A simulation approach for analyzing metro resilience under operational incidents

Operational incidents represent the most prevalent anomalies encountered within metro systems. This study develops a simulation-based approach aimed at comprehensively understanding the impact of such incidents on metro resilience. Unlike prior research, which often assumes complete station or link closures in response to abnormal events, the proposed approach acknowledges the implementation of dynamic rescheduling strategies to restore metro services. A performance-based metric is proposed to assess metro resilience. To validate the effectiveness of the developed approach, a case study is conducted utilizing empirical data from the Shanghai metro system. Results demonstrate that the proposed metric offers enhanced discrimination between performance degradation resulting from operational incidents and that arising from daily performance fluctuations, surpassing the capabilities of existing metrics. Furthermore, the validity and practicality of our approach are underscored through simulations of multiple real-world operational incidents and comparisons with traditional approaches. The time-varying resilience produced by the developed approach closely aligns with real-world data, showcasing its ability to accurately capture metro resilience evolution.