United States Department of Transportation
i
Improve Data Quality for Automated Pavement Distress Data Collection [Project Summary Report]
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2024-08-31
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[PDF-284.37 KB]
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Abstract:The study commenced with a comprehensive review of the existing literature combined with a questionnaire survey that focused on the evaluation of prevailing automated pavement condition data collection techniques. The primary objective was to identify potential strategies for enhancing data quality and operational efficiency, drawing insights from various state highway agencies. Furthermore, an in-depth analysis was conducted on historical pavement condition data obtained from 25 districts and three distinct pavement types spanning a period of four years. This analysis involved statistical examinations of key influencing factors, assessments of accuracy and precision utilizing diverse methodologies, and individual distress evaluations across different pavement types. Additionally, the researchers delved into the utilization of stratified sampling methods to optimize the data quality audits, particularly in scenarios characterized by significant variability among population units. Subsequently, a set of data quality assurance indexes were chosen, thresholds were established, and procedures were developed to facilitate the consistent assessment of pavement condition data quality. A pilot study conducted in the San Antonio district served to validate the proposed data quality assurance framework, showcasing its efficacy in pinpointing sections with potential data quality issues. To further validate the suggested data quality thresholds and procedures, a raw image inspection of the roadway sections was carried out.
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