## 4 Model Validation and Result Analysis
### Security Resource Scheduling Optimization Implementation
#### 4.3.1 Movement Control Procedures Implementation
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Time** & **Predicted Passenger Flow** &
\begin{tabular}{c} **Number of Security** \\ **Channels** \\ \end{tabular} \\ \hline
2024-01-12 04:36 & 195 & 6 \\
2024-01-12 07:16 & 979 & 14 \\
2024-01-12 08:16 & 1421 & 20 \\
2024-01-12 09:16 & 1775 & 24 \\
2024-01-12 11:06 & 1315 & 18 \\
2024-01-12 12:46 & 1640 & 23 \\
2024-01-12 18:56 & 1266 & 18 \\
2024-01-12 19:56 & 644 & 9 \\
2024-01-12 20:56 & 230 & 6 \\
2024-01-12 22:06 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Results of the implementation of plan B (with an adjustment interval of 60 min and a passenger flow threshold of 20%). \begin{table}
\begin{tabular}{c c c} \hline \hline
**Time** & **Predicted Passenger Flow** &
\begin{tabular}{c} **Number of Security** \\ **Channels** \\ \end{tabular} \\ \hline
2024-01-12 04:36 & 196 & 6 \\
2024-01-12 06:46 & 831 & 12 \\
2024-01-12 07:26 & 1019 & 14 \\
2024-01-12 07:56 & 1264 & 18 \\
2024-01-12 08:36 & 1652 & 23 \\
2024-01-12 09:26 & 1991 & 27 \\
2024-01-12 10:16 & 1557 & 22 \\
2024-01-12 13:46 & 1903 & 26 \\
2024-01-12 15:26 & 1490 & 21 \\
2024-01-12 19:16 & 1176 & 16 \\
2024-01-12 19:46 & 839 & 12 \\
2024-01-12 20:16 & 501 & 7 \\
2024-01-12 20:46 & 356 & 6 \\
2024-01-12 22:06 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Optimized partial security screening resource scheduling plan (Plan A). 3. In the extension of this study, the total human-hours calculation is introduced as important for evaluating the cost of the dynamic scheduling program. The method calculates the total human-hours required for all the security check lanes in a day by summing up the product of the number of each security check lane and its duration. This reflects the economic cost becuase operating each lane requires a fixed amount of equipment and personnel. This step is intended to quantify the overall cost of security screening resource utilization in passenger rail stations when implementing a particular dynamic scheduling strategy. The total human-hours for Scenarios A, B, and C are shown in Table 6.  
According to the results of this experiment, plan B has the least total human-hours on 12 January 2024, i.e., the lowest cost required among these three scenarios when the adjustment interval is 60 min and the passenger flow threshold is 20%. Further, this study compares plan B with two typical scheduling models currently used in passenger rail stations: the fixed-shift model and the static scheduling model. The fixed-shift model assumes that 18 security check channels operate continuously throughout the day, regardless of passenger flow variations. The static scheduling model, on the other hand, deploys different numbers of channels during predefined peak and non-peak periods. Specifically, 8 channels are deployed during non-peak periods (04:30-08:00 and 18:30-22:00), while 24 channels are deployed during peak periods (08:00-18:30). Through experiments conducted on real passenger flow data from 12 January 2024, the average waiting time per passenger and total human-hours for each scheduling strategy were calculated. The results, as shown in Table 7, indicate that Plan B reduces the average waiting time per passenger by 18.49% compared to the fixed-shift model and by 13.59% \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Plan A** & **Plan B** & **Plan C** \\ \hline Total human-hours & 308 & 299.83 & 302.67 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Total human-hours in the security channel on 12 January 2024, using different parameters. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Time** & **Predicted Passenger Flow** &
\begin{tabular}{c} **Number of Security** \\ **Channels** \\ \end{tabular} \\ \hline  
\hline \hline \end{tabular}
\end{table} 
Table 5: Results of the implementation of plan C (with an adjustment interval of 30 min and a passenger flow threshold of 10%). compared to the static scheduling model.