Research on the Public Transport Network Based on Complex Network

Abstract

The public transport infrastructure of a city is one of the most important indicators of its economic growth and development. Here we investigate the statistical properties of the public transport network in Shenyang to explore its various properties based on complex network theory. The statistical properties of the public transport system consist of the degree of a node, the average shortest path length, the clustering coefficient of a node, the average clustering coefficient, and the degree distribution. In contrast with the small world evolution model, we find that the public transport system of Shenyang, a network of public transportation routes connected by bus links, is a small-world network characterized by a Poisson degree distribution. Simulation results show that the public transport network exhibits small world behavior with N=148.