Urban traffic system is a huge system, with strong randomness and complexity. In order to effectively control the system, we must continue to study and analyze. This paper mainly discusses on the application of two kinds of intelligent optimization algorithms in urban traffic control. The algorithms are chaos genetic algorithm and chaotic particle swarm optimization algorithm. Through the simulation of these two intelligent optimization algorithms, the results show that the adaptive robust and self-learning ability of these algorithms are very strong. They can realize the optimization of traffic signal effectively. Due to the application of fixed cycle control, the average delay of vehicle has been effectively alleviated, having positive significance to improve the traffic situation.