TY - JOUR A2 - Guo, Yanyong AU - Shangguan, qiqiang AU - Fu, Ting AU - Wang, Junhua AU - Jiang, Rui AU - Fang，守我PY - 2021 DA - 2021/04/30 TI -追尾事故风险的量化和分析其影响因素基于一种新的代理安全措施SP - 5551273六世- 2021 AB -传统代理安全措施(SMoS)不能充分考虑事故机制或不能反映事故概率和事故严重程度时间。此外，驾驶风险也随着驾驶员个人驾驶特征和环境因素的变化而不断变化。考虑到驾驶员的异质性，研究行为特征和环境特征对追尾事故风险的影响是保证驾驶安全的必要条件。本研究从上海自然驾驶研究(SH-NDS)中提取了16905起追车事件。提出了一种新的追尾事故风险指数(RCRI)来量化追尾事故风险。在此基础上，对天气、时间变量和交通条件等不同方面的影响因素进行了风险比较分析。然后，应用混合效应线性回归模型，明确追尾事故风险与其影响因素之间的关系。结果表明，该模型能够反映追尾事故风险的动态变化，适用于任意车辆跟车场景。 The comparative analysis indicates that high traffic density, workdays, and morning peaks lead to higher risks. Moreover, results from the mixed-effects linear regression model suggest that driving characteristics, traffic density, day-of-week (workday vs. holiday), and time-of-day (peak hours vs. off-peak hours) had significant effects on driving risks. This study provides a new surrogate safety measure that can better identify rear-end crash risks in a more reliable way and can be applied to real-time crash risk prediction in driver assistance systems. In addition, the results of this study can be used to provide a theoretical basis for the formulation of traffic management strategies to improve driving safety. SN - 0197-6729 UR - https://doi.org/10.1155/2021/5551273 DO - 10.1155/2021/5551273 JF - Journal of Advanced Transportation PB - Hindawi KW - ER -