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Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288 (2007)

Chapter: 3 Institutional Framework for Travel Demand Modeling

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Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
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Page 35
Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
×
Page 36
Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
×
Page 37
Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
×
Page 38
Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
×
Page 39
Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
×
Page 40
Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
×
Page 41
Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
×
Page 42
Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
×
Page 43
Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
×
Page 44
Suggested Citation:"3 Institutional Framework for Travel Demand Modeling." Transportation Research Board. 2007. Metropolitan Travel Forecasting: Current Practice and Future Direction -- Special Report 288. Washington, DC: The National Academies Press. doi: 10.17226/11981.
×
Page 45

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

3 Institutional Framework for Travel Demand Modeling T he federal government, state transportation agencies (STAs), and metropolitan planning organizations (MPOs) have historically shared responsibilities for developing travel demand models and making metropolitan travel forecasts. Initially, federal agencies took the lead in developing travel fore- casting methods and software and were able to devote substantial staff and finan- cial resources to this effort. Through time, these responsibilities have devolved to the states, MPOs, and the private sector. Following is a discussion of how the federal government, the STAs, and the MPOs work together to accom- plish metropolitan travel forecasting. FEDERAL GOVERNMENT In the 1950s and 1960s, the Bureau of Public Roads (BPR) led the develop- ment of standardized computer programs for simulating and forecasting travel on urban highway networks. These models were essential to those conducting metropolitan transportation studies, who did not have the resources to develop their own programs. BPR staff also provided substantial assistance to state and local planners wishing to apply these new models, which collectively became known as PLANPAC (Weiner 1999). Indeed, during this period it was not unusual “for BPR employees to actually staff and run the Planning Survey oper- ations for a state” (Mertz n.d.). Computer programs for transit planning were also developed in the mid-1960s by the U.S. Department of Housing and Urban Development, which had responsibility for the federal transit program. A new version of these programs was released by the Urban Mass Transporta- tion Administration (UMTA) in 1973 as the Urban Transportation Planning 35

METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 36 System (UTPS). In 1976, the Federal Highway Administration (FHWA) (the successor to BPR) decided to join UMTA in supporting the UTPS package. UTPS was supported by the federal government as the standard set of pro- grams for metropolitan travel forecasting from the mid-1970s to the late 1980s. Running the programs required an IBM mainframe computer, which most STAs and large MPOs either owned or could access. UTPS encompassed the primary submodels of the four-step process—trip generation, trip distri- bution, mode split, and traffic assignment. FHWA and UMTA provided soft- ware, training, and manuals for both basic and advanced practice in setting up and running the UTPS models. Users were responsible for establishing area systems, coding networks, providing local data, and calibrating the models to local conditions. In some states, such as Ohio, the STA assumed responsibil- ity for setting up and running all the models (Ohio Department of Trans- portation 2006). In other states, the STA addressed the modeling needs of smaller MPOs, and the larger MPOs were self-sufficient. In still other states, the MPOs handled all their own modeling needs. In the 1980s, advances in the storage capacity and speed of micro- computers allowed them to replace mainframe computers for running the travel forecasting models. Within a decade, the common practice evolved from modeling on mainframe computers to reliance on microcomputers, and while operating systems differed, the basic computational approaches to travel modeling remained the same. By 1989 FHWA and the Federal Tran- sit Administration (FTA) had stopped providing user support for mainframe UTPS applications, and the transition to microcomputers was nearly com- plete. Responsibility for the development and operation of travel forecasting models had shifted from the federal government to STAs and MPOs, with support from the private sector and universities. This devolution of modeling responsibilities and engagement of the pri- vate sector might have been expected to result in the emergence of new and improved modeling approaches and practices. In fact, as the survey of MPOs described in Chapter 4 shows, the basic practice of travel forecasting has changed little since the days of UTPS. The most significant advances have been in computer technology and such software enhancements as improved graphical displays and geographic information systems. The federal government has not become a disinterested bystander with respect to metropolitan travel forecasting, however. A robust travel forecast- ing process with which to estimate travel impacts and facility needs is neces- sary to meet the requirements of federal laws, in particular the Clean Air Act,

Institutional Framework for Travel Demand Modeling 37 the National Environmental Policy Act (NEPA), and the recently enacted Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (SAFETEA-LU). FTA has taken a particular interest in the adequacy of travel forecasts. New Starts is a discretionary grant program, so FTA is careful to ensure that candidate projects compete on an equal basis. The projected ridership for projects under consideration and the associated benefits are key factors in FTA’s evaluation. The agency carefully reviews the travel forecasting proce- dures employed to ensure that they are free of factors that would bias the results. In addition, SAFETEA-LU established a requirement that projects receiving funding under the New Starts program be the subject of before- and-after studies. Those studies are to document how the ridership achieved under the project compares with the forecasts made during project planning, thus establishing a formal and regular process for retrospective analysis of travel forecasts for major transit projects. FTA intends that the data collected and analyses performed in these studies contribute to improved travel fore- casting procedures. FTA has published guidance for New Starts that includes reporting instruc- tions specific to travel forecasting procedures (FTA 2006). These instructions note a guiding principle: “to make sure that the travel forecasting approach does not bias the results in favor of any particular alternative.” In keeping with this principle, FTA asks that the chief executive officer of an agency applying for New Starts funding certify in writing the adequacy of the tech- nical methods employed, including use of the best available data and quality assurance reviews to identify and correct any large forecasting errors. In addi- tion, applicants must use the FTA reporting tool Summit with the results of their travel forecasting model to calculate user benefits. Summit also imposes a rigor in quality control of travel forecasts by producing summary tables and color-coded maps that easily identify anomalies in travel patterns that high- light erroneous or illogical results in the travel forecasts. There may be some risks in applying such a structured approach. For exam- ple, in the experience of the committee, agencies administering NEPA and New Starts requirements have sometimes interpreted them to mean that pop- ulation and employment allocations must remain fixed throughout a multisce- nario analysis. This restriction does not encourage the development and use of land use allocation models. FTA and FHWA jointly conduct a certification of each transportation management area (TMA) at least every 4 years to ensure the adequacy of the

METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 38 transportation planning process. The TMA certification process includes a review of travel forecasting methods that typically assesses the following: • Such factors as whether the MPO is currently applying for an FTA New Starts grant, air quality nonattainment status, planning for major projects that will increase highway capacity, local opposition to transportation plans, and threatened or actual legal actions that challenge the adequacy of travel forecasting methods; • Measures of technical capability, including the training and experience of MPO staff, the adequacy of funding allocated for improving travel models, and peer review of travel forecasting methods; and • Documentation of travel forecasting methods. FHWA takes the lead for the Travel Model Improvement Program (TMIP), which comprises a number of activities designed to support metropolitan travel forecasting, including development of the TRANSIMS advanced model suite. These activities are discussed in Chapter 6. STATE TRANSPORTATION AGENCIES STAs are increasingly developing and using statewide travel forecasting mod- els that can be applied in coordination with the metropolitan area models within the state. Statewide models can provide valuable information for use in metropolitan modeling, such as information on freight flows and long-distance passenger travel. This information is often difficult to obtain from within the metropolitan area. A recent study (Horowitz 2006) reviews the current state of practice in statewide travel forecasting models. Currently, about half of the 50 states have such models operational or in development. These models have many uses, including statewide transportation planning, intercity corridor planning, eco- nomic development studies, and freight planning. Most follow the urban models closely in structure for forecasting of passenger travel. For freight fore- casting, there is a trend away from truck models designed primarily to pro- duce estimates of truck volumes on roadway segments toward models of commodity flows that permit analysis of a wider range of modal options for moving freight. Three states—California, Ohio, and Oregon—are implement- ing a new modeling paradigm that integrates economic activity and land use into the travel model.

Institutional Framework for Travel Demand Modeling 39 In the future, statewide and metropolitan travel models may share com- mon networks and zone systems and a common goal of seamless forecasting of the impacts of freight, passenger, and land use policies and major capital investments. COMBINED EFFORTS OF STAs AND MPOs Continuing federal interest notwithstanding, STAs and MPOs have assumed increased responsibility for model development and forecasting of metropol- itan travel. To explore how STAs and MPOs work together in carrying out these responsibilities, the committee surveyed the 50 states at the outset of this study, in 2004. All 50 states, representing all 384 of the current MPOs, responded. For purposes of reporting the survey results, MPOs were classified into three groups according to population, as shown in Figure 3-1. Just over half of the MPOs (55 percent) are in areas with populations of 50,000 to >1,000,000 11% 200,000–1,000,000 50,000–200,000 34% 55% FIGURE 3-1 MPOs by population.

METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 40 200,000, 34 percent in areas with populations of 200,000 to 1 million, and 11 percent in areas with greater than 1 million population.1 Sixteen states indicated that they provided MPOs with formal guidance for model development and forecasting. Some states, such as Florida and Kentucky, required that all MPOs use the same software. Some had formal guidelines, some had less formal minimum standards, and some provided training for MPO staff. In each case, there was a clear intent to achieve uni- formity of practice and quality assurance of the modeling work being done by the MPOs. In addition, 14 states (Arkansas, Connecticut, Delaware, Georgia, Michigan, Montana, North Carolina, North Dakota, Ohio, Rhode Island, Texas, Virginia, Wisconsin, and Wyoming) performed model devel- opment and forecasting for many or all MPOs in the state. These states had direct control over the travel forecasting process. For the three categories of MPO by population size, the STAs and MPOs worked together in model development and forecasting as follows: • Population 50,000 to 200,000: Under federal regulations, urban areas with populations of more than 50,000 must have a metropolitan transporta- tion planning process that meets all legislative and regulatory requirements. However, those with populations below 200,000 and not in a nonattainment or maintenance area for ozone or carbon monoxide may be allowed to develop an abbreviated metropolitan transportation plan and Transportation Improvement Program. Figure 3-2 shows the breakdown of modeling and forecasting between states and MPOs for this class of small MPOs. • Population 200,000 to 1 million: Urban areas with populations of more than 200,000 are designated by federal regulations as TMAs, and the MPOs that serve them are required to create and maintain a congestion management process in addition to carrying out the entire set of MPO responsibilities. Fig- ure 3-3 shows the breakdown of modeling and forecasting between states and MPOs for these medium-sized MPOs. • Population exceeding 1 million: These MPOs are likely to have more complex planning requirements and to account for multiple transit modes in their modeling processes. Figure 3-4 shows the breakdown of modeling and forecasting between states and MPOs for these larger MPOs. As might be expected, most (89 percent) did their own model development and forecast- ing with or without some STA assistance. Rhode Island and Virginia were 1 While there are officially 384 MPOs, 381 were identified by this survey. By population range, they are as follows: 50,000 to 200,000, n = 208; 200,000 to 1 million, n = 130; more than 1 million, n = 43.

Institutional Framework for Travel Demand Modeling 41 MPO develops models and makes forecasts without state technical assistance 8% MPO develops models; state provides technical assistance 28% No modeling 15% State develops models and makes forecasts 42% State develops models; MPO makes forecasts 7% FIGURE 3-2 MPOs with population 50,000 to 200,000. the only states with primary responsibility for modeling for large MPOs (for Providence and Hampton Roads). An important finding of this survey is the extent to which STAs were directly involved in model development and forecasting, in particular for small and medium MPOs; of those small or medium MPOs that did mod- eling, the STA did all model development and forecasting for 37 percent. Another significant finding is that a number of states (16) provided MPOs with guidance aimed at standardizing modeling practice. Another study identified 16 states in which STAs organize statewide MPO model user groups that meet regularly and provide such services as staff training, technology transfer, and pooled purchase of software licenses (FHWA 2007). In one state (New York), the MPOs and the state have entered into a shared-cost multiyear research and development program.2 2 Overview of New York’s Shared Cost Initiative. Personal communication (e-mail) from John Poor- man to Jon Williams, March 28, 2006.

MPO develops models and makes forecasts without state technical assistance 8% State develops models and makes forecasts 27% MPO develops models; state provides technical assistance 55% State develops models; MPO makes forecasts 10% FIGURE 3-3 MPOs with population 200,000 to 1 million. MPO develops models and makes forecasts without state technical assistance 9% State develops MPO develops models and makes models; state forecasts provides 9% technical assistance 77% State develops models; MPO makes forecasts 5% FIGURE 3-4 MPOs with population exceeding 1 million.

Institutional Framework for Travel Demand Modeling 43 The federal government, the states, and the MPOs have a strong shared interest in the production of accurate travel forecasts to guide investments and operational planning. The public interest is best served by coordination of model development and implementation activities among these levels of government. This would be a natural role for the federal government and other national orga- nizations. Chapter 6 explores how the research and development activities of the various levels of government and other entities could be better integrated. SUMMARY FINDINGS AND RECOMMENDATIONS The federal government, STAs, and MPOs have historically shared respon- sibilities for developing travel demand models and making metropolitan travel forecasts. Initially, federal agencies took the lead in developing travel forecasting methods and software and were able to devote substantial staff and financial resources to these efforts. Over time, these responsibilities have devolved to the states, MPOs, and the private sector. Computer programs for transportation planning were developed in the mid-1960s. By 1973, they had evolved into UTPS, which required an IBM mainframe computer. The federal government provided software, training, and manuals for setting up and running the UTPS models. In some states, the STA assumed responsibility for setting up and running all the models. In other states, the STA addressed the modeling needs of smaller MPOs, and the larger MPOs were self-sufficient. In still other states, the MPOs handled all their own modeling needs. In the 1980s, advances in microcomputers allowed them to replace main- frame computers for running the travel forecasting models. Within a decade, this shift had become commonplace. The basic computational approaches to modeling travel that had been used on mainframes were employed in the desk- top versions that succeeded them. By 1989, FHWA and FTA had stopped providing user support for mainframe UTPS, and the transition to micro- computers was nearly complete. Responsibility for the development and oper- ation of travel forecasting models had shifted from the federal government to STAs and MPOs, with support from the private sector and universities. Despite this devolution of modeling responsibilities and engagement of the private sector, the basic practice of travel forecasting has changed little since the days of UTPS. The most significant advances have been in computer technology and such software enhancements as improved graphical displays and geographic information systems.

METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 44 At the same time, the federal government retains an interest in metropol- itan travel forecasting. FTA has taken a particular interest in the adequacy of travel forecasts. New Starts is a discretionary grant program, so FTA is care- ful to ensure that candidate projects compete on an equal basis. The com- mittee commends FTA for taking steps to ensure quality in the travel forecasting methods used for major project planning. FTA and FHWA jointly conduct a certification of each TMA at least every 4 years to ensure the adequacy of the transportation planning process; this includes a review of travel forecasting methods. The federal MPO certi- fication process, which, with a model checklist, provides MPOs with use- ful information on minimum expectations for their models, should be continued. In addition, examination of the conduct and results of MPO peer reviews should be incorporated into the certification process (see Chapter 4). TMIP, sponsored by FHWA, has the mission of supporting metropolitan travel forecasting. TMIP is discussed in detail in Chapter 6. STAs are increasingly developing and applying statewide travel forecast- ing models, which may be applied in coordination with the metropolitan area models within the state. Statewide models have the potential to provide valu- able information for metropolitan modeling practice. In the future, statewide and metropolitan travel models may share common networks and zone sys- tems and a common goal of seamless forecasting of the impacts of freight, passenger, and land use policies and major capital investments. STAs and MPOs often work together in travel model development and forecasting. The committee’s survey of the states found that STAs were responsible for model development and forecasting for 42 percent of small, 24 percent of medium, and 3 percent of large MPOs. Other useful state activ- ities in support of MPOs include establishing guidelines for standardizing modeling practice and forming statewide model user groups for such pur- poses as training and joint acquisition of computer software and hardware. States play a particularly important role in supporting smaller MPOs but should also be collaborating with larger MPOs within their borders. The committee believes this can be accomplished in the following ways: • Support for the development of a national MPO cooperative research program (described in Chapter 6); • Support for model user groups;

Institutional Framework for Travel Demand Modeling 45 • Evaluation, in cooperation with MPOs, of socioeconomic forecasts used for MPO modeling and forecasting; and • Coordination with MPOs on statewide and metropolitan models and data needs. This chapter has reviewed the institutional relationships among the fed- eral government, the states, and the MPOs in developing travel models and making forecasts. These relationships have evolved over time, with the fed- eral government playing a less prominent role. The next chapter presents information on the current state of travel forecasting practice. REFERENCES Abbreviations FHWA Federal Highway Administration FTA Federal Transit Administration FHWA. 2007. Model User Groups. tmip.fhwa.dot.gov/dbtw-wpd/exec/dbtwpub.dll?QF0= MUG_State_Area&QI0=*&TN=tmipcontacts&RF=MUG&DL=0&RL=0&NP=3& AC=QBE_QUERY. FTA. 2006. Guidance on New Starts Policies and Procedures. May 16. www.fta.dot.gov/ planning/newstarts/planning_environment_5203.html. Horowitz, A. 2006. NCHRP Synthesis of Highway Practice 358: Statewide Travel Forecasting Models. Transportation Research Board of the National Academies, Washington, D.C. Mertz, L. n.d. Memories of 499. www.fhwa.dot.gov/infrastructure/memories.htm. Ohio Department of Transportation. 2006. A Brief History. Modeling and Forecasting Sec- tion. www.dot.state.oh.us/urban/AboutUs/history.htm. Weiner, E. 1999. Urban Transportation Planning in the United States. Praeger, Westport, Conn.

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TRB Special Report 288, Metropolitan Travel Forecasting: Current Practice and Future Direction, examines metropolitan travel forecasting models that provide public officials with information to inform decisions on major transportation system investments and policies. The report explores what improvements may be needed to the models and how federal, state, and local agencies can achieve them. According to the committee that produced the report, travel forecasting models in current use are not adequate for many of today's necessary planning and regulatory uses.

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