System Development & Application
|
App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 2
504-509,514

TR-light：traffic organization plan optimization algorithm based on multiple traffic signal lights reinforcement learning

Wu Haosheng
Zheng Jiaoling
Wang Maofan
School of Software Engineering, Chengdu University of Information Technology, Chengdu 610225, China
DOI: 10.19734/j.issn.1001-3695.2021.06.0283

Abstract

Focusing on the problem with traffic congestion under changing environmental conditions, this paper proposed a trajectory reward light(TR-light) model by combining reinforcement learning, neural network, multi-agent and traffic simulation technology to optimize the traffic at multi-intersections. This method had considerable merits in the following aspects. The traffic organization plan was formulated based on traffic lights; multi-agent reinforcement learning was used on traffic light control; regional traffic organization was optimized through the coordination of traffic lights; the agent implemented trajectory reconstruction after the execution of each behavior so as to change the vehicle travel path without changing the OD pair, and to calculate the final reward of the agent according to the plan and reconstructed trajectory. Finally, it conducted a traffic simulation experiment through SUMO. The comparison of traffic indicators verifies that the proposed model improves the smoothness of the road network and the traffic state at the multi-intersections. Experiments show that the model is feasible and effectively mitigates the traffic congestion.

Foundation Support

四川省科技厅应用基础研究项目(2020YJ0430)
基于群体智能的区域交通流量精准控制技术应用研究

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.06.0283
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 2
Section: System Development & Application
Pages: 504-509,514
Serial Number: 1001-3695(2022)02-030-0504-06

Publish History

[2021-11-06] Accepted Paper
[2022-02-05] Printed Article

Cite This Article

吴昊昇, 郑皎凌, 王茂帆. TR-light：基于多信号灯强化学习的交通组织方案优化算法 [J]. 计算机应用研究, 2022, 39 (2): 504-509,514. (Wu Haosheng, Zheng Jiaoling, Wang Maofan. TR-light：traffic organization plan optimization algorithm based on multiple traffic signal lights reinforcement learning [J]. Application Research of Computers, 2022, 39 (2): 504-509,514. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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