Mechanistic-empirical compatible traffic data generation : portable weigh-in-motion versus cluster analysis

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dc.contributor.author Walubita, Lubinda F.
dc.contributor.author Fuentes, Luis
dc.contributor.author Faruk, Abu N.M.
dc.contributor.author Komba, Julius Joseph
dc.contributor.author Prakoso, Adrianus
dc.contributor.author Naik, Bhaven
dc.date.accessioned 2020-11-11T09:46:39Z
dc.date.issued 2020-05
dc.description.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. en_ZA
dc.description.department Civil Engineering en_ZA
dc.description.embargo 2021-05-01
dc.description.librarian am2020 en_ZA
dc.description.uri https://www.astm.org/DIGITAL_LIBRARY/JOURNALS/TESTEVAL/index.html en_ZA
dc.identifier.citation L. F. Walubita, L. Fuentes, A. N. M. Faruk, J. J. Komba, A. Prakoso, and B. Naik, “Mechanistic- Empirical Compatible Traffic Data Generation: Portable Weigh-in-Motion versus Cluster Analysis,” Journal of Testing and Evaluation 48, no. 3 (May/June 2020): 2377–2392. https://DOI.org/10.1520/JTE20190745. en_ZA
dc.identifier.issn 0090-3973 (print)
dc.identifier.issn 1945-7553 (online)
dc.identifier.other 10.1520/JTE20190745
dc.identifier.uri http://hdl.handle.net/2263/76963
dc.language.iso en en_ZA
dc.publisher ASTM International en_ZA
dc.rights Copyright by ASTM Int'l (all rights reserved) en_ZA
dc.subject Traffic load spectra en_ZA
dc.subject Weigh-in-motion en_ZA
dc.subject Portable weigh-in-motion en_ZA
dc.subject Cluster analysis en_ZA
dc.subject Mechanistic-empirical en_ZA
dc.subject Pavement design en_ZA
dc.subject Axle load distribution factors (ALDFs) en_ZA
dc.subject Equivalent single axle load (ESAL) en_ZA
dc.title Mechanistic-empirical compatible traffic data generation : portable weigh-in-motion versus cluster analysis en_ZA
dc.type Article en_ZA


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