Traffic light control based on fuzzy Q-leaming

M. J. Moghaddam, Matin Hosseini, R. Safabakhsh
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引用次数: 18

Abstract

Traffic is an issue that many big cities are confronted with because of ever-increasing population growth. In this paper we propose a two phase traffic light control system based on fuzzy Q-learning for an isolated 4-way intersection. The states and actions of the Q-learning variables is set by a fuzzy algorithm which can be learned through environmental interactions and taking advantage of fuzzy logic. The proposed algorithm was simulated for a period of one hour for each of 14 different traffic conditions. Comparison with other methods was carried out on the 14 traffic conditions. The results showed that the proposed algorithms decrease the total waiting time and the mean of queue length.
基于模糊q学习的交通灯控制
由于人口的不断增长,交通是许多大城市面临的一个问题。本文提出了一种基于模糊q学习的孤立四路交叉口两相交通灯控制系统。q -学习变量的状态和动作由模糊算法设定,该算法可以通过环境交互学习并利用模糊逻辑。在14种不同的交通状况下,对所提出的算法进行了一小时的模拟。在14种交通工况下与其他方法进行了比较。结果表明,所提出的算法能够有效地降低总等待时间和平均队列长度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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