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FIGURE 2 Air Freight, Express, and Mail Revenue Ton-Miles16Ton-miles (billions)Eno1412NTSImprovedBTS1081990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002p2003Key: p = preliminary.TruckOak Ridge National Laboratory produced estimatesof truck ton-miles based on the 1993 and 1997Commodity Flow Surveys (CFS) (USDOT andUSDOC 1993 and 1997), supplemented with dataon farm-based shipments and imports arriving bytruck from Canada and Mexico. Transportation StatisticsAnnual Report provides this 1997 estimate oftruck ton-miles (USDOT BTS 2000, p. 124). To producethe improved BTS estimate, the 1993 and 1997estimates were updated and backdated using intercityand intracity vehicle miles-traveled (VMT) forsingle-unit and combination trucks, as reported inHighway Statistics (USDOT FHWA 1990–2003).Figure 3 presents the resulting estimates (also seeappendix table A3). The trend in both series is thesame, because the same VMT data were used toupdate each series. After making these adjustmentsfor different time periods and population coverage,the difference between the 1993 and 1997 estimatesis less than 2%. 11 The VMT data include a substantial amount of trucktraffic that is outside the scope of the CFS, e.g., shipmentsby households and retail, service, utility, and governmentestablishments (including the U.S. Postal Service); and certainnoncommercial freight shipments, e.g., constructiontraffic and municipal solid waste. The VMT data can,therefore, be taken to provide a reasonable estimate of thetrend in truck ton-miles, but not the level, and should notbe used to make inferences about operational parameterssuch as empty mileage or average load per truck.FIGURE 3 Development of Truck Ton-MileEstimates1,3001,2001,1001,0009008001990Ton-miles (billions)1992Key: p = preliminary.19941997 base19961993 base1998200020022003 pThe CFS captures export movements, as well asmovements of imports once they reach their firstdomestic destination, such as a warehouse. In orderto provide a more complete estimate of truck traffic,the data in figure 3 were further adjusted to reflecttruck ton-miles from maritime movements prior toreaching their first domestic destination. Thenumber of loaded 20-foot equivalent unit (TEU)containers shipped through U.S. ports is reportedin U.S. Waterborne Container Traffic by Port (U.S.Army Corp of Engineers WCSC 2003). These figureswere then divided by 2.4 to convert them to an26 JOURNAL OF TRANSPORTATION AND STATISTICS V8, N1 2005
equivalent number of 48-foot trucks. Estimates ofthe percentage of import traffic, the truck share ofimport traffic, miles to the first domestic destination,and tons per truck for East, Gulf, and WestCoast ports were obtained through interviews withport personnel in New York, Houston, and LosAngeles, respectively. The resulting estimates addedbetween 7 billion and 12 billion truck ton-mileseach year. This represents approximately 1% of alltruck ton-miles currently estimated.Figure 4 shows trucking ton-mile estimates (alsosee appendix table A4). The improved BTS estimatesare based on the Oak Ridge National Laboratorysupplement to the 1997 study, which is the morerecent of the two studies. The improved BTS estimateis about 10% higher than the NTS and Enoestimates, each of which reflects only intercity trucktraffic. Therefore, the improved BTS estimate providesa more comprehensive estimate of truck traffic.The CFS data used to construct the improvedtrucking ton-miles estimate exclude shipments byhouseholds and retail, service, utility, and governmentestablishments (including the U.S. Postal Service);and certain noncommercial freight shipments,such as construction traffic and municipal solidwaste. The existing NTS and Eno estimates do notinclude intracity traffic. Therefore, it appears that asignificant percentage of truck VMT and a somewhatsmaller percentage of truck ton-miles are notincluded in any of these estimates. Clearly morework is needed in this area.RailroadBTS developed its improved railroad ton-miles estimatesusing data from the Carload Waybill Sample(USDOT STB 1990–2003). The population estimatein this source is based on a 500,000 recordsample of all traffic terminating on all railroads inthe United States. The sample implicitly includestraffic originating on U.S. railroads and terminatingon Mexican railroads, because almost all such trafficis rebilled to U.S. border crossings. 22 Traffic originating on U.S. railroads and terminating onMexican railroads is treated for accounting purposes as ifit terminated at the U.S. border crossing, and is thereforeincluded in the Carload Waybill Sample. This practice isknown as rebilling.FIGURE 4 Truck Ton-MilesTon-miles (billions)1,3001,2001,1001,00090080070019901992Key: p = preliminary.1994Improved BTS19961998NTS, Eno200020022003 pPopulation data on the tonnage of railroadshipments originating in the United States and terminatingin Canada come from Transportation inCanada (Transport Canada 1990–2002) for yearsprior to 2003. The average length of haul for U.S.railroad shipments was applied to this tonnage toobtain an estimate of U.S. railroad ton-miles forshipments terminating in Canada. This assumptionseems reasonable, because even though much of thistraffic originates in states bordering Canada, moredistant states such as California, Texas, and Georgiaare also among the 10 largest originating states. TheCarload Waybill Sample’s improved coverage ofCanadian terminations of rail shipments originatingin the United States allows estimates of all railroadton-miles for 2003 and subsequent years.Figure 5 illustrates the railroad ton-mile estimates(also see appendix table A5). From 1998 to 2001(the most recent years for which all three estimatesare available), the improved BTS estimates areabout 5% greater than the NTS estimates, whichinclude only Class I railroads; about 1% greaterthan the Waybill estimates, which do not includeCanadian terminations; and almost identical to theEno estimates, which include both non-Class I railroadsand Canadian terminations. The increase inthe improved BTS estimates relative to the other estimatesis probably due to better coverage of the rapidlygrowing railroad shipments originating in theUnited States and terminating in Canada. Further,DENNIS 27
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Page 3 and 4: A PEER-REVIEWED JOURNALJOURNAL OF T
Page 5: JOURNAL OF TRANSPORTATION AND STATI
Page 9 and 10: The Dynamics of Aircraft Degradatio
Page 11 and 12: would show a corresponding increase
Page 13 and 14: FIGURE 2 Aircraft Degradation and R
Page 15 and 16: so that- r 2 1 ) . (15)This change
Page 17 and 18: β⎛⎜⎜⎜= ⎜⎜⎜⎜⎝β 1
Page 19: and the fleet management practices
Page 22 and 23: of passengers and cargo to the econ
Page 24 and 25: TABLE 3 Cycle Parameters and Final
Page 26 and 27: TABLE 4 Forecasts of Numbers of Pas
Page 28 and 29: FIGURE 4 Slope Components for the Z
Page 30 and 31: 2. LS: this kind of intervention ha
Page 32 and 33: CONCEPTTon-miles is the primary phy
Page 36 and 37: FIGURE 5 Railroad Ton-MilesTon-mile
Page 38 and 39: Transport Canada. 1990-2002. Transp
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Page 46 and 47: account for premature investments i
Page 48 and 49: zonal definitions. In Supernak et a
Page 50 and 51: TABLE 2 Differences Among the 1972,
Page 52 and 53: FIGURE 1 Research Sequence of Stage
Page 54 and 55: TABLE 3 Regression Models by Metrop
Page 56 and 57: TABLE 5 Tobit Models by Metropolita
Page 58 and 59: Table 9 presents the predicted aver
Page 60 and 61: TABLE 9 Aggregate Estimation Result
Page 62 and 63: TABLE 11 Tobit Estimation of Nontra
Page 64 and 65: Fleet, C. and S. Robertson. 1968. T
Page 66 and 67: INTRODUCTIONThe Intermodal Surface
Page 68 and 69: SUPPLEMENTAL STATE-LEVEL DATAIn add
Page 70 and 71: METHODOLOGYAn exploratory factor an
Page 72 and 73: Thus, a relatively large p value an
Page 74 and 75: FIGURE 1 Final Model Specifications
Page 76 and 77: CONCLUSIONSISTEA and the TEA-21 leg
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Incidents have become one of the ma
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FIGURE 1 Map of the M4 MotorwayA40A
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TABLE 2 Variables in the Fuzzy Logi
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FIGURE 9 Result of the ANN ModelMod
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Garib, A., A.E. Radwan, and H. Al-D
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Fx ( )Working Correlation Matrix in
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TABLE 3 Modeling Results for the MG
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REFERENCESAbdalla, M. 2003. Modelin
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the relevant covariates including t
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BOOK REVIEWSEconomic Impacts of Int
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TABLE 1 Airline Employees by Busine
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JOURNAL OF TRANSPORTATION AND STATI
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U.S. Department of TransportationRe
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