# A Study on Crowd Evacuation Model Considering Squeezing Equilibrium in Crowded Areas
## 5 Conclusions  
1. The relational expression of the acting force between pedestrians and between pedestrians and obstacles is constructed. Many experiments have shown that when the values of \(h1\), \(h2\) and \(h3\) in the optimized model are 12,000, 24,000 and 120,000, respectively, the optimized model has the best ability to control the intersection without exceeding the maximum degree of squeezing. In addition, the values of \(h1\), \(h2\) and \(h3\) satisfy the relational expression.
2. Simulation experiments are conducted by establishing different scenes and using the self-built evacuation platform to compare the probabilities of the original model in different time periods in three cases: intersection without exceeding the maximum degree of squeezing; and separation. In a complex scene, the optimized model has a more obvious ability to control the intersection without exceeding the maximum degree of squeezing. Meanwhile, this paper also verifies that the original model and the optimized model have the same ability in controlling the intersection exceeding the maximum degree of squeezing.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Scene 1** & **Scene 2** & **Scene 3** & **Scene 4** \\ \hline Original Model & 90.4+ s & 80.8+ s & 87.0+ s & 113.6 s \\ Optimization Model & 90.2 s & 80.8 s & 87.0 s & 85.8 s \\ Real Experiment & 95.0 s & 80.0 s & 90.0 s & 88.0 s \\ \hline \hline \end{tabular}
\end{table}
Table 1: Evacuation time of different model experiments in four scenarios.  
Figure 16: Relationship between pedestrian evacuation time and number of people.  
3. In a complex scene when a lot of pedestrians evacuate to the exit or a narrow area the stagnation phenomenon of the original model is obvious, but the optimized model has a smaller squeezing probability and can better reduce the successful evacuation time of pedestrians, so the optimized model has significant advantages over the original model.  
Conceptualization, L.Y. and Z.T.; methodology, Z.T.; software, Z.T.; validation, L.Y., Z.T. and Z.H.; formal analysis, L.Y. and Z.T.; investigation, J.W.; resources, J.H.; data curation, Z.T.; writing--original draft preparation, Z.T.; writing--review and editing, L.Y.; visualization, Z.T. and Z.H.; supervision, L.Y.; project administration, J.H.; funding acquisition, L.Y. and J.H. All authors have read and agreed to the published version of the manuscript.  
Project supported by the National Natural Science Foundation of China (Grant Nos. 51978089), and Key R&D Plan of Sichuan Science and Technology Department in 2022 (Grant No. 22 ZDYF2726), and Chengdu Normal University Scientific Research and Innovation Team (Grant No. CSCXTD2020809, ZZBS201907, CS21 ZC01), and Open Fund of Artificial Intelligence Key Laboratory of Sichuan Province (Grant No. 2020 RY01), and Open Project of Intelligent Manufacturing Industry Technology Research Institute (Grant No. ZNZZ2208), and National College Students' innovation and entrepreneurship training program (NO. S202014389070).  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
The authors declare no conflict of interest.