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Title:

Application of Bayesian Statistics to Identify Highway Sections with Atypically High Rates of Median-Crossing Crashes

Accession Number:

01123080

Record Type:

Component

Availability:

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Washington, DC 20001 United States
Order URL: http://www.trb.org/Main/Blurbs/Statistical_Methods_2009_162994.aspx

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Order URL: http://worldcat.org/isbn/9780309142656

Abstract:

This paper describes a Bayesian statistical technique for using crash records to estimate the frequency and rate of median-crossing crashes (MCCs) on each set of highway sections, in cases where MCCs are not explicitly identified in computerized crash records. This technique requires an analyst to review only a subset of hardcopy accident reports to produce a training sample, which is then used to identify computerized data associated (possibly imperfectly) with whether a crash was an MCC. This association can then be exploited to use larger sets of computerized records to increase statistical power over that provided by the training sample alone. This technique is applied to data from Minnesota’s freeways and rural expressways. Estimates that allow highway sections to be ranked according to the estimated frequency or density of MCCs, or to the estimated MCC rate, are computed, and then the estimated frequency rankings are reported.

Monograph Title:

Statistical Methods 2009

Monograph Accession #:

01147883

Report/Paper Numbers:

09-2595

Language:

English

Authors:

Davis, Gary A
Xiong, Hui
Tao, HunWen

Pagination:

pp 77-81

Publication Date:

2009

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 2136
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

9780309142656

Media Type:

Print

Features:

References (14) ; Tables (4)

Geographic Terms:

Subject Areas:

Data and Information Technology; Highways; Safety and Human Factors; I81: Accident Statistics

Files:

TRIS, TRB, ATRI

Created Date:

Jan 30 2009 6:57PM

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