Acceptability of connected automated vehicles: Attributes, perceived behavioural control, and perceived adoption norm

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Samenvatting

Connected Automated Vehicles (CAVs) could be dominating the roads in the near future. CAVs are fully automated vehicles equipped to communicate and share data with other devices both inside and outside the vehicles, and can increase traffic safety and decrease greenhouse emissions from traffic, as they can ensure a more efficient traffic flow and reduce traffic jams. However, CAVs can only achieve this potential when they are accepted and widely adopted by the public. In this paper, we propose a model to explain the acceptability (i.e. evaluation before experience) of CAVs. We hypothesize that the acceptability of CAVs is higher when people evaluate its attributes more favourably, feel more able to use CAVs (i.e. higher perceived behavioural control), and think close others would consider adopting CAVs (i.e. the perceived adoption norm). We identified seven key attributes that could be important for the acceptability of CAVs, namely: safety, instrumental, hedonic, control, symbolic, environmental, and trustworthiness attributes. Results from a large-scale online questionnaire (N = 3783) showed that the proposed model explains acceptability well. Together, the evaluation of attributes of CAVs, perceived behavioural control, and perceived adoption norm explained 60 % of variance in acceptability. Positive evaluations of attributes were the strongest predictor of acceptability of CAVs, in particular safety, instrumental, and environmental attributes. Interestingly, we found that symbolic attributes predict acceptability better when the perceived adoption norm is low. The results suggest the acceptability of CAVs may be enhanced by improving the evaluations of its key attributes and by introducing it as a status product in the early adoption phase.

Originele taal-2English
Pagina's (van-tot)411-423
Aantal pagina's13
TijdschriftTransportation Research Part F: Traffic Psychology and Behaviour
Volume102
DOI's
StatusPublished - apr.-2024

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