Freight-Demand Modeling to Support Public-Sector Decision Making (2010) / Chapter Skim
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Pages 46-57
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From page 46... ...
The largest gap in the application of these models that was identified from the interview process was data to support the models. The research topics in Section 3 were selected not only to develop data that might be used to support these models, but also to show that publicly available data or low-cost data acquisitions can be used to develop data that can improve freight forecasting models.
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From page 47... ...
Measures help agencies provide accountability to the public, stay focused on intended results, improve communication with internal and external customers, and improve delivery of services. This is 47 Need Description General and Long-Range Planning Transportation planning including preparation of multimodal transportation plans and/or freight plans; includes forecasts in support of design, asset management, safety, operations, financial planning, and all transportation agency needs Project Prioritization Project prioritization and transportation improvement plan development Modal Diversion Modal diversion analysis Policy and Economic Policy and economic studies Rail Planning Rail planning Table 4.1.
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From page 48... ...
After identifying the freight outputs that are 48 Policy Needs Performance Measures Forecasting Outputs Required Average fuel consumption per trip for selected trips (or shipments) Modal link volumes, modal link speeds Fuel consumption per ton-mile traveled Modal link volumes, modal link speed Market share of international or regional trade by mode Total modal volumes Average cost per trip Modal link volumes, modal link speeds Average shipment time, cost, variability in arrival time for freight shipments (local versus long-distance by commodity, by mode)
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From page 49... ...
• Commodity forecasting -- synthetic modeling of commodity flows -- This consists of Steps 4, 5, and 6, which are used to develop modal commodity flow trip tables, and Steps, 7, 9, and 10, which are used to convert that commodity trip table to a suitable format for assignment to modal networks and then to evaluate the flows on those networks. • Commodity forecasting -- direct acquisitions of commodity flows -- This consists of Step 6a, which directly acquires a commodity flow table instead of following the synthetic process.
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From page 50... ...
This is because commodities are expected to behave in similar fashion in trip generation to changes in activity drivers, such as employment; in trip distribution to changes in accessibility such as interzonal composite costs; and in mode choice to changes in costs by mode regardless of location. For service or nonfreight trucks, this may mean difference by land use categories, since truck trips to, from, and between land uses should behave in a similar manner.
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From page 51... ...
Trip Generation: Productions and Attractions by Commodity in Tons This step is necessary for those models that estimate commodity freight tables synthetically. The volume of commodity flows that begin in a zone, called productions, and an end in a zone, called attractions, must be determined for each zone.
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From page 52... ...
The match of the trip length distribution for one commodity in the Florida freight model of the observed commodity flow and the estimated flow in a gravity model is shown in Figure 4.3. It is possible that impedance variables other than distance and other distributions may better match observed data.
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From page 53... ...
When a commodity flow survey has been acquired and developing the trip generation, trip distribution, and mode-choice equations from that survey, as well as the forecast data required to use these models, is costly, a decision to use that commodity flow directly in the modeling process may be quite reasonable. This step uses an acquired commodity flow survey as a trip table.
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From page 54... ...
For that reason models may choose to handle the nonfreight truck table differently than the freight truck table. The forecast of nonfreight trucks will most often be through a synthetic process of trip generation and trip distribution, similar to the steps for freight 54 Commodity Pounds per Truck Tons per Truck Agriculture 48,500 24 Chemicals 48,500 24 Construction and mining 50,500 25 Food and kindred products 48,500 24 Household goods and other manufactures 38,500 19 Machinery 36,500 18 Mixed misc.
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From page 55... ...
PSRC Truck Model (Attraction) Households 0.011 0.011 0.069 0.0087 0.0163 0.0283 Ag/Mining/Construction 0.040 0.044 0.106 0.0836 0.0404 0.2081 Mining 0.0404 10.8831 Construction 0.0453 0.0644 Retail 0.032 0.035 0.132 0.0962 0.0744 0.0090 Government Education/Government 0.037 0.038 0.006 0.0022 0.0135 0.0118 Finance/Insurance/Real Estate 0.008 0.008 0.021 – 0.0197 0.0276 Manufacturing Products 0.050 0.050 0.100 0.0575 0.0390 0.0396 Equipments 0.0390 0.0396 Transportation/Utility 0.168 0.170 0.106 0.4570 0.0944 0.0733 Wholesale 0.192 0.190 0.106 0.0650 0.1159 0.0258 Other – – 0.106 0.0141 – – Source: Cambridge Systematics, SCAG Heavy-Duty Truck Model Update, Southern California Council of Governments, April 2008.
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From page 56... ...
Assignment of Modal Vehicles to Networks This step assigns the freight trip tables, expressed in modal vehicles, to the modal networks. Although public agencies traditionally forecast assignment to the highway system, they less often forecast assignment to other modal networks.
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From page 57... ...
4.2 New Methods to Generate Freight Demand and Performance Although the freight forecasting process described in the steps above can adequately support most existing public decisions, it is not clear that they will always be able to provide this support as the decisions under consideration change. New methods of monitoring, regulating, and charging for vehicle operations may require different models.
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