The U.S. Congress has placed a number of important mandates on the Bureau of Transportation Statistics (BTS)-now part of the Research and Innovative Technology Administration (RITA)-of the U.S. Department of Transportation.1 Among them is a directive to compile, analyze, and publish a comprehensive set of transportation statistics, including information on a specific list of topics included in legislation.
The Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA), which originally established the Bureau, included a list of 11 topics. In the Transportation Equity Act for the 21st Century of 1998 (TEA-21), Congress added a 12th topic to the list.2 Congress instructed RITA/BTS to include information on these topics in this annual report for the President and Congress. Chapter 2 of this and previous editions of the annual report compiles and analyzes a selection of data on each of these 12 topics. Other RITA/BTS publications (e.g., National Transportation Statistics and its associated volume of state transportation statistics) provide additional data on these topics assembled from multiple sources.
Surface transportation legislation passed by Congress in 2005-the Safe, Accountable, Flexible, Efficient Transportation Equity Act-A Legacy for Users3 (SAFETEA-LU)-amended the list of data topics. While it added only 1 new item, the law altered 10 of the preexisting 12 topics (table 3-1). The new and revised topics reflect changing ideas in Congress about the appropriate extent of transportation statistics. These changes are, thus, the subject of this year's discussion of the state of transportation statistics, the theme of this chapter.
Compared with the previous list, the 13 data topics in SAFETEA-LU place additional emphasis on goods movement, intermodalism, connectivity, and security data. In addition, they require more modal, infrastructure, and vehicle coverage.
Goods movement is added to several topics that previously focused only on passenger travel or had only implied goods movement. Intermodalism and connectivity are new on the topics list for information reporting to Congress by RITA/BTS through reference to the mandated Intermodal Transportation Data Base. Connectivity is also a component added to another amended topic. The original list, which was created 14 years ago, made no mention of security data. As an issue of major concern today, the legislation proposes including security data within the broad context of travelers, vehicles, and the transportation system. Improved modal coverage is explicitly added or, in other cases, is implied, as is infrastructure data. Several amended topics ask for more types of vehicle data (e.g., characteristics and extent).
Not surprisingly, overlaps exist among the 13 topics. Accordingly, in the following pages RITA/BTS has grouped the topics under five main categories:
Examples of many of the datasets discussed below can be found in chapter 2 of this report. The focus of that chapter is on the previously mandated 12 data topics. However, some of the new topics, such as goods movement and modal, infrastructure, and vehicle coverage, are included, as they have been in previous editions of the Transportation Statistics Annual Report.
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Passenger travel and freight movement are the basic currency of transportation. Information about the flow of people, goods, and vehicles on the transportation system is key for evaluating current system capacities and planning future infrastructure needs, and also is needed to understand transportation energy usage, safety risks, and other aspects of transportation. While most of the data topics in table 3-1 pertain in some way to movement of goods and people on the transportation system, those discussed in this section-traffic flows for all modes of transportation and availability and use of mass transit and other for-hire passenger modes-address the subject most directly.
Traffic Flows [B].4 Generally measured by the origins and destinations of passenger and freight movements, traffic volume, and the routes taken, these data are especially important for planning purposes at local, state, and regional levels and are used in policy analyses at all levels of government. While aggregate data on amounts of traffic by specific modes are generally available, less information is available on how the data translate to flows on networks or on connections between modes. Traffic data are often used as input for models that simulate flows.
For freight transportation, the Commodity Flow Survey (CFS), conducted by RITA/BTS and the U.S. Census Bureau on a five-year cycle, provides the most comprehensive national source of multimodal freight flow data. This survey of shippers includes tons, value, and ton-miles of shipments for covered industry sectors. All sectors are not surveyed nor are most imports. Also, the sample size of the most recent survey in 2002 was smaller than prior surveys in 1992 and 1997, making it less useful in terms of commodity detail and geographic coverage than earlier surveys. Other mode-specific data sources can be used to fill some but not all missing pieces in the CFS. RITA/BTS and the Federal Highway Administration (FHWA) have developed an extended dataset to provide a more complete national picture of freight flows than is currently available from this survey . Over the longer term, survey modifications (e.g., increasing the sample size of the 2007 version) could enhance coverage. Working groups from RITA/BTS and the Census Bureau are jointly developing design improvements for the 2007 CFS.
Insufficient geographic detail on freight flows at the metropolitan and corridor level is a key limitation in current data. Such data can provide insight into transportation demand, relationships between freight movement and business patterns, and flow of freight through major corridors. The CFS was not intended to provide detailed local-level data. Currently, there is a lack of detailed data for many metropolitan areas, especially for trucking, which accounts for the majority of freight shipments in the United States on both a value and tonnage basis.
Conducting a national survey of carriers would be one option for collecting more detailed trucking data and other mode-specific information. An initial survey might begin with trucking and then possibly be expanded to include other modes. RITA/BTS is evaluating options for a survey of a selected group of for-hire trucking carriers to obtain detailed information on freight movement characteristics. The goal of such a survey would be to capture specific types of carrier information that is unavailable from the CFS shipper-based survey (e.g., whether shipments are less-than-truckload or truckload, origin and destination locations, and intermodal characteristics of shipments). This type of survey would need to be carried out in partnership with carriers and provide carriers with assurance that data would not identify individual firms.
To capture passenger travel flows, the National Household Travel Survey (NHTS), last conducted jointly by RITA/BTS and FHWA in 2001/2002, covers local and long-distance travel, encompasses all modes of transportation, and also offers considerable demographic detail about travelers. However, the sample size of the 2001/2002 survey is insufficient for identifying traveler origins and destinations and geography. Hence, the NHTS, while useful for policy analysis and modeling, has been less useful for planning at the state and local level. However, nine jurisdictions-four states, part of Kentucky, and four urban areas-contributed funds to the survey in order to obtain greater detail on travel patterns in these areas. Other states use NHTS daily trip data as default values for their travel demand models.
In most areas, passenger flow data at the metropolitan level are limited. The Decennial Census and American Community Survey provide specific state-, county-, and city-level journey-to-work data distributed to planners by RITA/BTS, FHWA, and the Federal Transit Administration (FTA) through the Census Transportation Planning Package. Other than journeys to and from work, detailed information about other trips varies.
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No annual data are available for travel flows by bicycle or pedestrians, although NHTS does supply data on trips and typical weekly behavior for both. RITA/BTS and the National Highway Traffic Safety Administration collaborated on a one-time study in 2004 of pedestrian and bicyclist attitudes and behavior in which respondents were asked about frequency of walking and bicycling and conditions . Recreational boating may need a different measure than that provided by the NHTS for trip counts and distance traveled. One option would be to measure the amount of time people spend boating, for instance. The Federal Aviation Administration's annual survey on general aviation focuses on aircraft characteristics and hours flown, but does not include origins and destinations or distances flown.
Most travel, whether local or long distance, occurs in cars and other personal highway vehicles. FHWA and state departments of transportation estimate vehicle movements through the Highway Performance Monitoring System, and these estimates can be used to assign flow data to specific routes.
The flow of people and goods across U.S. borders is a subject of great importance, especially given the security concerns that have arisen since September 11, 2001. RITA/BTS obtains data from Customs and Border Protection of the U.S. Department of Homeland Security that covers the number of people, vehicles, trains, and containers crossing into the United States from Canada and Mexico through more than 100 U.S. land gateways. The data are compiled and verified and then disseminated on the RITA/BTS website.
RITA/BTS also releases data on U.S. imports from and exports to Canada and Mexico by transportation mode. Monthly releases of the surface trade data show the shipment value, breakdowns by mode, and the state of origin or destination. In 2004, RITA/BTS initiated the collection and compilation of similar data for air and water.
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Availability and use of for-hire passenger modes [H]. While previous legislation asked RITA/BTS to compile, analyze, and publish statistics on the availability and use of mass transit, SAFETEA-LU places additional emphasis on "other forms of for-hire travel." Other for-hire travel modes include intercity train; intercity scheduled and charter bus; local taxis; and air transportation, including commercial, air taxi, and charter operations.
FTA collects data from large transit agencies that receive federal funding; others report voluntarily. These agencies account for 95 percent of U.S. transit ridership. The American Public Transportation Association also collects data from its members and makes the data available publicly. Less information is available on rural public transportation. FTA commissioned a survey of rural providers in 2000, but this survey has not been repeated.
For other for-hire passenger travel, data on enplanements by airport and air carrier are available from RITA/BTS, and intercity train boardings are available from Amtrak. These data can be accessed by the public. The Federal Motor Carrier Safety Administration has been assigned the responsibility to collect data from Class I bus operators on the numbers of their passengers, including whether the passengers are intercity, charter or special, or local; but these data are not listed by facility location.
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In terms of availability of for-hire passenger service, no comprehensive national statistics exist that track trends in routes and schedules across for-hire modes. However, RITA/BTS evaluated scheduled service operations for over 200 city pairs covering air carriers, intercity train, and intercity bus operations in 2003 and is updating that study with the release expected in 2005 . Another RITA/BTS study evaluates the proximity of rural Americans to for-hire intercity transportation services. First conducted in 1999, the study has been updated periodically when conditions change, with the most recent update in June 2005 .
Information on system status relates to transportation infrastructure-its physical characteristics in terms of extent, connectivity, and condition, and its economic status in terms of capital investment-and its availability for use as reflected in travel times, congestion, and service interruptions. It also pertains to the physical characteristics of the vehicles and other conveyances that use the infrastructure.
System extent, connectivity, and condition [L]. An enormous amount of information exists about the extent and location of transportation facilities, the number and nature of connections within and between modes, and the physical condition of system components. Putting such information together so it is meaningful for decisionmaking has much promise as an aid for identifying priorities among transportation investments, planning, and policy setting. Offering 250 summary tables aggregated at the national level on a wide variety of topics that characterize the transportation system, RITA/BTS's National Transportation Statistics report compiles data that cover all modes and all aspects of the transportation system from a variety of sources. A companion volume presents over 100 state-level tables for the 50 states and the District of Columbia .
Recent decades have seen great expansion in the capability of geographic information systems to display transportation data in meaningful ways for decisionmaking. RITA/BTS's National Transportation Atlas Database (NTAD) enables display of transportation information in its geographic context (box 3-A). Comprised of geographic databases of transportation facilities, networks, and associated infrastructure, the atlas can display relevant data at national, regional, state, and local levels. It includes spatial information for specific modes, intermodal terminals, and related attribute information. The data, obtained from multiple sources, include the National Highway Planning Network, a national rail network, public-use airports and runways, and Amtrak stations. In addition, the NTAD includes state, county, congressional district, and metropolitan statistical area boundary files to provide a geographic reference for transportation features.
Geospatial information on transportation infrastructure can be stored and used for development and maintenance planning. For instance, the National Bridge Inventory maintained by FHWA contains information on structurally deficient bridges. Information describing the location and bridge conditions can be displayed cartographically and analyzed. Geographically accurate maps can be produced using a variety of data tables or layers placed one on top of the other to show geographic relationships.
Travel times and congestion [D]. Tracking changes in how long it takes to travel from one point to another is one way to measure transportation system performance, and change over time is one measure of congestion. Travel times can be affected by the density of traffic on a transportation network, the number of modal and intermodal connections, and service availability and reliability. Individual carriers often collect data on travel times associated with their operations, although the extent to which such information is routinely summarized and made publicly available varies by mode. Surveys can ask customers about their perceptions of transportation systems and to identify delays they have experienced-an approach taken in RITA/BTS's Omnibus Survey, which periodically polls households on a range of transportation questions.
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In the case of air passenger travel, a particular problem is to evaluate "door-to-door" movements. Thus, travelers are not only concerned about flight time and delay, but also about how long it takes to get to and from airports. Scheduled versus actual travel times is another dimension. For instance, frequency of service, nonstop versus having to make connections, cancellations, and diversions all may need to be taken into consideration to get a full accounting of travel times.
National-level travel time data are most extensive and detailed for air passenger travel. Each month, RITA/BTS issues data on the on-time performance of large U.S. air carriers. Since 2003, cause-of-delay data have also been available. On-time arrival and departure data also can be displayed by airport. Additionally, RITA/BTS has developed an Air Travel Time Index, which measures average flight times of domestic nonstop flights (the difference between scheduled times and actual elapsed times) while controlling for different flight characteristics.
For freight transportation, some of the information needed to evaluate travel times is proprietary, which complicates public analysis. Sometimes, however, it is possible to use data in such a way that individual carriers are not identified. This can benefit both the industry (which gains information useful in benchmarking their operations against the industry average) and the public (which gains trend information). RITA/BTS has calculated quarterly estimates of average overall line-haul speeds for the rail freight industry, making it possible to compare overall national line-haul speeds over time.
The best way to estimate congestion remains a subject of debate. More than likely, a range of estimates and methods will be needed to provide an accurate picture. Partnerships between industry, trade associations, and different levels of government may offer promise as a way to gather information needed for measurement without compromising the confidentiality of proprietary data.
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Measuring highway congestion is of continuing interest. An FHWA report  in 2004 summarized the data challenges ahead, noting that continuous streams of data are not available in some regions, data cover only a portion of the transportation network, erroneous data or gaps in data are common, and lack of consistent standards for data across regions hinder meaningful comparison. Meanwhile, an index of highway congestion for metropolitan areas is reported annually by the Texas Transportation Institute. Delays in surface border crossings from Canada and Mexico are captured by Customs and Border Protection of the Department of Homeland Security.
Interest in port congestion is growing at the national level. However, there are no standard congestion measures for ports. Individual ports use their own methods to determine congestion. Some measure the number of vessels in port at a given time, the amount of time a vessel has to wait to be unloaded, throughput (in terms of the number of TEUs-20-foot equivalent units-in a given hour or day), or truck idling time.
Repairs and other interruptions of service [I]. The time in which vehicles and facilities are unavailable for use because of repairs and other interruptions of service is another aspect of system status and could be a basic performance measure for the transportation system. However, nationwide data are not currently available to properly characterize the frequency of repairs for vehicles and infrastructure for most modes. Local and state transportation authorities routinely provide information to the public about the location and duration of scheduled maintenance operations and other sources of travel interruptions. FHWA has a website that displays contemporaneous reporting from these and other sources for all 50 states.
A comprehensive national database on interruptions caused by weather, work stoppages, security alerts, and other service outages is not available. However, FHWA and others produce composite information on traffic delays for some metropolitan areas that can be summarized on a monthly basis. Data on some specific interruptions have been compiled, such as the halt in air traffic on September 11, 2001, and the effects of a labor dispute that shut down West Coast ports in fall 2002.5
Public availability of data on vehicle repairs is mixed. For instance, data pertaining to the repair of most trucks in operation are not public information but are proprietary. (RITA/BTS has used data on trucks pulled out of service for repairs at highway inspection stations as a surrogate measure.) In the case of passenger cars and other household vehicles, consumer advocacy groups and research organizations compile some reliability and repair information on specific models. But these data have not been aggregated in any way to satisfy this data topic.
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Vehicle weights and other characteristics [E]. Vehicle weight data are useful for infrastructure planning, safety analysis, estimation of energy usage, evaluation of environmental trends in transportation, and other matters. While the term "vehicle" may imply highway vehicles, data for other modes are also relevant. Proposed legislation adds the phrase "and other vehicle characteristics" to weight. The term "other characteristics" is not defined, but could include size, fuel usage and efficiency, age, condition, ownership, and number available in service and in reserve fleets. Additional vehicle features, such as accessibility for disabled persons, safety equipment, and emissions, noise generation, and other environmental characteristics, are also relevant. Not all characteristics are suitable for application across all modes. In the case of maritime vessels, for example, deadweight tonnage and draft are more appropriate than weight, because these measurements determine whether vessels can access or will impact infrastructure such as channels and ports.
The most detailed survey of highway vehicles-the Census Bureau's Vehicle Inventory and Use survey-is conducted every five years and covers light (including sport utility vehicles and minivans), medium, and heavy trucks. Data include the number of vehicles by weight category.
Elements of the Intermodal Transportation Data Base [C]. Congress, in previous legislation, required RITA/BTS to establish and maintain a transportation database for all modes of transportation (box 3-B). SAFETEA-LU added elements of this database to the list of topics that RITA/BTS reports on to Congress. Doing so may require RITA/BTS to newly compile, analyze, and/or publish data on transportation intermodalism and connectivity and provide a national accounting of transportation expenditures and capital stocks. Other elements of the database, such as movement of goods and passengers by all modes of transportation, are included in other components of the data topics list.
Intermodalism and connectivity are about linkages between modes resulting in efficient flows of transportation. Examples include moving goods from incoming vessels through ports via rail or truck and moving people between cities via surface transportation modes in combination with air travel. To initiate development of data in these areas, RITA/BTS has considered ways to use the data gathered for the scheduled intercity transportation studies to evaluate the intermodal connectivity of the passenger transportation network [2,4].
The system status of both infrastructure and vehicles is reflected in the economic concept of capital stock, which is an economic measure of capacity. In transportation terms, it combines the capabilities of modes, components, and owners into a single measure of capacity, expressed in dollars. The measure takes both the quantity of each component (as reflected in initial investment) and its condition (as reflected in depreciation and retirements) into account.
A comprehensive set of modal capital stock data would be useful to policymakers and others in evaluating the current investment in transportation infrastructure and rolling stock and levels of investment needed to accommodate anticipated future traffic. While the Bureau of Economic Analysis in the U.S. Department of Commerce compiles data on private sector transportation capital stock, its data do not capture all public sector transportation capital stock. RITA/BTS is developing values for publicly owned transportation capital stocks, including airports, waterways, and transit systems. RITA/BTS also publishes a biennial report-Government Transportation Financial Statistics-that presents a compilation of data on government transportation revenues and expenditures for all modes of transportation.
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Overlap exists among variables that influence travel and goods movement, the domestic economy and U.S. global competitiveness, productivity in the transportation sector, and other data topics (e.g., transportation cost is a variable for both passengers and goods movement).
Variables influencing traveling behavior [F]. A host of demographic, economic, and other variables influence passenger traveling behavior, including access to transportation, transportation costs, employment status and location, income, location of housing and services, and other factors such as family status, age, and disabilities. In the broadest sense, goods movement is influenced by the economy and population and its geographic distribution, including the location of goods producers, suppliers, and customers in relation to each other. Goods movement is also driven by trends in technology and industrial organization, such as just-in-time delivery, logistics organization, and e-commerce.
One way to shed light on the variables influencing travel behavior and choices is through surveys. The previously mentioned National Household Travel Survey provides much information on the demographic and economic characteristics of household travelers in relation to their transportation choices. Surveys also can be useful for goods movement, although much of the data needed to evaluate firm choices are proprietary.
Variables influencing the domestic economy and global competitiveness [M]. A great many transportation variables influence the performance of the domestic economy and U.S. global competitiveness including:
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Considerable data exist for many of these topics. In the case of global competitiveness, for example, RITA/BTS compiles data on the relative prices of U.S. transportation goods and services versus selected major trading partners and on U.S. international trade in transportation-related goods and services and the associated U.S. trade balance. RITA/BTS has also conducted a study on the capacity of U.S. highway infrastructure relative to other G-7 countries. Still, data gaps exist (box 3-C).
Several data issues that pertain to transportation and the economy are discussed in other parts of this chapter. Data on private and government investment in transportation infrastructure and equipment and on transportation capital stock are covered under System Status above. Productivity measures are covered in the next paragraph.
Transportation sector productivity [A]. In general, productivity measures describe the relationship between the quantity of output produced and the inputs (labor and capital) used, and the data are helpful for economic and public policy analysis and private sector planning. They should enable comparisons across transportation modes, between transportation and other sectors of the domestic economy, and of U.S. productivity with that of other countries.
Data limitations exist among the three types of productivity measures: labor productivity, capital productivity, and multifactor productivity. Productivity data have been affected by the transition of U.S. government statistical agencies to a different way of classifying sectors of the U.S. economy, going from the Standard Industrial Classification (SIC) system to the NAICS. Currently, NAICS-based productivity estimates cover only some of the transportation sectors, while SIC-based data for some sectors were produced in the past but are no longer generated (table 3-2). RITA/BTS is developing multifactor productivity measures for other modes (e.g., trucking, pipeline, and water). All of these data cover the for-hire component of the transportation sector. Data on the in-house component of the transportation sector are not available, thus it is not possible to report on the productivity of the transportation sector as a whole.
Costs of passenger travel and goods movement [G]. The proprietary nature of data on the costs of goods movement means that little such information is publicly available. However, producer price indexes prepared by the Bureau of Labor Statistics (BLS) of the U.S. Department of Labor allow tracking of changes over time in prices charged for many passenger and freight transportation sectors. Producer prices reflect charges to anyone, including consumers, when the producing firm also serves as the retailer and may not always reflect actual prices paid by end users.
In general, data on the average costs of passenger travel are available by mode, but detailed data are missing. However, modal data are not necessarily compatible, making comparisons between modes difficult. For passenger travel costs as a whole, the BLS annual survey on average household spending captures data that include private vehicle expenditures and spending on transportation fares such as airlines, transit, taxis, trains, and buses.
RITA/BTS has developed an Air Travel Price Index to measure the change over time in the actual prices paid by air travelers. The index can be used to compare airfares in the most recent quarter available with any quarter since the 1995 base year. The index reflects fares paid by travelers, not published fares. It is computed using data from the RITA/BTS Passenger Origin and Destination (O&D) Survey, a 10 percent sample of all airline tickets for U.S. carriers, excluding charter air travel. By using the actual fares from the O&D survey data, the index accounts for consumers' tendency to substitute less expensive air travel services for more expensive ones when relative prices change.
The legislation expands this topic from the previous request for information on "accidents" to cover security and, explicitly, the safety and security of vehicles and infrastructure, as well as people. Accident, injury, and fatality data are available by mode, although problems exist with exposure rates for some forms of transportation (e.g., walking/bicycling, general aviation, and recreational boating).
However, security data once readily available are not anymore, especially data that relate to terrorism.6 In some cases, the data are still generated but not released to the public. In other cases, the data are no longer collected because priorities have changed in the agencies that once made relevant data available. While the U.S. Department of State's Patterns of Global Terrorism annual document is still made available, it does not dissaggregate transportation data. The U.S. Department of Transportation's annual Worldwide Terrorist and Violent Criminal Attacks Against Transportation document has not been produced since 1998, and the Federal Aviation Administration is no longer producing its Criminal Acts Against Civil Aviation report. Some of the latter data can be culled from private databases available online, however.
As the proposed legislative change makes clear, differences among vehicles have implications for safety data. Changes in consumer preferences for vehicles, such as the rapid increase in sales of sport utility vehicles and other light trucks over the last 15 years, has made crashes more likely between these larger vehicles and smaller passenger cars and also has raised issues about the vehicles themselves. Data on crashes involving more than one mode of transportation, such as passenger cars or bicycles with trains at grade crossings, remains an important topic. In addition, safety incidents involving freight and passenger modes, which often share the same facility or road, also present data challenges.
Transportation system safety data issues present other challenges. Safety statistics continue to be difficult to compare across modes because of different reporting criteria and inconsistent definitions. There is also lack of agreement about the scope of coverage: should a systemwide perspective encompass deaths and injuries arising from, say, repair of vehicles in a facility dedicated to this purpose, or should reporting be limited to incidents involving a moving vehicle?
Other federal agencies and departments have much of the responsibility for collecting data used in assessing the consequences of transportation for the human and natural environment. The U.S. Environmental Protection Agency (EPA) produces data on national estimates of air pollutant emissions from transportation vehicles and air quality across the nation (although these data are not necessarily specific to transportation or any other source). EPA also generates data on the disposal rates of some transportation equipment (e.g., batteries and tires) and tracks problems related to the underground storage of petroleum.
Energy does not explicitly appear in Congress' list of data topics. Energy data related to transportation, however, is a relevant component of both security and this data topic. Energy and fossil fuel usage, for instance, are a key factor in evaluating the air pollution impacts of transportation. These data are collected or estimated by the Energy Information Agency (EIA) of the U.S. Department of Energy. Both EPA and EIA annually estimate transportation's greenhouse gas emissions, which may contribute to global climate change. While both agencies use EIA survey data on energy consumption as a basis for their estimates, their coverage and methodologies differ, resulting in different datasets.
The U.S. Coast Guard, which moved from the Department of Transportation (DOT) to the Department of Homeland Security, has been the source of national data on oil spills, another important indicator of transportation's environmental consequences. However, new homeland security priorities for the Coast Guard have caused these environmental data to become less timely and robust. EPA collects information on other damages to the nation's water, but the data are not necessarily specific to transportation. Data on hazardous materials incidents are collected by DOT's Pipeline and Hazardous Materials Safety Administration but, again, the data do not directly measure environmental consequences.
The need for transportation information is constantly evolving. Each year, RITA/BTS has evaluated transportation data in response to the congressional mandate that the Transportation Statistics Annual Report provide recommendations for improving transportation statistical information. Over the years, other reports by RITA/BTS, such as Transportation Statistics Beyond ISTEA: Critical Gaps and Strategic Responses (1998) and Bicycle and Pedestrian Data: Sources, Needs, and Gaps (2000),7 and by others, such as the Transportation Research Board's Information Needs to Support State and Local Transportation Decision Making into the 21st Century (1997) and its reviews of the CFS (2003) and NHTS (2002), have supplemented this information.
In addition to expanding the scope of data issues in 2005, the U.S. Congress has mandated that the Secretary of the U.S. Department of Transportation enter into an agreement with the National Research Council to assess national transportation information needs.8 This comprehensive assessment is expected to take two years to complete and provide the nation with information on data needed to improve transportation decisionmaking at all levels of government and on new data-collection methods that would improve the standardization, accuracy, and utility of transportation data and statistics. Congress has also asked for an estimate of the cost of implementing any recommendations.
Given the expansion of data issues the U.S. Congress has asked RITA/BTS to collect, compile, analyze, and publish and the new study requirement, it is evident that the need for relevant, timely, high-quality transportation information for decisionmaking remains.
1. U.S. Department of Transportation, Federal Highway Administration. 2004. Traffic Congestion and Reliability: Linking Solutions to Problems. Available at http://www.ops.fhwa.dot.gov/congestion_report/, as of September 2005.
2. U.S. Department of Transportation, Research and Innovative Technology Administration, Bureau of Transportation Statistics. 2003. Many Intercity Travelers Face Longer Travel Schedules, Issue Brief. Available at http://www.bts.gov/.
3. ______. 2004. State Transportation Statistics. Washington, DC. Also available at http://www.bts.gov.
4. ______. 2005. Scheduled Intercity Transportation: Rural Service Areas in the United States. Available at http://www.bts. gov/.
6. U.S. Department of Transportation (USDOT), Research and Innovative Technology Administration, Bureau of Transportation Statistics, and USDOT, National Highway Traffic Safety Administration. 2002. National Survey of Pedestrian and Bicyclist Attitudes & Behaviors. Washington, DC.
1 On November 30, 2004, the President signed Public Law 108-426, the Norman Y. Mineta Research and Special Programs Improvement Act, creating the Research and Innovative Technology Administration and placing the Bureau of Transportation Statistics under this new administration. Among other things, the RITA Administrator is to carryout powers and duties prescribed by the Secretary of Transportation for "comprehensive statistics, research, analysis, and reporting." Prior to becoming part of the new modal administration, the Bureau functioned as a separate Department of Transportation operating administration.
2 49 U.S. Code 111(c)(1).
3 Public Law 109-59
4 The capital letter here and at the end of the subtitles that follow refers to the data topic in the legislation (see table 3-1).
5 As this report was being finished, data were being collected on the impacts on transportation of Hurricanes Katrina and Rita, which hit the Gulf Coast regions in September 2005.
6 See Transportation Statistics Annual Report 2001, pp. 107-135 (Chapter 5, Security). This is the most recent, comprehensive compilation of publicly available transportation security data.
7 Documents available at http://www.bts.gov/.
8 49 U.S. Code, Section 111(d)