Road-types classification using audio signal processing and SVM method

Abstract

In this study, a low-cost system which classifies different road conditions (asphalt, gravel, snowy and stony road) using acoustic signal processing is proposed. Thus it is aimed to estimate road/tire friction forces in the active safety systems. Classical acoustic signal processing methods which are linear predictive coding (LPC), power spectrum (PSC) and mel-frequency cepstrum coefficients (MFCC) are used with minimum variance and maximum distance principle in this system. The classification process is also executed by support vector machine (SVM).