Resilience evaluation and improvement of post-disaster multimodal transportation networks

As a type of critical infrastructure, multimodal transportation networks are susceptible to disturbances from natural disasters and intentional attacks. Resilience reflects the performance of a multimodal transportation network after suffering from a disaster, and the failure of this network influences the public life and induces economic losses. This research aims to evaluate and improve the resilience of post-disaster multimodal intercity transportation networks to mitigate negative influences of disturbances. A comprehensive resilience performance metric, accounting for influences on unserved demand and adaptation of served demand was proposed to evaluate the resilience of multimodal transportation networks. The multimodal traffic assignment model was developed to derive the components of this comprehensive performance metric, integrating user equilibrium and modal split, while considering the capacity upper bound of some links. A route-based link recovery sequence was also proposed to improve network resilience, taking into account interdependencies and utilization of damaged links. The operational measure of capacity enlargement of functioning links was adopted to supplement the recovery sequence. The proposed resilience evaluation and improvement method was applied to a multimodal transportation network, namely, the constituent road, rail, and air networks in the Beijing–Tianjin–Hebei–Shandong region. Results show that the proposed route-based strategy outperforms volume-based, betweenness-based, and random strategies in enhancing resilience. Capacity enlargement of functioning links can further improve resilience by accommodating more affected demand, particularly effectively in scenarios characterized by inefficient repair sequences, higher fixed demand and a larger punishment multiplier. These findings highlight the interdependencies of links in establishing the recovery sequence, capacity enlargement in challenging scenarios, and enhanced availability and convenience of transportation modes to promote multimodal network resilience after a disruption.