## 1 Introduction  
In the last few decades, with increased interest in the technologies of autonomous vehicles, substantial efforts have been made in the research and development of various driver assistance systems as part of autonomous driving technologies, and such systems are now being introduced at a faster rate. Advanced Driver Assistance Systems (ADASs) such as Adaptive Cruise Control (ACC), Lane Keeping Aid (LKA), and Automatic Emergency Brake (AEB) have a positive impact on traffic safety [1]. It is expected that further development of Advanced Driver Assistance Systems, and eventually highly automated driving, will continue to increase traffic safety by reducing the impact of human error [2]. To advance the commercialization of fully autonomous vehicles, considerable efforts have been invested in the research of semi-automated driving systems such as an automatic lane change system. However, important issues remain including safety, reliability, passengers' acceptance, etc. In particular, acceptance assessment is recognized as one of the most important issues [3, 4]. Because customers decide to use or not use a system, most advanced technologies, such as an autonomous vehicle, will have no value if customers do not use a proposed system even when the system satisfies all requirements of safety and reliability. In accordance with the increased interest in higher levels of automated driving technologies, a reliable assessment tool for driver acceptance is needed for their development and deployment which estimates and secures driver acceptance in a broad manner. Because acceptance is on an individual level, it can only be based on an individual's personal attitudes, expectations, experiences, and subjective evaluation of a system and the effects of using it [3; 5]. A number of studies on user acceptance have been conducted over the past decades. A standardized checklist was proposed for the assessment of the level of acceptance of a new vehicle technology [6]. The idea of technology acceptance was also defined in terms of usefulness, ease of use, effectiveness, affordability, and social acceptance [4]. Technology adaptation characteristics were studied based on gender differences [7]. A technology acceptance model was suggested based on subjective rating scales [8]. The aforementioned technologies are being developed not only for safety but also for convenience. Accordingly, drivers' experience and acceptance of an Intelligent Speed Adaptation system were investigated [9]. Various studies on lane change assistance have been carried out to satisfy drivers' acceptance [10; 11; 12; 13; 14]. In a literature review, referring to [3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14], almost all of the research was conducted based on subjective methods: questionnaire development, questions and/or rating scales, etc. Even though research results concerning acceptance have been presented, how it has been assessed and how the results have been obtained are not described in most studies. Previous studies mostly focused on measuring acceptance as various types of participants' opinions on the target systems. These studies have suggested various types of methods to validate that their results are objectively reliable. As seen in the literature review, acceptance has been considered with individuals' subjective evaluation. Consequently, most studies have used moderate questions/or phrases to obtain individuals' subjective opinions in accordance with a specific structure for the acceptance analysis, and the results were presented with statistics. Therefore, there are a few significant problems as follows. Acceptance is generally assessed after the target systems are realized at certain levels, for example, by performing a jury test with a prototype of the system. Target values or ranges for the evaluation are different in each case. Responses and evaluation results of participants may be dependent on the questionnaires used.