Impact of training and in-vehicle task performance on manual control recovery in an automated car
- Submitting institution
-
Coventry University
- Unit of assessment
- 32 - Art and Design: History, Practice and Theory
- Output identifier
- 21457061
- Type
- D - Journal article
- DOI
-
10.1016/j.trf.2017.02.001
- Title of journal
- Transportation Research Part F: Traffic Psychology and Behaviour
- Article number
- -
- First page
- 216
- Volume
- 46
- Issue
- Part A
- ISSN
- 1369-8478
- Open access status
- Not compliant
- Month of publication
- March
- Year of publication
- 2017
- 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
-
4
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This research was inspired by the Federal Aviation Administration recommending professional pilots fly manually as much as possible to maintain their skills; it was considered by the authors that drivers of automated vehicles should do the same.
This study is one of the first to investigate the benefits of practice and training undertaken by non-professional drivers in a fully automated vehicle, and sought to consider engagement in non-driving related tasks while using full automation, as well as the effect on emergency manual control.
The methodological approach draws on the psychology of trust, as developed and explored in the author’s output ‘Fully Automated Driving: Impact of Trust and Practice on Manual Control Recovery’ and extends this by focusing on the impact of training, using activity analysis methods from ergonomics. The simulator-based study involved 113 participants in which training (simple vs. elaborated) and in-vehicle task performance (with vs. without) were manipulated. The training program developed and implemented is based on theoretical knowledge of automation and practice of specific driving manoeuvres.
Training drivers, using practice of the system and explaining its underlying logic, contributed to improve the human-automation performance. The result highlights the benefits of a training policy to enhance performance and optimize trust in the system. A key outcome is the development of a framework for training individuals when using fully automated vehicles for the first time.
The research was funded by Institut Vedecom, France, and has been applied by the UK and Scottish Law Commissions (Consultation Paper 240, 2016) to discuss the development of new laws about future mobility.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -