Flood-Induced Evacuation Time Prediction and Optimization Strategy Toward Metro Stations

Escaping the station during the golden time is the main reference for managers to develop optimization strategies under floods. However, regular evacuation drills often fail to incorporate the impact of flood evolution and involve ethical considerations. The evacuation time obtained from microscopic simulations makes it difficult to meet real-time requirements, which is time-consuming and labor-intensive. To address this issue, this paper proposes a flood-induced evacuation time prediction model for metro stations, with high accuracy and strong real-time performance. The hydrodynamic model and passenger dynamics model for the metro station are built based on the Fluent and the PathFinder software, to obtain the evacuation time corresponding to different scene parameters and evacuation scales. The flood invasion speed and gate availability parameters in the scene parameters, as well as the number of passengers and the proportion of passengers with different attributes, are used as inputs to the prediction model, and the evacuation time is used as the output. The accuracy of the constructed time prediction model is mainly concentrated between 0.85 and 1.00, with a high fit between the predicted values and the actual values. An evacuation path optimization strategy is further provided to reduce evacuation time and improve evacuation safety. Taking evacuation time, evacuation path length, and human stability risk as optimization objectives, the optimal path decision under a multi-objective game is obtained. Results show that adopting an optimization strategy significantly reduces evacuation time and increases the maximum passenger capacity threshold allowed by the platform during the golden evacuation time. The proposed method provides feasible suggestions for the rapid evaluation of station evacuation efficiency and improvement of escape strategies under flood conditions.