An integrated resilience assessment model of urban transportation network: A case study of 40 cities in China

The transportation network is essential in providing daily accessibility and essential service to societies. An acceptable level of service needs to be maintained in critical infrastructures, even in the case of disruptions. The authors develop an integrated model to assess the resilience of urban transportation networks when exposed to different disruptions. Resilience is evaluated from perspectives of both traffic network topology and traffic flow. This model contains three parts: (1) a traffic flow simulation model to get flow distributed throughout the whole network, (2) different real-world disruptions are abstracted as random, localized, and flood disturbances, (3) functional and topological resilience are accessed by analyzing variations in travel time and connected components before and after a disruption occurs. 40 major cities are chosen to conduct resilience assessments. As the intensity of the disruption increases, common trends in the changes of functional and topological resilience values are observed and analyzed across all studied cities. In most cases, flood disruption is the least disruptive one of all three types of disruptions. Regression models are developed to estimate functional and topological resilience after random, localized, and flood disturbances. Possible resilience enhancement strategies are discussed based on analyses of regression models. This study could aid stakeholders in gaining a clear understanding of resilience not only topologically but also from the perspective of traffic flow and offer them practical strategies to enhance resilience in face of disruptions.

• Record URL:
  https://doi.org/10.1016/j.tra.2023.103687
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0965856423001076
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Yin, Kai
  • 0000-0002-4440-4846
  • Wu, Jianjun
  • Wang, Weiping
  • 0000-0001-7307-3735
  • Lee, Der-Horng
  • 0000-0001-5428-8810
  • Wei, Yun
• Publication Date: 2023-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 103687
• Serial:
  • Transportation Research Part A: Policy and Practice
  • Volume: 173
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0965-8564
  • Serial URL: http://www.sciencedirect.com/science/journal/09658564

Subject/Index Terms

• TRT Terms: Disaster resilience; Level of service; Networks; Service disruption; Traffic flow; Traffic simulation; Urban transportation
• Geographic Terms: China
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Public Transportation;

Filing Info

• Accession Number: 01889495
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 1 2023 9:04AM