Freight Trip Generation and Land Use (2012) / Chapter Skim
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Pages 107-121
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From page 107... ...
103 This chapter describes the current practices, both domestic and international, of FG and FTG modeling. The different modeling applications of FG and FTG modeling are classified (Fischer and Han 2001)
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104 • Level of geography: Five cases are considered: Facility specific (F) ; Corridor (C)
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105 Table 70. Summary of modeling applications.
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106 Table 71 summarizes the features of the various modeling approaches by level of geography. As shown, the bulk of the metropolitan-level planning applications use vehicle trips as the dependent variable, while statewide applications favor commodity flows.
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Models t ne dn ep e D se lb ai ra v Independent variables no it ag er gg A yh pa rg oe G Modeling technique er ut cu rt S Data Sources Øresund Traffic Forecast Model - Denmark C&V A C Regression N Trip survey, national statistics Fehmarnbelt Model - Denmark C&V A C Regression L Trip survey, national statistics TREMOVE - Europe C&V Production, consumption, import, expenditures, value density A EU General equilibrium N National statistical data on traffic, weightto-vehicle conversion factors STREAMS, SCENES - Europe C Production, consumption, import, export, investment, public expenditures, value density A EU Multi-regional Input Output (MRIO) N IO National tables (Eurostat)
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Models t ne dn ep e D se lb ai ra v Independent variables no it ag er gg A yh pa rg oe G Modeling technique er ut cu rt S Data Sources EUNET2.0 - UK C Production, consumption, import, export, investment, public expenditures, value density A N MRIO, added trip gen through warehouses N National account data (IO) and foreign trade data, regional economic aggregates.
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109 The trip rates listed in the ITE Manual are for all vehicletrips. For some of the land use types, the ITE Manual provides an estimated percentage of truck trips among all vehicle-trips.
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110 site analysis related to freight. The Quick Response Freight Manual was developed for the Travel Model Improvement Program by the FHWA of the United States Department of Transportation (USDOT)
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111 the new facility may also be used. It is worthy of mention that, in addition to the total number of new trips, the analyst may also be interested in the distribution of these trips on a given day, week, or even month.
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112 FTG. This reflects the fact that FG and FTG are determined by fundamentally different processes.
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113 eling at specific land use classes could perform as well as economic variables such as employment. This is certainly the case when variables such as square footage are used to explain and predict FTG (Bartlett and Newton 1982; Tadi and Balbach 1994)
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114 • Great care must be taken to ensure that the aggregation procedures used to estimate FG/FTG at an aggregate level are adequate. Not doing so may lead to large estimation errors.
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115 techniques of wider applicability. More specifically, the discussion considers the cases shown in Table 78.
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116 direct proportionality between FTG and the independent variable used, will underestimate the FTG for businesses smaller than average, and will overestimate the FTG for those larger than average; as shown in Figure 13. It is not clear how well a constant rate would perform in modeling FG as no such applications have been reported in the literature.
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From page 121... ...
117 The use of IO models is generally considered to be a solid technique that is grounded in well-established economic theory. However, there are a number of observations that should be made: • The set of parameters that link the output to the corresponding inputs, i.e., the technical coefficient matrix, is usually estimated using national or regional accounting techniques.
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