Study of fuzzy control for intersections based on improved genetic algorithm
基于改进遗传算法的交叉口模糊控制研究

In order to decreas vehicle delay in intersection, this paper presented an improved GA-based fuzzy control method for the traffic signal in urban intersections. To avoid prematurity problem, applied improved adaptive GA to optimizing the fuzzy controller. The crossing and mutation probability of individual that enjoyed the maximum fitness value were dynamically adjusted during the evolution of the population, which ensured that the evolution of the population will not suspend. To validate the performance of this control method, carried out simulation with vehicle average delay in the intersections being the performance index. The result indicates that the optimized fuzzy controller outperforms the traditional one in decreasing the vehicle average delay and increasing traffic capacity of the intersections.