Network-Wide Traffic Signal Control Based on MARL with Hierarchical Nash-Stackelberg Game Model

Network-wide traffic signal control is an important means of relieving urban congestion, reducing traffic accidents, and improving traffic efficiency. However, solving the problem of computational complexity caused by multi-intersection games is challenging. To address this issue, we propose a Nash-...

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Veröffentlicht in:	IEEE access Jg. 11; S. 1
Hauptverfasser:	Shen, Hui, Zhao, Hongxia, Zhang, Zundong, Yang, Xun, Song, Yutong, Liu, Xiaoming
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Approximation algorithms Game theory Games Hierarchical game model Machine learning Multi-agent reinforcement learning Multi-agent systems Multiagent systems Network-wide traffic signal control Optimization Process control Q-learning Reinforcement learning Roads Roads & highways Traffic accidents Traffic congestion Traffic control Traffic flow Traffic intersections Traffic models Traffic signals Travel time Urban areas
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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