Traffic-State-Dependent Cascading-Failure Dynamics in Urban Bus Networks: An Improved Coupled Map Lattice Framework

Urban bus networks are exposed to cascading disruptions whose propagation depends not only on network topology but also on temporally varying traffic states and passenger-flow distributions. Existing vulnerability analyses often rely on static topology or hypothetical flows, limiting their ability to characterize traffic-dependent failure dynamics. This study develops a data-driven vulnerability framework for urban bus networks by integrating a coupled road-bus network, user-equilibrium assignment and a weighted Coupled Map Lattice (CML) model. Smart-card data are used to estimate passenger origin-destination demand, while road traffic states at four representative periods are mapped onto bus links to characterize travel-speed-dependent capacity reductions. The resulting weighted networks are evaluated using degree, strength, conventional betweenness, and traffic-flow betweenness. The improved CML model jointly incorporates topological connectivity, passenger-flow characteristics, external perturbations, and flow redistribution to simulate cascading failures under targeted and random attacks. The Harbin trunk bus network is used as an empirical case study. Results show that cascading-failure patterns are strongly traffic-state dependent: under more congested conditions, failures reach their peak propagation rate earlier. Across the tested parameter settings, perturbation intensity and coupling strength influence the timing and extent of cascade propagation, with responses varying by attack strategy and traffic condition. These findings demonstrate that incorporating time-varying traffic states and actual passenger flows can reveal vulnerability patterns that static topology-based analyses may overlook, providing a basis for time-sensitive disruption management and resilience-oriented bus operations.