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

• Older Australian drivers’ perception and acceptance of Fully Automated Vehicles were studied. • A path analysis with Structural Equation Modelling was conducted based on the Theory of Planned Behaviour model. • Older drivers’ age, education level and Advanced Driver Assistance Systems experience were significant factors. • Perceived driving ability and inclination to avoid challenging driving situations influenced acceptance. • Effects of perceived health and driving ability were mediated by the constructs of the Theory of Planned Behaviour. 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.

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Publication Details

Journal
Transportation Research Part F Traffic Psychology and Behaviour
Published
2025-02-12
DOI
https://doi.org/10.1016/j.trf.2025.02.009
Citations
9
Primary Topic
Older Adults Driving Studies
Type
article
Field-Weighted Citation Impact
38.08
Controls
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article

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

Andry Rakotonirainy, Ning Liu, Ronald Schroeter, Xiaomeng Li
9 citations
Transportation Research Part F Traffic Psychology and Behaviour
Older Adults Driving Studies
38.08
article

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

Andry Rakotonirainy, Ning Liu, Ronald Schroeter, Xiaomeng Li
article en
9 citations

Abstract

• Older Australian drivers’ perception and acceptance of Fully Automated Vehicles were studied. • A path analysis with Structural Equation Modelling was conducted based on the Theory of Planned Behaviour model. • Older drivers’ age, education level and Advanced Driver Assistance Systems experience were significant factors. • Perceived driving ability and inclination to avoid challenging driving situations influenced acceptance. • Effects of perceived health and driving ability were mediated by the constructs of the Theory of Planned Behaviour. 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.

Transportation Research Part F Traffic Psychology and BehaviourVol. 110
Queensland University of Technology (AU)
Openalex Percentile: Top 0%
Older Adults Driving Studies
38.08
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