Distributed Traffic Signal Control at Multiple Intersections Based on Reinforcement Learning 


Vol. 45,  No. 2, pp. 303-310, Feb.  2020
10.7840/kics.2020.45.2.303


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  Abstract

Intelligent Transportation System(ITS) is a system for efficient traffic management in smart cities. The traffic management system has been studied in various ways to solve traffic congestion, the most commonly used system is a traffic signal control system. In the past, traffic control was considered for each intersection. However, in order to optimize performance, traffic signal control techniques have recently studied considering all surrounding intersections. In this paper, a system for controlling traffic signals at multiple intersections is proposed using Q-learning which is reinforcement learning. The purpose of this study is to maximize throughput at intersections and minimizing waiting time at adjacent intersections.

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  Cite this article

[IEEE Style]

H. Joo and Y. Lim, "Distributed Traffic Signal Control at Multiple Intersections Based on Reinforcement Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 2, pp. 303-310, 2020. DOI: 10.7840/kics.2020.45.2.303.

[ACM Style]

Hyunjin Joo and Yujin Lim. 2020. Distributed Traffic Signal Control at Multiple Intersections Based on Reinforcement Learning. The Journal of Korean Institute of Communications and Information Sciences, 45, 2, (2020), 303-310. DOI: 10.7840/kics.2020.45.2.303.

[KICS Style]

Hyunjin Joo and Yujin Lim, "Distributed Traffic Signal Control at Multiple Intersections Based on Reinforcement Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 2, pp. 303-310, 2. 2020. (https://doi.org/10.7840/kics.2020.45.2.303)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880