Calibrating trust through knowledge: Introducing the concept of informed safety for automation in vehicles
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Most autonomous driving studies included information on automation capabilities such as conditional automation levels (e.g., Level 3 - roughly 75% automation), except for one study which included a highly automated system (Level 4).
“In contrast, most autonomous driving studies included information on the automation capabilities such as conditional automation levels (e.g., Level 3 -roughly 75% automation), except for one study, which included a highly automated system (Level 4) [61].”
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 [61]
Khastgir et al. found that increasing knowledge about a system's capabilities and limitations increased trust in high and low capability autonomous vehicles and reduced accidents for low capability autonomous vehicles.
“To that end, Khastgir et al. [61] found that increasing knowledge about a system's capabilities and limitations increased trust in high and low capability-autonomous vehicles and reduced the number of accidents for low capability-autonomous vehicles.”
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 [61]
Most commonly, trust calibration was measured as statistical differences of trustworthiness perceptions between high-reliability and low-reliability groups, examined through analysis of variance.
“Most commonly, the trust calibration was measured as the statistical diferences of trustworthiness perceptions of systems with high reliability and trustworthiness perceptions of systems with low-reliability groups, examined through analysis of variance (see, e.g., [4, 15, 26, 47, 58, 61, 68-70, 82, 84, 89, 90, 107, 117, 130, 140, 145]).”
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 [61]
Performance trust calibrations inform users about specific capabilities and limitations of a system, such as confidence or general reliability, and do not inform how the system arrived at a decision.
“Performance trust calibrations inform users about the specifc capabilities and limitations of a system, such as information about a system's confdence [90,104,145] or general information about a system's reliability [61,69].Such performance-oriented trust calibrations do not inform users how the system arrived at a decision.”
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 [61]
Informing users about the reliability of a system helped appropriately adjust trustworthiness perceptions, coined informed safety.
“Informing users about the reliability of a system, for example, helped to appropriately adjust trustworthiness perceptions [61] which the authors coined as”
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 [61]
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3D Printed Self Driving Electric Vehicle
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- Authors
- Khastgir, S., Birrell, S., Dhadyalla, G., & Jennings, P.
- Affiliations
- University of Warwick (GB)
- Corresponding author
- Khastgir, Siddartha
- Venue
- Transportation Research Part C: Emerging Technologies
- Publisher
- Elsevier BV
- Published
- 2018-11
- Volume
- 96
- Pages
- 290-303
- ISSN
- 0968-090X (ISSN-L)
- OpenAlex
- W2894922550
- Cited by
- 134
- References
- 64
- Citations by year
- 2026: 13 · 2025: 14 · 2024: 23 · 2023: 15 · 2022: 19 · 2021: 28 · 2020: 12 · 2019: 9 · 2018: 1
- FWCI
- 16.92
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Transportation Research Part C Emerging Technologies (publishedVersion)
- Warwick Research Archive Portal (University of Warwick) (acceptedVersion)
- Warwick Research Archive Portal (University of Warwick) (submittedVersion)
- Funders
- EPSRC (EP/K011618/1)
- 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 in automated vehicles, driver knowledge, autonomous driving, public acceptance, driver-vehicle interaction, trust calibration, driving simulator study
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