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

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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  

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). 

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. 

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. 

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. 

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 

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) 

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 

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 

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. 

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 

32  How We Travel: A Sustainable National Program for Travel Data Costs of Travel Data Collection The annual costs of collecting travel data, borne primarily by the federal government, can be estimated from the information provided in Table 2-2. The table also shows staffing levels, in terms of full-time equivalents (FTEs), for some travel data programs. The two flagship multimodal surveys—the NHTS and the CFS—represent the single largest federal expenditure on travel data—nearly $50 million every 5 years or so, or about $10 million per year were the survey costs to be spread out over several years. The CTPP plus the other federal modal data programs cost about another $20 million annually, for a total annual cost of about $30 million.3 The focus of several of these programs extends beyond the collection of travel data, so it is difficult to apportion the costs. In addition, many of the costs are unknown, particularly for private travel data providers. Furthermore, the estimates, for the most part, do not include the costs of travel data collected at the state and local levels, which can be significant.4 The annual costs for household travel data collection by large MPOs, for example, have been projected at more than $200 million.5 Nevertheless, even if these esti- mates were increased by an order of magnitude, current spending on travel data programs would still represent a tiny fraction of total expenditures for transportation. In 2007, for example, federal, state, and local public expen- ditures on transportation totaled $221.7 billion,6 and U.S. transportation- related goods and services totaled $1.38 trillion in 2008 (RITA 2010).7 Funding continuity is perhaps even more important than the total expenditures each year for travel data collection. Chapter 1 recounts the 3. Annual costs were estimated as follows: $1.18 million for CTPP; $0.53 million for North American Trans- portation Border Freight Data; $7.42 million for HPMS ($0.4 million FHWA plus 93,600 hours × $75/hr fully loaded, or $7.02 million state); $6.9 million for the National Transit Database ($3.5 million FTA plus $3.4 million transit properties); $0.322 million for the rail Carload Waybill Sample; $0.3 million for the Air Carrier Traffic Statistics; and $4.5 million for Waterborne Commerce Statistics (see Table 2-2). 4. The exceptions are the estimated costs of data collected by the states and transit properties for FHWA (HPMS) and FTA (National Transit Database [NTD]), respectively, as well as the costs of the state and MPO add-ons to the NHTS. 5. A recent estimate of annual data costs for MPOs with better-than-average data collection and modeling programs, for example, indicated that a total of as much as $210–225 million would be required if all MPOs were to adopt these capabilities (Burbank 2009 in TRB 2009). Of course, these estimates cover activities beyond the collection of travel data. 6. Federal expenditures include direct federal spending, excluding grants to state and local governments (RITA 2010, Table 5-12). State and local expenditures encompass outlays from all funding sources, including federal grants. State and local expenditures for rail and pipeline, however, include outlays funded only by federal grants. Local government outlays for highway were not included in 2007 because of a lack of data. 7. Transportation-related goods and services accounted for 9.5 percent of gross domestic product in 2008 (RITA 2010, Table 5-1). Goods and services include all consumer and government purchases of goods (e.g., vehicles and fuel), services (e.g., auto insurance), and exports related to transportation. 

Overview of Current Travel Data Programs and Gaps  33  abrupt termination of the Vehicle Inventory and Use Survey for budgetary reasons and the threat to the 2009 NHTS resulting from the withdrawal of BTS support. Although FHWA reassumed full responsibility for the NHTS, the federal contribution—$3 million out of $24 million—was a tiny fraction of the total cost; the bulk of the funding was provided by state and MPO add-ons. Moreover, the uneven cycle of the NHTS—1990, 1995, 2001, 2009—attests to the difficulty of conducting a survey that depends on a “pass-the-hat” approach to funding. The CFS is conducted on a more regular cycle because it is tied to the 5-year economic survey administered by the Census Bureau. Since it was first conducted in 1993, however, the CFS has been subject to large reductions in sample size to address resource constraints. Because of budget constraints, for example, only 50,000 establishments were sampled in 2002—down from 100,000 in 1997 and 200,000 in 1993—severely limiting the usefulness of the data (Kriger et al. 2010). The sample was restored to 100,000 establishments in the most recent 2007 CFS. Unpredictable funding also takes its toll on staffing and partnering arrangements. Currently, only 1 FTE at FHWA supports the NHTS with the help of 2.5 FTE on-site contractors, while the CFS has many times that number, particularly at the Census Bureau because of the survey’s ties to the economic census (see Table 2-2). Even when strong user support and cost sharing exist, as was the case with the 2009 NHTS, the lack of a sustained federal funding source makes it difficult to retain and develop experienced data program staff and, for even the most supportive funding partners, to plan and budget for their share of the cost. Sustained funding appears to be easier to secure when a data program is required by statute, which is the case for many of the modal databases (e.g., the National Transit Database [NTD], the rail Carload Waybill Sample, the Waterborne Commerce Statistics).8 Summary The picture that emerges from this brief overview of current travel data programs is the number of agencies involved in travel data collection and the general lack of coordination among them. U.S. DOT has not taken the 8. The NTD, for example, is funded by an annual designation of FTA grant funds for data collection. Rail data collection (the Carload Waybill Sample) is funded jointly by the Federal Railroad Administration and the STB to meet regulatory requirements. Funding for collection of the Waterborne Commerce Statistics is provided through annual appropriations to the Navigation Data Center of USACE (see Appendix E for more detail). 

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. 

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. 

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 

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). 

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. 

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. 

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. 

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. 

42  How We Travel: A Sustainable National Program for Travel Data References Abbreviations BTS Bureau of Transportation Statistics FHWA Federal Highway Administration RITA Research and Innovative Technology Administration TRB Transportation Research Board Amtrak Media Relations. 2009. National Fact Sheet: FY 2009. http://www.amtrak. com. Accessed Sept. 27, 2010. Bronzini, M. S. 2008. Relationships Between Land Use and Freight and Commer- cial Truck Traffic in Metropolitan Areas. Prepared for TRB Special Report 298: Driving and the Built Environment: The Effects of Compact Development on Motorized Travel, Energy Use, and CO2 Emissions, George Mason University, Oct. 22. http://onlinepubs.trb.org/onlinepubs/sr/sr298bronzini.pdf BTS. 2010. Significant Accomplishments, Fiscal Year 2009. Research and Innovative Technology Administration, Washington, D.C. Burbank, C. J. 2009. Greenhouse Gas (GHG) and Energy Mitigation for the Trans- portation Sector: Recommended Research and Evaluation Program. Prepared for TRB Special Report 299: A Transportation Research Program for Mitigating and Adapting to Climate Change and Conserving Energy, Parsons Brinckerhoff, Inc., Oct. 29. http://onlinepubs.trb.org/onlinepubs/sr/sr299GHG.pdf Christopher, E. 2009. Census Data for Transportation Planning. FHWA, Washington, D.C. Briefing presented to the Committee on Strategies for Improved Passenger and Freight Travel Data, Washington, D.C., Dec. 10. Contrino, H. 2010. The National Household Travel Survey. FHWA, Washington, D.C. Presentation to a stakeholder meeting at the American Automobile Association, Washington, D.C., Feb. 25. FHWA. 2009. Freight Facts and Figures 2009. FHWA-HOP-10-007. U.S. Department of Transportation, Washington, D.C., November. Kominski, R. 2009. Commuting and the American Community Survey (ACS). The U.S. Bureau of the Census, Suitland, MD. Briefing presented to the Committee on Strategies for Improved Passenger and Freight Travel Data, Washington, D.C., Dec. 10. Kriger, D., M. McCumber, A. Clavelle, B. Gan, and T. Chow. 2010. Freight Transpor- tation Surveys—Existing Methods and Guidelines. Prepared for NCHRP Project No. 20-05, Synthesis Topic 40-09, HDR/iTRANS, Ottawa, Ont., Canada, August. Krizek, K. J., and A. M. El-Geneidy. 2006. Better Understanding the Potential Market of Metro Transit’s Ridership and Services. Final Report. Center for Transportation Studies, Minneapolis, Minn., October. Margreta, M., C. Ford, and M. A. Dipo. 2009. Special Report: U.S. Freight on the Move: Highlights from the 2007 Commodity Flow Survey Preliminary Data. SR-018. The Research and Innovative Technology Administration, U.S. Department of Transportation, Washington, D.C., September. 

Overview of Current Travel Data Programs and Gaps  43  McNeil, S. 2009. Adaptation Research Programs and Funding. Prepared for TRB Special Report 299: A Transportation Research Program for Mitigating and Adapting to Climate Change and Conserving Energy. University of Delaware, October. http://onlinepubs.trb.org/onlinepubs/sr/SR299Adaptation.pdf. Murakami, E. 2009. Census Transportation Planning Products. FHWA, Seattle, Wash. Briefing presented to the Committee on Strategies for Improved Pas- senger and Freight Travel Data, Washington, D.C., Dec. 10. Pisarski, A. E. 2009. Testimony on Research and Development to Support the Department of Transportation’s Strategic Goals. Submitted to the Subcommittee on Technology and Innovation of the House Committee on Science and Tech- nology, U.S. House of Representatives, Washington, D.C., Nov. 19. RITA. 2010. Pocket Guide to Transportation 2010. U.S. Department of Transportation, Jan. http://www.bts.gov/publications/pocket_guide_to_transportation/2010/. Accessed March 18, 2010. Schofer, J. L., T. J. Lomax, T. M. Palmerlee, and J. P. Zmud. 2006. Transportation Research Circular E-C109: Transportation Information Assets and Impacts: An Assessment of Needs. Transportation Research Board of the National Academies, Washington, D.C., December. http://onlinepubs.trb.org/onlinepubs/circulars/ ec109.pdf. Skinner, R. E., Jr. 2009. Testimony on Research and Development to Support the Department of Transportation’s Strategic Goals. Submitted to the Subcommittee on Technology and Innovation of the House Committee on Science and Tech- nology, U.S. House of Representatives, Nov. 19. TRB. 2003a. Special Report 276: A Concept for a National Freight Data Program. Transportation Research Board of the National Academies, Washington, D.C. http://onlinepubs.trb.org/onlinepubs/sr/sr276.pdf. TRB. 2003b. Special Report 277: Measuring Personal Travel and Goods Movement: A Review of the Bureau of Transportation Statistics’ Surveys. Transportation Research Board of the National Academies, Washington, D.C. http://onlinepubs. trb.org/onlinepubs/sr/sr277.pdf. Zmud, J. 2009. Metropolitan Planning Organizations, Travel Surveys: View from the Trenches. NuStats, LLC, Austin, Tex. Briefing presented to the Committee on Strategies for Improved Passenger and Freight Travel Data, Washington, D.C., Dec. 11.