Department of Civil Engineering, Democritus University of Thrace, Xanthi, 67100, Greece.
European Commission - Joint Research Centre, Via E. Fermi, 2749 - 21023, Ispra, IT, Italy.
Accid Anal Prev. 2020 Dec;148:105794. doi: 10.1016/j.aap.2020.105794. Epub 2020 Oct 5.
The present paper discusses two fuzzy Surrogate Safety Metrics (SSMs) for rear-end collision, the Proactive Fuzzy SSM (PFS) and Critical Fuzzy SSM (CFS). The objective is to investigate their applicability for evaluating the real-time rear-end risk of collision of vehicles to support the operations of advanced driver assistance and automated vehicle functionalities (from driving assistance systems to fully automated vehicles). The proposed Fuzzy SSMs are evaluated and compared to other traditional metrics on the basis of empirical observations. To achieve this goal, an experimental campaign was organized in the AstaZero proving ground in Sweden. The campaign consisted of two main parts: a car-following experiment with five vehicles solely driven by Adaptive Cruise Control (ACC) systems and a safety critical experiment, testing the response of the Autonomous Emergency Braking (AEB) system to avoid collisions on a static target. The proposed PFS is compared with the safe distance defined by the well-known Responsibility Sensitive Safety (RSS) model, showing that it can produce meaningful results in assessing safety conditions also without the use of crisp safety thresholds (like in the case of RSS). The CFS outperformed the well-known Time-To-Collision (TTC) SSM in the a-priori identification of the cases, where the tested vehicles were not able to avoid the collision with the static target. Moreover, results show that CFS at the time of the first deceleration is correlated with the velocity of the vehicle at the time of collisions with the target.
本文讨论了两种用于追尾碰撞的模糊替代安全指标（SSM），即主动模糊 SSM（PFS）和关键模糊 SSM（CFS）。目的是研究它们在评估车辆实时追尾碰撞风险方面的适用性，以支持先进驾驶员辅助和自动驾驶功能的操作（从驾驶辅助系统到全自动车辆）。基于经验观察，对所提出的模糊 SSM 进行了评估和比较。为了实现这一目标，在瑞典的 AstaZero 试验场组织了一项实验活动。该活动由两部分组成：五辆仅由自适应巡航控制系统（ACC）驱动的汽车的跟车实验，以及安全关键实验，测试自动紧急制动（AEB）系统对避免静态目标碰撞的反应。所提出的 PFS 与著名的责任敏感安全（RSS）模型定义的安全距离进行了比较，结果表明，即使不使用清晰的安全阈值（如 RSS 情况），它也可以在评估安全条件方面产生有意义的结果。在事先识别测试车辆无法避免与静态目标碰撞的情况下，CFS 优于著名的碰撞时间（TTC）SSM。此外，结果表明，在第一次减速时的 CFS 与碰撞目标时车辆的速度相关。
