You are being redirected because this document is part of your ASTM Compass® subscription.
    This document is part of your ASTM Compass® subscription.

    Volume 48, Issue 3 (February 2020)

    Special Issue Paper

    Mechanistic-Empirical Compatible Traffic Data Generation: Portable Weigh-in-Motion versus Cluster Analysis

    (Received 23 September 2019; accepted 11 November 2019)

    Published Online: 20 February 2020

    CODEN: JTEVAB

      Format Pages Price  
    PDF (1.63 MB) 16 $25   ADD TO CART

    Cite this document

    X Add email address send
    X
      .RIS For RefWorks, EndNote, ProCite, Reference Manager, Zoteo, and many others.   .DOCX For Microsoft Word



    Abstract

    Axle load distribution factors (ALDFs) are used as one of the primary traffic data inputs for mechanistic-empirical (ME) pavement design methods for predicting the impact of varying traffic loads on pavement performance with a higher degree of accuracy than empirical methods that are solely based on equivalent single axle load (ESAL) concept. Ideally, to ensure optimal pavement structural design, site-specific traffic load spectra data—generated from weigh-in-motion (WIM) systems—should be used during the pavement design process. However, because of the limited number of available permanent WIM stations (in Texas, for example), it is not feasible to generate a statewide ALDFs database for each highway or project from permanent WIM data. In this study, two possible alternative methods, namely, the direct measurement using a portable WIM system and the cluster analysis technique, were explored for generating site-specific ME-compatible traffic data for a highway test section, namely, state highway (SH) 7 in Bryan District (Texas). The traffic data were then used for estimating pavement performance using a ME pavement design software, namely, the Texas Mechanistic-Empirical Thickness Design System (TxME). The TxME-predicted pavement performance (e.g., rutting) using the portable WIM-generated traffic input parameters closely matched with the actual field performance. Overall, the study findings indicated that the portable WIM (with proper installation and calibration) constitutes an effective means for rapidly collecting reliable site-specific ME-compatible traffic data.

    Author Information:

    Walubita, Lubinda F.
    Texas A&M Transportation Institute (TTI), College Station, TX

    Department of Civil and Environmental Engineering, Universidad del Norte (UniNorte), Barranquilla,

    Fuentes, Luis
    Department of Civil and Environmental Engineering, Universidad del Norte (UniNorte), Barranquilla,

    Faruk, Abu N. M.
    Advanced Infrastructure Design, Inc., Hamilton, NJ

    Komba, Julius J.
    Department of Transport Infrastructure Engineering, University of Pretoria/Council for Scientific and Industrial Research (CSIR), CSIR Smart Mobility, Pretoria,

    Prakoso, Adrianus
    Texas A&M Transportation Institute (TTI), College Station, TX

    Naik, Bhaven
    Department of Civil Engineering, Ohio University, Athens, OH


    Stock #: JTE20190745

    ISSN:0090-3973

    DOI: 10.1520/JTE20190745

    Author
    Title Mechanistic-Empirical Compatible Traffic Data Generation: Portable Weigh-in-Motion versus Cluster Analysis
    Symposium ,
    Committee E17