Correlation between heterogeneity and vulnerability of subway networks based on passenger flow

Abstract In this paper, we represent a subway network as a dynamic, directed and weighted graph, where vertices represent subway stations and edge weights represent passenger volume passing between two stations. Static and dynamic metrics which can represent vertices and edges' local and global attributes are proposed. Then dynamic properties of subway network in heterogeneity and vulnerability are further analyzed by standard deviation. Through a detailed analysis of Beijing subway network, we illustrate that the heterogeneity and vulnerability of Beijing subway network vary over time when passenger flow is taken into consideration. In addition, the vulnerability of the network is correlated with its heterogeneity based on local dynamic metric's distribution when passenger flow is taken into account, instead of the global dynamic metric's distribution, and the important station with higher flow degrees are identified.

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

[2]  Shauhrat S Chopra,et al.  A network-based framework for assessing infrastructure resilience: a case study of the London metro system , 2016, Journal of The Royal Society Interface.

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

[4]  Sybil Derrible,et al.  The complexity and robustness of metro networks , 2010 .

[5]  Wang Ying,et al.  Evaluating Disruption in Rail Transit Network: A Case Study of Beijing Subway , 2016 .

[6]  Yongxue Liu,et al.  Robustness assessment of urban rail transit based on complex network theory: a case study of the Beijing Subway , 2015 .

[7]  K. Seaton,et al.  Stations, trains and small-world networks , 2003, cond-mat/0311254.

[8]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[9]  Qiming Li,et al.  A Research on Subway Physical Vulnerability Based on Network Theory and FMECA , 2015 .

[10]  Massimo Marchiori,et al.  Is the Boston subway a small-world network? , 2002 .

[11]  Keumsook Lee,et al.  Statistical analysis of the Metropolitan Seoul Subway System: Network structure and passenger flows , 2008, 0805.1712.

[12]  J Li.  Research of Complexity of Urban Subway Network , 2009 .

[13]  Keiki Takadama,et al.  Analysis on Transport Networks of Railway, Subway and Waterbus in Japan , 2007, Emergent Intelligence of Networked Agents.

[14]  Shuliang Wang,et al.  Networked analysis of the Shanghai subway network, in China , 2011 .

[15]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[16]  Ying Lu,et al.  Topology Vulnerability Analysis and Measure of Urban Metro Network: The case of Nanjing , 2013, J. Networks.

[17]  Hong Cai,et al.  Vulnerability Analysis of Metro Network Incorporating Flow Impact and Capacity Constraint after a Disaster , 2017 .

[18]  Tao Tang,et al.  Measuring Route Diversity for Urban Rail Transit Networks: A Case Study of the Beijing Metro Network , 2017, IEEE Transactions on Intelligent Transportation Systems.

[19]  Yue Deng,et al.  Analysis of Site Selection for Metro Emergency Stations in Network Operation , 2013 .