## 1 Introduction  
Automation, usually referred to as automatic control, has developed into a significant component of our modern civilization [1]. Many different supply chains have become more streamlined and efficient during the last decades thanks to automation. These adjustments have frequently led to a decrease in the total cost of operation (TCO) [2]. One of the real-world applications of automation is a fully autonomous truck (AT) in the logistics industry, which refers to light- or heavy-duty commercial trucks that are fully automated (i.e., level 5). The auto industry has been developing new technologies for ATs, which are anticipated to be deployed gradually and earn market shares [3]. This shift will not only provide risks for the involved companies, but it will also present opportunities for them to pursue in the logistics businesses [4]. Accordingly, the past few years have seen significant advancements in the research on the effects of introducing ATs. The economic advantages and costs of ATs are frequently discussed in the gray literature; specifically, in comparison to human-driven trucks (HDTs), it is anticipated that ATs will be able to facilitate significant cost reductions [5]. The availability of data and the unpredictability of costs are two of the primary research challenges associated with calculating TCO. To be more specific, autonomous trucks are still a comparatively new technology, and as a result, there is a paucity of information regarding the costs associated with their operation and maintenance. In addition, the costs associated with operating an autonomous truck can differ greatly depending on a variety of variables including the kind of cargo being transported, the distance traveled, and the terrain.  
This study attempts to overcome the issues and quantify the change in TCO when introducing ATs, from the viewpoint of freight transport operators. This study employs the cost-benefit analysis framework with scenario planning ranging between the most pessimistic and the most optimistic. This study further focuses on the following points in the analysis: first, it developed assumptions of each scenario based on previous literature; second, it used diverse operation cost factors collected from a logistics firm; third, it utilized a case study area of a middle-mile route in South Korea; and fourth, it explored TCO of different types of ATs, such as 1-ton, 5-ton, 12-ton, and 25-ton ATs. The following research questions were posed to investigate: (1) what are the anticipated operating costs involved in putting 1-ton, 5-ton, 12-ton, and 25-ton ATs into operation?; (2) how will the adoption of the ATs influence the costs associated with logistics operations?; and (3) how significant would the impact be on cost estimation when considering various scenarios?  
This study has several areas of significance and many implications. First, the results of this study have the potential to have a substantial economic impact, as they may not only result in substantial cost reductions for logistics firms but may also increase economic productivity if ATs prove cost-effective. Second, it may cast light on the readiness of the logistics industry to adopt ATs, given that the study provides information on the cost-effectiveness of ATs and may help firms overcome potential obstacles and difficulties. Thirdly, investors in the logistics and technology sectors can make informed investment decisions based on the findings of such a study. Fourth, the findings of this study can assist freight transport operators in reallocating resources to operations that are both more vital and performance-enhancing by investigating and analyzing procedures from an operation cost-reduction perspective.