Abstract: Urban metro systems are increasingly exposed to operational failures, demand shocks, and climate-related disruptions. Despite rapid growth in resilience research, conceptual ambiguity and methodological fragmentation persist. Robustness, reliability, and resilience are frequently conflated, recovery dynamics are inconsistently modeled, and passenger-centered performance metrics remain underdeveloped. This compliant systematic scoping review synthesizes 194 studies (2005–2025), of which 72 met strict inclusion criteria requiring explicit public transport focus and quantifiable resilience or robustness indicators. Studies were classified by disruption type, methodological paradigm (optimization/control, simulation, network science, data-driven models), recovery strategy (bus bridging, short-turning, passenger flow control), and data source (AFC, AVL, APC, GTFS). Results reveal six dominant research clusters, with strong growth after 2019. However, most contributions operationalize resilience through static connectivity or efficiency loss metrics, while comparatively few model recovery trajectories, passenger delay distributions, accessibility degradation, or multimodal capacity interactions under uncertainty. Optimization-based disruption management and uncertainty-aware substitute bus models demonstrate the highest operational relevance, yet empirical validation and equity-sensitive indicators remain limited. We propose a unified three-layer resilience architecture linking topology, operations, and passenger behavioral response under stochastic recovery. Advancing metro resilience requires shifting from static robustness indices toward calibrated passenger-impact recovery curves integrated into real-time decision-support systems.

Keywords: Metro Disruptions, Public Transport Resilience, Bus Bridging, Passenger Flow Control, Robust Timetabling, Multimodal Networks

Pages: 84-93

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