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CycLight: learning traffic signal cooperation with a cycle-level strategy
This study introduces CycLight, a novel cycle-level deep reinforcement learning (RL) approach for network-level adaptive traffic signal control (NATSC) systems.
Joint Optimization of Traffic Signal Control and Vehicle Routing in Signalized Road Networks using Multi-Agent Deep Reinforcement Learning
In this paper, we propose a joint optimization approach for traffic signal control and vehicle routing in signalized road networks.
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