基于双向定期绿波协调的多层次速度指导合作方法,在智能和连接的环境下
Luxi Dong1,2,3, Xiaolan Xie1,2, Lieping Zhang4
1College of Computer Science and Engineering, Guilin University of Technology, Guilin 541006, China.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
这项研究引入了用于智能和互联环境 (ICE) 的新交通控制方法,该方法优化了绿色波带宽,显著减少了车辆的延误和停车. 该方法通过协调多层次的速度指导和绿色波控制来提高交叉路口的效率.
科学领域:
- 智能运输系统 (ITS) 是一种智能运输系统.
- 交通工程是交通工程.
- 优化算法 优化算法
背景情况:
- 在动脉协调信号控制中,绿灯时间的低效利用导致旅行延迟增加和车辆吞吐量减少.
- 现有的交通控制策略在智能和互联环境 (ICE) 中难以有效优化绿色波带宽.
- 需要先进的方法来提高交通流量和交叉路口效率.
研究的目的:
- 为协调交叉群组开发一个协作优化方法,以最大限度地利用动脉绿波带宽.
- 为了最大限度地减少平均旅行延误,并在协调的十字路口最大限度地提高车辆吞吐量.
- 在智能和互联的环境中提高交叉路口的效率.
主要方法:
- 一种新的方法,将多层次的速度指导与绿色波协调控制相结合,用于交叉群.
- 使用主动速度指导来确定车辆轨迹并评估绿灯通行.
- 采用双层组合优化方法,深度Q网络遗传算法 (DQNGA),以获得全球最佳解决方案.
主要成果:
- 拟议的方法实现了平均延迟减少20.76%和停止次数减少44.49%.
- 与传统的交通控制策略相比,表现出优越的性能.
- 有效地解决了动脉协调信号控制中低效的绿灯时间利用问题.
结论:
- 开发的协作优化方法显著提高了智能和互联环境中的交叉效率.
- 多级速度指导和绿色波协调控制的整合为现代交通管理提供了有前途的解决方案.
- 通过真实世界的交通和地图传感器数据进行验证,证实了该方法的可靠性和有效性.
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