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NCHRP Report 606: Forecasting Statewide Freight Toolkit (2008)
National Cooperative Highway Research Program (NCHRP)

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Horowitz, Alan, Cohen, Harry, Pendyala, Ram, Transportation Research Board. "2.3 Freight Terminology." NCHRP Report 606: Forecasting Statewide Freight Toolkit. Washington, DC: The National Academies Press, 2008.

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Front Matter (R1-R10)
Chapter 1 - Introduction (1-2)
2.2 Statewide Freight Forecasting (3-3)
2.3 Freight Terminology (4-4)
3.1 Freight Policy Needs (5-7)
3.2 Available Methods (8-8)
4.1 Direct Factoring (9-9)
4.2 Trip Generation (10-10)
4.3 Trip Distribution (11-11)
4.4 Mode Split (12-13)
4.5 Traffic Assignment (14-14)
4.6 Economic/Land Use Modeling (15-15)
5.1 Model Development (16-19)
5.2 Flow Conversion (20-22)
5.3 Network Data (23-23)
5.4 Forecasting Data (24-24)
5.5 Validation Data (25-25)
5.6 Classification Schemes (26-26)
6.1 The Direct Facility Flow Factoring Method (27-28)
6.2 The Origin-Destination Factoring Method (29-30)
6.3 The Truck Model (31-31)
6.4 The Four-Step Commodity Model (32-32)
6.5 The Economic Activity Model (33-34)
7.2 Performance Measures for States' Primary Needs (35-35)
7.4 Recommended Toolkit Performance Measures (36-41)
8.1 Development of a Forecasting Model Template (42-43)
8.2 Case Study Minnesota Trunk Highway 10 Truck Trip Forecasting Model (44-46)
8.3 Case Study The Heavy Truck Freight Model for Florida Ports (47-53)
8.4 Case Study Ohio Interim Freight Model (54-62)
8.5 Case Study Freight Analysis Framework (63-72)
8.6 Case Study New Jersey Statewide Model Truck Trip Table Update Project (73-81)
8.7 Case Study SCAG Heavy-Duty Truck Model (82-91)
8.8 Case Study Indiana Commodity Transport Model (92-100)
8.9 Case Study Florida Intermodal Statewide Highway Freight Model (FISHFM) (101-109)
8.10 Case Study Cross-Cascades Corridor Analysis Project (110-118)
8.11 Case Study Oregon Statewide Passenger and Freight Forecasting Model (119-129)
References (130-130)
Bibliography (131-133)
Acronyms (134-135)
Appendix A - Commodity Classifications (136-145)
Appendix B - Tool Components and Forecastable Performance Measures (146-151)
Appendix C - References with Mode Components (152-158)
Abbreviations used without definitions in TRB publications (159-159)

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4 While freight forecasting often is used to estimate future value per ton, the same density (weight per volume), and demand, it also may provide information on freight move- the same handling characteristics. There are several classi- ments in the current transportation system. This could fication schemes for freight, most notably the Standard include evaluating changes in performance in response to Transportation Commodity Classification (STCC) codes changes in the current transportation system, such as of the American Association of Railroads, and the Standard increases in the price of travel on a specific facility, or devel- Classification of Transported Goods (SCTG) a system oping information on existing flows that could not be easily developed jointly by U. S. and Canadian government agen- observed, such as freight flows by commodity using a specific cies based on the Harmonized System to address statistical roadway that could not be obtained by counting the number needs in regard to products transported. of trucks. · Origins and Destinations ­ The geographic starting and ending points of a freight shipment. Origins and destina- tions generally do not refer to a specific street address, but 2.3 Freight Terminology to a larger identifiable geographic unit in which the address In order to identify and forecast freight shipments, it is is located, such as a county, a state, or a census tract. important to define key attributes of those shipments. The · Mode ­ The vehicles and infrastructure used to transport Transportation Research Board Committee on Freight Trans- goods. The most common modes defined in freight are portation Data refers to the desirable elements of a freight data- truck, rail, water, air, and pipeline. Subcategories and com- base using the mnemonic CODMRT, which stands for: binations of these basic modes may themselves be defined as modes. · Commodity ­ The type of freight being moved. · Route ­ The sequence of specific individual facilities (such · Origin ­ The geographic start of the freight trip. as, sections of roads, railroad tracks, etc.) that are used to · Destination ­ The geographic end of the freight trip. transport freight between the origin and destination on a · Mode ­ The mode or modes being used to carry the freight. specific mode. · Route ­ The route on the modal network used to carry the · Time ­ The time of day, as defined by the Committee on freight. Freight Transportation Data. For purposes of this Toolkit, · Time ­ The time period for which the freight data was col- it is assumed that time refers to the freight forecast time lected.4 period as reflected in the flow data, such as tons per year or vehicles per day. An implicit data element is also the flow unit, such as · Flow Units ­ The way the freight flow is being reported tons, dollar value, or vehicles, that is being recorded. The and forecast as defined by all of the above attributes. If the CODMRT mnemonic also is useful to describe the elements freight flow is expressed for all modes, the flow unit must that will be produced by freight forecasts. The terms are be expressed in a unit common to all modes, such as tons defined as: per year. · Commodity ­ A way of classifying the type of freight being Knowing all of the above characteristics for given ship- shipped. Commodities are assumed to be indistinguishable ments of freight makes it possible to sum those shipments to based on the characteristics important in shipping. Com- identify the total of all freight using a specific route or origi- modities of the same class are assumed to have the same nating from a specific location.