Driver Identification Using Driving Behavior Signals(Human-computer Interaction)
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概要
- 論文の詳細を見る
In this paper, we propose a driver identification method that is based on the driving behavior signals that are observed while the driver is following another vehicle. Driving behavior signals, such as the use of the accelerator pedal, brake pedal, vehicle velocity, and distance from the vehicle in front, were measured using a driving simulator. We compared the identification rate obtained using different identification models. As a result, we found the Gaussian Mixture Model to be superior to the Helly model and the optimal velocity model. Also, the driver's operation signals were found to be better than road environment signals and car behavior signals for the Gaussian Mixture Model. The identification rate for thirty driver using actual vehicle driving in a city area was 73%.
- 2006-03-01
著者
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TAKEDA Kazuya
Nagoya University
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Takeda Kazuya
Nagoya Univ.
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Takeda Kazuya
Nagoya Univ. Nagoya‐shi Jpn
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Wakita Toshihiro
The Toyota Central R&d Labs. Inc.:the Graduate School Of Information Science Nagoya University
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MIYAJIMA Chiyomi
Nagoya University
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Itou Katsunobu
Faculty Of Computer And Information Sciences Hosei University
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TAKEDA Kazuya
the Graduate School of Information Science, Nagoya University
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Miyajima Chiyomi
The Graduate School Of Information Science Nagoya University
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ITAKURA Fumitada
Graduate School of Information Engineering, Meijo University
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Itakura Fumitada
The Faculty Of Science And Technology Meijo University
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Igarashi Kei
The Ntt Docomo Inc. Ntt Docomo R&d Center
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OZAWA Koji
the Graduate School of Information Science, Nagoya University
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ITOU Katunobu
the Graduate School of Information Science, Nagoya University
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ITAKURA Fumitada
the Department of Information Engineering, Meijo University
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Ozawa Koji
The Graduate School Of Information Science Nagoya University
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Takeda Kazuya
The Graduate School Of Information Science Nagoya University
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