Evaluating and addressing the effects of regression to the mean phenomenon in estimating collision frequencies on urban high collision concentration locations

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Two different methods for addressing the regression to the mean phenomenon (RTM) were evaluated using empirical data: 1 The Empirical Bayes (EB) method, which combines observed collision data and Safety Performance Functions (SPF) to estimate expected collision frequency of a site. 2 Continuous Risk Profile (CRP), which estimates true collision profile constructed after filtering out the noise. Data from 110 miles of freeway located in California were used to evaluate the performance of the EB and CRP methods in addressing RTM. CRP outperformed the EB method in estimating collision frequencies in selected high collision concentration locations (HCCLs). Findings indicate that the performance of the EB method can be markedly affected when SPF is biased, while the performance of CRP remains much less affected. The CRP method was more effective in addressing RTM. Published by Elsevier Ltd.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2016-12
Language
English
Article Type
Article
Citation

ACCIDENT ANALYSIS AND PREVENTION, v.97, pp.49 - 56

ISSN
0001-4575
DOI
10.1016/j.aap.2016.08.019
URI
http://hdl.handle.net/10203/251537
Appears in Collection
GT-Journal Papers(저널논문)
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