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State of Transportation Statistics
Introduction
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.
Summary of Amended Topics
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:
- movement of people, goods, and vehicles;
- system status;
- variables and factors affecting travel
and goods movement;
- safety and security; and
- unintended consequences.
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.
Movement of People, Goods, and
Vehicles
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| Photo credit: Dorinda Edmondson |
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.
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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 [5]. 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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| Photo credit: Chip Moore |
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 [6]. 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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| Photo credit: Marsha Fenn |
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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| Photo credit: Marsha Fenn |
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 [2]. 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 [4].
System Status
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
[3].
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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| Photo credit: Marsha Fenn |
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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| Photo credit: Elliott Linder |
Measuring highway congestion is of continuing interest. An FHWA
report [1] 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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| Photo credit: Marsha Fenn |
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.
Variables Affecting Travel and Goods
Movement
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| Photo credit: Chip Moore |
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:
- Relative prices of
transportation goods and services. This important and direct
measure of competitiveness takes into account the quality of the products and
services. Relative prices show whether domestic industries or domestically
produced goods and services are less expensive than their foreign counterparts.
- Quality and reliability of
transportation goods and services. These factors affect demand
for transportation goods and services but are difficult to quantitatively
measure. Possible measures might include passenger flight delays and
cancellations, freight shipment delays and cancellations, after-sales services
of transportation goods, and so forth.
- Relative cost of transportation inputs. This includes, for example, unit labor cost, unit capital cost, and unit total
input cost.
- Relative productivity. This covers labor, capital, and multifactor
productivity for overall transportation and by mode of transportation. (See separate discussion of productivity factors.)
- Transportation
infrastructure. This is a necessary and essential input for the
provision of transportation services and can be measured by transportation
investment, transportation capital stock, transportation capacity (e.g.,
capacity per vehicle-mile, per gross domestic product, per capita, and so on),
accessibility of transportation infrastructure (network density), and the
quality and reliability of transportation infrastructure.
- U.S. international trade in transportation-related
goods and services. This includes their shares of
U.S. trade in the global market and trade balances (exports minus imports).
- Employment. This measure captures transportation employment in for-hire and private
industries. For-hire data is collected by the Census Bureau and is classified
by North American Industry Classification System (NAICS) categories. Private
transportation employment is harder to quantify, because it involves extracting
the number of transportation-related workers from nontransportation-related
industries.
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| Photo credit: Getty Images |
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.
Safety and Security of Transporation [J]
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).
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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?
Consequences of Transportation [K]
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.
Conclusions
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.
References
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/.
5. ______. 2005. Freight in
America
. Washington, DC.
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)
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