3D Model of Pavement Distress Based on Road Gradient Using Unmanned Aerial Vehicle

DOI

10.2991/aer.k.220131.013How to use a DOI?

Keywords

Pavement Distress; road infrastructure; Road Gradient; UAV

Abstract

The implementation of UAVs in Indonesia on road infrastructure projects still widely used at the planning stage of new road routes and the supervision stage to determine the progress of the work. Meanwhile, at the post-work monitoring stage, the UAV is only used to identify and inventory the pavement distress in determining the type of damage, not followed by the further pavement assessment. This study aims to determine the type of damage and the dimensions (area and depth) of the damage and determine the level of pavement distress. Data acquisition was carried out by taking direct photos using a drone of some damage to the road segment based on different road gradients in the study location, which was a 1% - 6% slope. Photos taken from the drone are processed according to the rules of photogrammetry to produce an orthophoto as a 3D model. Furthermore, identification and inventory of types of pavement distress are carried out, as well as calculating the dimensions (area and depth) of pavement distress on photo maps. A minimum value difference of 0.3cm to 3cm is obtained from the calculation of the dimensions of the pavement distress in the model against the results of measurements in the field. The level of precision of the dimensions of the pavement distress in the model is not affected by the gradient of the road, meaning that the 3D model does not make the value of the depth of the pothole on a high road gradient more precise.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Yackob Astor
AU  - Retno Utami
AU  - Sarah Nabilah Winata
AU  - F A Rahman
AU  - F A Gustaman
AU  - M R Firdaus
PY  - 2022
DA  - 2022/02/01
TI  - 3D Model of Pavement Distress Based on Road Gradient Using Unmanned Aerial Vehicle
BT  - Proceedings of the Conference on Broad Exposure to Science and Technology 2021 (BEST 2021)
PB  - Atlantis Press
SP  - 79
EP  - 85
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.220131.013
DO  - 10.2991/aer.k.220131.013
ID  - Astor2022
ER  -