Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of Affection
Driver's propensity is a dynamic measurement of driver's characteristics, such as affection and preference. In the vehicle driver-assistance system, especially its collision warning subsystem, it is also an important parameter of computing driver's intention. The prediction of driver&...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2013-01-01
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| Series: | Advances in Mechanical Engineering |
| Online Access: | https://doi.org/10.1155/2013/658103 |
| _version_ | 1818954151496777728 |
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| author | Jinglei Zhang Xiaoyuan Wang Xuegang (Jeff) Ban Kai Cao |
| author_facet | Jinglei Zhang Xiaoyuan Wang Xuegang (Jeff) Ban Kai Cao |
| author_sort | Jinglei Zhang |
| collection | DOAJ |
| description | Driver's propensity is a dynamic measurement of driver's characteristics, such as affection and preference. In the vehicle driver-assistance system, especially its collision warning subsystem, it is also an important parameter of computing driver's intention. The prediction of driver's propensity from relative static and macroscopic perspective is an essential precondition for further researching and extracting dynamic characteristics. Physiology and psychology tests are designed to measure driver's character and calculate physiological rhythm. Changing data of driver's psychology and emotion during driving are obtained by real vehicle test. Then driver's propensity values of different types are calculated by weighting method according to the contribution rate of standard features. Results show that this method is better than the traditional psychology test, and it provides a basis for further studying dynamic characteristics of driver's affection. |
| first_indexed | 2024-12-20T10:17:36Z |
| format | Article |
| id | doaj.art-6d619eb95fdc443284731bcfeb2903a5 |
| institution | Directory Open Access Journal |
| issn | 1687-8132 |
| language | English |
| last_indexed | 2024-12-20T10:17:36Z |
| publishDate | 2013-01-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Advances in Mechanical Engineering |
| spelling | doaj.art-6d619eb95fdc443284731bcfeb2903a52022-12-21T19:44:00ZengSAGE PublishingAdvances in Mechanical Engineering1687-81322013-01-01510.1155/2013/65810310.1155_2013/658103Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of AffectionJinglei Zhang0Xiaoyuan Wang1Xuegang (Jeff) Ban2Kai Cao3 School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo Shandong 255091, China Department of Civil and Environmental Engineering, School of Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA Department of Civil and Environmental Engineering, School of Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo Shandong 255091, ChinaDriver's propensity is a dynamic measurement of driver's characteristics, such as affection and preference. In the vehicle driver-assistance system, especially its collision warning subsystem, it is also an important parameter of computing driver's intention. The prediction of driver's propensity from relative static and macroscopic perspective is an essential precondition for further researching and extracting dynamic characteristics. Physiology and psychology tests are designed to measure driver's character and calculate physiological rhythm. Changing data of driver's psychology and emotion during driving are obtained by real vehicle test. Then driver's propensity values of different types are calculated by weighting method according to the contribution rate of standard features. Results show that this method is better than the traditional psychology test, and it provides a basis for further studying dynamic characteristics of driver's affection.https://doi.org/10.1155/2013/658103 |
| spellingShingle | Jinglei Zhang Xiaoyuan Wang Xuegang (Jeff) Ban Kai Cao Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of Affection Advances in Mechanical Engineering |
| title | Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of Affection |
| title_full | Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of Affection |
| title_fullStr | Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of Affection |
| title_full_unstemmed | Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of Affection |
| title_short | Prediction Method of Driver's Propensity Adapted to Driver's Dynamic Feature Extraction of Affection |
| title_sort | prediction method of driver s propensity adapted to driver s dynamic feature extraction of affection |
| url | https://doi.org/10.1155/2013/658103 |
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