Evaluation of Semiautomated and Automated Pavement Distress Collection for Network-Level Pavement Management

2008 ◽  
Vol 2084 (1) ◽  
pp. 11-17 ◽  
Author(s):  
Susan L. Tighe ◽  
Li Ningyuan ◽  
Tom Kazmierowski
Keyword(s):  
Pavement Management ◽  
Pavement Distress

scholarly journals Pavement Distress Detection Methods: A Review

2018 ◽  
Vol 3 (4) ◽  
pp. 58 ◽  
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.

scholarly journals Flexible Pavement Performance Evaluation in Ontario: an Overview

2021 ◽  
Author(s):  
Muzaffar Hassan
Keyword(s):  
Management System ◽  
Prediction Models ◽  
Pavement Management ◽  
Pavement Performance ◽  
Ride Quality ◽  
Physical Parameters ◽  
Pavement Management System ◽  
Pavement Condition ◽  
Pavement Distress ◽  
Verification Techniques

Measuring pavement performance is a major component of the pavement management system. It assists in decision-making for finding the optimum strategies to provide, evaluate, and maintain serviceability in an acceptable condition cost effectively. The Ontario Ministry of Transportation (MTO) has been systematically rating pavement performance since the mid-1960s. Pavement condition survey involves measurement of two physical parameters: ride quality of pavement surfaces, and the extent and severity of pavement distress manifestations. The pavement ride quality can be measured with an acceptable level of consistency and repeatability through automation. However, achieving consistency in the evaluation of pavement distress manifestations is a challenging task because the automation that could accurately and consistently detect, quantify and record surface distresses is not fully developed is spite of rapid advances in video imagery and non-contact sensing devices. This report evaluates the progress made over the past three decades in the key areas of Distress Manifestation Index, Riding Comfort Rating, Pavement Condition Index and second generation Pavement Management System (PMS2). A review of the Ministryʼs network-level pavement performance database is presented, emphasizing pavement condition surveys, prediction models and main factors influencing assessment of long-term pavement performance. Several key issues related to the quality control and quality assurance of the pavement roughness are discussed with reference to the verification techniques used by the MTO. Based on the literature review, future recommendations for possible improvements of the prediction models and techniques used for the evaluation of pavement performance are presented in order to obtain more consistent values.

Contracting for Pavement Distress Data Collection

1998 ◽  
Vol 1643 (1) ◽  
pp. 80-85 ◽  
Author(s):  
Roger E. Smith ◽  
Thomas J. Freeman ◽  
Olga J. Pendleton
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Data Collection ◽  
Pavement Management ◽  
Management Systems ◽  
Automated Data Collection ◽  
Pavement Distress ◽  
Data Collection Methods ◽  
Pavement Management Systems ◽  
Collection Methods

Many agencies responsible for managing pavements have adopted pavement management systems (PMS) to help manage their pavement networks more cost-effectively. One of the most costly parts of operating a PMS is collecting condition information, especially pavement distress information. Many agencies have started to contract for pavement distress data collection. Some of the agencies have experienced problems with the data collected by contract. A study for agencies in Washington and Oregon to define the accuracy of data needed by the agencies with an evaluation of certain participating vendors using semiautomated data collection methods is described. Issues about quality control and quality assurance faced by agencies considering contracting for automated data collection also are raised. These issues need additional study to develop appropriate guidelines. The initial set provided is based on discussions with some of the agencies currently contracting for pavement distress data collection.

Prediction of Pavement Crack Initiation from In-Service Pavements

2005 ◽  
Vol 1940 (1) ◽  
pp. 38-42 ◽  
Author(s):  
Andreas Loizos ◽  
Matthew G. Karlaftis
Keyword(s):  
Prediction Models ◽  
Climatic Factors ◽  
Pavement Management ◽  
Data Set ◽  
Pavement Distress ◽  
Stochastic Duration ◽  
Pavement Management Systems ◽  
Distress Prediction ◽  
Surface Distress

It is widely accepted that the success of pavement management systems largely depends on the quality of the deterioration models embedded in their structure. As such, much research has concentrated on developing a large array of approaches to model and predict pavement distress and deterioration. This study develops surface distress prediction models for pavement failure times (the initiation of cracking on the surface of flexible and semirigid pavements) on the basis of a large (more that 1,000 observations) and recent (1998) data set collected from in-service pavements in 15 European countries by using the principles of stochastic duration (hazard) models. The results indicate that, as expected, construction, traffic, and climatic factors affect pavement distress and that the lognormal functional form, in contrast with the findings of previous studies, best describes the distress initiation process.

Crack Development in Linear Tracking Test Pavements from Visual Survey to Pixel Analysis

1997 ◽  
Vol 1570 (1) ◽  
pp. 48-54 ◽  
Author(s):  
A. Miradi ◽  
J. Groenendijk ◽  
L. J. M. Dohmen
Keyword(s):  
Crack Pattern ◽  
Pavement Management ◽  
Digital Data ◽  
Growth Speed ◽  
Transparent Plastic ◽  
Pavement Distress ◽  
Visual Survey ◽  
Scientific Analysis ◽  
Pixel Analysis ◽  
Tracking Device

Cracking is one of the most common and important types of pavement distress. This includes structural cracking, originating at the bottom of the bound layers and growing toward the surface, and surface-originated cracking. Descriptions of cracking and its development, both for research and for pavement management and maintenance, are limited to some global nonnumerical characterization, which is not sufficient for detailed computerized analyses. The crack pattern of the linear tracking device (LINTRACK) test Lane I was originally recorded nonnumerically on photographs and transparent plastic sheets. These data were digitized to enable scientific analysis and interpretation. Crack length, crack direction, growth speed, and percentage of cracked area were calculated from the digital data.

Rebuilding the Distress Thresholds for Pavement Warranty Program in Mississippi

2019 ◽  
Vol 2673 (2) ◽  
pp. 323-334 ◽  
Author(s):  
Xiaohua Luo ◽  
Feng Wang ◽  
Ningning Wang ◽  
Jueqiang Tao ◽  
Xin Qiu ◽  
...  
Keyword(s):  
Confusion Matrix ◽  
Measurement Data ◽  
Pavement Management ◽  
Smooth Transition ◽  
Random Errors ◽  
Pavement Distress ◽  
Practical Procedure ◽  
Pavement Distresses ◽  
System Data ◽  
Pavement Construction

Pavement warranty is an innovative contracting procedure increasingly adopted by state transportation agencies to protect investment in pavement construction and maintenance. In Mississippi, the pavement warranty program was initiated in 2000 and the pavement distress thresholds were set based on the deduct points calculated by conversion equations from distress measurements of unacceptable pavement conditions. The conversion of distress measurements into deduct points using empirically regressed conversion equations has been questioned, however, on the grounds that it actually reduces the accuracy of the objective distress measurements by adding subjective and random errors. Moreover, the validity and applicability of continual use of these conversion equations has become problematic with time, because the equations were empirically developed in the 1990s, reflecting the data, experience, and technologies at that time. This research aims to develop analytically new distress thresholds based on direct measurements of pavement distresses for the pavement warranty program in Mississippi. The bootstrapping method was employed to process the skewed historical distress measurement data into normal distributions. The upper bound of confidence interval or standard deviations of the normalized distress measurement data was determined as an alternative method to rebuild the threshold for each distress type. The confusion matrix was employed to consider a smooth transition of updating the thresholds from the current deduct point based system to a new measurement based system. This study provides a practical procedure for developing a set of measurement based thresholds to renew the pavement warranty program using the available pavement management system data.

scholarly journals HDM-4 Deterioration Modelling: Validation and Adoption for Flexible Pavements With Modified Bituminous Road Surfacing

2019 ◽  
Vol 14 (2) ◽  
pp. 208-226
Author(s):  
Sanjay Deori ◽  
Rajan Choudhary ◽  
Devesh Tiwari ◽  
Abhinay Kumar
Keyword(s):  
High Speed ◽  
Time Series Data ◽  
Asphalt Binder ◽  
Pavement Management ◽  
Series Data ◽  
Local Conditions ◽  
Pavement Distress ◽  
Pavement Deterioration ◽  
Modified Asphalt Binder ◽  
Student’S T

Highway Development and Management (HDM-4) is an internationally recognised tool to analyse pavement management and investment alternatives. The HDM-4 pavement deterioration models help to predict the initiation and progression of various pavement distresses under the different combinations of traffic, climate, pavement structure, and composition. Since the rate of initiation and propagation of each pavement distress is strongly dependent on local conditions, it is essential to calibrate and validate the HDM-4 models for local conditions before their use. Validation of the calibrated HDM-4 pavement deterioration models is needed to check the adequacy of the calibration factors before the model is put to use for future applications. Time series data collected consecutively for three years of 23 high-speed corridors sections constructed with modified binders in India was used to calibrate the HDM-4 distress models. The main aim of this paper is to discuss the validation aspects of the calibrated HDM-4 models, to compare the distresses predicted to those observed on test sections. In this study, a novel technique termed the “proximity to the line of equality” approach is used to validate the HDM-4 models. In addition, Student’s t-test is also used as a conventional validation technique. The advantage of the “proximity to the line of equality” approach is that it removes subjectivity associated with judging the nearness of best-fit straight line of predicted-observed data to the line of equality. Validation results show that distresses predicted by HDM-4 are statistically similar to those observed on the sections. Therefore, the calibrated HDM-4 models can be adopted for planning future maintenance strategies for flexible pavement sections with modified asphalt binder road surfacing.

scholarly journals Pavement Distress Detection Methods: A Review

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.

scholarly journals Flexible Pavement Performance Evaluation in Ontario: an Overview

2021 ◽  
Author(s):  
Muzaffar Hassan
Keyword(s):  
Management System ◽  
Prediction Models ◽  
Pavement Management ◽  
Pavement Performance ◽  
Ride Quality ◽  
Physical Parameters ◽  
Pavement Management System ◽  
Pavement Condition ◽  
Pavement Distress ◽  
Verification Techniques

Measuring pavement performance is a major component of the pavement management system. It assists in decision-making for finding the optimum strategies to provide, evaluate, and maintain serviceability in an acceptable condition cost effectively. The Ontario Ministry of Transportation (MTO) has been systematically rating pavement performance since the mid-1960s. Pavement condition survey involves measurement of two physical parameters: ride quality of pavement surfaces, and the extent and severity of pavement distress manifestations. The pavement ride quality can be measured with an acceptable level of consistency and repeatability through automation. However, achieving consistency in the evaluation of pavement distress manifestations is a challenging task because the automation that could accurately and consistently detect, quantify and record surface distresses is not fully developed is spite of rapid advances in video imagery and non-contact sensing devices. This report evaluates the progress made over the past three decades in the key areas of Distress Manifestation Index, Riding Comfort Rating, Pavement Condition Index and second generation Pavement Management System (PMS2). A review of the Ministryʼs network-level pavement performance database is presented, emphasizing pavement condition surveys, prediction models and main factors influencing assessment of long-term pavement performance. Several key issues related to the quality control and quality assurance of the pavement roughness are discussed with reference to the verification techniques used by the MTO. Based on the literature review, future recommendations for possible improvements of the prediction models and techniques used for the evaluation of pavement performance are presented in order to obtain more consistent values.

scholarly journals Towards Low-Cost Pavement Condition Health Monitoring and Analysis Using Deep Learning

2020 ◽  
Vol 10 (1) ◽  
pp. 319 ◽  
Author(s):  
Ronald Roberts ◽  
Gaspare Giancontieri ◽  
Laura Inzerillo ◽  
Gaetano Di Mino
Keyword(s):  
Deep Learning ◽  
Low Cost ◽  
Road Networks ◽  
Integrated Approach ◽  
Pavement Management ◽  
Management Systems ◽  
Hotspot Analysis ◽  
Pavement Distress ◽  
Industry Standards ◽  
Pavement Management Systems

Governments are faced with countless challenges to maintain conditions of road networks. This is due to financial and physical resource deficiencies of road authorities. Therefore, low-cost automated systems are sought after to alleviate these issues and deliver adequate road conditions for citizens. There have been several attempts at creating such systems and integrating them within Pavement management systems. This paper utilizes replicable deep learning techniques to carry out hotspot analyses on urban road networks highlighting important pavement distress types and associated severities. Following this, analyses were performed illustrating how the hotspot analysis can be carried out to continuously monitor the structural health of the pavement network. The methodology is applied to a road network in Sicily, Italy where there are numerous roads in need of rehabilitation and repair. Damage detection models were created which accurately highlight the location and a severity assessment. Harmonized distress categories, based on industry standards, are utilized to create practical workflows. This creates a pipeline for future applications of automated pavement distress classification and a platform for an integrated approach towards optimizing urban pavement management systems.

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