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Freight-Demand Modeling to Support Public-Sector Decision Making (2010) / Chapter Skim
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Summary
Pages 1-5

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 1...
... The outreach showed general satisfaction with the methods available to support freight planning, but dissatisfaction with the data that are available to support freight planning. Research The review of the model framework and the survey responses suggested a number of research topics that could be improved through additional research.
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From page 2...
... Includes choicebased and survey-based demand models CommodityBased and Input-Output Estimate current and forecasted freight traffic generation and distribution by linking industrial activity through input-output models of economic activity Multimodal Network Link-node network representations of freight supply useful for determining travel times, costs, reliability, and overall level of service Microsimulation and Agent-Based Microsimulation models the individual movement of large numbers of units and their attributes, while agent-based modeling defines potential actors in freight transporatation and an allowable set of actions and interactions Supply Chain/ Logistics Supply chains define the life cycle of products from raw materials to the final consumer, including production, inventory, and transportation Network Design Private-sector models for locating factories, distribution centers, warehouses, and other freight generating facilities Routing and Scheduling Private-sector models for locating factories, distribution centers, warehouses, and other freight generating facilities Other and Emerging Topics Hybrid models, real-time decision making Widely used, state of the practice Emerging model, limited use Lacking research or application Table S.1. Comparison of model development and implementation in the literature to public-sector applications.
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From page 3...
... Average trip characteristics ranged from a low of 38 min and 9.2 mi in Baltimore to 44 min and 11.3 mi in Los Angeles. The research on temporal and seasonal commodity flow factors suggested that it is possible to assign truck commodity flows to the highway network and to compare the flows with observed truck counts.
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From page 4...
... Mode choice: trip table Os and Ds by mode. Step 6a -- Direct acquisition of commodity OD tables: alternate ways to get freight OD tables.
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From page 5...
... The research showed that existing and readily available data can be used to develop the inputs required by freight models. Economic Inputs Step 4 Trip Generation Step 5 Trip Distribution Step 6 Mode Choice Step 7 Payload and Temporal Factors Step 8 Service (nonfreight)
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Key Terms

  • commodity flow
  • mode choice
  • trip table
  • public decisionmakers
  • truck trips

  • support freight
  • freight transportation
  • freight planning
  • public datasets
  • using public

  • gps data
  • trip distribution
  • model framework
  • explain mode
  • seasonal commodity

  • data suggested
  • parameters using
  • chaining data
  • daily traffic
  • flow factors

  • residential land
  • freight model
  • freight analysis
  • implementing freight
  • forecasted freight

  • freight models
  • freight demand
  • freight traffic
  • analyze freight
  • public sector


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