Driver identification and driver's emotion verification using KDE and MLP neural networks
A Driver's behavior is a major factor that contributes to the high accidents rates. However, if we are able to identify their behavior, it may be possible for us to detect driving idiosyncrasies that may prevent accidents. Therefore, this paper presents some simple and effective methods for an...
| Main Authors: | , |
|---|---|
| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2010
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/20830/ http://irep.iium.edu.my/20830/1/Driver_identification_and_driver%27s_emotion_verification_using_KDE_and_MLP_neural_network.pdf |
| _version_ | 1848778675898548224 |
|---|---|
| author | Md Nor, Norzaliza Abdul Rahman, Abdul Wahab |
| author_facet | Md Nor, Norzaliza Abdul Rahman, Abdul Wahab |
| author_sort | Md Nor, Norzaliza |
| building | IIUM Repository |
| collection | Online Access |
| description | A Driver's behavior is a major factor that contributes to the high accidents rates. However, if we are able to identify their behavior, it may be possible for us to detect driving idiosyncrasies that may prevent accidents. Therefore, this paper presents some simple and effective methods for an in-car data acquisition in collecting real time driving data. The data has been classified into three different driver's condition which leads into accident. They are happy expression, talking on the phone and normal driving. These data will be used to investigate the effectiveness of a driver's behavior which focusing on the driver's response towards the brake and gas pedals as well as its rate of change. From these data we will demonstrate simple yet effective technique in driver identification and driver verification. We use the kernel density estimation (KDE) as tools to extract features. Then, we use these features to recognize the emotion of the driver by using multi layer perceptron (MLP) as classifiers. The enhancement of driver's security, safety and comfort driving can be derived trough the performances of the driver's emotion verification which contribute to the development in the area of intelligent vehicle driver verification system. |
| first_indexed | 2025-11-14T15:05:39Z |
| format | Proceeding Paper |
| id | iium-20830 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:05:39Z |
| publishDate | 2010 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-208302020-12-16T16:08:07Z http://irep.iium.edu.my/20830/ Driver identification and driver's emotion verification using KDE and MLP neural networks Md Nor, Norzaliza Abdul Rahman, Abdul Wahab QA75 Electronic computers. Computer science A Driver's behavior is a major factor that contributes to the high accidents rates. However, if we are able to identify their behavior, it may be possible for us to detect driving idiosyncrasies that may prevent accidents. Therefore, this paper presents some simple and effective methods for an in-car data acquisition in collecting real time driving data. The data has been classified into three different driver's condition which leads into accident. They are happy expression, talking on the phone and normal driving. These data will be used to investigate the effectiveness of a driver's behavior which focusing on the driver's response towards the brake and gas pedals as well as its rate of change. From these data we will demonstrate simple yet effective technique in driver identification and driver verification. We use the kernel density estimation (KDE) as tools to extract features. Then, we use these features to recognize the emotion of the driver by using multi layer perceptron (MLP) as classifiers. The enhancement of driver's security, safety and comfort driving can be derived trough the performances of the driver's emotion verification which contribute to the development in the area of intelligent vehicle driver verification system. 2010 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/20830/1/Driver_identification_and_driver%27s_emotion_verification_using_KDE_and_MLP_neural_network.pdf Md Nor, Norzaliza and Abdul Rahman, Abdul Wahab (2010) Driver identification and driver's emotion verification using KDE and MLP neural networks. In: 2010 International Conference on Information and Communication Technology for the Muslim World (ICT4M), 13-14 December 2010, Jakarta, Indonesia. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5971922&tag=1 |
| spellingShingle | QA75 Electronic computers. Computer science Md Nor, Norzaliza Abdul Rahman, Abdul Wahab Driver identification and driver's emotion verification using KDE and MLP neural networks |
| title | Driver identification and driver's emotion verification using KDE and MLP neural networks |
| title_full | Driver identification and driver's emotion verification using KDE and MLP neural networks |
| title_fullStr | Driver identification and driver's emotion verification using KDE and MLP neural networks |
| title_full_unstemmed | Driver identification and driver's emotion verification using KDE and MLP neural networks |
| title_short | Driver identification and driver's emotion verification using KDE and MLP neural networks |
| title_sort | driver identification and driver's emotion verification using kde and mlp neural networks |
| topic | QA75 Electronic computers. Computer science |
| url | http://irep.iium.edu.my/20830/ http://irep.iium.edu.my/20830/ http://irep.iium.edu.my/20830/1/Driver_identification_and_driver%27s_emotion_verification_using_KDE_and_MLP_neural_network.pdf |