Examining older drivers’ acceptance of fully automated vehicles by considering their health and driving ability conditions

Older adults often face outdoor mobility challenges due to age-related declines in vision, cognitive and physical functions. Although there is still a great proportion of older drivers who continue to drive, some have gradually reduced their driving frequency or even ceased driving. Automated Vehicle technology has developed rapidly and has the potential to benefit older drivers in maintaining their mobility and social activities. However, these prospective benefits can only be achieved if older drivers intend to use Automated Vehicles. This study aims to investigate older drivers’ intention to use Fully Automated Vehicles based on the Theory of Planned Behaviour by considering the impact of their perceived health, perceived driving ability and current driving patterns. A total of 672 participants consisting of 197 females and 475 males who lived in Australia joined the study and completed an online survey, and the collected data were analysed by using the Structural Equation Modelling. The results indicate that the older drivers’ intention to use Fully Automated Vehicles decreased with their age and increased with their education levels. Older driver who had more experience in using Advanced Driver Assistance Systems were more likely to use Fully Automated Vehicles, and those who tended to avoid challenging driving situations (e.g., night driving, highways) were likely conservative in using Fully Automated Vehicles. The Theory of Planned Behaviour constructs of attitudes and subjective norms played mediating effects between perceived health, perceived driving ability and the intention to use Fully Automated Vehicles. Older drivers with lower perceived health were more likely to exhibit negative attitudes and a lower level of subjective norms towards Fully Automated Vehicles, ultimately leading to a lower intention to use them. Overall, the findings provide deep insights into the key individual determinants influencing older drivers’ intention to use Fully Automated Vehicles and offer strategic policy recommendations to encourage the adoption of Fully Automated Vehicles when they become available.