## 1 Introduction  
The Industrial Revolution was an outcome of continuous technological development, and it profoundly improved the quality of people's lives, and brought paradigmatic shifts in various fields, including industry, culture, and the economy. Human requirements continue to evolve with the improving quality of human life as time and the sociotechnical environment progress [1]. Likewise, technology develops because it coevtives with human values (Figure 1) [2]. Developers must understand the user requirements of a period and establish efficient research and development strategies on the basis of that understanding [3]. If mismatches arise between users and developers with regard to the acceptance of a technology, challenges can ensue when a new technology is introduced [4]. It is important to note that any attractive technological characteristic cannot maintain its utility for user satisfaction indefinitely. These days, user values have progressed to include usability and good user experiences, which are far beyond the functionality and reliability values of a technology [5]. It should also be noted that people differ, and the level of user acceptance of a technology can likewise differ. Various factors determine technological acceptance, and their effects are not homogeneous for all users [6]. Along with artificial intelligence and Internet of Things technologies, autonomous driving is representative of the Fourth Industrial Revolution. Its commercialization is being accelerated by the rapid developments in information and communication technology [7]. Research and developments in autonomous driving are supported at various national levels, and several automobile companies are rapidly developing the relevant technologies [8]. However, according to research conducted by the Korea Research Institute for Human Settlements (KRIHS), most of these studies are only focused on developing the functional aspects of the technology [9]. Although studies related to transportation systems are being conducted, their discussions of the social impacts are relatively insufficient [10]. It is noted that the specific definitions for: (a) the factors determining the acceptance of autonomous driving; and (b) the systematic investigation methods, are also unclear [10]. \"The higher the functional performance and reliability, the better the user acceptance\" seems to be a faulty assumption that is commonly found in technological acceptance studies. As mentioned previously, the needs of users are changing and the contribution of a specific factor on technological acceptance becomes less critical when that factor is more atypical [11]. To solve the shortcomings of previous research, we must identify the criteria for classifying components that affect the acceptance of autonomous driving technology; moreover, analysis and interpretation are required to provide specific information regarding the driver acceptance of autonomous driving. The Kano model classifies the quality attributes of a product or service into several factors, according to the customer satisfaction and product function [12]. In addition, it is excellent at deriving the direction of product development because it accommodates the needs of customer satisfaction and interests [13; 14; 15]. A Kano model implementing these features is considered to be an appropriate research method to compensate for the shortcomings of previous research because it can capture the varying acceptances of a technology across various dimensions. It is also considered to be effective for understanding the differences in user requirements with regard to technology [16]. In this study, we use the Kano model as a tool to identify and categorize the factors determining the acceptance of autonomous driving technology. A research framework based on this model is presented, and its validity is reviewed.