Utilization of UAV for Pavement Condition Evaluation with SDI Method On The Bandung-Subang Road Km. Jkt. 179+800 - 178+300 Yackob Astor (a), Retno Utami (a*), Atmy Verani Rouly (a), Desutama Rachmat (a), Saldila Pramestu (a), Syahreza Apriansyah (a)
(a) Department of Civil Engineering, Jl. Gegerkalong Hilir Ds. Ciwaruga, Politeknik Negeri Bandung, Indonesia
*retnoutami[at]polban.ac.id
Abstract
Road construction has become a priority for the government to make community mobilization easier. High mobilization also means increasing traffic which can lead to pavement distress due to high traffic volume. This phenomenon happened on Jalan Raya Bandung-Subang KM. JKT. 179+800 - KM. JKT. 178+300 in Cicenang Village, Ciater, Subang Regency, West Java. As the connecting road to one of the tourist destinations in West Java, some pavement distress occurred which could trigger traffic accidents. Based on the condition of the distressed pavement, an evaluation of pavement conditions was carried out using the Surface Distress Index (SDI) method with two measurement methods, visual photogrammetry using an Unmanned Aerial Vehicle (UAV) or drones with the help of Agisoft Metashape software and visual measurements in the field. The validation process is carried out by comparing the results of the dimensions of the distress measurement on the model to the dimensions of the distress that occurred in the field. Based on the results of the pavement condition evaluation using the SDI method, it was found that the pavement conditions with the most visual measurements in the field were ^good^ with an SDI value of <50 for as many as 6 segments out of a total of 15 overall segments, while measurements using UAV assistance obtained pavement conditions in ^good^ with an SDI value of <50 for as many as 5 segments out of a total of 12 segments. This result can be accepted because there were 3 segments blocked by objects. Based on the results of data processing, the average value of the visual measurement accuracy test using a UAV with visual measurements in the field obtained is 94.326%. Pavement condition evaluation using UAV assistance is expected to be one of the more efficient SDI measurement methods for use in Indonesia.
