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

被引:4
作者
Du, Chongyang [1 ]
Ouyang, Min [1 ,2 ]
Zhang, Hui [1 ]
Wang, Bo [1 ]
Wang, Naiyu [3 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Key Lab Image Proc & Intelligent Control, Minist Educ, Wuhan, Peoples R China
[3] Zhejiang Univ, Coll Civil Engn & Architecture, Hangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
localized disruption; resilience pattern; urban road network; worst-case scenario; MATHEMATICAL FRAMEWORK; ACCESSIBILITY; INFRASTRUCTURES; RELIABILITY; HEALTH;
D O I
10.1111/risa.14236
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页码:2333 / 2347
页数:15
相关论文
共 70 条
  • [1] Characterization of Vulnerability of Road Networks to Random and Nonrandom Disruptions Using Network Percolation Approach
    Abdulla, Bahrulla
    Birgisson, Bjorn
    [J]. JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2021, 35 (01)
  • [2] [Anonymous], 2020, press release
  • [3] Spatial networks
    Barthelemy, Marc
    [J]. PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS, 2011, 499 (1-3): : 1 - 101
  • [4] The size, scale, and shape of cities
    Batty, Michael
    [J]. SCIENCE, 2008, 319 (5864) : 769 - 771
  • [5] BBC News, 2021, BBC NEWS 1115
  • [6] Localized attacks on spatially embedded networks with dependencies
    Berezin, Yehiel
    Bashan, Amir
    Danziger, Michael M.
    Li, Daqing
    Havlin, Shlomo
    [J]. SCIENTIFIC REPORTS, 2015, 5
  • [7] Measuring the long-distance accessibility of Italian cities
    Beria, Paolo
    Debernardi, Andrea
    Ferrara, Emanuele
    [J]. JOURNAL OF TRANSPORT GEOGRAPHY, 2017, 62 : 66 - 79
  • [8] A unified theory of urban living
    Bettencourt, Luis
    West, Geoffrey
    [J]. NATURE, 2010, 467 (7318) : 912 - 913
  • [9] The Origins of Scaling in Cities
    Bettencourt, Luis M. A.
    [J]. SCIENCE, 2013, 340 (6139) : 1438 - 1441
  • [10] OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks
    Boeing, Geoff
    [J]. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2017, 65 : 126 - 139