Personalizing motion sickness models: estimation and statistical modeling of individual-specific parameters.

ABSTRACT: As users transition from drivers to passengers in automated vehicles, they often take their eyes off the road to engage in non-driving activities. In driving simulators, visual motion is presented with scaled or without physical motion, leading to a mismatch between expected and perceived motion. Both conditions elicit motion sickness, calling for enhanced vehicle and simulator motion control strategies. Given the large differences in sickness susceptibility between individuals, effective countermeasures must address this at a personal level. This paper combines a group-averaged sensory conflict model with an individualized Accumulation Model (AM) to capture individual differences in motion sickness susceptibility across various conditions. The feasibility of this framework is verified usi

SUBMITTER: Kotian V 

PROVIDER: S-EPMC12206751 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature