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What drives support for self-driving car technology in the United States?

Author

Listed:
  • Graham Dixon
  • P. Sol Hart
  • Christopher Clarke
  • Nicole H. O’Donnell
  • Jay Hmielowski

Abstract

Recent advances in automotive technology have made fully automated self-driving cars technologically feasible. Despite offering many benefits such as increased safety, improved fuel efficiency, and greater disability access, public support for self-driving cars remains low. While previous studies find that demographic factors such as age and sex influence self-driving car support, limited research has examined variables that are well known to predict public attitudes toward emerging technology. Using self-report data from a quota sample of American adults (N = 1008), we find that age and sex are not significantly associated with support for self-driving car policies when controlling for these other variables. Instead, significant predictors of support included trust in automotive institutions and regulatory bodies, recognition of self-driving car benefits, positive affect toward self-driving cars, and a greater perception that human-driven cars are riskier than self-driving cars. Importantly, we also find that individualism is negatively associated with support. That is, people who value personal autonomy and limited government regulation may perceive policies encouraging self-driving car use as threatening to their worldviews. Altogether, our results suggest strategies for encouraging greater public support of self-driving vehicles while also forecasting potential barriers as this technology emerges as a fixture in transportation policy.

Suggested Citation

  • Graham Dixon & P. Sol Hart & Christopher Clarke & Nicole H. O’Donnell & Jay Hmielowski, 2020. "What drives support for self-driving car technology in the United States?," Journal of Risk Research, Taylor & Francis Journals, vol. 23(3), pages 275-287, March.
  • Handle: RePEc:taf:jriskr:v:23:y:2020:i:3:p:275-287
    DOI: 10.1080/13669877.2018.1517384
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    Cited by:

    1. Myeongji Oh & Hyejin Jang & Sunhye Kim & Byungun Yoon, 2023. "Main path analysis for technological development using SAO structure and DEMATEL based on keyword causality," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2079-2104, April.
    2. Tyron Louw & Ruth Madigan & Yee Mun Lee & Sina Nordhoff & Esko Lehtonen & Satu Innamaa & Fanny Malin & Afsane Bjorvatn & Natasha Merat, 2021. "Drivers’ Intentions to Use Different Functionalities of Conditionally Automated Cars: A Survey Study of 18,631 Drivers from 17 Countries," IJERPH, MDPI, vol. 18(22), pages 1-19, November.
    3. Hemesath, Sebastian & Tepe, Markus, 2023. "Framing the approval to test self-driving cars on public roads. The effect of safety and competitiveness on citizens' agreement," Technology in Society, Elsevier, vol. 72(C).
    4. O'Shaughnessy, Matthew & Schiff, Daniel & Varshney, Lav R. & Rozell, Christopher & Davenport, Mark, 2021. "What governs attitudes toward artificial intelligence adoption and governance?," OSF Preprints pkeb8, Center for Open Science.

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