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 m comparison with results found in the literature, vehicle delay time is significantly reduced using the proposed method.