Complexity analysis of railway passenger transport service network

With the development of complex science, the complex network theory has been widely used in the field of transport system. The current paper statistically analyzed the China railway passenger transport service network using the complex network theory. Several important factors are concerned: the degree distribution of nodes, average path length, and clustering coefficient. The results indicate that a power-law distribution curve is used to fit the RPTSN (railway passenger transport service network). Regarding the shortest path length, there are average 4 or 5 stop sites from one stop site to other stop site. The results of the static indicators prove that the RPTSN is a scale-free network.