一个综合的潜在安全危险评估框架,用于连接汽车的后续场景
Guilong Xu1, Zhen Yang1, Jinfeng Ying1
1The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China; College of Transportation, Tongji University, 4800 Cao'an Highway, Shanghai 201804, China.
Accident; analysis and prevention
|April 1, 2025
概括
一个新的潜在安全危害指数 (PSHI) 通过分析多辆车来评估跟随汽车的风险,而不仅仅是前面的车辆. 这通过更早预测危险,提高了连接和自动驾驶汽车 (CAV) 的安全性.
科学领域:
- 交通安全工程 交通安全工程
- 智能运输系统 智能运输系统
- 可靠性理论可靠性理论
背景情况:
- 持续的汽车追踪可以放大轻微的冲突,导致危险的后端情况.
- 传统的替代安全措施 (SSM) 评估的风险不足,超出了之前的车辆.
- 连接和自动化车辆 (CAV) 需要先进的安全措施来主动预防事故.
研究的目的:
- 开发一个综合框架,用于评估汽车跟踪场景中的潜在安全隐患.
- 引入一个创新的SSM,潜在的安全危险指数 (PSHI),考虑多个先前的车辆.
- 为了实现 PSHI 的实时应用,以提高 CAV 安全性.
主要方法:
- 开发了一个基于可靠性理论的潜在安全危险评估框架.
- 引入了潜在安全危险指数 (PSHI),使用来自多辆先前车辆的运动数据.
- 采用直角变换第一阶可靠性方法 (OTFORM) 进行加速计算 (在0.01秒内).
主要成果:
- 拟议的PSHI有效地捕捉了来自多辆先前车辆的潜在安全隐患.
- 在现实世界的后端撞车场景中证实了PSHI的有效性.
- 在危险的汽车追踪情况中,主要的安全隐患来自前三个车辆.
结论:
- 开发的框架为评估汽车追踪安全提供了一个新的视角.
- 在CAV中,PSHI显示了改善纵向安全控制策略的巨大潜力.
- 这些发现强调了考虑先进驾驶辅助系统的多车辆动态的重要性.
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