EEG-based evaluation of motion sickness and reducing sensory conflict in a simulated autonomous driving environment.

Abstract

Autonomous driving offers significant potential for changes in the automotive industry. However, sensory conflict during autonomous driving can lead to motion sickness. Quantitative evaluation and effective preventions to predict and reduce motion sickness are needed. The goal of this study is to verify the objective indicator of motion sickness level based on encephalography (EEG) that we proposed before and investigate the influence of attenuating sensory conflict on motion sickness. A 6-degree of freedom (DOF) driving simulator platform was used to provide an autonomous driving environment to the subjects, and the subjective motion sickness level (MSL), as well as the EEG signals of 15 healthy subjects, were collected simultaneously during 3 conditions, i) autonomous driving, ii) autonomous driving with eyes blindfolded and iii) active driving. The MSLs were reported by the subjects every two minutes, providing a reference to the recorded EEG signals. The EEG signals were analyzed and compared among different conditions. Average MSLs were higher in autonomous driving than in autonomous driving with eyes blindfolded and active driving, together with the increase of the mean EEG frequency of theta band in the central, parietal and occipital areas (FC5, Cz, CP5, P3, and POz). These findings validated that EEG mean frequency of theta band could be an indicator of motion sickness, besides an attenuated visual input or active control of the vehicle can effectively reduce the generation of motion sickness.