4

Travel Demand

An argument against adding highway capacity is that the roads will simply fill up again with traffic as service levels improve. Traffic conditions, the argument continues, will become congested again but with larger traffic volumes, thus increasing total emissions and energy consumption. In this chapter the current knowledge about the stimulative effects of highway capacity projects on motor vehicle trips and travel is reviewed (Figure 4-1). An introductory section on the primary determinants of travel demand and recent travel trends is provided.

DETERMINANTS OF METROPOLITAN TRAVEL DEMAND AND RECENT TRAVEL TRENDS IN THE UNITED STATES

Travel is a derived demand; that is, it is derived from the activities of households and businesses that locate in a metropolitan area. Travel activities can be classified as commercial, involving goods movement and distribution, and personal. Personal travel is typically categorized as work travel and other personal travel (e.g., for shopping or recreation).



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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use 4 Travel Demand An argument against adding highway capacity is that the roads will simply fill up again with traffic as service levels improve. Traffic conditions, the argument continues, will become congested again but with larger traffic volumes, thus increasing total emissions and energy consumption. In this chapter the current knowledge about the stimulative effects of highway capacity projects on motor vehicle trips and travel is reviewed (Figure 4-1). An introductory section on the primary determinants of travel demand and recent travel trends is provided. DETERMINANTS OF METROPOLITAN TRAVEL DEMAND AND RECENT TRAVEL TRENDS IN THE UNITED STATES Travel is a derived demand; that is, it is derived from the activities of households and businesses that locate in a metropolitan area. Travel activities can be classified as commercial, involving goods movement and distribution, and personal. Personal travel is typically categorized as work travel and other personal travel (e.g., for shopping or recreation).

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use FIGURE 4-1 Impacts of highway capacity additions on travel demand.

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use The primary factors affecting metropolitan travel growth are demographic and economic. Metropolitan areas have grown tremendously in population. In 1990, nearly half the population (124 million people) lived in metropolitan areas with populations of more than 1 million, a 60 percent increase since 1960 (Rossetti and Eversole 1993, ES-2). Growth has been particularly rapid in the South and West, fueled in part by high rates of immigration (Pisarski 1992a, 4). During the same period household size has dropped sharply, from 3.24 to 2.65 persons per household (Rossetti and Eversole 1993, 2-1). To the extent that there are economies of scale in household trip making, persons organized in smaller households make more trips on the average than if they were part of larger households. Metropolitan area economic growth has accompanied population increases. Job growth in metropolitan areas outpaced the national average between 1960 and 1990, reflecting in part the entrance of the baby boomers into the work force (Rossetti and Eversole 1993, 2-1). The number of workers per household also grew. Women in the work force increased from one-third to nearly one-half of the metropolitan area work force, becoming an important factor affecting travel demand (Rossetti and Eversole 1993, 2-1). During the same period, growth in personal income resulted in increased household automobile ownership and travel. These growth trends have led to substantial increases in both trips and travel in urban areas.1 According to the Nationwide Personal Transportation Survey,2 between 1983 and 1990 household vehicle trips increased by 22 percent and household vehicle miles traveled (VMT) by 34 percent3 (Vincent et al. 1994, 10). Although travel for commuting purposes still represents the largest share of urban VMT (36 percent), travel for family and other personal business other than shopping was the fastest-growing element of household VMT. Trips for this purpose exceeded work trips for the first time in 1990 (Vincent et al. 1994, 1-1, 2-1). The implications of this shift for travel demand are important because a larger portion of nonwork trips are likely to be discretionary and thus more responsive to changes in the cost of travel. The location of population growth and economic activity in metropolitan areas has also affected the amount and type of travel. Most

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use population and job growth has taken place in the suburban portions of metropolitan areas (Mieszkowski and Mills 1993; Chinitz 1993). The trend toward decentralization has increased average trip lengths for all travel purposes between 1983 and 1990, with commute trips increasing the most (Vincent et al. 1994, 3-3). However, commuting trip speeds have remained relatively stable,4 reflecting more travel on higher-speed, suburban roads and a shift from slower to faster commuting modes (i.e., a decrease in transit use and carpooling and an increase in driving alone). Low density suburban growth is correlated with more automobile travel and higher automobile trip rates than occurs in core central cities where alternative modes of travel are available (Dunphey and Fisher 1993). For all urban areas in the United States, the share of urban trips made by automobile is 87 percent. The corresponding figure for urban areas with rail transit systems and populations greater than 1 million is only 78 percent (Vincent et al. 1994, 4-4, 6-11). These locations provide a variety of transportation services and have residential and employment densities that promote less reliance on the private vehicle for trip making (Vincent et al. 1994, 2, 4-2). Most personal travel in urban areas is by automobile, reflecting both low-density development that does not support alternatives to driving for most travel activities and the travel speed advantages of private vehicles.5 In 1990, 87 percent of all urban person-trips were made by private vehicle, 2 percent by public transportation, and the remainder by all other modes6 (Vincent et al. 1994, 4-4). Commercial travel in major metropolitan areas is primarily by truck, although some rail shipments are brought to key distribution centers in urban areas. The cost of transportation to the individual and to businesses also affects the demand for travel. Although the provision of highway capacity in urban areas has tapered off in recent years,7 it has resulted in high levels of accessibility and substantial reductions in the time-related cost of motor vehicle travel. Out-of-pocket costs of motor vehicle travel have also declined as a share of household budgets with the rise in personal income and the drop in oil prices over the past decade. Consumer surveys suggest that about 9 percent of typical household budgets is spent on gas and oil and other vehicle expenses (BTS 1994, 2).8 In the manufacturing and retail sectors, transporta-

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use tion costs typically account for between 1 and 4 percent of total production costs (Appendix C). All else being equal, the lower the cost of highway travel, the greater the propensity to travel and the less priority residents and businesses will give to transportation relative to other preferences and costs of doing business. The link between the low cost of and increased demand for travel suggests that raising the price of travel should reduce demand. Empirical evidence suggests that motorists respond to increases in bridge and turnpike tolls, transit fares, and parking fees (Harvey 1994). The decline in demand depends on the size of the price increase, the current costs of travel, and the capacity of alternative roads and transit systems (Bhatt 1994). Are current travel trends likely to continue? There is evidence that the rate of travel growth may be slowing. Historical trends indicate some reduction in the rate of growth of urban VMT (Figure 4-2). In addition, automobile ownership patterns may be reaching a saturation point. In 1989 there were 0.95 vehicles per person of driving age (Lave 1992, 5-7). As the proportion of household members who are eligible to drive and have access to a car approaches 100 percent, trip making per household and VMT per vehicle increase, but at a less rapid rate, with the purchase of additional vehicles (Hu and Young 1992, 30; Vincent et al. 1994, 1-16). Moreover, although the number of households with more than one vehicle has grown, households with three or more vehicles are mostly located in rural states (Pisarski 1992b, 19–20).9 Finally, some researchers argue that the potential for substantial additions to the driver pool is limited by the aging of the driving population and a reduction in the rate of growth of women in the work force. Offsetting these trends are the rise in young immigrant populations and the potential for increased travel by older drivers. For example, individuals 65 years old or older took 6 percent more trips and traveled 25 percent more on the average in 1990 than in 1983. However, travel in this age group in 1990 was still 30 percent below the average annual number of trips and 42 percent below the average annual miles traveled of all other age groups (Hu and Young 1992, 42). In summary, regional and metropolitan differences in immigration levels, work force participation levels, and overall rates of population and economic growth are likely to determine travel and trip demand levels in specific metropolitan areas.

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use FIGURE 4-2 Changes in the rate of growth of urban VMT, 1945–1990 (FHWA 1987, 225-228; FHWA 1992, 193). OVERVIEW OF EXPECTED IMPACTS AND DEFINITION OF TERMS10 By reducing the onerousness of travel as perceived by individuals, expansion of highway capacity can affect decisions about where, when, and how to travel. The primary impact of adding highway capacity is to reduce travel times in the corridor in which the improvement is located. Highway capacity additions can also improve the reliability of travel by diminishing the day-to-day variability in the time required to make a trip. Vehicles using congested facilities experience daily delays and unanticipated delays that can occur because of disabled vehicles and crashes. Adding capacity to these facilities reduces the likelihood11 and severity of delays from both recurring congestion and nonrecurring incidents. Finally, highway capacity additions can also affect the out-of-pocket cost of highway travel to the extent that fuel consumption and other

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use vehicle operating costs vary with speed and level of congestion. These effects are generally much smaller than travel time effects and are not perceived by most drivers. Description of Effects Potential direct effects of highway capacity improvements on travel patterns include the following: Changes in the route used to make a given trip: Construction of a new highway or the addition of capacity to an existing highway will allow some automobile users to reduce their travel times by shifting their route to the new or improved facility. Route shifts can increase or decrease total highway system use as measured in VMT by increasing or decreasing the circuity of trips. In most cases these effects are minor. Of more importance from an environmental perspective, route diversion can result in traffic shifts toward or away from areas that are more sensitive to local air quality and noise impacts. Changes in the time of day a given trip is made: Travelers may alter the time of day during which a trip is made in response to congestion levels. For example, individuals may deliberately avoid periods of congestion in scheduling shopping or other nonwork trips. Also, to the extent that their work requirements permit, individuals may schedule journeys to and from work outside of the period of most severe congestion. Adding capacity to a highway can reduce the severity and duration of congestion experienced on that facility. When peak-period congestion decreases, some of the trips that were shifted in time to avoid congestion in peak periods may be shifted back to the peak period. Changes in the mode used to make a given trip: Capacity additions can increase speeds and reduce automobile travel times, enhancing the attractiveness of highway use relative to other modes that do not benefit from the capacity improvement. The importance of mode shifts as a source of additional highway use depends heavily on the presence, type,12 and use of alternative modes such as transit13 in the corridor where capacity additions are made. Bicycle and pedestrian travel may also be discouraged if capacity

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use additions improve traffic flow for motor vehicles to the detriment of slower-moving modes. Changes in trip destinations: Capacity additions can increase the relative attractiveness of some trip destinations by reducing travel times to those destinations. Capacity additions can thus cause individuals to shift the destinations of their trips. This effect is more important for shopping and recreational travel (for which individuals have some flexibility in choosing destinations) and less important for work-related travel (for which individuals have little or no flexibility in choosing destinations in the short term). The substitution of one trip destination for another can increase or decrease total highway system use measured in VMT, depending on which destination is closer. The net effect of changes in trip destinations because of highway improvements is usually to increase VMT (i.e., new destinations are typically further away than the destinations they replace). Increases in the number of trips made: Because travel is a derived demand that reflects the need to carry out other activities, highway capacity additions are unlikely to significantly affect the number of home-to-work trips made. However, capacity additions could influence travel associated with more discretionary activities, for which the cost of travel might be an appreciable part of the total cost of the activity. In addition, improved travel times may reduce driver incentives to link trips (e.g., stopping for gas on the way home from the grocery store). The time periods over which these changes occur will likely vary. Most route diversion (which merely involves a shift from one route to another with no change in destination or time of day) may occur soon after a new or expanded facility opens, as drivers learn about the new route and the time savings it offers. Changes in the time of day for shopping trips may also occur soon after the new or expanded facility opens. Changes in the mode used for work travel, shifts in trip destinations, and new trips could occur more gradually because they involve more significant changes in travelers' activity patterns. In addition to the direct effects on traffic noted above, highway capacity additions can influence traffic levels by affecting other types of decisions, as illustrated by the following:

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use Automobile ownership: A traveler's shift from transit to automobile use for the journey to work might contribute to a household's decision to acquire an additional automobile. The availability of an additional automobile may lead to more of the household's non-work trips being made by automobile. Interrelationships among mode choice, destination choice, and automobile ownership are poorly understood and, as discussed later in this chapter, are seldom taken into account in conventional travel forecasting procedures. Land use and related travel: Highway capacity additions can improve access to developable land in outlying areas of a metropolitan area. The improved access makes these areas more attractive for future development and influences the location decisions of residents, employers, and shopping facilities. Shifts in the location of residences, jobs, and shopping opportunities affect trip distances and the potential for trips to be made by modes other than the automobile. The impacts of highway capacity additions on land use and related effects on travel are discussed in Chapter 5. Definition of Induced Travel The primary focus of this chapter is induced traffic, which is defined here as the increase in highway system use caused by an addition to highway capacity. Induced traffic thus includes new and longer motor vehicle trips that are made because the highway capacity addition has reduced the cost (primarily the time cost) of travel. Induced traffic does not include shifts in the route used to make a trip or shifts in the time of day a trip is made, because such changes generally do not result in a net increase in highway system use. Induced traffic does not include increases in traffic that occur for other reasons such as population and income growth. Changes in travel patterns because of capacity expansion should be distinguished from changes caused by other factors. Highway system use has grown because of increases in population, automobile ownership, and income, as well as expansion of the highway system itself. In the shorter term, highway system use can increase or decrease in response to such factors as fuel prices and economic conditions. In practice it is difficult to separate these effects because changes in high-

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use way use attributable to such factors as population and income growth often occur in parallel with additions to highway capacity and may either influence or be influenced by them. Figure 4-3 shows how highway capacity additions and other factors, such as population growth, can affect travel costs (user costs per mile of travel) and the amount of travel (vehicle miles). The demand for travel, Curve D, illustrates the relationship between the amount of travel and travel cost at a given time. The curve indicates that as the cost of travel decreases, the amount of travel increases. The corresponding supply relationship, Curve S, illustrates the congestion-induced effect of highway system use on travel cost. As use increases, travel cost (primarily time) also increases. The intersection of these two curves at Point a represents the short-term equilibrium between supply and demand. The travel volume and costs of travel represented by this point are the values observed in the transportation system. The effect of an addition to highway capacity is represented by a new supply curve, S′, which lies below Curve S except at very low traffic volumes, at which there will be little or no reduction in travel time from an expansion of highway capacity. In the absence of any increase in travel because of external factors (population and income growth), the additional highway capacity would result in a new equilibrium at Point c with increased travel volume and decreased travel cost. In this case the increased travel is induced by the reduction in travel cost. The demand for travel will generally increase over time because of such factors as population and income growth. This results in a right-ward shift of the demand curve (i.e., population and income growth will result in increased travel for each level of travel cost). This growth in demand is represented by Curve D′. Its intersection with Curve S at Point b represents the changes in travel—higher volume and higher cost—that will occur in the absence of changes in the transportation system. However, when there is also an expansion of highway capacity, the combined effect of the capacity addition and external growth is represented by Point d. Travel volume will be higher than the original travel volume. Whether the cost of travel is higher or lower than the original cost depends on the magnitude of the supply increase compared with the growth in travel due to external factors. In this example the travel cost is slightly higher.

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use FIGURE 4-3 Combined effects of highway capacity additions and travel 175growth from other factors on highway use.

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use These findings are consistent with the supply-demand framework diagrammed in Figure 4-3. That framework is useful for distinguishing between increases in highway use attributable to an increase in capacity and those attributable to external factors, such as population and income growth. In this framework, an increase in highway capacity (a supply-side shift) causes additional highway use by reducing the cost (primarily time) of motor vehicle travel. Over time, population and income growth may also result in increased highway use (a demand-side shift). The combined effect can eliminate the travel-time advantage of the added highway capacity, as occurs when the new highway capacity fills up with traffic again within a few years of construction. However, only part of the increased highway use can be attributed to the highway capacity addition. If the travel time reduction afforded by the new capacity is eliminated, the reason for new travel induced by the supply increase is also eliminated. The evidence also supports the view that projects involving the construction of new freeways have much more potential to cause additional highway system use than projects that involve widening of existing freeways or other major roads. New freeways in urban areas can provide significant increases in speeds and travel times during peak periods (by reducing congestion) and during off-peak periods (because freeways have higher speed limits than other arterials). The speed and travel time effects of projects involving widening of existing freeways and other highways occur primarily during peak periods. Much of the additional highway system use during peak periods resulting from a capacity addition appears to come from route diversions or shifts of trips from the off-peak to the peak period. Because travel is a derived demand it is unlikely that highway capacity additions will significantly affect the number of home-to-work trips. However, capacity additions could significantly affect travel associated with more discretionary activities for which the cost of travel might be an appreciable part of the total cost of the activity. This intuitive result is supported by the finding of some researchers that travel time elasticities are higher for nonwork trips. The potential for induced travel depends on the total cost of travel. Other things being equal, less induced traffic would be expected in corridors with high tolls or parking charges.

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use The existing four-step travel forecasting process was developed primarily to assist in determining the size of capital facilities (e.g., number of lanes), not to estimate the amount of travel new facilities might induce. The four-step process, as it is conventionally applied, will generally understate the amount of induced travel because the models used to predict the number of trips are not sensitive to travel times. Separating cause and effect is an extremely difficult problem in predicting induced travel. Highway capacity additions in a corridor can cause an increase in demand, but they might also be implemented because future growth in corridor demand is expected. Elasticities provide a useful means of making simple quantitative statements about the responsiveness of highway use to highway capacity additions in a specific context. However, caution should be exercised in applying elasticities developed in one context to other types of highway capacity projects in other locations. REVIEW OF IMPACTS ON TRUCK TRAVEL Highway capacity additions should affect freight travel in metropolitan areas in substantially different ways than they affect personal travel. Because of these differences, a separate analysis has been prepared to examine the impacts of highway capacity additions on travel by truck—the dominant carrier of freight within metropolitan areas. The results are summarized in this section and presented in their entirety in Appendix C. Effects on Truck Traffic The effects of adding highway capacity are the same for truck drivers as for other highway travelers. Capacity additions reduce travel times, make trip times more predictable, and improve accessibility to new areas and new markets. The response to these changes, however, is likely to differ because of the characteristics of the freight transportation sector. In the short term, highway capacity additions are unlikely to result in significant changes in truck travel. The demand for truck travel is

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use determined mainly by the level of economic activity in a metropolitan area and the area's role in the national and global economy. Moreover, deregulation of the transportation industry and technological innovations in other freight sectors have decreased the cost of transportation relative to labor and materials, making the cost savings from highway capacity additions less important to the shippers and receivers. Finally, the business cycle of the shippers and receivers of goods insulates many trucks from the morning and evening peak traffic periods, resulting in truck travel that is spread more evenly across the day than automobile travel. Continuing structural changes in the economy, freight logistics, and the trucking industry may make truck travel more sensitive to highway capacity changes in the future. The dispersion of business and housing across metropolitan areas will expand the service area that trucking firms must cover. High land and labor costs, encroaching residential development, and noise regulations are likely to push warehouses and truck terminals toward the periphery of metropolitan areas, leading to an increase in truck miles of travel. Finally, the adoption of just-in-time manufacturing and retailing practices and the globalization of trade will produce longer and more time-sensitive supply and distribution networks that leave trucks more exposed to the effects of congestion. However, internal competitive pressures will force the deregulated trucking industry to carry more freight with fewer trucks and fewer truck miles of travel. These productivity improvements are being achieved by automated fleet management technologies and automated urban traffic management systems [intelligent transportation system (ITS) programs]. To date, the former have been adopted by long-haul national truckload carriers, urban courier and parcel services, and large less-than-truckload carriers such as Federal Express and United Parcel Service, but not by smaller urban trucking fleets. ITS programs generally, and ITS programs for trucks specifically, are not yet widespread in urban areas. A recent report entitled Transport and the Environment noted the difficulty of altering highway freight transport patterns in the United Kingdom even with a considerable increase in fuel prices; more regulation and restriction of heavy goods vehicles in certain locations would be required (Royal Commission on Environmental Pollution

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use 1994, 166). The potential for mode shifts is considerably less in metropolitan areas than for long-distance travel because of the greater flexibility and considerable cost advantages trucking offers for short-haul distribution (Appendix C). Modeling Truck Travel Regional travel demand models are generally not well equipped to forecast the separate effects of changes in metropolitan highway capacity on truck travel versus automobile travel. Truck travel represents a small share of total traffic, well within the margin of error of the models, so only modest efforts have been made to forecast it separately. The typical regional model apportions forecast vehicle trips that have been assigned to highways on the metropolitan network among trucks and automobiles. The apportionment is based on traffic counts by functional class of roadway (for the more sophisticated systems) or on a single estimated percentage of truck travel for major roads only. To account for the size difference among trucks and cars, trucks are converted into passenger car equivalents.18 A few metropolitan areas have developed separate trip tables for trucks on the basis of extensive surveys of shippers and motor carriers in their regions, but these are the exception to the rule. The primary hurdles to developing more sophisticated regional truck travel models are the general lack of data on freight and truck movements in metropolitan areas and the complexity of freight demand estimation and truck trip modeling. In sum, regional travel models are not well equipped to forecast separately changes in truck travel and changes in automobile travel within metropolitan areas due to an addition to highway capacity. The models cannot examine the effects of reduced travel times on truck behavior or tie the effects to specific carriers, industries, or commodities, because the models do not take into account shipper demand or motor carrier behavior. If the highway capacity addition is modest in scale and limited to a single corridor, the shortcomings of the models can be overcome by using direct interviews with industries and motor carriers to adjust model forecasts. For larger projects in complex metropolitan areas, planners must develop truck trip tables and truck networks and incorporate them into the regional forecasting process.

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use RECOMMENDATIONS FOR IMPROVING THE KNOWLEDGE BASE A better understanding of how individual travelers and freight carriers and shippers make travel choices is necessary to forecast more accurately the likely effects on travel demand of changes in highway cost, highway service, and other policy options. For many metropolitan areas, the household travel surveys that provided the origin-destination and mode choice data for regional travel forecasting models are out of date. Changes in demographic characteristics (family size, structure, and income) and in travel conditions and options offer choices that were unavailable when many of the surveys were conducted (Harvey and Deakin 1993, 3-101). Most metropolitan planning organizations (MPOs) have never collected data on the determinants of truck travel in their area. To remedy this situation, more current household travel survey data should be collected.19 This activity could be supported by the planning funds given to MPOs to develop the management systems required by the Intermodal Surface Transportation Efficiency Act (ISTEA) if these data were viewed as critical to assessing and monitoring the achievement of air quality goals in metropolitan areas.20 Although the planning funds are already committed to supporting ISTEA requirements, there may be potential for collecting travel data that support both model improvements and certain of the management systems required by the act. ISTEA also requires more attention to freight transportation and more private-sector involvement in the planning and programming of highway and other transportation improvements, which could lead to a more sophisticated understanding of freight movement and truck travel. Basic data are needed on freight generation rates by industry and commodity that can be tied to specific land uses and industrial facilities in metropolitan areas, on trip patterns by industry and commodity by different types of carrier, and on the factors that affect truck routing and dispatching decisions and terminal location choices. Carefully planned longitudinal studies (panel surveys) of a diverse and representative population of travelers, firms, and metropolitan areas to determine the effects of policy actions—such as major transportation investments or pricing changes—on travel behavior should

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use help shed light on how these policy actions affect travel choices over time. A major methodological challenge is to control for the effects of other variables, such as regional population and economic growth, on long-term growth in travel. The results of these data collection and research efforts should be used to update existing travel forecasting models. In particular, the models should be modified to more adequately represent the effect of changes in the cost of transportation on automobile ownership, the number of trips made, the time of day of travel, the interdependencies among trips (i.e., the opportunities for combining trips), and bicycle and pedestrian travel. Where good historical data are available on changes in transportation facilities and travel demand, they could be used to calibrate regional travel models and “predict” current travel patterns to evaluate their forecasting capabilities. Development of more sophisticated models of freight transportation in metropolitan areas requires a more substantial effort because of the current state of freight modeling practice. Because of the complexity of freight demand estimation and truck trip modeling, efforts should be focused on corridor-scale models, which can accommodate multiple truck trip tables and truck networks, rather than comprehensive regional freight models. A new travel forecasting paradigm should be developed in the long run to address the policy questions currently being asked. Activity-based models hold considerable promise for providing more detailed modeling of household activities and travel options. Such models would allow more precise forecasts of likely traveler responses to a range of policy options. These models, however, are still in the early stages of development. Advancing their development requires collection of substantially enhanced data about the travel behavior of households and individuals; estimation of enhanced models that incorporate more of the behavioral links that affect household travel decisions and take into consideration the importance of trip linkages and time of day in travel choices; and test applications in one or more regions, including the development of implementation software. Model calibration and validation continue to be major challenges. Finally, model results will have to be merged with the results of enhanced emission and energy models to improve prediction of the air quality and energy consequences of traveler responses to highway capacity additions.

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use Better models more relevant for policy analysis can be developed. Although the limitations of models in the policy process—particularly in the precision of their estimates—should be recognized, they are useful in analyzing complex phenomena. NOTES 1. Urban area, as defined in the Nationwide Personal Transportation Survey, refers to the urbanized portion of the larger metropolitan area. Urbanized area is a U.S. Bureau of the Census term defined by the presence of a central city, a total population of 50,000 or more, and a population density exceeding 386 persons per square kilometer (1,000 persons per square mile) (Vincent et al. 1994, 2). Data are not available for metropolitan areas. 2. The magnitude of the changes should be interpreted with caution because of changes in sample size and survey methods between the 1983 and 1990 surveys. For example, the sample size was 22,000 in 1990 and only 6,500 in 1983. Telephone surveys were used in 1990 and in-person home interviews in the earlier survey. Finally, some metropolitan area and central city boundaries changed between the survey years (Vincent et al. 1994, 4, 5). 3. These numbers are based on urban trips of less than 121 km (75 mi) (Vincent et al. 1994, 10). 4. The average national travel time to work increased from about 21.7 min in 1980 to about 22.4 min in 1990. The most common trip duration was between 15 and 29 rain (Rossetti and Eversole 1993, 4-36). Several large metropolitan areas, however, such as Los Angeles, San Diego, Orlando, and Sacramento, had commuter travel time increases of more than 10 percent (Rossetti and Eversole 1993, 4-38). 5. For example, the average commuting trips by bus transit and private vehicle are similar in distance, but the bus trip takes nearly twice as long (Vincent et al. 1994, 3-1). 6. Other modes include bicycle, walking, taxi, and other. Trips greater than 121 km (75 mi) are excluded (Vincent et al. 1994, 4-4). 7. The Federal Highway Administration's Highway Statistics reports the following figures for surfaced road and street mileage in the United States: 1960, 4.1 million km (2.56 million mi); 1970, 4.72 million km (2.95 million mi); 1980, 5.38 million km (3.36 million mi); and 1990, 5.63 million km (3.52 million mi) (in Rossetti and Eversole 1993, 2-4). 8. These figures do not include vehicle purchases, which represent about 7.1 percent of total spending, or purchased transportation, which represents about 1.0 percent of the total (BTS 1994, 2).

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use 9. An exception is California. In the San Francisco area, for example, 20 percent of the households have three or more vehicles. In Los Angeles, 28 percent of homeowner households and less than 10 percent of renter households have three or more vehicles (Pisarski 1992b, 19). 10. The following five sections were written by Harry Cohen of Cambridge Systematics, Inc., as part of a special Literature Review on Travel Impacts of Highway Capacity Improvements prepared for the study committee. 11. See Appendix C for a review of the literature on how congestion levels affect crash severity. The literature suggests that accident rates will not be reduced under all conditions. Studies of the relationship between accident rates and congestion levels have found that accident rates are highest at night when traffic volumes are lowest. As traffic volumes increase, accident rates drop, but they begin to climb again as traffic volumes approach 60 to 70 percent of highway capacity, typically during congested daytime traffic. 12. Highway capacity additions that reduce travel times may make bus travel faster and thus more attractive. However, automobile travel times will also be reduced. Diversions from car to bus are likely to depend on bus reliability and comfort as well as travel times. 13. In areas with large transit systems, highway capacity additions that result in large diversions from existing transit services might affect subsidy requirements and the financial viability of these services, which in turn are likely to result in service cutbacks and additional ridership loss. 14. The magnitude of the reductions would depend on traffic speeds realized after the capacity addition (see discussion in Chapter 3). If the capacity addition results in a net increase in free flow freeway speeds during peak and off-peak periods, some of the emission reductions and fuel use savings from peak-period congestion relief will be offset. 15. More specifically, elasticity of demand is the percent change in demand relative to a 1 percent change in price or other measurable attributes of service quality. 16. As discussed in Appendix B, because of data limitations the analysis was focused on estimating how changes in lane miles affect VMT on state highways. 17. Revealed preference surveys, while capturing actual responses to real changes, raise several survey design issues, including identifying the appropriate population to sample (how large an area to cover) and selecting a control location to compare changes with and without the improvement. The revealed preference approach also requires multiple surveys to capture the before-and-after effects (Dowling et al. 1994, 18). The stated preference approach, which was used in this study, overcomes these limitations and costs less, but has the obvious disadvantage that it does not measure actual decisions.

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use 18. Small or medium trucks are represented as equivalent to two passenger cars and large trucks to three passenger cars. 19. A recent report (Hartgen et al. 1994, 18) found that a considerable number of metropolitan regions have begun to conduct travel surveys (19 had done home interviews) or have plans to do so. 20. Both ISTEA and the Clean Air Act Amendments require collection of data on many aspects of the transportation system, such as VMT tracking and monitoring. There is no comparable requirement for travel survey data collection (Harvey and Deakin 1993, 3-101). However, travel data could be collected to support the congestion management systems and, to a lesser extent, the transit and intermodal management systems required by ISTEA. REFERENCES ABBREVIATIONS BTS Bureau of Transportation Statistics DOT U.S. Department of Transportation DOE U.S. Department of Energy EPA Environmental Protection Agency FHWA Federal Highway Administration NCHRP National Cooperative Highway Research Program NRC National Research Council SACTRA The Standing Advisory Committee on Trunk Road Assessment Bhatt, K. 1994. Potential of Congestion Pricing in the Metropolitan Washington Region In Special Report 242: Curbing Gridlock, Vol. 2, National Research Council, Washington, D.C., pp. 62–88. Bovy, P.H.L., A.L. Loos, and G.C. De Jong. 1992. Effects of the Opening of the Amsterdam Orbital Motorway. Final Report Phase I. Ministry of Transport and Public Works, Transportation and Traffic Research Division, Rotterdam, Netherlands, 83 pp. Burright, B.K. 1984. Cities and Travel. Garland Publishing, New York. BTS. 1994. Transportation Statistics: Annual Report, 1994. U.S. Department of Transportation, 205 pp. Chinitz, B. 1993. Urban Growth Patterns. Presented at Conference on Metropolitan America in Transition: Implications for Land Use and Transportation Planning, Washington, D.C., Sept. 9–10.

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EXPANDING METROPOLITAN HIGHWAYS: Implications for Air Quality and Energy Use Domencich, T.A., G. Kraft, and J.P. Vallette. 1968. Estimation of Urban Passenger Travel Behavior: An Economic Demand Model. In Highway Research Record 238, Highway Research Board, National Research Council, Washington, D.C., pp. 64–78. Dowling, R.G., S.B. Colman, and A. Chen. 1994. Effects of Increased Highway Capacity on Travel Behavior. California Air Resources Board, Dowling Associates, Oakland, Calif., Oct. DOT, EPA, and DOE. 1994. Travel Model Improvement Program. Texas Transportation Institute, College Station, 11 pp. Dunphey, R., and K. Fisher. 1994. Transportation, Congestion, and Density: New Insights. Presented at the 73rd Annual Meeting of the Transportation Research Board, Washington, D.C. FHWA. 1987. Highway Statistics: Summary to 1985. HPM-10/4-87. U.S. Department of Transportation. FHWA. 1992. Highway Statistics, 1991. HPM-40/10-92. U.S. Department of Transportation. Frye, F.F. 1964a. Redistribution of Traffic in the Dan Ryan Expressway Corridor. CATS Research News, Vol. 6, No. 3, pp. 6–14. Frye, F.F. 1964b. Eisenhower Expressway Study Area—1964. CATS Research News, Vol. 6, No. 4, pp. 7–13. Hansen, M., D. Gillen, A. Dobbins, U. Huang, and M. Puvathingal. 1993. The Air Quality Impacts of Urban Highway Capacity Expansion: Traffic Generation and Land Use Change. UCB-ITS-RR-93-5. Institute of Transportation Studies, University of California, Berkeley, April. Hartgen, D.T., A.J. Reser, and W.E. Martin. 1994. State of the Practice: Transportation Data and Modeling Procedures for Air Quality Emissions Estimates. Center for Interdisciplinary Transportation Studies, The University of North Carolina at Charlotte, July. Harvey, G.W. 1994. Transportation Pricing and Travel Behavior. In Special Report 242: Curbing Gridlock, Vol. 2, National Research Council, Washington, D.C., pp. 89–114. Harvey, G., and E. Deakin. 1993. A Manual of Regional Transportation Modeling Practice for Air Quality Analysis. National Association of Regional Councils, Washington, D.C., July. Holder, R.W., and V.G. Stover. 1972. An Evaluation of Induced Traffic on New Highway Facilities. Texas A&M University, College Station, March. Hu, P.S., and J. Young. 1992. Summary of Travel Trends: 1990 Nationwide Personal Transportation Survey. FHWA-PL-92-027. Oak Ridge National Laboratory, Oak Ridge, Tenn., March, 43 pp. Jorgensen, R.E. 1947. Influence of Expressways in Diverting Traffic from Alternate Routes and in Generating New Traffic. HRB Proc., Vol. 27, pp. 322–329.

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