Evaluating the Benefits of Red-Light Violation Warning System in a Connected Vehicle Simulation Environment

Abstract

The rapid development of connected vehicle (CV) and cooperative automated vehicle (CAV) technologies in recent years calls for the assessment of the impacts of these technologies on system performance. Microscopic simulation can play a major role in assessing these impacts, particularly during the early stages of the adoption of the technologies and associated applications. This study develops a method to evaluate the safety benefits of red-light violation warning (RLVW), a CV-based vehicle-to-infrastructure (V2I) application at signalized intersections, utilizing simulation. The study results confirm that it is critical to calibrate the probability to stop on amber in the utilized simulation model to reflect real-world driver behaviors when assessing RLVW impacts. Without calibration, the model is not able to assess the benefits of RLVW in reducing RLR and right-angle conflicts. Based on a surrogate safety assessment, the calibrated simulation models result shows that the CV-based RLVW can enhance the safety at signalized intersections by approximately 50.7% at 100% utilization rate of the application, considering rear-end, and right-angle conflicts.