Evaluating Initial Public Acceptance of Highly and Fully Autonomous Vehicles

ABSTRACT

The autonomous vehicle (AV) is expected to dramatically increase road safety. Understanding the public’s initial perceptions and acceptance of AV is imperative because these aspects are likely to determine the future evolution of AVs. This study focuses on public perceptions and acceptance of the two highest levels of vehicle automation – highly autonomous vehicle (HAV) and fully autonomous vehicle (FAV). We drew from the conversation on trust and developed a psychological model to explain three acceptance measures, namely, general acceptance, behavioral intention to use, and willingness to pay (WTP). Using a between-subject survey (N = 742), we determined that the respondents held a stronger belief of benefits from FAV than from HAV. Trust in AV retained a direct effect as well as an indirect effect (mainly through perceived benefit) on the three acceptance measures. In comparison with perceived risk, perceived benefit exerted a higher direct effect on AV acceptance and a higher mediating effect on the trust–acceptance relationship. A prediction analysis further demonstrated that the model exhibited acceptable predictive capability for public acceptance. We drew certain implications for increasing AV acceptance.

Acknowledgments

This study was supported by the National Natural Science Foundation of China (Project no. 71601139) and National Research Foundation of Korea (NRF) under Grant no. NRF-2017R1C1B5076718 funded by the Korea government (MSIP).

Additional information

Notes on contributors

Hongwei Liu

Hongwei Liu is an associate professor of the College of Management and Economics Department in Tianjin University in China. He received his PhD from Tianjin University. His research interests include Industrial Engineering, Human Factors and Ergonomics, and Intelligent Manufacturing.

Run Yang

Run Yang was a graduate student of the College of Management and Economics in Tianjin University in China. She graduated from the University of Jinan in China. Her research is focused on human-automation interaction.

Lin Wang

Lin Wang is an assistant professor at the Department of Library and Information Science of Incheon National University in South Korea. She received her PhD from Tsinghua University in China. Her research interests include human-computer interaction, user experience design, cross-cultural design and design for older adults.

Peng Liu

Peng Liu is an assistant professor in the College of Management and Economics Department in Tianjin University in China. He received his PhD from Tsinghua University in China. His research is focused on human factors and ergonomics and risk analysis in complex systems such as autonomous driving and nuclear power plants. His work has been published in Risk Analysis, Reliability Engineering and System Safety, Transportation Research Part C: Emerging Technologies, International Journal of Industrial Ergonomics, and Energy Policy.