With self-driving cars making their way on to our roads, we ask not what it would take for them to gain acceptance among consumers, but what impact they may have on other drivers. How they will be perceived and whether they will be trusted will likely have a major effect on traffic flow and vehicular safety. This work first undertakes an exploratory factor analysis to validate a trust scale for human-robot interaction and shows how previously validated metrics and general trust theory support a more complete model of trust that has increased applicability in the driving domain. We experimentally test this expanded model in the context of human-automation interaction during simulated driving, revealing how using these dimensions uncovers significant biases within human-robot trust that may have particularly deleterious effects when it comes to sharing our future roads with automated vehicles.


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    Titel :

    Hitting the Road: Exploring Human-Robot Trust for Self-Driving Vehicles


    Beteiligte:
    Razin, Yosef S. (Autor:in) / Feigh, Karen M. (Autor:in)


    Erscheinungsdatum :

    2020-09-01


    Format / Umfang :

    827812 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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