A Survey on Deep Reinforcement Learning for Traffic Signal Control

doi:10.1109/CCDC52312.2021.9601529

	A Survey on Deep Reinforcement Learning for Traffic Signal Control
	Miao, Wei 1; Li, Long 1; Wang, Zhiwen2,3,4
	2021
会议名称	33rd Chinese Control and Decision Conference (CCDC)
会议录名称	PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021)
页码	1092-1097
会议日期	MAY 22-24, 2021
会议地点	Kunming, PEOPLES R CHINA
会议录编者/会议主办者	NE Univ,Tech Comm Control & Decis Cyber Phys Syst,Chinese Assoc Automat,Kunming Univ Sci & Technol,IEEE Control Syst Soc,Tech Comm Control Theory,Chinese Assoc Automat,State Key Lab Synthet Automat Proc Ind
出版者	IEEE
摘要	Traffic congestion is one of the most important and complex problems in urban governance for a long time. Although traffic lights are used at intersections, traffic bottlenecks still appear with the increasing number of private cars. In recent years, with the continuous development of related technologies in the field of intelligent transportation, more attention has been paid to the automatic driving scheme with intelligent vehicle infrastructure cooperative systems as the core. As a kind of advanced artificial intelligence method, deep reinforcement learning (DRL) is applied to traffic signal control (TSC) to achieve the purpose of optimizing roadside traffic timing. In this paper, we introduce the background of TSC (i.e., main parameters, methods and simulation tools), and then summarize the representation of DRL model (i.e., state, action and reward) and the application of DRL in TSC. The research scenarios of TSC are divided into single-agent and multi-agent. Finally, according to existing works in this field, the problems to be solved are put forward and the paper is summarized.
关键词	Deep reinforcement learning Traffic signal control Multi-agent Intersection
DOI	10.1109/CCDC52312.2021.9601529
收录类别	CPCI-S
语种	英语
WOS研究方向	Automation & Control Systems
WOS类目	Automation & Control Systems
WOS记录号	WOS:000824370101061
ISSN	1948-9439
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	会议论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/159873
专题	电气工程与信息工程学院
通讯作者	Li, Long
作者单位	1.GS Unis Intelligent Transportat Syst & Control Te, Lanzhou 730030, Peoples R China; 2.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Peoples R China; 3.Lanzhou Univ Technol, Key Lab Gansu Adv Control Ind Proc, Lanzhou 730050, Peoples R China; 4.Lanzhou Univ Technol, Natl Demonstrat Ctr Expt Elect & Control Engn Edu, Lanzhou 730050, Peoples R China
推荐引用方式 GB/T 7714	Miao, Wei,Li, Long,Wang, Zhiwen. A Survey on Deep Reinforcement Learning for Traffic Signal Control[C]//NE Univ,Tech Comm Control & Decis Cyber Phys Syst,Chinese Assoc Automat,Kunming Univ Sci & Technol,IEEE Control Syst Soc,Tech Comm Control Theory,Chinese Assoc Automat,State Key Lab Synthet Automat Proc Ind:IEEE,2021:1092-1097.