Heterogeneous attitudes toward autonomous vehicles: evaluation of consumer acceptance of vehicle automation technology using a latent class approach

Abstract

Vehicle automation is expected to reduce the cost of driving and to solve social problems, such as traffic accidents. However, despite the expected benefits of autonomous vehicles, some consumers hesitate to adopt autonomous vehicles due to fears of negative effects from vehicle automation. This study analyzes consumers' heterogeneous preferences for autonomous vehicles using a discrete choice experiment and a latent class model, which enables the clustering of consumer preferences. As a result, consumers' preferences for autonomous vehicles are largely divided into two groups: one group is technology-friendly users (78.0%), and the other group is change avoiders (22.0%). Technology-friendly users tend to prefer advanced vehicle automation and intend to offer their personal information for advanced functions if the information is highly secured and protected. However, change avoiders express tendencies to avoid highly active vehicle automation and are reluctant to use their personal information for operating automation systems. Change avoiders think that laws or regulations specialised for vehicle automation are redundant. In addition, technology-friendly users and change avoiders prefer conditional automation and driver assistance, respectively.