## 3 Methodology
### Calibration Procedures
In particular, the values of the table above were reached by varying the parameters one by one and trying to obtain reliable results comparable with the real ones. Therefore, the parameters studied can influence the simulated walking speeds of pedestrians in the model and have therefore been chosen. For each parameter, various adjustments have been made. The parameter values were analyzed around the chosen values used for the speed calibration and the pedestrian type survey. The comparison between the real value and the simulated one was carried out considering microscopically data and validated using Root Mean Square Error (RMSE) procedure to calibrate the model parameters and optimize the model like described in Equation (3). \[\text{RMSD}=\sqrt{\frac{\sum_{t-1}^{T}(x_{1,t}-x_{2,t})^{2}}{T}} \tag{3}\]  
with variables observed over \(T\) times. Simulated data were obtained from the optimized model and compared with the real field data. In accordance with [56] a difference in observed and simulated data is less than 10%. Observing variation between two sets of data it can be concluded that Viswalk simulated data is applicable to the real field data in the evaluated context. It was found that higher values of tau reduce pedestrian acceleration towards the desired speed. However, this is not desirable in cases of maintenance or evacuation as it is necessary to quickly clear the area for which smaller tau values have been entered for these scenarios. It is also estimated that for small values of tau, the average simulated walking speed is a little more sensitive for parameter settings. The sensitivity analysis shows that the adjustments of the parameters investigated differently affected the average simulated walking speed. The parameters titled tau, B_soc_isotropic and A_soc_mean have a greater influence on average walking speed. Parameters that do not affect the the simulated average walking speed was A_soc_isotropic and VD. The investigation of the parameter value for B_soc_mean does not show significant static differences in the average simulated walking speed. The human mix investigated is heterogeneous where, however, disabled people with wheelchairs were not taken into account because the geometry of the bridge does not allow them to be crossed due to repeated steps in both directions. The people considered globally on each scenario is characterized by 50% man, 40%female and 10% female with children in accordance with real-time monitoring results; \begin{table}
\begin{tabular}{c c c c} \hline
**Viswalk Parameters** & **Default** & **Normal** & **Evacuation** \\ \hline tau (\(\tau\)) & 0.40 & 0.06 & 0.06 \\ react\_to\_n parameter & 8 & 4 & 2 \\ ASocIso & 2.72 & 1 & 1 \\ BSocIso & 0.20 & 0.10 & 0.10 \\ Lambda (\(\lambda\)) & 0.176 & 0.176 & 0.176 \\ ASocMean & 0.40 & 0.40 & 0.40 \\ BSocMean & 2.80 & 2.80 & 2.80 \\ VD & 3 & 9 & 6 \\ Noise & 1.2 & 1.2 & 2.4 \\ PrefLato & nothing & nothing & nothing \\ \hline \end{tabular}
\end{table} 
Table 6: Specific pedestrian parameters of Viswalk tool. 20% of mentioned adults (10% man and 10% female) were evaluated as elderly people because in this infrastructure, many under 65 s were observed. The study of density allows establishing the level of congestion that can be created in certain areas inside the terminal. People are used to move individually, but if they move with the same characteristics due to external factors, such as congestion or regulation and flow control factors, groups, called platoons, are formed involuntarily out-flow variables. The main outflow variables implemented in the micro-simulation model derive from previous real studies through cameras in the investigated area.