中国科学院大学学报2024，Vol.41Issue(3)：398-410,13.DOI:10.7523/j.ucas.2023.076
基于时空依赖关系多智能体强化学习的多路口交通信号协同控制方法
Cooperative traffic signal control method for multi-intersection:an approach based on spatiotemporal dependence multi-agent reinforcement learning
摘要
Abstract
In the face of increasingly serious traffic congestion,intelligent traffic signal control has become an indispensable means to improve the performance of urban road network.In this paper,a spatiotemporal traffic light control(STLight)based on multi-agent reinforcement learning algorithm is proposed.Through the spatiotemporal dependent module(STDM)based on the attention mechanism,STLight can extract the initial traffic observation data as spatiotemporal features,so as to effectively capture the spatiotemporal dependence relationship between intersections.In addition,based on the extracted spatiotemporal characteristics,STLight further introduces global spatiotemporal information to each agent on the basis of the multi-agent reinforcement learning algorithm based on the centralized training decentralized execution framework,so as to further improve the cooperation ability among multi-agents.The experimental results show that STLight has significant advantages in improving the performance of urban road networks,and helps to alleviate the traffic congestion problem of current large-scale urban road networks.关键词
多智能体强化学习/多路口交通信号控制/注意力机制/马尔可夫博弈/时空依赖Key words
multi-agent reinforcement learning/multi-intersection traffic signal control/attention mechanism/Markov game/spatiotemporal dependent分类
信息技术与安全科学引用本文复制引用
王兆瑞,岩延,张宝贤..基于时空依赖关系多智能体强化学习的多路口交通信号协同控制方法[J].中国科学院大学学报,2024,41(3):398-410,13.基金项目
国家重点研发计划项目(2018AAA0100804)和国家自然科学基金(61872331)资助 （2018AAA0100804）
