Abstract

When driving becomes fully automated, media browsing and PC work in the car are expected to increase, which is likely to cause car sickness. In this study, we investigated a method to assess car sickness objectively and quantitatively by inducing sickness with a driving simulator (DS) and examining the changes in physiological indices with low-burden measurement devices. Ten participants were asked to ride DS and read a book there, and subjective ratings of sickness and drowsiness, electrocardiogram, respiration, and skin conductance were obtained. Experiments were conducted under two conditions: with sinusoidal vibration at a roll angle of 0.2 Hz (A) and without vibration (B). Nine out of ten participants experienced mild subjective sickness, although no statistically significant differences between conditions were obtained. The principal component analysis on physiological indices was conducted on seven participants across conditions; two were excluded due to arrhythmia and one was due to no sickness. In addition, skin conductance was excluded from the analysis because of measurement deficits. As a result, the first component related to respiratory instability was commonly obtained in all, and the principal component loadings were similar for all but one of the participants. This component increased with moderate sickness and drowsiness. The second component was related to mean heart rate and heart rate variability. Not only there were large individual differences in the loading patterns of this component and its principal component scores showed complex changes depending on the degree of sickness and drowsiness. Thus, although the process of sickness is complex and differs among individuals, the combination of changes in these two principal components may be used to assess the process. Further studies with a larger number of participants are needed to develop a method to assess sickness and drowsiness separately and to address individual differences.

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