National Academies Press: OpenBook

Automated Pavement Condition Surveys (2019)

Chapter: Summary

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Suggested Citation:"Summary." National Academies of Sciences, Engineering, and Medicine. 2019. Automated Pavement Condition Surveys. Washington, DC: The National Academies Press. doi: 10.17226/25513.
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Suggested Citation:"Summary." National Academies of Sciences, Engineering, and Medicine. 2019. Automated Pavement Condition Surveys. Washington, DC: The National Academies Press. doi: 10.17226/25513.
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1 Pavement condition data are critical components of all pavement management systems. The accuracy and validity of pavement condition data are crucial for assessing existing and future pavement condition, establishing budget needs, evaluating budget impacts, supporting asset management, and selecting projects for pavement maintenance and rehabilitation. The Fixing America’s Surface Transportation (FAST) Act requires state highway agencies to report pavement condition on the National Highway System (NHS). Pavement condition reporting for the FAST Act includes the International Roughness Index (IRI), rut depth, and percent cracking for asphalt pavements (top-most surface is constructed with asphalt materials); IRI, percent cracking, and faulting for jointed plain concrete pavement; and IRI and percent cracking for continuously reinforced concrete pavement. The FAST Act also requires agencies to report pavement condition based on 0.1-mi (0.16-km) intervals. This interval of data reporting can be cost-effectively achieved only by using automated pavement condition data collection systems. Highway agency use of automated data collection systems has greatly increased over the last several decades, in part due to significant advancements in data collection technology. For example, rut-depth measurements have progressed from three (or five) profile sensors to systems capable of capturing continuous cross-profile measurements and from high-speed video images to three-dimensional imaging of the roadway surface. As the number of agencies using automated pavement condition surveys has also increased, it is important to capture agency experiences with implementation of automated pavement condition data collection. Documentation of agency automated data collection procedures and processes will be beneficial to agencies moving toward (or with limited experience regarding) auto- mated pavement data collection. The objective of this synthesis is to document agency practices, challenges, and successes in conducting automated pavement condition surveys. The study is intended to showcase successful practices, integration of automated data into pavement management systems, and efforts needed for reporting pavement condition according to the FAST Act. This synthesis is based on the results of a literature review of agency automated pave- ment condition data collection and analysis efforts, a survey of highway transportation agencies (U.S. highway agencies and Canadian provincial and territorial governments), and follow-up questions with agencies experienced with automated pavement condition surveys. In total, 57 highway transportation agencies (46 American and 11 Canadian) pro- vided responses to the agency survey (a total response rate of 90 percent). Of the 57 agencies that responded to the survey, 45 indicated using automated data collection methods exclusively, six agencies indicated using both manual and automated S U M M A R Y Automated Pavement Condition Surveys

2 Automated Pavement Condition Surveys condition surveys, and six agencies indicated using only manual pavement condition surveys. Of the agencies that use only automated condition surveys, about half of the agencies use fully automated analysis and about half of the agencies use both semi- and fully automated analysis. There was also an equal distribution of agencies that collect and analyze data using purchased equipment and in-house staff (16 responses), hire a vendor to conduct both data collection and analysis (16 responses), and use a combina- tion of agency and vendor data collection and analysis (16 responses). With the advent of identifying roadside appurtenances using the automated data collection vehicle, a number of agencies indicated the collection and assessment of secondary assets. Ten agencies indicated collecting and analyzing a wide variety of appurtenances, including, for example, shoulder condition, bridge, railroad crossing, utility locations, traffic signals, signs, guard- rail, and pavement markings. As required by the FAST Act, U.S. highway agencies must report pavement and bridge condition on all Interstate and non-Interstate roadways as part of the NHS. In addition, the FAST Act requires U.S. highway agencies to develop and implement pavement condition data quality management plans. The data quality management plans provide a process by which agencies can ensure pavement condition data are of high quality and representative of field conditions. The requirements of the data quality management plans include pro- cedures for data collection equipment calibration and certification; processes for certifying persons conducting manual data collection; quality-control measures before and during data collection; data sampling, review, and checking processes; and error resolution and data acceptance criteria. In total, 33 agencies provided copies of their data quality management plans, and information from these plans was used in the development of this synthesis. To further illustrate agency automated data collection practices, three agency case examples were developed covering the data quality management plans (or approaches) for the highway transportation agencies of British Columbia, Pennsylvania, and North Dakota. The agency case examples were developed using information provided by each agency in the agency survey, supplemented with follow-up questions and a review of agency-provided documents. The technology associated with automated pavement condition data collection and analysis has undergone a number of significant changes over the past 20 years, and successes and challenges have been noted. On the success side, automated condition surveys provide a safer, faster, more time-effective data collection effort; more consistent data; and the ability to successfully extract appurtenance information from the right-of-way images. Challenges with automated data collection include standardizing the method for quantifying distress, integrating a linear reference system into existing agency programs, quantifying more challenging distress types (e.g., patching, potholes, raveling, bleeding), and maintaining consistent distress ratings from year to year and when switching vendors. Although the technology of automated data collection surveys has provided vast improvements in assessing pavement condition, there remain a number of issues that require further investigation. This includes staff training; standardization of equipment, methods, algorithms, and reporting; establishing region certification facilities; improving the accuracy of crack detection; establishing protocols and staff certification for semi- automated surveys; and establishing user groups (including agencies and vendors) to discuss issues, successes, and resolutions.

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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.

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