Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle
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 vie...
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| Format: | Article |
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MDPI AG
2020-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/14/4769 |
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| author | Sarah ‘Atifah Saruchi Mohd Hatta Mohammed Ariff Hairi Zamzuri Noor Hafizah Amer Nurbaiti Wahid Nurhaffizah Hassan Khairil Anwar Abu Kassim |
| author_facet | Sarah ‘Atifah Saruchi Mohd Hatta Mohammed Ariff Hairi Zamzuri Noor Hafizah Amer Nurbaiti Wahid Nurhaffizah Hassan Khairil Anwar Abu Kassim |
| author_sort | Sarah ‘Atifah Saruchi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T18:32:11Z |
| format | Article |
| id | doaj.art-045f0ec23255467d9e260b43fb97026d |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T18:32:11Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-045f0ec23255467d9e260b43fb97026d2023-11-20T06:28:43ZengMDPI AGApplied Sciences2076-34172020-07-011014476910.3390/app10144769Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous VehicleSarah ‘Atifah Saruchi0Mohd Hatta Mohammed Ariff1Hairi Zamzuri2Noor Hafizah Amer3Nurbaiti Wahid4Nurhaffizah Hassan5Khairil Anwar Abu Kassim6MalaysiaJapan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur 54100, MalaysiaMalaysiaJapan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur 54100, MalaysiaMalaysiaJapan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur 54100, MalaysiaFaculty of Engineering, Universiti Pertahanan Nasional Malaysia, Kuala Lumpur 57000, MalaysiaFaculty of Electrical Engineering, Universiti Teknologi MARA, Dungun 23000, MalaysiaFaculty of Electrical Engineering, Universiti Teknologi MARA, Dungun 23000, MalaysiaMalaysian Institute of Road Safety Research (MIROS), Kajang 43000, MalaysiaIn 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.https://www.mdpi.com/2076-3417/10/14/4769autonomous vehiclefuzzy-PIDhead roll anglelateral accelerationmotion sickness minimizationradial basis function neural network |
| spellingShingle | Sarah ‘Atifah Saruchi Mohd Hatta Mohammed Ariff Hairi Zamzuri Noor Hafizah Amer Nurbaiti Wahid Nurhaffizah Hassan Khairil Anwar Abu Kassim Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle Applied Sciences autonomous vehicle fuzzy-PID head roll angle lateral acceleration motion sickness minimization radial basis function neural network |
| title | Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle |
| title_full | Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle |
| title_fullStr | Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle |
| title_full_unstemmed | Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle |
| title_short | Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle |
| title_sort | novel motion sickness minimization control via fuzzy pid controller for autonomous vehicle |
| topic | autonomous vehicle fuzzy-PID head roll angle lateral acceleration motion sickness minimization radial basis function neural network |
| url | https://www.mdpi.com/2076-3417/10/14/4769 |
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