Impact of Driving Dynamic Fluctuations of 6DOF-SVC Model Predictions Across Five Real-World Driving Studies
- 1Systems Neuroscience & Neurotechnology Unit, Saarland University, Faculty of Medicine
Abstract
Despite the use of technological countermeasures, studies show that the sensory conflict, and thus symptoms of motion sickness such as nausea, cannot be completely prevented while traveling as a car passenger. Accordingly, reliable prediction of motion sickness will represent a possible solution for intelligent vehicles to avoid the abortion of the drive, e.g., through adapted driving strategies or route planning. In previous works, the authors were able to demonstrate an application-oriented parameter set for the popular 6DOF-SVC model to estimate motion sickness incidence (MSI) in passengers with a lowered gaze on a non-driving-related task. In the current study, these parameters were validated and further optimized using five previous conducted motion sickness driving experiments. For the first time, it is also shown that the expected natural MSI fluctuations based on the driving dynamic profile, due to route characteristics or driving style, as well as the variation in experimental determined MSI is approximately 10%. Moreover, findings indicate that the participants appear to have an individual MSI threshold that correlates with their susceptibility to motion sickness, however, this threshold fluctuates too strongly across experiments to be suitable for practical application. As a result, the model can successfully estimate motion sickness risk across the test tracks, however, inaccuracies in the predicted MSI trajectories remain.
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BibTeX
@misc{buchheit2026impact,
title = {{Impact of Driving Dynamic Fluctuations of 6DOF-SVC Model Predictions Across Five Real-World Driving Studies}},
author = {B. Buchheit and Y. Robin and E. N. Schneider and M. Alayan and D. J. Strauss},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.18.752352},
url = {https://www.biorxiv.org/content/10.64898/2026.09.18.752352v1},
note = {CC BY-ND},
}
RIS
TY - UNPB
TI - Impact of Driving Dynamic Fluctuations of 6DOF-SVC Model Predictions Across Five Real-World Driving Studies
AU - B. Buchheit
AU - Y. Robin
AU - E. N. Schneider
AU - M. Alayan
AU - D. J. Strauss
PY - 2026
DA - 2026/09/18
PB - bioRxiv
DO - 10.64898/2026.09.18.752352
UR - https://www.biorxiv.org/content/10.64898/2026.09.18.752352v1
AB - Despite the use of technological countermeasures, studies show that the sensory conflict, and thus symptoms of motion sickness such as nausea, cannot be completely prevented while traveling as a car passenger. Accordingly, reliable prediction of motion sickness will represent a possible solution for intelligent vehicles to avoid the abortion of the drive, e.g., through adapted driving strategies or route planning. In previous works, the authors were able to demonstrate an application-oriented parameter set for the popular 6DOF-SVC model to estimate motion sickness incidence (MSI) in passengers with a lowered gaze on a non-driving-related task. In the current study, these parameters were validated and further optimized using five previous conducted motion sickness driving experiments. For the first time, it is also shown that the expected natural MSI fluctuations based on the driving dynamic profile, due to route characteristics or driving style, as well as the variation in experimental determined MSI is approximately 10%. Moreover, findings indicate that the participants appear to have an individual MSI threshold that correlates with their susceptibility to motion sickness, however, this threshold fluctuates too strongly across experiments to be suitable for practical application. As a result, the model can successfully estimate motion sickness risk across the test tracks, however, inaccuracies in the predicted MSI trajectories remain.
ER -