2024
DOI: 10.1109/access.2024.3397495
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Application of Traffic Light Control in Oversaturated Urban Network Using Multi-Agent Deep Reinforcement Learning

Ei Ei Mon,
Hideya Ochiai,
Chaodit Aswakul

Abstract: Adaptive traffic signal control techniques have been developed in numerous studies to increase traffic flow efficiency. Using traffic signals to design an adaptive traffic management system is ideal for reducing traffic congestion. Reinforcement learning is a branch of current approaches that try to learn a policy function through a trial-and-error process and maximize the reward through properly adjusted interaction with the learning agent's environment. We propose a traffic signal control architecture for an… Show more

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