Data-Driven Methods to Assess Transportation System Resilience: Case Study of the Arkansas Roadway Network

This study presents a novel method for assessing systemwide resilience of highway transportation systems by considering the likelihood of disruptions and the significance of critical links in the network while relying only on data available to state transportation agencies. This work expands on corridor-level resilience and vulnerability studies by expanding the methods to network-level analyses and incorporating both data-driven estimates and stakeholder inputs. Six criteria are used to estimate the criticality of roadway segments: annual average daily traffic, roadway classification, freight value, tourism value, social vulnerability index, and redundancy. To compute redundancy, this study adopts a Network Robustness Index (NRI) method, which computes the total system travel time under a closed link scenario. Individual criticality metrics are combined using a ranked weighting approach that incorporates stakeholder feedback through the Analytical Hierarchy Process (AHP). Vulnerability is assessed for floods, landslides, and earthquakes. The criticality and vulnerability of roadway segments are combined and scored as low, moderate, and high. The methodology is applied to the Arkansas state-maintained roadway network with approximately 32,186 km segmented into 70,000 links. Comparisons are shown across scoring and weighting approaches to identify top-ranked sites. The key contribution of this work is a network expanded approach to data-driven criticality and vulnerability assessment balanced with stakeholder insights with an emphasis on commonly available data.