Effect of frequency shaping cost on trajectory planner for mitigation of motion sickness

Motion sickness (MS) remains a significant challenge in deploying autonomous vehicles, impacting passenger comfort, safety, and overall user acceptance. We investigate the impact of frequency shaping costs to mitigate motion sickness in autonomous vehicles into the vehicle’s control algorithm. Building upon existing research on MS evaluation and mitigation strategies, we develop a computational model that incorporates the frequency characteristics of vehicle motion and their impact on passenger comfort. To enhance passenger comfort in autonomous vehicles, this work proposes an optimal control framework that shapes vehicle control inputs to suppress motion sickness (MS)-inducing frequencies. The effectiveness of the proposed approach is evaluated across multiple road profiles by comparing the different cost formulations in terms of their ability to attenuate MS within the motion sickness sensitive frequency band and to consistently reduce established MS metrics. Simulation results demonstrate a significant reduction in motion sickness severity compared to other cost functions. The validity of the MS cost function is confirmed through cross-verification using multiple MS metrics. Practical implications and potential challenges of deploying frequency-shaped cost functions in real-world autonomous vehicle control systems are also addressed. Overall, this research contributes to the ongoing efforts to improve passenger well-being and acceptance of autonomous transportation technologies.