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NEW DIRECTIONS IN COLLECTION AND USE OF HOUSEHOLD TRAVEL SURVEY DATA

David Reinke

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Abstract

Household travel survey data are the foundations for development of travel demand models. But in many urban areas, existing household travel survey data are not sufficiently detailed for current transportation and air quality analysis needs. In addition, many data sets are 15 or more years old; because of large demographic changes since then, it is highly likely that these older data sets do not adequately represent current travel. A further issue is that these data are not often fully used; by limiting their use to travel model development, transportation planning agencies are not aware of potential uses of the data for analysis of transportation and air quality issues that cannot be directly analyzed with current travel models. This paper presents an overview of the collection and use of household travel survey data. The paper reviews household travel survey data collection experience, focusing on recent surveys in the San Francisco Bay Area, California, and summarizes lessons learned from survey experience. The paper also discusses the use of household travel survey data beyond that of estimating traditional travel demand models. The paper concludes with a look at new advances in household travel survey data collection, with an emphasis on longitudinal data collection.

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What this paper is about

Household travel survey data are the foundations for development of travel demand models. But in many urban areas, existing household travel survey data are not sufficiently detailed for current transportation and air quality analysis needs. In addition, many data sets are 15 or more years old; because of large demographic changes since then, it is highly likely that these older data sets do not adequately represent current travel. A further issue is that these data are not often fully used; by limiting their use to travel model development, transportation planning agencies are not aware of potential uses of the data for analysis of transportation and air quality issues that cannot be directly analyzed with current travel models. This paper presents an overview of the collection and use of household travel survey data. The paper reviews household travel survey data collection experience, focusing on recent surveys in the San Francisco Bay Area, California, and summarizes lessons learned from survey experience. The paper also discusses the use of household travel survey data beyond that of estimating traditional travel demand models. The paper concludes with a look at new advances in household travel survey data collection, with an emphasis on longitudinal data collection.

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Available abstract

Household travel survey data are the foundations for development of travel demand models. But in many urban areas, existing household travel survey data are not sufficiently detailed for current transportation and air quality analysis needs. In addition, many data sets are 15 or more years old; because of large demographic changes since then, it is highly likely that these older data sets do not adequately represent current travel. A further issue is that these data are not often fully used; by limiting their use to travel model development, transportation planning agencies are not aware of potential uses of the data for analysis of transportation and air quality issues that cannot be directly analyzed with current travel models. This paper presents an overview of the collection and use of household travel survey data. The paper reviews household travel survey data collection experience, focusing on recent surveys in the San Francisco Bay Area, California, and summarizes lessons learned from survey experience. The paper also discusses the use of household travel survey data beyond that of estimating traditional travel demand models. The paper concludes with a look at new advances in household travel survey data collection, with an emphasis on longitudinal data collection.

Key concepts: Data collection, Travel survey, Survey data collection, Travel behavior, Data quality, Survey methodology, Transport engineering, Vehicle miles of travel

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