Abstract Autonomous vehicles (AVs) are stepping into our daily life. The acceptance of AVs by people, especially private vehicle drivers (PVDs), would significantly influence the deployment of AVs and the future shape of our transportation. Trait mindfulness, characterized by novel distinction-drawing that results in being sensitive to the novelty, is an enduring mindset that may, though not certain, facilitate the acceptance of AVs. To provide an answer, a questionnaire survey was conducted and the 14-item Langer Mindfulness Scale is adopted to measure participants' trait mindfulness. A structural equation model is established based on the Technology Acceptance Model to explore the relationship between trait mindfulness and PVDs' AV acceptance. Results show that trait mindfulness is a positive predictor of PVDs' AV acceptance, and mindful drivers tend to be open to accept AVs and would become early users of AVs. Mindfulness could improve PVDs’ AV perceptions to promote AV acceptance. This finding contributes to the early promotion of AVs in practice, e.g., targeting AV advertisements to the mindful PVDs would be particularly effective.

    Highlights A trait mindfulness and autonomous vehicle (AV) acceptance model is established. Trait mindfulness positively predicts private vehicle drivers' AV acceptance via social image, ease of use, and usefulness. Compared to perceived ease of use and social image, trait mindfulness is a stronger predictor of AV acceptance. It suggests that targeting mindful individuals would be effective for the early promotion of AV adoptions.


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    Titel :

    Private vehicle drivers’ acceptance of autonomous vehicles: The role of trait mindfulness


    Beteiligte:
    Guan, Jinping (Autor:in) / Du, Xinyu (Autor:in) / Zhang, Jiayue (Autor:in) / Maymin, Philip (Autor:in) / DeSoto, Emma (Autor:in) / Langer, Ellen (Autor:in) / He, Zhengbing (Autor:in)

    Erschienen in:

    Transport Policy ; 149 ; 211-221


    Erscheinungsdatum :

    2024-02-18


    Format / Umfang :

    11 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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