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22 into a statewide model. Therefore, many states have opted for vague, shows how the behavioral realism of the model affects other sources of economic forecasts. The following is a list of the uses to which the model can be put. the sources, in order of prevalence. State agency forecast (8) PASSENGER COMPONENTS A regional economic model (5) Statewide travel forecasting models are often thought of hav- An IO model (4) ing two equally complex components: passenger and freight. MPO databases (4) In some models, vehicles in commercial service that do not BEA (4) carry freight are treated separately. With a few exceptions, Commercial forecast vendor (3) passenger components look much like urban travel forecast- State DOT (2) ing models in structure; containing the four major steps of University (1) trip generation, trip distribution, model spit, and trip assign- None or not mentioned (3) ment. Oregon's model and Ohio's new model (see chapter three) have more complex structures, but the four traditional The largest number of states obtain their economic fore- steps are still present, conceptually. This section deals pri- casts from another state agency. Five states use a regional marily with details of how the four steps are implemented. economic model, either a commercial model or one devel- oped particularly for the statewide model, and three states use an IO model. As with employment data, a few states ef- Passenger Component Data ficiently rely on their MPOs for economic forecasts. States use a wide variety of data sources to calibrate their statewide models, although only a few sources are used in Generic Model Structures each state. The following are the data sources identified by states in order of prevalence. There is an intrinsic relationship between model structure and the policies and projects that can be addressed, as illustrated in CTTP (13) Figure 3. This figure can be interpreted either backwards or for- Census journey-to-work data (11) wards, depending on whether it is illustrating part of the model NCHRP Report 365 (10) design process or model operation. The structure of the model NHTS normal sample (10) dictates what it can reasonably produce as outputs, and the out- MPO household survey(s) or puts limit what can be accomplished by the model when adding panel(s) (9) information to the decision process. However, the design of the ATS (9) model is largely derived from what the model is intended to ac- Own household survey (8) complish. Conceptually this is a two-stage process, where the Institute of Transportation Engineers (ITE) issues needing to be addressed dictate the required model out- Trip Generation (7) puts, which further dictate the model structure. PUMS (7) Roadside survey(s) (6) Figure 4 expands the relationship between the first two NHTS add-on (5) items in Figure 3, the generic structure and the range of model NCHRP Report 187 (5) outputs. There are essentially six generic structures, ranging GPS-based survey (3) from statistical trend analysis to an integrated model of freight, Amtrak (2) passenger travel, and economic activity. The behavioral real- Intercity bus service (2) ism generally increases from left to right, except for the dis- FAA sample ticket data (2) tinction between freight-only and passenger-only models. Al- Ferry service (1) though freight-only models may be as sophisticated as Tourism survey (1) passenger-only models, their use for traffic operational analy- Own on-board rail survey(s) (1) sis is limited. The arrow in Figure 4, deliberately drawn to be Bus onoff counts (1) Other agency survey (1) Design The extensiveness of this list of calibration data sources indicates that modelers are being quite resourceful; using Generic Range of Issues to Be Structure Model Outputs Addressed what is readily available and augmenting as necessary. With home interview surveys costing approximately $165 per sample (based on the cost of an NHTS add-on), there is a Operation strong advantage to exploiting whatever data have already FIGURE 3 Relationship between model structure and policies been collected. The most often cited data source was the and project decision making. CTPP. A total of 11 states either did their own household
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23 Generic Structures Integrated OD Table Combined Passenger, Trend Passenger Estimation & Freight Only Passenger & Freight & Analysis Only Assignment Freight Economic Activity Individual Link ADT Generalized Outputs Freight or Passenger Volumes Across State Inputs to Traffic Operational Analysis Details of Freight and Passenger Volumes Transport Effect on Economic Development FIGURE 4 Generic model structures and their potential outputs. survey or funded an NHTS add-on. Connecticut reported us- Another state agency (5) ing both a household survey and an NHTS add-on, although A regional economic model (4) the survey dated back to the 1970s. California did the most Commercial data vendor (4) extensive home interview survey of their own with 17,000 School enrollment data (3) samples. Seven states tapped into MPO household surveys. A state natural resources department (2) Ten states used either NCHRP Report 187 (Sosslau et al. Local property tax records (1) 1978) or NCHRP Report 365 (Martin and McGuckin 1998) GIS maintained by another agency within your state (1) for transferable parameters. Maine transferred parameters from the Michigan model. Although the ATS is now 10 years There were only a few sources of highway traffic data, old, many states believe that it is still essential. The ATS is with most states relying on their own counts or their own the only comprehensive data source on long distance travel. Highway Performance Monitoring System (HPMS) data- base. Only six states used either their own speeds or travel The NHTS add-ons varied greatly in size. Wisconsin times. Massachusetts was the only state reporting that it ob- bought the largest number of samples (17,610) and Massa- tained counts from other states. chusetts bought the fewest (500). Own agency counts Interestingly, Oregon did not use the NHTS, but performed (18) four different surveys in support of its statewide models, as HPMS (11) well as MPO models: Household Activity and Travel Survey, Own agency speeds (6) Oregon Travel Behavior Survey, Recreation/Tourism Activity Own agency travel times (5) Survey, and Continuous Oregon Survey for Oregon Models. Toll or bridge authority counts (5) Counts, speeds, or travel times from another Household socioeconomic data came from a few obvious agency (2) sources as listed here. The U.S. Census dominated as a data Other states (1) source, followed by MPO databases, which most likely were derived largely from the U.S. Census. Five states obtained Building passenger networks is an expensive and time- employment data from another state agency, although there consuming task. Data that would allow the construction of were often considerable problems using such data. statewide passenger networks (links and nodes) came mostly through MPO networks or through DOT road inventory sys- Other U.S. Census than tems. The National Highway Planning Network (NHPN) was CTPP (15) used principally for out-of-state portions of the network. CTTP (12) Delaware and Rhode Island asked neighboring states for net- MPO databases (10) work data. For out-of-state highway networks, Florida and