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UPGRADING TRAVEL DEMAND FORECASTING CAPABILITIES: U.S. DOT TRAVEL MODEL IMPROVEMENT PROGRAM

E Weiner, F W Ducca

Open publisher page 8 citations

Abstract

Current travel forecasting models have shortcomings. There are many factors influencing travel behavior that were not present when these models were originally developed and that now need to be taken into account in travel forecasting. To advance the state of modeling practice, an extensive program of technical assistance, training, and improved documentation of procedures is crucial. In the longer term, there is a considerable need to develop a new generation of travel forecasting procedures. The various components of the existing conventional travel forecasting process were developed separately and merged into an integrated system. It is time to build a new set of procedures, developed as an internally consistent approach, on the basis of what is now known and what is expected in the future. In 1993, the U.S. Department of Transportation and the Environmental Protection Agency established the Travel Model Improvement Program (TMIP) to improve the quality of passenger and freight travel-analysis procedures for federal, state, and local agencies. The program, funding for which has grown from $1.8 million to more than $5 million, pursues five tracks of activity: outreach, near-term improvements, long-term improvements, data needs, and land use. This article discusses in detail each of these tracks of activity.

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What this paper is about

Current travel forecasting models have shortcomings. There are many factors influencing travel behavior that were not present when these models were originally developed and that now need to be taken into account in travel forecasting. To advance the state of modeling practice, an extensive program of technical assistance, training, and improved documentation of procedures is crucial. In the longer term, there is a considerable need to develop a new generation of travel forecasting procedures. The various components of the existing conventional travel forecasting process were developed separately and merged into an integrated system. It is time to build a new set of procedures, developed as an internally consistent approach, on the basis of what is now known and what is expected in the future. In 1993, the U.S. Department of Transportation and the Environmental Protection Agency established the Travel Model Improvement Program (TMIP) to improve the quality of passenger and freight travel-analysis procedures for federal, state, and local agencies. The program, funding for which has grown from $1.8 million to more than $5 million, pursues five tracks of activity: outreach, near-term improvements, long-term improvements, data needs, and land use. This article discusses in detail each of these tracks of activity.

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Available abstract

Current travel forecasting models have shortcomings. There are many factors influencing travel behavior that were not present when these models were originally developed and that now need to be taken into account in travel forecasting. To advance the state of modeling practice, an extensive program of technical assistance, training, and improved documentation of procedures is crucial. In the longer term, there is a considerable need to develop a new generation of travel forecasting procedures. The various components of the existing conventional travel forecasting process were developed separately and merged into an integrated system. It is time to build a new set of procedures, developed as an internally consistent approach, on the basis of what is now known and what is expected in the future. In 1993, the U.S. Department of Transportation and the Environmental Protection Agency established the Travel Model Improvement Program (TMIP) to improve the quality of passenger and freight travel-analysis procedures for federal, state, and local agencies. The program, funding for which has grown from $1.8 million to more than $5 million, pursues five tracks of activity: outreach, near-term improvements, long-term improvements, data needs, and land use. This article discusses in detail each of these tracks of activity.

Key concepts: Documentation, Demand forecasting, Transport engineering, Outreach, Operations research, Process (computing), Term (time), Agency (philosophy)

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