Fundamentals of Motion Planning for Mitigating Motion Sickness in Automated Vehicles

Abstract

This paper investigates the fundamentals of motion planning for minimizing motion sickness in transportation systems of higher automation levels. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one within specific and given boundaries and constraints in order to minimize the motion sickness and the journey time. An empirical approach based on British standard is used to evaluate motion sickness. The tradeoff between minimizing motion sickness and journey time is investigated through multi-objective optimization by altering the weighting factors. The correlation between sickness and journey time is represented as a Pareto front because of their conflicting relation. The compromise between the two components is quantified along the curve, while the severity of the sickness is determined using frequency analysis. In addition, three case studies are developed to investigate the effect of driving style, vehicle speed, and road width, which can be considered among the main factors affecting motion sickness. According to the results, the driving style has higher impact on both motion sickness and journey time compared to the vehicle speed and the road width. The benefit of higher vehicle speed gives shorter journey time while maintaining relatively lower illness rating compared with lower vehicle speed. The effect of the road width is negligible on both sickness and journey time when travelling on a longer road.The results pave the path for the development of vehicular technologies to implement for real-world driving from the outcomes of this paper.

Optimal Trajectory Planning for Mitigated Motion Sickness: Simulator Study Assessment

“…For the selected weight settings, the MSDV for the journey reduced by 53% with the proposed MSM algorithm. This aligns with the projections made in the literature [22], [23], as expected due to the presence of MSDV in the cost function. According to Figure 4 as the weight ratio w m /w t is increased, the MSDV through the journey reduces.…”

“…The model only considered longitudinal jerk as the input, the lateral accelerations were calculated using longitudinal velocity and road curvature. Similarly, an optimal velocity profiling architecture using optimal control-oriented methods is proposed using Motion Sickness Dose Value (MSDV) as a cost function for minimisation [23]. Such an approach allowed deviation of the vehicle from the predefined path and showed substantial MSDV reduction when more lateral deviation is allowed.…”

Integrated Active Seat Suspension for Enhancing Motion Comfort

“…Then, the fitted curves of the ones with higher R 2 are presented ). In ND, SA metrics are more correlated with MS rather than RC, which might be because the driving behaviour is proven to affect more the low frequencies that are related to MS [23]. At the same time, there is principally no correlation of SA metrics with MS in RD, except from SA31 and SA32 both related with drivers' confidence and control.…”

Mitigating Motion Sickness with Optimization-based Motion Planning

“…Some recent works paid more attention to mitigating motion sickness by considering the frequency sensitivity discussed above. Explicit minimization of MSDV in addition to travel time has been explored in [28], where the vehicle motion is formulated in curvilinear coordinates and details were provided on the distribution of acceleration energy in the frequency domain and on the trade-off between comfort and travel time [28]. An alternative approach to the problem was proposed using a time-domain planning algorithm by including a second-order high-pass filter in the objective function [29].…”