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.
Dominant Driving Operations in Curve Sections Differentiating Skilled and Unskilled Drivers
2012
14 Seiten
Aufsatz (Konferenz)
Englisch
Dominant driving operations in curve sections differentiating skilled and unskilled drivers
Kraftfahrwesen | 2012
|Dominant Driving Operations in Curve Sections Differentiating Skilled and Unskilled Drivers
Springer Verlag | 2012
|British Library Conference Proceedings | 2013
|Learning Characteristic Driving Operations in Curve Sections that Reflect Drivers’ Skill Levels
Springer Verlag | 2014
|Engineering Index Backfile | 1943