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Published on: January 20, 2023
Resilience patterns of urban road networks under the worst-case localized disruptions
Chongyang Du1, Min Ouyang1,2, Hui Zhang1
1School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.
Abstract:
Recent 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.
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