Multi-Objective Optimization of Evacuation Route for Heterogeneous Passengers in the Metro Station Considering Node Efficiency

Reasonable planning of passenger evacuation routes can directly improve evacuation efficiency in the metro station. Considering the effect of traffic capacity at the node such as gate and stair/escalator, a multi-objective optimization model aimed at minimizing the maximum evacuation time of heterogeneous passengers in different segmentation areas is established, which achieves local optimization on the basis of global optimization of the evacuation route. Node traffic capacity is assessed based on the combination of BP neural network and atomic orbital search algorithm, which is conducive to improving the calculation accuracy of total evacuation time. The simulation results indicate that the performance of the established prediction model of node travel time is good, and the mean square error can be as low as 0.2555. Meanwhile, the proposed route strategy can improve the overall evacuation efficiency by 21.85%, and passengers' choices of evacuation routes are more reasonable. The sensitivity analysis of factors affecting evacuation through a random forest algorithm shows that the number of passengers with person attribute E has the greatest impact on evacuation time, which should be the focus of attention in the evacuation process.