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Title:

Forecasting Network Data: Spatial Interpolation of Traffic Counts from Texas Data

Accession Number:

01137535

Record Type:

Component

Availability:

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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:

Annual average daily traffic (AADT) values have long played an important role in transportation design, operations, planning, and policy making. However, AADT values are almost always rough estimates that are based on the closest short-period traffic counts and are factored by using permanent automatic traffic recorder data. This study develops Kriging-based methods for mining network and count data over time and space. With the use of Texas highway count data, the method forecasts AADT values at locations where no traffic detectors are present. While low-volume road counts remain difficult to predict, available explanatory variables are few, and extremely high-count outlier sites skew predictions in the data set used here, overall AADT-weighted median prediction error is 31% (across all Texas network sites). Here, Kriging performed far better than other options for spatial extrapolation, such as assigning AADT on the basis of a point’s nearest sampling site, which yields errors of 80%. Beyond AADT estimation, Kriging is a promising way to explore spatial relationships across a wide variety of data sets, including, for example, pavement conditions, traffic speeds, population densities, land values, household incomes, and trip generation rates. Further refinements, including spatial autocorrelation functions based on network (rather than Euclidean) distances and inclusion of far more explanatory variables are possible, and will further enhance estimation.

Monograph Accession #:

01141653

Report/Paper Numbers:

09-2294

Language:

English

Authors:

Wang, Xiaokun
Kockelman, Kara M

Pagination:

pp 100-108

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 (7) ; References (15) ; Tables (2)

Uncontrolled Terms:

Geographic Terms:

Subject Areas:

Data and Information Technology; Highways; Planning and Forecasting; I71: Traffic Theory; I72: Traffic and Transport Planning

Files:

TRIS, TRB, ATRI

Created Date:

Jan 30 2009 6:39PM

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