计算机应用研究2011，Vol.28Issue(1)：199-202,4.DOI:10.3969/j.issn.1001-3695.2011.01.056
结合Q学习和模糊逻辑的单路口交通信号自学习控制方法
Self-learning traffic signal control method of isolated intersection combining Q-learning and fuzzy logic
摘要
Abstract
To address the dynamics and uncertainty in unban transportation system, this paper proposed a traffic signal control system based on reinforcement learning, which was suitable for real-time control in isolated intersection.The proposed method was capable of online learning through a combination of BP neural network and Q-learning algorithm.Furthermore, due to the multi-objective property in traffic signal control, this paper developed a reward design method for Q-learning based on fuzzy logic.Conducted simulated experiments in three traffic scenarios, using the Paramics microscopic traffic simulation software.Experimental results show that the proposed method has high control efficiency in different traffic scenarios, and is significantly better than fixed timing control method.关键词
交通信号控制/强化学习/BP神经网络/模糊评价/Paramics仿真分类
信息技术与安全科学引用本文复制引用
何兆成,佘锡伟,杨文臣,陈宁宁..结合Q学习和模糊逻辑的单路口交通信号自学习控制方法[J].计算机应用研究,2011,28(1):199-202,4.基金项目
广东省科技计划资助项目(2009A011601013) （2009A011601013）
