United States Department of Transportation
i
LTPP Data Analysis: Optimization of Traffic Data Collection for Specific Pavement Design Applications
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2006-08-01
[PDF-243.65 KB]
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Abstract:Traffic loads are an essential input to the pavement analysis and design process. In the past, the impact of traffic was aggregated into equivalent single-axle loads and input into regression-based pavement performance equations. The recently developed Mechanistic-Empirical Pavement Design Guide (M-E PDG) (NCHRP 1-37A) characterizes traffic in terms of axle numbers by type and load frequency distribution, including axle load spectra. This is a significant improvement over past methods because it allows for a mechanistic pavement design approach.
Traffic data collection is carried out using several data acquisition technologies, including weigh in motion (WIM) systems, automated vehicle classifiers (AVC), and automated traffic recorders (ATR). The data coverage of traffic data acquisition systems can vary widely from operating continuously to providing simple 48-hour data coverage. Hence, there is wide variation in the characteristics of traffic data used for designing pavements.
The challenge for both pavement design and traffic engineers is to determine the combination of traffic data acquisition technology and the amount of time coverage required for particular pavement design situations outlined in the M-E PDG. The problem needs to be addressed in light of the sensitivity of pavement design and performance to the level of traffic data input. Understanding this sensitivity will allow for the optimization of traffic data collection resources allocated for pavement design processes.
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