Novel Approach for Quantifying the Propagation of Subway Equipment Faults by Using Multimodal Networks

Abstract

In subway systems, equipment failures can lead to train stoppages, delays, or even accidents, severely affecting the safety of train operations. It is crucial for emergency handling to identify the vulnerable areas and explore propagation laws in the subway network. In this paper, based on multimodal networks, several indicators are systematically proposed to demonstrate the vulnerability of each subway station. These indicators are then applied in a gravitation model to quantify and study the propagation or spatiotemporal distribution of cascading effects caused by equipment failures. To verify the effectiveness of the proposed model, a case study is conducted using a data set of equipment faults in the Beijing subway. Quantification results show that the propagation of equipment faults between subway stations exhibits diagonal characteristics, with stations closer to the faulty equipment being more heavily affected. The results also indicate that gravitation values display a long-tail distribution and their highest proportion falls within a certain interval. Furthermore, this paper proposes several prevention measures in response to equipment fault propagation.