多级信号车辆合作控制,以提高混合自主交通中的动脉交叉路口的安全性和效率
Gongquan Zhang1, Fengze Li2, Jaeyoung Jay Lee3
1School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China; Harvard Medical School, Harvard University, Boston 02138, United States.
Accident; analysis and prevention
|March 4, 2026
概括
本研究介绍了连接自动驾驶汽车 (CAV) 和交通信号的多级信号-车辆合作控制 (ML-SVCC) 系统. 该系统显著减少了动脉道路上的交通冲突和延误.
科学领域:
- 智能运输系统 智能运输系统
- 交通工程是交通工程.
- 交通运输中的人工智能
背景情况:
- 交通信号和连接自动驾驶汽车 (CAV) 的合作控制可以提高隔离交叉路口的安全性和效率.
- 将合作控制扩展到动脉交叉路口,由于复杂的协调和异质的交通,因此存在挑战.
研究的目的:
- 提出和评估一个多级信号-车辆合作控制 (ML-SVCC) 系统,以优化动脉网络的安全性和效率.
- 整合基于多代理强化学习 (MARL) 的交通信号控制 (TSC) 与CAV速度建议.
主要方法:
- 开发了一个ML-SVCC系统,每个十字路口都有本地MARL代理,并有一个全球代理进行协调.
- 在CAV中实现了速度控制模块,以与交通信号时间同步.
- 在中国长沙市的真实动脉环境中模拟了该系统.
主要成果:
- 减少了42%-54%的交通冲突和25%-57%的延误.
- 超过了传统的TSC,基于MARL的TSC和绿灯最佳速度咨询.
- 最小化车辆停止,加速和减速,表现出强大的性能,增加了CAV透率.
结论:
- ML-SVCC系统有效地提高了动脉道路上的交通安全和效率.
- 整合MARL和CAV速度建议为未来的智能运输系统提供了一个有希望的方法.
- 该系统在不同级别的CAV采用中展示了适应性和有效性.
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