Expressway, as the backbone of the traffic model, realizes inter-regional interconnection. The expressway network is diversified and it is the focus of research to find the shortest path between the starting node and the goal node efficiently and quickly from the huge expressway network data. Clustering analysis algorithm can complete the shortest path analysis of expressway network through data preprocessing technology and online query. Based on clustering analysis algorithm, this study explores the shortest path analysis method of expressway network model, and puts forward relevant statistical parameters. The results show that the data obtained by Matlab simulation is in good coincidence with the actual expressway network structure. The pre-processing time of the shortest path calculated by clustering analysis algorithm increases with the increase of the distance between the starting node and the goal node and the time spent by clustering analysis algorithm is less than that of construction hierarchy algorithm and CDZ algorithm, and the accuracy of clustering analysis algorithm is higher. This study is of a certain guiding significance for the analysis and planning of expressway network.
Keywords: expressway; clustering analysis algorithm; shortest path; Matlab simulation; starting node; goal node