Acceptance of Driverless Vehicles: Results from a Large Cross-National Questionnaire Study

Abstract

Shuttles that operate without an onboard driver are currently being developed and tested in various projects worldwide. However, there is a paucity of knowledge on the determinants of acceptance of driverless shuttles in large cross-national samples. In the present study, we surveyed 10,000 respondents on the acceptance of driverless vehicles and sociodemographic characteristics, using a 94item online questionnaire. After data filtering, data of 7,755 respondents from 116 countries were retained. Respondents reported that they would enjoy taking a ride in a driverless vehicle (mean = 4.90 on a scale from 1 = disagree strongly to 6 = agree strongly). We further found that the scores on the questionnaire items were most appropriately explained through a general acceptance component, which had loadings of about 0.7 for items pertaining to the usefulness of driverless vehicles and loadings between 0.5 and 0.6 for items concerning the intention to use, ease of use, pleasure, and trust in driverless vehicles, as well as knowledge of mobility-related developments. Additional components were identified as thrill seeking, wanting to be in control manually, supporting a car-free environment, and being comfortable with technology. Correlations between sociodemographic characteristics and general acceptance scores were small (<0.20), yet interpretable (e.g., people who reported difficulty with finding a parking space were more accepting towards driverless vehicles). Finally, we found that the GDP per capita of the respondents' country was predictive of countries' mean general acceptance score ( = −0.48 across 43 countries with 25 or more respondents). In conclusion, self-reported acceptance of driverless vehicles is more strongly determined by domain-specific attitudes than by sociodemographic characteristics. We recommend further research, using objective measures, into the hypothesis that national characteristics are a predictor of the acceptance of driverless vehicles.

Toward a User Acceptance Model of Autonomous Driving

“…While they do not explicitly focus their survey on cars of automation level 4 or 5, they also took the expected user experience into account. Several studies [5,17,19] partly used the UTAUT model as a framework to gain a better understanding of the factors affecting the construct "intention to use". Hein et al [10] made use of the technology acceptance model to assess users' adoption of autonomous cars while integrating moderating factors into their model.…”

“…The construct performance expectancy is the strongest predictor of behavioral intentions and has a positive influence on the intention to use [27]. The positive effect of performance expectancy on the acceptance of autonomous vehicles has been investigated and validated in various articles [19,24].…”

“…The construct effort expectancy gives valuable insights into the perceived difficulty in using autonomous driving systems and has a positive influence on intention to use. The impact of effort expectancy plays a significant role in the context of autonomous vehicle acceptance [5,19].…”

“…Mayer et al [18], p. 712 define trust as the "willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party". Studies have investigated and proved that trust is a redundant determinant to predicting the acceptance of autonomous driving [5,19]. Therefore, trust items are included in the construct of behavioral intentions.…”

Safer than the average human driver (who is less safe than me)? Examining a popular safety benchmark for self-driving cars

“…This possibility notwithstanding, perceived safety, although important, is not the only factor that will contribute to acceptance of high automation in vehicles. Research on acceptance of automation in vehicles has been studied as a multidimensional construct (see, e.g., Nees, 2016;Nordhoff, de Winter, Kyriakidis, van Arem, & Happee, 2018). Acceptance is expected AUTOMATION SAFETY 21 also to be impacted by factors including (but not limited to) cost, experience with technology, and ease-of-use, and these additional factors may attenuate concerns with perceived safety.…”