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Standard Definitions for Common Types of Pavement Cracking 1 C H A P T E R 1 Introduction Background Pavements are a critical part of our nationâs transportation infrastructure. As reported by the American Society of Civil Engineers (ASCE), 21% of the nationâs highways had poor pavement condition in 2015; driving on roads in need of repair cost the United States (U.S.) motorists $120.5 billion in extra vehicle repairs and operating costs or $533 per driver (ASCE 2018). Therefore, road surface condition should be properly evaluated, along with accurate and timely defect detection. An effective pavement management system (PMS) requires reliable pavement condition data for forecasting future conditions, providing project and treatment recommendations, and determining budget needs (AASHTO 2012). Pavement performance prediction models require accurate historical cracking data, which is one of the primary components of a pavement condition survey. In recent years, there has been a growing need for high-quality cracking data to assist local calibration of the American Association of State Highway and Transportation Officials (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG) and accompanying software, AASHTOWare Pavement ME Designâ¢, to meet the new data reporting requirements for the Federal Highway Administration (FHWA) Highway Performance Monitoring System (HPMS) and relevant performance measures, and in support of asset management. Cracking data are collected and processed through pavement condition surveys using manual, semi-automated, or fully automated approaches (Kulkarni and Miller 2003, Timm and McQueen 2004, Attoh-Okine and Adarkwa 2013). Manual surveys are considered to be visual assessments of pavement conditions conducted by one or more individuals who inspect the pavement surface through the windshield of a vehicle or by walking along the roadway. However, this method can be subjective, inconsistent, error-prone, labor and time-consuming, and unsafe to the field crew and travelling public (Attoh-Okine and Adarkwa 2013, Wang 2011). More recently, agencies are moving toward automated condition surveys using highway-speed vehicular system consisting of lasers, digital cameras, and other supporting platforms to record pavement surface images and measure transverse and longitudinal roadway profiles. Automated survey systems, with varying data resolutions and methods, are becoming popular with State Highway Agencies (SHAs) to collect pavement cracking along with other condition data at the network and project levels (Wang 2011, Wix and Leschinski 2013, Laurent et al. 2012, Daleiden et al. 2015, Mathison 2016). The transition to automated surveys is primarily due to advantages in safety and efficiency, potentially improved data consistency and repeatability, and high-resolution cracking
Standard Definitions for Common Types of Pavement Cracking 2 data for full lane coverage (Wang and Smadi 2011, Offrell et al. 2005, Henning and Morrow 2017). Three-dimensional (3D) laser imaging technology has also gained popularity and is able to detect crack widths with 1-mm resolution (Wang 2011, Laurent et al. 2012). Despite significant advances in sensor and computer hardware and software for pavement image acquisition and interpretation, the transition from manual surveys to image-based automated distress detection and quantification is often problematic (Mraz et al. 2006, Lee and Kim 2005, Wang and Gong 2006, McGhee 2004, McQueen and Timm 2005, Albitres et al. 2007, Pierce et al. 2013). A reason for this difficulty is the incompatibility between traditional distress definitions based on manual observation and capabilities of modern computer-based automated survey and processing. In traditional surveys, raters visually judge the presence of pavement cracking, classify cracking into predefined categories, evaluate the severity of each type of cracking, and finally quantify and record the cracking extent (length) at each severity level (e.g., low, medium, high). Many SHAs have adopted some elements of the FHWA Distress Identification Manual for the Long-Term Pavement Performance (LTPP) Program (LTPP Distress Manual) or the American Society of Testing and Materials (ASTM) D6433 Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys, commonly known as the Pavement Condition Index (PCI) (FHWA 2014, ASTM 2016). Both the LTPP Distress Manual and the ASTM PCI distress data collection approaches were initially developed for manual surveys and did not consider the use of automated processing. More recently, AASHTO initiated the development of crack protocols for automated systems. The Provisional Standard, AASHTO R 85-18, Quantifying Cracks in Asphalt Pavement Surfaces from Collected Pavement Images Utilizing Automated Methods, outlines the procedures for quantifying cracking distress for asphalt pavement at the network level (AASHTO 2018). The protocol for collecting image data for distress detection is described in AASHTO R 86-18, Collecting Images of Pavement Surfaces for Distress Detection (AASHTO 2018). The protocols were developed based on engineering wisdom of the cracking data collection community, and in recent years they have been the basis for some agencies to transition from human-rater-oriented distress measurements toward computer-oriented distress quantification. However, some definitions in the protocols are difficult to be implemented in practice or for automated data collection systems. Building upon work accomplished in AASHTO R 85-18 and R 86-18, additional research is needed to define cracking measurement terms and relevant processes for uniformity, standardization, and automation. Many state and local agencies used variations of the LTPP Distress Manual and ASTM D6433 definitions, resulting in variability in the way distress information is collected and reported. Some SHAs developed their distress identification manuals either as a stand-alone reference or as a supplement to the LTPP Distress Manual or ASTM standards. There is also a multitude of methods and software programs for defining, classifying, and reporting cracking data. In recent years, several agencies have developed pavement distress protocols to accommodate applications of automated data collection systems, such as California Department of Transportation (Caltrans), Florida Department of Transportation (DOT), and Virginia DOT (Caltrans 2015, FDOT 2017, VDOT 2012). However, these methods and the cracking data they produce are not
Standard Definitions for Common Types of Pavement Cracking 3 always comparable among agencies. Vendors must customize the cracking definitions for each client they serve. In order to unify data reporting, sharing, and evaluation, standardization of pavement cracking definitions is needed. With the changes in the HPMS requirements, the performance measures in the Moving Ahead for Progress in the 21st Century Act (MAP-21) and the Fixing Americaâs Surface Transportation (FAST) Act rulemaking, and the need for high-quality cracking data for the calibration of performance models in the Pavement ME Designâ¢ procedure, standardization of pavement cracking definitions for automated technologies is also needed to allow data reporting, sharing, and evaluation. Furthermore, there is a need to define user and system requirements to aid the future development of production-grade evaluation software for classifying cracking type, extent, and severity. The standard cracking definitions will aid in improving precision and bias levels of future automated systems as well as reporting to national organizations, such as the FHWA. Results of future automated cracking processing for all agencies who adopt the standard will be comparable and multi-year distress data can produce trustworthy performance data for both pavement design and pavement management purposes. The objective of National Cooperative Highway Research Program (NCHRP) project 01-57A is to develop standard, discrete definitions for common cracking types for asphalt and concrete pavements. The new definitions will help pavement cracking survey providers and pavement engineers at SHAs conduct objective cracking measurements and encourage continuing technological innovations by researchers and vendors. The standard definitions shall be used to facilitate comparable measurement and interpretation of pavement cracking. The definitions shall be of sufficient details to serve as the basis to meet user and system requirements for developing automated cracking software, and for being compatible with both existing and emerging image- based data collection technologies. The new definitions will be primarily tailored for network level surveys with the hope that successful implementations of the definitions will directly help the application of new technologies at the project level. Report Outline This report documents the work performed in the NCHRP 01-57A project and is organized as follows: ï· Chapter 1 introduces the background and objectives of this report. ï· Chapter 2 delivers a summary of cracking data collection practices and data protocols through a comprehensive literature review and survey of SHAs. ï· Chapter 3 conducts a review of the role of cracking data in decision-making processes. ï· Chapter 4 summarizes the cracking data desired by SHAs. ï· Chapter 5 proposes a standard cracking definition based on the results from previous work. ï· Chapter 6 lists field data collection and validation of the proposed cracking definitions. ï· Chapter 7 provides the conclusions and recommendations of this report.