Optimization of exit-restricted aircraft evacuation with a dual-axis rotation cellular automaton model

Abstract

Emergency evacuation efficiency is critical for passenger safety in civil aviation, particularly under severe exit-restricted conditions such as fire-induced scenarios. This study proposes organized evacuation strategies to enhance efficiency using a fine discrete floor field cellular automaton (FFCA). A dual-axis rotation mechanism mimicking human bipedal motion is integrated to capture realistic passenger movements within confined cabin spaces. Using this improved FFCA, five evacuation strategies are systematically analyzed under various exit availability configurations. Simulation results demonstrate that organized evacuation sequences significantly outperform proximity-based methods by reducing congestion and evacuation time. Specifically, the Back-to-Front and Front-to-Back strategies prove most effective under extreme limited-exit conditions. These findings provide theoretical support for optimizing emergency evacuation protocols and improving aviation safety management.