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Title:

Model-Based Synthesis of Household Travel Survey Data in Small and Midsize Metropolitan Areas

Accession Number:

01137512

Record Type:

Component

Availability:

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Washington, DC 20001 United States
Order URL: http://trb.org/Main/Blurbs/Information...ographic_Information_Systems_162392.aspx

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Order URL: http://worldcat.org/isbn/9780309126205

Abstract:

Household travel data synthesis–simulation has become a promising alternative or supplement to survey data from both small urban areas and large metropolitan regions in which data are expensive to collect or the data required to support the planning process have become outdated. This paper proposes and applies model-based approaches [i.e., small area estimation (SAE) methods] to synthesize household travel characteristics. The proposed methods address the sampling-bias concerns in the existing methods. Specifically, three SAE methods—the generalized regression estimators method, the empirical best linear unbiased predictor (EBLUP) method, and the synthetic method (an EBLUP without random area effects)—are applied to synthesize household travel characteristics at both census tract and individual levels. The SAE framework of synthesizing household travel characteristics is demonstrated with the National Household Travel Survey data and the Census Transportation Planning Package data in the Des Moines metropolitan area in central Iowa. Results indicate that SAE methods are promising approaches to synthesize unbiased aggregate and disaggregate household travel characteristics by incorporating population auxiliary information and local, small-household travel survey data. The proposed data synthesis methods and analysis findings will provide a useful tool for practitioners, planners, and policy makers in transportation analyses. The paper also points out that by linking population synthesis with the travel data simulation framework described here, this method could be of broad application in transportation planning.

Monograph Accession #:

01141653

Report/Paper Numbers:

09-3456

Language:

English

Authors:

Long, Liang
Lin, Jie
Pu, Wenjing

Pagination:

pp 64-70

Publication Date:

2009

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 2105
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

9780309126205

Media Type:

Print

Features:

Figures (2) ; References (22) ; Tables (3)

Geographic Terms:

Subject Areas:

Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Files:

TRIS, TRB, ATRI

Created Date:

Jan 30 2009 7:52PM

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