A Fusion Approach of Reinforcement Learning and Traffic Engineering in Multiple Traffic Signal Control
This paper targets traffic signal control in Japan and proposes an implementable signal control method by combining reinforcement learning with traditional traffic engineering, demonstrating the potential of integrating traffic engineering with RL to develop effective signal control methods.
Yoshiki Yamamoto, Marika Izawa
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