@article{ref1,
title="Learning characteristic driving operations in curve sections that reflect drivers' skill levels",
journal="International journal of intelligent transportation systems research",
year="2014",
author="Li, Shuguang and Yamabe, Shigeyuki and Sato, Yoichi and Suda, Yoshihiro and Chandrasiri, Naiwala P. and Nawa, Kazunari",
volume="12",
number="3",
pages="135-145",
abstract="Our main objective was to develop a new driving assistance system that could help less experienced drivers improve their driving skills. We describe a statistical method we developed to extract distinctions between experienced and less experienced drivers. This paper makes three key contributions. The first involves a technology for feature extraction based on AdaBoost, which selects a small number of features critical for operation between experienced and less experienced drivers. The second involves a simple definition for experienced and less experienced drivers. The third involves the introduction of wavelet transforms that were used to analyze the frequency characteristics of driver operations. We performed a series of experiments using a driving simulator on a specially designed course that included several curves and then used the proposed method to extract features of driving operations that demonstrated the differences between the two groups.<p /> <p>Language: en</p>",
language="en",
issn="1348-8503",
doi="10.1007/s13177-014-0083-2",
url="http://dx.doi.org/10.1007/s13177-014-0083-2"
}