Formalized learning automata with adaptive fuzzy coloured Petri net; an application specific to managing traffic signals

Investigation of the chaotic behavior of traffic streams at urban intersections due to signals has involved researchers in endeavoring to predict a smooth traffic flow model for stabilizing traffic congestion and avoid unnecessary delays. In this paper, we study a hybrid adaptive model, based on a combination of coloured Petri nets, fuzzy logic and learning automata, to efficiently control traffic signals. We show that in comparison with results found in the literature, vehicle delay time is significantly reduced using the proposed method.