Effects of Non-Driving Related Tasks During Self-Driving Mode
- Submitting institution
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The University of Essex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1486
- Type
- D - Journal article
- DOI
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10.1109/tits.2020.3025542
- Title of journal
- IEEE Transactions on Intelligent Transportation Systems
- Article number
- -
- First page
- 1
- Volume
- Early Access
- Issue
- -
- ISSN
- 1524-9050
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2020
- 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
- No
- Number of additional authors
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3
- Research group(s)
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D - Robotics and Embedded Systems (RES)
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper develops a new virtual-simulator and investigates how immersion in non-driving related tasks affects the take-over performance of drivers in autonomous driving scenarios. The novel-simulator is used efficiently to gather data crucial to easing the transition between manual and autonomous driving; it is one of the first-examples of humans in virtual autonomous driving experiences. Capability of the simulator is proven and permits greater safety/robustness in data collection. Insights provided are highly-relevant for the autonomous driving industry for designing Human-Machine Interfaces. This is collaborative work with the Universitat Autonoma de Barcelona, and results from our EPSRC National Centre for Nuclear-Robotics(EP/R02572X/1-£11.4M).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -