使用主动安全方法在山地水平曲线上的重型商用车辆撞车风险估计
Pranab Kar1, Suvin P Venthuruthiyil2, Mallikarjuna Chunchu1
1Indian Institute of Technology Guwahati, India.
Accident; analysis and prevention
|March 1, 2024
概括
这项研究使用预期碰撞时间 (ACT) 来分析重型商用车辆 (HCV) 在山区道路上的碰撞风险. 调查结果显示,利的曲线增加了跑出路线 (ROR) 事件,但严重事故的频率较低,这表明有针对性的安全改进.
科学领域:
- 运输工程 运输工程
- 道路交通安全 道路交通安全
- 交通分析 交通分析
背景情况:
- 由于道路的复杂几何结构,重型商用车辆 (HCV) 在山区具有更高的撞车风险.
- 传统的撞车数据分析有限;越来越多地采用使用替代安全措施 (SSM) 的主动安全研究.
- 对于山区的HCV驾驶员,准确的显微数据很少,这阻碍了主动的安全评估.
研究的目的:
- 通过使用SSM,研究水平曲线对山地地区HCV碰撞风险的影响.
- 解决在具有挑战性的环境中涉及HCV的主动安全研究的数据稀缺差距.
- 开发和验证用于山区道路的非静止碰撞风险模型.
主要方法:
- 利用从古瓦哈蒂-希隆绕道的水平曲线的视频数据进行轨迹提取.
- 采用预期碰撞时间 (ACT) 来识别交通冲突和极端价值理论 (EVT) 的高峰超值值 (POT) 方法来估计碰撞风险.
- 开发了非静止碰撞风险模型,包括道路几何和HCV动态 (制动,曲率).
主要成果:
- 跑出路线 (ROR) 事件在山区的水平曲线上或附近更为频繁,但严重的ROR事件并不常见.
- 与静止模型相比,结合道路几何和HCV动态的非静止模型与观察到的碰撞频率提供了更好的对齐.
- 尖的曲线 (半径<200m) 和水平和垂直曲线中点之间的距离增加 (>1m) 显著提高了ROR碰撞风险.
结论:
- 预期碰撞时间 (ACT) 和峰值超越值 (POT) 模型适用于印度山地地区对HCV的主动安全分析.
- 道路几何形状,特别是曲线半径和与垂直曲线的对齐,是影响HCV安全性的关键因素.
- 建议包括减少接近触点长度和增强标志,以减轻ROR在利曲线上的碰撞风险.
相关概念视频
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