基于非冲突合流策略的交叉口灵活信号控制方法

doi:10.16097/j.cnki.1009-6744.2024.02.009

交通运输系统工程与信息 ›› 2024, Vol. 24 ›› Issue (2): 86-95.DOI: 10.16097/j.cnki.1009-6744.2024.02.009

• 智能交通系统与信息技术 • 上一篇下一篇

基于非冲突合流策略的交叉口灵活信号控制方法

黄玮^*，李世昌，曾海鹏

中山大学，智能工程学院，广东518107

收稿日期:2023-10-19 修回日期:2023-12-01 接受日期:2024-01-25 出版日期:2024-04-25 发布日期:2024-04-25
作者简介:黄玮(1986- )，女，广西贺州人，副教授。
基金资助:
国家自然科学基金 (52102401)。

Flexible Traffic Signal Control Method Based on Non-conflict Merging Strategy

HUANGWei^*,LI Shichang,ZENG Haipeng

School of Intelligent Systems Engineering, Sun Yat-sen University, Guangdong 518107, China

Received:2023-10-19 Revised:2023-12-01 Accepted:2024-01-25 Online:2024-04-25 Published:2024-04-25
Supported by:
NationalNaturalScienceFoundation of China (52102401)。

摘要/Abstract

摘要： 汽车行业智能化和网联化的发展使车辆轨迹能够实现精细化控制，为改进城市交叉口交通信号控制方法提供了新思路。本文提出一种基于非冲突合流策略的灵活信号控制方法，将同时容纳直行和左转来车的合流相位定义为非冲突相位，在双环相位结构基础上融入合流策略，形成一种具备12个动作空间的双环合流信号相位结构。在优化相位结构基础上，进一步提出改进的强化学习算法求解信号配时，以车辆到达情况为输入，当前状态下车辆等待时间最小为目标，充分考虑双环结构下相位切换的实际规律，学习当前状态下的最优相位控制策略。在SUMO (Simulation of Urban Mobility)仿真中根据算例需求生成场景数据，对比传统双环结构和双环合流相位结构在感应控制和改进强化学习算法下的不同控制策略的性能指标，分析网联车渗透率对控制效果的影响。结果显示：基于非冲突合流策略和改进强化学习算法能够在提升相位切换灵活性的基础上生成更加符合现实规律的相位配时方案；在不同交通流量条件，尤其是高流量和交通量分布不均衡的场景下，相较于双环相位结构和感应控制方法降低约37%的车均延误，提升了信号控制方案实际运行效果。

关键词: 智能交通, 非冲突合流策略, 改进强化学习, 灵活信号控制, 智能体动作设计

Abstract: The development of intelligent and connected vehicles makes it possible to finely control the vehicle trajectories and the new ideas and concepts have appeared for urban traffic signal control. This paper proposes a flexible signal control method based on non-conflict merging strategies. The merging phase is introduced to accommodate both through and left-turn vehicles. Based on the NEMA (National Electrical Manufacturers Association) dual-ring phase structure, the merging strategy is integrated to form a dual-ring merging signal phase structure with 12 action spaces. With the optimized phase structure, this paper proposes an improved reinforcement learning algorithm for the signal timing. The algorithm fully considers the actual rules of phase switching under the NEMAdual-ring structure and learns the optimal phase control strategy for the current state. The performance of the proposed control method is tested with the SUMO simulation. Different control strategies are compared, including the traditional NEMA dual-ring structure, and the NEMA dual-ring merging phase structure under both actuated control and improved reinforcement learning algorithms. The impact of the penetration rate of connected vehicles on the control performance is also analyzed. The results show that the proposed method can generate more realistic and flexible phase timing plans while maintaining the NEMA dual-ring merging phase structure. Under different traffic flow conditions, especially high traffic volume and uneven distribution of traffic volume scenarios, compared with the traditional NEMA dual-ring phase structures and actuated control methods, the proposed method can reduce vehicle delay by about 37% and hence improve the traffic operation at the signalized intersections.

Key words: intelligent transportation, non-conflict merging strategy, improved reinforcement learning, flexible signal control, intelligent agent action design

中图分类号:

U491

黄玮, 李世昌, 曾海鹏. 基于非冲突合流策略的交叉口灵活信号控制方法[J]. 交通运输系统工程与信息, 2024, 24(2): 86-95.

HUANGWei, LI Shichang, ZENG Haipeng. Flexible Traffic Signal Control Method Based on Non-conflict Merging Strategy[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(2): 86-95.

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基于非冲突合流策略的交叉口灵活信号控制方法

Flexible Traffic Signal Control Method Based on Non-conflict Merging Strategy

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