  With the advancements in automated driving, there is concern that motion
sickness will increase as non-driving-related tasks increase. Therefore,
techniques to reduce motion sickness have drawn much attention. Research
studies have attempted to estimate motion sickness using computational models
for controlling it. Among them, a computational model for estimating motion
sickness incidence (MSI) with visual information as input based on subjective
vertical conflict theories was developed. In addition, some studies attempt to
mitigate motion sickness by controlling visual information. In particular, it
has been confirmed that motion sickness is suppressed by matching head movement
and visual information. However, there has been no research on optimal visual
information control that suppresses motion sickness in vehicles by utilizing
mathematical models. We, therefore, propose a method for generating optimal
visual information to suppress motion sickness caused from vehicle motion by
utilizing a motion sickness model with vestibular and visual inputs. To confirm
the effectiveness of the proposed method, we investigated changes in the motion
sickness experienced by the participants according to the visual information
displayed on the head-mounted display. The experimental results suggested that
the proposed method mitigates the motion sickness of the participants.
