In the traditional cellular automata evacuation model, the space is divided into fine grids at a micro level, which is mainly used in a two-dimensional plane case. The evacuation space is mostly a small-scale architectural space or local area. Therefore, it is difficult to simulate a wide range of evacuation scenario, and there are less researches of the cellular automata model for a wide range of evacuation. Therefore, this article combines the movement characteristics and status of the pedestrian flow to establish a mesoscopic cellular automata model of evacuation applied to larger evacuation scenarios. This model uses road cell division instead of planar grid cell division, which augments the area of a single cell physically, increases the number of people occupied by a single cell, and expresses the number of people in each cell in the form of state variables. By changing personnel density and personnel speed, and by introducing “source loading” cell loading to simulate the evacuation of people in the scene, the behavior of pedestrians evacuating from the building to the road in the actual evacuation process can be simulated. The state transition equation simulates the movement of people in the evacuation process. When the number of people in the cell is larger, the density of people in the cell is higher, and their walking speed also decreases, which reflects the distribution and movement characteristics of pedestrian flow. This paper uses this model to divide the evacuation area of the college campus, and divides the entire campus into four evacuation areas. The evacuees in each area are evacuated corresponding to the corresponding exit, by planning the evacuation path, pedestrians walking from the “source loading” cell to the exit for evacuation. Through simulation, it is possible to analyze the macro-evacuation situation in the scene and observe the status change of a single cell. There are observed a high density of people in local road sections during campus evacuation, and the problem about the distribution of people on campus problems such as unevenness of pedestrian distribution and long evacuation schedules in certain places. Through the simulation of this model, possible problems in the actual evacuation process are found, and the improvement guidance and opinions are presented correspondingly.