Browsing by Author "Morian, Dennis A."

Now showing 1 - 2 of 2
  • Thumbnail Image
    A Case Study in Establishing Quality Assurance Limits for Automated Pavement Distress Data in North Carolina
    Frith, Douglas J.; Stoffels, Shelley M.; Mastin, J. Neil; Morian, Dennis A. (2015-06-04)
    The North Carolina Department of Transportation (NCDOT) began collecting automated pavement distress data on a state-wide basis in 2012. Concurrently, they contracted the quality assurance reviews of the reported pavement distress to an independent source. This paper discusses the means and methods utilized by NCDOT and the quality assurance contractor to develop statistically valid quality assurance limits, which are also meaningful in terms of pavement management decision-making impacts, for the collected and processed asphalt pavement distress data. The paper describes the strategic selection of control sections to include a range and mix of the distresses with impact in the current decision trees, the data collection on the control sections, the rating methodology, and the rater pools and preparation to develop predicted limits for the control of the data. The paper discusses the consideration of multiple control indices, and the need to also reflect a range of values for those aggregate indices for multiple distresses, and presents the statistical analysis from the asphalt concrete control sites.
  • Thumbnail Image
    Ten Years of Pavement Distress Independent Verification & Validation (IV&V) in Virginia
    Frith, Douglas J.; Shekharan, Raja A.; Morian, Dennis A.; Chowdhury, Tanveer (2015-06-04)
    High quality data is essential in a pavement management process for achieving the objective of accurately reporting the existing network conditions, recommending maintenance and rehabilitation activities, developing performance models, and predicting the future network condition. The Virginia Department of Transportation (VDOT) has required an independent verification and validation (IV&V) of the automated distress data collection process since the early 2000s. The IV&V process includes both quality control and quality assurance activities. The process of IV&V has been effective in identifying systematic errors, correcting those, and in taking steps to prevent further recurrence of such errors. At the same time, it insures that random errors are kept to a minimum. At this time the process has been applied to 10 data collection cycles using pavement monitoring information collected by a single vendor using automated data collection equipment and a semi-automated rating process. Results of this process are presented in this paper. Two pavement distress indices used by VDOT, the Load Distress Rating and the Non-Load Distress Rating have been closely controlled for each data collection cycle. As shown in the paper, there is an indication of data quality enhancement over time as well as a stabilization of the variability in the data from one year to the next. The paper also includes a summary of several significant issues that should be considered in any data quality effort.