Statewide Travel Forecasting Models (2006) / Chapter Skim
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From page 32... ...
of links: 77,272 Passenger modes: Automobile Trip purposes: Home-based work Home-based nonwork Nonhome-based Long distance business Long distance -- Recreation/vacation Long distance -- Other Special generators: Military bases Trip productions: Rates per household based on MSA size, area type Trip attractions: Rates per level of activity Trip distribution: Gravity expression, Fratar Mode split: None Assignment: Static equilibrium with subzones Delay estimation: BPR curves Major data: NHTS, HPMS, ATS, vendors Time frame: Two years of development time Computation time: 1 h In-house staff: 1 FTE The zone structure was built for compatibility with other databases. It is readily seen that zones well outside of Kentucky are based on BEA Economic Areas.
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Fratar factored trip tables from the ATS were used for long distance trip purposes. Table 5 shows how each long distance trip purpose FIGURE 6 Kentucky's highway network.
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From page 34... ...
of signals: 3,900 Travel modes: Automobile, truck, intercity bus/rail Trip purposes: Home-based work Home-based nonwork Nonhome-based Long trip Trip productions: Rates per household based on household size, automobile ownership, and area type Trip attractions: Rates per employment categories and households Trip distribution: Gravity expression Mode split: Fixed shares for short trip purposes Multinomial logit for long trip purpose Assignment: Static equilibrium with feedback to distribution Delay estimation: BPR travel time volume curves Truck models: Commodity based for freight trucks; empirical for non-freight trucks Major data: Census, NHTS, CTPP, own surveys Time frame: Seven years of continuous improvement following 3 years of initial development Computation time: 2 h In-house staff: 0.5 FTE The ISTDM covers all 92 counties in Indiana and parts of adjacent states. A detailed network was developed for areas within the state of Indiana, including all state jurisdictional highways (more than 19,500 links)
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FIGURE 10 Indiana Statewide Travel Demand Model ISTDM TAZ structure. ISTDMnet INDOT Inventory New Signals from Crash Data FIGURE 11 Traffic signals in Indiana Statewide Travel Demand Model network.
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ISTDM trip generation models were developed for four trip purposes (home-based work, home-based other, nonhome-based, and long purpose) and for three area types (urban, suburban, and rural)
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From page 37... ...
For freight trucks, base year 1993 truck trip tables from the Indiana University study were factored up to year 2000 levels by commodity group." Non-freight truck trip tables were estimated from truck ground counts after first removing freight trucks. The ISTDM used a multiclass assignment approach for traffic assignment, with truck trips and automobile trips loaded to the network at the same time.
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From page 38... ...
Independent variables in the regression model included: • Total population, • Total households, • Population density, • Population under age 17, • Percent of households with head of household over age 65, • Household workers, • Average household income, • Accessibility to wealth (by place of residence) , • Accessibility to unoccupied housing units, • Accessibility to schools, • Accessibility to university enrollment, 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Pe rc e n t D is tri bu tio n 1 1.2 1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4 Average Persons per Household H1 HH3 HH2 HH4 FIGURE 14 Household size stratification curves.
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From page 39... ...
These two statewide models share many similarities, particularly their emphasis on forecasting the spatial distribution of economic activity and land use. The Oregon statewide model was recently described in the draft report for NCHRP Project 8-43.
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The major data sources were: • Household travel surveys, • Household long distance travel survey, • GPS-based travel survey, • Business establishment survey, • National Transport Networks, • Ohio DOT Roadway Information Database, • U.S. Census, • ES-202, • TRANSEARCH, Interregional Economic Model Aggregate Demographic Model Land Development Model Activity Allocation Model Employment Spatial Disaggregation Model Disaggregate Household Synthesis Model Personal Travel Tour Models Commercial Travel Tour Models Network Assignment Models Air Quality & Accident Models Sub-Area Traffic Micro-Simulation Model Travel Demand Models Times & Costs FIGURE 18 Overall structure of Ohio's statewide travel forecasting model.
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From page 41... ...
The traditional generation, distribution, and mode split steps for personal travel are replaced by microsimulation of household travel decisions. Separate submodels are provided for household synthesis; short-distance, home-based person tours; long distance, home-based person tours; commercial, work-based person tours; and visitor person tours.
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The TRANSEARCH data for Virginia gave commodity flows in tons from, to, and within Virginia. Data were organized geographically by state, BEA region, and Virginia county.
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Virginia used a maximum likelihood method of OD table estimation from ground counts that was contained within their travel forecasting software package. This method required a "seed" OD table, as well as numerous truck ground counts.
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45 FIGURE 22 Virginia's zone system, in and near state. FIGURE 23 Virginia's highway network, full extent.
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Initial Truck Network Assignment Local Truck Matrix Estimation Local Truck Trips Overall Truck Trips Network Assignment FIGURE 25 Major steps in Virginia's truck model.
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Both Virginia and Louisiana (Wilbur Smith Associates 2004) implemented essentially two distinct travel forecasting models, referred to as the "micro" model and the "macro" model.
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48 • Secondary warehousing; • Rail drayage; • Other minerals; • Furniture or fixtures; • Printed matter; • Other nondurable manufacturing products; • Other durable manufacturing products; • Miscellaneous freight; • Hazardous materials; and • Air drayage. These commodity groups were selected to emphasize those commodities that were of the greatest economic importance to Wisconsin and to allow a direct match to industrial categories.
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From page 48... ...
Employment data were FIGURE 28 Wisconsin's freight component network. Commodity Production Consumption Farm and Fish SIC01 + SIC02 + SIC07 + SIC09 SIC20 + SIC54 Nonmetallic Minerals SIC14 + SIC15 + SIC16 + SIC17 SIC14 + SIC15 + SIC16 + SIC17 Food SIC20 Population Lumber SIC24 SIC24 + SIC25 + SIC50 Pulp, Paper, Allied Products SIC26 SIC26 + SIC27 Chemicals SIC28 Total employment Clay, Concrete, Glass, and Stone SIC32 Population Primary Metal Products SIC33 SIC33 + SIC34 Fabricated Metal Products SIC34 Population Transportation Equipment SIC37 SIC42 Secondary Warehousing SIC42 Population Furniture or Fixtures SIC25 Population Printed Matter SIC27 Total employment Other Nondurable Manufacturing Products SIC21 + SIC22 + SIC23 Population Other Durable Manufacturing Products SIC30 + SIC31 + SIC35 + SIC36 + SIC38 + SIC39 SIC50 TABLE 9 INDEPENDENT VARIABLES FOR TONNAGE GENERATION FOR SELECTED COMMODITY GROUPS
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From page 49... ...
Internal truck travel in the MPO models is handled with procedures taken from the QRFM, but external traffic patterns come from the statewide model. In adSTCC Description Tons per Truck 1 Farm products 8 Forest products 9 Fresh fish or other marine products 10 Metallic ores 11 Coal 13 Crude petroleum, natural gas, or gasoline 14 Nonmetallic minerals, excluding fuels 19 Ordnance or accessories 20 Food or kindred products 21 Tobacco products 22 Textile mill products 23 Apparel or other finished textile products 24 Lumber or wood products 25 Furniture or fixtures 26 Pulp, paper, or allied products 27 Printed matter 28 Chemicals 29 Petroleum or coal products 30 Rubber or miscellaneous plastics products 31 Leather or leather products 32 Clay, concrete, glass, or stone products 33 Primary metal products 34 Fabricated metal products 35 Machinery -- Other than electrical 36 Electrical machinery, equipment, or supplies 37 Transportation equipment 38 Instruments -- Photographic or optical goods 39 Miscellaneous manufacturing products 40 Waste or scrap materials 41 Miscellaneous freight shipments 42 Shipping devices returned empty 43 Mail and express traffic 44 Freight forwarder traffic 45 Shipper association or similar traffic 46 Miscellaneous mixed shipments 47 Small packaged freight shipments 48 Hazardous waste 49 Hazardous materials 99 Unknown 24 13 6 24 24 14 19 24 18 5 5 3 15 3 16 9 22 19 4 3 19 24 9 8 12 5 2 16 23 4 3 4 3 7 4 16 18 12 Note: STCC = Standard Transportation Community Codes.
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From page 50... ...
However, there is more similarity in the freight models, particularly in basing the forecasts on commodity movements. Ohio's model emphasizes how non-freight commercial vehicles can be important to a forecast and might need special treatment apart from freight-carrying vehicles.
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