Dynamic path optimization method based on ant colony algorithm and group decision-making

The paper built an urban road network model through analysis of urban traffic flow characteristics. The minimizing total travel time of vehicle in the road network was taken as control target, and the dynamic path model was built. The ant colony algorithm was used to find out the optimum path from start point to destination by collecting the real-time traffic information of the road network. Then using the theory of group decision making, the dynamic path optimization method was put forward. In this method, the two parameters of distance between adjacent intersections and section traffic flow saturation which have influence on the control target was considered, and they were combined with ant colony algorithm, and the optimal path was gotten through the group decision making for different results of the algorithm, and the realization of the optimization method was given. The dynamic path optimization process of regional network was described by programming with Matlab through a simulation example. The results show that the new method in this paper had better control effect compared with other methods.