Real-Time Network-Level Traffic Signal Control: An Explicit Multiagent Coordination Method

Traffic signal control (TSC) has been one of the most useful ways for reducing urban road congestion. The challenge of TSC includes 1) real-time signal decision, 2) the complexity in traffic dynamics, and 3) the network-level coordination. Reinforcement learning (RL) methods can query policies by ma...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems 2024-12, Vol.25 (12), p.19688-19698
Hauptverfasser:	Wang, Wanyuan, Zhang, Haipeng, Qiao, Tianchi, Ma, Jinming, Jin, Jiahui, Li, Zhibin, Wu, Weiwei, Jiang, Yichuan
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Computer science Cost function distributed constraint optimization problem Electromagnetic compatibility message-passing multiagent coordination Real-time systems Reinforcement learning Roads Scalability Traffic signal control Turning Vehicle dynamics
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