Talking Cars, Doubtful Users—A Population Study in Virtual Reality

Abstract

Autonomous vehicles represent a significant development in our society, and their acceptance will largely depend on trust. This study investigates strategies to increase trust and acceptance by making the cars’ decisions. For this purpose, we created a virtual reality (VR) experiment with a self-explaining autonomous car, providing participants with verbal cues about crucial traffic decisions. First, we investigated attitudes toward self-driving cars among 7850 participants using a simplified version of the Technology Acceptance Model (TAM) questionnaire. Results revealed that female participants are less accepting than male participants, and that there is a general decline among all genders. Otherwise in general, a self-explaining car has a positive impact on trust and perceived usefulness. Surprisingly, it adversely affected the intention to use and perceived ease of use. This entails dissociation of trust from the other items of the questionnaire. Second, we analyzed behavioral of 26 750 participants to investigate the effect of self-explaining systems on head movements during the VR drive. We observed significant differences in head movements during the critical events and the baseline periods of the drive between the three driving conditions. Additionally, we demonstrated positive correlations between head movement parameters and the TAM scores, where trust showed the lowest correlation. This provides further evidence of the dissociation of trust from other TAM items. These findings illustrate the benefits of combining subjective questionnaire data with objective behavioral data. Overall, the outcomes indicate a partial dissociation of self-reported trust from intention to use and objective behavioral data.