Evaluation of Motion Sickness Prediction Models for Autonomous Driving

Abstract

The introduction of autonomous vehicles is expected to change the transportation system radically. One of the essential factors that affect the acceptance and choice of autonomous driving is passenger comfort. All people in the autonomous vehicle will be passengers and be able to perform non-driving tasks like reading etc. which increases the likelihood of motion sickness. This makes accurate estimation of motion sickness a necessity in the design stages of autonomous vehicles. The aim of this work is to review and apply two motion sickness prediction models (ISO-2631 and the 6D-SVC model) and evaluate their ability to capture individual motion sickness feelings using measured data and subjective assessment ratings from field tests. The comparison with the experimental results shows that the applied estimation models can be tuned to capture the individual motion sickness feelings. The results also show that habituation of motion sickness is an important property that needs to be taken into consideration and modelled.