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7 FHWA) has been used by states to implement the truck mode allocates activities to grid cells (30 m 30 m) once each year within a freight component. The QRFM provides default co- until reaching the planning horizon. efficients for trip generation and trip distribution steps. "Driving to Distractions, Recreational Trips NCHRP Report 187: Quick-Response Urban in Private Vehicles" 2000 Travel Estimation Techniques and Transferable Parameters: User's Guide 1978 and NCHRP Mallett and McGuckin (2004) present descriptive statistics Report 365: Travel Estimation Techniques for of recreational trips by private automobile from the 1995 Urban Planning 1998. American Travel Survey (ATS) and the National Personal Transportation Survey (NPTS) from 1990. Comparisons NCHRP Report 365 (Martin and McGuckin 1998) is essen- were made of both urban and long distance recreational trips tially an update of NCHRP Report 187 (Sosslau et al. 1978). across racial and income groups. Although not specifically for statewide models, these two re- ports have allowed states to quickly implement passenger components when there were data deficiencies as to local "Modeling the Competition Among Air Travel travel patterns in urban areas. The reports provide transfer- Itinerary Shares: GEV Model Development" 2005 able parameters for trip production estimation, trip attraction estimation, gravity expressions for trip distribution, time-of- This article by a research group from Northwestern Univer- day, automobile occupancy, and delay calculations. sity (Coldren and Koppelman 2005) presents results from the creation of an itinerary share prediction model for air travel. Both multinomial logit expressions and nested logit algo- rithms were created to forecast choices of travelers when RECENT RESEARCH ON UNITED STATES INTERCITY TRAVEL FORECASTING booking air travel based on service characteristics such as number of stops, connection quality, distance, competing "Critical Review of Statewide Travel Forecasting carriers, aircraft type, and time of day. Practice" 1999 This article by Horowitz and Farmer (1999) is based primar- MAJOR DATABASES OF PARTICULAR INTEREST ily on the literature review section of the Guidebook. It offers FOR STATEWIDE TRAVEL FORECASTING suggestions for areas where statewide travel forecasting American Travel Survey 1995 models can be improved. The ATS was conducted in 1995 and early 1996 by the "The Trouble with Intercity Travel Demand Bureau of Transportation Statistics (BTS). It is the only Models" 2004 comprehensive national database on long distance (more than 100 mi) passenger travel. Approximately 54,000 Miller (2004) critically reviews the literature on intercity households provided information, with each household re- passenger demand modeling. The article particularly con- porting on one year of travel in four quarterly surveys. Data trasts models of total demand with nested logit algorithms. about each trip include the reason for making the trip, prin- Also described are the issues involved in applying intercity ciple mode (including vehicle type), mode of access or passenger demand models. egress, origin, destination, intermediate stops, travel dates, duration, nights away from home, type of lodging, and travel distance. Origins and destinations are geocoded to "Evaluating Role of Distance and Location in states and metropolitan areas. Most surveys were obtained Statewide Travel Demand Forecasting by Using American Travel Survey" 1999 by telephone, although some personal visits were made. Individual trip records and complete household data are O'Neill et al. (1999) present average distances of person available on CD-ROM. There are no immediate plans to do travel, cross-tabulated by purpose and mode for California, another long distance survey similar to the ATS, although Colorado, Florida, Massachusetts, and Michigan. Modes in- some information on long distance travel can be obtained vestigated were personal vehicle, air, bus, train, and water. from the NHTS. As expected, the study found that trips by air were much longer than the other modes; however, there was no clear National Household Travel Survey break point of trip length that separated modes. Formerly known as the National Personal Transportation "The Land Development Module of the Oregon2 Survey, this survey of passenger travel has been conducted Modeling Framework" 2004 at varying times since 1969, with the last survey completed in 2002. Approximately 66,000 households were surveyed, Hunt et al. (2004a) explains one of the seven modules of the of which about 40,000 were from 9 specific geographic ar- Oregon2 statewide travel forecasting model. The model eas (who requested add-on samples) and the remainder was

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8 a general coverage of the entire United States. Households Vehicle Inventory and Use Survey were sampled by means of random-digit dialing and were interviewed by telephone. Data on all trips in a household The Vehicle Inventory and Use Survey (VIUS), formerly over a 24-h period were collected as were data on long known as the Truck Inventory and Use Survey, consists of data distance trips, defined as greater than 50 mi, over a 28-day on the operation and physical characteristics of commercial ve- period. Individual household and trip records are available hicles. The survey was first done in 1963, and is currently con- on CD-ROM from the BTS. Daily trip data include trip ducted every 5 years. The latest survey was done in 2002, with times, modes, purposes, vehicles used, durations, lengths, the next on schedule for 2007. Operating characteristics include day of the week, and the presence of other travelers for the number of miles driven and commodities carried. Individual same trip. Long distance trip data include dates of travel, truck records are available for almost 100,000 trucks. Opera- whether the trips are recurring, purposes, primary modes, tional characteristics that are of general interest for travel destinations, types of lodging, overnight stops, and access models are base state, average weight with payload, type of and egress information for air, bus, and rail modes. It business, miles driven outside state, miles driven by trip length, should be noted that the definition of "long distance" is miles driven by commodity group (50 groups including empty different from that used by the ATS; therefore, the data sets and waste), miles driven by hazardous materials class and type are not directly comparable. The results of the survey may of service. VIUS data may be obtained from the U.S. Census have been affected by the September 11, 2001, terrorist Bureau. More information about VIUS may be obtained from attacks. Individual trip records from the NHTS are available and Transborder Surface Freight Data are easy to summarize or analyze. Much of the transferable parameters in NCHRP Report 365 were developed from the The Transborder Surface Freight Data set is a large sample 1990 National Personal Transportation Survey. Planning is of shipments between the United States and Canada and the currently underway for the next survey in 2008. More infor- United States and Mexico. Freight flow data in dollars and mation may be obtained from tons are provided by destination state or origin state, by point html_files/introduction.shtml. of entry or exit, by commodity and by mode (mail, highway, rail, vessel, and pipeline). Data are updated monthly. Indi- vidual shipment records may be obtained. More information Commodity Flow Survey on the Transborder Surface Freight Data may be obtained from The Commodity Flow Survey (CFS) is a survey of shippers in the United States. Shipments from most major industries are represented in the sample, last taken in 2002. It was Freight Analysis Framework composed of a stratified random sample of approximately 50,000 establishments with 2.6 million shipments. Estab- The FAF, developed by FHWA, is a modeling system that lishments reported a sample of their shipments (or all ship- forecasts the amount of freight traveling on modal (truck, wa- ments for smaller establishments) for one week in each of ter, and rail) networks throughout the United States. It is pri- four calendar quarters. Information about each shipment in- marily a policy tool for the federal government. Forecasts for cluded the origin, destination, value, weight, mode, dis- 2010 and 2020 have been made. Results for commodities are tance estimated from a network, and commodity group. reported at the two-digit Standard Transportation Commodity Modes covered by the survey included for-hire truck, pri- Code (STCC) level. The model itself and much of the input vate truck, rail, inland water, deep sea water, pipeline, air, data are not available for state use. However, the FAF provides and parcel delivery or U.S. Postal Service. Data are also the following results for its base year (1998) and forecast years available from the 1997 and 1993 surveys. The CFS does that can be of use to statewide travel forecasting models: not contain data on imports, and its level of spatial detail is coarse. Industrial sectors included mining, manufacturing, Tons of freight shipped in the United States by state or wholesale trade, electronic shopping, and mail-order busi- international gateway, type of commodity, and mode of nesses. The survey excluded services, transportation, transportation; construction, other retail, farms, fisheries, gas and oil Flows of freight along major routes by range of tonnage extraction, and most government-owned establishments. and mode; and The U.S. portions of imports that are transshipped from Number of trucks using road segments. within the United States are included. Shipments passing entirely through the United States are excluded. Detailed The FAF is currently undergoing major revisions to provide tables can be obtained on CD-ROM from the BTS. Plan- additional detail and to make its results more useful. Results are ning is underway for the next CFS in 2007. More informa- downloadable from the FHWA website. More information on tion on the survey may be found at the FAF may be obtained at programs/commodity_flow_survey/. freight_analysis/faf/. This site explains planned revisions to the