In Situ Pavement Monitoring: A Review

The assessment of pavement conditions and their evolution with time is a crucial component for the establishment of pavement quality management (QM) plans and the implementation of QM practices. An effective pavement management system (PMS) is based on pavement conditions data continuously collected along the lifetime of a road. These data are used to model the pavement response, evaluate its performances, and trigger the necessary maintenance actions when they do not meet previously defined performance indicators. In the last decades, pavement monitoring via embedded sensing technologies has attracted more and more attention. Indeed, the integration of sensors in the road pavement allows the assessment of the complete history of pavement conditions, starting from sensor installation. Once the technologies are stabilized, collecting this information is expected to help road managers to define more effective asset management plans. This paper first proposes an overview of the most used devices for pavement instrumentation, categorized according to the measured parameters. Then a review of some prominent instrumented sections is presented by focusing on the methodology used for data interpretation.

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Pavement Distress Detection Methods: A Review

Infrastructures ◽

10.3390/infrastructures3040058 ◽

2018 ◽

Vol 3 (4) ◽

pp. 58 ◽

Cited By ~ 17

Author(s):

Antonella Ragnoli ◽

Maria De Blasiis ◽

Alessandro Di Benedetto

Keyword(s):

Data Collection ◽

Operating Cost ◽

Pavement Management ◽

Point Of View ◽

Detection Methods ◽

Technical Improvement ◽

Pavement Distress ◽

The Road ◽

Road Pavement ◽

Pavement Distress Detection

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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Investigation on Identifying Road Anomalies using In-Vehicle Sensors for Cooperative Applications and Road Asset Management

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198120923989 ◽

2020 ◽

Vol 2674 (7) ◽

pp. 585-595

Author(s):

Moksheeth Padarthy ◽

Mohammed Sami ◽

Emiliano Heyns

Keyword(s):

Asset Management ◽

Real Life ◽

Pavement Management ◽

Machine Learning Techniques ◽

Lateral Acceleration ◽

The Road ◽

Pavement Management Systems ◽

Learning Techniques ◽

The Right ◽

Vehicle Sensors

One of the main challenges for road authorities is to maintain the quality of the road infrastructure. Road anomalies can have a significant impact on traffic flow, the condition of vehicles, and the comfort of occupants of vehicles. Strategies such as pavement management systems use pavement evaluation vehicles that are equipped with state-of-the-art devices to assist road authorities in identifying and repairing these anomalies. The quantity of data available is limited, however, by the limited availability and, therefore, coverage of these vehicles. To address this problem, several investigations have been conducted on the use of smartphones or equipping vehicles with additional sensors to identify the presence of road anomalies. This paper aims to add to this arsenal by using sensors already available in production vehicles to identify road anomalies. If production vehicles could be used to identify road anomalies, then road authorities would be equipped with an additional fleet of mobile sensors (vehicles traveling on a particular road) to receive initial insights into the presence of anomalies. This information could then be used to assist road authorities to deploy their staff and equipment more precisely at these locations, such that appropriate equipment reaches the right place at the right time. In this paper, an algorithm that uses lateral acceleration and individual wheel speed signals, which are commonly available vehicular variables, was developed to detect potholes using machine learning techniques. The results of the algorithm were validated with real life test scenarios.

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Sensor-based pavement diagnostic using acoustic signature for moduli estimation

International Journal of Pavement Research and Technology ◽

10.1007/s42947-020-6007-4 ◽

2020 ◽

Vol 13 (6) ◽

pp. 573-580

Author(s):

Salvatore Cafiso ◽

A. Di Graziano ◽

R. Fedele ◽

V. Marchetta ◽

F. Praticò

Keyword(s):

Elastic Modulus ◽

Asphalt Concrete ◽

Smart Cities ◽

Fatigue Cracks ◽

Health Condition ◽

Pavement Management ◽

The Road ◽

Road Pavement ◽

Acoustic Signature ◽

Innovative Solution

AbstractThe diffusion of smart infrastructures for smart cities provides new opportunities for the improvement of both road infrastructure monitoring and maintenance management.Often pavement management is based on the periodic assessment of the elastic modulus of the bound layers (i.e., asphalt concrete layers) by means of traditional systems, such as Ground Penetrating Radar (GPR) and Falling Weight Deflectometer (FWD). Even if these methods are reliable, well-known, and widespread, they are quite complex, expensive, and are not able to provide updated information about the evolving structural health condition of the road pavement. Hence, more advanced, effective, and economical monitoring systems can be used to solve the problems mentioned above.Consequently, the main objective of the study presented in this paper is to present and apply an innovative solution that can be used to make smarter the road pavement monitoring. In more detail, an innovative Non-Destructive Test (NDT)-based sensing unit was used to gather the vibro-acoustic signatures of road pavements with different deterioration levels (e.g. with and without fatigue cracks) of an urban road. Meaningful features were extracted from the aforementioned acoustic signature and the correlation with the elastic modulus defined using GPR and FWD data was investigated.Results show that some of the features have a good correlation with the elastic moduli of the road section under investigation. Consequently, the innovative solution could be used to evaluate the variability of elastic modulus of the asphalt concrete layers, and to monitor with continuity the deterioration of road pavements under the traffic loads.

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The Sustainability of Reclaimed Asphalt as a Resource for Road Pavement Management through a Circular Economic Model

Sustainability ◽

10.3390/su11082234 ◽

2019 ◽

Vol 11 (8) ◽

pp. 2234 ◽

Cited By ~ 8

Author(s):

Konstantinos Mantalovas ◽

Gaetano Di Mino

Keyword(s):

Asphalt Mixture ◽

Pavement Management ◽

Engineering Industry ◽

Asphalt Pavements ◽

Reclaimed Asphalt ◽

Sustainable Resources ◽

The Road ◽

Road Pavement ◽

Circularity Index ◽

Base Course

The transition of the road engineering industry to a circular way of doing business requires more efficient and sustainable resources, energy, and waste management. The rates in which reclaimed asphalt is being recycled or reused in the asphalt mixture production process constitutes a crucial parameter in this transition. This paper aims at establishing a further step towards the combined circularity and sustainability of asphalt pavements, by introducing a framework for quantifying their Material Circularity Index. The framework is based on the methodology proposed by the Ellen MacArthur Foundation and accordingly tailored for the context of asphalt pavements. This study, thus, attempts to provide a thorough analysis of the Reclaimed Asphalt’s recycling rates and trends on a European scale and to identify whether the efficiency of the current recycling practices is adequate or not. Moreover, a case study has been undertaken in order to quantify the Material Circularity index of the asphalt pavements forming Italy’s motorway network, following the proposed framework. For representative and accuracy reasons, the Material Circularity index of wearing, binder, and base courses has been calculated separately, and the results interestingly indicate that the base course exhibits the highest rates of circularity.

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Pavement Distress Detection Methods: A Review

10.20944/preprints201809.0567.v1 ◽

2018 ◽

Author(s):

Antonella Ragnoli ◽

Maria Rosaria De Blasiis ◽

Alessandro Di Benedetto

Keyword(s):

Data Collection ◽

Operating Cost ◽

Pavement Management ◽

Detection Methods ◽

Technical Improvement ◽

Pavement Condition ◽

Pavement Distress ◽

The Road ◽

Road Pavement ◽

Pavement Distress Detection

The road pavement condition affects 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 the 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, 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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RCT – a tool for continuous road pavement diagnostics

MATEC Web of Conferences ◽

10.1051/matecconf/201926205012 ◽

2019 ◽

Vol 262 ◽

pp. 05012 ◽

Cited By ~ 1

Author(s):

Marcin Staniek

Keyword(s):

Traffic Management ◽

Three Dimensional ◽

Linear Acceleration ◽

Freight Transport ◽

Related Services ◽

Pavement Condition ◽

The Road ◽

Road Pavement ◽

Pavement Monitoring ◽

Infrastructure Maintenance

The paper addresses a road pavement diagnostics solution created as a sub-module of the S-mileSys platform developed as a part the S-mile project, implemented under the “Sustainable Logistic and Supply Chain” competition of the ERANET Transport III programme. The S-mileSys solution was conceived as a means to support transport companies and their clients in planning, organisation and delivery of freight transport related services, but also to support local authorities and road administration bodies in matters related to road infrastructure maintenance and traffic management within cities or agglomerations. In principle, as typical transfers are made in connection with freight transport, the process of continuous road pavement monitoring and assessment is performed in a manner which does not involve interference of either vehicle drivers or employees of transport companies or logistics centres. The measuring system’s operation is essentially based on identification of values of linear accelerations recorded while vehicles traverse the road network. ICT solutions are used to send characteristics describing the vehicle motion dynamics, determined by the road pavement condition, to the S-mileSys system’s server, where, based on analysis of linear acceleration signals in a three-dimensional description of space and by taking GPS positioning into consideration, the current road pavement condition is estimated.

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An innovative approach for high-performance road pavement monitoring using black box

Journal of Civil Structural Health Monitoring ◽

10.1007/s13349-020-00463-8 ◽

2021 ◽

Author(s):

Monica Meocci ◽

Valentina Branzi ◽

Andrea Sangiovanni

Keyword(s):

High Performance ◽

Laser Scanning ◽

Poor Quality ◽

Vertical Acceleration ◽

Pavement Distress ◽

The Road ◽

Road Pavement ◽

Pavement Monitoring ◽

Global Condition ◽

On The Road

AbstractOne of the criteria adopted by the Word Bank with the aim of defining the economic level of a country is represented by the condition of the road pavements. To ensure adequate road pavement quality, road authorities should be continuously monitoring and repair the detected anomalies. To fast solve problems associated with poor quality of road surface such as comfort or safety, the presence of distress must be detected quickly. The high-performance pavement distress detection, such as those base on the image processing or on the laser scanning, is very expensive and does not allow to the road administration to conduct the appropriate monitoring campaigns. To solve these problems, the paper describes the pave box methodology, an innovative and immediately operational distress detection approach based on the exploitation of data collected by the black boxes located inside the vehicles that routinely pass on the road network. Data processing and the algorithms used in the post-processing evaluation of the vertical acceleration were compared with existing visual surveys procedures such as PCI. Two different indices have been proposed to detect and classify both the local damages and the global condition of the entire road. Pave box provides a robust evaluation of the pavement condition that allows to detect all the severe distress and not less than 70% of the minor damages on the pavement surface. The proposal is characterized by low time and cost consumption and it represents an effective tool for road authorities.

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