Fully automated driving : Impact of trust and practice on manual control recovery
- Submitting institution
-
Coventry University
- Unit of assessment
- 32 - Art and Design: History, Practice and Theory
- Output identifier
- 21457062
- Type
- D - Journal article
- DOI
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10.1177/0018720815612319
- Title of journal
- Human Factors
- Article number
- -
- First page
- 229
- Volume
- 58
- Issue
- 2
- ISSN
- 0018-7208
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This journal paper explores driver attitude and behaviour when interacting for the first time with a fully automated vehicle in a simulator. It addresses the following questions: How much training is needed to safely recover control from a fully automated car? Does trust in the system affect manual control recovery performances?
The research demonstrates the new manoeuvres introduced through fully automated driving, and extends knowledge on driver training requirements to ensure safe operation of such a system.
This research is grounded in the multidisciplinary Goals for Driver Education (GDE) framework, applying concepts from psychology such as trust, training and behaviour. The GDE matrix, initially used for manual cars, is applied here to identify the new driving manoeuvres introduced by fully automated driving. Manoeuvres within an automated car were articulated with the concept of trust, germinal in the field of human-machine interactions.
This research was funded by the Institut Vedecom, France, and is intended to advance the development of automated driving systems. It highlights the importance of driver training for the use of fully automated cars, particularly to improve response times when regaining control from the system; and shows that practicing manual control recovery mitigates the negative impact of over-trust in the system.
The research has been presented at the International Conference on Applied Psychology in 2014 and has been influential in a diverse range of fields, including applied ergonomics and human factors, accident analysis, and automotive design, as well as intelligent systems design (such as IEEE).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -