Critical station identification for cascading failure mitigation considering the Lyapunov-stability of metro stations

In order to mitigate cascading failures, research efforts have been made to alleviate or prevent failures at critical stations that have high station influence. However, overlooking the stability of stations under cascading failures results in the station's capacity to mitigate failures remaining unknown, leading to inaccurate identification results. Thus, a station Lyapunov-stability based methodology incorporating station Lyapunov-stability and station influence is proposed to identify and protect critical stations under cascading failures. Particularly, the station Lyapunov-stability is developed by combining the evolution of passengers and disrupted network topology at stations to assess their stability. The proposed methodology is applied to Shanghai urban rail transit network. The results show that stations that would exacerbate cascading failures are usually characterized with high degree, large ridership, low betweenness, and located in the network center. However, some stations without high degree but connecting the transfer stations in the network center also have high potential to exacerbate cascading failures. In addition, when using the proposed methodology, the number of failed stations is 3 times less than that of state-of-art methods which do not considering the Lyapunov-stability of stations. These findings would help to the management and protection of urban rail transit system under cascading failures.