Resilience Assessment of Multimodal Transportation Networks: A Hypergraph-Based Modeling Framework

Research on the resilience of multimodal transportation networks holds significant theoretical and engineering value for enhancing the collaborative recovery capabilities of urban agglomerations under extreme disturbances. However, existing methods are limited by the discrete representation of higher-order interactions in multilayer network models and lack a crossscale resilience assessment framework that integrates network-node coordination. This paper proposes a hypergraph theorydriven fusion modeling approach from a higher-order perspective. Composite hyperedges are constructed to characterize highway-railway-aviation multimodal transportation. A three-dimensional assessment framework integrating topological property analysis, dynamic perturbation simulation, and path accessibility is established. A depth-first search algorithm quantifies the resilience gain of critical hub nodes under multimodal alternative paths. Experimental results demonstrate that, compared to traditional multilayer network models, the proposed method effectively captures synergistic transportation among multiple nodes and hyperedges, evaluates the resilience of multimodal transportation networks, and provides an engineering-transposable methodological tool for resilience optimization and hub redundancy design in urban agglomeration traffic emergency management systems.