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Fundamentals of Motion Planning for Mitigating Motion Sickness in Automated Vehicles.
- Source :
- IEEE Transactions on Vehicular Technology; Mar2022, Vol. 71 Issue 3, p2375-2384, 10p
- Publication Year :
- 2022
-
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 trade-off 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- MOTION sickness
AUTONOMOUS vehicles
MOTOR vehicle driving
Subjects
Details
- Language :
- English
- ISSN :
- 00189545
- Volume :
- 71
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Vehicular Technology
- Publication Type :
- Academic Journal
- Accession number :
- 155866873
- Full Text :
- https://doi.org/10.1109/TVT.2021.3138722