Абстрактный

Improvement of genetic algorithm and its application in optimal control of intersections

Nan Ji1, Jie Zhang, Yingna Zhao

In this paper, average vehicle delay time is used as objective function to evaluate the performance of intersection signal control. Through the evolution process of dynamic adjustment in the population fitness the value of crossover probability and mutation probability of the maximum individual, then realize the improvement of genetic algorithm, effectively avoid the premature phenomenon. The simulation experiments show that the method is an effective and reliable method