Abstract

Motion sickness can occur in environments where new technologies, such as electric vehicles, are applied. Since motion sickness impedes user experience and the adoption of these technologies, accurate prediction is essential. This necessitates precise measurement of motion sickness variations across different environments to improve predictive model accuracy. However, current questionnaires lack detailed temporal and symptom-specific information, failing to provide accurate real-time data. To address this, we introduce the Real-Time Motion Sickness Scale (RMS), a practical tool designed for continuous monitoring of significant motion sickness symptoms. The RMS was developed by enhancing existing questionnaires through a systematic literature review and pilot tests. We validated its feasibility through a real-driving experiment with 24 passengers in an electric vehicle. The results demonstrated that the RMS accurately describes motion sickness severity and captures real-time changes in detail. Based on these findings, we discuss the applications of the RMS in motion sickness-provocative environments.