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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
Record URL: Availability: Transportation Research Board Business Office 500 Fifth Street, NW Find a library where document is available 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: Monograph Accession #: 01147883
Report/Paper Numbers: 09-2595
Language: English
Authors: Davis, Gary AXiong, HuiTao, HunWenPagination: pp 77-81
Publication Date: 2009
ISBN: 9780309142656
Media Type: Print
Features: References
(14)
; Tables
(4)
TRT Terms: Uncontrolled Terms: 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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