JSTE Journal of Traffic Engineering
Online ISSN : 2187-2929
ISSN-L : 2187-2929
Volume 4, Issue 4
Displaying 1-1 of 1 articles from this issue
Paper (1) Fundamental/Applied Academic Research
  • Yiliguoqi, Arong, Shigeyuki MURAKAMI, Hiroshi SASAKI
    2018Volume 4Issue 4 Pages 1-10
    Published: July 01, 2018
    Released on J-STAGE: July 01, 2018
    JOURNAL FREE ACCESS
    Recently, acceleration sensors / gyro sensor and so on have been embedded in smartphones and be-come popular. We can gather various kinds of information simply and on a massive scale by using such familiar information device. Therefore, in this study, we focus on acceleration data gathered by smartphone embedded sensors. Analysis the acceleration / angular velocity data by statistical processing to restrain the influence of measuring condition and extract features. Then, we propose a simple assessment method that utilizes features and using a Support Vector Machine (SVM) to classify the road surface roughness. Moreover, confirms the effectiveness of the proposed method.
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