A Method of Risk Assessment for Subway Stations Based on D-S Evidence Theory

The safety risk assessment of high-density passenger flow holds significant importance for improving the emergency response capabilities of urban metro systems. To address t traditional methods'limitations, such as inadequate indicator systems, insufficient integration of multi-source data, and low assessment accuracy, an enhanced Dempster-Shafer (D-S) evidence theory method was proposed. This method is structured around a five-dimensional indicator system encompassing personnel, equipment, passenger flow, environmental conditions, and management protocols. Comprehensive weights were determined through Game Theory-Combinatorial Empowerment. The safety level membership degrees of each indicator were quantified using a fuzzy half-gradient affiliation function, while an evidence similarity matrix is constructed via Jousselme's evidential distance function. To address high-conflict evidence, a calibration factor α, and adjustment parameter μ, are introduced to refine the fusion process, where the final risk level derived through a linear weighted method. A case study was conducted at Ningbo Metro Gulou Station, utilizing holiday evening peak passenger flow data and expert evaluations to establish a multi-source evidence set for validation. The results demonstrated that: ①Compared to the traditional D-S method and Yager's method, the proposed approach reduces average evidence conflicts by 34.4% and 8.5%, respectively; ②The membership grade of the critical"passenger flow"indicator has an R3 rank value reaches 0.8202, confirming the method's effectiveness in characterizing scenarios of high-density passenger flow; ③The proposed method exhibits robust adaptability and stability, with an error rate below 5% in the comparison of multiple scenarios. These findings provided actionable insights for identifying and mitigating risks in metro systems under high-density passenger flow conditions.