Measuring the dynamic evolution of road network vulnerability to floods: A case study of Wuhan, China

This study provides a new methodology to uncover the topology and dynamic evolution of road network vulnerability, and understand the interacted effects of the traffic conditions and the users/passengers’ traveling behaviors on it. In this paper, by using a data set included the traffic flows during the morning peak period (07:00 a.m. to 09:00 a.m.) in the normal state and the flood-hit state, the authors simulated and compared the dynamic characterisitics of the normal traffic condition with that of the flood-hit traffic condition. They identified and visualized 51 flood-prone areas to predict the geographical distribution of hot spots in the road network to floods. They built a conceptual framework to define and measure the vulnerability as a function of exposure and importance. The authors measured and mapped the flood-prone areas’ vulnerability scores in the normal state and the flood-hit state, respectively, and used statistical analysis to compare their dynamic characteristics. They investigated the influence of the traffic conditions and the users/passengers’ traveling behaviors on the dynamic evolution of road network vulnerability. The findings helped transport planners and decision-makers better derive the dynamic evolution of road network vulnerability affected by the users/passengers’ traveling behaviors, and they can also be used to guide the users/passengers to choose the optimum routes for improving the overall performance of the road network effectively when a flood occurs.

• Record URL:
  • https://doi.org/10.1016/j.tbs.2020.10.009
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2214367X20302313
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/2214367X
• Supplemental Notes:
  • © 2020 Hong Kong Society for Transportation Studies. Published by Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Liu, Jie
  • Shi, Zhenwu
  • Tan, Xianyu
• Publication Date: 2021-4

Language

• English

Media Info

• Media Type: Web
• Features: Figures; Maps; References; Tables;
• Pagination: pp 13-24
• Serial:
  • Travel Behaviour and Society
  • Volume: 23
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2214-367X
  • Serial URL: http://www.sciencedirect.com/science/journal/2214367X

Subject/Index Terms

• TRT Terms: Case studies; Floods; Risk assessment; Travel behavior
• Geographic Terms: Wuhan (China)
• Subject Areas: Highways; Planning and Forecasting; Security and Emergencies;

Filing Info

• Accession Number: 01760176
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 17 2020 9:53AM