Research On An Application In The Field Of Intelligent Transportation System By Improved Ant Colony Algorithm

In order to solve the increasingly serious traffic problems,the Intelligent Traffic Systems(ITS)which is based on the advanced information technology,data communication technology,sensor technology,electronic control technology and computer technology is coming at the proper moment.The optimal path planning problem is the most important for intelligent transportation system.Now some intelligent optimal algorithms are used to solve the problem,however,there are some issues to be considered for the problem.Therefore some research work for these issues is developed.The main works are as following:Firstly,a model is established for the optimal path planning problem in intelligent transportation system.Then the ant colony algorithm is used to solve the optimal model.In order to improve the efficiency of the ant colony algorithm,the effect of the parameters for the performance of the algorithm is studied through the simulation experiments.Therefore it provides a method for choosing the parameters of ACO.To improve the effectiveness of the ACO to solve the optimal path algorithm,an approach is proposed based on the ACO and genetic algorithm.The genetic algorithm is used to generate the initial pheromone distribution,and then the positive feedback strategy of ACO is used to provide the optimal solution for the problem.Furthermore in order to the related parameters for dynamic update,rewards and punishment mechanism is introduced.At last,the general path optimization problem is analyzed,and two of the most classical VRP mathematical model is built.Then the proposed approach is used to solve the model and the simulation results for the VRP problem verified the validity the method.