Self-organized Control Of Traffic Signals Through Genetic Reinforcement Learning

This paper introduces a learning approach for traffic signal control. The reinforcement learning is intended to optimize the traffic flow around cross roads, while the Genetic Algorithms are intended to introduce a global optimization criterion to each of the local learning processes. It is shown that the combination of reinforcement learning and the Genetic Algorithm exhibits good performance for dense traffic conditions.