## 4 Results
### General Study Details  
Regarding AD research, we found that SAE L3 is the most frequently studied level of automation with 58.39% (n = 94) followed by Level 2 (36.65%, n = 59) and Level 4 (22.36%, n = 36). Level 5 was investigated in 19.88% (n = 32) of the studies. Thereby, the number of publications gradually increased up to 2018 regardless of a specific level of automation. The one that stands out is SAE L3, which attracted earlier attention than the other levels (see Figure 3); however, the steepest increase in AD research was observed between 2015 and 2016.  
Overall, 73.29% (n = 118) of all studies were conducted in a lab environment, 13.66% (n = 22) as a survey, and 11.80% (n = 19) on real road, while only 2.48% (n = 4) reported results obtained on a test track. This is in accordance with the utilized AV representation. In addition, 71.43% (n = 115) of the papers reported to have used a driving simulator, 12.42% (n = 20) a real vehicle, 11.18% (n = 18) a textual description, 7.45% (n = 12) a Wizard-of-Oz setup, and 3.11% (n = 5) a visualization. We observed thereby a clear tendency towards single session evaluation (94.41%, n = 152), and only nine papers called in participants multiple times, where 3.11% (n = 5) investigated automated driving use over a  
Figure 3: Frequencies (n) of ADS papers regarding the investigated SAE level of automation as evolved over time since 2010. SAE L0 and L1 are excluded as they are not part of this literature review.  
short time period (e.g., up to one week) [70] and three studies (1.86%) long-term effects in longitudinal studies (e.g., by following a survey approach [47]).  
While 60.25% (n = 97) of the papers conducted basic research such as observing pedestrian interaction behavior with AVs on real roads [71], 34.78% (n = 56) papers evaluated a specific concept in their study (e.g., a haptic seat to prepare driver for TORs) [72]. Smaller percentages of studies conducted empirical research about AD with the aim to create a method (8.07%, n = 13) or a model (1.86%, n = 3). The center of empirical research on AD is clearly the driver, who was investigated in 78.26% (n = 126) of all studies. Passengers (9.32%, n = 15) and other road users (6.83%, n = 11, e.g., pedestrians) are still a side topic in AD HCI research. The environmental driving context is varying, while 47.83% (n = 77) investigated a highway setting, 19.88% (n = 32) addressed urban, and 19.25% (n = 31) rural road conditions. For the remaining studies (13.04%, n = 21), the road type was either not relevant or not described.  
Study participants' mean age in the most papers is below 40 years (n = 98), and only a few papers report higher mean ages such as [PERSON] et al. [73], who in particular invited participants older than 65 to investigate acceptance of AVs in comparison with participants of younger age (see Figure 4). In 12.42% (n = 20), participants' age is not reported.  
In total, 57.76% (n = 93) of the papers selected their participants randomly, while only 29.81% (n = 48) used targeted sampling. The rest (n = 20) did not provide any indication about participant sampling. Thereby, 34.40% (n = 57) of papers recruited participants internally (e.g., students or employees of their institution), and 44.10% (n = 71) invited external participants. The remaining publications (20.5%) did not provide this information.