超车
撞车
碰撞
车辆类型
机动车碰撞
描述性统计
汽车工程
毒物控制
运输工程
工程类
逻辑回归
航空学
模拟
计算机科学
统计
伤害预防
计算机安全
数学
环境卫生
医学
程序设计语言
作者
Chengcheng Xu,Zijian Ding,Chen Wang,Zhibin Li
标识
DOI:10.1016/j.jsr.2019.09.001
摘要
This study aimed to investigate the characteristics and patterns of the connected and autonomous vehicle (CAV) involved crashes. Method: The crash data were collected from the reports of CAV involved crash submitted to the California Department of Motor Vehicles. The descriptive statistics analysis was employed to investigate the characteristics of CAV involved crashes in terms of crash location, weather conditions, driving mode, vehicle movement before crash occurrence, vehicle speed, collision type, crash severity, and vehicle damage locations. The bootstrap based binary logistic regressions were then developed to investigate the factors contributing to the collision type and severity of CAV involved crashes. Results: The results suggested that the CAV driving mode, collision location, roadside parking, rear-end collision, and one-way road are the main factors contributing to the severity level of CAV involved crashes. The CAV driving mode, CAV stopped or not, CAV turning or not, normal vehicle turning or not, and normal vehicle overtaking or not are the factors affecting the collision type of CAV involved crashes.
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