Vulnerability Analysis of Urban Rail Network Cascade Failure Based on Dynamic Critical Station Identification

Vulnerability Analysis of Urban Rail Network Cascade Failure Based on Dynamic Critical Station Identification

연구 분야: Infrastructure

학회: IDST '24: Proceedings of the 2024 International Conference on Intelligent Driving and Smart Transportation

Identification of critical stations before cascading failures occur is crucial for preventing and controlling cascading failure phenomena, enhancing Urban Rail Transit Networks (URTN)'s emergency management capabilities against sudden events. To delve into the intrinsic mechanisms of cascading failure propagation, a method for identifying critical stations considering the dynamic characteristics of cascading failure networks is proposed. First, a spatiotemporal network model of urban rail transit is constructed extending over a timeline. Next, a dynamic critical station identification method is proposed, combining various topological and dynamic passenger flow metrics. Finally, a cascading failure model is established, and simulation analysis is conducted using Beijing's rail transit network as a case study. Simulation results indicate that compared to random attack strategies, degree-based and betweenness-based attack strategies, the URTN exhibits greater vulnerability under importance-based attack strategies. Under dynamic importance attack, the maximum giant component decreases by 85.1%, with passenger flow losses reaching 93.2%, resulting in the most severe network damage. The results demonstrate that critical stations during cascading failure processes exhibit dynamic variations as the network evolves, validating the proposed method for dynamic critical station identification.