Study on classification and identification methods of driver steering characteristics
Aiming at the vehicle driver's steering characteristic classification and identification, the research method is initially explored based on CarSim simulation platform. The simulation experiment of steering condition is designed and the test data is collected. According to the maximum yaw rate...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
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Hebei University of Science and Technology
2015-12-01
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| Series: | Journal of Hebei University of Science and Technology |
| Subjects: | |
| Online Access: | http://xuebao.hebust.edu.cn/hbkjdx/ch/reader/create_pdf.aspx?file_no=b201506002&flag=1&journal_ |
| _version_ | 1831701745718263808 |
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| author | Gang LI Hailan HAN Hang YUAN Zhicheng ZHOU |
| author_facet | Gang LI Hailan HAN Hang YUAN Zhicheng ZHOU |
| author_sort | Gang LI |
| collection | DOAJ |
| description | Aiming at the vehicle driver's steering characteristic classification and identification, the research method is initially explored based on CarSim simulation platform. The simulation experiment of steering condition is designed and the test data is collected. According to the maximum yaw rate of the vehicle, the driver steering characteristics are classified by K-means clustering algorithm. The driver steering characteristics identification models are established by learning vector quantization (LVQ) neural network, BP neural network, and support vector machine (SVM) respectively in the environment of Matlab software. The test experiment and comparison are done for the three kinds of approaches, and the results show that all those three kinds of identification approaches have high accuracy, and the SVM method has a certain advantage on driver steering characteristics identification. |
| first_indexed | 2024-12-20T15:07:57Z |
| format | Article |
| id | doaj.art-35453026d3df4bf690b580b226819e2f |
| institution | Directory Open Access Journal |
| issn | 1008-1542 |
| language | zho |
| last_indexed | 2024-12-20T15:07:57Z |
| publishDate | 2015-12-01 |
| publisher | Hebei University of Science and Technology |
| record_format | Article |
| series | Journal of Hebei University of Science and Technology |
| spelling | doaj.art-35453026d3df4bf690b580b226819e2f2022-12-21T19:36:25ZzhoHebei University of Science and TechnologyJournal of Hebei University of Science and Technology1008-15422015-12-0136655956510.7535/hbkd.2015yx06002b201506002Study on classification and identification methods of driver steering characteristicsGang LI0Hailan HAN1Hang YUAN2Zhicheng ZHOU3College of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou, Liaoning 121001, ChinaCollege of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou, Liaoning 121001, ChinaCollege of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou, Liaoning 121001, ChinaCollege of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou, Liaoning 121001, ChinaAiming at the vehicle driver's steering characteristic classification and identification, the research method is initially explored based on CarSim simulation platform. The simulation experiment of steering condition is designed and the test data is collected. According to the maximum yaw rate of the vehicle, the driver steering characteristics are classified by K-means clustering algorithm. The driver steering characteristics identification models are established by learning vector quantization (LVQ) neural network, BP neural network, and support vector machine (SVM) respectively in the environment of Matlab software. The test experiment and comparison are done for the three kinds of approaches, and the results show that all those three kinds of identification approaches have high accuracy, and the SVM method has a certain advantage on driver steering characteristics identification.http://xuebao.hebust.edu.cn/hbkjdx/ch/reader/create_pdf.aspx?file_no=b201506002&flag=1&journal_vehicle engineeringdriversteering characteristicssimulation platform of CarSimclassificationidentification model |
| spellingShingle | Gang LI Hailan HAN Hang YUAN Zhicheng ZHOU Study on classification and identification methods of driver steering characteristics Journal of Hebei University of Science and Technology vehicle engineering driver steering characteristics simulation platform of CarSim classification identification model |
| title | Study on classification and identification methods of driver steering characteristics |
| title_full | Study on classification and identification methods of driver steering characteristics |
| title_fullStr | Study on classification and identification methods of driver steering characteristics |
| title_full_unstemmed | Study on classification and identification methods of driver steering characteristics |
| title_short | Study on classification and identification methods of driver steering characteristics |
| title_sort | study on classification and identification methods of driver steering characteristics |
| topic | vehicle engineering driver steering characteristics simulation platform of CarSim classification identification model |
| url | http://xuebao.hebust.edu.cn/hbkjdx/ch/reader/create_pdf.aspx?file_no=b201506002&flag=1&journal_ |
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