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The Need for Freight Transportation Data
More than 6 million business establishments in the United States rely on the nation’s transportation system to engage in local and interstate commerce and international trade (BTS 1998). In 1999, the nation’s freight transportation bill was $562 billion—approximately 6 percent of gross domestic product (Wilson 2001). The effective and efficient movement of freight is critical to the nation’s economy and must be assured in the face of changing circumstances, such as an increased emphasis on global markets, shifts in domestic economic activity to the suburbs and suburban malls, new transportation patterns for improved logistics efficiency, growing congestion on the nation’s roads, heightened concerns about transportation security and capacity, and increased maintenance requirements associated with the aging U.S. transportation network.1
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A more detailed discussion of trends affecting freight movements is provided in a series of working papers on the changing nature of freight demand, carrier operations and infrastructure, and public policy, prepared for the Federal Highway Administration’s Office of Freight Management and Operations (www.ops.fhwa.dot.gov/freight/theme_papers/theme_paper_index.htm). |
While the focus of this report is on freight transportation and associated data needs, it is important to remember that freight activity and passenger travel both affect the demand for transportation facilities and services. Since most major freight nodes (ports, airports, and railheads) and the origins and destinations of most shipments are in cities, freight must compete with passenger traffic for the use of transportation facilities (TRB 2003). Thus, limitations imposed by the transportation infrastructure affect the movement of both goods and people. For example, road congestion around New York’s John F. Kennedy Airport is making access difficult for cars carrying passengers and for trucks carrying freight.
Changes in the transportation infrastructure and related operations cannot be made without influencing the complex transportation network as a whole and all its users. For example, efforts to alleviate highway congestion are likely to benefit passengers as well as freight. Conversely, attempts to accelerate the flow of trucks carrying freight on the highway without affecting passenger traffic would appear problematic. Despite this interrelationship between freight and passenger movements, transportation-related problems affecting passengers (e.g., delays due to congestion) may attract more attention than problems affecting freight because “parcels cannot talk.”
One consequence of the focus on passenger needs—and complaints—is a lack of widely available data to inform decisions about freight transportation issues. For example, analysis of the effectiveness and costs of alternative options for mitigating congestion in urban areas requires better data on patterns of freight movements. Metropolitan planning organizations typically have detailed origin–destination data on commuting patterns by industry and occupation from the Census Bureau’s journey-to-work data. However, data on truck movements in metropolitan areas are often scant and lack details of trip origins and destinations and the industry/commodity breakdown for products being carried. Furthermore, many of the existing metropolitan data on truck movements miss delivery of business products and services by car, van, and light-delivery vehicle (Weisbrod et al. 2001). Another important gap is the lack of shipment weight data for U.S. exports by land modes of transportation (truck, rail, pipeline, and mail). This deficiency hampers efforts to estimate and forecast the impact of international
trade on domestic transportation infrastructure—efforts that are critically dependent on accurate shipment weight data (BTS 2002).
CHARGE TO THE COMMITTEE
In November 2001, the New York State Department of Transportation and the Transportation Research Board (TRB) convened a conference in Saratoga Springs, New York, to address data needs in the changing world of logistics and freight transportation. The main conference objective was to provide transportation officials concerned about the economic competitiveness of their regions with a broader understanding of data issues associated with the changing focus of the global competitive market and accompanying implications for the existing transportation infrastructure, trade corridors, and markets (Meyburg and Mbwana 2002). At the conclusion of the conference, participants agreed on a major action item—to develop a strategic freight data business plan to guide future data collection efforts. They proposed that the plan identify all freight data users and their needs. On the basis of these needs, a national or international freight data framework would be developed.
After the Saratoga Springs conference, the Bureau of Transportation Statistics asked TRB to conduct a study to recommend a framework for the development of national freight data. The framework was to identify
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The data requirements for the various users of freight data (public, including various levels of government, and private); and
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Appropriate federal, state, and private-sector roles in the development and dissemination of freight data.
The framework was to be conceptual in nature and not a detailed data collection plan. Instead, it would articulate the types of freight data needed by the variety of users in transportation and the roles of different data providers.
The findings and recommendations of the study committee are presented at the outset of this report. In the remainder of Chapter 1, needs for freight transportation data are identified, and examples of policy and investment decisions and associated data requirements are provided. In
Chapter 2 an overview of existing freight transportation data is provided, and some of their limitations for the purposes of transportation analysis are identified. The conceptual model for a national freight data program, which was developed through extensive interactions between the committee and its consultant, Rick Donnelly, is discussed in Chapter 3. Dr. Donnelly’s commissioned paper, A Freight Data Business Plan, is presented in Appendix A.
WHY DATA ARE NEEDED
Although the public and private sectors have a different focus, their requirements for reliable, high-quality data are similar. Such data allow investment decisions—many of which may be long-lived—to be taken in the knowledge that alternative strategies have been developed and compared on the basis of reliable information.
Reliable data on the movement of freight are needed to inform public policy decisions on issues such as congestion mitigation, transportation security, air quality improvement, economic development, and land use. Many of these decisions are more difficult today than they would have been 20 years ago. There are fewer opportunities to add capacity to the transportation system, and the need to meet environmental and other social goals often results in delays and increased project costs. Consequently, optimizing modal and intermodal choices requires much better information about the freight transportation system to evaluate the advantages and disadvantages of a limited number of expensive options. A recent report notes that infrastructure projects costing from $100 million to several billion dollars are becoming more common, especially in urban areas (TRB 2003).
Reliable, high-quality freight transportation data are also needed by the private sector to inform a range of strategic investment decisions relating to topics such as equipment utilization, new market opportunities, and business relocation. For example, information on the movements of empty shipping containers and railroad cars could assist freight carriers in identifying opportunities to reduce unprofitable movements of empty equipment. The associated improvements in operational efficiency could allow lower pricing of freight transportation services and increase the potential for economic growth.
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Box 1-1 Major Reasons for Needing Freight Data
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Within the broad context of policy making and investment decisions, the committee identified 11 major reasons for needing freight data (Box 1-1). Some of these reasons are related; for example, reduced fuel consumption is likely to result in reduced incremental operating costs. While these reasons are intended to be illustrative rather than exhaustive, the related examples and case histories presented in the remainder of this chapter reflect the diverse and wide-ranging social and economic impacts of freight transportation.
EXAMPLES AND CASE HISTORIES
Promote Transportation Efficiency and Mitigate Congestion
Efforts to improve transportation efficiency require data to identify problem areas and to evaluate proposed improvements. For example, Metroplan Orlando recently developed its Freight, Goods and Services
Mobility Strategy Plan to identify and address concerns about the movement of freight, goods, and services in the Orlando Urbanized Area in central Florida (Metroplan Orlando 2002). One of the key underpinnings of the plan was a data set describing freight traffic movements to, from, and through the area. The development of this data set constituted an important part of the entire effort and required considerable specialized technical expertise.
A review of the National Highway System (NHS) freight connectors also required considerable effort to obtain the necessary data (U.S. Department of Transportation 2000). These connectors are public roads linking the NHS to seaports, airports, and major intermodal terminals, and are therefore vital to the national intermodal freight system. However, because the connectors are frequently local, county, or city streets that cannot accommodate high volumes of heavy truck traffic, they can be major bottlenecks. Identification of major connectors required data on the level of activity of a terminal and its importance to a particular state. The participation of national associations, state departments of transportation, metropolitan planning associations, terminal operators, and the staff of the U.S. Department of Transportation modal administrations was needed to obtain the necessary information.
Data issues encountered in implementing a regional transportation plan for Portland, Oregon, are discussed in Box 1-2.
Local problems, such as bottlenecks at a hub airport or rail center during peak periods, can have a severe impact on airline or railroad transportation networks, can quickly spread hundreds or thousands of miles from their source, and can be costly for operators (TRB 2003). For example, if a cargo plane misses its landing slot and the associated distribution bank of flights, the operator may need to charter another aircraft in an effort to deliver goods on time.2 Aggregate data from national freight data sets may not be sufficiently detailed to reveal such local capacity constraints. Instead, they may simply indicate that an average link is operating below capacity over an average time period. The lack of geographic detail in many current data sets is particularly damaging to decisions made at the metropolitan and county levels, where the
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Box 1-2 Improved Freight Mobility Around Portland, Oregon Portland, Oregon, has developed a regional transportation plan, which includes a freight network. As part of the plan implementation, projects to improve freight mobility into, around, and through the region are being solicited. However, the lack of relevant data will impede assessment of the potential merits of different projects and associated funding decisions. Although the volume of trucks on any particular route is known, available data do not provide satisfactory information on where these trucks are going, what goods they are carrying, whether the shipments are part of a series of intermodal moves, or the extent to which timely delivery of the goods affects just-in-time production schedules. |
bottlenecks and greatest congestion delay costs occur. Because most of the available data concerning freight flow are at the state level, decision makers do not have the information they require to identify specific freight demands on metropolitan and county infrastructure or evaluate the relative merits of proposed improvements. Difficulties are also encountered in obtaining data for metropolitan areas that extend across state boundaries, rather than being located within a single state.
The need for better data to inform decisions about options for mitigating congestion on the Upper Mississippi River–Illinois Waterway is discussed in Box 1-3.
Improve Regional and Global Economic Competitiveness
Accurate freight data are needed to support investment decisions aimed at improving regional and global economic competitiveness. The example of the Northeast North American Free Trade Agreement (NAFTA) corridor is discussed in Box 1-4. Such data could also provide insights into opportunities for supply chain efficiencies and possible business relocation.
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Box 1-3 Upper Mississippi River Locks The U.S. Army Corps of Engineers recently conducted a study evaluating proposals for improvements to locks and other navigation facilities on the Upper Mississippi River–Illinois Waterway. The purpose of these improvements is to relieve increasing waterway congestion, particularly for grain being transported to New Orleans for export. During a 300-hour trip from the Upper Midwest to New Orleans, a barge may typically experience 30 hours of congestion-induced delay. The study proved controversial, and a National Academies committee was asked to review the methods used. This committee identified one of the problem areas as a lack of adequate data for forecasting future levels of barge traffic across the entire navigation system. Without such data, the potential benefits of proposed improvements to locks and other navigation facilities cannot be assessed satisfactorily. The committee recommended that the corps obtain a database of grain and other relevant freight shipments by barge and alternative modes that includes quantity, origin and destination, and price. The committee suggested that such data take account of seasonal effects and that grain flow surveys seek information from both barge terminal operators and grain shippers. Sources: NRC 2001; TRB 2003. |
For example, better freight data could reveal the effect of improved information technology on the location of production in the United States. Measuring which commodities have been affected most strongly by changes in information technology and observing how commodity flows have changed for these commodities would yield an understanding of the effects. This understanding could be used to help identify opportunities for further efficiencies.
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Box 1-4 NAFTA Corridors The New York State Department of Transportation is seeking to identify freight transportation improvements that could result in better linking of NAFTA shipments, thereby making the Northeast transportation network a more effective contributor to the NAFTA corridors. The Northeast states require accurate strategic freight shipping data (origin and destination, commodity, mode of transport, route, etc.) to understand the role of the Montreal–Boston–New York–Washington corridor vis-à-vis competing routings. At the national level, such data would help inform national transportation policies on NAFTA corridors and allow an objective assessment of related funding requirements. Source: Boardman 2002. |
Enable Effective Land Use Planning
In some urban areas, there may be opportunities to improve the transportation system through effective land use planning. Possible strategies include the relocation or consolidation of rail terminals and track, the use of brownfields and other vacant lands as freight centers, and the improvement of access to intermodal terminals. For example, the Baltimore Regional Rail Corridor Study is considering the possibility of building a new rail route to free up old railroad tunnels and other rights-of-way in congested areas. These existing corridors could then be used for commuter rail or light rail service. However, planners need good data on freight movements into, out of, and through the area of interest, including route structures and use, to identify promising options and likely outcomes. In another example, the New Jersey Transportation Planning Authority is planning to reclaim abandoned industrial brownfield sites near northern New Jersey ports, airports, and rail terminals for the development of a “freight village” (Meyer 2001). Again, effective planning
of these freight- and trade-related distribution facilities will require comprehensive and reliable data on freight movements.
Inform Decisions About Modal Optimization
Improved freight data would help in identifying opportunities to substitute rail for truck transportation and vice versa. Currently, much of the information on freight flows does not provide enough detail on commodities or on specific routes to allow planners to understand when one mode can substitute for the other and when the two modes complement each other. Thus, state secretaries of transportation do not have the information they need to make good decisions about investing limited capital in more highway lanes or more rail capacity. More detailed geographic and commodity data would help transportation planners and marketing experts conduct better analyses to identify promising opportunities for modal diversion. The example of the I-81 corridor in Virginia is presented in Box 1-5.3
Enhance Transportation Safety and Security
Information on vehicle weight is important for many transportation planning applications and is even more useful if it can be linked to route data. Many traffic data collection systems count numbers of vehicles passing fixed points on the highway system but do not distinguish between passenger vehicles and trucks. Highway investments are often based on vehicle counts because data on vehicle type and weight needed to provide a more informative picture of road use are not available. Infrastructure projects may be adversely affected if engineers have to design pavements without the benefit of reliable estimates of loads over the expected life of the structure. Since pavement damage increases rapidly with increasing axle weight,4 the vehicle mix has an im-
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Box 1-5 Expanding Capacity on the I-81 Corridor in Virginia I-81, an Interstate highway running through Virginia, is a major truck route. The state has a plan for several billion dollars in highway improvements over the next 20 years to accommodate expected traffic growth on I-81, notably in truck traffic. Norfolk Southern Corporation proposed to the state of Virginia that it consider public investment in improvements to the company’s Shenandoah rail corridor as an alternative to widening I-81. As a result, the Virginia state legislature instructed the Virginia Department of Transportation to study the feasibility of shifting traffic in the I-81 corridor from highway to rail. Extensive data on goods shipped, shipment origin and destination, mode and cost of transport, routes, and the like are needed to compare the benefits and costs of the two alternative approaches to expanding freight capacity in the I-81 corridor. Data on the nature and amount of freight moving by truck are particularly important for identifying opportunities to shift freight from truck to rail. Many of these data are not available or are not sufficiently reliable to constitute a robust foundation for decision making. Consequently, investment decisions may need to be taken without the benefit of well-informed assessments of road and rail options. Source: TRB 2003. |
portant influence on the service life of a highway, and reliable data on vehicle weight are critical to the design process. Without such data, structures may be over- or underdesigned for their intended use and life. Such inefficient designs not only result in an inappropriate allocation of scarce funds but also pose a risk to the public if structures such as pavements deteriorate rapidly because of unanticipated patterns of use by heavy vehicles.
Comprehensive and reliable freight transportation data offer the potential to enhance the security of goods movements within and into the United States. For example, to support their mission of protecting critical infrastructure, policy makers at the state and local levels need accurate data on the movement of goods to make better resource allocation decisions about the types and levels of protection to put in place. Even before September 11, 2001, terrorist attacks on the United States using the global transportation logistics network were identified as a possible risk to homeland security—for example, by smuggling weapons of mass destruction into the country in oceangoing cargo containers (Flynn 2001). Measures have now been taken to reduce the likelihood of such a scenario. These include amended Customs regulations requiring advance presentation of certain manifest information prior to lading at the foreign port and the implementation of container screening procedures (Federal Register 2002). However, screening of all the nearly 6 million cargo containers off-loaded at U.S. seaports every year is clearly impractical. Therefore, cost-effective methods for pinpointing high-risk shipments that require special screening are important in ensuring that security procedures are effective but do not impede the timely movement of goods on which the nation’s economy depends. By providing a picture of normal shipment patterns, good freight transportation data (and data analyses) would establish a baseline against which to identify unusual or suspicious patterns meriting special scrutiny.
Identify Transportation Marketing Opportunities
Freight transportation providers seeking to develop and market their services to meet evolving customer requirements need freight transportation data for logistics modeling. Data on origin and destination, commodities moved, and the stage of completion of manufactured products help identify opportunities for expediting the efficient flow of raw materials, work-in-process inventory, and finished goods from supplier to customer. Freight carriers and third-party logistics providers can then market their services to potential clients on the basis of anticipated time and cost savings. For example, air cargo carriers providing service into and out of Anchorage, Alaska, would like better data on interna-
tional freight movements. Data on the true origins and destinations of shipments—not just the segments into, out of, or through the international air cargo hub in Anchorage—would help firms identify business development opportunities.5
Trucking firms are increasing partnering with railroads to move more of their domestic long-haul shipments from the highway to rail. These partnerships marry the long-haul cost advantages of rail with the delivery flexibility of truck, resulting in win-win solutions for these commercial enterprises, as well as for government entities facing major investment in highway infrastructure. Despite the benefits, the resulting service and capacity impacts on the railroad can prove significant. Intermodal growth requires long-term investment in yard and track infrastructure. These investments must be financially sound and justified by accurate capacity and revenue estimates. Though trucking partners may share some information on a case-by-case basis, capacity and service planning requires accurate freight data on an aggregated basis, by commodity and by market. Primary data at this level are not available today.
The proposed expansion of Norfolk Southern’s rail line paralleling the I-81 corridor presents one example of this deficiency (see Box 1-5). For the railroad, planning for this project requires estimating the total amount of freight traffic that could be handled on the expanded rail line. These calculations require the volume of traffic currently moving along the I-81 corridor, along with the actual origin and destinations. The lack of accurate freight movement information along the corridor has made planning difficult, limiting the amount of potential investment. Better capacity planning also enables the railroads to provide their trucking partners with better rail service. Service requirements for intermodal transportation are stringent, and scheduling must be planned in concert with other traffic requirements. More complete freight flow information will allow planners to determine the amount of demand in key markets and the capacity needed to meet this demand. Adequate capacity will ensure that intermodal transportation maintains a service standard that allows it to attract greater motor carrier support.
CONCLUDING REMARKS
The objective of the 1991 Intermodal Surface Transportation Efficiency Act was “to develop a National Intermodal Transportation System.” As a result, the last decade has seen an increased emphasis on multimodal approaches to transportation issues, including those affecting freight. At the same time, the U.S. economy experienced the longest uninterrupted expansion in its history over the period from 1991 to 2001 (TRB 2003). The resulting demands on the nation’s transportation infrastructure, coupled with greatly heightened concerns about transportation security, have resulted in an urgent need for better data on freight movements to inform public-sector policy and investment decisions. Such data are also needed by the private sector to identify underserved and emerging markets and potential efficiency improvements. In the next chapter, the limitations of existing freight data are summarized, and the need for a new approach to provide the data required to inform public- and private-sector decision making is identified.
REFERENCES
Abbreviations
BTS Bureau of Transportation Statistics
NRC National Research Council
TRB Transportation Research Board
Boardman, J. 2002. Foreword. In Conference Synthesis: Data Needs in the Changing World of Logistics and Freight Transportation (A. H. Meyburg and J. R. Mbwana, eds.), New York State Department of Transportation, Albany. www.dot.state.ny.us/ttss/conference/synthesis.pdf.
BTS. 1998. Transportation Statistics Beyond ISTEA: Critical Gaps and Strategic Responses. BTS98-A-01. U.S. Department of Transportation, Washington, D.C.
BTS. 1999. Transportation Satellite Accounts: A New Way of Measuring Transportation Services in America. BTS99-R-01. U.S. Department of Transportation, Washington, D.C.
BTS. 2002. International Trade Traffic Study (Section 5115): Measurement of Ton-Miles and Value-Miles of International Trade Traffic Carried by Highways for Each State (draft). U.S. Department of Transportation, Washington, D.C.
Federal Register. 2002. Presentation of Vessel Cargo Declaration to Customs Before Cargo Is Laden Aboard Vessel at Foreign Port for Transport to the United States. Final Rule. Vol. 67, No. 211, Oct. 31, pp. 66,318–66,333.
Flynn, S. 2001. Cargo Clearance, Security, and Safety: National Security. In Conference Proceedings 25: Global Intermodal Freight: State of Readiness for the 21st Century, TRB, National Research Council, Washington, D.C., pp. 75–78.
Metroplan Orlando. 2002. Freight, Goods and Services Mobility Strategy Plan. www.metroplanorlando.com/msplan.
Meyburg, A. H., and J. R. Mbwana (eds.). 2002. Conference Synthesis: Data Needs in the Changing World of Logistics and Freight Transportation. New York State Department of Transportation, Albany. www.dot.state.ny.us/ttss/conference/synthesis.pdf.
Meyer, D. M. 2001. Delivering the Future: e-Freight. Presented at the Roundtable Discussion of e-Freight and Metropolitan Implications, Foundation for Intermodal Research and Education, March 7–9. www.intermodal.org/FIRE/meyerpaper.html.
NRC. 2001. Inland Navigation System Planning: The Upper Mississippi River– Illinois Waterway. National Academy Press, Washington, D.C.
TRB. 2003. Special Report 271: Freight Capacity for the 21st Century. National Research Council, Washington, D.C.
U.S. Department of Transportation. 2000. NHS Intermodal Freight Connectors: A Report to Congress. www.ops.fhwa.dot.gov/freight/pp/nhs%20final%20report.DOC.
Weisbrod, G., D. Vary, and G. Treyz. 2001. NCHRP Report 463: Economic Implications of Congestion. TRB, National Research Council, Washington, D.C.
Wilson, R. A. (ed.). 2001. Transportation in America, 18th ed. Eno Transportation Foundation, Washington, D.C.
