Road Damage Identification and Degree Assessment Based on UGV

J. H. Song; H. W. Gao; Y. J. Liu; Y. Yu

doi:10.21307/ijssis-2017-953

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Road Damage Identification and Degree Assessment Based on UGV

International Journal on Smart Sensing and Intelligent Systems

Volume 9 (2016): Issue 4 (January 2016)

By: J. H. Song, H. W. Gao, Y. J. Liu and Y. Yu

Open Access

|Dec 2016

Abstract

Aiming at the problem of automatic identification and evaluation of road damage degree, the road damage identification and degree assessment algorithms based on unmanned vehicles experimental platform are studied. The road crack segmentation extraction method based on adaptive sliding window is studied. On this basis, the road damage crack classifies and identifies according to the crack geometry information and the principle of template matching. The road damage degree assessment algorithm based on fuzzy decision is proposed based on the quantitative analysis of the road crack and the corresponding parameters information. The experimental results demonstrate that the road damage identification and degree assessment algorithms proposed in this paper are effective and stable.

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Articles in this issue

DOI: https://doi.org/10.21307/ijssis-2017-953 | Journal eISSN: 1178-5608

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Language: English

Page range: 2069 - 2087

Submitted on: Jul 27, 2016

Accepted on: Oct 19, 2016

Published on: Dec 1, 2016

Published by: Macquarie University, Australia

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

unmanned vehicle,

damage identification,

quantitative analysis,

fuzzy decision

Related subjects:

Engineering,

Introductions and overviews,

Engineering, other

© 2016 J. H. Song, H. W. Gao, Y. J. Liu, Y. Yu, published by Macquarie University, Australia
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 9 (2016): Issue 4 (January 2016)