Agent-based behavioral modeling framework of driver behavior at the onset of yellow indication at signalized intersections

Abstract

This paper presents a state-of-the-art behavioral model (BM) that can be used as a tool to simulate driver behavior after the onset of a yellow indication until (s)he reaches the intersection stop line. The paper presents the general framework of the proposed BM, its components, and discusses its ability to track Dilemma Zone (DZ) drivers and update the information available to them every time step until they reach a final decision. The BM framework is ideal for testing dilemma zone mitigation strategies before actual implementation. In addition, the BM framework can be easily implemented in any traffic simulation software. The paper performs system-based and agent-based characterization of the components involved in the BM framework using data collected from a controlled field driving experiment. The BM is validated using Monte Carlo (MC) simulations, and produces high success rates of 72.8% and 87.2% for system-based and agent-based models, respectively.