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.

近年来，互联汽车（CV）和协同自动驾驶汽车（CAV）技术的快速发展要求评估这些技术对系统性能的影响。微观模拟可以在评估这些影响方面发挥重要作用，尤其是在采用技术和相关应用的早期阶段。本研究开发了一种方法来评估红灯违规警告 (RLVW) 的安全优势，这是一种在信号交叉口处基于 CV 的车辆到基础设施 (V2I) 应用程序，利用模拟。研究结果证实，在评估 RLVW 影响时，在使用的模拟模型中校准在琥珀色上停车的概率以反映真实世界的驾驶员行为至关重要。无需校准，该模型无法评估 RLVW 在减少 RLR 和直角冲突方面的好处。基于替代安全评估，校准的仿真模型结果表明，在应用程序利用率为 100% 的情况下，考虑到追尾和直角冲突，基于 CV 的 RLVW 可以将信号交叉口的安全性提高约 50.7%。