Data underlying the publication: Visually Induced Motion Sickness Correlates with On-Road Car Sickness while Performing a Visual Task

Abstract—Previous literature suggests that the motion sickness susceptibility questionnaire (MSSQ) is inadequate for prediction of motion sickness under naturalistic driving conditions. In this study, we investigated whether visually induced motion sickness using a virtual reality head-set could be used as a quick and reliable way to predict participant susceptibility. We recruited 22 participants to complete a two-part experiment. In randomised order, we determined their susceptibility to visual motion sickness and their susceptibility to car sickness. To determine visual susceptibility, the visual scene was sequentially rotated at constant velocity around an earth-vertical yaw axis and rolled about the nasiooccipital axis, in 30 s intervals. Car sickness, on the other hand, was elicited under completely naturalistic conditions, being driven in the back-seat of a car in the city of Delft, performing a visual task on a laptop. Sickness ratings were collected at regular intervals in both parts of the experiment.We found that the frequencies excited by naturalistic driving are very low, which has important consequences for motion sickness modelling and mitigation in automated vehicles.We found that individual car sickness correlated positively with visual motion sickness. This indicates that both are influenced by a common sickness susceptibility factor. Car sickness correlated similarly with visual motion sickness and MSSQ. Overall, our results indicate that combining measurements of sickness responses to a visual stimulus and MSSQ can yield a reliable method for determining individual sickness susceptibility. To this end the visual stimulus and the weighting with MSSQ responses can be refined using a much larger sample and considering additional visual conditions in driving.

摘要—既往研究表明，晕动病易感性问卷（motion sickness susceptibility questionnaire, MSSQ）无法有效预测自然驾驶场景下的晕动病。本研究旨在探究：采用虚拟现实头显（virtual reality head-set）诱发的视觉性晕动病，能否作为一种快速且可靠的个体晕动易感性预测手段。我们招募了22名受试者完成两阶段实验，实验顺序采用随机化设计，分别测定受试者的视觉性晕动病易感性与乘车晕动病易感性。为测定视觉易感性，我们以恒定速度依次旋转视觉场景：绕地球垂直偏航轴旋转、沿鼻枕轴滚转，每30秒循环一次。而乘车晕动病则在完全自然的场景下诱发：受试者乘坐位于代尔夫特市城区的轿车后座，并在笔记本电脑上完成一项视觉任务。实验两个阶段均定期收集晕动病评分数据。我们发现，自然驾驶场景下诱发晕动病的刺激频率极低，这对自动驾驶车辆的晕动病建模与缓解策略具有重要指导意义。此外，个体乘车晕动病易感性与视觉性晕动病易感性呈正相关，提示二者受共同的晕动易感性因素影响；且乘车晕动病易感性与视觉性晕动病、MSSQ的相关性程度相近。总体而言，本研究结果表明，结合视觉刺激诱发的晕动反应与MSSQ评分，可构建可靠的个体晕动易感性测定方法。未来可通过扩大样本量、纳入更多驾驶相关视觉场景，对该视觉刺激方案及与MSSQ的权重分配进行优化。