Trust, risk perception, and intention to use autonomous vehicles: an interdisciplinary bibliometric review

Mohammad Naiseh, Jediah Clark, Tugra Akarsu, Yaniv Hanoch, Mario Brito, Mike Wald, Thomas Webster, Paurav Shukla

    Research output: Contribution to journalArticlepeer-review

    5 Citations (Scopus)
    66 Downloads (Pure)

    Abstract

    Autonomous vehicles (AV) offer promising benefits to society in terms of safety, environmental impact and increased mobility. However, acute challenges persist with any novel technology, inlcuding the perceived risks and trust underlying public acceptance. While research examining the current state of AV public perceptions and future challenges related to both societal and individual barriers to trust and risk perceptions is emerging, it is highly fragmented across disciplines. To address this research gap, by using the Web of Science database, our study undertakes a bibliometric and performance analysis to identify the conceptual and intellectual structures of trust and risk narratives within the AV research field by investigating engineering, social sciences, marketing, and business and infrastructure domains to offer an interdisciplinary approach. Our analysis provides an overview of the key research area across the search categories of ‘trust’ and ‘risk’. Our results show three main clusters with regard to trust and risk, namely, behavioural aspects of AV interaction; uptake and acceptance; and modelling human–automation interaction. The synthesis of the literature allows a better understanding of the public perception of AV and its historical conception and development. It further offers a robust model of public perception in AV, outlining the key themes found in the literature and, in turn, offers critical directions for future research.

    Original languageEnglish
    Pages (from-to)(In-Press)
    Number of pages21
    JournalAI & Society
    Volume(In-Press)
    Early online date25 Mar 2024
    DOIs
    Publication statusE-pub ahead of print - 25 Mar 2024

    Bibliographical note

    This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

    Funder

    This work was supported by the Engineering and Physical Sciences Research Council (EP/V00784X/1).

    Funding

    This work was supported by the Engineering and Physical Sciences Research Council (EP/V00784X/1).

    FundersFunder number
    Engineering and Physical Sciences Research CouncilEP/V00784X/1

    Keywords

    • Autonomous vehicles
    • Trust
    • Risk
    • Bibliometric analysis

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