Road Network Vulnerability Assessment Based on Fragile Factor Interdependencies in Spatial-Functional Perspectives

Cheng-Hsien Hsieh and Cheng-Min Feng
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Cheng-Hsien Hsieh: Department of Marketing and Logistics Management, Chihlee Institute of Technology, 313, Sec. 1, Wenhua Road, Banqiao District 22050 New Taipei City, Taiwan
Cheng-Min Feng: Department of Transportation and Logistics Management, National Chiao Tung University, 4F, 118, Sec. 1, Chung-Hsiao W. Road, 10044 Taipei City, Taiwan

Environment and Planning A, 2014, vol. 46, issue 3, 700-714

Abstract: Road networks are instrumental in resource allocation and preevacuation, and profoundly affect disaster response and recovery, particularly emergent-disaster logistics and island rescues. Disruptions to road networks impair daily operations, irrespective of whether they are damaged by external forces or failures in interacting elements. However, functional interdependency is absent from transportation vulnerability assessments. This study thus constructed a framework to assess the interdependent vulnerability of road network failures. Based on eleven fragile factors developed in the literature and an empirical case study in the Taipei metropolitan area, road network vulnerability is determined by fuzzy cognitive maps and geographic information systems for functional and spatial interactions, respectively. The analytical results indicate that road network vulnerability is underestimated if the interdependency is neglected. Delay time on the shortest substitution, level of service on adjacent links, and inaccessibility to hospital emergency centers significantly affect vulnerability. Whereas certain socioeconomic resilience is performed in the short term, spatial–functional interdependency dilutes those effects in the long term. The framework developed facilitates decision makers in understanding interdependent vulnerabilities and adopting appropriate strategies to improve vulnerability.

Keywords: road network vulnerability; interdependency; geographic information system (GIS); fuzzy cognitive maps (FCMs) (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envira:v:46:y:2014:i:3:p:700-714

DOI: 10.1068/a4664

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