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Use of Unmanned Aerial Vehicles (UAVs) for Transport Pavement Inspection
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Resumo(s)
Technological evolution has allowed the use of unmanned aerial vehicles
(UAVs) in an easier and more diversified way, creating opportunities for its
application in various fields of engineering, namely in the inspection of transport
infrastructures. The present study begins with the analysis of the main practices that
resort to the use of UAVs, in order to frame its application in the field of transport
pavement inspection. A review of studies and other available literature served as a
starting point to define the methodology adopted for the development of the case
study presented. The methodology includes the collection of images of a flexible
road pavement section, its processing, and the creation of an orthoimage and a 3D
model from which it was possible to identify and characterize the distresses present
on the pavement surface. The main results obtained point to planimetric and altimetric
deviations of less than 2 and 10 mm, respectively, for the images collected by
theMavic 2 Pro drone at 3 and 20mhigh.With the collected data, itwas also possible
to calculate the global quality index PCI for the inspected pavement section. Under
these conditions, it is possible to conclude that the accuracy is very good and suitable
for the intended purpose, allowing fast data collection at low cost. This new technological
approach supports infrastructure managers in the design of maintenance
programs and in the scheduling of interventions, thus contributing to the increase of
the durability and safety levels of the inspected pavements.
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Contexto Educativo
Citação
Santos, B., Gavinhos, P., Almeida, P.G., Nery, D. (2025). Use of Unmanned Aerial Vehicles (UAVs) for Transport Pavement Inspection. In: Rujikiatkamjorn, C., Xue, J., Indraratna, B. (eds) Proceedings of the 5th International Conference on Transportation Geotechnics (ICTG) 2024, Volume 1. ICTG 2024. Lecture Notes in Civil Engineering, vol 402. Springer, Singapore. https://doi.org/10.1007/978-981-97-8213-0_1
Editora
Springer Nature
Licença CC
Sem licença CC