---
title: "6DOF-SVC Model Performance and Driving Dynamics: Predicting Motion Sickness Across Five Real-World"
id: "biorxiv-2-impact-of-driving-dynamic-fluctuations-of-6dof-svc-model-predictions-across"
canonical_url: "https://medichelpline.com/clinical-feed/biorxiv-2-impact-of-driving-dynamic-fluctuations-of-6dof-svc-model-predictions-across"
content_type: "clinical_feed_article"
specialty: "Neurology"
source_name: "bioRxiv (Biomedical Preprints)"
source_url: "https://www.biorxiv.org/content/10.64898/2026.09.18.752352v1?rss=1"
published_at: "2026-09-22T08:47:28.000Z"
evidence_level: "Verified Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# 6DOF-SVC Model Performance and Driving Dynamics: Predicting Motion Sickness Across Five Real-World
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/biorxiv-2-impact-of-driving-dynamic-fluctuations-of-6dof-svc-model-predictions-across
- **Specialty:** [Neurology](https://medichelpline.com/clinical-feed/neurology.md)
- **Primary Source:** bioRxiv (Biomedical Preprints)
- **Source URL:** [Original Journal Publication](https://www.biorxiv.org/content/10.64898/2026.09.18.752352v1?rss=1)
- **Published At:** 2026-09-22T08:47:28.000Z
- **Evidence Rating:** Verified Feed
## Executive GIST (TL;DR)
- The study validated and further optimized an application-oriented parameter set for the **6DOF-SVC** (six degrees-of-freedom subjective vertical conflict) model to estimate **motion sickness incidence (MSI)** in passengers engaged in a non-driving task with a lowered gaze. - Validation used data from five previously conducted real-world driving experiments; the same parameter set was tested and adjusted across these datasets. - Authors report that expected natural fluctuations in model-predicted MSI due to driving dynamic profiles, route characteristics, or driving style, as well as variability in experimentally determined MSI, are approximately **10%**. - Participants appear to have an individual MSI threshold that correlates with their susceptibility to motion sickness, but this threshold varied substantially across experiments and therefore is not robust for practical application. - The model can estimate motion sickness risk across different test tracks, but notable inaccuracies remain in the predicted MSI trajectories, indicating residual prediction errors despite parameter optimization. - The work underscores the potential for predictive MSI modeling to support intelligent-vehicle strategies (adaptive driving or route planning) aimed at reducing drive abortion due to motion sickness, while acknowledging current limitations. - The study is reported as a preprint and not peer reviewed; funding was provided by the German Federal Ministry of Education and Research (BMBF) with additional support from ZF Friedrichshafen AG; authors state funders had no involvement in study conduct or manuscript decisions.
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Strauss doi: https://doi.org/10.64898/2026.09.18.752352 This article is a preprint and has not been certified by peer review [[what does this mean?](https://www.biorxiv.org/about/FAQ#unrefereed)]. Benedikt Buchheit 1 Systems Neuroscience & Neurotechnology Unit, Saarland University, Faculty of Medicine; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Benedikt%2BBuchheit%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Buchheit%20B&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3ABenedikt%2BBuchheit%2B) * [ORCID record for Benedikt Buchheit](http://orcid.org/0000-0003-2303-8573 "Open in new tab") * For correspondence: benedikt.buchheit@uni-saarland.de Yannick Robin 1 Systems Neuroscience & Neurotechnology Unit, Saarland University, Faculty of Medicine; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Yannick%2BRobin%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Robin%20Y&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AYannick%2BRobin%2B) * [ORCID record for Yannick Robin](http://orcid.org/0000-0002-6558-6554 "Open in new tab") Elena Nadja Schneider 1 Systems Neuroscience & Neurotechnology Unit, Saarland University, Faculty of Medicine; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Elena%2BNadja%2BSchneider%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Schneider%20EN&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AElena%2BNadja%2BSchneider%2B) * [ORCID record for Elena Nadja Schneider](http://orcid.org/0000-0002-8902-7693 "Open in new tab") Mohamad Alayan 2 ZF Friedrichshafen AG * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Mohamad%2BAlayan%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Alayan%20M&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AMohamad%2BAlayan%2B) Daniel J. Strauss 1 Systems Neuroscience & Neurotechnology Unit, Saarland University, Faculty of Medicine; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Daniel%2BJ.%2BStrauss%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Strauss%20DJ&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3ADaniel%2BJ.%2BStrauss%2B) * [ORCID record for Daniel J. Strauss](http://orcid.org/0000-0001-8481-499X "Open in new tab") * [Abstract](https://www.biorxiv.org/content/10.64898/2026.09.18.752352v1)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_art/node:5799445/1) * [Info/History](https://www.biorxiv.org/content/10.64898/2026.09.18.752352v1.article-info)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_info/node:5799445/1) * [Metrics](https://www.biorxiv.org/content/10.64898/2026.09.18.752352v1.article-metrics)[](https://www.biorxiv.org/panels_ajax_tab/article_tab_metrics/node:5799445/1) * [ Preview PDF](https://www.biorxiv.org/content/10.64898/2026.09.18.752352v1.full.pdf+html)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_pdf/node:5799445/1) ![Loading](https://www.biorxiv.org/sites/all/modules/contrib/panels_ajax_tab/images/loading.gif) ## 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. ### Competing Interest Statement The research projects underlying this manuscript were funded by the German Federal Ministry of Research, Technology and Space (BMFTR) (previous known as Federal Ministry of Education and Research BMBF), with additional project funding provided by ZF Friedrichshafen AG, Friedrichshafen, Germany. The authors declare that the funding sources had no involvement in the study design, data analysis, interpretation of results, writing of the manuscript, or the decision to submit the article for publication. ## Funder Information Declared Federal Ministry of Education and Research, BMBF FZ 13FH737IX6, BMBF-FZ 13FH169KX0 Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a [CC-BY-ND 4.0 International license](http://creativecommons.org/licenses/by-nd/4.0/). bioRxiv and medRxiv thank the following for their generous financial support: > The Chan Zuckerberg Initiative, Cold Spring Harbor Laboratory, the Sergey Brin Family Foundation, California Institute of Technology, Centre National de la Recherche Scientifique, Fred Hutchinson Cancer Center, Imperial College London, Massachusetts Institute of Technology, Stanford University, The University of Edinburgh, University of Washington, and Vrije Universiteit Amsterdam. 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[ Download PDF](https://www.biorxiv.org/content/10.64898/2026.09.18.752352v1.full.pdf) Print/Save Options [Download PDF](https://www.biorxiv.org/content/biorxiv/early/2026/09/22/2026.09.18.752352.full.pdf)Full Text & In-line FiguresXML [More Info](https://www.biorxiv.org/about/FAQ#PrintOptions "More Information on Print/Save Options") [ Email](https://www.biorxiv.org/ "Email this Article") [ Share](https://www.biorxiv.org/) Impact of Driving Dynamic Fluctuations of 6DOF-SVC Model Predictions Across Five Real-World Driving Studies Benedikt Buchheit, Yannick Robin, Elena Nadja Schneider, Mohamad Alayan, Daniel J. Strauss bioRxiv 2026.09.18.752352; doi: https://doi.org/10.64898/2026.09.18.752352 This article is a preprint and has not been certified by peer review [[what does this mean?](https://www.biorxiv.org/about/FAQ#unrefereed)]. 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