Freight Models

The Model section provides descriptions of samples and descriptions of national, state and MPO level freight modeling. It also creates a place where new and innovative breakthroughs in freight transportation modeling can be promoted, as users can put new description on the site, thus helping to disseminate new forecasting and planning methods.

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ARC Commercial Vehicle and Truck Models

•    Truck Trip Generation: Separate linear regression equations are developed to estimate Heavy and Medium Size Truck trips, based on zonal employment in industrial, retail and commercial industry classes, and number of households in a zone, in each case adjusted by one of 7 different area type factors, with heavy truck trips multiplied by a factor of 3 in zones known to contain high truck traffic volumes.

California Statewide Freight Forecasting Model (CSFFM)

The California Statewide Freight Forecasting Model (CSFFM) is a policy-sensitive tool that is intended to forecast commercial vehicle and commodity flows within California. The model will address socioeconomic conditions, freight-related land use policies; environmental policy; and multimodal infrastructure investments. The model will allow for a better understanding of freight movement related policies, regulatory decisions, project decisions, and the impacts of these decisions.

Florida Statewide Multi-Modal Freight

The model converts the supply chain information on firms, shipments, and modes into modal trip tables, and assigns these trip tables to a multimodal statewide transportation network. This network consists of highway and railway links, seaports and waterways, airports, and intermodal connectors. The model uses a combination of FAF zones and Florida counties. The model covers the freight movements within, into and out of the entire state of Florida, using a transportation network database that extends to the entire United States and around the world.

Freight Analysis Framework Version 3 (FAF3)

The Freight Analysis Framework (FAF) integrates data from a variety of sources to create a comprehensive picture of freight movements among states and major metropolitan areas by all modes of transportation. With data from the 2007 Commodity Flow Survey and additional sources, FAF version 3 (FAF3) provides estimates for tonnage, value, and domestic ton-miles by region of origin and destination, commodity type, and mode for 2007, the most recent year, and forecasts through 2040.

Iowa Statewide Freight Commodity Model

The first generation iTRAM (statewide traffic model) focused on car and truck traffic. The 2013-2014 updated model incorporates freight and commodity flows plus long distance passenger movements. The updated iTRAM model consists of three main parts, each comprised of multiple steps (see Figure 1):

Navigation Investment Model

Waterways are a very attractive alternative to rail and highway transportation of heavy bulk cargo such as coal, grains, and building materials as long as the travel times are within reasonable ranges.  However, as the travel times increase due to congestion at the locks, additional operating costs for towboats and barges begin to cut into savings.  Lock congestion is created by high demand, limited capacity, maintenance closures, and construction closures.  Eventually, delayed shippers will respond by decreasing the amount shipped by water, either shifting to another mode or reducing total

SANDAG Truck Model

The SANDAG Truck Model is an aggregate flow model developed to make use of existing data sources. It follows the traditional and sequential trip generation-distribution-traffic assignment modeling framework, and offers a well-documented example of the data and modeling issues associated with doing so at a detailed level of spatial resolution and on a limited data collection budget.