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Analyzing Motion Sickness Level in Autonomous Vehicles According to Look-Ahead Distance

dc.contributor.authorZengin, Namik
dc.contributor.authorSever, Mert
dc.contributor.authorKirli, Ahmet
dc.contributor.authorArslan, M. Selcuk
dc.date.accessioned2026-06-27T14:16:38Z
dc.date.issued2018
dc.description.abstractIn this study, the motion sickness level (defined in the ISO standards) for autonomous vehicles is analyzed as a function of the look-ahead distance. A standard linearized vehicle model is used to design linear quadratic regulators (LQR) for the automated steering. The dynamics of the otolith organ of the human vestibular system is integrated to the linearized control oriented model. This integration enabled to evaluate the motion sickness level with an H-2 norm performance index. Several automated steering controllers are designed with the same performance indices for various vehicle speeds and various look-ahead distance values. The H-2 norm of the motion sickness dose values (MSDV) of each controller are used to demonstrate the effect of the look-ahead distance on the motion sickness level. A 3 degrees-of-freedom nonlinear vehicle model with yaw plane dynamics and the semi-empirical Magic Formula tire model is used for the simulation studies by which the analytical results, obtained by linear analysis, are validated.en
dc.identifier.isbn978-1-5386-7641-7
dc.identifier.urihttps://hdl.handle.net/20.500.14981/58706
dc.identifier.wos000491282100059
dc.language.isoeng
dc.publisherIEEE
dc.relation.conference6th International Conference on Control Engineering and Information Technology (CEIT)
dc.relation.ispartof2018 6TH INTERNATIONAL CONFERENCE ON CONTROL ENGINEERING & INFORMATION TECHNOLOGY (CEIT)
dc.subjectReliability
dc.subjectautonomous vehicles
dc.subjectmotion sickness
dc.subjectlook-ahead distance
dc.subjectH-2 norm
dc.subjectAutomation & Control Systems
dc.subjectComputer Science
dc.subjectEngineering
dc.titleAnalyzing Motion Sickness Level in Autonomous Vehicles According to Look-Ahead Distance
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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