Development of Automated Pavement Condition Score and Decision Logic
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2022-02-01
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Edition:Final Report
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Abstract:The Ohio Department of Transportation (ODOT) has been collecting 3D digital data on their pavement network since 2014. This data contains a variety of information derived from 3d laser scans of the pavement. While ODOT has been using the data to meet federal HPMS reporting requirements of pavement condition, the agency wished to leverage this wealth of data to aid their pavement management system and transition from a manual pavement condition survey to an automated one. This research aims to provide ODOT a means to interpret the data and use it to make the same decisions as the existing pavement management system. Topics include analysis and development of a new rating methodology for automated distress detection and classification as well as deterioration models and decision trees for the new rating methodology. The rating system was developed using comparisons with existing manual ratings and automated data collected from 2014 through 2018. Additionally, the report covers how to implement this methodology and how it impacts pavement management decisions.
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