What changes the autonomous vehicle acceptance after COVID-19? Evidence from China

Abstract

We propose a new theoretical autonomous vehicle (AV) acceptance model and use pre-post data to predict acceptance intention changes in the post-pandemic era. Based on the Technology Acceptance Model (TAM), this paper further incorporated trust, perceived risk, social influence, and perceived COVID-19 risk into the original TAM to explore the public acceptance of AVs. Moreover, combining the structural equation model and ordered logit model, this paper adopted a hybrid choice model including psychological attributes, socio-demographic attributes, travel attributes as well as ethics, legal responsibilities, and vehicle safety levels to clarify determinants of the public AV acceptance changes before and after the pandemic. This study solicited 466 residents in China, and used online surveys to collect stated preference data. The results show that the significant positive impact of COVID-19 on the changes in acceptance of AVs for people's mobility, especially for the higher automation levels. It makes AVs more appealing after COVID-19 outbreak. In addition, perceived usefulness, perceived ease of use, trust, and social influence also have a significant positive impact on the public AV acceptance changes. Gender, age, dedicated lanes, government subsidies, traffic accident experience, travel mode, travel expense, and other factors are related to AV acceptance changes as well. We provide insights for measuring the changes in acceptance of AVs across time due to public health emergencies.