Resilience-oriented road network recovery strategies with urban air mobility under rainstorm-induced waterlogging

Road networks are increasingly vulnerable to natural disasters, especially the frequent rainstorm-induced waterlogging. While existing studies have proposed various methods to recover the network performance resilience, the potential of UAM (Urban Air Mobility) as an emerging transport mode remains underexplored. This paper addresses this gap by establishing a bi-level network recovery model aimed at maximizing network performance resilience through optimized daily repair strategies for damaged links and the integration of UAM routes and flights. An ABC-based (Artificial Bee Colony) heuristic algorithm is developed to solve the bi-level model, complemented by a BRUE-based (Boundedly Rational User Equilibrium) algorithm for the lower-level model. In addition, this study further considers the geographic heterogeneity factors, including straight line flight distance, road height, road type, etc., to ensure the applicability of the optimized solution in the actual environment. The proposed method is validated through case studies involving the Sioux Falls Network and Chicago Network. The numerical results demonstrate that incorporating the UAM with optimized repair strategies significantly recovers network performance resilience post-disaster.