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Freight Demand Modeling and Data Improvement: A Strategic Roadmap for Making Better Freight Investments

SHRP2 C20 Implementation Assistance Pilots for Freight Demand Modeling and Local Freight Data Improvement

Behavior-Based Freight Modeling

The Maricopa Association of Governments in Arizona developed a multi-modal freight model to better replicate the economic behaviors of establishments, shippers, and carriers by modeling travel and tour formations in Arizonaís Sun Corridor mega-region.

The Maryland Department of Transportation and Baltimore Regional Transportation Board developed a regional tour-based truck model covering intra-local distribution with sensitivity to the long-distance truck flows represented in the statewide freight model.

Portland Metro in Oregon used a hybrid approach to understand the local portion of the regionís supply chains, as well as the tour-based behavior of individual trips to address economic policy questions, and depict truck volumes and flow of goods.

The Wisconsin Department of Transportation developed a hybridized model for statewide freight forecasting and quantifying how different scenarios affect freight transportation.

Innovations in Local Freight Data

The Florida Department of Transportation improved the accuracy of freight forecasts by collecting data representing the supply and demand chain for petroleum commodities distributed throughout South Florida.

The Mid-America Regional Council in Missouri used a combination of existing data and new sources of commercial waybill data to demonstrate the impacts of congestion to the cost of freight movement.

The Capital District Transportation Committee in New York created a unified data set for the region at the zip code or transportation analysis zone (TAZ) level by integrating diverse data sources that will support analysis of freight.

The Winston-Salem Metropolitan Planning Organization, as part of the Piedmont Triad Regional Model Team, in North Carolina collected data to support development of an advanced freight model.

The Delaware Valley Regional Planning Commission in Pennsylvania and New Jersey advanced a freight data planning program to better understand intermodal transportation for freight and created a platform for sharing freight data.

The South Dakota Department of Transportation studied the growth in agricultural production and the current and expected location, timing, and impact of commodity shipping on South Dakotaís highways.

The Washington State Department of Transportation collected detailed information from industry and local urban truck deliveries for the State's food distribution supply chain to accurately model behavioral responses to different State policy scenarios aimed at reducing emissions.


This is a map from the Maricopa Association of Governments behavior-based supply chain freight model showing number of employees by traffic analysis zones for the Phoenix Arizona metropolitan area. The map shows the density of employment in core areas of the city and the other major employment centers in the metropolitan area. The information is used to estimate freight trip generation in the model. Source: Maricopa Association of Governments

Efficient freight transportation is essential to national, State, and local economic well-being. Understanding and forecasting freight flows is critical to planning for future transportation capacity, operation, preservation, safety and economy investment needs. The Freight Demand Modeling and Data Improvement program, funded by the second Strategic Highway Research Program (SHRP2), provides tools for incorporating freight movement considerations in the transportation planning process. SHRP2 is a national partnership of three key transportation organizations: the Federal Highway Administration (FHWA), the American Association of State Highway and Transportation Officials (AASHTO), and the Transportation Research Board (TRB).

The Freight Demand Modeling and Data Improvement program includes an analysis of the current state of the practice, freight decisionmaking and forecasting needs. The project provides innovative ideas and tools for developing improved freight data sets and freight modeling practices. Creating better data and models will enable State, regional, and local planners to better predict freight movement trends, and make more informed project investment decisions.

This page provides the following resources:

SHRP2 C20 Freight Demand Modeling and Local Freight Data Improvement Final Report

This report provides information about freight data and modeling tools through examples and pilot projects for State Departments of Transportation (DOTs) and Metropolitan Planning Organizations (MPOs) to improve freight-related decisionmaking. It gives an overview of the projects funded by the SHRP2 Implementation Assistance Program (IAP), and the applicability to potential issues faced by freight planners.

This report is designed to provide an overview of the data and tools available. It is organized around the two subject areas of data and modeling tools; providing an overview of the options, benefits, and challenges of the respective data and modeling tools identified.

  • SHRP2 C20 Freight Demand Modeling and Data Improvement Handbook [HTML, PDF 4.7MB]

Additional information on each of the freight data and modeling projects funded by the SHRP2 IAP is provided to the right.

Regional Freight Data Collaboration and Standardization

The FHWA and AASHTO conducted a series of Freight Data Collaboration and Standardization Regional Forums in 2016 and 2017, bringing together state DOTs and MPOs to identify areas of collaboration on regional or local freight data collection, standardization, and maintenance. The overall goal is to collaborate on improving freight data programs to support local, regional, and State freight transportation programs. The results of this work are currently under development.

Behavioral/Agent-Based Supply Chain Modeling Research Synthesis and Guide

This report and guide evaluates recent advancements in behavioral based models and supports the broader application of these methods to forecast future freight flows. Public agencies interested in developing behavioral/agent-based freight models can use this synthesis to assess the feasibility and practicality of developing similar models for their own regions based on the experiences of other agencies.

  • Behavioral/Agent-Based Supply Chain Modeling Research Synthesis and Guide [HTML, PDF 3.7MB]

Best Practices in Incorporating Land Use and Demographics into Freight Trip Demand Analysis

Photo of a semi-truck on Interstate 75 in Cincinnati, Ohio. Source: Federal Highway Administration

This report documents the current state of the practice on how land use, local economic development and demographic factors influence freight movement, trip generation, and freight demand analysis. This information provides practitioners with improved freight demand analysis tools that better reflect the relationship between freight movement and land use.

The results give a better understanding of the factors influencing freight-generating industrial and commercial development.

  • Best Practices in Incorporating Land Use and Demographics into Freight Trip Demand Analysis – Report Coming Soon

Related Information

Freight Model Improvement Program / Travel Model Improvement Program

The Freight Model Improvement Program (FMIP)/Travel Model Improvement Program (TMIP) has been created to advance the state of the practice of travel modeling by advancing research and building the technical capabilities of agencies staff. The is a collaborative effort of the transportation research community, consultants, public agencies and their private sector partners to improve the state-of-the-art and the state-of-the-practice in data, models, network and freight logistical analyses, and their application to transportation policy, planning, and decisionmaking in federal, State, regional, and local governments.

The Freight FMIP/TMIP Forum fosters new approaches to designing and implementing freight analytics.

  • Freight Models creates a place to promote and disseminate breakthroughs.
  • Freight Data provides links to multimodal data sets to populate models.
  • The Bibliography offers an extensive list of relevant citations.

For more information about FMIP/TMIP, please go to the FMIP/TMIP Web site https://tmip.org/.

Staff Contacts

Jeff Purdy
202-366-6993
Jeffrey.Purdy@dot.gov

Vidya Mysore
404-895-6215
Vidya.Mysore@dot.gov

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