Cover Image

Not for Sale

View/Hide Left Panel
Click for next page ( 10

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 9
9 CHAPTER 4 Forecasting Components This Toolkit is organized on the basis of five basic model Guidebook on Statewide Travel Forecasting discusses time classes and six modeling components. The model classes series methods for direct forecasts of vehicular volumes on share many basic components, as shown in Table 4.1. All of highway and for forecasting the inputs to four-step models.5 the classes, except the direct facility flow factoring model The Guidebook emphasizes autoregressive integrated moving class, assign one or more modal tables to modal networks. average (ARIMA) models and growth factor methods, while The origin-destination (O-D) factoring, four-step commod- describing a linear regression model to forecast truck vol- ity, and economic activity models all have mode split com- umes on Interstate 40 in New Mexico. The Federal Highway ponents. The truck, four-step commodity, and economic Administration's Quick Response Freight Manual describes activity model classes all have trip generation and trip distri- two methods of applying factors to traffic volumes applicable bution components. The truck and four-step models use to rural highways as well as urban highways.3 The first method exogenously supplied zonal employment or economic activ- involves estimating a growth factor from current and past ity in the trip generation component, while the economic truck count data and applying the resulting factor to future activity model forecasts the employment or economic activ- years using a conventional compound interest formula. The ity based on economic and land use data. second method determines separate growth factors for vari- Section 4.6 discusses economic activity/land use models, ous "economic indicator variables," usually employment in which, depending on the model class, can be integrated into local industrial sectors. The future growth in economic indi- the freight forecasting process, run separately to provide socio- cator variables, as calculated by a compound interest formula, economic data forecasts, or used to obtain growth factors. is used to forecast growth in commodity groups. NCHRP Report 260: Application of Statewide Freight Demand Forecasting Techniques, describes a generalized pro- 4.1 Direct Factoring cedure of O-D table factoring and assignment.6 The report As shown in Figure 4.1, the direct factoring model compo- assumes that commodity production is directly related to nent produces forecasts of link volumes, such as those on employment in industries that produce the commodity. For roads, railroad tracks, or ports, using basic information about estimating consumption, it recommends the use of an input- existing flows and forecasts of economic data or trends that output table. Commodity consumption calculations follow a would affect the facility. three-step process: This method uses existing freight flow for a facility, modal network link, or terminal. Factors are developed and applied 1. Obtain an input-output table; to estimate changes in this facility flow due to growth or 2. Convert dollar amounts to tons and sum the columns of changes in transportation service on that facility or on a com- the table to find consumption by industry; and peting facility regardless of mode. 3. Allocate tons to counties (the assumed size of the Traffic Direct factoring is used in many states. Usually intended for Analysis Zone, or TAZ) according to the employment by short-term forecasts, the model component involves simple consuming industries and population (for final demand) methods intended for rapid application of existing data to in each county. determine one or more forecasted items. Successful direct fac- toring requires many assumptions and the model's range of These steps assume that the production and consump- applicability is limited. The Federal Highway Administration's tion estimates can be applied to an existing commodity