A Visual-Vestibular Model to Predict Motion Sickness for Linear and Angular Motion

• Published in: Human factors Vol. 66; no. 8; pp. 2120 - 2137
• Main Authors: Sousa Schulman, Daniel, Jalgaonkar, Nishant, Ojha, Sneha, Rivero Valles, Ana, Jones, Monica L. H., Awtar, Shorya
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.08.2024; Human Factors and Ergonomics Society
• Subjects: Adult; Angular velocity; Automobile Driving; Driving conditions; Human motion; Humans; Male; Motion detection; Motion perception; Motion Perception - physiology; Motion sickness; Motion Sickness - physiopathology; Motion simulators; Passengers; Simulators; Three dimensional motion; Trends; Vestibular system; Vestibule, Labyrinth - physiology; Vestibule, Labyrinth - physiopathology; multisensory integration; perception-action; motion sickness; usability/acceptance measurement and research; simulation; autonomous driving
• ISSN: 0018-7208; 1547-8181; 1547-8181
• DOI: 10.1177/00187208231200721

Objective This study proposed a model to predict passenger motion sickness under the presence of a visual-vestibular conflict and assessed its performance with respect to previously recorded experimental data. Background While several models have been shown useful to predict motion sickness under repetitive motion, improvements are still desired in terms of predicting motion sickness in realistic driving conditions. There remains a need for a model that considers angular and linear visual-vestibular motion inputs in three dimensions to improve prediction of passenger motion sickness. Method The model combined the subjective vertical conflict theory and human motion perception models. The proposed model integrates visual and vestibular sensed 6 DoF motion signals in a novel architecture. Results Model prediction results were compared to motion sickness data obtained from studies conducted in motion simulators as well as on-road vehicle testing, yielding trends that are congruent with observed results in both cases. Conclusion The model demonstrated the ability to predict trends in motion sickness response for conditions in which a passenger performs a task on a handheld device versus facing forward looking ahead under realistic driving conditions. However, further analysis across a larger population is necessary to better assess the model’s performance. Application The proposed model can be used as a tool to predict motion sickness under different levels of visual-vestibular conflict. This can be leveraged to design interventions capable of mitigating passenger motion sickness. Further, this model can provide insights that aid in the development of passenger experiences inside autonomous vehicles.