Understanding the public acceptance of automated minibuses: A market segmentation analysis across European cities

The introduction of automated vehicles (AVs) in public transport may facilitate a shift towards a more sustainable urban mobility system. However, the success of AV deployment in public transport hinges on public acceptance of this new transportation option. Acceptance levels vary significantly and are influenced more by psychographic factors—such as attitudes—than by demographic characteristics such as age or gender. To better understand the acceptance of AVs in public transport, this study attempts to analyse the diversity in the population on the basis of a psychographic market segmentation study. The study was conducted by means of a representative online survey in four European cities: Lyon, Copenhagen, Luxembourg, and Geneva. We identified five distinct market segments: unreserved goodwill, sceptical goodwill, undecided, critical reserved, and unconvinced refusers. The findings reveal substantial variations in AV acceptance among these segments, indicating that a uniform strategy is inadequate. This research provides a better understanding of the factors that influence the public's willingness to use AVs in public transport and thus reduce dependence on private vehicles. This study emphasizes that acceptance is more dependent on psychographic characteristics, particularly individual and subjective attitudes towards the associated risks and benefits. • Public acceptance is essential for AV success in public transport and sustainable urban mobility. • This study assessed public perceptions of automated vehicles (AVs) on risks and benefits across various cities. • The survey in Lyon, Copenhagen, Luxembourg, and Geneva identified five market segments regarding AV acceptance. • A slight majority of citizens are open to adopting AVs, influenced more by psychographic factors than demographics. • .Insights gained emphasize individual attitudes toward risks and benefits as key to understanding AV acceptance variability.