Journal Article
Dawei Li and Mustafa F.M. Al-Mahamda
Oct-20
Li, D. & Al-Mahamda, M.F. (2020). Collective Risk Ranking of Highway Segments on the Basis of Severity-Weighted Crash Rates. Journal of Advanced Transportation, Volume 2020, Article ID 8837762.
This study is intended to focus on the major factors affecting traffic crash rates and severity levels, in addition to identifying crash-prone locations (i.e., black spots) based on the two indicators. The available crash data for different road segments used for the analysis were obtained from the Washington state database provided by the Highway Safety Information System (HSIS) for the years 2006 to 2011. A Random Forest (RF) classifier was used to predict the outcome level of crash severity, while crash rates were predicted by applying RF regressor. Certain features were selected for each model besides the abstraction of new features to check if there are unobserved correlations affecting the independent variables, such as accounting for the number and weight of crashes within 1-km2 area by implementing the Getis-Ord Gi* index. Moreover, to calculate the collective risk (CR) score, crash rates were adjusted to incorporate crash severity weights (cost per severity type) and regression-to-the-mean (RTM) bias via Empirical Bayes (EB) method. Finally, segments were ranked according to their CR score.
Journal of Advanced Transportation
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HSIS Summary Reports are two to eight pages in length and include a brief description of the issue addressed, data used, methodology applied, significant results, and practical implications.
A variety of research studies have been performed using data from HSIS. Many of the final reports prepared are now available electronically.
Research reports are often summarized in executive summaries, technical briefs, or other abbreviated formats. Included here are those road safety summaries that involved research using HSIS data.
In addition to conducting research, HSIS resources are also used to develop products that can be used by practitioners in the analysis of safety problems.
HSIS data are sometimes used in research studies that result in other types of finished products, such as dissertations, theses, and conference proceedings.
