Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 2
465-469

Research on intelligent coordinated control of traffic light based on fog computing and reinforcement learning

An Mengmeng
Fan Xiumei
Cai Hanyu
Faculty of Automation & Information Engineering, Xi'an University of Technology, Xi'an 710048, China
DOI: 10.19734/j.issn.1001-3695.2018.08.0543

Abstract

For intersection traffic congestion phenomenon, combined fog computing and reinforcement learning theory, this paper proposed a traffic light control model FRTL. The model performed intelligent coordinated control of traffic lights based on real-time traffic flow information. The fog node uploaded the collected real-time traffic flow information to the fog server, and the fog server realized information sharing on the fog platform, and the fog platform combined the processed shared data and Q learning to formulate a traffic light control algorithm. The algorithm used the detected real-time traffic data to calculate a suitable traffic light timing scheme, which was finally applied to the traffic light. The simulation results show that compared with the traditional time-phase control method and the main road control method(ATL), the FRTL control method improves the throughput of intersections, reduces the average waiting time of vehicles, and achieves the goal of properly regulating traffic lights and alleviating traffic congestion.

Foundation Support

国家自然科学基金资助项目(61272509)
陕西省重点研发计划重点项目(2017ZDCXL-GY-05-01)
陕西省百人计划资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.08.0543
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 2
Section: Algorithm Research & Explore
Pages: 465-469
Serial Number: 1001-3695(2020)02-031-0465-05

Publish History

[2020-02-05] Printed Article

Cite This Article

安萌萌, 樊秀梅, 蔡含宇. 基于雾计算和强化学习的交通灯智能协同控制研究 [J]. 计算机应用研究, 2020, 37 (2): 465-469. (An Mengmeng, Fan Xiumei, Cai Hanyu. Research on intelligent coordinated control of traffic light based on fog computing and reinforcement learning [J]. Application Research of Computers, 2020, 37 (2): 465-469. )

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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