The aim of road surface monitoring is to detect the distress on paved or unpaved road surfaces. Depending on the types of surface rupture, required parameters are measured on-site to determine the severity level of the road damage. Local infrastructure engineers and supervisors must therefore optimize their resources when monitoring road conditions and scheduling maintenance activities. Automation of road surface monitoring process may result in great monetary savings and can lead to more frequent inspection cycles, for this reasons departments of road maintenance, repair and transportations have become more interested in using automatic systems for pavement assessment. The scope of the presented work is the performance evaluation of a UAV system that was built to rapidly and autonomously acquire mobile three-dimensional (3D) mapping data to identify pavement distresses. © Springer International Publishing AG, part of Springer Nature 2019.
3D mapping of pavement distresses using an Unmanned Aerial Vehicle (UAV) system / Leonardi, G; Barrile, V.; Palamara, R.; Suraci, F.; Candela, G.. - 101:(2019), pp. 164-171. ( 3rd International New Metropolitan Perspectives. Local Knowledge and Innovation dynamics towards territory attractiveness through the implementation of Horizon/Europe2020/Agenda2030 Reggio Calabria 22/05/2018 - 25/05/2018) [10.1007/978-3-319-92102-0_18].
3D mapping of pavement distresses using an Unmanned Aerial Vehicle (UAV) system
Leonardi G
;Barrile V.;Palamara R.;Suraci F.;Candela G.
2019-01-01
Abstract
The aim of road surface monitoring is to detect the distress on paved or unpaved road surfaces. Depending on the types of surface rupture, required parameters are measured on-site to determine the severity level of the road damage. Local infrastructure engineers and supervisors must therefore optimize their resources when monitoring road conditions and scheduling maintenance activities. Automation of road surface monitoring process may result in great monetary savings and can lead to more frequent inspection cycles, for this reasons departments of road maintenance, repair and transportations have become more interested in using automatic systems for pavement assessment. The scope of the presented work is the performance evaluation of a UAV system that was built to rapidly and autonomously acquire mobile three-dimensional (3D) mapping data to identify pavement distresses. © Springer International Publishing AG, part of Springer Nature 2019.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
