This paper proposes a high-fidelity simulation framework that can estimate the potential safety benefits of vehicle-to-infrastructure (V2I) pedestrian safety strategies. This simulator can support cooperative perception algorithms in the loop by simulating the environmental conditions, traffic conditions, and pedestrian characteristics at the same time. Besides, the benefit estimation model applied in our framework can systematically quantify both the risk conflict (non-crash condition) and the severity of the pedestrian's injuries (crash condition). An experiment was conducted in this paper that built a digital twin of a crowded urban intersection in China. The result shows that our framework is efficient for safety benefit estimation of V2I pedestrian safety strategies.

翻译：本文提出了一种高保真仿真框架，能够评估车辆与基础设施（V2I）行人安全策略的潜在安全效益。该仿真器通过同时模拟环境条件、交通状况和行人特征，支持协同感知算法在环运行。此外，框架中应用的利益评估模型能够系统量化风险冲突（非碰撞场景）和行人受伤严重程度（碰撞场景）。本文通过构建中国某拥挤城市路口的数字孪生体进行了实验。结果表明，该框架在评估V2I行人安全策略的安全效益方面具有高效性。