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  Efficacy of augmented visual environments for reducing sickness in autonomous vehicles

de Winkel, K., Pretto, P., Nooij, S., Cohen, I., & Bülthoff, H. (2021). Efficacy of augmented visual environments for reducing sickness in autonomous vehicles. Applied Ergonomics, 90: 103282, pp. 1-7. doi:10.1016/j.apergo.2020.103282.

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de Winkel, K1, 2, Author           
Pretto, P1, 2, Author           
Nooij, SAE1, 2, Author           
Cohen, I1, 2, Author           
Bülthoff, HH1, 2, Author           
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: The risk of motion sickness is considerably higher in autonomous vehicles than it is in human-operated vehicles. Their introduction will therefore require systems that mitigate motion sickness. We investigated whether this can be achieved by augmenting the vehicle interior with additional visualizations. Participants were immersed in motion simulations on a moving-base driving simulator, where they were backward-facing passengers of an autonomous vehicle. Using a Head-Mounted Display, they were presented either with a regular view from inside the vehicle, or with augmented views that offered additional cues on the vehicle’s present motion or motion 500ms into the future, displayed on the vehicle’s interior panels. In contrast to the hypotheses and other recent studies, no difference was found between conditions. The absence of differences between conditions suggests a ceiling effect: providing a regular view may limit motion sickness, but presentation of additional visual information beyond this does not further reduce sickness.

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 Dates: 2021-01
 Publication Status: Issued
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 Identifiers: DOI: 10.1016/j.apergo.2020.103282
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Title: Applied Ergonomics
Source Genre: Journal
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Publ. Info: Elsevier
Pages: - Volume / Issue: 90 Sequence Number: 103282 Start / End Page: 1 - 7 Identifier: ISSN: 0003-6870