Frequency Shaping-Based Control Framework for Reducing Motion Sickness in Autonomous Vehicles

Area of Science:

• Automotive Engineering
• Control Systems
• Human Factors

Background:

• Motion sickness is a significant challenge for passenger comfort in autonomous vehicles.
• Existing control strategies often do not adequately address motion sickness-inducing frequencies.
• Electric Autonomous Vehicles (EAVs) present unique control challenges for ride comfort.

Purpose of the Study:

• To introduce and evaluate a novel control strategy for reducing motion sickness in EAVs.
• To enhance overall ride comfort and passenger experience in autonomous driving.
• To maintain robust path-following performance while mitigating motion sickness.

Main Methods:

• Adaptive adjustment of look-ahead distance for lateral control based on Motion Sickness Dose Value (MSDV) analysis (ISO 2631-1).
• Application of Linear Quadratic Regulator (LQR) optimal control for longitudinal acceleration minimization.
• Implementation of a band-stop filter to attenuate motion-sickness-inducing frequencies in acceleration signals.

Main Results:

• Significant reduction in MSDV from 16.3 to 10.46, an improvement of up to 35.8%.
• Effective mitigation of lateral acceleration and its motion-sickness-related frequency components.
• Consistent lane adherence maintained throughout path-following tasks, despite a slight increase in lateral position error.

Conclusions:

• The proposed control strategy effectively reduces motion sickness in EAVs.
• The method offers a promising approach to enhance ride comfort without compromising essential driving performance.
• This research contributes to the development of more passenger-friendly autonomous vehicles.