Citation

Li S, Yamabe S, Sato Y, Suda Y, Chandrasiri NP, Nawa K. Int. J. Intell. Transp. Syst. Res. 2014; 12(3): 135-145.

Copyright

(Copyright © 2014, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s13177-014-0083-2

PMID

unavailable

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.

Language: en