With the precedence of connected automated vehicles (CAVs), car-following control technology is a promising way to enhance traffic safety. Although a variety of research has been conducted to analyze the safety enhancement by CAV technology, the parametric impact on CAV technology has not been systematically explored. Hence, this paper analyzes the parametric impacts on surrogate safety measures (SSMs) for a mixed vehicular platoon via a two-level analysis structure. To construct the active safety evaluation framework, numerical simulations were constructed which can generate trajectories for different kind of vehicles while considering communication and vehicle dynamics characteristics. Based on the trajectories, we analyzed parametric impacts upon active safety on two different levels. On the microscopic level, parameters including controller dynamic characteristics and equilibrium time headway of car-following policies were analyzed, which aimed to capture local and aggregated driving behavior’s impact on the vehicle. On the macroscopic level, parameters incorporating market penetration rate (MPR), vehicle topology, and vehicle-to-vehicle environment were extensively investigated to evaluate their impacts on aggregated platoon level safety caused by inter-drivers’ behavioral differences. As indicated by simulation results, an automated vehicle (AV) suffering from degradation is a potentially unsafe component in platoon, due to the loss of a feedforward control mechanism. Hence, the introduction of connected automated vehicles (CAVs) only start showing benefits to platoon safety from about 20% CAV MPR in this study. Furthermore, the analysis on vehicle platoon topology suggests that arranging all CAVs at the front of a mixed platoon assists in enhancing platoon SSM performances.

中文翻译：

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解开参数对混合排替代安全措施的影响

随着联网自动驾驶汽车 (CAV) 的普及，跟驰控制技术是提高交通安全的一种很有前途的方法。尽管已经进行了各种研究来分析 CAV 技术对安全性的增强，但尚未系统地探讨对 CAV 技术的参数影响。因此，本文通过两级分析结构分析了对混合车辆排的替代安全措施（SSM）的参数影响。为了构建主动安全评估框架，构建了数值模拟，可以在考虑通信和车辆动力学特性的同时为不同类型的车辆生成轨迹。基于轨迹，我们分析了两个不同层次上对主动安全的参数影响。在微观层面，分析了控制器动态特性和跟驰策略的平衡时距等参数，旨在捕捉局部和综合驾驶行为对车辆的影响。在宏观层面上，广泛研究了包含市场渗透率 (MPR)、车辆拓扑和车辆到车辆环境的参数，以评估它们对由驾驶员间的行为差​​异引起的聚合队列级安全的影响。正如仿真结果所表明的那样，由于前馈控制机制的丧失，遭受退化的自动车辆 (AV) 是排中潜在的不安全组件。因此，在本研究中，联网自动驾驶汽车 (CAV) 的引入仅开始显示出约 20% CAV MPR 对排安全的好处。此外，