Reinforcement learning in urban network traffic signal control: A systematic literature review
作者：
Highlights：
• A review on Reinforcement Learning in the network-scale Traffic Signal Control area.
• Presents a comprehensive systematic literature review of 160 included articles.
• Consolidates and characterizes the existing research on the defined area.
• Explores the methods, applications, domains, and first events in the defined scope.
• Identifies past and present trends and directions for further research in the area.
摘要
•A review on Reinforcement Learning in the network-scale Traffic Signal Control area.•Presents a comprehensive systematic literature review of 160 included articles.•Consolidates and characterizes the existing research on the defined area.•Explores the methods, applications, domains, and first events in the defined scope.•Identifies past and present trends and directions for further research in the area.
论文关键词：Reinforcement learning,Traffic light control,Urban network,Multi-agent system,Intelligent transportation system,Artificial intelligence
论文评审过程：Received 25 March 2021, Revised 23 February 2022, Accepted 3 March 2022, Available online 17 March 2022, Version of Record 2 April 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.116830
