Department of Architecture and Civil Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580, Japan.
J21 Corporation, Toyohashi, Japan.
Accid Anal Prev. 2022 Feb;165:106528. doi: 10.1016/j.aap.2021.106528. Epub 2021 Dec 8.
Recently, connected vehicle (CV) and advanced driver assistance system (ADAS) technologies, including retrofit ADAS products, have been introduced in the real-world market. This study focuses on pedestrian collision warning (PCW) as an intensive function of the ADAS, which operates when a vehicle is at a collision risk with a vulnerable road user (VRU). Although several studies have been conducted on surrogate safety measures for crashes against VRUs, none of these studies used real-world CV data with collision warning information. Thus, the current study aims to i) develop a safety performance function (SPF) for crashes against VRUs at unsignalized intersections, where the PCW information was acquired using connected advanced probe vehicles (APVs), and ii) assess the effectiveness of a traffic-safety treatment implemented at an unsignalized intersection based on the developed SPF. In particular, this study proposes a two-step empirical Bayesian estimation based on the SPF model (2-step EB-SPF) to consider the issue regarding the limited number and vehicle types of APVs that can obtain PCW information. Based on the APV data, the vehicle-VRU crash-count negative binomial (NB) models were separately estimated using the actual PCW incidence rate and the EB estimate of PCW incidence rate, respectively. Although the actual PCW incidence rate was not statistically significant in the former model, the EB estimate of the PCW incidence rate was statistically significant and positively related to the crash count in the latter model. Moreover, a traffic-safety treatment was implemented at an unsignalized intersection and subsequently assessed as a case study based on the estimated 2-step EB-SPF model. Consequently, the model with the EB estimate of PCW incidence rate revealed that the vehicle-VRU crash risk was reduced by approximately 70%, and it was statistically significant at the 99% confidence level, which diminished the confidence interval in comparison to the model without the PCW incidence rate. Thus, the APV data including collision warning information can improve the estimation accuracy of determining the effect of the traffic-safety treatment, which can considerably contribute toward traffic safety assessment, especially for short after-treatment periods such as that prevailing in this case study.
最近，联网车辆 (CV) 和先进驾驶辅助系统 (ADAS) 技术，包括改装的 ADAS 产品，已经在现实市场中推出。本研究重点关注行人碰撞警告 (PCW) 作为 ADAS 的强化功能，当车辆与弱势道路使用者 (VRU) 发生碰撞风险时，该功能将运行。尽管已经有几项针对 VRU 碰撞的替代安全措施进行了研究，但这些研究都没有使用带有碰撞警告信息的现实世界 CV 数据。因此，本研究旨在：i）开发用于无信号交叉口 VRU 碰撞的安全性能函数 (SPF)，其中 PCW 信息是使用联网先进探测车 (APV) 获取的，ii）根据开发的 SPF 评估在无信号交叉口实施的交通安全处理的有效性。特别是，本研究提出了一种基于 SPF 模型的两步经验贝叶斯估计 (2 步 EB-SPF)，以考虑可以获取 PCW 信息的 APV 的数量和车辆类型有限的问题。基于 APV 数据，使用实际 PCW 发生率和 PCW 发生率的 EB 估计，分别对车辆-VRU 碰撞计数负二项式 (NB) 模型进行了单独估计。虽然在前一个模型中，实际 PCW 发生率没有统计学意义，但在后一个模型中，PCW 发生率的 EB 估计具有统计学意义，并与碰撞计数呈正相关。此外，在无信号交叉口实施了一项交通安全处理，并随后根据估计的 2 步 EB-SPF 模型作为案例研究进行了评估。因此，使用 PCW 发生率的 EB 估计的模型表明，车辆-VRU 碰撞风险降低了约 70%，在 99%置信水平下具有统计学意义，与没有 PCW 发生率的模型相比，置信区间减小。因此，包含碰撞警告信息的 APV 数据可以提高确定交通安全处理效果的估计准确性，这对交通安全评估特别是在本案例研究中普遍存在的短期处理后时期非常有帮助。
