Resilience patterns of urban road networks under the worst‐case localized disruptions

Author:

Du Chongyang1ORCID,Ouyang Min12,Zhang Hui1,Wang Bo1,Wang Naiyu3

Affiliation:

1. School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

2. Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan China

3. College of Civil Engineering and Architecture Zhejiang University Hangzhou China

Abstract

AbstractRecent events, including COVID‐19, extreme floods, and explosion accidents, commonly induced localized closures and disruptions of urban road networks (URNs), resulting in significant impacts on human mobility and socio‐economic activities. Existing studies on URN resilience to those events mainly took few cases for empirical studies, limiting our understanding on the URN resilience patterns across different cities. By conducting a large‐scale nationwide resilience analysis of URNs in 363 cities in mainland China, this study attempts to uncover the resilience patterns of URNs against the worst‐case single (SLDs) and multiple localized disruptions (MLDs). Results show that the distance from the worst‐case SLD to the city center would be less than 5 km in 62.3% cities, as opposed to more than 15 km in 14.3% cities. Moreover, the average road network resilience of cities in western China could be 7% and 13% smaller than that of the eastern cities under the worst‐case SLDs and MLDs, respectively. This inequality in the worst‐case resilience is partly attributable to variations in urban socio‐economic, infrastructure‐related, and topographic factors. These findings could inspire nationwide pre‐disaster mitigation strategies to cope with localized disruptions and help transfer insights for mitigation strategies against disruptive events across cities.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Physiology (medical),Safety, Risk, Reliability and Quality

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