## 3 Materials and Methods
### Definition of User Acceptance Requirements  
Prior research on SAV's HMI has not yet reached a consensus on user acceptance criteria. As summarized in Section 2.1, many scholars have developed a series of models to evaluate the HMI of autonomous driving systems and summarize the relevant factors that can affect user acceptance. However, no standardized requirements exist to compare user acceptance between different HMIs. Table 2 consolidates nearly all the factors that impact user acceptance in those models and categorizes these variables. The influencing factors with personal characteristics such as \"social demographics\" and \"travel behavior\" are eliminated. Hence, we establish six criteria for determining the acceptability parameters for an HMI in a SAV. Figure 2: The three related pillars of the acceptance concept include definition, acceptance model, and assessment structure. The HMI should support users in completing the defined task while interacting with the ASB (**usefulness**) efficiently and accurately (**efficiency**). Furthermore, it should prevent wrong behavior from passengers and other road users (**effectiveness**) without requiring advanced competencies (**learnability**). Additionally, it should be designed for easy comprehension, promote positive user perception (**satisfaction**), and be accessible to individuals with disabilities (**accessibility**). Since this study aims to compare user acceptance between different HMIs, six parameters require a relative instead of an absolute criterion. In addition, the test procedure needs to determine the specific method for evaluating these six parameters. As [PERSON] et al. (1997) stated, user acceptance is directed more toward assessing the system's ergonomics ([PERSON] et al., 2004). According to [PERSON] et al. (2004), the consumer's post-use reaction to HMI can be divided into three categories: behavioral response, cognitive response, and affect ([PERSON] et al., 2004). Their specific performance factors are also sorted out minutely in Figure 3, which shows the categories and directions of user responses in the field of ergonomics. \begin{table}
\begin{tabular}{c c c} \hline
**Influencing Factors** & **Theory/Model Name (Abbr.)** & **Parameters** \\ \hline Perceived usefulness (PU) & TAM; AAM & Usefulness \\ Performance Expectancy (PE) & UTAUT; CTAM; AVAM; MAVA & \\ Perceived Safety & CTAM; AVAM; MAVA & \\ \hline Perceived ease-of-use (PEOU) & TAM; AAM & Efficiency \\ Self-Efficacy & CTAM; AVAM & \\ \hline Effort Expectancy (EE) & UTAUT; CTAM; AVAM; MAVA & Effectiveness \\ \hline Attitude Toward Using & TAM; CTAM; AAM; AVAM & \\ Social Influence (SI) & UTAUT; CTAM; AVAM & \\ Hedonic motivation & MAVA & \\ Perceived benefits/risks & MAVA & \\ \hline Perceived ease-of-use (PEOU) & TAM; AAM & \\ Social Influence (SI) & UTAUT; CTAM; AVAM & \\ Facilitating Conditions (FC) & UTAUT; CTAM; AVAM; MAVA & \\ Service and vehicle characteristics & MAVA & \\ \hline Facilitating Conditions (FC) & UTAUT; CTAM; AVAM; MAVA & \\ Compatibility & AAM & Learnability \\ Service and vehicle characteristics & MAVA & \\ \hline \end{tabular}
\end{table} 
Table 2: Summarized parameters from the technology acceptance theoretical models in Table 1.  
Figure 3: Correlation between the users’ response and ergonomic analysis. Clarify the six parameters that must be examined while engaging with AV interfaces in an ergonomic study environment. In conjunction with the analysis presented in Table 2, categorize the precise description of each influencing factor in the field of ergonomics, together with the specific metrics in which they were measured and the corresponding type of user response, as outlined in Table 3.  
The outcome is presented in Table 4, which displays the assessment metrics for user acceptance. It encompasses five categories of ergonomic analysis and incorporates the stated indications for each factor analysis of user acceptability. Additionally, it includes the specific measurement items and procedures for data collection.