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Public acceptance of driver state monitoring for automated vehicles : applying the UTAUT framework

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Smyth, Joseph, Chen, Hanlin, Donzella, Valentina and Woodman, Roger (2021) Public acceptance of driver state monitoring for automated vehicles : applying the UTAUT framework. Transportation Research Part F: Traffic Psychology and Behaviour, 83 . pp. 179-191. doi:10.1016/j.trf.2021.10.003 ISSN 1369-8478.

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Official URL: http://dx.doi.org/10.1016/j.trf.2021.10.003

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Abstract

Driver state monitoring (DSM) systems aim to measure driver/occupant state, considering factors such as fatigue, workload, attentiveness, and wellbeing. They are influential for some vehicles on the road today, but as we move towards higher levels of automation their use is expected to become even more important. Uncertainty around public perception of these systems is a potentially limiting factor, with potential concerns for privacy, data storage, perceived utility, and reliability amongst other things posing potential threats. A survey was conducted based on the Universal Theory of Acceptance and Use of Technology (UTAUT) framework, which collected 311 individual responses to explore the acceptability of this technology in specific relation to conditionally and partially automated vehicles. This paper identified that the factors of effort expectancy, performance expectancy, social influence, and attitudes towards using new technology are all positively related to overall behavioural intention, whereas anxiety is negatively related. Other demographic influences are discussed, and recommendations made for future research and marketing/implementation of DSM systems to ensure acceptance by future users.

Item Type: Journal Article
Subjects: T Technology > TE Highway engineering. Roads and pavements
Divisions: Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH): Automobiles -- Safety appliances, Automated vehicles -- Evaluation, Automobile driving -- Human factors, Automobiles -- Automatic control, Intelligent transportation systems, Automobile driving -- Psychological aspects
Journal or Publication Title: Transportation Research Part F: Traffic Psychology and Behaviour
Publisher: Elsevier
ISSN: 1369-8478
Official Date: November 2021
Dates:
DateEvent
November 2021Published
2 November 2021Available
10 October 2021Accepted
Volume: 83
Page Range: pp. 179-191
DOI: 10.1016/j.trf.2021.10.003
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 5 November 2021
Date of first compliant Open Access: 2 November 2022

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