Gauging Public Acceptance of Conditionally Automated Vehicles in the United States
This research addresses the lack of data on U.S. public acceptance for stakeholders aiming to facilitate autonomous vehicle adoption, but it is incremental as it extends prior European findings to a new region.
The study investigated public acceptance of conditionally automated vehicles in the United States, finding that social influence, performance expectancy, effort expectancy, hedonic motivation, and facilitating conditions determine acceptance, with specific factors influencing perceptions of usefulness, effort, and conditions.
Public acceptance of conditionally automated vehicles is a crucial step in the realization of smart cities. Prior research in Europe has shown that the factors of hedonic motivation, social influence, and performance expectancy, in decreasing order of importance, influence acceptance. Moreover, a generally positive acceptance of the technology was reported. However, there is a lack of information regarding the public acceptance of conditionally automated vehicles in the United States. In this study, we carried out a web-based experiment where participants were provided information regarding the technology and then completed a questionnaire on their perceptions. The collected data was analyzed using PLS-SEM to examine the factors that may lead to public acceptance of the technology in the United States. Our findings showed that social influence, performance expectancy, effort expectancy, hedonic motivation, and facilitating conditions determine conditionally automated vehicle acceptance. Additionally, certain factors were found to influence the perception of how useful the technology is, the effort required to use it, and the facilitating conditions for its use. By integrating the insights gained from this study, stakeholders can better facilitate the adoption of autonomous vehicle technology, contributing to safer, more efficient, and user-friendly transportation systems in the future that help realize the vision of the smart city.