Improved Predictive Model of Drivers' Subjective Perception of Vehicle Reaction under Aerodynamic Excitations.
Saved in:
| Title: | Improved Predictive Model of Drivers' Subjective Perception of Vehicle Reaction under Aerodynamic Excitations. |
|---|---|
| Authors: | Kumar, Arun1,2 (AUTHOR), Sällström, Erik2 (AUTHOR), Sebben, Simone1 (AUTHOR) simone.sebben@chalmers.se, Jacobson, Bengt1 (AUTHOR) |
| Source: | International Journal of Automotive Technology. Dec2023, Vol. 24 Issue 6, p1655-1664. 10p. |
| Subjects: | Prediction models, Automobile driving simulators, Standard deviations, Dynamic models, Regression analysis, Perception testing, Steering gear, Automobile steering gear |
| Abstract: | In vehicle development, rating vehicle reactions to external disturbances such as aerodynamic excitations are important for improving safety and comfort of passengers. Vehicle motion reactions under such conditions are dependent on both disturbance and drivers' steering actions. A predictive model has been developed to correctly anticipate the drivers' ability to identify unexpected external disturbances for straight-line, high-speed driving in a driving simulator. The measured variables were band-pass filtered to desired frequency ranges. Excess yaw and roll velocities, defined as the difference between actual rotations and rotations predicted with a dynamic model from the cause of actual steering, were calculated. The standard deviations of the measured variables in a time window around disturbances were used in a regression model to predict the driver responses. Replacing actual rotations with excess rotations reduced the importance of steering input as a predictor by approximately 2/3, thus improving the accuracy of the predictive model. The model showed the change in driver sensitivity to rotations at different frequency intervals. It also showed that only driver input in around 1 ∼ 2 Hz reduces driver sensitivity and that drivers are not necessarily sensitive to high rotational accelerations, but rather to large differences between actual vehicle yaw and roll and expected vehicle yaw and roll responses from the steering input The result from this study were later compared to succeeding on-road tests which confirmed that the predictive model was improved with the use of excess motion variables. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Automotive Technology is the property of Springer Nature 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 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 173429453 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Improved Predictive Model of Drivers' Subjective Perception of Vehicle Reaction under Aerodynamic Excitations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kumar%2C+Arun%22">Kumar, Arun</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sällström%2C+Erik%22">Sällström, Erik</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sebben%2C+Simone%22">Sebben, Simone</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> simone.sebben@chalmers.se</i><br /><searchLink fieldCode="AR" term="%22Jacobson%2C+Bengt%22">Jacobson, Bengt</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Automotive+Technology%22">International Journal of Automotive Technology</searchLink>. Dec2023, Vol. 24 Issue 6, p1655-1664. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Automobile+driving+simulators%22">Automobile driving simulators</searchLink><br /><searchLink fieldCode="DE" term="%22Standard+deviations%22">Standard deviations</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+models%22">Dynamic models</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Perception+testing%22">Perception testing</searchLink><br /><searchLink fieldCode="DE" term="%22Steering+gear%22">Steering gear</searchLink><br /><searchLink fieldCode="DE" term="%22Automobile+steering+gear%22">Automobile steering gear</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In vehicle development, rating vehicle reactions to external disturbances such as aerodynamic excitations are important for improving safety and comfort of passengers. Vehicle motion reactions under such conditions are dependent on both disturbance and drivers' steering actions. A predictive model has been developed to correctly anticipate the drivers' ability to identify unexpected external disturbances for straight-line, high-speed driving in a driving simulator. The measured variables were band-pass filtered to desired frequency ranges. Excess yaw and roll velocities, defined as the difference between actual rotations and rotations predicted with a dynamic model from the cause of actual steering, were calculated. The standard deviations of the measured variables in a time window around disturbances were used in a regression model to predict the driver responses. Replacing actual rotations with excess rotations reduced the importance of steering input as a predictor by approximately 2/3, thus improving the accuracy of the predictive model. The model showed the change in driver sensitivity to rotations at different frequency intervals. It also showed that only driver input in around 1 ∼ 2 Hz reduces driver sensitivity and that drivers are not necessarily sensitive to high rotational accelerations, but rather to large differences between actual vehicle yaw and roll and expected vehicle yaw and roll responses from the steering input The result from this study were later compared to succeeding on-road tests which confirmed that the predictive model was improved with the use of excess motion variables. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Automotive Technology is the property of Springer Nature 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=173429453 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s12239-023-0133-3 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 1655 Subjects: – SubjectFull: Prediction models Type: general – SubjectFull: Automobile driving simulators Type: general – SubjectFull: Standard deviations Type: general – SubjectFull: Dynamic models Type: general – SubjectFull: Regression analysis Type: general – SubjectFull: Perception testing Type: general – SubjectFull: Steering gear Type: general – SubjectFull: Automobile steering gear Type: general Titles: – TitleFull: Improved Predictive Model of Drivers' Subjective Perception of Vehicle Reaction under Aerodynamic Excitations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kumar, Arun – PersonEntity: Name: NameFull: Sällström, Erik – PersonEntity: Name: NameFull: Sebben, Simone – PersonEntity: Name: NameFull: Jacobson, Bengt IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 12299138 Numbering: – Type: volume Value: 24 – Type: issue Value: 6 Titles: – TitleFull: International Journal of Automotive Technology Type: main |
| ResultId | 1 |
