This study developed traffic inputs for use with the Guide for the Mechanistic–Empirical Design of New and Rehabilitated Pavement Structures (MEPDG) in Virginia and sought to determine whether the predicted distresses showed differences between site-specific and default traffic inputs for flexible pavements. The predicted distresses based on site-specific inputs from eight Interstate weigh-in-motion sites in Virginia were compared with predicted distresses by means of MEPDG default traffic inputs. These comparisons were performed with the use of a normalized-difference statistic for each site-specific traffic input and the coefficient of variation for each pavement distress model. In addition, the practical significance was considered from the difference in the predicted time to failure between site-specific and default traffic inputs. The analysis showed that the effect of the site-specific traffic inputs was generally not statistically significant when the uncertainty of the distress models was considered. However, the site-specific axle load spectra inputs showed a practically significant increase in the predicted time to failure compared with the default traffic inputs. From this study, it is recommended that users of the MEPDG consider collecting site-specific axle load spectra data for analysis of flexible pavements. In addition, analysis of flexible pavements may be performed by using the default inputs for the remaining traffic parameters. Given the mixed conclusions in previous studies, it may be necessary for each user or agency to conduct a similar evaluation for its local combination of traffic, materials, climate, and typical pavement structures.


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    Titel :

    Analysis of Virginia-Specific Traffic Data for Use with Mechanistic–Empirical Pavement Design Guide


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    01.01.2010




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch