Parametric Versus Non-parametric Models of Driving Behavior Signals for Driver Identification
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 of the accelerator pedal, brake pedal, vehicle velocity, and distance from the vehicle in front, are measured using a driving simulator. We compared the identification rate obtained using different identification models and different features. As a result, we found the non-parametric models to be better than the parametric models. Also, the driver’s operation signals were found to be better than road environment signals and car behavior signals.
KeywordsGaussian Mixture Model Behavior Signal Driving Simulator Optimal Velocity Vehicle Velocity
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- 1.Oguchi, T.: Analysis of Bottleneck Phenomena at Basic Freeway Segments - Carfollowing Model and Future Exploration. Journal of the Japan Society of Civil Engineers 660(IV-49), 39–51 (2000) (in Japanese)Google Scholar
- 2.Brackstone, M., McDonald, M.: Car-following: a historical review. Transportation Research Part F 2, 181–196 (1999)Google Scholar
- 3.Ranjitkar, P., Nakatsuji, T., Asano, M.: Performance Evaluation of Microscopic Traffic Flow Models Using Test Track Data, 2004 TRB Annual Meeting (2004)Google Scholar
- 4.Helly, W.: Simulation of Bottlenecks in Single Lane Traffic Flow. In: Proc. of the Symposium on Theory of Traffic Flow, Research Laboratories, General Motors, pp. 207–238 (1959)Google Scholar
- 5.Bando, M., Hasebe, K., Nakayama, A., Shibata, A., Sugimaya, Y.: Dynamical Model of Traffic Congestion and Numerical Simulation. Physical Review E51, 1035–1042 (1995)Google Scholar
- 8.Igarashi, K., Miyajima, C., Itou, K., Takeda, K., Itakura, F., Abut, H.: Biometric identification using driving behavioral signals. In: Proc. 2004 IEEE International Conference on Multimedia and Expo (2004)Google Scholar