Trust Repair Strategies with Self-Driving Vehicles: An Exploratory Study
Abstract
Trust is important for any relationship, especially so with self-driving vehicles: passengers must trust these vehicles with their life. Given the criticality of maintaining passenger’s trust, yet the dearth of self-driving trust repair research relative to the growth of the self-driving industry, we conducted two studies to better understand how people view errors committed by self-driving cars, as well as what types of trust repair efforts may be viable for use by self-driving cars. Experiment 1 manipulated error type and driver types to determine whether driver type (human versus self-driving) affected how participants assessed errors. Results indicate that errors committed by both driver types are not assessed differently. Given the similarity, experiment 2 focused on self-driving cars, using a wide variety of trust repair efforts to confirm human-human research and determine which repairs were most effective at mitigating the effect of violations on trust. We confirmed the pattern of trust repairs in human-human research, and found that some apologies were more effective at repairing trust than some denials. These findings help focus future research, while providing broad guidance as to potential methods for approaching trust repair with self-driving cars.
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Kohn et al. found apologies worked better to regain trust than a system denying an error.
“To that end, Kohn and colleagues [64] found that apologies worked better to regain trust than a system denying an error.”
From Measuring and Understanding Trust Calibrations for Automated Systems: A Survey of the State-Of-The-Art and Future Directions (2023) · cites this paper as [64]
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- Authors
- Kohn, S. C., Quinn, D., Pak, R., de Visser, E. J., & Shaw, T. H.
- Affiliations
- George Mason University (US)
- Clemson University (US)
- United States Air Force Academy
- Venue
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting
- Publisher
- SAGE Publications
- Published
- 2018-09
- Volume
- 62
- Issue
- 1
- Pages
- 1108-1112
- ISSN
- 0163-5182 (ISSN-L)
- 1071-1813
- 2169-5067
- OpenAlex
- W2893887721
- Cited by
- 64
- References
- 17
- Citations by year
- 2026: 2 · 2025: 12 · 2024: 7 · 2023: 11 · 2022: 10 · 2021: 11 · 2020: 2 · 2019: 8 · 2018: 1
- FWCI
- 7.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Keywords
- trust repair, autonomous vehicles, passenger trust, breach of trust, apology, denial, error evaluation
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