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1  The assessment of pavement surface conditions has evolved over the past decade from manual to semiautomated to fully automated methods. Automated pavement condition surveys (APCSs) provide the opportunity to assess the current health of the pavement sur- face, including cracking, rutting, faulting, and roughness. The transition from manual to fully automated methods allows for 100% coverage of the roadway surface, collection at posted highway speeds, and improved safety conditions; however, agencies are faced with assessing the impacts the results from automated data collection may have on pavement management activities (e.g., index calculations, reporting). Federal regulations [23 CFR 490 National Performance Management Measures (PM2)] require state highway agencies (SHAs) to report pavement condition and to establish pave- ment performance targets for the Interstate highway system and the non-Interstate National Highway System. In providing information on pavement condition, the majority of agencies have already transitioned from manual to automated pavement condition surveys. While agencies gain more data, knowledge, and experience with APCSs, this migration also brings new challenges, due in large part to the rapidly evolving technology, including data quality control and acceptance, data analysis methods, and impacts on decision-making. The objectives of this synthesis are to document the experiences, challenges, and state-of- the-practice solutions used by SHAs that are in the midst of transitioning or have already transitioned to automated or semiautomated processes for collecting pavement data and to summarize the data for state and federal requirements for reporting pavement condition. This synthesis is based on the combined results of a literature review of agency practices and reporting requirements in collecting pavement condition data and a questionnaire of U.S. SHAs. In total, 48 of 52 agencies surveyed responded to the questionnaire (total response rate of 92%). Of the 48 responding agencies, 46 indicated the use of fully automated, semiautomated, or a combination of semi- and fully automated methods for quantifying pavement condition. More than half the agencies reported using automated methods for 10 or more years. All agencies quantify the international roughness index, rutting, faulting, and percent cracking as part of the pavement condition survey. To meet PM2 requirements, the majority of agencies (42 agencies) had developed or updated a data quality management plan for pavement condition; developed data quality control requirements and procedures (29 agencies); established control, verification, and/or blind site sections (27 agencies); and established requirements and procedures for data acceptance (26 agencies). Agency challenges with meeting PM2 reporting requirements S U M M A R Y Automated Data Collection and Quality Management for Pavement Condition Reporting
2 Automated Data Collection and Quality Management for Pavement Condition Reporting included establishing agency performance targets (22 agencies), determining baseline con- ditions (15 agencies), and needing to adjust targets (12 agencies). In relation to implementation of an APCS, agencies indicated the need to assess data quality issues (24 agencies), modify pavement condition index and/or rating calculations (20 agencies), and modify existing pavement distress definitions (19 agencies). Noted chal- lenges with implementing APCSs included validating and verifying data quality (30 agencies); obtaining consistent, year-to-year results (22 agencies); managing the difference in results as compared with manual surveys (19 agencies); and integrating the results into the pave- ment management system (18 agencies). A number of noted benefits of APCSs included the ability to collect data compatible with the Highway Performance Monitoring System and PM2 reporting (36 agencies); increased rater safety (31 agencies); the ability to collect sensor and distress data with a single device (30 agencies); and the ability to easily track, review, and reproduce historical data and images (28 agencies). Areas of future research include improving methods for identifying surface irregularities (e.g., raveling, weathering, and spalling), improving the methods for quantifying faulting in jointed plain concrete pavements, assistance with the implementation of the recently developed universal APCS data format, and conducting a synthesis of local agency and metropolitan planning organization efforts with transitioning to APCSs.
