Research of Highway Transportation Path Planning Based on a Fast Traveler Demand Clustering Algorithm

Abstract

To realize real–time and reliable transportation path planning for improving the efficiency of a traveler in a highway transportation network, this paper presents a fast traveler demand clustering algorithm based on simulated annealing particle swarm optimization (SAPSO). First, we apply fast clustering according to the traveler demand obtained by a cooperative vehicle system, and then integrate the results with the planning destination target and traveling vehicle information to realize the optimized highway transportation path. Based on an experiment and comparison results, this method has better performance than two algorithms and has high effectiveness and should increase traveler satisfaction.