Citation

Sekizawa S, Inagaki S, Suzuki T, Hayakawa S, Tsuchida N, Tsuda T, Fujinami H. IEEE Trans. Intel. Transp. Syst. 2007; 8(4): 593-606.

Copyright

(Copyright © 2007, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TITS.2007.903441

PMID

unavailable

Abstract

This paper presents the development of the modeling and recognition of human driving behavior based on a stochastic switched autoregressive exogenous (SS-ARX) model. First, a parameter estimation algorithm for the SS-ARX model with multiple measured input-output sequences is developed based on the expectation-maximization algorithm. This can be achieved by extending the parameter estimation technique for the conventional hidden Markov model. Second, the developed parameter estimation algorithm is applied to driving data with the focus being on driver's collision avoidance behavior. The driving data were collected using a driving simulator based on the cave automatic virtual environment, which is a stereoscopic immersive virtual reality system. Then, the parameter set for each driver is obtained, and certain driving characteristics are identified from the viewpoint of switched control mechanism. Finally, the performance of the SS-ARX model as a behavior recognizer is examined. The results show that the SS-ARX model holds remarkable potential to function as a behavior recognizer.