Comparative study of several intelligent optimization algorithms for traffic control applications

For the problems of the traditional control methods in current urban traffic control system can not effectively meet the real-time traffic flow variation and it's inefficiency, several optimization algorithms are proposed in this paper. Simulation results show that each algorithm has strong robustness, adaptivity and self-learning ability, all of them can solve problems of area traffic control signal timing optimization efficiently.