## 5 The Development of the Prediction Model for the Efficiency of Evacuation
### RPES Model and Parameters for Evacuation  
In this research, the following hypotheses are proposed to construct a model for evacuating passengers from metro platforms that incorporate decision-making capabilities:  
1. The evacuation model is divided into four categories of groups: the population at risk, the pre-evacuation group, the group during evacuation and the safety group. The ratios of each group to the total population at time t are denoted as R(t), P(t), E(t) and S(t), respectively. The initial state has only the at-risk population and the pre-evacuation group, and when t = 0, E(t) = 0 and S(0) = 0. 2. In an emergency, no new people enter during the evacuation and the total number of people does not change during the evacuation, \(\text{R(t)}+\text{P(t)}+\text{E(t)}+\text{S(t)}=1\). Therefore, this study proposes that the crowd state evolution relationship for the evacuation process is shown in Figure 4, and the main variables are described in Appendix A. Additionally, to simulate this evolutionary process, differential equations incorporating decision capabilities were constructed based on system dynamics and the model of epidemics. \[\frac{dR}{dt}=\frac{-de(P_{1}+P_{2})}{N}-\rho R_{I} \tag{1}\]  
\[\frac{dP_{1}}{dt}=-\frac{dR}{dt}-\frac{\lambda_{1}P_{1}}{A_{coo}}-\frac{(1- \lambda_{1})P_{1}}{A_{com}}+\frac{\alpha_{1}R}{A_{act}} \tag{2}\]  
\[\frac{dP_{2}}{dt}=-\frac{dR}{dt}-\frac{\lambda_{2}P_{2}}{A_{coo}}-\frac{(1- \lambda_{2})P_{2}}{A_{com}}+\frac{\alpha_{2}R}{A_{pos}} \tag{3}\]  
\[\frac{dE_{1}}{dt}=\frac{\lambda_{1}P_{1}}{A_{coo}}+\frac{\mu_{1}\theta_{1} \delta_{1}E_{2}}{A_{com}}-\
u_{1}\kappa_{1}E_{1}+\frac{\lambda_{2}P_{2}}{A_{ coo}}-\frac{\mu_{2}\theta_{2}\delta_{2}E_{1}}{A_{coo}} \tag{4}\]  
\[\frac{dE_{2}}{dt}=\frac{(1-\lambda_{1})P_{1}}{A_{com}}+\frac{(1-\lambda_{2})P _{2}}{A_{com}}+\frac{\mu_{2}\theta_{2}\delta_{2}E_{1}}{A_{com}}-\frac{\mu_{1} \theta_{1}\delta_{1}E_{2}}{A_{coo}}-\beta_{2}E_{2} \tag{5}\]  
\[\frac{dS}{dt}=\
u_{1}\kappa_{1}E_{1}+\
u_{2}\kappa_{2}E_{2} \tag{6}\]  
Combining the above assumptions, this study used the system dynamics analysis software module in Anylogic to construct an RPES model for metro platform evacuation based on decision-making capability, with the str  
Figure 4: Model of the evolution of the state of the evacuated crowd on an underground platform. Following the model proposed in this study, assumptions are made about the parameters in the model and simulation studies are carried out based on this. The simulation experiment is as follows: Suppose there are 500 people on a metro platform, wherein in the initial state, the participant in 2 people adopt the active and passive strategies, respectively and propagate them. We assume that the diffusion rate of the evacuation message in the initial state is 1.25, the probability that passengers believe the evacuation message is true is 0.8, and the probability that passengers adopt different evacuation behaviour strategies is 0.5. In addition, passengers may transform between adopting cooperative and competitive strategies during the evacuation process; therefore, we assume that the crowd density during the evacuation process is 2.5 [83], and passengers who adopt competitive strategies can influence 1.5 surrounding passengers with a cooperative strategy with an effective probability of 0.6. Conversely, a passenger with a cooperative strategy can influence 2 surrounding passengers with a competitive strategy with an effective probability of 0.8. Assuming an exit throughput rate of 50 passengers/second, the impact of a passenger with a cooperative strategy and a passenger with a competitive strategy on evacuation efficiency is 1.3 and 0.8, respectively.