Large-scale traffic signal control using machine learning: some traffic flow considerations

7 Aug 2019 Jorge A. Laval Hao Zhou

This paper uses supervised learning, random search and deep reinforcement learning (DRL) methods to control large signalized intersection networks. The traffic model is Cellular Automaton rule 184, which has been shown to be a parameter-free representation of traffic flow, and is the most efficient implementation of the Kinematic Wave model with triangular fundamental diagram... (read more)

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Random Search
Hyperparameter Search