Multiple models to estimate motion sickness (MS) have been proposed in the literature; however, few capture the influence of visual cues, limiting the models’ ability to predict MS that closely matches experimental MS data. This is especially significant in the presence of conflicts between visual and vestibular sensory signals. This paper provides an analysis of the gaps within existing MS estimation models and addresses these gaps by proposing the visual-vestibular motion sickness (VVMS) model. In this paper, the structure of the VVMS model, associated model parameters, and mathematical and physiological justification for selecting these parameters are presented. The VVMS model integrates vestibular sensory dynamics, visual motion perception, and visual-vestibular cue conflict to determine the conflict between the sensed and true vertical orientation of the passenger. The model performance is verified by comparing MS response output against experimentally determined motion sickness measures from past investigations.


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    Titel :

    A Visual-Vestibular Model to Predict Motion Sickness Response in Passengers of Autonomous Vehicles


    Weitere Titelangaben:

    Sae Int. J. Adv. and Curr. Prac. in Mobility


    Beteiligte:

    Kongress:

    SAE WCX Digital Summit ; 2021



    Erscheinungsdatum :

    06.04.2021


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch


    Schlagwörter :


    A Visual-Vestibular Model to Predict Motion Sickness Response in Passengers of Autonomous Vehicles

    Jalgaonkar, Nishant / Sousa Schulman, Daniel / Ojha, Sneha et al. | British Library Conference Proceedings | 2021


    Model to predict motion sickness within autonomous vehicles

    Salter, Spencer / Diels, Cyriel / Herriotts, Paul et al. | SAGE Publications | 2020


    MOTION SICKNESS DETECTION SYSTEM FOR AUTONOMOUS VEHICLES

    TARTZ ROBERT | Europäisches Patentamt | 2024

    Freier Zugriff

    Minimisation of Motion Sickness in Autonomous Vehicles

    Htike, Zaw / Papaioannou, Georgios / Siampis, Efstathios et al. | IEEE | 2020


    MOTION SICKNESS DETECTION SYSTEM FOR AUTONOMOUS VEHICLES

    TARTZ ROBERT | Europäisches Patentamt | 2022

    Freier Zugriff