Empirical investigation of topological and weighted properties of a bus transport network from China

Many bus transport networks (BTNs) have evolved into directed networks. A new representation model for BTNs is proposed, called directed-space P. The bus transport network of Harbin (BTN-H) is described as a directed and weighted complex network by the proposed representation model and by giving each node weights. The topological and weighted properties are revealed in detail. In-degree and out-degree distributions, in-weight and out-weight distributions are presented as an exponential law, respectively. There is a strong relation between in-weight and in-degree (also between out-weight and out-degree), which can be fitted by a power function. Degree–degree and weight–weight correlations are investigated to reveal that BTN-H has a disassortative behavior as the nodes have relatively high degree (or weight). The disparity distributions of out-degree and in-degree follow an approximate power-law. Besides, the node degree shows a near linear increase with the number of routes that connect to the corresponding station. These properties revealed in this paper can help public transport planners to analyze the status quo of the BTN in nature.

[1]  Alessandro Vespignani,et al.  The Structure of Interurban Traffic: A Weighted Network Analysis , 2005, physics/0507106.

[2]  Yurij Holovatch,et al.  Network harness: Metropolis public transport , 2007 .

[3]  Yong-Zhou Chen,et al.  A study on some urban bus transport networks , 2007 .

[4]  Jianhua Zhang,et al.  Networked characteristics of the urban rail transit networks , 2013 .

[5]  V. Palchykov,et al.  Public transport networks: empirical analysis and modeling , 2008, 0803.3514.

[6]  Baoyu Hu,et al.  Empirical study on a directed and weighted bus transport network in China , 2016 .

[7]  Bao-qun Yin,et al.  Power-law strength-degree correlation from resource-allocation dynamics on weighted networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  Panagiotis Angeloudis,et al.  Large subway systems as complex networks , 2006 .

[9]  Shengyong Chen,et al.  Study on some bus transport networks in China with considering spatial characteristics , 2014 .

[10]  Pan Di,et al.  Weighted complex network analysis of travel routes on the Singapore public transportation system , 2010 .

[11]  A. Vespignani,et al.  The architecture of complex weighted networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[12]  Chen Yong-zhou,et al.  Connectivity correlations in three topological spaces of urban bus-transport networks in China , 2008 .

[13]  J. Hołyst,et al.  Statistical analysis of 22 public transport networks in Poland. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Xinping Xu,et al.  Scaling and correlations in three bus-transport networks of China , 2007, 0708.2606.

[15]  J.I.L. Miguens,et al.  Travel and tourism: Into a complex network , 2008, 0805.4490.