Hierarchical methodology to evaluate the quality of disparate axle load data sources for pavement design

Quality axle load data are an essential input for pavement design, yet for most North American agencies, there is uncertainty about the quality of axle load data obtained from weigh-in-motion (WIM) systems, the applicability of these data for pavement design, and potential opportunities to integrate axle load data from disparate sources. This article presents a novel and practical methodology to evaluate the quality of axle load data from WIM systems and roadside weigh scales through a series of hierarchical analyses designed to test data validity. When applied using data from Manitoba, Canada, the methodology quantified the uncertainty of axle loads measured at the weigh scales and piezo-quartz WIM, concluding that both could be used for pavement design applications. Data collected at piezo-polymer WIM sites exhibited poorer data validity; however, application of site-specific temperature correction factors significantly improved data validity at these sites. The article describes how other data quality dimensions, including spatial coverage, temporal coverage, and long-term data availability, could be considered when determining the suitability of disparate axle load data sources for pavement design.

Language

  • English

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Filing Info

  • Accession Number: 01843427
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Apr 25 2022 10:06AM