Generation Method of Visual Information to Reduce Motion Sickness Based on its Computational Model

Yujiro Tamura･Takahiro Wada･Hailong Liu (NAIST)

We propose a method to reduce motion sickness in vehicle occupants by presenting visual motion cues. A model of motion sickness that takes into account head movements and visual information as inputs is utilized. Visual information that minimizes motion sickness when vehicle motion is given is generated, and presented to the occupants. Experimental results demonstrate that our proposed method reduces motion sickness.

Effect of Visual Information on Motion Sickness Mitigation

Yoshimi Kobayashi･Yuto Korogi･Akihito Kamiya (Toyota Motor)･Ryo Kodama･Nobushige Fujieda (Toyota Central R&D Labs.)

It is said that motion sickness occurs when there is a contradiction in the information obtained from multiple sensory organs. With the advancement of autonomous driving and driving assistance, an increase in motion sickness is perceived due to the driver becoming a passenger and an increase in subtasks. In this study, we aimed to alleviate motion sickness by abstractly representing vehicle motion information from the missing visual perspective, assuming video viewing inside the car. We will now report the results of this attempt.

Effect of Image Features on Visibility in Rear Vision by Camera Monitoring System (CMS)

Ryunosuke Kiyota･Riku Adachi (Keio University)･Seishi Takagi･Chiharu Sasaki･Kento Mera (Penstone)･Miwa Nakanishi (Keio University)

When replacing traditional rearview mirrors with Camera Monitoring Systems (CMS), it is known that the burden of focus transition from front to rear vision increases. However, processing the image on the monitor can potentially improve visibility, especially in rainy or nighttime conditions. This study aims to identify the image processing conditions that minimize focus transition burden and optimize visibility, through ergonomic experiments.