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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
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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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