Characterization and Development of Truck Load Spectra and Growth Factors for Current and Future Pavement Design Practices in Louisiana [Final Report]
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Characterization and Development of Truck Load Spectra and Growth Factors for Current and Future Pavement Design Practices in Louisiana [Final Report]

  • 2011-07-01

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      Final report; Mar. 31, 2007-Mar. 31, 2009.
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    • Abstract:
      For pavement design practices, several factors must be considered to ensure good pavement performance over the anticipated life cycle. Such factors include, but are not limited to, the type of paving materials, traffic loading characteristics, prevailing environmental conditions, and others. Traditional pavement design practices have followed the standards set by the American Association of State Highway and Transportation Officials (AASHTO) which require the use of an equivalent single axle load (ESAL), 18 kip single axle load, for design traffic input. The new mechanistic-empirical pavement design guide (MEPDG) was developed to improve pavement design practices. The guide, however, requires the development of truck axle load spectra, which are expressed by the number of load applications of various axle configurations (single, dual, tridem, and quad) within a given weight classification range. This raises the need for more axle load data from new and existing traffic data sources. Such additional data requirements pose a challenge for many states including Louisiana. This research study was conducted for LADOTD to address traffic data needs and requirements for the adoption of the new pavement design guide. The study reviewed current practices of traffic data collection processes adopted by LADOTD as well as existing and newly proposed traffic data collection procedures followed by other states. The study developed a strategic plan for Louisiana to meet the MEPDG traffic data requirements. Two alternative plans were proposed for the addition of new permanent Weigh-in-Motion (WIM) stations on major truck routes as well as utilizing axle load data from the existing weight enforcement sites. Cost estimates were also provided for each plan. In addition, the study developed axle load spectra and vehicle class distributions using screened traffic data collected by portable WIM sites from 2004 to 2006. For current design practices, the study also utilized portable WIM data to update load equivalency factors (LEF) using the Vehicle Travel Information System (VTRIS) software.
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