Pavement Distress Estimation via Signal on Graph Processing

Bruno, Salvatore; Colonnese, Stefania; Scarano, Gaetano; Serrone, Giulia Del; Loprencipe, Giuseppe

doi:10.3390/s22239183

Cited by 4 publications

(2 citation statements)

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“…The Pavement condition index (PCI), as defined by ASTM D6433 [66], provides a quantitative assessment of the current state of the pavement. It takes into account the type, extent, and severity of identified road distress [67,68]. More precisely, the detection and assessment of road surface distress are grouped for flexible pavements into cracking, distortion, disintegration, and skid hazards.…”

Section: Pavement Condition Index (Pci)mentioning

confidence: 99%

Modified Asphalt with Graphene-Enhanced Polymeric Compound: A Case Study

Bruno,

Carpani,

Loprencipe

et al. 2024

Infrastructures

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In recent years, the increased use of heavy commercial vehicles with higher axle weights has required the development of innovative technologies to improve the mechanical properties of asphalt concrete conglomerates, such as fatigue resistance and rutting. This study offers a comprehensive comparative analysis of different types of asphalt concrete tested in four trial sections (S1, S2, S3, S4) of the SP3 Ardeatina rural road in Rome, under actual traffic and operational conditions. More precisely, the pavement technologies applied include modified asphalt concrete with graphene and recycled hard plastics for S1, asphalt concrete modified with styrene–butadiene–styrene (SBS) for S2, asphalt concrete with a standard polymeric compound for S3, and traditional asphalt concrete for S4. The evaluation approach involved visual inspections in order to calculate the pavement condition index (PCI) and falling weight deflectometer (FWD) tests. In addition, back-calculation analyses were performed using ELMOD software to assess the mechanical properties. The laboratory tests revealed superior properties of M1 in terms of its resistance to permanent deformations (+13%, +15%, and +19.5% compared to M2, M3, and M4, respectively) and stiffness (10,758 MPa for M1 vs. 9259 MPa, 7643 MPa, and 7289 MPa for M2, M3, and M4, respectively). These findings were further corroborated by the PCI values (PCIS1 = 65; PCIS2 = 17; PCIS3 = 28; PCIS4 = 29) as well as the FWD test results after 5 years of investigation, which suggests greater durability and resistance than the other sections.

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Section: Pavement Condition Index (Pci)mentioning

confidence: 99%

Modified Asphalt with Graphene-Enhanced Polymeric Compound: A Case Study

Bruno,

Carpani,

Loprencipe

et al. 2024

Infrastructures

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“…The detection and analysis of road surface defects impact the definition of the most appropriate maintenance strategy to ensure traffic safety and ride comfort [1]. Effective maintenance planning also reduces maintenance costs for road managers who face increasing budgetary constraints [2].…”

Section: Introductionmentioning

confidence: 99%

A Robotized Raspberry-Based System for Pothole 3D Reconstruction and Mapping

Bruno

Loprencipe

Mascio

et al. 2023

Sensors

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Repairing potholes is a task for municipalities to prevent serious road user injuries and vehicle damage. This study presents a low-cost, high-performance pothole monitoring system to maintain urban roads. The authors developed a methodology based on photogrammetry techniques to predict the pothole’s shape and volume. A collection of overlapping 2D images shot by a Raspberry Pi Camera Module 3 connected to a Raspberry Pi 4 Model B has been used to create a pothole 3D model. The Raspberry-based configuration has been mounted on an autonomous and remote-controlled robot (developed in the InfraROB European project) to reduce workers’ exposure to live traffic in survey activities and automate the process. The outputs of photogrammetry processing software have been validated through laboratory tests set as ground truth; the trial has been conducted on a tile made of asphalt mixture, reproducing a real pothole. Global Positioning System (GPS) and Geographical Information System (GIS) technologies allowed visualising potholes on a map with information about their centre, volume, backfill material, and an associated image. Ten on-site tests validated that the system works in an uncontrolled environment and not only in the laboratory. The results showed that the system is a valuable tool for monitoring road potholes taking into account construction workers’ and road users’ health and safety.

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