Driver gaze model for motion cueing yaw feedback optimisation

Driving simulators are increasingly important in vehicle development, benefiting from hardware and motion cueing algorithm (MCA) advancements. However, current state-of-the-art MCAs are optimising with regards to a vehicle fixed vestibular system, ignoring active and passive head movements during manoeuvres. Research shows that drivers actively move their heads to focus their gaze and passively stabilising it during involuntary trunk movements, resulting in significant differences between vehicle and head yaw angles. Humans isolate trunk and head movement in the range of 0.1-1.0 Hz, suggesting neck-driven gaze stabilisation. This behaviour is not accounted for in current MCAs, warranting an investigation. This study develops a driver gaze model to enhance motion cueing strategies and compares it to existing methods. Findings indicate significant discrepancies between vehicle and estimated head yaw rate in winter testing with high slip angles, and that omitting vestibular models and separating the slip angle in the yaw feedback improves the motion cueing with regards to induced head movements. Further, the results shows that there is a clear relationship between motion cueing, visual feedback, and induced driver head movement. In conclusion, driver gaze models can improve motion cueing strategies in driving simulators, and thus the study highlights the need for considering driver gaze behaviour and provides insights for tuning and optimising MCAs.
QC 20240521