A multidimensional resilience assessment framework for urban road networks under time-varying link disruptions

Local road disruptions can redistribute traffic and cause network-wide performance degradation, yet existing resilience studies integrate operational, topological, recovery, and uncertainty dimensions unevenly. This study develops a multidimensional resilience assessment framework for time-varying link disruptions. At each hourly interval, the framework updates link damage and repair states, active topology, and capacities. It reassigns fixed origin–destination demand using a quasi-static deterministic user-equilibrium model solved by the Frank–Wolfe algorithm. The framework then calculates normalized traffic-operational and topological performance and derives robustness, cumulative recovered performance, and cumulative performance loss. A case study of the Xi’an network evaluates nine disruption scenarios. Complete blockage generally causes greater performance loss than partial capacity reduction. Robustness declines as more links are affected, disrupted-link structural characteristics influence all three indicators, and random damage severity broadens their distributions. The framework supports scenario comparison, critical-link identification, resilience-oriented planning, and emergency repair prioritization.