The objective of this comprehensive review study was to compile a state-of-the-art understanding of the resilience of the transportation system due to natural and man-made disasters. This study identified resilience measurement parameters that can be used to formulate resilience quantification and improvement strategies of a transportation system. Reviewed articles were classified and summarized from two perspectives: (i) modeling based on the mode of transportation; and (ii) modeling based on the mathematical technique used to quantify resilience. One of the unique contributions of this review article is that it compiled the key resilience indices that were analyzed to quantify resilience. This review revealed that the majority of the scholarly articles on the topic of transportation system resilience published since 2006, were focused on the resilience of the roadway-based transportation system, and vulnerability was one of the most explored resilience indices in evaluating transportation system resilience. Several future research directions were identified considering the implications of emerging transportation technologies (e.g., connected and automated vehicle technology). The complex interdependency among critical infrastructure systems such as power, transportation, and communication system, as well as the cybersecurity issues in the advanced intelligent transportation system, will be vital in the resilience analysis of future transportation systems.

Large-scale natural disasters challenge the resilience of the surface transportation system. The objective of this research was to develop a resilience model of the surface transportation system with a mixed-traffic environment and considering varying Connected and Automated Vehicle (CAV) penetration scenarios. As deployment of CAVs is expected to improve traffic operations, a resilience model was developed in this research to evaluate the resilience performance of a transportation system with several CAV penetration levels (0%, 25%, 50%, 75%, and 100%) for a given budget and recovery time. The proposed resilience quantification model was applied on a roadway network considering several disaster scenarios. The network capacity in relation to trips at any phase of disaster was compared with the pre-disaster trips to determine the system resilience. The capacity variation and the travel time variation were also estimated. The analysis showed that the resilience of the transportation system improved with CAVs in relation to travel time and capacity improvement. Link travel times were significantly improved by higher CAV penetration rate. The findings also suggested that higher penetration of CAVs (i.e., 50% or more) increased the recovery costs. For example, the recovery costs needed for medium and large-scale disasters were 50% and 90% higher, respectively, compared with the recovery costs for a small-scale disaster. These higher costs were primarily for the repair and replacement of intelligent infrastructure required to support the operation of CAVs.

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Resilience Modeling of Surface Transportation System in Mixed Traffic Environment Shofiq Ahmed Large-scale natural disasters challenge the resilience of surface transportation system. The objective of this research was to develop a resilience model of surface transportation system in mixed-traffic environment considering varying Connected and Automated Vehicle (CAV) penetration scenarios. As deployment of CAVs are expected to improve traffic operations, a resilience model was developed in this research to evaluate the resilience performance of a transportation system with several CAV penetration levels (0%, 25%, 50%, 75% and 100%) for a given budget and recovery time. The proposed resilience quantification model was applied on a roadway network considering several disaster scenarios. The network capacity in terms of trips at any phase of disaster was compared to the pre-disaster trips to determine the system resilience. The capacity variation and the travel time variation was also estimated. The analysis showed that the resilience phenomenon of the transportation system improved with CAVs in respect of travel time and capacity improvement. The rate of improvement in link travel time for varied CAV penetration was almost identical for different disaster scenarios. For each disaster scenario, the individual link travel time reduced significantly with increased CAV penetration. However, higher penetration of CAVs (i.e., 50% or more), increased the recovery budget requirement. For example, the recovery budget needed for medium and large-scale disasters were 50% and 90% higher respectively compared to the recovery budget needed for a small-scale disaster. These higher costs were primarily needed for repair and replacement of intelligent infrastructure required for CAV.

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