Research on Intelligent Transportation System Based on Improved Ant Colony Algorithm
Abstract— At present, the optimal path planning based on the path condition has become one of the key research directions of the intelligent transportation system. Based on the characteristics and existing problems of the actual intelligent transportation system, this paper studied the intelligent transportation system based on improved ant colony algorithm. Firstly, we used the Dijkstra algorithm to plan an initial sub-optimal path, and then established the objective function by combining the distance, time and cost of vehicle travel, and improved pheromone update method. Finally using the improved ant colony algorithm simulation results, the effectiveness of the proposed method was verified. The experimental results show that the improved ant colony algorithm is used to plan the path in the intelligent transportation system and finally solve the optimal driving route. It has been improved in terms of efficiency and effectiveness, which can basically meet customer requirements and make full use of road resources and vehicle resources.
Index Terms— ant colony algorithm, intelligent transportation system, path planning, Dijkstra algorithm
Xingli Wu, Huimin Lv, Shigang Cui
Tianjin University of Technology and Education, Tianjin Key Laboratory of Information Sensing & Intelligent Control, CHINA
Cite: Xingli Wu, Huimin Lv, Shigang Cui, "Research on Intelligent Transportation System Based on Improved Ant Colony Algorithm," Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering, pp. 806-811, Bangkok, 28-30 June, 2018.