Speaker: Pouya Jalali Khalilabadi, Ph.D. student, Department of Civil and Architectural Engineering and Mechanics, University of Arizona
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Summary: Red-light running (RLR) is a critical safety concern at signalized intersections, contributing to a significant number of severe crashes nationwide. It is often a result of complex interactions between driver behavior and signal timing parameters, particularly yellow and red clearance intervals. Addressing this issue requires a combination of behavioral, enforcement, and engineering strategies. While driver behavior can be influenced through education and enforcement, adjustments to yellow and red clearance intervals represent a practical engineering approach to mitigating RLR violations. To investigate the effectiveness of engineering-based interventions in reducing RLR, the City of Phoenix, in collaboration with the University of Arizona, initiated a multi-phase research effort to evaluate how changes to yellow and red clearance intervals influence driver compliance at signalized intersections. In Phases 1 and 2, the Institute of Transportation Engineers (ITE) 2020 guidelines for yellow and red clearance interval calculations were implemented at twelve intersections equipped with advanced sensors capable of capturing high-resolution traffic signals and vehicle entry data. This allowed for a detailed analysis of driver compliance behavior during the yellow and red clearance phases before and after implementing the guidelines. Building on the initial findings, Phase 3 of the study expands the evaluation to fifteen additional intersections, incorporating calculations from ITE 2020 and NCHRP Report 731 guidelines to assess the impact of updated yellow and red clearance intervals on RLR violations. Findings from this ongoing research are expected to provide actionable, data-driven insights for improving driver compliance and reducing red-light running violations. The results will support refined signal timing practices and enhance intersection safety.
Researcher's Bio: Pouya is a graduate research assistant at the University of Arizona's Center for Applied Transportation Science (CATS) and is in his fifth year of pursuing a Ph.D. His research focuses on traffic safety, transportation operations, and intelligent transportation systems. He is particularly interested in investigating methods to reduce traffic signal violations and improve safety at signalized intersections.