Analysis of safety verification behavior and classification of driver´s head posture

Many car accidents are caused by driver´s deviation from normal condition like carelessness. We aim to construct a driving assist system that is able to detect driver´s deviation signal from normal condition. The system detects the deviation signal using driver´s time-series head motion information. In this paper, we analyze driver´s head posture of safety verification at the unsignalized blind intersection, and propose a classification method of head posture using two kinds of unsupervised neural networks: SOMs and Fuzzy ART. Moreover, we discuss ability of proposed method for face orientation categorization.