Pavement Distress Detection Methods: A Review

Antonella Ragnoli,Maria De Blasiis,Alessandro Di Benedetto

doi:10.3390/infrastructures3040058

Antonella Ragnoli, Maria De Blasiis + Show 1 more

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https://doi.org/10.3390/infrastructures3040058

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Journal: Infrastructures	Publication Date: Dec 19, 2018
Citations: 110	License type: CC BY 4.0

Affiliation: Sapienza University of Rome, Roma Tre University

Abstract

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.

Highlights

Road condition is an important aspect for the development of a country, it indicates the economic level and it has been adopted as rating criteria by the World Bank [1]: “the density of paved roads in good condition varies from 40 km/million inhabitants in low-income economies to 470 middle-income and 8,550 in high-income economies”
This paper aims to provide an overview of current practices and emerging technologies in order to build a solid information base for pavement management that is based on safety and comfort criteria
In order to correspond the information need, the most popular technological solutions have been considered in order to classify them according to their appropriateness in capturing road pavement data

Summary

Introduction

Road condition is an important aspect for the development of a country, it indicates the economic level and it has been adopted as rating criteria by the World Bank [1]: “the density of paved roads in good condition varies from 40 km/million inhabitants in low-income economies to 470 middle-income and 8,550 in high-income economies”. Maintaining an acceptable level of service for the whole road network, and, in particular, assessing an effective pavement maintenance and rehabilitation program is challenging for the road public authorities. Pavement Management System (PMS) is a planning tool assisting road agencies in decision-making process to efficiently maintain the road network in a timely and cost-effective manner as well as to assure comfort and safety of the users. A traditional reactive approach for pavement maintenance prescribes road replacement once significant structural damage has occurred: this approach leads to more severe and expensive rehabilitation, which can cause unsafe conditions for road users prior to the interventions, as described in [2,4,5]. Data collection and analysis phases are crucial to perform a proactive approach, fundamental or a successful PMS implementation, as reported by other authors [7,8]

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