Progress in road vehicle automation is tainted by an increased occurrence of passenger motion sickness. Yet, these advances drive the design of car cockpits towards user-centric approaches, such as monitoring passenger well-being. In this framework, the present study aimed to identify robust predictors of motion sickness severity based on data from two experimental studies reproducing a stop-and-go passenger ride. The data from 54 participants tested in a total of 106 identical sessions involving gaze restriction to a visuomotor activity were analysed. Individual characteristics, contextual, behavioural, and physiological parameters were investigated in relation to motion sickness severity. Individual susceptibility had the strongest influence. Pulse rate and the amplitude range of pitch movements of the head additionally exhibited a significant relationship with the progression of symptoms. Such findings open new perspectives for the development of passenger-centric methods to screen early stages of motion sickness and prevent its escalation.
Emond et al. (2026) studied this question.