2
Forecasting Metropolitan Travel

The current practice of metropolitan travel forecasting and the relationships among the agencies that produce the forecasts are grounded in circumstances and events of the past 50 years. To understand the present state of practice, it is important to have some knowledge of the historical context in which metropolitan transportation planning and travel forecasting emerged.

HISTORICAL CONTEXT

Metropolitan Transportation Planning

America’s cities lie within larger metropolitan regions that comprise a patchwork of local governments. The Boston metropolitan region, for example, includes 101 local governments; San Francisco, 111; and Chicago, 274. Each of these constituent towns, cities, or counties manages infrastructure and delivers administrative services within its jurisdiction. There are, however, matters of public interest that transcend the boundaries of local jurisdictions and require regional attention. The transportation system, economic development, and environmental quality are examples of such regional matters.

In the Progressive Era of the early 1920s, as America’s cities grew, the concept of metropolitan regional planning emerged. Lewis Mumford and others founded the Regional Planning Association of America (RPAA) to promote a designed and controlled approach to managing the growth of cities. In the same decade, the Russell Sage Foundation funded the creation of a plan for the New York City region of New Jersey, New York, and Connecticut, and the New York Regional Planning Association was founded to implement the proposals in the plan. RPAA hoped that this New York City initiative would result in a comprehensive approach to regional land



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2 Forecasting Metropolitan Travel T he current practice of metropolitan travel forecasting and the relation- ships among the agencies that produce the forecasts are grounded in circumstances and events of the past 50 years. To understand the present state of practice, it is important to have some knowledge of the historical context in which metropolitan transportation planning and travel forecasting emerged. HISTORICAL CONTEXT Metropolitan Transportation Planning America’s cities lie within larger metropolitan regions that comprise a patch- work of local governments. The Boston metropolitan region, for example, includes 101 local governments; San Francisco, 111; and Chicago, 274. Each of these constituent towns, cities, or counties manages infrastructure and delivers administrative services within its jurisdiction. There are, however, matters of public interest that transcend the boundaries of local jurisdictions and require regional attention. The transportation system, economic devel- opment, and environmental quality are examples of such regional matters. In the Progressive Era of the early 1920s, as America’s cities grew, the concept of metropolitan regional planning emerged. Lewis Mumford and others founded the Regional Planning Association of America (RPAA) to promote a designed and controlled approach to managing the growth of cities. In the same decade, the Russell Sage Foundation funded the creation of a plan for the New York City region of New Jersey, New York, and Connecticut, and the New York Regional Planning Association was founded to implement the proposals in the plan. RPAA hoped that this New York City initiative would result in a comprehensive approach to regional land 19

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METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 20 use planning, one that would lead to a rational distribution of population and economic growth. Instead, the emphasis was on the development of road sys- tems and parks. This transportation-oriented model of regional planning would become prevalent throughout America (Gerckens 2002). Following World War II, the federal government showed increasing interest in addressing urban issues through regional councils. The Housing Act of 1954 for the first time gave federal grants to councils of governments and other metropolitan planning agencies for work to address regional prob- lems (Solof 1996). The Federal-Aid Highway Act of 1956 authorized con- struction of the multibillion dollar, 41,000-mile National System of Interstate and Defense Highways. The act included the Highway Revenue Act of 1956, which created the Highway Trust Fund to receive tax revenues dedicated solely to highway purposes (Weiner 1999). The transportation program thus initiated eventually resulted in more than 46,000 miles of Interstate high- ways, which were to have a huge impact on the landscape and economy of America and its cities. Means of planning the metropolitan infrastructure and operations of a new transportation system were needed. These means were provided first by the Housing Act of 1961, which allowed federal aid for “preparation of comprehensive urban transportation surveys, studies, and plans to aid in solving problems of traffic congestion, facilitating the circu- lation of people and goods on metropolitan and other urban areas, and reducing transportation needs.” This was followed by the Federal-Aid High- way Act of 1962, the first federal legislation to require urban transportation plan- ning as a condition for receiving federal-aid transportation funds in urban areas. According to this act: After July 1, 1965, the Secretary shall not approve under section 105 of this title any programs for projects in any urban area of more than fifty thousand population unless he finds that such projects are based on a continuing, comprehensive transportation planning process carried out cooperatively by states and local communities in conformance with the objectives stated in this section. The act laid the foundation for the current metropolitan transportation plan- ning process and led to the establishment of metropolitan planning organiza- tions (MPOs) for every urbanized area in the country (Weiner 1999). MPOs exist in an unusual stratum of governance. They are designated by agreement between a state governor (or governors in the case of multistate MPOs) and units of local government, a process mandated by the federal gov- ernment through laws enacted by Congress and rules promulgated by the U.S.

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Forecasting Metropolitan Travel 21 Department of Transportation (USDOT). A designated MPO and an ongo- ing planning process are required for federal-aid funding to flow to trans- portation projects within metropolitan areas. MPOs are governed by policy boards comprising local elected officials and representatives of public trans- portation agencies and relevant state agencies. MPOs therefore represent a partnership among the federal government, state governments, and local gov- ernments, created to ensure that a continuing, comprehensive, and coopera- tive transportation planning process is in place in each metropolitan area. MPO policy boards require support from a “staffing agency” to prepare planning documents, conduct studies and make forecasts, and provide logisti- cal support for coordination with other groups. These staffing agencies may be regional planning agencies, councils of government, or in-house staff hired by the MPO policy board. In a few cases, state transportation agencies serve as the staffing agency for the MPO. MPOs receive annual core funding from both the Federal Highway Administration (FHWA) and the Federal Transit Administration (FTA), often with state matching funds. Nationally, the federal share of this funding was $366 million in 2006, up from $161 million in 1992 (see Figure 6-1, Chapter 6). Metropolitan Travel Forecasting A connected national system of limited-access freeways was proposed prior to World War II. The Federal-Aid Highway Act of 1934 provided federal funds to the states for the conduct of survey research. The Federal-Aid Highway Act of 1938 directed the Chief of the Bureau of Public Roads (BPR, called the Public Roads Administration from 1939 to 1949) to investigate the feasibility of “toll superhighways” running from the east to the west and the north to the south of the United States. Supported by data collected by the states, BPR concluded that a toll road network was not viable but that a national network of expressways was needed. Traffic counts and travel sur- veys continued through the 1940s. These studies of volume and direction included information on origins and destinations gathered from license plate studies and driver interviews (Weingroff 2000). In 1944 the Public Roads Administration, working with the U.S. Bureau of the Census, developed a sampling technique for interviewing household members on their travel pat- terns, now known as a “home interview survey” (FHWA 1977). These means

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METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 22 of collecting and organizing travel information are an important basis of today’s metropolitan transportation planning process. In addition to information on current travel patterns, a method for fore- casting future travel was needed. One such method, developed by Thomas Fratar, employed factoring of origin–destination trip patterns to account for growth over time. This method, while still in use for certain applications, lacks an underlying theory and cannot account for future travel if there is none in the present. Other researchers explored the use of a “gravity model” approach to forecasting urban travel. The underlying assumption of the grav- ity model is that urban places will attract travel in direct proportion to their size (population and employment) and in inverse proportion to the distance between them. Alan M. Voorhees organized work on the gravity model into a comprehensive theory of urban travel, published as “A General Theory of Traffic Movement” (Voorhees 1956). The introduction of the gravity model into the travel modeling process allowed planners to forecast future travel on the basis of forecasts of population, households, and employment (Heightchew 1979). Other basic modeling innovations were developed in the 1950s and 1960s as large cities such as Detroit, Chicago, Cleveland, Philadelphia, Washington, D.C., and New York undertook transportation studies to plan for major highway and transit capital investments, in particular the Interstate highway system. These innovations included a model for calculating the split between transit and highway travel (mode choice). Another problem was how to load travel onto a network; this problem was solved through the use of a “mini- mum path algorithm.” Both travel-mode choice models and network loading procedures evolved through a series of improvements of increasing mathemat- ical complexity. Perhaps the most important innovation was the adoption in the 1950s of IBM mainframe computers to store the large amount of infor- mation collected on travel and to run the various models needed to simulate and forecast metropolitan travel. Over time, the use of computers for travel forecasting has evolved into the present practice of using high-speed desktops running software supplied by commercial vendors. As public ownership of and investment in transit increased in the 1960s and 1970s, more sophisticated models were developed to better represent transit and high-occupancy vehicle alternatives. By the 1990s, commercial transportation planning software for microcomputers had largely replaced federally supported transportation planning software for mainframes, but the commercial software retained similar modeling methods and approaches.

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Forecasting Metropolitan Travel 23 All the major technical innovations mentioned in this brief summary are in use for today’s practice of travel forecasting. Home interview surveys and related information are used to estimate travel generated by households and employment sites (trip generation). The gravity model is used to determine how much travel will occur between places (trip distribution). In larger urban areas, a mode-choice model estimates transit trips and car occupancy. Mini- mum path algorithms are used to load travel onto highway and transit net- works (assignment). Forecasts of future travel are made by using forecasts of future demographics. This entire process is termed “travel demand forecast- ing” or the “four-step process.” The metropolitan travel demand forecasting process was born of neces- sity in the postwar era during a time of major capital investment in inter- and intracity transportation systems. The process grew in a piecemeal manner as a linked chain of submodels, each designed to solve a particular problem asso- ciated with the ultimate goal—forecasting future travel to assist in planning the size and location of new and expanded highway and transit facilities. It is notable that these models, as they have evolved, are deterministic, providing point-estimate forecasts. This approach is acceptable for solving simple prob- lems, such as whether a new freeway should have four or six lanes. More com- plex problems might benefit from probabilistic models, which would provide distributions of possible outcomes. While the use of computerized, network-based travel models is not man- dated by federal or state law, most MPOs operate such four-step models as an integral part of their planning process. MPO PLANNING AND TRAVEL DEMAND FORECASTING MODELS As noted above, federal regulations require that urban areas with a population of 50,000 or more either establish a new or join an existing MPO (FHWA 2007b). Urbanized areas with a population of 200,000 or more are desig- nated transportation management areas (TMAs), and the MPOs that serve these areas have stricter requirements. The MPO planning process in a TMA must include a congestion management process to monitor and evaluate the performance of regional transportation facilities. In 2006 there were 384 MPOs. The MPO and its policy board are charged with developing a metropolitan long-range transportation plan with at least a 20-year horizon and a short-range Transportation Improvement

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METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 24 Program comprising projects drawn from the long-range plan. In developing these transportation plans and programs, the MPO is to consider the follow- ing eight factors:1 • Economic vitality of the region; • Safety of the transportation system; • Security of the transportation system; • Accessibility and mobility options; • Environmental protection, energy conservation, and quality of life; • Integration and connectivity of the system; • Efficient system management and operations; and • System preservation. To discharge the above responsibilities, MPO staff must develop a trans- portation plan that reflects a 20-year forecast of future travel. This is com- monly done with the assistance of computerized travel demand models that provide information on how urban growth and proposed facility and opera- tional investments will affect the operation of the transportation system. In addition, MPOs in federally designated air quality nonattainment and maintenance areas must determine whether their regional transportation plans and programs conform to state air quality implementation plans (SIPs) for meeting national air quality standards.2 This transportation conformity evaluation requires MPOs to use forecasts for their Transportation Improve- ment Program and long-range plan to estimate traffic volumes and speeds, which become inputs to the Environmental Protection Agency’s (EPA’s) MOBILE model.3 That model, in turn, provides estimates of future motor vehicle source emissions. These emissions estimates are used to determine whether the proposed transportation plan and programs will result in motor vehicle emission levels that are consistent with those established in state air quality plans and approved by EPA. Under federal “conformity” requirements, if the estimated emissions that result from future vehicle travel exceed the lim- its established in the SIP and transportation conformity cannot be determined, projects and programs may be delayed (FHWA 2007a). 1 23 USC 134(h)(1) and 49 USC 5303(h)(1). 2 The Clean Air Act, last amended in 1990, requires the Environmental Protection Agency to set National Ambient Air Quality Standards (40 CFR Part 50) for pollutants considered harmful to pub- lic health and the environment. 3 In California, EPA has authorized the use of the Emission Factor (EMFAC) model.

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Forecasting Metropolitan Travel 25 Travel demand models also play a significant role in FTA’s New Starts and Small Starts program as a basis for project development and the environmen- tal review process (e.g., preparation of the Environmental Impact Statement). Travel demand forecasts produced by computer models are central to the statutory responsibilities of MPOs. The future is intrinsically clouded by uncer- tainty, and it is critical for MPOs to employ models and modeling practice pro- ducing the best possible forecasts of future travel for alternative scenarios. The following key concepts underlie the most widely used travel demand forecasting procedures: • Human activities are spatially separate, and travel is needed because of that separation. Travel consumes time, money, and resources, but it is nec- essary because of the need to reach activities that are not close by (Stopher and Meyburg 1975). • Demand for travel is, thus, “derived.” Except for certain recreational purposes, people do not demand travel for its own sake. Rather, they demand such daily activities as work, shopping, recreation, and education, and travel allows them to reach these activities (Meyer and Miller 2001). • The analysis of travel is derived from microeconomic theory relating demand to supply in a market setting. Travel demand comprises the volumes of travelers flowing from one place to another. Travel supply includes the available transportation systems (highways, transit, bikeways, and walkways) and their operating features. Price in urban travel markets is represented by travel times or distances and travel costs. The most commonly used metro- politan travel forecasting models represent the interactions among demand, supply, and price in a combined regional travel demand model. More advanced modeling practice may require interfaces with separate supply models to pro- vide detailed information on such transportation system characteristics as speeds, volumes, congestion, delay, and traffic by time of day. Some of these advanced approaches are discussed in more detail in Chapter 6. • Travel demand forecasting is in done in two basic steps: 1. Analyze demand for and supply of travel. 2. Forecast demand for travel through association with forecasts for other variables, such as population, housing, employment, and automobile ownership. Travel demand forecasting models in use by MPOs are sequential systems of component submodels, sometimes referred to as a “model chain” or “model set.” In the present study, “model” refers to the complete system of model

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METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 26 components unless otherwise noted. The entire process in a typical four-step model system is summarized in Chapter 4. EXPANDED REQUIREMENTS FOR METROPOLITAN TRAVEL MODELING MPOs today face a much broader and more complex set of requirements and needs in their travel modeling than they did in the 1960s and 1970s, when the primary concern was evaluating highway and transit system capacity expansions. Some of the most salient of these requirements and the demands they make on modeling practice are discussed below. Chapter 5 reviews the shortcomings of current models for meeting these expanded needs, and Chap- ter 6 reviews advances toward improved modeling practice. Motor Vehicle Emissions and Vehicle Speeds EPA’s currently approved methodologies for estimating motor vehicle emis- sions4 rely heavily on vehicle speeds, a factor to which emissions estimates are extremely sensitive (FHWA 2006). Modeled speed estimates in turn rely on accurate representations of capacity and validation against measures of conges- tion. Since congestion is a determinant of speed and changes with the time of day, time-of-day modeling is necessary. Currently, some MPOs model sepa- rate time periods, but this approach still does not yield a full representation of the continuous time shifting of trips due to changes in congestion levels. More- over, current travel forecasting models are used primarily to produce estimates of vehicle and traveler volumes. Modeled speeds may not accord well with observed speeds and may need to be adjusted through a “postprocessing” pro- cedure prior to being used as inputs to the MOBILE model. The production of accurate representations of vehicle speeds for emissions modeling using the current travel models is therefore a considerable challenge. Induced Travel The report Expanding Metropolitan Highways (TRB 1995) documented the finding that highway capacity expansions that reduce travel times induce new 4 MOBILE6.2 model for areas outside of California and EMFAC within California.

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Forecasting Metropolitan Travel 27 travel on the improved highway facility. This occurs because improved travel times may encourage travelers to change their route, change the time they travel, switch from transit to driving, or make a trip they would not have made when the highway was more congested. The same report also noted that the then-current four-step travel models could not adequately measure induced travel. This finding is significant because it means that the models may underestimate the usage of new or widened highways. To forecast volumes and emissions more accurately, some MPOs have decided to include the induced-travel effects of major capacity additions. The need for such expanded model applications has led to the develop- ment of household activity–based modeling, which starts with activity schedules, vehicle allocations, and the development of tours for each driver. Only a few large MPOs have developed activity-based models, but these models will become more common as the software and data issues involved become more tractable. Activity-based models are discussed in more detail in Chapter 6. Land Use Policies Many growing regions must consider options other than transportation cap- ital improvements for addressing future mobility needs. Their MPOs there- fore need to be able to model land use policies such as increases in overall density, urban growth boundaries, intensification around rail stations, and more mixed housing and employment. Models must be sensitive to these variables. Larger MPOs have respecified their models accordingly, adding the necessary variables in their trip generation and mode-choice model steps. They have also added an automobile ownership step that is sensitive to land use characteristics. Nonmotorized Travel The amount of nonmotorized travel (walking and biking) is affected by urban form (density and mix), road congestion, automobile ownership, and neigh- borhood amenability to walking and biking. As these characteristics change through time, the share of walking and bicycle trips changes as well. Modeling of nonmotorized travel is a major issue for urban areas con- sidering policies of smart growth and transit-oriented development to address

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METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 28 future mobility needs and to reduce vehicle miles traveled and vehicle emis- sions. More broadly, nonmotorized travel can make up nearly 10 percent of the trips in a medium-sized or large urban region. Thus, a model that does not address these modes fails to account for a substantial market share of the region’s travel. Transportation Policies Air quality nonattainment areas must pay increased attention to travel demand management as a means of reducing vehicle emissions. Travel demand man- agement encompasses such policy measures as variable tolls, parking charges, and fuel taxes. Some regions are exploring such measures as a means of con- trolling traffic congestion or raising revenues to pay for highway and transit construction. These pricing policies place additional demands on modeling. For example, time-of-day responses to changes in tolls must be modeled to represent the effects of peak-period tolls. Doing so requires a detailed under- standing of the value of time and behavioral responses to time-variable prices for different segments of the traveling public. Cumulative and Secondary Impacts The National Environmental Policy Act requires assessment of the impacts of new or expanded transportation facilities, which often includes the growth- inducing impacts of projects. Recent research has yielded estimates of the elasticity of development (permits per year) with respect to changes in driving speed and changes in freeway capacity (Cervero 2003). Methods for estimating induced land development impacts range from professional judg- ment to use of expert panels or formal models. Several MPOs and state departments of transportation have used expert panels, a practice that has been documented in published reports (FHWA 2003). Several other MPOs have used formal integrated “urban models” that combine land use and travel forecasting, and models that are stronger in their adherence to theory have recently come into use (Wegener 2005) and are discussed in the literature (Wegener 2004; Hunt et al. 2005). Several MPOs, such as that in the Sacra- mento region, are applying the newest land use models in conjunction with tour-based and activity-based travel models.

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Forecasting Metropolitan Travel 29 Environmental Justice The human environment is a key consideration in the transportation plan- ning and decision-making processes. Presidential Executive Order 12898 (Federal Actions to Address Environmental Justice in Minority Populations and Low Income Populations) was signed in February 1994. It requires agen- cies to account for and avoid disproportionate adverse impacts on low- income and minority households or disproportionate distribution of benefits. To implement this executive order, USDOT and FHWA and FTA have published program guidance specifying that MPOs should have processes in place for assessing the environmental justice impacts of trans- portation plan investments (USDOT 1997; FHWA and FTA 1999). These impacts can be analyzed with census household data or with more complete methods that include measures of traveler economic welfare by income class. Economic Development Some regions and states are becoming interested in how changes in the transportation system affect economic growth. Certain types of statewide and combined transportation–land use integrated urban models can pro- duce performance measures for wages, land rents, and economic growth rates. Some MPOs are adding heavy-truck models, and larger MPOs are developing goods movement models, which provide more complete repre- sentations of total vehicle movements. Truck traffic is forecast to increase more rapidly than automobile traffic as a result of higher consumption of goods per capita, just-in-time manufacturing, and increased global trade. Projecting changes in economic development requires that agencies under- take new modeling practices. But a travel model does not encompass the total economy, just personal travel. Urban models represent an opportunity to measure changes in the economy in much more inclusive ways. Metropoli- tan regions and states that use commodities movement models with a mode- choice step can obtain a more accurate version of the economic benefits of alternative transportation investments because these models represent the costs of goods movement more accurately. Some urban models can also project changes in total production for different economic sectors. Such a set of mea- sures is useful in many cases. The 2004 Oregon Bridge Study, for instance, used

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METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 30 this set of economic impact measures to determine priorities for bridge repair or reconstruction (Weidner et al. 2005). Many MPOs and a few states are developing urban models to represent future land use patterns more accu- rately but will also be able to use these models to obtain various measures of changes in economic development. Planning for Emergencies Travel models are increasingly being employed to plan evacuations due to natural disasters, to plan immunization programs, and to conduct risk assess- ments related to homeland security. The events of September 11, 2001, exemplify the need for these new modeling applications and, in turn, the need to develop new modeling practices and data that are appropriate for emergency planning. Changes in Population Demographic trends anticipated in the United States over the coming decades may have effects on travel demand and thus pose new challenges for modelers. These trends include the aging of the population, continued increases in population growth, and increases in immigrant populations (Little and Triest 2001): • Those aged 65 and older will grow to 20 percent of the population by 2030. The increased older population will be located disproportionately in low-density areas, with attendant mobility, access, and road safety issues (Herbel et al. 2006). • While U.S. population growth is expected to slow in the coming years, an overall increase of almost 25 percent is expected from 2005 to 2030. This growth will be highly concentrated in the south and west, particularly Cali- fornia, Texas, and Florida. New demand for transportation facilities will be especially acute in higher-growth areas, and certain types of travel modeling may be specific to these needs (PB Consult 2006). • The Census Bureau has projected that new immigrants and their off- spring will account for about two-thirds of U.S. population growth from 1998 to 2100. It is challenging to forecast and plan for the impacts of this popula- tion shift on urban development and travel demand (Little and Triest 2001).

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Forecasting Metropolitan Travel 31 Summary The changes in demography, federal laws, and transportation policies discussed above have resulted in a need for models that are (a) more completely speci- fied, to address more variables of interest; (b) more disaggregate in time, space, and categories of activities; and (c) better able to account for supply-side effects (traffic operations). SUMMARY FINDINGS The current practice of metropolitan travel forecasting and the relationships among the responsible agencies are grounded in circumstances and events of the past 50 years. Following World War II, the federal government showed increasing interest in addressing urban issues through regional councils. The Housing Act of 1961 and the Federal-Aid Highway Act of 1962 laid the foundation for the current metropolitan transportation planning process and led to the establishment of MPOs for every urbanized area in the country. A designated MPO and an ongoing planning process are required for federal-aid funding to flow to transportation projects within metropolitan areas. MPOs are des- ignated by agreement between a state governor (or governors in the case of multistate MPOs) and units of local government. This is a requirement of the federal government through laws enacted by Congress and rules promulgated by USDOT. MPOs represent a partnership among the federal, state, and local gov- ernments, created to ensure that a continuing, comprehensive, and coop- erative transportation planning process is in place in each metropolitan area. MPOs receive annual core funding from both FHWA and FTA, often with state matching funds. Nationally, the federal share of this funding was $366 million in 2006, up from $161 million in 1992. In 2006 there were 384 MPOs. The MPO and its policy board are charged with developing a metro- politan long-range transportation plan with at least a 20-year horizon and a short-range Transportation Improvement Program comprising projects drawn from the long-range plan. The major technical innovations in use for today’s practice of travel forecasting were developed in the 1950s and 1960s through transportation studies in such cities as Detroit, Chicago, Cleveland, Philadel- phia, Washington, D.C., and New York. The entire process is termed “travel

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METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 32 demand forecasting” or the “four-step process.” While the use of comput- erized, network-based travel models is not mandated by federal or state law, most MPOs operate such four-step models as an integral part of their planning process. The analysis of travel is derived from microeconomic theory relating demand to supply in a market setting. Travel demand comprises the volumes of travelers flowing from one place to another. Travel supply includes the available transportation systems (highways, transit, bikeways, and walkways) and the operating features of those systems. Travel demand models, as they have evolved, are deterministic, provid- ing point-estimate forecasts. This approach is acceptable for solving simple problems, such as whether a new freeway should have four or six lanes. Today, however, MPOs face a much broader and more complex set of requirements and needs in their travel modeling than they did in the 1960s and 1970s, when the primary concern was evaluating highway and transit system capac- ity expansions. They must now account for or evaluate such issues as the following: • Motor vehicle emissions and vehicle speeds; • Induced travel; • Alternative land use policies; • Nonmotorized travel (walking and bicycling); • Transportation policies, such as congestion pricing; • Cumulative and secondary impacts of transportation facilities; • Environmental justice, or avoiding disproportionate adverse impacts on low-income and minority households or disproportionate distribution of benefits; • Economic development; • Emergencies due to weather, health, or threats to homeland security; and • Demographic changes. Changes in demography, federal laws, and transportation policies have resulted in a need for models that are (a) more completely specified, to address more variables of interest; (b) more disaggregate in time, space, and categories of activities; and (c) better able to account for supply-side effects (traffic operations).

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Forecasting Metropolitan Travel 33 REFERENCES Abbreviations FHWA Federal Highway Administration FTA Federal Transit Administration TRB Transportation Research Board USDOT U.S. Department of Transportation Cervero, R. 2003. Road Expansion, Urban Growth, and Induced Travel. Journal of the Amer- ican Planning Association, Vol. 69, No. 2, pp. 145–163. FHWA. 1977. America’s Highways, 1776–1976. Washington, D.C. FHWA. 2003. Use of Expert Panels in Developing Land Use Forecasts. Proceedings of a Peer Exchange. FHWA-EP-03-01. Washington, D.C. FHWA. 2006. FHWA Transportation Conformity Reference Guide. March. www.fhwa. dot.gov/environment/conformity/ref_guid/coverpag.htm. Accessed April 7, 2006. FHWA. 2007a. Air Quality Planning for Transportation Officials. Transportation Confor- mity. www.fhwa.dot.gov/environment/aqplan/aqplan12.htm. Accessed Feb. 20, 2007. FHWA. 2007b. Metropolitan Planning Organization Designation and Redesignation. FHWA 23 CFR Part 450.310. a257.g.akamaitech.net/7/257/2422/01jan20071800/edocket. access.gpo.gov/2007/07-493.htm. FHWA and FTA. 1999. Implementing Title VI Requirements in Metropolitan and Statewide Planning. Memorandum from K. Wykle and G. Linton to FHWA Division Administra- tors and FTA Regional Administrators, Oct 7. www.fhwa.dot.gov/environment/ejustice/ ej-10-7.htm. Gerckens, L. 2002. Regional Planning. Champlain Planning Press. www.plannersweb.com/ planning-abcs/r.html. Heightchew, R. E. 1979. TSM: Revolution or Repetition. ITE Journal, Vol. 48, No. 9, pp. 22–30. Herbel, S. B., S. Rosenbloom, J. Stutts, and T. Welch. 2006. The Impact of an Aging Pop- ulation on Systems Planning and Investment Policies. NCHRP 08-36 Task 50 Final Report. Transportation Research Board of the National Academies, Washington, D.C. Hunt, J. D., D. S. Kriger, and E. J. Miller. 2005. Current Operational Land-Use Transport Modelling Frameworks: A Review. Transport Research, Vol. 25, No. 3, pp. 329–376. Little, J. S., and R. K. Triest. 2001. The Impact of Demographic Change on U.S. Labor Mar- kets. In Conference Series 46: Seismic Shifts: The Economic Impact of Demographic Change (J. S. Little and R. K. Triest, eds.), Federal Reserve Bank of Boston, Mass. Meyer, M. D., and E. J. Miller. 2001. Urban Transportation Planning: A Decision-Oriented Approach. McGraw-Hill, Boston, Mass. PB Consult. 2006. Future Options for the National System of Interstate and Defense High- ways. Working papers, NCHRP Project 20-24 (52). www.trb.org/TRBNet/Project Display.asp?ProjectID=558.

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METROPOLITAN TRAVEL FORECASTING Current Practice and Future Direction 34 Solof, M. 1996. History of Metropolitan Planning Organizations. North Jersey Transportation Planning Authority, Inc., Newark, N.J. Stopher, P., and A. Meyburg. 1975. Urban Transportation Modeling and Planning. D.C. Heath, Lexington, Mass. TRB. 1995. Special Report 245: Expanding Metropolitan Highways: Implications for Air Qual- ity and Energy Use. National Research Council, Washington, D.C. USDOT. 1997. U.S. Department of Transportation Order on Environmental Justice. Fed- eral Register, Vol. 62, No. 721, pp. 18377–18381, April 15. Voorhees, A. M. 1956. A General Theory of Traffic Movement. 1955 Proceedings, Institute of Traffic Engineers, New Haven, Conn. Wegener, M. 2004. Overview of Land-Use Transport Models. In Handbook of Transport Geography and Spatial Systems (D. A. Hensher, K. J. Button, K. E. Haynes, and P. Sto- pher, eds.), Vol. 5 of Handbooks in Transport, Pergamon/Elsevier Science, Kidlington, United Kingdom. Wegener, M. 2005. Integrated Land-Use Transport Modelling Progress Around the Globe. Presented at Fourth Oregon Symposium on Integrated Land-Use Transport Models, Portland, Nov. www.oregon.gov/ODOT/TD/TP/docs/Modeling/4symp/1115_930. pdf. Weidner, T. J., B. J. Gregor, M. Wert, and J. D. Hunt. 2005. Oregon Bridge Investment Alternatives: Using Integrated Modeling and Analysis in Policy Decisions. Presented at 84th Annual Meeting of the Transportation Research Board, Washington, D.C. Weiner, E. 1999. Urban Transportation Planning in the United States. Praeger, Westport, Conn. Weingroff, R. F. 2000. The Genie in the Bottle: The Interstate System and Urban Problems, 1939–1957. Public Roads, Vol. 64, No. 2. http://www.tfhrc.gov/pubrds/septoct00/ urban.htm.