Virtual Reality Digitization of Driving Learning Simulators: Optimization via Fuzzy Compensation.
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| Title: | Virtual Reality Digitization of Driving Learning Simulators: Optimization via Fuzzy Compensation. |
|---|---|
| Authors: | Wang, Shuai1, Cui, Bingsheng2 18047071182@163.com |
| Source: | Jordan Journal of Mechanical & Industrial Engineering. Apr2026, Vol. 20 Issue 2, p293-306. 14p. |
| Subjects: | Automobile driving simulators, Fuzzy algorithms, Motion sickness, Mathematical optimization, Algorithms, Virtual reality, Motion perception (Vision) |
| Abstract (English): | Virtual reality technology has significant potential in enhancing the realism and interactivity of driving simulators. However, traditional simulators often have problems such as motion perception distortion and high hardware requirements. To address the above issues, a VR digitalization method for driving simulators based on a washout algorithm optimized by fuzzy compensation is proposed. By integrating a fuzzy controller, it dynamically adjusts the filter parameters and gain weights within the framework of the washing algorithm, thereby enhancing the fidelity of motion prompts and reducing perceptual conflicts. The experimental results show that when the banquet method is subjected to an instantaneous acceleration of 1.7 G on a rough road surface, the output position error is only 12.7 mm, the acceleration accuracy reaches 99.7% under a vertical resultant force of 0.5kN, and the maximum processor occupancy rate during operation is only 58%. The above results indicate that this method not only enhances the realism of the simulation but also maintains low computational and hardware requirements, and effectively alleviates motion sickness in the simulator through adaptive motion perception adjustment. [ABSTRACT FROM AUTHOR] |
| Abstract (Arabic): | يركز المقال على تطوير وتقييم تقنية رقمية للواقع الافتراضي (الواقع الافتراضي) لمحاكيات تعلم القيادة، والتي تدمج خوارزمية غسل محسّنة بواسطة تعويض ضبابي لتعزيز واقعية الحركة وتقليل دوار المحاكاة. تقوم خوارزمية الغسل بمحاكاة الإدراك الدهليزي البشري من خلال ترشيح إشارات الحركة، بينما يقوم المتحكم الضبابي بضبط معلمات المرشح وأوزان الكسب بشكل ديناميكي في الوقت الحقيقي لمعالجة تقلبات الإدخال غير الخطية وقيود المنصة. تُظهر النتائج التجريبية أن هذه الطريقة تحقق أخطاء أقل في الموضع والوضعية، ودقة أعلى في التسارع، وتقليل زمن استجابة الجهاز (بمتوسط 5.3 مللي ثانية)، وانخفاض في احتلال المعالج (بحد أقصى 58%) مقارنةً بأساليب المحاكاة التقليدية القائمة على التحجيم غير الخطي والمحاكاة الحسية للتسارع، مع الحفاظ على استهلاك طاقة أقل. أظهرت اختبارات التطبيق مع طلاب القيادة تحسناً في نتائج التعلم باستخدام محاكي الواقع الافتراضي المقترح. وتقترح الدراسة أعمالاً مستقبلية لدمج التعلم التكيفي لقواعد الضبابي والتكامل مع نماذج ديناميكيات المركبات لتعزيز استقرار النظام وواقعيته بشكل أكبر. [Extracted from the article] |
| Copyright of Jordan Journal of Mechanical & Industrial Engineering is the property of Hashemite University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 194591607 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Virtual Reality Digitization of Driving Learning Simulators: Optimization via Fuzzy Compensation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Shuai%22">Wang, Shuai</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Cui%2C+Bingsheng%22">Cui, Bingsheng</searchLink><relatesTo>2</relatesTo><i> 18047071182@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Jordan+Journal+of+Mechanical+%26+Industrial+Engineering%22">Jordan Journal of Mechanical & Industrial Engineering</searchLink>. Apr2026, Vol. 20 Issue 2, p293-306. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Automobile+driving+simulators%22">Automobile driving simulators</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+algorithms%22">Fuzzy algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Motion+sickness%22">Motion sickness</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Virtual+reality%22">Virtual reality</searchLink><br /><searchLink fieldCode="DE" term="%22Motion+perception+%28Vision%29%22">Motion perception (Vision)</searchLink> – Name: Abstract Label: Abstract (English) Group: Ab Data: Virtual reality technology has significant potential in enhancing the realism and interactivity of driving simulators. However, traditional simulators often have problems such as motion perception distortion and high hardware requirements. To address the above issues, a VR digitalization method for driving simulators based on a washout algorithm optimized by fuzzy compensation is proposed. By integrating a fuzzy controller, it dynamically adjusts the filter parameters and gain weights within the framework of the washing algorithm, thereby enhancing the fidelity of motion prompts and reducing perceptual conflicts. The experimental results show that when the banquet method is subjected to an instantaneous acceleration of 1.7 G on a rough road surface, the output position error is only 12.7 mm, the acceleration accuracy reaches 99.7% under a vertical resultant force of 0.5kN, and the maximum processor occupancy rate during operation is only 58%. The above results indicate that this method not only enhances the realism of the simulation but also maintains low computational and hardware requirements, and effectively alleviates motion sickness in the simulator through adaptive motion perception adjustment. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Abstract (Arabic) Group: Ab Data: يركز المقال على تطوير وتقييم تقنية رقمية للواقع الافتراضي (الواقع الافتراضي) لمحاكيات تعلم القيادة، والتي تدمج خوارزمية غسل محسّنة بواسطة تعويض ضبابي لتعزيز واقعية الحركة وتقليل دوار المحاكاة. تقوم خوارزمية الغسل بمحاكاة الإدراك الدهليزي البشري من خلال ترشيح إشارات الحركة، بينما يقوم المتحكم الضبابي بضبط معلمات المرشح وأوزان الكسب بشكل ديناميكي في الوقت الحقيقي لمعالجة تقلبات الإدخال غير الخطية وقيود المنصة. تُظهر النتائج التجريبية أن هذه الطريقة تحقق أخطاء أقل في الموضع والوضعية، ودقة أعلى في التسارع، وتقليل زمن استجابة الجهاز (بمتوسط 5.3 مللي ثانية)، وانخفاض في احتلال المعالج (بحد أقصى 58%) مقارنةً بأساليب المحاكاة التقليدية القائمة على التحجيم غير الخطي والمحاكاة الحسية للتسارع، مع الحفاظ على استهلاك طاقة أقل. أظهرت اختبارات التطبيق مع طلاب القيادة تحسناً في نتائج التعلم باستخدام محاكي الواقع الافتراضي المقترح. وتقترح الدراسة أعمالاً مستقبلية لدمج التعلم التكيفي لقواعد الضبابي والتكامل مع نماذج ديناميكيات المركبات لتعزيز استقرار النظام وواقعيته بشكل أكبر. [Extracted from the article] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Jordan Journal of Mechanical & Industrial Engineering is the property of Hashemite University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.59038/jjmie/200215 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 293 Subjects: – SubjectFull: Automobile driving simulators Type: general – SubjectFull: Fuzzy algorithms Type: general – SubjectFull: Motion sickness Type: general – SubjectFull: Mathematical optimization Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Virtual reality Type: general – SubjectFull: Motion perception (Vision) Type: general Titles: – TitleFull: Virtual Reality Digitization of Driving Learning Simulators: Optimization via Fuzzy Compensation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Shuai – PersonEntity: Name: NameFull: Cui, Bingsheng IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19956665 Numbering: – Type: volume Value: 20 – Type: issue Value: 2 Titles: – TitleFull: Jordan Journal of Mechanical & Industrial Engineering Type: main |
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