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, Volume 107, Issue 1, pp 193–204 | Cite as

An Integrative Vulnerability Evaluation Model to Urban Road Complex Network

  • Hong ZhangEmail author
  • Yangang Yao
Article
  • 36 Downloads

Abstract

In order to analyze topological properties and vulnerable elements of urban road complex network, 98 lines and 128 nodes are selected by taking Shiyan city in China as an example. Firstly, the definitions of the urban road network’s running state vulnerability and structural vulnerability are proposed in this paper, and the assessment indexes are given respectively. From the perspective of the urban road network topology’s structural characteristics and the traffic demand characteristics, the internal relationship of the running state vulnerability and the structural vulnerability is introduced in order to show the necessity and reasonableness of the urban road network vulnerability assessment. Secondly, the concepts of the urban road network element’s structural-running state parameters are proposed to identify the source of network vulnerability. The Original Method is used to acquire the topology of the urban road network. Finally, with static vulnerability assessment principle, the structural vulnerability index is calculated on the premise that the cascading failure is not considered. With dynamic vulnerability assessment principle, the running state vulnerability index is calculated on the premise that the propagation effects of traffic congestion are considered. The results show that the vulnerability of road network is influenced by two factors: network topology structure and network running state.

Keywords

Urban road network Complex network Vulnerable element Vulnerability 

Notes

Acknowledgements

The research is sponsored by China Automotive Test Cycle (CATC) project and by Transportation Department of Inner Mongolia Autonomous Region (NJ-2017-8). We are grateful to the anonymous reviewers for their insightful comments and recommendations.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Transportation Institute of Inner Mongolia UniversityHohhotChina
  2. 2.Inner Mongolia Engineering Research Center for Urban Transportation Data Science and ApplicationsHohhotChina

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