2020
DOI: 10.1177/0954407020943316
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Abstract: It is anticipated that passengers in autonomous vehicles will be more occupied with in-vehicle activities. Loss of the authority on driving and engaging in non-driving tasks could cause lower predictability of car motions. This decrease in predictability is expected to increase the sensitivity to carsickness. It appears that it is crucial to develop controllers for autonomous driving with the capability of improving passenger comfort by reducing carsickness. In this regard, it can be asked how the motion varia… Show more

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Cited by 6 publications
(4 citation statements)
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References 39 publications
(87 reference statements)
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“…People and the market will not accept a driverless vehicle with strange manoeuvres or uncomfortable handling. Following the intuitions of people and reducing carsickness when driving could help improve occupants’ comfort, 7 therefore, the characteristics of human drivers when driving on a road should be considered. 8 Each driver’s driving habits vary from person to person, and driving behaviour mainly includes acceleration, braking operations and steering wheel turning according to the surrounding environment’s information.…”
Section: Introductionmentioning
confidence: 99%
“…People and the market will not accept a driverless vehicle with strange manoeuvres or uncomfortable handling. Following the intuitions of people and reducing carsickness when driving could help improve occupants’ comfort, 7 therefore, the characteristics of human drivers when driving on a road should be considered. 8 Each driver’s driving habits vary from person to person, and driving behaviour mainly includes acceleration, braking operations and steering wheel turning according to the surrounding environment’s information.…”
Section: Introductionmentioning
confidence: 99%
“…Recent publications focusing on finding the optimal solution of path tracking algorithms to minimise motion sickness are for example [40], [41] and [42]. Zengin et al [40] have proposed an augmented road-vehicle model with a vestibular system model to investigate the effect of look-ahead distance for path tracking algorithms.…”
Section: Trajectory Planning and Tracking Algorithms Considering Ride Comfortmentioning
confidence: 99%
“…Zengin et al [40] have proposed an augmented road-vehicle model with a vestibular system model to investigate the effect of look-ahead distance for path tracking algorithms. Sever et al [41] proposed to tune a gain-scheduled LQR based path following controller to reduce the motion sickness dose value defined in ISO 2631-1 also integrating the dynamics of the human vestibular system similar to Zengin et al [40]. A fuzzy-PID based path tracking algorithm is proposed by Saruchi et al [43] that is controlling the wheel angle to reduce the lateral acceleration and the roll angle of the head of the driver and the passengers aiming for reducing motion sickness incidence which is calculated with the help of using the 6-DOF SVC model.…”
Section: Trajectory Planning and Tracking Algorithms Considering Ride Comfortmentioning
confidence: 99%
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