Dominant Driving Operations in Curve Sections Differentiating Skilled and Unskilled Drivers
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Our objective is to develop a new driving assist system that can help low-skilled drivers improve their driving skill. In this paper, we describe a statistical method we have developed to extract distinctions between high- and low-skilled drivers. There are three key contributions. The first is the introduction of wavelet transform to analyze the frequency character of driver operations. The second is a feature extraction technology based on AdaBoost, which selects a small number of critical operation features between high- and low-skilled drivers. The third is a simple definition for high- and low-skilled drivers. We performed a series of experiments using a driving simulator on a specially designed course including several curves and then used the proposed method to extract driving operation features showing the difference between the two groups.
KeywordsDriver behavior Driving simulator Driving skill Features extraction Curve sections
The author Li was supported through the Global COE Program, “Global Center of Excellence for Mechanical Systems Innovation,” by the Ministry of Education, Culture, Sports, Science and Technology.
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