## 3 Materials and Methods
### Literature-Based Scenario Planning  
#### 3.5.1 The Five Scenarios  
In the 1950s, [PERSON] pioneered the application of the scenario planning approach, which combined in-depth assessments with so-called scenarios on emerging types of technology [18]. This study adopted the definition of scenario planning offered by [PERSON] [19], who refers to it as a methodical approach to the imaginative recreation of potential futures as they relate to the implementation of organizational decisions, although there are numerous definitions of scenario planning [4].  
Thus, this study uses this approach to examine future development with uncertain outcomes. Specifically, this study creates five alternative scenarios ranging between pessimistic and optimistic in the long-term horizons instead of regarding it as fixed (see Table 2). The findings of earlier research are used in this study to define the five possible outcomes as follows: (1) the most pessimistic, (2) pessimistic, (3) the base, (4) optimistic, and (5) the most optimistic (see Table 2). Since the basic scenario would correspond to a real-world situation, we concentrated on the interpretation of the scenario's results. In this imagined version of the future, all the scenarios take place when AT technology has advanced to a point where it is commonly available. The literature utilized in the development of the scenarios encompassed a range of research, including both outdated and recent studies.  
We make several assumptions for this analysis. First, because of the inherent unpredictability of changes to real costs, it has been assumed that the connection between the various cost components connected with AT operations will remain the same. Second, there will be no disruption to the transport or logistics processes, such as transport routes, the average share of cargo, and loading capacity, due to the introduction of ATs. Third, it is assumed that the economic impacts of ATs across all the scenarios will have the same relative impacts on all different types of ATs.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Variables** & **1-Ton** & **5-Ton** & **12-Ton** & **25-Ton** \\
**Truck** & **Truck** & **Truck** & **Truck** \\ \hline vehicle driver & 2430.00 & 2835.00 & 3240.00 & 3645.00 \\ vehicle acquisition & 611.43 & 993.57 & 1222.86 & 1528.57 \\ vehicle depreciation & 86.39 & 292.77 & 490.38 & 663.80 \\ fuel consumption & 191.47 & 340.44 & 437.64 & 547.05 \\ driver insurance & 159.22 & 247.81 & 407.18 & 472.79 \\ car insurance & 150.79 & 239.90 & 275.27 & 299.08 \\ commercial driver license fee & 1.65 & 56.98 & 202.27 & 232.66 \\ taxes & 25.39 & 86.57 & 211.60 & 250.10 \\ environment improvement payment & 171.06 & 491.76 & 881.85 & 990.95 \\ tax filing fee & 28.00 & 27.14 & 24.85 & 24.90 \\ regular inspection fee & 242.21 & 325.91 & 360.59 & 379.75 \\ maintenance & 30.21 & 43.26 & 52.92 & 59.30 \\ tire & 8.46 & 17.53 & 23.19 & 33.48 \\ other car components & 1.55 & 1.61 & 2.05 & 2.64 \\ car wash & 10.76 & 7.38 & 7.84 & 7.83 \\ logistics association registration fee & 15.66 & 16.11 & 24.85 & 24.59 \\ parking & 36.82 & 60.54 & 61.87 & 92.14 \\ accommodation & 0.00 & 0.00 & 0.00 & 0.00 \\ telecommunication & 64.46 & 62.37 & 74.26 & 72.30 \\ toll & 0.00 & 0.00 & 0.00 & 0.00 \\ Total & 4265.53 & 6146.65 & 8001.45 & 9326.92 \\ \hline \hline \end{tabular}  
* Unit: since the data source converted all factor units to US dollars per month, we used US dollars per month as the unit of analysis. Note: this study categorized trucks into 1-, 5-, 12-, and 25-ton trucks since they are used most frequently in the logistics industry in South Korea. Note: this study used the factors in this table since they are utilized by Hanjin Logistics Corporation, which provided the data. Note: all values have been converted to US dollars using the exchange rate of 26 January 2023, which is 1230.87 South Korean won per US dollar.  
\end{table}
Table 1: Operation cost data for the manually driven trucks in the case study of the route.