在高速公路合并区域新出现的混合交通流的交通安全评估,考虑驾驶行为
Yaqin He1, Dingshan Xiang2, Daobin Wang2
1School of Automobile and Traffic Engineering, Wuhan University of Science and Technology, Wuhan, 430065, China. heyaqin@wust.edu.cn.
Scientific reports
|March 29, 2025
概括
当自动驾驶汽车 (AV) 透率超过20%时,混合交通安全得到改善. 较高的交通流量和坡道速度增加了风险,特别是在很少的AV的情况下,突出了需要AV部署策略的需要.
科学领域:
- 交通工程是交通工程.
- 智能运输系统 智能运输系统
- 汽车安全 汽车安全
背景情况:
- 自动驾驶汽车 (AV) 和人驾驶汽车 (HDV) 的混合交通环境带来了独特的安全挑战.
- 人类驾驶行为的变化使交通动态变得复杂,特别是在高速公路合并等复杂场景中.
研究的目的:
- 调查高速公路合并区域混合交通流的安全影响,考虑各种人类驾驶行为.
- 开发和验证一个改进的变化车道模型,包括驾驶行为特征.
主要方法:
- 在现场数据上使用k-means集群对人类驾驶行为进行分类 (侵略性,正常,保守性).
- 开发了使用多目标优化改进的HV车道换行模型,并结合了车道换行时间和动机.
- 在不同的条件下在SUMO平台上验证了HV模型和模拟混合流量场景.
主要成果:
- 低的AV透率 (<20%) 并没有改善混合交通安全.
- 超过20%的AV透率导致了显著的安全改善,减少了冲突率和碰撞时间 (TTC) 频率.
- 增加的坡道流量比率和合并流量比率增加了安全风险,特别是在低AV透水平时.
结论:
- 自动驾驶汽车 (AV) 一旦其透率超过了关键值 (约20%),就会显著提高混合交通安全.
- 交通流量条件和坡道合并动态是影响混合交通环境安全的关键因素.
- 结果为改善混合交通安全和优化AV部署以提高道路安全的战略提供信息.
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