Driver Identification Using Driving Behavior Signals

Toshihiro WAKITA  Koji OZAWA  Chiyomi MIYAJIMA  Kei IGARASHI  Katunobu ITOU  Kazuya TAKEDA  Fumitada ITAKURA  

IEICE TRANSACTIONS on Information and Systems   Vol.E89-D   No.3   pp.1188-1194
Publication Date: 2006/03/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e89-d.3.1188
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Human-computer Interaction
driving behavior,  signal processing,  pattern recognition,  biometrics,  

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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%.