Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle

Abstract

In terms of vehicle dynamics, motion sickness (MS) occurs because of the large lateral acceleration produced by inappropriate wheel turning. In terms of passenger behavior, subjects experience MS because they normally tilt their heads towards the direction of lateral acceleration. Relating these viewpoints, the increment of MS originates from the large lateral acceleration produced by the inappropriate wheel’s turn, which then causes greater head movement with respect to the lateral acceleration direction. Therefore, this study proposes the utilization of fuzzy-proportional integral derivative (PID) controller for an MS minimization control structure, where the interaction of the lateral acceleration and head tilt concept is adopted to diminish the lateral acceleration. Here, the head movement is used as the controlled variable to compute the corrective wheel angle. The estimation of the head movement is carried out by an estimation model developed by the radial basis function neural network (RBFNN) method. An experiment involving a driving simulator was conducted, to verify the proposed control system’s performance in regard to the autonomous vehicle’s passengers. The results show that the averages of motion sickness incidence (MSI) index can be lowered by 3.95% for single lap and 11.49% for ten laps.

The Braking-Pressure and Driving-Direction Determination System (BDDS) Using Road Roughness and Passenger Conditions of Surrounding Vehicles

“…Sarah Atifah Saruchi et al proposed the utilization of a fuzzy-proportional integral derivative (PID) controller for a motion sickness (MS) minimization control structure. In this study, the interaction of the lateral acceleration and head tilt concept was adopted to diminish the lateral acceleration [7]. This study aimed to minimize motion sickness through the controller of an autonomous vehicle.…”

Proceedings of the Resource Efficient Vehicles Conference - 2021 (rev2021)

“…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.…”

“…Being a pilot study, 10 participants each were chosen from the public to test the two platforms. They were then grouped in age ranges of [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55] and 56-70 years to ensure a balanced and diverse range of responses. Participants were screened for inclusion criteria including driver license status and motion sickness.…”

Effectiveness of a Head Movement Interface for Steering a Vehicle in a Virtual Reality Driving Simulation

“…Tanaka et al [19] studied an optimal value search system that efficiently calculates the angular velocity and viewing angle that limit VR sickness without affecting the sense of presence. In addition, there have been studies on motion sickness when vehicles are travelling [20]. It is known that passengers need to reduce the tilting angle of their head towards the lateral acceleration direction to help relieve the symptoms.…”