DERLight: A Deep Reinforcement Learning Traffic Light Control Algorithm with Dual Experience Replay,ERICDATA高等教育知識庫
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篇名
DERLight: A Deep Reinforcement Learning Traffic Light Control Algorithm with Dual Experience Replay
並列篇名
DERLight: A Deep Reinforcement Learning Traffic Light Control Algorithm with Dual Experience Replay
作者 Zhichao YangYan KongChih-Hsien Hsia
英文摘要

In recent years, with the increasingly severe traffic environment, most cities are facing various traffic congestion problems, and the demand for intelligent regulation of traffic signals is also increasing. In this study, we propose a new intelligent traffic light control algorithm, dual experience replay light (DERLight), which innovatively and efficiently designs a dual experience replay training mechanism based on the classic deep Q network (DQN) framework and considers the dynamic epoch function. As results show that compared with some state-of-the-art algorithms, DERLight can shorten the average travel time of vehicles, increase the throughput at intersections, and also speed up the convergence of the network. In addition, the design of this algorithm framework is not only limited to the field of intelligent transportation, but also has transferability for some other fields.

 

起訖頁 079-086
關鍵詞 Deep reinforcement learningTraffic light controlDual experience replayDynamic epoch function
刊名 網際網路技術學刊  
期數 202401 (25:1期)
出版單位 台灣學術網路管理委員會
DOI 10.53106/160792642024012501007   複製DOI
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