A Computational Approach For Evaluating Post-Disaster Transportation Network Resilience

The comprehension of transportation network resilience is of prime interest to transportation agencies. Thus, this study seeks to complement the ongoing discussion by (i) extending a traffic assignment model in a hypothetical framework by considering multilevel bridge damages and recovery sequences; (ii) formulating recovery time-sensitive network resilience indexes that account for bridge closures; and (iii) undertaking sensitivity analyses to verify the adequacy of the formulations in explaining transportation network resilience. This work improves the original resilience measure which has the tendency to yield the same values for different recovery curves. Analytical results highlight expected functional losses under various bridge closure events. Resilience indexes echo the importance of comparing predicted to scheduled restoration times because this method ensures that systems that recover earlier than scheduled are identified as more resilient and vice versa. Sensitivity analyses reinforce the previous assertion, stressing the need for rapid recovery instead of simply mitigating functional losses