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A Review of Carsickness Mitigation: Navigating Challenges and Exploiting Opportunities in the Era of Intelligent Vehicles

Daofei Li, Tingzhe Yu, Binbin Tang

TL;DR

The paper reviews motion sickness (MS) in intelligent vehicles, addressing the driver–passenger transition and new EV dynamics as drivers of MS. It synthesizes two core theories, subjective and objective MS quantification methods, and countermeasures across passenger adjustments, intelligent vehicle capabilities, and motion cues, framing an integrated framework for MS mitigation. Core contributions include detailing mechanistic models such as $SVC$ and $6DOF-SVC$, highlighting metrics like $MSDV$ and $MSI$, and outlining a holistic architecture that combines global/local planning, vehicle control, smart cockpit interventions, and personalized cueing. The work identifies key gaps—lack of standard MS quantification, limited real‑road validation, and high hardware costs—and articulates practical opportunities for next‑generation autonomous EVs to deliver smoother, MS‑resilient travel through data‑driven personalization and multi‑modal countermeasures.

Abstract

Motion sickness (MS) has long been a common complaint in road transportation. However, in the era of driving automation, MS has become an increasingly significant issue. The future intelligent vehicle is envisioned as a mobile space for work or entertainment, but unfortunately passengers' engagement in non-driving tasks may exacerbate MS. Finding effective MS countermeasures is crucial to ensure a pleasant passenger experience. Nevertheless, due to the complex mechanism of MS, there are numerous challenges in mitigating it, hindering the development of practical countermeasures. To address this, we first review two prevalent theories explaining the mechanism of MS. Subsequently, this paper provides a summary of current subjective and objective approaches for quantifying motion sickness levels. Then, it surveys existing methods for alleviating MS, including passenger adjustment, intelligent vehicle solutions, and motion cues of various modalities. Furthermore, we outline the limitations and remaining challenges of current research and highlight novel opportunities in the context of intelligent vehicles. Finally, we propose an integrated framework for alleviating MS. The findings of this review will enhance our understanding of carsickness and offer valuable insights for future research and practice in MS mitigation within modern vehicles.

A Review of Carsickness Mitigation: Navigating Challenges and Exploiting Opportunities in the Era of Intelligent Vehicles

TL;DR

The paper reviews motion sickness (MS) in intelligent vehicles, addressing the driver–passenger transition and new EV dynamics as drivers of MS. It synthesizes two core theories, subjective and objective MS quantification methods, and countermeasures across passenger adjustments, intelligent vehicle capabilities, and motion cues, framing an integrated framework for MS mitigation. Core contributions include detailing mechanistic models such as and , highlighting metrics like and , and outlining a holistic architecture that combines global/local planning, vehicle control, smart cockpit interventions, and personalized cueing. The work identifies key gaps—lack of standard MS quantification, limited real‑road validation, and high hardware costs—and articulates practical opportunities for next‑generation autonomous EVs to deliver smoother, MS‑resilient travel through data‑driven personalization and multi‑modal countermeasures.

Abstract

Motion sickness (MS) has long been a common complaint in road transportation. However, in the era of driving automation, MS has become an increasingly significant issue. The future intelligent vehicle is envisioned as a mobile space for work or entertainment, but unfortunately passengers' engagement in non-driving tasks may exacerbate MS. Finding effective MS countermeasures is crucial to ensure a pleasant passenger experience. Nevertheless, due to the complex mechanism of MS, there are numerous challenges in mitigating it, hindering the development of practical countermeasures. To address this, we first review two prevalent theories explaining the mechanism of MS. Subsequently, this paper provides a summary of current subjective and objective approaches for quantifying motion sickness levels. Then, it surveys existing methods for alleviating MS, including passenger adjustment, intelligent vehicle solutions, and motion cues of various modalities. Furthermore, we outline the limitations and remaining challenges of current research and highlight novel opportunities in the context of intelligent vehicles. Finally, we propose an integrated framework for alleviating MS. The findings of this review will enhance our understanding of carsickness and offer valuable insights for future research and practice in MS mitigation within modern vehicles.
Paper Structure (36 sections, 2 equations, 5 figures, 5 tables)

This paper contains 36 sections, 2 equations, 5 figures, 5 tables.

Table of Contents

  1. Introduction
  2. Theories of motion sickness
  3. Sensory conflict theory
  4. Postural instability theory
  5. Summary
  6. Quantifying motion sickness
  7. Subjective methods
  8. Quantification of MS susceptibility
  9. Quantification of MS status
  10. Objective methods
  11. MSDV
  12. EGG
  13. ECG
  14. EDA
  15. EEG
  16. ...and 21 more sections

Figures (5)

  • Figure 1: Statistics of MS quantification methods (number of use count).
  • Figure 2: MS quantification in experiment: MS susceptibility and sickness level.
  • Figure 3: The evoking and mitigating of motion sickness (upper: stimulation side, lower: human side).
  • Figure 4: Example motion cues for MS mitigation
  • Figure 5: A carsickness mitigation framework for an intelligent vehicle.