Motion Sickness Prediction Device for Automated Vehicles

Spencer Salter, Doug Thake, Stratis Kanarachos, Cyriel Diels

Research output: Contribution to journalArticlepeer-review

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Abstract—Motion sickness is a persistent problem in many forms of transport. It affects most of the population, is debilitating for the sufferer and can disrupt the journey for the rest. Automated Vehicles (AV’s) offer greater flexibility in cabin design particularly in the future where no physical controls are required. This poses additional risks to passenger well being with increased levels of motion sickness when passengers and historical drivers are multi-tasking. This study demonstrates a device that can predict real time occupant motion sickness based on motion, head tilt and ambient conditions. Recovery is also considered for multiple journeys. The device can be easily modified to reflect an individual’s susceptibility or use group settings for the general population.
Original languageEnglish
Article numberIA-ICMAELNDN-07118-10117
Pages (from-to)68-74
Number of pages16
JournalInternational Journal of Mechanical and Production Engineering
Issue number2
Publication statusPublished - 21 May 2019

Bibliographical note

The IJMPE is a peer-reviewed open access journal


  • automated vehicles
  • Motion sickness
  • prediction
  • wellbeing


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