Resilience Assessment of Beijing Subway Lines under Extreme Precipitation Weather

Traffic infrastructure safety is a core topic in traffic construction and development. As the impact of global climate change becomes more and more significant, extreme weather brings more and more safety issues to the normal operation of subway systems. Therefore, it is an urgent issue in the construction of subway systems to fully prepare for extreme weather and improve system resilience under external disturbances. The resilience of a complex system generally refers to its ability to adapt to external disturbances and return to a functional state. As one of several key infrastructure systems in large cities, a subway system needs to be highly resilient to cope with various risks, and it needs to recover quickly under uncertain weather conditions and other external damage events. In order to achieve the goal of conducting a real-time resilience assessment of a subway system, this study adopts the Bayesian network and the traditional failure mode and effect analysis (FMEA) method to realize resilience assessment with multiple performance indicators. Combined with the risk matrix method from FMEA, multiple important indicators of a subway system under the influence of extreme weather are obtained. These important indicators are integrated into the resilience assessment of the subway system within a Bayesian method. In this paper, the feasibility and applicability of the proposed method are verified by taking the Changping Line of the Beijing subway under extreme rainfall weather (>10 mm) as a case.