## 5 Discussion  
### Measurement of Truck Travel Time by Setting Different Tag Recognition Data Aggregation Periods  
The changes in truck travel time statistics that occurred when the data aggregation period was set differently were analyzed in this study. The analyses focused on the tag recognition packet data acquired from October to December, 2018. The data aggregation period was set as the most recent day (2018/12/28), 5 days (2018/12/24-2018/12/28), 10 days (2018/12/17-2018/12/28), 1 month (2018/12), 2 months (2018/11-2018/12), and 3 months (2018/10-2018/12). Table 8 shows the statistical values of truck unit travel time that were found when the data aggregation period was set differently. DT was assumed to be constant even when the data aggregation period changed. TE1, TE2, TE3, TL1, TL2, and TL3 maintained relatively fixed times even as the period changed. Therefore, it is possible to calculate statistical values for these times using data collected during a short period.  
The statistical values for K1 could not be calculated for the last 1 day, 5 days, 10 days, or one month and could only be calculated for October and November because data collection was not performed for December. Therefore, to calculate accurate statistical values for the K1 time, it is necessary to use the data obtained over a long period. It is known that large fluctuations occur in the K2 time in the statistical results acquired during a period of less than one month. In other words, similar to the K1 time, the statistical values for the K2 time must be calculated using the data acquired over a long period.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Date**} & \multirow{2}{*}{**Statistics**} & \multicolumn{8}{c}{**Absolute Error (min)**} & \multirow{2}{*}{**MAE 2**} \\ \cline{3-3} \cline{5-10}  & & **TE1** & & **TE2** & & **TE3** & **TL1** & **TL2** & **TL3** \\ \hline \multirow{2}{*}{2019-01-02} & Mean & 0.08 & 0.05 & 0.02 & 0.01 & 0.00 & 0.61 & 0.128 \\  & STD 1 & 0.34 & 0.01 & 0.01 & 0.00 & 0.00 & 0.40 & 0.127 \\ \hline \multirow{2}{*}{2019-01-09} & Mean & 0.26 & 0.08 & 0.06 & 0.06 & 0.10 & 0.26 & 0.137 \\  & STD 1 & 0.34 & 0.02 & 0.01 & 0.34 & 0.02 & 0.11 & 0.140 \\ \hline \multicolumn{10}{c}{\({}^{1}\) Standard deviation, 2 Mean absolute error.} \\ \end{tabular}
\end{table}
Table 7: Results of absolute error for truck travel times derived from simulation results and the haulage operation performed on January 2 and 9, 2019.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Period**} & \multirow{2}{*}{**Statistics**} & \multicolumn{8}{c}{**Truck Travel Time (min)**} \\ \cline{3-10}  & & **DT** & **TE1** & **TE2** & **TE3** & **K1** & **K2** & **TL1** & **TL2** & **TL3** \\ \hline \multirow{2}{*}{1 day} & Mean & 0.59 & 2.66 & 0.43 & 0.35 & - & 17.03 & 0.41 & 0.54 & 5.88 \\  & STD 1 & 0.11 & 0.00 & 0.04 & 0.07 & - & 0.26 & 0.04 & 0.01 & 0.00 \\ \hline \multirow{2}{*}{5 days} & Mean & 0.59 & 3.18 & 0.4 & 0.35 & - & 20.21 & 0.44 & 0.53 & 5.34 \\  & STD 1 & 0.11 & 0.73 & 0.03 & 0.04 & - & 2.79 & 0.08 & 0.03 & 0.46 \\ \hline \multirow{2}{*}{10 days} & Mean & 0.59 & 2.82 & 0.42 & 0.35 & - & 20.58 & 0.44 & 0.55 & 5.36 \\  & STD 1 & 0.11 & 0.52 & 0.04 & 0.04 & - & 3.61 & 0.06 & 0.03 & 0.51 \\ \hline \multirow{2}{*}{1 month} & Mean & 0.59 & 3.4 & 0.43 & 0.35 & - & 20.85 & 0.43 & 0.55 & 5.46 \\  & STD 1 & 0.11 & 1.18 & 0.06 & 0.04 & - & 3.88 & 0.05 & 0.03 & 0.64 \\ \hline \multirow{2}{*}{2 months} & Mean & 0.59 & 3.18 & 0.42 & 0.36 & 5.89 & 19.74 & 0.43 & 0.52 & 5.61 \\  & STD 1 & 0.11 & 0.82 & 0.05 & 0.04 & 1.14 & 3.03 & 0.05 & 0.05 & 0.61 \\ \hline \multirow{2}{*}{3 months} & Mean & 0.59 & 3.21 & 0.43 & 0.36 & 5.96 & 19.78 & 0.45 & 0.53 & 5.52 \\  & STD 1 & 0.11 & 0.82 & 0.05 & 0.04 & 0.84 & 3.17 & 0.06 & 0.05 & 0.57 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Results of measuring truck travel time when the statistical data collection period is set differently.