Freight-Demand Modeling to Support Public-Sector Decision Making (2010) / Chapter Skim
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Pages 7-12
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From page 7... ...
As a result, this approach relied heavily on information collected from a series of interviews conducted concurrently with freight modelers, planners, and decisionmakers from state DOTs and MPOs as shown in Figure 2.1. These in-person and phone interviews were supported with a Web survey and a comprehensive review of freight demand forecasting literature that focused on models and analysis tools that enhance the understanding of freight demand and public-sector decisionmaking.
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From page 8... ...
8Freight Costs and Benefits Performance Measures Estimate of Mode Shifting Estimate of Time-of-Day Shifting Route Diversion Estimates Freight Forecasts Existing Routings Facility Flow Information 3.5 3.3 3.4 2.9 3.2 3.4 3.9 3.5 1 32 4 5 Figure 2.1. Interview locations.
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From page 9... ...
Therefore, truck models based exclusively on commodity flow data tend to underestimate truck trips in the urban area. In addition, the commodity flow data generally are not available at the Traffic Analysis Zone (TAZ)
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From page 10... ...
These models can help provide information on a number of topics that would be of interest to public-sector freight planners, particularly freight trip chaining and mode-choice decisions. However, most of these models were initially developed with the intention of helping producers (who ship goods)
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From page 11... ...
Establishment of a national vision for freight demand modeling would help coordinate and guide freight data collection, model consistency, and validation/calibration procedures across all public-sector agencies. • Limited ties between freight planning and economic development -- There is a need to fully integrate freight demand models with economic models to facilitate transportation strategies that maximize a state or region's economic advantage.
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From page 12... ...
The subset of people that can actually run the model gets smaller as the model gets more sophisticated. – Temporal variability -- Particularly relevant to urban truck models, current freight demand models often lack the ability to evaluate temporal variability, such as time of day and seasonal demand.
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