## 4 Results
### Constructs and Methodological Approaches
#### 4.3.2 Trust, Acceptance, and Workload  
_Trust_ in AD is investigated as the second most used construct, see Table 1. Here, in contrast to safety, more self-reported (n\({}_{\text{p}}\) = 42) data are reported. Most common is the usage of a self-defined questionnaire (n = 19), or a standardized questionnaire, especially the Automation Trust Scale (ATS) [91] (n = 12) is popular. The interpersonal trust scale (ITS) [92], trust in technology scale [93], Van der Laan scale [94], the Trust Perception Scale-HRI [95] and the Propensity to Trust Scale [96] are each used only once. Interviews, structured and semi-structured, are more rarely used (n = 4). However, behavioral parameters (n\({}_{\text{p}}\) = 19) are also collected, by observing (n = 5) body pose and movements, acceleration and braking behavior, gaze duration on an area of interest, etc. In addition, eye-tracking (n = 4) is conducted. Only one paper [97] used driving performance (braking and steering behavior) and TOR (reaction time) performance measures. This paper additionally collected participants' hands on wheel and eyes on road time using observation, see Table 3. In total, n\({}_{\text{p}}\) = 28 different parameters were collected across all papers investigating trust--78% of the studies were conducted in a driving simulator, 16% in a real vehicle, 11% used a textual description and 5% a Wizard-of-Oz setup to represent the AV. _Acceptance_ is investigated by self-reported parameters as intensively as _trust_ (n\({}_{\text{p}}\) = 41). Researchers mostly apply standardized questionnaires (n = 18). Thereby, the Van der Laan acceptance scale [94] is the most frequently used questionnaire. Furthermore, the technology acceptance model (TAM) [35], the Unified Theory of Acceptance and Use of Technology (UTAUT) [36] or the Car Technology Acceptance Model (CTAM) [24] are frequently used approaches. The self-defined questionnaire is also a popular collection method here (n = 13). Behavioral data (n\({}_{\text{p}}\) = 3) on acceptance is collected by observing (n = 3) the time to system activation, and the number/share of times the automation was enabled/disabled by study participants. Driving performance, or qualitative methods like interviews or focus groups, are applied less frequently (n\(<\) = 2), see Table 4.  
In total, n\({}_{\text{p}}\) = 15 different parameters were collected across all papers investigating acceptance. In total, 53% of the studies were conducted in a driving simulator, 29% used only static text, and 15% used a real vehicle, respectively 3% used either a sketch or a Wizard-of-Oz setup. \begin{table}
\begin{tabular}{l l l} \hline \hline
**Collection Method for Safety (n)** & **Parameter** & **n\({}_{\text{p}}\)** \\ \hline \multirow{4}{*}{Standardized Questionnaire (6)} & Scale for Criticality Assessment of Driving and Traffic Scenarios & 2 \\ \cline{2-3}  & Cooper–Harper Scale & 2 \\ \cline{2-3}  & Auditory Urgency Scale & 1 \\ \hline \multirow{4}{*}{Secondary Task Performance (3)} & NDRT Engagement & 1 \\ \cline{2-3}  & Reaction Time & 1 \\ \cline{2-3}  & \(N\)/\(D\) & 1 \\ \hline Interviews (2) & Semi-structured Interview & 2 \\ \hline Matching (1) & Accuracy & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont.__Workload_ is also investigated mainly by using self-reported measures (n\({}_{\text{p}}\) = 26), usually by implementing standardized questionnaires. The NASA Task Load Index (NASA-TLX, n = 17) [69] is the most popular, other questionnaires like Driver Activity Load Index (DALI) [98], Rating Scale Mental Effort (RSME) [99], scale for subjectively experienced effort (SEA) [100], or the global mental workload measurement by [PERSON] [101] are more rarely applied, as well as self-defined questionnaires (n = 4) and semi-structured interviews (n = 1).