Trust in automated vehicles: constructs, psychological processes, and assessment Article Swipe
Francesco Walker
,
Yannick Forster
,
Sebastian Hergeth
,
Johannes Kraus
,
William Payre
,
Philipp Wintersberger
,
Marieke Martens
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fpsyg.2023.1279271
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fpsyg.2023.1279271
There is a growing body of research on trust in driving automation systems. In this paper, we seek to clarify the way trust is conceptualized, calibrated and measured taking into account issues related to specific levels of driving automation. We find that: (1) experience plays a vital role in trust calibration; (2) experience should be measured not just in terms of distance traveled, but in terms of the range of situations encountered; (3) system malfunctions and recovery from such malfunctions is a fundamental part of this experience. We summarize our findings in a framework describing the dynamics of trust calibration. We observe that methods used to quantify trust often lack objectivity, reliability, and validity, and propose a set of recommendations for researchers seeking to select suitable trust measures for their studies. In conclusion, we argue that the safe deployment of current and future automated vehicles depends on drivers developing appropriate levels of trust. Given the potentially severe consequences of miscalibrated trust, it is essential that drivers incorporate the possibility of new and unexpected driving situations in their mental models of system capabilities. It is vitally important that we develop methods that contribute to this goal.
Related Topics
Concepts
Software deployment
Objectivity (philosophy)
Automation
Set (abstract data type)
Reliability (semiconductor)
Computer science
Psychology
Risk analysis (engineering)
Applied psychology
Knowledge management
Business
Epistemology
Engineering
Philosophy
Quantum mechanics
Physics
Power (physics)
Programming language
Operating system
Mechanical engineering
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fpsyg.2023.1279271
- https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1279271/pdf?isPublishedV2=False
- OA Status
- gold
- Cited By
- 31
- References
- 82
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388945506
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4388945506Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fpsyg.2023.1279271Digital Object Identifier
- Title
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Trust in automated vehicles: constructs, psychological processes, and assessmentWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-11-23Full publication date if available
- Authors
-
Francesco Walker, Yannick Forster, Sebastian Hergeth, Johannes Kraus, William Payre, Philipp Wintersberger, Marieke MartensList of authors in order
- Landing page
-
https://doi.org/10.3389/fpsyg.2023.1279271Publisher landing page
- PDF URL
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https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1279271/pdf?isPublishedV2=FalseDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1279271/pdf?isPublishedV2=FalseDirect OA link when available
- Concepts
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Software deployment, Objectivity (philosophy), Automation, Set (abstract data type), Reliability (semiconductor), Computer science, Psychology, Risk analysis (engineering), Applied psychology, Knowledge management, Business, Epistemology, Engineering, Philosophy, Quantum mechanics, Physics, Power (physics), Programming language, Operating system, Mechanical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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31Total citation count in OpenAlex
- Citations by year (recent)
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2025: 23, 2024: 8Per-year citation counts (last 5 years)
- References (count)
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82Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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