A Case Study of Transportation Network Resiliency of Santo Domingo, Dominican Republic

摘要

Everyday the dependence on transportation grows as local, regional, national, and internationalindependence increases. Resilient transportation systems are needed to secure the highestpossible Level of Service during disruptive events including natural and man-made disasters. Toprepare for these events, decision makers need guidance to determine what investments are likelyto improve the resiliency of their networks that are often hampered by limited resources. Suchguidance to date has been largely qualitative.This paper presents a methodology to quantify resiliency, at pre-event conditions, using afuzzy inference approach. This methodology expands upon previous work by the authors andothers, refining key variable definitions, adjusting model interactions, and increasingtransparency between metrics.A case study is included in which the methodology is applied to a disruptive event inSanto Domingo, Dominican Republic. The case study illustrates the methodology's ability to: a)evaluate the extent to which the Dominican Republic's transportation network is prepared for adisruptive event; b) help select investments that have the potential to increase the resiliency ofthe network; and 3) provide outputs that will support a variety of current economic analysisstrategies, allow for the comparison of different investment scenarios, and facilitate decision-making. The paper concludes a sensitivity analysis that shows the effects of alternativeinvestments on network.