Neuroscience

Perception

Technology acceptance model

Social acceptance

Human–computer interaction

Usability

Heuristic

Artificial intelligence

Psychology

Economics

Risk perception

Microeconomics

Affect (linguistics)

Willingness to pay

Computer science

Communication

Social psychology

Risk Analysis

Automated driving (AD) is one of the most significant technical advances in the transportation industry. Its safety, economic, and environmental benefits cannot be realized if it is not used. To explain, predict, and increase its acceptance, we need to understand how people perceive and why they accept or reject AD technology. Drawing upon the trust heuristic, we tested a psychological model to explain three acceptance measures of fully AD (FAD): general acceptance, willingness to pay (WTP), and behavioral intention (BI). This heuristic suggests that social trust can directly affect acceptance or indirectly affect acceptance through perceived benefits and risks. Using a survey (N = 441), we found that social trust retained a direct effect as well as an indirect effect on all FAD acceptance measures. The indirect effect of social trust was more prominent in forming general acceptance; the direct effect of social trust was more prominent in explaining WTP and BI. Compared to perceived risk, perceived benefit was a stronger predictor of all FAD acceptance measures and also a stronger mediator of the trust-acceptance relationship. Predictive ability of the proposed model for the three acceptance measures was confirmed. We discuss the implications of our results for theory and practice.

Public Acceptance of Fully Automated Driving: Effects of Social Trust and Risk/Benefit Perceptions