Reports from University of Hawaii Highlight Recent Findings in Risk Management (Examining driver injury severity outcomes in rural non-interstate…

Reports from University of Hawaii Highlight Recent Findings in Risk Management (Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Investigators publish new report on Risk Management. According to news reporting from Honolulu, Hawaii, by VerticalNews journalists, research stated, "Rural non-interstate crashes induce a significant amount of severe injuries and fatalities. Examination of such injury patterns and the associated contributing factors is of practical importance."

Financial support for this research came from National Natural Science Foundation of China.

The news correspondents obtained a quote from the research from the University of Hawaii, "Taking into account the ordinal nature of injury severity levels and the hierarchical feature of crash data, this study employs a hierarchical ordered logit model to examine the significant factors in predicting driver injury severities in rural non-interstate crashes based on two-year New Mexico crash records. Bayesian inference is utilized in model estimation procedure and 95% Bayesian Credible Interval (BCI) is applied to testing variable significance. An ordinaryordered logit model omitting the between-crash variance effect is evaluated as well for model performance comparison. Results indicate that the model employed in this study outperforms ordinary ordered logit model in model fit and parameter estimation. Variables regarding crash features, environment conditions, and driver and vehicle characteristics are found to have significant influence on the predictions of driver injury severities in rural non-interstate crashes. Factors such as road segments far from intersection, wet road surface condition, collision with animals, heavy vehicle drivers, male drivers and driver seatbelt used tend to induce less severe driver injury outcomes than the factors such as multiple-vehicle crashes, severe vehicle damage in a crash, motorcyclists, females, senior drivers, driver with alcohol or drug impairment, and other major collision types. Research limitations regarding crash data and model assumptions are also discussed."

According to the news reporters, the research concluded: "Overall, this research provides reasonable results and insight in developing effective road safety measures for crash injury severity reduction and prevention."

For more information on this research see: Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model. Accident Analysis and Prevention, 2016;96():79-87. Accident Analysis and Prevention can be contacted at: Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England. (Elsevier - www.elsevier.com; Accident Analysis and Prevention - www.journals.elsevier.com/accident-analysis-and-prevention/)

Our news journalists report that additional information may be obtained by contacting C. Chen, Univ Hawaii Manoa, Dept. of Civil & Environm Engn, Honolulu, HI 96822, United States. Additional authors for this research include G.H. Zhang, H.L. Huang, J.F. Wang and R.A. Tarefder.

Keywords for this news article include: Honolulu, Hawaii, United States, North and Central America, Risk Management, University of Hawaii.

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