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Open AccessArticle

Evaluation of a Human–Machine Interface for Motion Sickness Mitigation Utilizing Anticipatory Ambient Light Cues in a Realistic Automated Driving Setting

1
Institute of Transportation Systems, German Aerospace Center (DLR), 38108 Braunschweig, Germany
2
Hella GmbH & Co. KGaA, 59557 Lippstadt, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Gholamreza Anbarjafari (Shahab)
Information 2021, 12(4), 176; https://doi.org/10.3390/info12040176
Received: 21 March 2021 / Revised: 14 April 2021 / Accepted: 15 April 2021 / Published: 20 April 2021
(This article belongs to the Section Information Applications)
Motion sickness (MS) is a syndrome associated with symptoms like nausea, dizziness, and other forms of physical discomfort. Automated vehicles (AVs) are potent at inducing MS because users are not adapted to this novel form of transportation, are provided with less information about the own vehicle’s trajectory, and are likely to engage in non-driving related tasks. Because individuals with an especially high MS susceptibility could be limited in their use of AVs, the demand for MS mitigation strategies is high. Passenger anticipation has been shown to have a modulating effect on symptoms, thus mitigating MS. To find an effective mitigation strategy, the prototype of a human–machine interface (HMI) that presents anticipatory ambient light cues for the AV’s next turn to the passenger was evaluated. In a realistic driving study with participants (N = 16) in an AV on a test track, an MS mitigation effect was evaluated based on the MS increase during the trial. An MS mitigation effect was found within a highly susceptible subsample through the presentation of anticipatory ambient light cues. The HMI prototype was proven to be effective regarding highly susceptible users. Future iterations could alleviate MS in field settings and improve the acceptance of AVs. View Full-Text
Keywords: motion sickness; kinetosis; automated vehicles; human–machine interface; realistic driving study on test track motion sickness; kinetosis; automated vehicles; human–machine interface; realistic driving study on test track
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MDPI and ACS Style

Hainich, R.; Drewitz, U.; Ihme, K.; Lauermann, J.; Niedling, M.; Oehl, M. Evaluation of a Human–Machine Interface for Motion Sickness Mitigation Utilizing Anticipatory Ambient Light Cues in a Realistic Automated Driving Setting. Information 2021, 12, 176. https://doi.org/10.3390/info12040176

AMA Style

Hainich R, Drewitz U, Ihme K, Lauermann J, Niedling M, Oehl M. Evaluation of a Human–Machine Interface for Motion Sickness Mitigation Utilizing Anticipatory Ambient Light Cues in a Realistic Automated Driving Setting. Information. 2021; 12(4):176. https://doi.org/10.3390/info12040176

Chicago/Turabian Style

Hainich, Rebecca; Drewitz, Uwe; Ihme, Klas; Lauermann, Jan; Niedling, Mathias; Oehl, Michael. 2021. "Evaluation of a Human–Machine Interface for Motion Sickness Mitigation Utilizing Anticipatory Ambient Light Cues in a Realistic Automated Driving Setting" Information 12, no. 4: 176. https://doi.org/10.3390/info12040176

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