Gauging the Evolution of Operational Risks for Urban Rail Transit Systems under Rainstorm Disasters

Abstract

With global warming and the frequent occurrence of extreme weather, damage to urban rail transit systems and casualties caused by rainstorm disasters have increased significantly and are becoming more serious. This research developed a network model for the evolution of operational risk in URT systems under rainstorm scenarios that can cause 35 typical accidents. Furthermore, we also investigated the evolution mechanism and devised improvement strategies. Through the network, combined with the complex network theory, the study explored the critical risks and the extent of their impact on the network and proposed optimized strategies to avoid these critical risks. The results show that risk nodes such as R1, R4, R18, and R21 have the most significant impact on the evolution network, both in static and dynamic networks, indicating that station flooding, train stoppage, heavy rainfall, and ponding are the most critical risks to guard against. Gauging the evolution of operational risks in urban rail transit systems and adopting reasonable avoidance measures in this research can effectively improve resilience to rainstorm disasters and the level of operational safety, which can contribute to the sustainable development of transport infrastructure.