  This study integrates pedestrian flow characteristics to formulate a
mesoscopic cellular automata model tailored for simulating evacuations in
large-scale scenarios. Departing from the conventional planar grid cell
division, the model employs road cell segmentation, thereby physically
enlarging the dimensions of individual cells. This augmentation accommodates an
increased occupancy of individuals per cell, representing pedestrian flow
parameters within each cell through state variables. The source loading cell
facilitates the simulation of pedestrian behavior transitioning from buildings
to roads during an actual evacuation event, while the unloading cell situated
at the exit removes evacuees from the system. The continuity equation for state
transitions comprehensively encapsulates the dynamics of pedestrians throughout
the evacuation process. Potential challenges in actual evacuation processes are
identified through the simulation, offering valuable insights for improvement.
This research aims to contribute to a more effective and informed approach to
evacuation planning and management.
