Robustness of urban railway networks against the cascading failures induced by the fluctuation of passenger flow

This paper constructs an urban railway network (URN) as a directed weighted network at different times and studies the dynamic network robustness against the fluctuation of passenger flow-induced cascading failures under different failure modes. The propagation of cascading failure is then imitated through the linear threshold (LT) model, where the influence parameter of edges is defined. In the light of network topology and functionality, two robustness indices, which include the change of edge size in the most connected component (R_GCSe) and operational efficiency (R_OEt) are employed. By coalescing these two indices, a synthetic operator R_t is proposed to quantify the dynamic TURN robustness comprehensively. The simulation results show that the TURN robustness varies over time. Besides, an increase in the volume of passenger flow can exacerbate the sizes of cascading failure and the impacts on network robustness under different scenarios. Consequently, it is imperative to examine the impacts of time-varying cascading failure on URN robustness. The findings of this research are widely applicable to other networked systems.