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2
Overview of Current
Travel Data Programs
and Gaps
T
his chapter presents an introduction to the major travel data pro-
grams and the current gaps in the data they produce, responding to
the committee’s charge to assess the state of passenger and freight
travel data at the federal, state, and local levels. The chapter starts with a
discussion of what constitutes a comprehensive data program. Gaps in
current passenger and freight travel data are then examined, drawing on
informational briefings presented to the committee by data providers and
users at its early meetings, as well as on prior studies. The chapter concludes
with findings on the current state of travel data.
Elements of a Comprehensive Data Program
Data programs are typically built around a core set of data collection
activities, including surveys, data drawn from administrative records,
and/or direct data sources (e.g., road sensors). A well-functioning data
program, however, includes a much broader range of activities:
• Trained staff to oversee data collection, provide quality control, and
turn data into useful information and products for users;
• Staff development, with clear career paths;
• Systematic mechanisms for involving users and obtaining user feedback
on a wide range of issues, from the design of data collection, to data
products, to data access and dissemination;
21
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22 How We Travel: A Sustainable National Program for Travel Data
• Continuing outreach to identify opportunities for partnering in data
collection, appropriate cost-sharing arrangements, and effective
methods for ensuring data integrity and confidentiality;
• A continuing program of research on improved methods of data collec-
tion, with sufficient funds for pilot testing of new methods; and
• Dissemination activities to increase the visibility and value of the data
to users and help build strong constituency and sustained funding
support.
Core data collection activities are at the heart of data programs. At a
minimum, essential data must be identified and maintained over time to
provide continuity for trend analyses. Data must be sufficiently granular
(detailed) to support user needs for planning and policy studies. Also
desirable is for data elements to be flexible and scalable so they can be
organized in different ways to meet different user needs. Finally, the data
must be timely and of sufficient frequency to provide an accurate portrayal
of the phenomena being represented. Comprehensive travel data programs
with all these characteristics do not currently exist. Indeed, meeting all
these needs may not be possible, particularly with a single survey or other
data collection method. Issues of cost and confidentiality, for example,
must be balanced against user needs for detailed data in program design
and management.
Overview of Current Travel Data Programs
Responsibility for Travel Data Collection
Travel data are collected by various government agencies and the private
sector. The most comprehensive sources of travel data—the flagship
multimodal National Household Travel Survey (NHTS) and the Commodity
Flow Survey (CFS), which provide a national picture of U.S. passenger and
freight travel, respectively—are administered by the federal government.
The U.S. Department of Transportation (U.S. DOT) is responsible for the
NHTS but shares this responsibility with the U.S. Bureau of the Census for
the CFS (Table 2-1). The Census Bureau serves as the lead in collecting data
on the Journey to Work, once part of the long form of the decennial census
but now part of the Census Bureau’s continuous American Community
Survey (ACS).
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TABLE 2-1
Responsibility for Major Travel Data Programs
States, MPOs, and
Data Provider and Survey U.S. DOT Other Federal Agency Other Local Public Agencies Private Sector
Multimodal
NHTS With state and MPO
FHWA
funding support
JTW Census Bureau
CFS BTS With Census Bureau
North American Transborder With data purchased
BTS/FHWA
Freight Data from the Census Bureau
TrANSeArCH IHS Global Insight
D. K. Shifflet & Associates D. K. Shifflet & Associates
Survey System
Survey of International
OTTI, DOC
Air Travelers
Modal
HPMS
States collect and
FHWA
report data
NTD Transit properties collect
FTA
and report data
rail Carload Waybill Sample railroads collect and report data
FrA/STB
to STB; STB produces public-use
sample
Air Carrier Traffic Statistics Certificated air carriers collect
BTS
and report data
Waterborne Commerce Vessel operators report to USACe
USACe
of the U.S. on domestic commerce
PIerS UBM Global Trade
Note: BTS = Bureau of Transportation Statistics; CFS = Commodity Flow Survey; DOC = Department of Commerce; FHWA = Federal Highway Administration; FrA = Federal
railroad Administration; FTA = Federal Transit Administration; HPMS = Highway Performance Monitoring System; JTW = Journey to Work; MPO = metropolitan planning
organization; NHTS = National Household Travel Survey; NTD = National Transit Database; OTTI = Office of Travel & Tourism Industries; PIerS = Port Import export reporting
Service; STB = Surface Transportation Board; U.S. DOT = U.S. Department of Transportation; USACe = U.S. Army Corps of engineers.
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24 How We Travel: A Sustainable National Program for Travel Data
Within U.S. DOT, responsibility for the flagship surveys is divided: the
Federal Highway Administration (FHWA) is responsible for the NHTS and
the Bureau of Transportation Statistics (BTS) (with the Census Bureau)
for the CFS. When BTS was created as the federal statistical agency
for transportation by the Intermodal Surface Transportation Efficiency
Act of 1991, it was expected to develop a comprehensive set of transporta-
tion statistics, including data on travel, to support decision making on
broad transportation problems that crossed traditional modal boundaries
(see Appendix D).1 The new agency also was expected to work with the
operating administrations of U.S. DOT, which had their own modal data
programs, to help coordinate, harmonize, and modernize data collection
activities. Indeed, BTS restarted the CFS with the Census Bureau in 1993,
conducted the American Travel Survey on intercity passenger travel in
1995, and worked with FHWA to conduct and fund the NHTS.2 The agency,
however, has lacked the sustained leadership, resources, and staffing to
carry out its intended mission. Of the flagship surveys, BTS currently
retains responsibility only for the CFS, a responsibility it shares with the
Census Bureau.
In addition to the multimodal travel surveys, modal travel data are
collected by several of the operating administrations of U.S. DOT, as well
as other federal agencies that collect transportation information. For
example, FHWA and the Federal Transit Administration (FTA) collect
data on highway and transit travel, respectively. Responsibility for airline
travel data, which had been collected by the Civil Aeronautics Board before
deregulation, was transferred by Congress to U.S. DOT and assigned by
Secretarial order to BTS. The railroad industry reports data on rail freight
shipments to the Surface Transportation Board (STB), which replaced
the Interstate Commerce Commission in 1995 as part of the continuing
deregulation of the railroad industry. Finally, waterborne freight travel
data are provided by the U.S. Army Corps of Engineers (USACE). These
modal data sources can be quite comprehensive (e.g., the Origin and
Destination Survey of air travelers), and they often serve other purposes
(e.g., regulatory oversight) in addition to providing travel data.
States conduct substantial travel monitoring programs, collecting data
on traffic volumes and travel speeds, for a wide range of purposes, from
safety studies and congestion management to air quality analyses and
1. Intermodal Surface Transportation Efficiency Act of 1991, Public Law 102-240, 105 Stat. 1914 (1991).
2. The 2001 NHTS attempted to combine both short- and long-distance travel in a single survey. FHWA had
primary responsibility for the former, and BTS for the latter.
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Overview of Current Travel Data Programs and Gaps 25
evacuation planning. Some states also collect origin–destination data to
support statewide travel demand models. In some cases, states share the
cost of data collection with U.S. DOT—for example, for the NHTS. In fact,
as noted in Chapter 1, the willingness of numerous states (and a few
metropolitan planning organizations [MPOs]) to pay for larger samples
(add-ons to the national sample) prevented the most recent survey from
being canceled because of a lack of sufficient federal support. Similarly,
states and MPOs, working through the American Association of State
Highway and Transportation Officials (AASHTO) and the National Asso-
ciation of Regional Councils, support a small dedicated staff at FHWA,
AASHTO, and the Census Bureau to conduct special tabulations of the
Journey-to-Work data from the ACS for transportation users through the
Census Transportation Planning Products (CTPP) program. States also
collect travel data as required by U.S. DOT. The Highway Performance
Monitoring System is a good example; states collect and report data on
pavement condition, passenger and heavy-truck travel volumes, and other
roadway characteristics according to guidelines issued by FHWA. MPOs
in large metropolitan areas also conduct travel surveys periodically,
primarily to provide detailed data with which to calibrate and update
regional travel demand models.
Private firms also collect travel data for their own uses or to sell to other
private and public users for forecasting, planning, and operational purposes.
One of the best known and most widely used databases—TRANSEARCH—
was developed by Reebie Associates to provide timely and geographically
detailed data on freight movement. The company has been acquired by
IHS Global Insight, which continues to sell the data to private and public
clients. The Journal of Commerce, now a division of UBM Global Trade, has
collected data on foreign waterborne commerce for the Port Import Export
Reporting Service (PIERS) database for decades. This database has been
purchased by USACE so it can obtain detailed and timely data on water-
borne imports, exports, and in-transit freight traffic. Finally, D. K. Shifflet
& Associates (DSKA) collects annual data on travel within the United States
from a panel of U.S. households for private clients in the tourism industry
and public entities, such as state offices of economic development.
Appendix E provides a detailed description of the primary sources of
travel data in the United States, highlighting issues and gaps associated
specifically with each. Table 2-2 offers a high-level look at key character-
istics of a selected set of these programs and activities for which collecting
travel data is a major program focus.
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26 How We Travel: A Sustainable National Program for Travel Data
TABLE 2-2
Characteristics of Selected Travel Data Programs and
Data Collection Activities
Program and Data Cost and Staff
Collection Activity Category Support (FTEs) Frequency
Data Programs for Monitoring Passenger Travel
every 5–8 years
• 24 million ($21 mil-
$
Passenger,
National Household
lion, states and MPOs;
all modes
Travel Survey
$3 million, FHWA)
• 1 FTe FHWA +
2.5 FTe on-site
contractors
Journey to Work/ACS + Annual/continuous
• JTW part of much
Passenger,
larger annual
all modes
Census Transportation
$180 million ACS
Planning Products
• $5.9 million for
2007–2011 CTPP
(mainly by states and
MPOs through SP&r
and planning funds)
• 0.8 FTe FHWA, 1 FTe
AASHTO, 5 FTes CB
paid for by AASHTO/
MPOs
Annual; monthly
• 3.5 million designa-
$
Passenger,
National Transit Database
data on unlinked
tion from FTA grant
public transit
passenger trips
funds
are available
• 229,634 hours and
from urban
$3.4 million cost
transit properties
(estimates of transit
property data collec-
tion burden)
• 4.5 FTe FTA + 20 FTe
contractors
Monthly
• $1.7 million (last
Passenger,
Survey of International
manual survey in
all modes,
Air Travelers
2008); electronic
for travel
survey based on
within the
automated records
United States
being phased in
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Overview of Current Travel Data Programs and Gaps 27
Level of Geographic
Data Provider Content of Data Provided Specificity Status
National, limited coverage Uneven
• ravel characteristics
T
FHWA
of states and some large
(trip frequency, length,
metropolitan areas
time, and mode)
• Household and personal
data (household com-
position, income, age,
work characteristics)
• ehicle ownership and
V
use data
Stable
Traffic Analysis Zones and
• ode of transporta-
M
JTW: CB data; CTPP:
selected small areas
tion to work, time left
AASHTO, FHWA, CB
home, and travel time
• TPP provides special
C
tabulations and prod-
ucts for transportation
users
Stable
Data are reported by
• Financial and operat-
FTA and transit
urbanized area for urban
ing data and service
properties
transit properties and by
characteristics of transit
rural area for rural transit
agencies
• ravel data = passenger
properties
T
boardings and
passenger-miles
traveled
Stable
National and selected
• ravel to states and
T
OTTI/DOC
states
major U.S. destinations
by nationality of visitor,
use of transportation
facilities, mode of trans-
port within the United
States, group size, and
length of stay
• ocus on top 20 origin
F
countries
(continued on next page)
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TABLE 2-2
Characteristics of Selected Travel Data Programs and
Data Collection Activities (continued)
Program and Data Cost and Staff
Collection Activity Category Support (FTEs) Frequency
Annual on the
• No cost or staff
D. K. Shifflet & Associates Passenger,
basis of monthly
support data avail-
Survey System all modes
panel surveys
able; database is sold
by D. K. Shifflet &
Associates
Data Programs for Monitoring Freight Movement
every 5 years
• $24.5 million
Commodity Flow Survey Freight,
(80% BTS, 20% CB)
all modes
+ $1.8 million (BTS
additional analysis)
• .75 FTes BTS
3
9–10 FTes CB + 2
programmers and 2
statisticians
Monthly and
• 52,575 from BTS
$
North American Freight,
annual
to purchase 2010
TransBorder Freight all modes
transborder freight
Data Program
data from the CB;
reimbursed by FHWA
• .4 FTe BTS + 1 FTe
0
contractor support +
0.2 CB FTe
Annual
• 322,000 cost of
$
Carload Waybill Sample Freight, rail
confidential sample,
shared evenly
between STB and
FrA; public-use file is
available without cost
from STB
Annual
• 4,488,660 (2010
$
Waterborne Commerce Freight,
appropriation for
of the United States domestic
the Waterborne
and foreign
Commerce Statistics
waterborne
Project)
commerce
• 28 FTes at USACe
OCR for page 29
Level of Geographic
Data Provider Content of Data Provided Specificity Status
Stable
region, city, tourist
• raveler volume to loca-
T
D. K. Shifflet &
destination
tion by number of trips,
Associates
number of travelers,
length of stays
• ode of transportation
M
• urpose of stay and
P
travel activities
• isitor spending and
V
related demographic
data
Stable
National, state, and
Origin–destination,
BTS/CB
for now
selected large metro-
value, weight, mode
politan areas within
of transport, distance
states
transported, commodity
type and ton-miles of
commodities shipped
for domestic freight
Stable
Port of entry or exit, ex-
Commodity type, mode
BTS through contract
cept for commodity data
of transportation
with the CB
because of disclosure
(rail, truck, pipeline, air,
limitations; state of
and water), and port
origin for exports and
of entry/exit for U.S.
state of destination for
exports to and imports
imports
from Canada and
Mexico
Stable
economic areas, with
Origin and destina-
railroads terminating
≥4,500 carloads per
confidentiality restrictions
tion points, types of
commodities shipped,
year for 3 years in a
number of cars, tons,
row must report to
revenue, length of haul
STB; public-use file
is developed by
STB–FrA contractor
Stable
State and region for
• rigin and destination
O
Vessel operators of
domestic commerce;
by tons by commodity
record report to
U.S. ports
code for domestic
USACe for domestic
commerce, with con-
commerce; PIerS
fidentiality restrictions
database for foreign
• mports, exports,
I
commerce (pur-
and in-transit traffic
chased by USACe)
between the United
States, Puerto rico,
and the Virgin Islands
and any foreign county
for foreign waterborne
(continued on next page)
commerce
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30 How We Travel: A Sustainable National Program for Travel Data
TABLE 2-2
Characteristics of Selected Travel Data Programs and
Data Collection Activities (continued)
Program and Data Cost and Staff
Collection Activity Category Support (FTEs) Frequency
Annual
• No cost or staff sup-
TrANSeArCH Freight,
port data available;
all modes
database is sold by
IHS Global Insight
Monthly
• No cost or staff sup-
PIerS Freight,
port data available
waterborne
Data Programs for Monitoring Both Passenger Travel and Freight Movement
Monthly
• 300,000 annual
$
Air Carrier Traffic Statistics Passenger and
contractor cost
freight, air
• 0.5 BTS FTe
Annual
• 3,600 hours
9
Highway Performance Passenger
(estimate of state data
Monitoring System and freight,
collection burden;
highways
no monetary cost
provided, but states
generally use SP&r
or state funds for
data collection);
$400,000 FHWA
annual cost for sys-
tem development and
support
• 5 FTes FHWA
Note: AASHTO = American Association of State Highway and Transportation Officials;
ACS = American Community Survey; BTS = Bureau of Transportation Statistics; CB = Census Bureau;
CTPP = Census Transportation Planning Products; DOC = Department of Commerce; DOT =
department of transportation; FHWA = Federal Highway Administration; FrA = Federal railroad
Administration; FTA = Federal Transit Administration; FTe = full-time equivalent; JTW = Journey to
Work; MPO = metropolitan planning organization; OTTI = Office of Travel & Tourism; PIerS =
Port Import export reporting Service; SP&r = State Planning and research; STB = Surface
Transportation Board; USACe = U.S. Army Corps of engineers.
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Overview of Current Travel Data Programs and Gaps 31
Level of Geographic
Data Provider Content of Data Provided Specificity Status
Stable
National, state, economic
• Freight flows by county
IHS Global Insight
for now
Area, county, and some
origin and destination,
zip codes
four-digit commodity,
and transport mode
Stable
U.S. ports
• oreign imports and
F
UBM Global Trade
exports—tons,
commodity type,
and value
Stable
Airports, domestic and
• Point of origin, destina-
reports from cer-
international travel (i.e.,
tion, airline, class of
tificated air carriers in
between the United
service, and fare for air
scheduled domestic
States and a foreign
passengers
passenger service to
point); the latter are
• umber of passengers
N
BTS (Office of Airline
restricted for 6 months
and weight of cargo
Information); public-
after the report date
(mail and freight) by
use database is made
nonstop flight segment
available by BTS
and by market segment
or leg
Stable
Areawide summary infor-
• xtent, pavement
e
FHWA/state DOTs
mation by state, urban-
condition, performance,
ized, small urban, rural,
user, and operating
and air quality nonattain-
characteristics for all
ment and maintenance
federal-aid highways
• ravel data = average areas
T
annual daily traffic by
six vehicle classes
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34 How We Travel: A Sustainable National Program for Travel Data
lead and provided the necessary sustained funding to integrate and develop
these disparate data collection activities into a coherent national travel data
program to support policy and decision making. This role was envisioned
for BTS but has not been realized to date.
Major Gaps in Current Travel Data Programs
This section reviews the gaps in current travel data content; shortfalls in
the areas of data collection methods are examined in Chapter 3. Gaps in
both passenger and freight travel data have been enumerated in at least
two TRB special reports (TRB 2003a,b), in a host of data needs studies
(see Schofer et al. 2006 and Appendix C for an illustrative list), in recent
testimony on transportation research and data needs in congressional
hearings focused on reauthorization of surface transportation legislation
(see, for example, Pisarski 2009 and Skinner 2009), and by selected indi-
viduals who briefed the committee at its initial meetings (see Appendix B).
This section summarizes the main findings of these sources; the reader is
directed to the cited documents for more detail.
Passenger Travel Data
The greatest gap in data on passenger flows is at the national level
(Table 2-3). The NHTS captures household travel but covers mainly local
trips (i.e., less than 50 miles). A sufficiently large and comprehensive sample
of data on intercity passenger travel by surface modes (i.e., passenger
vehicle, rail,9 intercity bus) has not been collected since the 1995 American
Travel Survey (Pisarski 2009) was conducted.10 The private D. K. Shifflet
& Associates (DKSA) survey collects data on long-distance travel within the
United States for U.S. resident households, but the data are proprietary
and are licensed to clients with restrictions on disclosure (see Appendix E).
The absence of publicly available data on intercity passenger travel
by surface transportation modes is keenly felt in light of the renewed
interest in and new federal funding available for high-speed intercity rail
investments, and FHWA is patching together numerous data sources to
9. Amtrak provides limited data on passenger travel on its busiest corridors and ridership at its 25 busiest
stations (Amtrak Media Relations 2009).
10. Data on intercity air travel, by comparison, are collected consistently and reliably.
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Overview of Current Travel Data Programs and Gaps 35
TABLE 2-3
Key Gaps in Passenger and Freight Travel Data
Type of Data and
Geographic Level Passenger Travel Data Freight Travel Data
Limited data on inter- Poor data on inland origins
International
national travel to and destinations of freight
states and specific flows across borders
U.S. destinations
No recent publicly Absence of industry-based
National, interstate, state
available data on data on freight flows
intercity surface focused on supply chain
passenger travel linkages; incomplete indus-
(last survey in 1995);
try coverage; incomplete
no geographic flow coverage of motor carriers
data
Incomplete data on Few or no data on goods
Metropolitan area, local
household travel movement or commercial
in metropolitan/local traffic in metropolitan/local
areas areas
help fill the void.11 More generally, data on long-distance travel demand are
needed to ensure that surface transportation systems remain competitive
and are able to meet the needs of domestic and international business and
pleasure travel.
The NHTS provides good data on household travel, but here, too, the
data are incomplete. Fourteen states pay for larger sample sizes, but the
remaining states are limited by small sample sizes to state-level data
that include only basic information on household characteristics and
trip purpose (Contrino 2010).12 With only six MPOs paying for larger
sample sizes, moreover, reliable household data at the metropolitan area
level are very limited. Most larger MPOs conduct their own travel surveys
periodically, as noted previously, but these surveys are costly and conducted
infrequently, typically at 10-year or longer intervals, and are not sufficiently
11. As an interim measure, FHWA is developing a model of interregional passenger origins and destinations,
similar to the Freight Analysis Framework (FAF) for freight, that relies on extrapolating from existing
data (see Appendix E for a more complete description of the FAF). The effort will not involve a new
survey, and geographic detail will be limited to the 114 National Transportation Analysis Regions
(T. Tang, FHWA, personal communication, Feb. 9, 2010).
12. A minimum sample size of 250 households for each of the remaining states was deemed adequate by
the survey design team to provide reliable national results, but only limited state-level analyses can
be conducted.
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36 How We Travel: A Sustainable National Program for Travel Data
standardized for the data to be aggregated for state, regional, or national
analysis (Zmud 2009). Smaller MPOs rely mainly on the NHTS, but the
small sample sizes result in a paucity of useful detail.
More geographic detail on work trips is available from the ACS by
traffic analysis zones—the unit of analysis for travel demand models—and
selected small areas (e.g., census blocks). However, the move to more
timely continuous data collection with the ACS has resulted in smaller
annual sample sizes, greater variability of results, and data suppression to
meet disclosure limitations, threatening the availability of the finer-grained
geographic information on commuting trips needed for travel demand
modeling (Christopher 2009; Kominski 2009; Murakami 2009). The lack
of this level of detail limits analysis and evaluation of policies such as those
designed to encourage nonautomobile trip making and transit-oriented
development to reduce vehicle-miles traveled and carbon dioxide (CO2)
emissions at the regional or neighborhood level.
Data on international passenger travel are spotty. National-level data
on international air travelers are available from the U.S. Department of
Commerce (see Appendix E), but data on travel destinations within the
United States are less robust. BTS collects information on incoming
border crossings for vehicles, passengers, and pedestrians at land ports
on the U.S. border with Canada and Mexico using U.S. Customs and Border
Protection data, but this source includes no data on passenger travel within
the United States.
Freight Travel Data
In contrast to passenger travel data, freight travel data have critical gaps
that can be filled only with a reorientation in approach (see Table 2-3).
The CFS captures freight flows, although incompletely, at the national
level, and the privately provided TRANSEARCH database fills some of
the gaps in the CFS and includes more geographic detail on freight flows
(i.e., by state, county, Economic Area, and some zip codes). Nevertheless,
national data on freight flows are not well aligned with the supply chain
orientation of industry and shippers. Data connecting freight shipments
from origin, to intermediate handling and warehousing locations, to final
destination are critical to understanding what businesses ship, why, and
where, but these data are poorly covered by the CFS. Industry coverage in
the CFS, for example, is limited to those shipper establishments surveyed
by the Census Bureau, and survey data on shipment coverage are becoming
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Overview of Current Travel Data Programs and Gaps 37
more unreliable as third-party logistics firms rather than surveyed estab-
lishments increasingly manage freight shipment mode and routing patterns
(TRB 2003a,b). Adequate representation of shipments by motor carrier—
the predominant freight mode—is a significant gap (TRB 2003b).13 Thus,
decision makers are left with a poor understanding of the economic
impacts of logistics choices on state and regional economies and of the
critical investments necessary to support such activities.
Another major gap is at the metropolitan and local-area levels: virtually
no data exist on freight operations flows at the intraregional level, par-
ticularly for urban goods movement—a long-standing gap in freight data
(see Table 2-3).14 Few MPOs conduct local freight surveys, and without
these data, MPOs and local governments lack important information for
modeling freight movements and planning freight corridor improvements
or other infrastructure investments to support major freight facilities
(e.g., improvements to port access) (Skinner 2009).15
International data on freight flows, particularly reliable origin and
destination data for imports and exports, are also incomplete—a major gap
in view of the increasing globalization of the economy. Data on the inland
destinations of freight movements are particularly important for ensuring
adequate investment in major freight facilities (e.g., ports, warehouses,
intermodal terminals) and infrastructure access. The North American
Transborder Freight Database fills part of the gap for freight flows
between the United States and Canada and between the United States and
Mexico. This database, however, is not intended to capture transportation
data on all foreign freight flows, nor does it accurately reflect the physical
destinations of many imported commodities.
Finally, with some exceptions, existing data on freight flows do not
encompass the performance of the transportation system in terms of
transport travel times, shipment costs, or other performance-related
13. According to the 2007 CFS, trucks account for 71 percent of the total value and 40 percent of the ton-miles
of shipments (Margreta et al. 2009), and forecasts derived from the FAF indicate that trucking is one of
the fastest-growing freight modes (FHWA 2009). The FAF estimates missing components of flows
among CFS regions and provides annual provisional updates from a variety of data sources and models.
14. In a white paper, Bronzini (2008) notes the difficulties of obtaining good data on urban goods movement,
including data on commercial vehicle travel as well as heavy-truck freight movements, either in-transit
through metropolitan areas or for local deliveries.
15. In the absence of local truck surveys, many MPOs rely on trip tables that estimate truck trips by traffic
analysis zones on the basis of establishment type, size, and location. Trip rates are often based on default
values from national studies. Growing evidence suggests, however, that truck trip generation does not
correlate well with employment (A. Bassok, Puget Sound Regional Council, personal communication,
May 21, 2010).
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38 How We Travel: A Sustainable National Program for Travel Data
factors.16 Together with the gaps in understanding freight origins and
destinations, this lack of data on the performance on the network hampers
states that are contemplating making multimillion dollar capacity or facility
investments to grow their share of trade and economic development and
reduce truck congestion. Without these data, they cannot adequately
analyze modal alternatives, such as investing in a parallel rail line rather
than in highway capacity expansion, nor can they fully understand the
consequences of different investment alternatives for total traffic as well
as air quality and CO2 emissions.
Crosscutting Issues
Data needs to support decisions about transportation policies, investments,
and operations go beyond flows of people and goods to encompass the
availability and service characteristics of competing travel options,
the physical and economic context for travel, and the characteristics of
people and goods traveling and of passengers and firms making travel
choices. These needs cut across both passenger and freight travel data.
They include the following:
• Transportation service and cost measures—No data source provides
detailed measures of transportation services and their costs for particular
trips or movements, nor is there easy access to linked data describing
the travel options that were available. Without such supply-side data
on service quality and costs, it is impossible to understand the decision
behaviors of travelers and shippers. While MPOs normally collect
both supply and demand data to support the development of regional
models, the development and application of policy analysis tools for
higher-level state, corridor, and national studies are not feasible because
these data are not available in a standardized format that enables them
to be integrated and aggregated for the analysis.
• System reliability—Very limited data are collected on the reliability of
passenger or freight services, a critical element of service quality. The
exceptions are on-time performance statistics for passenger air travel
and selected performance data on heavy-duty vehicle freight travel
16. The FHWA–American Transportation Research Institute Freight Performance Measurement (FPM)
Initiative, described in Chapter 3, collects data on heavy-truck travel times at key international border
crossings and motor vehicle travel speeds on major freight highway corridors.
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Overview of Current Travel Data Programs and Gaps 39
and on rail travel by Amtrak.17 Reliability data are critical to ensuring
efficient freight movement, particularly with just-in-time delivery
systems. For highway passenger travel, data on congestion are critical,
particularly for commuting trips, given congestion’s adverse effects on
personal travel time, fuel use, and emissions. And the unreliability of
transit is frequently cited as one of many impediments to greater transit
use (Krizek and El-Geneidy 2006).18
• Travel behavior—Considerable amounts of data are collected on travel
movements, mode of transport, and even trip purpose. However, far
less attention has been given to understanding what motivates travel
for both individuals and firms. This understanding is important
not only for designing and evaluating policies that involve changing
travel behavior (e.g., travel demand management measures), but also
for more basic purposes, such as designing travel surveys and other
data collection activities. For example, one of the difficulties of using
the establishment-based CFS to obtain freight travel data is a change in
the underlying logistics patterns and supply chain orientation that has
rendered shipper-based surveys on freight movements increasingly
less reliable. On both the passenger and freight sides, a better grasp
of trip chaining or tours19 that included all modes would improve
understanding of total trips and potential impediments to efforts to
change travel behavior.
• Impacts of travel—Increasingly, transportation and travel are coming
under scrutiny for their wide-ranging impacts on economic productivity;
economic opportunity; the environment; and equity in the allocation of
resources, services, and costs. Box 1-2 in Chapter 1 provides examples
of many of the gaps in understanding the impacts of travel.
• Linkages to contextual data—The context for travel—nearby land use,
activity densities, and availability of facilities that support nonmotorized
travel—is an important influence on many key travel choices, such as
17. BTS collects data from 18 major air carriers and one voluntary reporting carrier on on-time and delay
data for the Airline Service Quality Program (BTS 2010). The FHWA–ATRI FPM Initiative gathers
data on the reliability of a sample of over-the-road trucks on major freight corridors. Amtrak provides
information on on-time performance and primary causes of delay (last 12 months) for a selected group of
major corridors (see “Historical On-Time Performance” on the Amtrak website).
18. Availability, frequency, and travel times are other impediments to greater transit use.
19. These terms refer to trips with multiple stops, such as stopping at the grocery store and the cleaners on
the way from work to home, or truck stops at multiple store locations to complete food or other deliveries.
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40 How We Travel: A Sustainable National Program for Travel Data
the decision to make a trip, the selection of mode, and the choice
of route. Travel data, however, are poorly linked to contextual data.
For example, travel data on transit use, bicycling, and walking are
collected, but data on access to work or other destinations using any
of these modes (e.g., destinations reachable by walking, distance to
the closest rail or bus stop) are not gathered for any large-scale surveys.
Similarly, data on land use patterns, particularly higher-density
development, mixing of land uses, and high-quality transit service—
characteristics that are thought to encourage reductions in automo-
bile use and more livable communities—are seldom linked to data
on personal travel to provide the information needed to probe these
relationships.20
• Geographic specificity—Geocoding of travel data is important for linking
separate data sets to understand the relationships between travel and
contextual factors and to construct models for policy evaluation.21
Geocoding also supports map-based analysis and display of data, an
important way to visualize and understand travel patterns. At the
national level, the Freight Analysis Framework has been instrumental
in visualizing freight flows and identifying major interstate freight cor-
ridors as a first step in examining capacity issues. At the local level,
more MPOs are geocoding the data collected in local travel surveys to
better understand trip generators (e.g., shopping malls, office parks)
and travel patterns. Geographic information systems have been avail-
able for decades, enabling data to be linked with geographic locations,
but their application, particularly at the state and local levels, is uneven.
• Timeliness—The relative infrequency of data collection—at least
5 years between the flagship passenger and freight travel surveys—
and the length of time required to process and release survey results
(up to 2 years for the CFS) make it difficult to track trends and may
20. Some limited linked data are available at the national level. FHWA purchased data on neighborhood
and workplace location characteristics from Claritus, a private company, for use with the NHTS. The
Claritus data were tagged to individual addresses of the NHTS respondents, so that at a national level,
questions such as whether higher-density locations result in shorter home or work trips could be
explored (H. Contrino, FHWA, personal communication, May 24, 2010).
21. Geocoding refers to the process of identifying associated geographic coordinates from other geographic
data, such as street addresses or zip codes. With such coordinates, the data can be mapped and entered
into geographic information systems.
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Overview of Current Travel Data Programs and Gaps 41
result in an unrepresentative picture of travel patterns. For example,
the NHTS was conducted during 2008 and 2009 when the nation was
in a deep recession and travel was depressed, and the next survey will
not be conducted before 2014, if then. Personal travel patterns are
likely to remain relatively stable from year to year; with the excep-
tion of recessionary periods, however, such infrequent cross-sectional
“snapshots” provide an inadequate picture of travel trends. The lag in
reporting of results from the CFS and its relative infrequency are more
problematic still for users because of more rapid changes in freight
patterns. For both surveys, analysis of travel and trip-making trends
over time, including the stability of travel patterns, could help deter-
mine how often these data should be collected.
Findings
This chapter and the related Appendix E examine current major travel
data programs—who administers them; what data are collected and at
what level of geographic specificity; how frequently key surveys or other
data collection activities are conducted; and, for many data sources, at
what cost and with what level of staff support. They also provide an
assessment of shortfalls in travel data, identifying gaps in data content.
The picture of travel data programs that emerges can best be described as
uneven, incomplete, and poorly integrated.
In particular, individual programs suffer from a lack of integrated,
strategic management. The federal government, through U.S. DOT and
the Census Bureau, plays a key role in the conduct of important travel
surveys and other data collection activities for both passenger and freight
travel. But no one office—presumably at U.S. DOT—has assumed the
necessary leadership to integrate these surveys into a coherent national
data program to support policy analysis and decision making. Moreover,
travel data programs often are funded modestly and inconsistently.
The lack of sustained funding for core programs affects the frequency,
sample sizes, level of geographic detail, and scale of data collection, as
well as the extent of data analysis and dissemination to users and research
on new data collection methods. In the next chapter, opportunities for
new approaches to collecting travel data to alleviate some of these
problems are explored.
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42 How We Travel: A Sustainable National Program for Travel Data
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Abbreviations
BTS Bureau of Transportation Statistics
FHWA Federal Highway Administration
RITA Research and Innovative Technology Administration
TRB Transportation Research Board
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