How We Travel: A Sustainable National Program for Travel Data (2011)

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1 Introduction T he U.S. transportation system moves some 5.5 trillion passenger- miles of traffic each year, mainly on the nation’s highways, and approximately 4.6 trillion ton-miles of freight (BTS 2010).1 Trans- portation is a major industry in its own right, but its primary purpose is to provide mobility and access to millions of travelers and to move goods rapidly and reliably in support of economic activity. Policy and decision makers in both the public and private sectors need to know how well the system is performing; what changes in travel patterns can be expected with changes in demographics and logistics; how travelers and shippers respond to changes in the system and external factors; and what impact travel patterns have on safety, congestion, energy use, and the environment. Unfortunately, many of the policy and investment decisions facing transportation decision makers in such crucial areas as improving travel safety, alleviating congestion, increasing the energy efficiency of travel, and reducing transportation-related air pollution and greenhouse gas emissions often are made on the basis of travel data that are lacking in modal coverage, timeliness, and geographic detail. Moreover, the most comprehensive passenger and freight travel data are collected in periodic federal surveys that are highly contingent upon shifting political and funding priorities and not infrequently in danger of cancellation. 1. Bureau of Transportation Statistics, National Transportation Statistics, Section D: Travel and Goods Movement, Table 1-37 for U.S. passenger-mile data (updated April 2010) and Table 1-46b for U.S. ton-miles of freight (special tabulation dated September 2009).   5  

6  How We Travel: A Sustainable National Program for Travel Data Study Charge, Scope, and Audience The purpose of this study is to assess the state of passenger and freight travel data at the federal, state, and local levels and to make recommendations for an achievable and sustainable system for estimating personal and freight travel to support public and private transportation planning and decision making. (See Appendix A for the study’s full statement of task.) In particular, the study • Examines user needs for travel data, that is, what passenger and freight travel data are essential for policy and decision making; • Explores how these data might be collected more cost-effectively through such techniques as continuous longitudinal surveys, web surveys, and methods for capturing data from automated sources (e.g., instrumented vehicles, passive cellular telephone probes); • Investigates how data programs could be better managed and coordi- nated; and • Considers how these data programs should be funded on a consistent and continuing basis. The study builds on a long history of prior studies of data needs. Over a span of nearly two decades, starting with Data for Decisions in 1992 (TRB 1992), the National Research Council published four special reports and numerous other studies (referenced in Appendix C of this report) supporting the need for a more integrated data structure that has yet to materialize.2 The present study takes a strategic look at data issues as a basis for recommending ways to provide a sustainable system for essen- tial travel data. The study is national in scope and recognizes the multiple geographic levels—federal, state, regional, and local—and the multiple sectors—public, private, nonprofit—in which travel data are collected and used. The breadth of data needs—from national trends to project-level detail—and the diversity of users pose a major challenge. No single data collection model is appropriate. Moreover, building support for essential data programs is complicated by the number of disparate user constituencies. 2. See, for example, special reports on data by the National Research Council (NRC 1997) and, more recently, by the Transportation Research Board (TRB 2003a,b). 

Introduction  7  The study covers all travel modes—surface (i.e., highways, rail, public transit, pipeline, bicycle, and pedestrian), air, and marine transportation. The focus, however, is on the transportation system as a whole and how it performs as an integrated network, rather than on the individual modes. The committee defines travel data broadly to include origin-to-destination flows, their characteristics (purpose of passenger and freight movements; attributes of travelers and commodities being moved; costs and travel times; and impacts, such as those on congestion, energy use, and the environment), and the characteristics of the infrastructure on which these flows take place. An important issue motivating this study is the growing interest in performance-based management and the opportunity to focus greater attention on and provide resources for the necessary supporting data in the next authorization of surface transportation legislation. Preliminary bills reauthorizing surface transportation legislation and reauthorization principles released by the current administration,3 for example, place significant emphasis on performance-based decision making, outcomes, and accountability. This strategy for transportation management rests solidly on good performance measures and, in turn, on having the right data to drive those measures. More generally, faced with increasingly complex transportation problems, users are demanding more varied and more detailed transportation data. Addressing transportation demand, for example, is a matter not only of adding more capacity, but also of modifying demand and optimizing the operation of existing systems while at the same time minimizing adverse impacts on air quality, energy use, and climate. All of these strategies would benefit from a richer understanding of travel behavior and travel demand, often at a level of detail not currently available. Responding to these data needs is complicated by heightened sensitivities with respect to privacy, concern for the protection of proprietary data made available for public use, rapid adoption of technology (e.g., cellular telephone-only households) that makes many current survey methods outdated (e.g., sampling of only landline telephone users), and budgetary pressures that put a premium on using scarce resources productively. 3. See The Surface Transportation Authorization Act of 2009: A Blueprint for Investment and Reform, Executive Summary, presented by Chairman James L. Oberstar, Ranking Member John L. Mica, Chairman Peter A. DeFazio, and Ranking Member John J. Duncan, Jr., Committee on Transportation and Infrastructure, U.S. House of Representatives, June 18, 2009; “Fact Sheet: Renewing and Expanding America’s Roads, Railways, and Runways,” The White House (Office of the Press Secretary), September 6, 2010; and “Obama Administration Releases Principles for 18-month Surface Transportation Extension,” Transportation Weekly, July 1, 2009. 

8  How We Travel: A Sustainable National Program for Travel Data The situation facing data managers is challenging but provides many opportunities for improvement. Members of Congress, who provide for program funding, and senior leadership and managers of key travel data programs at the U.S. Department of Transportation (U.S. DOT) and other federal agencies are the primary audiences for this study’s findings and recommendations. The study is intended to have a wider audience, how- ever, including planners and decision makers at state departments of transportation (DOTs), metropolitan planning organizations, transit agencies, universities, and private businesses that use—and in some cases provide—travel data. The sections that follow examine the role and value of travel data in transportation decision making; fulfilling this role and providing real value are likely to be essential for securing user support for a comprehensive travel data program. Changes in the context in which transportation operates that affect both data needs and the ability to meet those needs are considered next. Finally, looking forward, key issues that affect data relevance and thereby user support are discussed. The chapter ends with a brief overview of the remaining chapters of the report. Role and Value of Travel Data Along with experience and judgment, good data are a critical component of good decision making. Travel data are used at many different levels and for many different purposes. They provide the basis for trend analyses and inputs to forecasting models, enabling “what if” analyses and providing early warning of changes in trends. They enable analysts to discern how travelers and shippers respond to various factors that influence travel decisions. They also help shape policy decisions that affect travel and, once a policy has been implemented, provide a basis for measuring and monitoring performance and outcomes. Travel data can help inform investment decisions, enabling analysis of program and project alternatives and trade-offs. For example, they provide the basis for highway and bridge capacity enhancements and pavement design. Travel data also are integral to environmental review for air quality, noise, and water quality analyses, and they are used extensively in transit planning and assessment of other modal investment opportunities. Real-time travel data are critical as well for operational decisions, such as traffic control and incident and emergency management and high-efficiency supply chains. 

Introduction  9  Because of these important roles, travel data have been characterized as a national asset (Schofer et al. 2006). Like any asset, data cost money to acquire and maintain, to turn into useful information, and to be made readily accessible to users. To justify the necessary expenditures, particu- larly on a sustained basis, funders must be able to see the value of data for planning and decision making as constituting a sufficient return on their investment. Today, however, some of the key national travel data programs are threatened, and others have been terminated, because of a lack of funding. If good transportation data are essential for good decision making, why are travel data programs struggling to identify champions and funding? The answer is not straightforward. First, it could be argued that trans- portation decision makers do recognize the value of good data. When a decision must be made, however, they tend to use whatever data are available “on the shelf”—good or indifferent—to inform it. Moreover, while data are important, they are but one of many factors, such as the political context and available resources, considered in decision making. Second, some decision makers, particularly highly placed transportation policy makers and agency administrators who influence budgets as well as policy and investment choices, may indeed be unaware of or overlook the importance of data. The data and analysis that lie behind a summary cost/benefit ratio or a rating score, for example, remain largely unseen and could easily be taken for granted. In other cases, data may be perceived as highly technical—a black box whose utility for supporting policy and decision making is not readily apparent. Even for the more technically savvy user, the sheer volume of data available through the Internet and search engines that have not been translated into usable information can be overwhelming. Finally, and related to the issue of data utility, providers of transportation data often are removed from users and sometimes are poorly coordinated among themselves, dispersed across federal agencies, agencies at other governmental levels (e.g., state DOTs), and private companies, as described in more detail in Chapter 2. Without adequate user feedback mechanisms, data programs risk becoming disconnected from the decisions facing policy makers and managers. Transportation data users themselves tend to be widely dispersed and often (appropriately) focused at a technical level, increasing the difficulty of obtaining needed feedback and building constituency support for data programs. The wealth of data on the Internet creates another insidious problem: it leads users to expect that data are free for the asking, sometimes masking 

10  How We Travel: A Sustainable National Program for Travel Data the sources of the data. Often, those sources are second or third hand, and users have no knowledge of the primary source, much less the quality or accuracy of its coverage. Thus, the easy availability of data on line may make it even more difficult to garner support for investments in travel data programs. The demise of the planned 2007 Vehicle Inventory and Use Survey (VIUS), which can be contrasted with the saving of the 2009 National Household Travel Survey (NHTS), illustrates many of these points, in particular the importance of a lead sponsor and strong user support (see Box 1-1 for detail). The VIUS was a national survey of commercial vehicle characteristics and use; the NHTS is a national survey of household personal travel. Although the VIUS was valued by several federal agencies (e.g., U.S. DOT, the Department of Energy) and the motor vehicle manu- facturing industry, its uses were often indirect. When the Census Bureau, which both conducted and funded the survey, announced its termination in early 2006 to close a budgetary gap, there was no strong and credible transportation advocate at U.S. DOT working with the Census Bureau to defend the survey. In contrast, when the Bureau of Transportation Statistics (BTS), the federal statistical agency for transportation, announced that it was unable to commit its share of funding for the planned 2009 NHTS, data users at the state and regional levels, along with such organizations as the American Association of State Highway and Transportation Officials, the American Highway Users Alliance, AAA, the Institute of Transportation Engineers, and AARP, recognizing how essential the NHTS was to travel models and investment decisions, lobbied U.S. DOT to defend the survey. The Federal Highway Administration (FHWA), which historically had sponsored the survey, reassumed full responsibility, although other user agencies provided the majority of the funding. The Changing Context for Travel Data Linking data and data providers more closely with users is becoming even more important with increasing interest in the performance management, outcomes, and accountability of the transportation system. Travel data are essential both to measure and to monitor system performance. Yet some travel data programs are still rooted in measuring the “what” and “how” of passenger and freight movement rather than extending to address “why,” including the motivations for travel, its efficiency, and its impacts. 

Introduction  11  Box 1-1 A Tale of Two Data Sets A comparison of the recent history of two data surveys—the Vehicle Inventory and Use Survey (VIUS) and the National Household Travel Survey (NHTS)—provides a good illustration of the importance of leadership, user support, and sustained funding for data program continuity. The Truck Inventory and Use Survey (retitled the VIUS in 1992 based on the expectation that the survey would be expanded to cover automobiles and buses and obtain comparable information for all vehicles on patterns of use, energy consumption, and economic activity served) had been conducted continuously at 5-year intervals since 1963 by the U.S. Bureau of the Census until it was abruptly canceled in February 2006. Based on a sample of vehicle registration files taken from R. L. Polk and Co., this mandatory survey provided national and state-level data on heavy-duty and light-duty trucks, including vehicle size, weight, engine type, fuel economy, miles driven, commodities carried, and operation type (e.g., for-hire transportation), among other items. Its uses were many, but often indirect, thus likely contributing to its lack of visibility and champions. For example, the VIUS was used to help calculate the size of the for-hire trucking component of the Transportation Services Index—an economic measure of freight and passenger services—and to apportion vehicle-miles traveled (VMT) among vehicle types on the nation’s highways as part of the Federal Highway Administration’s (FHWA’s) Highway Statistics series. It also was used as input to various freight forecasting models and for truck size and weight regulatory studies. At the time it was canceled in response to a governmentwide federal budget rescission, there were no strong sponsors within the U.S. Department of Transportation (U.S. DOT) or the broader transportation community working with the Census Bureau to defend the survey. The NHTS, which had been conducted since 1969 on a less regu- lar schedule than the VIUS, was also in danger of cancellation when (continued on next page) 

12  How We Travel: A Sustainable National Program for Travel Data Box 1-1 (continued) A Tale of Two Data Sets the Bureau of Transportation Statistics at U.S. DOT announced that it was unable to provide its share of the funding for the planned 2009 survey. In contrast with the VIUS, however, FHWA, which historically had administered the survey, reassumed full responsibility. Some 20 states and metropolitan planning organi- zations (MPOs), as well as associations representing transportation interests, which count on the data as input for travel models and for policy and investment analyses, provided the bulk of the funding and expanded the survey’s coverage, and the survey went forward. The experience proved the need for a lead sponsor, in this case FHWA; strong user support; and a product that is both visible and valuable to users. The NHTS experience, however, with the possible exception of the strong partnership among the federal government, the states, and MPOs, is not a sustainable model going forward. Despite FHWA’s role in stepping in to save the survey, the “pass-the-hat” approach to funding resulted in a small federal contribution to a national-level survey that paled in comparison with the size of the state and MPO add-ons, resulting in a skewed sample when viewed from a national perspective. When U.S. DOT staff were questioned about plans and a date for the next survey, the answers given were tentative. Massive changes in the context in which transportation operates have implications for both the content of travel data and the way they are collected. Some data programs have been slow to adapt to these changes and the needs they generate; as a result, these programs risk a decline in their salience to the point where their support is threatened. To illustrate, the following changes have occurred in just the past 20 years: • Policy focus—Policy concerns have shifted from a narrow focus on the rehabilitation and construction of transportation infrastructure; 

Introduction  13  to a broader interest in system performance and efficiency in moving people and goods; to more recent concerns about travel impacts on the environment, energy use, the economy, and equity.4,5 In general, travel data programs are not well designed to measure system perfor- mance or travel impacts. Box 1-2 provides examples of current policy issues that require good travel data but for which current data fall short. • Regulation—Continued deregulation of the economy has reduced the primary justification for many data collection activities and resulted in the loss of data sets. For example, the demise of the Interstate Commerce Commission in 1995 marked the end of economic regulation of railroads and trucking and of the supporting data on operations and finances of individual firms, geared to ensuring fair pricing and eliminating rate discrimination, among other regulatory requirements. As discussed in Chapter 2, broad industry data continue to be collected by various federal agencies (e.g., the rail Carload Waybill Sample, the Air Carrier Traffic Statistics, the Waterborne Commerce Statistics). In addition, safety and environmental regulations have often supplanted economic regulations, but not always with associated data capabilities (e.g., limited data exist on the safety of public transit systems). • Technology—More widespread use of technology has increased the ability to collect real-time data at micro levels of detail (e.g., inexpensive fixed sensors, wireless communications, passive cellular telephone probes) and with geographic precision (e.g., the Global Positioning System [GPS]). As noted earlier, broader penetration of the Internet has enabled increased accessibility of data. • Privacy and trust—Increasing concerns about the disclosure of personal information—one consequence of technological advances— have constrained the ability to acquire data at levels of detail desired by users for modeling, planning, and policy analysis. Privacy concerns and uncertainty about the use of data, particularly by government, 4. The focus on travel impacts can be traced back to the Intermodal Surface Transportation Efficiency Act of 1991, with its emphasis on the impact of travel on air quality and its link with the Clean Air Act Amend- ments of 1990. 5. Equity impacts include disproportionate cost burdens of various transportation financing mechanisms (e.g., dedicated sales taxes, congestion pricing, tolling) on the poor. 

14  How We Travel: A Sustainable National Program for Travel Data Box 1-2 Examples of Current Policy Issues for Which Travel Data Are Lacking Transportation and the Economy Recent attention focused on the economy and economic perfor- mance has resulted in increased interest in the role of the transpor- tation sector in the economy and productivity. The Transportation Services Index (TSI) was developed in 2002 and first reported in 2005 as a measure of the economic activity of the transporta- tion sector, both passenger and freight. Many of its components are weak, however, and others are missing entirely. For example, the TSI covers only domestic for-hire transportation services (i.e., services provided by an external company for a fee), although estimates suggest that such services across all modes account for only about half of all transportation services; many private firms have their own fleets (Young et al. 2007). Because of these omis- sions and the lack of timeliness of some of the data inputs, the TSI is generally a poor real-time indicator of economic changes. Travel Patterns of an Aging Population The United States is facing a potential sea change in housing and travel patterns over the next several decades as the Baby Boom generation retires and downsizes from its suburban housing. Detailed data are needed on the travel patterns of older households and individuals—how and where they travel and how much—as well as their access to transportation, particularly nonautomobile modes (e.g., transit). These data are important for providing services to an aging population to help maintain mobility. The National Household Travel Survey (NHTS) is a rich source for these data, but it is conducted too infrequently to capture useful trends and does not include data on transportation services. High-Speed Intercity Rail The current administration has made available $10.5 billion for high-speed rail projects, a down payment on a potentially much (continued) 

Introduction  15  larger program. The decision to go forward was made in the absence of any current data on intercity passenger travel, which were last collected in 1995. Although good origin-destination data are available for airline passenger travel, most high-speed rail trips are likely to be substitutes for motor vehicle travel. As high-speed rail projects seek federal funding, data on long-distance travel by automobile and air will be critical for analyzing potential travel markets and evaluating proposals. The U.S. Department of Transportation (U.S. DOT) is patching together numerous data sources to help fill the void, but without a major new survey, the necessary data are unlikely to be available. Energy Efficiency Transportation is a key contributor to both energy use and green- house gas (GHG) emissions. Data are needed to track the kinds of vehicles on the road (including alternative-fueled vehicles), fleet turnover, and vehicle use to determine whether policies to encourage lower energy use (e.g., higher Corporate Average Fuel Economy standards for passenger vehicles and light-duty trucks, soon to be extended to heavy-duty trucks) are having the desired effect and to what extent. The NHTS collects some data on house- hold vehicles, but only infrequently, as noted. With the demise of the Vehicle Inventory and Use Survey in advance of the 2007 NHTS, no data are available on heavy trucks and their travel. Climate Change and Greenhouse Gas Emissions As the U.S. Environmental Protection Agency moves to regulate GHG emissions, one strategy is to reduce the demand for driving by increasing the density of land use and by mixing residential and commercial uses to provide an environment that encourages non- motorized travel (e.g., walking and bicycling, as well as transit use). Regulations requiring such land use policies are already in effect in California, and many other communities are experimenting with similar development strategies that go under various names, such as smart growth, transit-oriented development, and livable communities. The current administration has created a $527 million (continued on next page) 

16  How We Travel: A Sustainable National Program for Travel Data Box 1-2 (continued) Examples of Current Policy Issues for Which Travel Data Are Lacking grant program for livable communities to encourage such initiatives. To evaluate proposed projects and properly monitor and measure outcomes, community-level data are needed on travel patterns (number and length of trips) by purpose and mode. Data for small areas are weak, particularly spatial data on where residents work, shop, and attend school, which are critical to improving transit accessibility and service. Congestion Congestion continues to be a major barrier to efficient goods move- ment and traveler mobility for most travel modes. Given forecasts of significant increases in freight movements and, to a lesser extent, passenger travel, good data on major bottlenecks, as well as peak period traffic congestion, are important. Congressional leaders and program managers at U.S. DOT need these data to help ensure adequate funding of transportation programs at the national level. State DOTs and local transportation managers also need these data for investment planning, traffic management and incident control, and emergency evacuation planning. Despite its importance, there are no detailed measures of congestion. The well-known travel-time index of the Texas Transportation Institute (TTI) provides trend data on congestion for large metropolitan areas, but travel time measurements are based on average annual daily traffic. The private sector has begun to capture automated data on vehicle movements from passive probes (e.g., cellular telephones) and vehicles instru- mented with Global Positioning System devices to provide timely traffic information to individual travelers and fleet managers. A few firms are partnering with the federal government and universities, TTI among them, so that these data can be integrated and aggregated to enable reporting on nationwide congestion trends and major traffic bottlenecks for policy analysis and invest- ment purposes. 

Introduction  17  as well as distrust of government generally, have eroded the willing- ness of both individuals and businesses to respond to surveys. In a recent survey by the Pew Research Center, for example, only 22 percent of respondents said they could trust the government in Washington almost always or most of the time—an attitude that has affected response rates for the U.S. census and other, less visible surveys (Pew Research Center 2010 in Billitteri 2010). Measures to improve survey response rates also have driven up the cost of data collection. Moreover, businesses are particularly concerned about protecting proprietary data, especially with respect to making data available for public use. • Globalization and logistics—Increased globalization and continued growth of the service economy have changed shipping, logistics, and supply chain patterns in ways that are not captured by current freight data surveys or at geographic levels (i.e., market areas) useful for network planning and management and economic analysis. • Resources—Resources have always been a constraint, but increased competition for funds has made it more important than ever to be strategic and selective in defining data needs, to identify ways of collecting data more cost-effectively, and to demonstrate the value per dollar invested in data. The above changes pose considerable challenges for travel data program managers. At the same time, however, they provide an opportunity to reorient and adapt data programs in ways that are more responsive and useful to policy and decision makers. Key Issues for Study Looking forward, improving passenger and freight travel data will require addressing several key issues. Defining essential travel data is an important first step. The range of different users and the breadth of their data needs, however, make this a difficult task. Core data organized around a few key surveys may prove valuable to all data users, but a more distributed system of data collection may be needed to meet specific user needs. In addition, being more strategic in defining essential data requires being selective and considering what can be discarded. 

18  How We Travel: A Sustainable National Program for Travel Data Second, developing a more policy-relevant and enduring travel data system requires leadership, particularly at the federal level, and greater coordination with data partners, such as states and metropolitan plan- ning organizations. What often exist now as disparate surveys with a myriad of different uses need to be integrated into a more logical and well-focused system of travel data programs, directed toward users and decision making. Third, data program managers need to address the growing conflict between the expressed desire of many users for more small-area data with which to examine regional and local policies, such as encouraging bicycling to work or greater transit use, and growing privacy concerns among those individuals and businesses that provide the data, particularly as the feasibility of collecting small-area data grows. What mechanisms are available to ensure confidentiality while meeting legitimate needs for detailed data? What are reasonable limits, and who should be responsible for negotiating these arrangements? Fourth, the timeliness of data is an increasing concern. Periodic surveys whose results can take up to 2 years to release after completion of the data collection are simply too little, too late for many decision makers. Continuous annual surveys are becoming more commonplace but have their own problems. Interpreting annual data for trend analysis, accumulating sufficient annual data to provide reliable information for small geographic areas, and accommodating greater data variability in return for better timeliness are just some of the issues that need to be addressed. Fifth, providing sustained resources to support travel data programs is a perennial concern. Finding partners to share the burden is part of the answer, but in the long run, it is no substitute for leadership and the build- ing of strong user constituencies. As discussed in this report, neither of these elements has been much in evidence. Finally, improving access to data—particularly making available data that have been transformed into useful products—is a necessary step toward meeting user needs and thereby building support for data programs. Modelers and researchers need detailed data with accompanying statistical information. Policy makers require timely summary products, tailored to particular policy uses and users, which should boost both the visibility and the value of the data. 

Introduction  19  Organization of the Report The remainder of the report addresses the key elements of the committee’s charge. Chapter 2 provides an overview of current travel data programs and critical gaps in coverage and characteristics, drawing on prior studies, as well as briefings to the committee from data providers and users (see Appendix B for a full listing of these briefings and Appendix C for a list of selected references; Appendix E provides a more detailed discussion of these programs). Chapter 3 examines barriers to data collection and opportunities for overcoming these barriers—from using technology more effectively to employing alternative methods for data collection. Chapter 4 introduces the committee’s proposal for a National Travel Data Program to better meet the travel data needs of policy and decision mak- ers and details how the program should be managed and funded. The final chapter presents the committee’s key findings and recommendations for a strategy for improved passenger and freight travel data. References Abbreviations BTS Bureau of Transportation Statistics NRC National Research Council TRB Transportation Research Board Billitteri, T. J. 2010. Census Controversy. CQ Researcher, May 14, pp. 433–455. BTS. 2010. National Transportation Statistics. http://www.bts.gov/publications/ national_transportation_statistics/. Accessed Aug. 26, 2010. NRC. 1997. The Bureau of Transportation Statistics: Priorities for the Future (C. F. Citro and J. L. Norwood, eds.), National Academy Press, Washington, D.C. Pew Research Center. 2010. Distrust, Discontent, Anger and Partisan Rancor. Pew Research Center Publications, Washington, D.C., April 18. http://pewresearch. org/pubs/1569/trust-in-government-distrust-discontent-anger-partisan-rancor. Accessed May 13, 2010. Schofer, J. L., T. J. Lomax, T. M. Palmerlee, and J. P. Zmud. 2006. Transportation Research Circular E-C109: Transportation Information Assets and Impacts: An Assessment of Needs. Transportation Research Board of the National Academies, Washington, D.C., December. http://onlinepubs.trb.org/onlinepubs/circulars/ ec109.pdf. 

20  How We Travel: A Sustainable National Program for Travel Data TRB. 2003a. Special Report 276: A Concept for a National Freight Data Program. Transportation Research Board of the National Academies, Washington, D.C. http://www.nap.edu/catalog.php?record_id=10793. TRB. 2003b. Special Report 277: Measuring Personal Travel and Goods Movement: A Review of the Bureau of Transportation Statistics’ Surveys. Transportation Research Board of the National Academies, Washington, D.C. http://onlinepubs. trb.org/onlinepubs/sr/sr277.pdf. TRB. 1992. Special Report 234: Data for Decisions: Requirements for National Transportation Policy Making—New TRB Study. TRB, National Research Council, Washington, D.C. Young, P., K. Notis, G. Feuerberg, and L. Nguyen. 2007. Transportation Services Index and the Economy. BTS, Research and Innovative Technology Administration, U.S. Department of Transportation, Washington, D.C., December. http://www. bts.gov/publications/bts_technical_report/2007_12_21/html/entire.html.