Use of Terrestrial Laser Scanner for Rigid Airport Pavement Management

Barbarella, Maurizio; D’Amico, Fabrizio; Blasiis, Maria Rosaria De; Benedetto, Alessandro Di; Fiani, Margherita

doi:10.3390/s18010044

Cited by 29 publications

(17 citation statements)

References 26 publications

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“…In the test case, the clearly recognizable swells are the number 25,35,38,45,49,66 and 72 ( Figure 14b) mainly oriented along the direction of travel and longer than 3 m. The shoves are all isolated segmented regions. Most were formed by the longitudinal acceleration (braking, speed up) of the tire and the vehicle load.…”

Section: Distress Identificationmentioning

confidence: 89%

“…Chin [22] focuses on filtering TLS data to make them comparable with IRI dynamic index values determined by standard methods, such as profile measuring instruments including level and rod, inclinometers and inertial profilometers. TLS has also been used for the computation and verification of the faulting of rigid concrete slabs in airport pavements [25] and for the analysis of the flexible geometry of the pavement [26].…”

Section: Introductionmentioning

confidence: 99%

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Mobile Laser Scanning Data for the Evaluation of Pavement Surface Distress

2020

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The surface conditions of road pavements, including the occurrence and severity of distresses present on the surface, are an important indicator of pavement performance. Periodic monitoring and condition assessment is an essential requirement for the safety of vehicles moving on that road and the wellbeing of people. The traditional characterization of the different types of distress often involves complex activities, sometimes inefficient and risky, as they interfere with road traffic. The mobile laser systems (MLS) are now widely used to acquire detailed information about the road surface in terms of a three-dimensional point cloud. Despite its increasing use, there are still no standards for the acquisition and processing of the data collected. The aim of our work was to develop a procedure for processing the data acquired by MLS, in order to identify the localized degradations that mostly affect safety. We have studied the data flow and implemented several processing algorithms to identify and quantify a few types of distresses, namely potholes and swells/shoves, starting from very dense point clouds. We have implemented data processing in four steps: (i) editing of the point cloud to extract only the points belonging to the road surface, (ii) determination of the road roughness as deviation in height of every single point of the cloud with respect to the modeled road surface, (iii) segmentation of the distress (iv) computation of the main geometric parameters of the distress in order to classify it by severity levels. The results obtained by the proposed methodology are promising. The procedures implemented have made it possible to correctly segmented and identify the types of distress to be analyzed, in accordance with the on-site inspections. The tests carried out have shown that the choice of the values of some parameters to give as input to the software is not trivial: the choice of some of them is based on considerations related to the nature of the data, for others, it derives from the distress to be segmented. Due to the different possible configurations of the various distresses it is better to choose these parameters according to the boundary conditions and not to impose default values. The test involved a 100-m long urban road segment, the surface of which was measured with an MLS installed on a vehicle that traveled the road at 10 km/h.

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Section: Distress Identificationmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Mobile Laser Scanning Data for the Evaluation of Pavement Surface Distress

2020

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“…Moreover, due to the huge amount of information acquired, the 3D point cloud can be used for general road asset management. Authors propose several applications on low areas that are susceptible to drainage problems [61], or a semi-automatic procedure to reconstruct longitudinal grade and the cross-slopes of a taxiway starting from a DEM [61] and a method in order to identify and quantify the fault size at each joint of apron slabs from terrestrial laser scanner data [62].…”

Section: Terrestrial Laser Scannermentioning

confidence: 99%

Pavement Distress Detection Methods: A Review

2018

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The road pavement conditions affect safety and comfort, traffic and travel times, vehicles operating cost, and emission levels. In order to optimize the road pavement management and guarantee satisfactory mobility conditions for all road users, the Pavement Management System (PMS) is an effective tool for the road manager. An effective PMS requires the availability of pavement distress data, the possibility of data maintenance and updating, in order to evaluate the best maintenance program. In the last decade, many researches have been focused on pavement distress detection, using a huge variety of technological solutions for both data collection and information extraction and qualification. This paper presents a literature review of data collection systems and processing approach aimed at the pavement condition evaluation. Both commercial solutions and research approaches have been included. The main goal is to draw a framework of the actual existing solutions, considering them from a different point of view in order to identify the most suitable for further research and technical improvement, while also considering the automated and semi-automated emerging technologies. An important attempt is to evaluate the aptness of the data collection and extraction to the type of distress, considering the distress detection, classification, and quantification phases of the procedure.

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“…The resultant point cloud is then post-processed to extract roadside feature data including pavement and roadsides in order to gather data for asset management, as-built documentation, and maintenance operations (Guan et al, 2016). In Highway and especially in airport the evaluation of road pavement performance is essential for effective maintenance design engineering (Barbarella et al, 2018;Barbarella et al, 2017). The research is oriented towards the study of survey methods in order to obtain increased safety, higher data collection speed, higher accuracy data, and minimising traffic interference (Ragnoli et al, 2018;Yen et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing Technologies for Linear Infrastructure Monitoring

D’Aranno¹,

Benedetto

Fiani

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> The need for a continuous evaluation of the state of preservation of civil infrastructures during their lifetime is increasingly requiring advanced monitoring technologies. The improvement of spatial and temporal resolution of the measurements is now one of the most significant achievement, especially for large infrastructures. Monitoring actions are necessary to maintain safety conditions by controlling the evolution of deformation patterns or detecting significant instabilities. Remote sensing technique such as Differential Interferometry by Synthetic Aperture Radar (DInSAR) allows identifying environmental vulnerability and potential damages on large road infrastructures thus contributing to plan and optimize maintenance actions. DInSAR data allow to highlight instability processes and to quantify mean deformation velocities and displacement time series. This information can be analysed considering geotechnical and structural characteristics and adopted to evaluate possible safety condition improvement and damage mitigation. Using proximal remote sensing techniques, such as Light Detection And Ranging (LiDAR), it is possible to analyse the pavement conditions on 3D models derived from a dense point cloud acquired by Mobile Laser Scanner (MLS). By combining the DInSAR and LiDAR datasets a great improvement is expected in the capability to promptly identifying critical situations and understanding potential risks affecting extended road infrastructures. The principal aim of this paper is to provide a general overview of the most innovative remote sensing techniques for infrastructure safety condition assessments. Furthermore, a methodological approach to define a reliable procedure for data processing and integration is applied on a test area located in the municipality of Rome.</p>

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Use of Terrestrial Laser Scanner for Rigid Airport Pavement Management

Cited by 29 publications

References 26 publications

Mobile Laser Scanning Data for the Evaluation of Pavement Surface Distress

Mobile Laser Scanning Data for the Evaluation of Pavement Surface Distress

Pavement Distress Detection Methods: A Review

Remote Sensing Technologies for Linear Infrastructure Monitoring

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