Bringing freight components into statewide and regional travel demand forecasting: part 1 : final report.
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2016-01-01
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Abstract:Transportation 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.
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