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Suggested Citation:"1 INTRODUCTION." National Academies of Sciences, Engineering, and Medicine. 2013. Freight Demand Modeling and Data Improvement Strategic Plan. Washington, DC: The National Academies Press. doi: 10.17226/22733.
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Page 3
Page 4
Suggested Citation:"1 INTRODUCTION." National Academies of Sciences, Engineering, and Medicine. 2013. Freight Demand Modeling and Data Improvement Strategic Plan. Washington, DC: The National Academies Press. doi: 10.17226/22733.
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Page 4

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1Freight transportation in the United States has been a topic of growing interest to policy makers, state departments of transportation (DOTs), metropolitan planning organizations (MPOs), and varied stakeholders, particularly since the passage of the Intermodal Surface Transportation Effi ciency Act (ISTEA) of 1991. The overarching policy challenge for transportation agencies is to make informed investments in trans- portation infrastructure that support effi cient freight mobility and access. Long-range transportation plans, transportation improvement programs, corridor studies, and project development should have a meaningful freight focus. This need to better inte- grate freight with transportation planning recognizes the importance of goods move- ment to economic performance and meeting consumer needs. Progress in freight plan- ning also requires effective communication and coordination with the private sector (shippers and carriers) and local government with respect to development and land use considerations. Although more than 20 years have passed since ISTEA was enacted, accurate and timely freight planning and forecasting still remain formidable challenges with substantial opportunity for improvement. Transportation investments are capital intensive and represent long-term commit- ments. It is important that transportation planners possess both the tools and the skills to forecast freight demand and to analyze scenarios and investment alternatives as part of the overall transportation analysis. Travel demand forecasting, however, has historically been oriented toward passenger transportation. Passenger-oriented fore- casting models draw on economic and demographic variables that are insuffi cient and sometimes irrelevant for estimating future freight demand, which is shaped by a much wider range of factors as a result of a complex logistics chain. 1 INTRODUCTION

2FREIGHT DEMAND MODELING AND DATA IMPROVEMENT STRATEGIC PLAN The SHRP 2 C20 research initiative has been developed to provide the strategic framework for making further inroads in freight forecasting, planning, and data and to accelerate innovative breakthroughs with the aim of integrating freight consider- ations into the planning process with confidence. Long-range transportation plans, transportation improvement programs, corridor studies, and project development should have a meaningful freight focus.

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Freight Demand Modeling and Data Improvement Strategic Plan Get This Book
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 Freight Demand Modeling and Data Improvement Strategic Plan
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TRB’s second Strategic Highway Research Program (SHRP 2) Report S2-C20-RW-2: Freight Demand Modeling and Data Improvement Strategic Plan outlines seven strategic objectives that are designed to serve as the basis for future innovation in freight travel demand forecasting and data, and to guide both near- and long-term implementation.

This report is only available in PDF format.

SHRP 2 Capacity Project C20 also produced the following items:

• A report intitled Freight Demand Modeling and Data Improvement that documents the state of the practice for freight demand modeling. The report also explores the fundamental changes in freight modeling, and data and data collection that could help public and private sector decision-makers make better and more informed decisions:

• A speaker's kit, which is intended to be a "starter" set of materials for use in presenting the freight modeling and data improvement strategic plan to a group of interested professionals; and

• A 2010 Innovations in Freight Demand Modeling and Data Symposium.

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