Revisiting cascading failures in urban rail transit networks: a multilayer framework integrating timetable constraints and passenger responses

Cascading failures have been widely used to assess vulnerability in urban rail transit networks (URTNs), yet most existing models rely on assumptions that are misaligned with timetable-based rail operations. In particular, they often equate congestion with functional failure, assume that station failures disable line operations, and allow unrestricted passenger redistribution, which may artificially amplify disturbance propagation. This study revisits cascading failures in URTNs from an operational perspective and develops a simulation framework that integrates (i) timetable-based batch service with explicit boarding/alighting and dwell-time dynamics, (ii) destination-oriented and time-dependent passenger demand, and (iii) passenger responses to service inaccessibility within a multi-layer network representation. Numerical experiments in the Shanghai URTN show that isolated station disruptions rarely trigger large-scale cascading failures under realistic parameters. More pronounced propagation emerges under consecutive train cancellations, but remains spatially localized and temporally bounded. Comparative experiments further show that stronger propagation arises mainly when passenger exit is suppressed and service continuity at failed stations is removed, highlighting the buffering roles of realistic accessibility limits and the multilayer service representation. Sensitivity analyses demonstrate the buffering role of residual capacity. These findings imply that large-scale cascades reported for URTNs appear to be sensitive to modeling assumptions, especially continuous flow redistribution, enforced topological disconnection, and the treatment of congestion as failure, rather than an inherent property of timetable-based rail operations.