Freight Demand Modeling and Data Improvement Strategic Plan

Abstract

Freight traffic has been growing faster than passenger traffic on the nation’s highway network. As a result, freight bottlenecks have begun to develop at various points throughout the network. These bottlenecks have historically been near ports and other intermodal facilities. However, travel forecasts are beginning to show the effects of growing freight traffic on congestion on urban freeways, urban arterials, and some cross-country routes in rural areas. Being able to understand freight flows and forecast freight demand is taking on greater and greater importance. The second Strategic Highway Research Program (SHRP 2) initiated two projects (Capacity Projects C15 and C20) designed to improve the nation’s ability to plan for increased freight-related traffic and to begin to address the growing issue of freight bottlenecks. Capacity Project C20, which was the first one and is the subject of this report, assessed the state of the practice of freight demand modeling and freight data as they relate to highway capacity planning and programming. This assessment concludes that the state of freight demand modeling has been relatively stable during the past several decades, unlike demand modeling for passenger travel, which is advancing toward activity-based modeling. The state of the practice in freight data has also been relatively stable; however, promising developments based on new information technologies may greatly improve transportation planners’ access to freight data. Examples include global positioning system data from trucks and (potentially) private supply chain data that could be aggregated for public sector planning purposes. Accelerated innovation is needed so that freight demand modeling and freight data can better serve the needs of public sector decision making regarding highway capacity investments. The C20 Strategic Plan suggests strategic research initiatives that could begin to improve the practice of freight demand modeling and freight data. These are grouped into themes such as knowledge gaps, modeling, data, and data visualization. Knowledge gaps are a key issue because the perspectives and business planning time frames of the private and public sectors are so divergent with respect to freight. The private sector focuses on optimizing short-term supply chains and operations, but the public sector focuses on making investments that may take a decade or more to put in place. Bridging this knowledge gap is essential to making progress in freight capacity planning. Visualization technologies are promising for helping freight decision makers and stakeholders understand each other’s perspectives. Since the responsibility for gathering freight data and conducting freight demand modeling is spread among a large number of agencies and organizations, the C20 Strategic Plan puts forward a potential model for organizing cooperation to encourage innovation and moving forward. One model for advancing the state of the practice in freight demand modeling and freight data is to hold innovation symposia. A pilot effort was initiated in September 2010 as part of the SHRP 2 C20 research project.

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.17226/22733

• http://pdfs.semanticscholar.org/c5d3/95fd96bc71fe4e49f82cf802f2577e049fa2.pdf

• https://trid.trb.org/view.aspx?id=1244065,

https://www.nap.edu/catalog/22733,

https://academic.microsoft.com/#/detail/639831769