speed and distance to stop line at the onset of the yellow phase) and external information (i.e., presence of a red-light photo enforcement camera, presence of a pedestrian countdown signal, and behavior of an adjacent vehicle) were considered as major factors on the stopping and proceeding decisions of a driver. In addition, the impact of factors on drivers' decisionmaking behaviors in the DZ was analyzed under four roadway conditions classified by facility speed limit of the roadway and degree of driving in a hurry. The highway driving simulator was used to collect real drivers' responses and to calibrate the ABMS model with E-BDI framework. To demonstrate and validate our proposed approach, the drivers' behaviors under two cases were compared: (1) drivers only knew the approaching speed and distance to the stop line of a vehicle (i.e., internal information), and (2) drivers knew the internal information as well as the external information. The experiments revealed that knowing the external information could predict real drivers' behaviors accurately and reduce the number of red-light violations, which could cause potential car crashes at an intersection.



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