Measuring and Maximizing Resilience of Transportation Systems for Emergency Evacuation

Abstract

A transportation system's resilience refers to its ability to recover and provide timely transportation services in emergency situations, which is extremely important for highly urbanized societies. However, the previous literature has not considered measuring resilience under different emergency levels or maximizing resilience by managing potential traffic demand. This article proposes a novel framework for resilience analysis that is composed of measurement and improvement. An approach based on emergency levels, quantified as the number of damaged lanes, is designed to evaluate the resilience of transportation systems. A genetic algorithm is used to identify the worst combination of damaged lanes under each emergency level. In maximizing the resilience, we use the integrated reconfiguration of both traffic supply and demand as the optimal recovery solution, which reduces traffic demand through a combination of different traffic modes and increases traffic capacity through a contraflow technique. The numerical results show that the proposed model can identify the maximum damage a system can resist and can determine the optimal recovery solution. Finally, some managerial insights on transportation system evaluation and emergency planning are obtained.