IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0260953.html
   My bibliography  Save this article

Perceived safety and trust in SAE Level 2 partially automated cars: Results from an online questionnaire

Author

Listed:
  • Sina Nordhoff
  • Jork Stapel
  • Xiaolin He
  • Alexandre Gentner
  • Riender Happee

Abstract

The present online study surveyed drivers of SAE Level 2 partially automated cars on automation use and attitudes towards automation. Respondents reported high levels of trust in their partially automated cars to maintain speed and distance to the car ahead (M = 4.41), and to feel safe most of the time (M = 4.22) on a scale from 1 to 5. Respondents indicated to always know when the car is in partially automated driving mode (M = 4.42), and to monitor the performance of their car most of the time (M = 4.34). A low rating was obtained for engaging in other activities while driving the partially automated car (M = 2.27). Partial automation did, however, increase reported engagement in secondary tasks that are already performed during manual driving (i.e., the proportion of respondents reporting to observe the landscape, use the phone for texting, navigation, music selection and calls, and eat during partially automated driving was higher in comparison to manual driving). Unsafe behaviour was rare with 1% of respondents indicating to rarely monitor the road, and another 1% to sleep during partially automated driving. Structural equation modeling revealed a strong, positive relationship between perceived safety and trust (β = 0.69, p = 0.001). Performance expectancy had the strongest effects on automation use, followed by driver engagement, trust, and non-driving related task engagement. Perceived safety interacted with automation use through trust. We recommend future research to evaluate the development of perceived safety and trust in time, and revisit the influence of driver engagement and non-driving related task engagement, which emerged as new constructs related to trust in partial automation.

Suggested Citation

  • Sina Nordhoff & Jork Stapel & Xiaolin He & Alexandre Gentner & Riender Happee, 2021. "Perceived safety and trust in SAE Level 2 partially automated cars: Results from an online questionnaire," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-21, December.
    • Handle: RePEc:plo:pone00:0260953
    DOI: 10.1371/journal.pone.0260953
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0260953
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0260953&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0260953?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kurani, Kenneth S., 2019. "User Perceptions of Safety and Security: A Framework for a Transition to Electric-Shared-Automated Vehicles," Institute of Transportation Studies, Working Paper Series qt40g1637b, Institute of Transportation Studies, UC Davis.
    2. Kalra, Nidhi & Paddock, Susan M., 2016. "Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 182-193.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andrea Bertolini & Massimo Riccaboni, 2021. "Grounding the case for a European approach to the regulation of automated driving: the technology-selection effect of liability rules," European Journal of Law and Economics, Springer, vol. 51(2), pages 243-284, April.
    2. Khastgir, Siddartha & Brewerton, Simon & Thomas, John & Jennings, Paul, 2021. "Systems Approach to Creating Test Scenarios for Automated Driving Systems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. Yueqi Mao & Qiang Mei & Peng Jing & Ye Zha & Ying Xue & Jiahui Huang & Danning Shao & Pan Luo, 2022. "Factors Affecting the Parental Intention of Using AVs to Escort Children: An Integrated SEM–Hybrid Choice Model Approach," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
    4. Blume, Maximilian & Oberländer, Anna Maria & Röglinger, Maximilian & Rosemann, Michael & Wyrtki, Katrin, 2020. "Ex ante assessment of disruptive threats: Identifying relevant threats before one is disrupted," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    5. Peng Liu & Run Yang & Zhigang Xu, 2019. "How Safe Is Safe Enough for Self‐Driving Vehicles?," Risk Analysis, John Wiley & Sons, vol. 39(2), pages 315-325, February.
    6. Henry X. Liu & Shuo Feng, 2024. "Curse of rarity for autonomous vehicles," Nature Communications, Nature, vol. 15(1), pages 1-5, December.
    7. Winston, Clifford & Karpilow, Quentin, 2017. "A New Route to Increasing Economic Growth: Reducing Highway Congestion with Autonomous Vehicles," Working Papers 03323, George Mason University, Mercatus Center.
    8. Zoltan Ferenc Magosi & Christoph Wellershaus & Viktor Roland Tihanyi & Patrick Luley & Arno Eichberger, 2022. "Evaluation Methodology for Physical Radar Perception Sensor Models Based on On-Road Measurements for the Testing and Validation of Automated Driving," Energies, MDPI, vol. 15(7), pages 1-20, March.
    9. Hudson, John & Orviska, Marta & Hunady, Jan, 2019. "People’s attitudes to autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 164-176.
    10. Liu, Peng & Zhang, Yawen & He, Zhen, 2019. "The effect of population age on the acceptable safety of self-driving vehicles," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 341-347.
    11. Cian Ryan & Finbarr Murphy & Martin Mullins, 2019. "Semiautonomous Vehicle Risk Analysis: A Telematics‐Based Anomaly Detection Approach," Risk Analysis, John Wiley & Sons, vol. 39(5), pages 1125-1140, May.
    12. Hazel Si Min Lim & Araz Taeihagh, 2019. "Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities," Sustainability, MDPI, vol. 11(20), pages 1-28, October.
    13. Jie Min & Yili Hong & Caleb B. King & William Q. Meeker, 2022. "Reliability analysis of artificial intelligence systems using recurrent events data from autonomous vehicles," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(4), pages 987-1013, August.
    14. Marius Wenning & Anton Akira Backhaus & Tobias Adlon & Peter Burggräf, 2022. "Testing the reliability of monocular obstacle detection methods in a simulated 3D factory environment," Journal of Intelligent Manufacturing, Springer, vol. 33(7), pages 2157-2165, October.
    15. Mauricio Marcano & José A. Matute & Ray Lattarulo & Enrique Martí & Joshué Pérez, 2018. "Low Speed Longitudinal Control Algorithms for Automated Vehicles in Simulation and Real Platforms," Complexity, Hindawi, vol. 2018, pages 1-12, March.
    16. Nourinejad, Mehdi & Bahrami, Sina & Roorda, Matthew J., 2018. "Designing parking facilities for autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 110-127.
    17. Demin Nalic & Aleksa Pandurevic & Arno Eichberger & Branko Rogic, 2020. "Design and Implementation of a Co-Simulation Framework for Testing of Automated Driving Systems," Sustainability, MDPI, vol. 12(24), pages 1-12, December.
    18. Kumar, Girish & James, Ajith Tom & Choudhary, Krishna & Sahai, Rishi & Song, Weon Keun, 2022. "Investigation and analysis of implementation challenges for autonomous vehicles in developing countries using hybrid structural modeling," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    19. Talebian, Ahmadreza & Mishra, Sabyasachee, 2022. "Unfolding the state of the adoption of connected autonomous trucks by the commercial fleet owner industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    20. Kurani, Kenneth S., 2019. "User Perceptions of Safety and Security: A Framework for a Transition to Electric-Shared-Automated Vehicles," Institute of Transportation Studies, Working Paper Series qt40g1637b, Institute of Transportation Studies, UC Davis.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0260953. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.