Hanyang University Erica Campus, Department of Transportation and Logistics Engineering, 55 Hanyangdaehak-ro, Sangnok-gu, Ansan, 15588, Republic of Korea.
Accid Anal Prev. 2021 Mar;151:105972. doi: 10.1016/j.aap.2021.105972. Epub 2021 Jan 16.
Valuable high-resolution data representing the maneuvering of both individual subject vehicles and adjacent vehicles are available in the era of the connected vehicle systems, which is also referred to as cooperative intelligent transportation systems (C-ITS). C-ITS can share useful traffic information between connected vehicles (CV) and between vehicles and infrastructure in support of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications. An excellent feature of a C-ITS pre-deployment project in Korean freeways that CVs are equipped with an in-vehicle forward collision warning system. This technical support provides a useful opportunity to evaluate crash risks more objectively and scientifically based on the analysis of vehicle interactions, which motivates our study. The purpose of this study is to develop a road safety information system based on the analysis of CV data. The proposed system estimates individual vehicle crash risks based on the crash potential index (CPI) and further utilizes them to develop a methodology for assessing road safety risks on freeways. High CPIs were observed in toll plaza area, recurrent congestion sections, and on and off-ramp areas. An encouraging result showed that the relationship between the estimated CPI and the actual crash frequencies was statistically meaningful. In addition, the impact of the CV market penetration rate (MPR) on the feasibility of the proposed road risk monitoring method was explored by microscopic traffic simulation experiments using VISSIM. A safety evaluation equivalent to 100 % MPR was obtainable with 30 % MPR. The outcomes of this study are expected to be utilized as fundamental to support the development of novel road risk monitoring systems in C-ITS environments.
在车联网系统时代，即所谓的协同智能交通系统（C-ITS），可以获得代表单个主体车辆和相邻车辆操纵的有价值的高分辨率数据。C-ITS 可以在联网车辆（CV）之间以及车辆和基础设施之间共享有用的交通信息，以支持车对车（V2V）和车对基础设施（V2I）无线通信。韩国高速公路 C-ITS 预部署项目的一个显著特点是 CV 配备了车载前方碰撞警告系统。这种技术支持为基于车辆交互分析更客观和科学地评估碰撞风险提供了一个有用的机会，这激发了我们的研究。本研究的目的是开发一个基于 CV 数据分析的道路安全信息系统。该系统基于碰撞潜在指数（CPI）来估计个体车辆的碰撞风险，并进一步利用这些风险来开发高速公路道路安全风险评估方法。在收费广场区域、反复拥堵路段、上下匝道区域观察到高 CPI。令人鼓舞的结果表明，估计的 CPI 与实际碰撞频率之间的关系具有统计学意义。此外，通过使用 VISSIM 进行微观交通模拟实验，探讨了 CV 市场渗透率（MPR）对所提出的道路风险监测方法可行性的影响。在 30%的 MPR 下可以实现相当于 100%的 MPR 的安全评估。本研究的结果有望被用作支持在 C-ITS 环境中开发新型道路风险监测系统的基础。
