The invention discloses a traffic light control method based on a deep Q network, a terminal and a storage medium, and the method comprises the steps: obtaining the traffic light information of each intersection in a preset region, and obtaining a communication topology network in the preset region according to the traffic light information; acquiring traffic light state information and traffic flow state information around the traffic light; constructing a decentralized deep Q network traffic light control model according to the communication topology network, the traffic light state information and the traffic flow state information around the traffic light; and controlling traffic lights in a preset area according to the deep Q network traffic light control model and a consistency algorithm. According to the method, the decentralized deep Q network traffic light control model is constructed based on the communication topology network, the experience of other traffic lights can be learned without sharing local experience sample data among the traffic lights through a decentralized training mode, and the traffic efficiency of a road network is improved under the condition of optimizing the control model.
本发明公开了一种基于深度Q网络的交通灯控制方法、终端及存储介质,其中,方法包括:获取预设区域内各路口的交通灯信息,并根据交通灯信息得到预设区域内的通信拓扑网络;获取交通灯状态信息和交通灯四周的车流状态信息;根据通信拓扑网络、交通灯状态信息以及交通灯四周的车流状态信息构建去中心化的深度Q网络交通灯控制模型;根据深度Q网络交通灯控制模型和一致性算法对预设区域内的交通灯进行控制。本发明基于通信拓扑网络构建去中心化的深度Q网络交通灯控制模型,通过去中心化的训练方式,使得各交通灯之间不需要分享本地的经验样本数据,就能学习到其他交通灯的经验,在优化控制模型的情况下,提高路网的通行效率。
Traffic light control method based on deep Q network, terminal and storage medium
一种基于深度Q网络的交通灯控制方法、终端及存储介质
2021-12-31
Patent
Electronic Resource
Chinese
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