Louw, T orcid.org/0000-0001-6577-6369, Madigan, R orcid.org/0000-0002-9737-8012, Carsten, O et al. (1 more author) (2017) Were they in the loop during automated driving? Links between visual attention and crash potential. Injury Prevention, 23 (4). pp. 281-286. ISSN 1353-8047
Abstract
Background: A proposed advantage of vehicle automation is that it relieves drivers from the moment-to-moment demands of driving, to engage in other, non-driving related, tasks. However, it is important to gain an understanding of drivers’ capacity to resume manual control, should such a need arise. As automation removes vehicle control-based measures as a performance indicator, other metrics must be explored. Methods: This driving simulator study, conducted under the European Commission (EC) funded AdaptIVe project, assessed drivers’ gaze fixations during partially-automated (SAE Level 2) driving, on approach to critical and non-critical events. Using a between-participant design, 75 drivers experienced automation with one of five out-of-the-loop (OOTL) manipulations, which used different levels of screen visibility and secondary tasks to induce varying levels of engagement with the driving task: 1) no manipulation, 2) manipulation by light fog, 3) manipulation by heavy fog, 4) manipulation by heavy fog plus a visual task, 5) no manipulation plus an n-back task. Results: The OOTL manipulations influenced drivers’ first point of gaze fixation after they were asked to attend to an evolving event. Differences resolved within one second and visual attention allocation adapted with repeated events, yet crash outcome was not different between OOTL manipulation groups. Drivers who crashed in the first critical event showed an erratic pattern of eye fixations towards the road centre on approach to the event, while those who did not demonstrated a more stable pattern. Conclusions: Automated driving systems should be able to direct drivers’ attention to hazards no less than 6 seconds in advance of an adverse outcome.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/. This is an author produced version of a paper published in Injury Prevention. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | human factors; highly automated driving; vision; driver behaviour; accident analysis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) |
Funding Information: | Funder Grant number EU - European Union 610428 EU - European Union EXT 448347 |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Aug 2016 09:39 |
Last Modified: | 17 Jan 2018 04:04 |
Published Version: | https://doi.org/10.1136/injuryprev-2016-042155 |
Status: | Published |
Publisher: | BMJ Publishing Group |
Identification Number: | 10.1136/injuryprev-2016-042155 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:103733 |