# A Study on Crowd Evacuation Model Considering Squeezing Equilibrium in Crowded Areas
## 4 Simulation Experiment
### Data Processing Method
\[p_{1}(x1)>p_{2}(x1),p_{1}(x2)>p_{2}(x2) \tag{29}\]3 Real evacuation simulation: **(a)** Scenario 2; **(b)** Scenario 3; **(c)** Scenario 3; **(d)** Scenario 4.  
set to g1 and the optimized model is set to g2. It could be seen that as the evacuation time increased, the peak value of the optimized model (29 s) was much later than that of the original model (3 s) and was much smaller than that of the original model. After T = 29 s, as the number of evacuees who successfully passed through the safety evacuation exit increased, the squeezing probability g2 of the optimized model showed a decreasing trend. However, in the original model, due to the large squeezing probability g1 at T = 30 s and the superposition of resultant forces on pedestrians, the force on the crowd presented a wave form, which eventually led to the failure of evacuation. Figure 16 and Table 1 compare the pedestrian evacuation time of the two models with those of the real experiment (Note: \"+\" in the table indicates that in the current scene some pedestrians are stagnant, pedestrians fail to evacuate, and the time is uncertain), and depict the variation in the number of pedestrians not evacuated in the different scene with time. The purpose is to reflect the controllability of congestion through evacuation time, or to observe the influence on evacuation time through the regulation of congestion. For complex scenario 1 in the optimized model, a pedestrian has reached the emergency exit in 13.2 s while in the original model the pedestrian has reached the emergency exit in 16.6 s, so the time difference between pedestrians and emergency exits is 3.4 s. In the optimized model 200 pedestrians were successfully evacuated in 90.2 s, while in the original model 86 pedestrians were not evacuated at that time. By contrast, the evacuation efficiency of the optimized model has increased by 43%. For the simple scenario 2 the evacuation completion time of the optimized model is 80.8 s, and 8 people in the original model failed to evacuate because of stagnation. By contrast, the evacuation efficiency of the optimized model is improved by 7.9%. For the complex scenario 3 the evacuation completion time of the optimized model is 87 s, and 45 people in the original model failed to evacuate because of stagnation. By contrast, the evacuation efficiency of the optimized model is improved by 24.5%. \[p_{1}(x1)>p_{2}(x1),p_{1}(x2)>p_{2}(x2) \tag{29}\]4 Comparison of situations where the figures intersect and are not greater than the maximum degree of extrusion. Obviously, for complex scenes such as scene 1 and scene 3, the stagnation phenomenon of the original model is obvious. Therefore, in a complex scene when a lot of pedestrians evacuated to the exit or a narrow area, a smaller squeezing probability can better reduce the time for pedestrians to pass through the area, thus reducing the evacuation time as a whole. The optimized congestion control of the model can help the evacuation time and the evacuation time is closer to the real experiment. The experiment shows that the optimized model is featured by reasonable control and significant squeezing ability, so the squeezing between pedestrians and between pedestrians and obstacles is less in the whole process, which reduces the time for pedestrians to pass through the exit to a large extent and guides and controls pedestrians in a better and orderly way to successfully evacuate to the emergency exit, thus maximizing the evacuation time and guaranteeing life safety.