Minimizing Motion Sickness In Autonomous Vehicles; A Hybrid Approach

The present study investigates different control strategies with various controllers such as; (1) The traditional Proportional-Integral-Derivative (PID) controllers , (2) Fuzzy Logic controllers (FLC) and (3) the use of Model Predictive Controller (MPC) to mitigate motion sickness of passengers by maximizing handling comfort and minimizing motion sickness and postural instability. The study draws an ideal path using a 3-pt NURBS curve over a reference track, that is designed considering various components of motion sickness (motion sickness thresholds). The effects on motion sickness reduction, using various control strategies with the mentioned controllers are then studied by numerically comparing results in terms of Fast Fourier Transform (FFT) of the frequency spectrum of steering angles, Motion sickness Dosage Value (MSDV) of the vehicle's lateral acceleration and Motion Sickness Incidence (MSI) of the head tilt angles of the passengers during the cornering maneuver. Consequently, the findings are used to propose potential guidelines for design of new infrastructure which are specifically built for an autonomous transportation future.