Agent-Based Dynamic Vulnerability Model for Pedestrians Exposed to Floodwaters in Critical Infrastructures

Climate change-amplified flooding poses severe risks to urban underground infrastructures, increasing exposure and vulnerability in densely populated cities. Motivated by the observation that current assessment methods may underestimate the impact of human motions in floodwaters on pedestrian evacuation safety, while traditional evacuation designs primarily focus on individual behavior, neglecting the critical influence of group dynamics and collective decision-making during real flood events. To address these gaps, this study develops an agent-based dynamic vulnerability model for pedestrians exposed to floodwaters, supported by a full-scale instrumented physical model to capture interactive and dynamic evacuation behaviors. The model incorporates group interactions, formation patterns, and hydrodynamic forces acting on pedestrians during evacuation. Analysis of spatial and temporal dynamics of pedestrian movement reveals significant variations in stability: walking against the flow increases instability and overall vulnerability, whereas moving with the flow reduces hydrodynamic forces, though this effect diminishes with increasing water depth. Preliminary results also indicate that group dynamics significantly influence evacuation efficiency: larger spacing between pedestrians mitigates hydrodynamic impacts and enhances evacuation performance, while lateral formations experience higher hydrodynamic forces compared with longitudinal formations, reducing overall efficiency. Integration of the multi-agent model into a hydrodynamic simulation framework enables comprehensive risk assessment and management of underground infrastructure under extreme flooding, facilitating identification of optimal evacuation timing and routing strategies. This framework provides practical guidance for designing flood-resilient underground spaces and contributes a novel approach for dynamic vulnerability assessment in climate-adaptive cities.