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Freight is the economy in motion. It is motivated by the economic trade between firms and households, providing the products necessary for modern societies to function. The trade can be a simple as a retail transaction, or part of a highly complex global supply chain. While the parties involved are most often in the private sector the movement of freight often affects both the built and natural environment. Transportation planners are interested in quantifying and predicting the overall levels of freight movement and their impact on the transportation system, as well as understanding how the various agents involved might respond to a wide variety of policy, pricing, regulatory, and investment actions. Such actions are often included in regional transportation plans and projects, with the goal of fostering the safe and efficient movement of freight within the affected areas.

There are several aspects of freight that makes it challenging to include in travel demand forecasting models. It typically involves a large number of decision-makers, some with conflicting goals and options. Shippers, carriers, third-party logistics firms, consumers, and regulators all make decisions that potentially influence important decisions affecting freight transportation choices. Some transportation choices might appear sub-optimal when viewed in isolation, but make sense within the larger context of total logistics cost or are constrained by long-term contracts. A great deal of freight moves between regions. While its impact is often felt locally one or more of the trip ends are often far outside of the local area, limiting the influence of local plans and policies on wider patterns and practices. Because most freight flows between private entities data about it are difficult and expensive to obtain, further challenging those who seek to build a holistic view of it and its impacts though travel demand modeling.

Perhaps the biggest challenge with modeling freight is constraining its scope. Freight does not move of its own accord. It is often part of a supply chain, with goods flowing between points of production. The output of such supply chains are in turn financial transactions, which are driven by the demands of corporate, government, and individual consumers. To build a comprehensive freight demand model one would need to include each of these systems at some level or assumptions about them. This can be a formidable challenge, for many of these transactions and the decisions affecting them are made far outside the area being modeled. Even if data are available the burden of maintaining such a system is formidable, and likely beyond the abilities of most urban and state transportation planners.

Until recently there was little emphasis on including freight as a major part of metropolitan or statewide transportation planning. Recent federal transportation bills, as well as a renewed concerns about economic competitiveness and market accessibility, have changed that over the past decade. Despite that there remains an enduring difficulty associated with obtaining freight data, and methodological advances have not kept pace with the evolution of activity-based travel models for person travel. This is at least in part due to the lack of a widely accepted best practice in freight modeling, either at the urban or regional levels.

There are several dimensions by which freight models can be classified:

  • Scale (urban, statewide, national, continental, global, aspatial, or multi-scale models)
  • Focus (trucks, commodities, supply chains, or hybrids)
  • Representation (aggregate, disaggregate, or agent-based behavior, or hybrids)
  • Methodological approaches (trip-based, tour or activity-based, synthetic, logistic or supply chain, econometric, optimization, or combinations thereof)

Within the Travel Forecasting Resource the discussion of freight models focuses upon the methodological approaches. The other dimensions are considered within each approach.

Freight Data