Urban Arterial Traffic Signal Coordination Control Research Based On Immune Algorithm

Congestion in urban traffic is a problem commonly concerned around the world, and the harmful results that produce are increasingly affecting our daily life and the development of our society. As the distributing center of urban traffic, intersections are the main taches that caused congestion, and rationally controlling the traffic flow in the intersection is not only an important method to relieve the traffic congestion but also a key respect to study urban traffic. As the important part of urban traffic network, the arterial traffic affects the whole urban traffic. In this paper, urban traffic signal control is studied, and urban arterial traffic signal coordination control is mainly studied.Firstly, the basic theory of traffic signal control is discussed. And the modeling course, timing optimization and system performance of three typical traffic signal control system is studied.Then the concept of a multi-objective optimization is briefly introduced, and a new multi-objective evolutionary algorithm for the distribution of evaluation methods is proposed. Immune algorithm is an intelligent optimization algorithm by simulating biological immune system function, which can solve complex engineering problems potential. In this paper a new multi-objective immune algorithm based on multi-population is proposed by the use of genetic algorithms parallel mechanism to avoid local convergence. Each population interacts mutually information by the shift of excellent individual. This can effectively promote the diversity of population, and accelerate convergence rate. The performance comparison has been made between the new method and the traditional Multi-objective evolutionary algorithm NSGA-II by using several typical testing functions in algorithms simulation experiment. Experimental results suggest that the proposed approach can resolve the problem of multi-objective effectively and has better performances.Finally, urban arterial traffic signal coordination control is mainly studied. In summing up the characters and shortage of exist methods, a new coordination control method is presented, which is to minimize the delay of vehicles in the artery. Then a dynamic optimization and control model which adopts offset as variables for an urban bidirectional artery system is established. An offset optimization simulation is conducted in a dynamic traffic demand mode by using the multi-poputation immune algorithm proposed in the paper, basic genetic algorithm and timing control method. The results show the delay by using multi-poputation immune algorithm is less than by using basic gennic algoritnm and in timing control obviously, which proved the validity of the proposed mothod and the applicabity of the proposed algorithm in this optimization problem.