Cooperative Multi-Agent Reinforcement Learning Framework for Edge Intelligence Empowered Traffic Light Control

Haiyong Shi1; Bingyi Liu1; Enshu Wang2; Weizhen Han1; Jinfan Wang3,4; Shihong Cui5; Libing Wu2

2024

10.1109/TCE.2024.3416822

IEEE Transactions on Consumer Electronics   影响因子和分区

1558-4127

Edge Intelligence (EI) technologies obtain an advance with promotion by Consumer Electronics (CE) and spread to the Intelligent Transportation System (ITS). As part of the edge in ITS, traffic lights suffer from overlooking the importance of cooperation among traffic lights and lack of long sequence scheduling. To address this challenge, we formulate the control problem of multi-intersection traffic lights as a multi-agent Markov game problem. In response, we propose a Cooperative Adaptive Control Method (CACOM), a framework based on multi-agent reinforcement learning. CACOM integrates the mixing network and the options framework. Specifically, the mixing network enables cooperation among intersections, and the options framework provides the ability for intersections to make a long sequence scheduling. Besides, we designed a weight generator for the mixing network based on the traffic conditions at intersections, allowing the agents to adjust their weights adaptively during cooperation. Finally, we build a simulator including two real-world urban road networks for extensive evaluation. In contrast to the best baseline methods, our approach achieves an average waiting time reduction of around 24% and 42% for high-priority vehicles in two scenarios. Moreover, the waiting time for all vehicles is decreased by approximately 15% and 6%, respectively.

EI

其他

ENGINEERING

1.School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China
2.School of Cyber Science and Engineering, Wuhan University, Wuhan, China
3.Institute of Future Networks, Southern University of Science and Technology, Shenzhen, China
4.LINKINSENSE Co., Ltd, Hefei, China
5.CICT Connected and Intelligent Technologies Co., Ltd, Beijing, China

Haiyong Shi,Bingyi Liu,Enshu Wang,et al. Cooperative Multi-Agent Reinforcement Learning Framework for Edge Intelligence Empowered Traffic Light Control[J]. IEEE Transactions on Consumer Electronics,2024,PP(99).

Haiyong Shi.,Bingyi Liu.,Enshu Wang.,Weizhen Han.,Jinfan Wang.,...&Libing Wu.(2024).Cooperative Multi-Agent Reinforcement Learning Framework for Edge Intelligence Empowered Traffic Light Control.IEEE Transactions on Consumer Electronics,PP(99).

Haiyong Shi,et al."Cooperative Multi-Agent Reinforcement Learning Framework for Edge Intelligence Empowered Traffic Light Control".IEEE Transactions on Consumer Electronics PP.99(2024).