Mitigating Motion Sickness with Optimization-based Motion Planning

The acceptance of automated driving is under the potential threat motion sickness. It hinders passengers' willingness to perform secondary activities. In order mitigate sickness in vehicles, we propose an optimization-based planning algorithm that minimizes distribution acceleration energy within frequency range found be most nauseogenic. formulated into integral and receding-horizon variants compared with a commonly used alternative approach aiming minimize accelerations general. proposed can reduce frequency-weighted by up 11.3% not considering sensitivity for price reduced overall comfort. Our simulation studies also reveal loss performance over when varying preview time nominal sampling time. computation planner around or below real-time threshold using longer but without causing significant loss. We present results experiments conducted measure human drivers on public road section simulated scenario actually based on. method achieve 19% improvement general comfort 32% reduction squared dose value best-performing participant. demonstrate considerable improving mitigating our vehicles.