Safety resilience assessment of subway operations based on cloud model and network theory

Operational resilience of subway systems is critical for sustaining service under disruptions. The lack of a practical assessment approach that links station-level capabilities to network-level performance can result in system overload, service inefficiency and increased operational costs for subway systems. This study develops a Pressure–State–Response (PSR) assessment framework for subway station resilience. A 31-indicator system is constructed and quantified using a cloud-model-based method to derive station resilience ratings of five selected stations in the Xuzhou subway system. The network efficiency metric evaluates network-level resilience assuming three disruption scenarios. Scenario 1 represents a functional failure that disconnects stations from the network. Scenario 2 represents service failure in which trains bypass affected stations without stopping, and scenario 3 is the combination of both scenarios. High state and response resilience are observed across five stations, consistent with standardised company-level procedures and resource configurations for monitoring, preparedness, safety management, responses and recovery. In contrast, cross-station differences are driven primarily by pressure resilience, which is sensitive to station-specific exposure, particularly at high-demand interchange stations. Network resilience is highest under bypass operations and lowest under functional disconnection with segmented services, underscoring the importance of preserving through‑movement and connectivity during disruptions. Findings recommend focusing on exposure control at high-demand stations, integrating monitoring with rapid response activation, institutionalising organisational learning and strengthening resilience governance. The PSR assessment framework supports comparative diagnosis of subway stations and scenario-based planning for resilience enhancement in subway operations.