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Use of long-term pavement performance data to develop traffic defaults in support of mechanistic-empirical pavement design procedures Tam, Weng On ; Von Quintus, Harold

By: Contributor(s): Publication details: Transportation Research Record, 2003Description: nr 1855, s. 176-82Subject(s): Bibl.nr: VTI P8169:2003 Ref ; VTI P8167Location: Abstract: Traffic data are a key element for the design and analysis of pavement structures. Automatic vehicle-classification and weigh-in-motion (WIM) data are collected by most state highway agencies for various purposes that include pavement design. Equivalent single-axle loads have had widespread use for pavement design. However, procedures being developed under the National Cooperative Highway Research Program (NCHRP) require the use of axle-load spectra. The Long-Term Pavement Performance database contains a wealth of traffic data and was selected to develop traffic defaults in support of NCHRP Project 1-37A as well as other mechanistic-empirical design procedures. Automated vehicle-classification data were used to develop defaults that account for the distribution of truck volumes by class. Analyses also were conducted to determine direction and lane-distribution factors. WIM data were used to develop defaults to account for the axle-weight distributions and number of axles per vehicle for each truck type. The results of these analyses led to the establishment of traffic defaults for use in mechanistic-empirical design procedures.
Item type: Reports, conferences, monographs
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Traffic data are a key element for the design and analysis of pavement structures. Automatic vehicle-classification and weigh-in-motion (WIM) data are collected by most state highway agencies for various purposes that include pavement design. Equivalent single-axle loads have had widespread use for pavement design. However, procedures being developed under the National Cooperative Highway Research Program (NCHRP) require the use of axle-load spectra. The Long-Term Pavement Performance database contains a wealth of traffic data and was selected to develop traffic defaults in support of NCHRP Project 1-37A as well as other mechanistic-empirical design procedures. Automated vehicle-classification data were used to develop defaults that account for the distribution of truck volumes by class. Analyses also were conducted to determine direction and lane-distribution factors. WIM data were used to develop defaults to account for the axle-weight distributions and number of axles per vehicle for each truck type. The results of these analyses led to the establishment of traffic defaults for use in mechanistic-empirical design procedures.

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