Formulation of traffic inputs required for the implementation of the M-E PDG in data-scarce regions: Lebanon case study

dc.contributor.authorChhade, Rana Haj
dc.contributor.authorMrad, Rayane N.
dc.contributor.authorHoussami, Lamis
dc.contributor.authorChehab, Ghassan R.
dc.contributor.departmentDepartment of Civil and Environmental Engineering
dc.contributor.facultyMaroun Semaan Faculty of Engineering and Architecture (MSFEA)
dc.contributor.institutionAmerican University of Beirut
dc.date.accessioned2025-01-24T11:27:10Z
dc.date.available2025-01-24T11:27:10Z
dc.date.issued2018
dc.description.abstractThe implementation of the Mechanistic-Empirical Pavement Design Guide (M-E PDG) in regions outside the United States and Canada, such as the Middle East and North Africa region (MENA), is still in its early stages due to the scarcity of the design input data required for its use at high reliability levels. Several studies have been carried out to present correlations for obtaining material properties as well as exploring the use of M-E PDG embedded climate files to account for the missing inputs and different environmental conditions. Yet, the main challenge resides in obtaining adequate traffic data and adapting local traffic inputs for M-E PDG default values. This paper presents guidelines for developing truck classification and growth factors from short-term traffic count surveys for countries where historical traffic data are unavailable or insufficient. The case of Lebanon is tackled as a case study for demonstration. The sensitivity of the pavement response to the variation of the extrapolated traffic input data is studied under different climatic and material conditions and validated against recent characterized and categorized traffic data. The results reveal that highway design agencies can process traffic count surveys to convert them into traffic input data as elaborated in the methodology, as the pavement's performance is not majorly affected by the variations and assumptions used in the calculations of the truck classes. However, the variation in the truck traffic volume, i.e., growth factor, significantly influences the predicted pavement distresses, which necessitates the continuous collection of traffic data to have more representative values for the growth rate estimation. Based on the obtained results, final recommendations are presented for the implementation of the M-E PDG in regions lacking traffic records. © 2018 American Society of Civil Engineers.
dc.identifier.doihttps://doi.org/10.1061/(ASCE)MT.1943-5533.0002279
dc.identifier.eid2-s2.0-85048746370
dc.identifier.urihttp://hdl.handle.net/10938/26812
dc.language.isoen
dc.publisherAmerican Society of Civil Engineers (ASCE)
dc.relation.ispartofJournal of Materials in Civil Engineering
dc.sourceScopus
dc.subjectMechanistic-empirical pavement design guide (m-e pdg)
dc.subjectPavement design
dc.subjectPavement me
dc.subjectTraffic data
dc.subjectVehicle classification
dc.subjectLebanon
dc.subjectDesign
dc.subjectInput output programs
dc.subjectPavement overlays
dc.subjectSensitivity analysis
dc.subjectSurveys
dc.subjectTrucks
dc.subjectEnvironmental conditions
dc.subjectGrowth rate estimation
dc.subjectMechanistic-empirical pavement design guides
dc.subjectMiddle east and north africa
dc.subjectRepresentative values
dc.subjectDesign method
dc.subjectPavement
dc.subjectRoad traffic
dc.subjectTransport vehicle
dc.subjectHighway planning
dc.titleFormulation of traffic inputs required for the implementation of the M-E PDG in data-scarce regions: Lebanon case study
dc.typeArticle

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