## 4 Results  
The target logistics fleet of this study comprised nearly 1000 vehicles, which generated a total of 65,249,808 travel records from April 2021 to March 2022 (Table 1). The first record suggested that Car01 was at Taoyuan Warehouse, and the second record indicated that Car01 was on a road. Therefore, the time mentioned in the second record was considered as Car01's departure time from the warehouse. The second last record indicates that Car01 was on a road, and the last record suggests that Car01 was at Linkou First Store. Accordingly, the time mentioned in the last record was considered Car01's arrival time at the aforementioned store. Figure 4: Data processing flow. A travel time record was obtained according to Car01's departure times from Taoyuan Warehouse and arrival times at Linkou First Store (Table 1). By using the aforementioned procedure, we calculated the travel time between any two points for all vehicles in the fleet by using their 65 million records from 2022 and obtained 3,794,744 travel time records (Table 2). The first travel time record (travel time of 780 s) was obtained for the travel data from Taoyuan Warehouse (departed at 08:08:20 on 17 March 2022) to Linkou First Store (arrived at 08:21:20 on 17 March 2022), as presented in Table 1. Because all the vehicles traveling from Taoyuan Warehouse to Linkou First Store were included in the calculation, the vehicle numbers were not recorded in the travel time records. The travel time records were then grouped by departure location, arrival location, and departure period. Consider the combination of Kaohsiung Warehouse and Zhutian First Store as an example. A total of 477 travel records for departure were found between these two points in period 6 (6:00-6:59; Table 3). Figure 5 presents the data distribution of these records, with the vertical and horizontal axes representing the travel time (seconds) and number of records, respectively. Most of the travel times were concentrated around 2600 s. Table 4 presents the travel time records for departure in period 7, and the data distribution \begin{table}
\begin{tabular}{c c c c c} \hline
**License Plate** & **Status** & **Time** & **Speed (km/h)** & **Location** \\ \hline Car01 & Driving & 17 March 2022 08:07:50 & 7 & Taoyuan Warehouse \\  & & & & Section 1, Fenliao Road, Linkou \\ Car01 & Leaving the geofence & 17 March 2022 08:08:20 & 40 & District, New Taipei City \\  & & & & (City Road No. 108) \\ Car01 & Driving & 17 March 2022 08:08:20 & 40 & District, New Taipei City \\  & & & & Section 1, Fenliao Road, Linkou \\ Car01 & Driving & 17 March 2022 08:08:50 & 41 & District, New Taipei City \\  & & & & (City Road No. 108) \\  & & & & Section 1, Wenhuasan Road, Linkou District, New Taipei City \\ Car01 & Temporarily parked & 17 March 2022 08:19:50 & 0 & Linkou District, New Taipei City \\  & & & & (Country Road Bei No.75) \\ Car01 & Driving & 17 March 2022 08:20:20 & 16 & Linkou District, New Taipei City \\  & & & & (Country Road Bei No.75) \\ Car01 & Driving & 17 March 2022 08:20:50 & 38 & Linkou District, New Taipei City \\  & & & & (Country Road Bei No.75) \\ Car01 & Parked in the geofence & 17 March 2022 08:21:20 & 4 & Linkou First Store, Linkou District, New Taipei City \\ \hline \end{tabular}
\end{table} 
Table 1: Example of a track log. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Origin** & **Destination** & **Depature Time** & **Arrival Time** & **Travel Time (s)** & **Period Number** \\ \hline Taoyuan & Linkou First Store & 17 March 2021 & 17 March 2021 & 780 & 8 \\ Warehouse & Linkou First Store & 08:08:20.000 & 08:21:20.000 & 780 & 8 \\ Tucheng Jinfu & Tucheng Industrial & 17 March 2021 & 17 March 2021 & & \\ Store & Store & 20:59:15.000 & 21:00:17.000 & 62 & 20 \\  & & & \(\vdots\) & & \\ Xinpu & [PERSON] & 17 March 2021 & 17 March 2021 & & \\ Xinwhenshan Store & Store & 00:26:08.000 & 00:32:43.000 & 395 & 0 \\ [PERSON] & [PERSON] & 17 March 2021 & 17 March 2021 & & 83 & 0 \\ Store & Store & 00:36:08.000 & 00:37:31.000 & & \\ \hline \end{tabular}
\end{table}