Use of Long-Term Pavement Performance Data to Develop Traffic Defaults in Support of Mechanistic-Empirical Pavement Design Procedures

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...

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Veröffentlicht in:Transportation research record 2003, Vol.1855 (1), p.176-182
Hauptverfasser: On Tam, Weng, Von Quintus, Harold
Format: Artikel
Sprache:eng
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Zusammenfassung: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 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 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.
ISSN:0361-1981
2169-4052
DOI:10.3141/1855-22