Abstract

3D pavement data are increasing in use and availability and open up new opportunities to evaluate variability in pavements. The majority of information we currently have on existing pavements is the result of the Long Term Pavement Performance Program (LTPP). While the program is comprehensive and the data are immense, the study sections are typically only 500 ft in length, which limits the ability to accurately gauge the variability of the distresses in a pavement over a longer length, especially cracking in Jointed Plain Concrete (JPC) slabs. 3D pavement data already collected by transportation agencies have the opportunity to complement LTPP data to analyze variability and improve the use of LTPP data. This paper presents a unique method to complement LTPP data using 3D pavement data, consisting of four steps: (1) crack detection using 3D pavement data; (2) categorize detected cracks by orientation and extent by slab using 3D slab-based methodology; (3) convert categorized slab level cracking into mechanistic-empirical pavement design guide cracking; and (4) perform local calibration with the 3D converted input values. The method uses 3D pavement data to provide a non-discrete value for percent cracking in GPS-3 LTPP sections for the purposes of local calibration. The proposed method is shown to be feasible using 3D pavement data and two JPC LTPP sections in Georgia. The method could be extended to any of the state Departments of Transportation that have active LTPP sections and are now or will shortly be collecting 3D pavement data.

Full Text
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