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Journal of Advanced Transportation
Volume 2017, Article ID 6193127, 12 pages
Research Article

Modeling Road Network Vulnerability for Evacuees and First Responders in No-Notice Evacuation

1School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
2Department of Emergency Management, Arkansas Tech University, Russellville, AR 72801, USA

Correspondence should be addressed to Xiang Chen; moc.liamg@retepgnaixnehc

Received 15 February 2017; Accepted 10 April 2017; Published 14 May 2017

Academic Editor: Dongjoo Park

Copyright © 2017 Xiang Chen and Qiang Li. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The concept of vulnerability has been employed to develop transport systems that sustain devastating disasters and ensure the efficient evacuation of neighborhoods. Existing studies of road network vulnerability overlook two important aspects of analysis: the no-notice evacuation and the different objectives of evacuees and first responders. First, a no-notice evacuation leaves limited time for proactive emergency planning; therefore, rescue strategies in this scenario rely heavily on real-time traffic information. Second, the goal of first responders in an evacuation is to move into an affected area immediately after a hazardous event unfolds, and the risk they face differs from that of evacuees. To this end, this paper develops a network-based model to evaluate vulnerability during a no-notice evacuation and applies it to a case study in Dublin, OH, USA. The model is suited to assessing network vulnerability in response to events with uncertainty and coordinating traffic control strategies in a no-notice evacuation. This study can become a valuable complement to the methodological conceptualization of vulnerability and can provide insights into developing comprehensive emergency management plans.