Driver Identification Using Driving Behavior Signals

Authors:
Toshihiro Wakita;Koji Ozawa;Chiyomi Miyajima;Kei Igarashi;Katunobu Itou;Kazuya Takeda;Fumitada Itakura
Affiliations:
The author is with the TOYOTA Central R&D Labs., Inc., Aichi-ken, 480--1192 Japan. E-mail: wakita@mosk.tytlabs.co.,;The authors are with the Graduate School of Information Science, Nagoya University, Nagoya-shi, 464--8603 Japan.,;The authors are with the Graduate School of Information Science, Nagoya University, Nagoya-shi, 464--8603 Japan.,;The author is with the NTT DoCoMo, Inc., NTT DoCoMo R&D Center, Yokosuka-shi, 239--8536 Japan.,;The authors are with the Graduate School of Information Science, Nagoya University, Nagoya-shi, 464--8603 Japan.,;The authors are with the Graduate School of Information Science, Nagoya University, Nagoya-shi, 464--8603 Japan.,;The author is with the Department of Information Engineering, Meijo University, Nagoya-shi, 468--8502 Japan.
Venue:
IEICE - Transactions on Information and Systems
Year:
2006

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Abstract

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%.