2000Transportation Research Record Journal of the Transportation Research BoardRequires access

Creating a Synthetic Household Travel and Activity Survey: Rationale and Feasibility Analysis

Stephen Greaves, Peter Stopher

Open publisher page 36 citations

Abstract

Proposed is a new approach for developing the travel survey data required for use in local travel-demand models. Using readily available local sociodemographic information in conjunction with a freely available national travel survey, a simulation procedure is described to create, in effect, a synthetic household travel survey. The reasons for interest in such a procedure are outlined, including the costs and difficulties associated with gathering high-quality travel data. Consideration is then given to alternatives for local model development, such as the use of national data averages and borrowed models. The simulation procedure is then described and tested in a region that has recently completed a travel survey; this provides a direct source of comparison of the merit of the approach. Trip production models are then built using the synthetic data set. The case study results show that the synthetic data ( a) offer significant improvements over the use of borrowed models and ( b) estimate new models that are similar to those same models estimated using the local travel survey data. It is concluded that these results show that the approach has considerable promise. Finally, some future directions are described, including the planned extension of the approach to other regions.

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What this paper is about

Proposed is a new approach for developing the travel survey data required for use in local travel-demand models. Using readily available local sociodemographic information in conjunction with a freely available national travel survey, a simulation procedure is described to create, in effect, a synthetic household travel survey. The reasons for interest in such a procedure are outlined, including the costs and difficulties associated with gathering high-quality travel data. Consideration is then given to alternatives for local model development, such as the use of national data averages and borrowed models. The simulation procedure is then described and tested in a region that has recently completed a travel survey; this provides a direct source of comparison of the merit of the approach. Trip production models are then built using the synthetic data set. The case study results show that the synthetic data ( a) offer significant improvements over the use of borrowed models and ( b) estimate new models that are similar to those same models estimated using the local travel survey data. It is concluded that these results show that the approach has considerable promise. Finally, some future directions are described, including the planned extension of the approach to other regions.

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Available abstract

Proposed is a new approach for developing the travel survey data required for use in local travel-demand models. Using readily available local sociodemographic information in conjunction with a freely available national travel survey, a simulation procedure is described to create, in effect, a synthetic household travel survey. The reasons for interest in such a procedure are outlined, including the costs and difficulties associated with gathering high-quality travel data. Consideration is then given to alternatives for local model development, such as the use of national data averages and borrowed models. The simulation procedure is then described and tested in a region that has recently completed a travel survey; this provides a direct source of comparison of the merit of the approach. Trip production models are then built using the synthetic data set. The case study results show that the synthetic data ( a) offer significant improvements over the use of borrowed models and ( b) estimate new models that are similar to those same models estimated using the local travel survey data. It is concluded that these results show that the approach has considerable promise. Finally, some future directions are described, including the planned extension of the approach to other regions.

Key concepts: Travel survey, Travel behavior, Survey data collection, Computer science, Set (abstract data type), Operations research, Transport engineering, Production (economics)

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