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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Liq Yee Tiong, P., Mustaffar, M., Rosli Haini, M.: Road surface assessment of pothole severity by close range digital photogrammetry method. World Appl. Sci. J. 19(6), 867–873 (2012)
Cet, K., Georgieva, K., Kasireddy, V., Akinci, B., Fieguthd, P.: A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure. Adv. Eng. Inform. 29(2), 196–210 (2015)
Buonsanti, M., Cirianni, F., Leonardi, G., Scopelliti, F.: Dynamic behavior of granular mixture solids. Key Eng. Mater. 488–489, 541–544 (2012)
Leonardi, G.: Finite element analysis for airfield asphalt pavements rutting prediction. Bull. Pol. Acad. Sci. Tech. Sci. 63(2), 397–403 (2015)
Schnebele, E., Tanyu, B.F., Cervone, G., Waters, N.: Review of remote sensing methodologies for pavement management and assessment. Eur. Transp. Res. (2015)
Leachtenauer, J.C., Driggers, R.G.: Surveillance and Reconnaissance Imaging Systems: Modeling and Performance Prediction. Artech House, Boston (2011)
Zhang, C.: An UAV-based photogrammetric mapping system for road condition assessment, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, ISPRS Congress, XXXVII. Part B (2008)
Zhang, C., Elaksher, A.: An unmanned aerial vehicle-based imaging system for 3D measurement of unpaved road surface distresses. Comput. Aided Civ. Infrastruct. Eng. 27(2), 118–129 (2012)
Lowe, D.G.: University of British Columbia, Canada - Object Recognition from Local Scale-Invariant Features (1999)
Wu, C.: University of Washington - Towards Linear-time Incremental Structure from Motion (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Leonardi, G., Barrile, V., Palamara, R., Suraci, F., Candela, G. (2019). 3D Mapping of Pavement Distresses Using an Unmanned Aerial Vehicle (UAV) System. In: Calabrò, F., Della Spina, L., Bevilacqua, C. (eds) New Metropolitan Perspectives. ISHT 2018. Smart Innovation, Systems and Technologies, vol 101. Springer, Cham. https://doi.org/10.1007/978-3-319-92102-0_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-92102-0_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-92101-3
Online ISBN: 978-3-319-92102-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)