Application of an Improved Accident Analysis Method for Highway Safety Evaluations
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1994-10-01
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TRIS Online Accession Number:00672516
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NTL Classification:NTL-HIGHWAY/ROAD TRANSPORTATION-HIGHWAY/ROAD TRANSPORTATION;NTL-HIGHWAY/ROAD TRANSPORTATION-Design;NTL-SAFETY AND SECURITY-Highway Safety;NTL-SAFETY AND SECURITY-Accidents;NTL-REFERENCES AND DIRECTORIES-Statistics;
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Abstract:Safety evaluations mostly rely on assessment of accident experience over before-and-after periods. One of the common pitfalls in the assessment methodologies is the failure to account for regression-to-the-mean (r-t-m) bias. The sampling bias due to the r-t-m phenomenon may seriously affect conclusions drawn in safety treatment evaluation studies. Safety treatment sites are generally selected because they have a high accident rate or accident count. If a site has an unusually high number of accidents occurring before the treatment, accident occurrence at that same site the following period would, in all probability, be lower even without any intervention at that site. This is the phenomenon known as r-t-m. Therefore, a simple before-and-after comparison for sites where the treatment is selected based on the accident experience is likely to result in an overestimation of the treatment's effect. In a recent Federal Highway Administration (FHWA) study, a new method, titled Empirical Bayes Estimation of Safety and Transportation (EBEST), was developed for providing a better estimate of the expected accident experience for a treated site, adjusted for any r-t-m bias. This study was undertaken to apply the EBEST methodology to actual data from the Highway Safety Information System (HSIS). The installation of traffic signal controls at previously unsignalized intersections was selected as the treatment to be evaluated.
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