Optimizing Pedestrian Evacuation: A PSO Approach to Interpretability and Herd Dynamics

Traditional pedestrian evacuation models struggle to balance global exit guidance with local, individual decision making under hazards. We address this by decomposing long-term objectives into Particle Swarm Optimization (PSO) -based micro-goals and proposing a hybrid Cellular Automaton (CA) and PSO model. The hybrid design reduces the decoupling between spatial discretization and individual choices and more tightly couples hazard and density fields with movement decisions. Two contributions are central. First, we develop an autonomous following pathfinding mechanism (AFPM) that linearly blends the direction toward a PSO micro-goal with a herd following direction and adds a small reward for directional consistency. This mitigates path chaos from purely autonomous moves and congestion aggregation from purely herding moves. Second, we build a multi-dimensional interpretability and robustness framework that combines the empirical Cumulative Distribution Function (CDF) and a kernel-smoothed Probability Density Function (PDF) of key evacuation times (Tclear, T₉5%ₐlive) together with vulnerability curves, to analyze the data and assess robustness. It combines Shapley Sobol analysis to quantify parameter effects on clearance time Tclear and the 95% survival evacuation time T₉5%ₐlive, with CDF/PDF summaries and vulnerability curves to assess anti-interference performance. Experiments use a simulated underground shopping mall. In a 60 pedestrian case, a geometry-only baseline yields Tclear ≈33 s; hazard- and density-aware strategies produce slightly longer Tclear but reduce peak bottleneck congestion by 20–30%. When one exit is closed, the exceedance probability at τ=70 s drops from 0. 44 to 0. 36, reducing long tail risk. Compared with geometry-based Dijkstra, the proposed model slightly increases clearance time while lowering peak congestion by 20–30%, achieving a balance between efficiency and safety. The model and evaluation protocol provide technical support for evacuation policy, facility layout, and emergency system design in large complex buildings.