Automated Pavement Condition Data Collection Quality Control Quality Assurance And Reliability
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Automated Pavement Condition Data Collection Quality Control Quality Assurance And Reliability
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Author : Ghim Ping Ong
language : en
Publisher: Purdue University Press
Release Date : 2009-06-01
Automated Pavement Condition Data Collection Quality Control Quality Assurance And Reliability written by Ghim Ping Ong and has been published by Purdue University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-01 with Transportation categories.
In recent years, state highway agencies have come to understand the need for high quality pavement condition data at both the project and network levels. At the same time, agencies also realize that they have become too dependent on contractors to ensure the quality of the delivered data without any means to independently assure the quality of these data. This research study therefore aims to investigate the inherent variability of the automated data collection processes and proposes guidelines for an automated data collection quality management program in Indiana. In particular, pavement roughness data (in terms of IRI) and pavement surface distress data (in terms of PCR and individual pavement surface distress ratings) are considered in this study. Quality control protocols adopted by the contractor are reviewed and compared against industry standards. A complete quality control plan is recommended to be adopted for all phases of the data collection cycle: preproject phase, data collection phase, and post-processing phase. Quality assurance of pavement condition data can be viewed in terms of (i) completeness of the delivered data for pavement management; (ii) accuracy, precision and reliability of pavement roughness data; and (iii) accuracy, precision and reliability of individual distress ratings and an aggregate pavement condition rating. An innovative two-stage approach is developed in this study to evaluate delivered data for integrity and completeness. Different techniques and performance measures that can be used to evaluate pavement roughness and pavement surface distress data quality are investigated. Causes for loss in IRI and PCR accuracy and precision are identified and statistical models are developed to relate project- and network-level IRIs and PCRs. Quality assurance procedures are then developed to allow highway agencies improve their pavement condition data collection practices and enhance applications in the pavement management systems.
Quality Management Of Pavement Condition Data Collection
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Author : Gerardo W. Flintsch
language : en
Publisher: Transportation Research Board
Release Date : 2009
Quality Management Of Pavement Condition Data Collection written by Gerardo W. Flintsch and has been published by Transportation Research Board this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Technology & Engineering categories.
Practical Guide For Quality Management Of Pavement Condition Data Collection
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Author : Linda M. Pierce
language : en
Publisher:
Release Date : 2013
Practical Guide For Quality Management Of Pavement Condition Data Collection written by Linda M. Pierce and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Pavements categories.
Pavement Management System Review
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Author :
language : en
Publisher:
Release Date : 2009
Pavement Management System Review written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Pavements categories.
Data Integration For Pavement
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Author : Majed Alinizzi
language : en
Publisher:
Release Date : 2017-12-15
Data Integration For Pavement written by Majed Alinizzi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-15 with categories.
This study was in two parts. The first part established and demonstrated a framework for pavement data integration. This is critical for fulfilling QC/QA needs of INDOT¿s pavement management system, because the precision of the physical location references is a prerequisite for the reliable collection and interpretation of pavement data. Such consistency is often jeopardized because the data are collected at different years, and are affected by changes in the vendor, inventory, or referencing system or reference points. This study therefore developed a ¿lining-up¿ methodology to address this issue. The applicability of the developed methodology was demonstrated using 2012-2014 data from Indiana¿s highway network. The results showed that the errors in the unlined up data are significant as they mischaracterize the true pavement condition. This could lead to the reporting of unreliable information of road network condition to the decision makers, ultimately leading to inappropriate condition assessments and prescriptions. Benefits of the methodology reverberate throughout the management functions and processes associated with highway pavements in Indiana, including pavement performance modeling, optimal timing of maintenance, rehabilitation, and reconstruction (MRR), and assessment of the effectiveness of MRR treatments and schedules.The second part of the study developed correlations for the different types of pavement distresses using machine learning algorithms. That way, the severity of any one type of distress can be estimated based on known severity of other distresses at that location. The 2012-2014 data were from I-70, US-41, and US-52, and the distress types considered are cracking, rutting, faulting, and roughness. Models were developed to relate surface roughness (IRI) to pavement cracks, and between the different crack types, with resulting degrees of confidence that varied across the different crack types and road functional classes. In addition, for each functional class and for each crack type, models were built to relate crack depth to crack width. The concept can be applied to other distress types, such as spalling, bleeding, raveling, depression, shoving, stripping, potholes, and joint distresses, when appropriate data are available.
Automated Data Collection And Quality Management For Pavement Condition Reporting
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Author : Linda M. Pierce
language : en
Publisher:
Release Date : 2022
Automated Data Collection And Quality Management For Pavement Condition Reporting written by Linda M. Pierce and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Pavements categories.
Automated collection of pavement data allows agencies to collect data on pavement health, including cracking, rutting, faulting, and roughness, at highway speeds. This provides important information for better pavement decision-making. The TRB National Cooperative Highway Research Program's NCHRP Synthesis 589: Automated Data Collection and Quality Management for Pavement Condition Reporting documents the experiences, challenges, and state-of-the-practice solutions used by state departments of transportation that are in the midst of transition or that have transitioned to automated and semiautomated processes for collecting pavement data. It also summarizes the data for state and federal reporting requirements, such as Transportation Asset Management Plans and MAP-21.
Automated Pavement Distress Collection Techniques
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Author : Kenneth H. McGhee
language : en
Publisher: Transportation Research Board
Release Date : 2004
Automated Pavement Distress Collection Techniques written by Kenneth H. McGhee and has been published by Transportation Research Board this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Automatic data collection systems categories.
At head of title: National Cooperative Highway Research Program.
Automated Pavement Condition Surveys
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Author : Linda M. Pierce
language : en
Publisher:
Release Date : 2019
Automated Pavement Condition Surveys written by Linda M. Pierce and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Pavements categories.
TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 531 documents agency practices, challenges, and successes in conducting automated pavement condition surveys. The report also includes three case examples that provide additional information on agency practices for conducting automated pavement surveys. Pavement condition data is a critical component for pavement management systems in state departments of transportation (DOTs). The data is used to establish budget needs, support asset management, select projects for maintenance and preservation, and more. Data collection technology has advanced rapidly over the last decade and many DOTs now use automated data collection systems.
Practical Guide For Quality Management Of Pavement Condition Data Collection
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Author : U.s. Department of Transportation
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-07-23
Practical Guide For Quality Management Of Pavement Condition Data Collection written by U.s. Department of Transportation and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-23 with categories.
Practical guide for quality management of pavement condition data collection /
Evaluation Of Automated Pavement Condition Data Collection Equipment
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Author : Kandiah Jeyapalan
language : en
Publisher:
Release Date : 1986
Evaluation Of Automated Pavement Condition Data Collection Equipment written by Kandiah Jeyapalan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Aerial photography in road surveying categories.