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dc.contributor.authorLee, David Jung-Hwi
dc.contributor.authorRoss, Catherine L.
dc.date.accessioned2018-05-21T12:54:08Z
dc.date.available2018-05-21T12:54:08Z
dc.date.issued2016-01
dc.identifier.urihttp://hdl.handle.net/1853/59698
dc.descriptionPrepared in cooperation with the U.S. Department of Transportation, Federal Highway Administration.en_US
dc.description.abstractTransportation decision makers have the difficult task of investment decision making having limited resources while maximizing benefit to the transportation system. Given the growth in freight transport and its importance to national, state, and regional economies, public-sector agencies need improved capabilities to analyze freight movement. In general, freight modeling is not widely developed and operationalized, at the metropolitan planning organization (MPO) level in particular due to the complexity of freight movement and the lack of availability of detailed truck trip data. This study develops a methodological framework of a tour-based freight demand model at the MPO level using GPS truck data. Methodologically it is a more accurate model compared to trip based models allowing truck trips to be linked, which reflects how truck drivers and dispatchers often make multiple trips within a single ‘trip chain’ or ‘tour’. Disaggregate truck movement data can be obtained via truck global positioning system (GPS) records collected in this study by the American Transportation Research Institute (ATRI). The developed framework has been applied to two metropolitan areas in the southeast, one covering the region around Atlanta, Georgia, and the other around Birmingham, Alabama. The report illustrates, with examples, potential uses of the model with multiple performance measures and also shows possibilities of applying the model to corridor analyses, small geographic area analyses, and scenario planning. The report introduces performance measures to compare the results of the two classes of models namely, the tour-based and the trip-based models. The results of six scenarios of the Atlanta metropolitan area are presented and compared along with some important policy implications for practice. The numerical results demonstrate that GPS data is feasible for model calibration and that tour-based models provide conceptually robust forecasts that sustain empirical validation under multiple scenarios. Although the study focuses on the Atlanta Metropolitan area, policymakers at all levels of government in other state DOTs and MPOs can benefit from this study and develop their own truck demand model borrowing the framework used.en_US
dc.languageen
dc.relation.ispartofseriesFHWA-GA-16-1223
dc.subjectTour-based truck modelen_US
dc.subjectGPS data-based truck modelen_US
dc.subjectDisaggregate truck demand modelen_US
dc.titleBringing Freight Components into Statewide and Regional Travel Demand Forecasting: PART 1en_US
dc.typeTechnical Reporten_US
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Quality Growth and Regional Developmenten_US


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