Findings on Risk Management Reported by Investigators at Virginia Tech (Performance of basic kinematic thresholds in the identification of crash and…

Findings on Risk Management Reported by Investigators at Virginia Tech (Performance of basic kinematic thresholds in the identification of crash and near-crash events within naturalistic driving data)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Current study results on Risk Management have been published. According to news reporting originating in Blacksburg, Virginia, by VerticalNews journalists, research stated, "Understanding causal factors for traffic safety-critical events (e.g., crashes and near-crashes) is an important step in reducing their frequency and severity. Naturalistic driving data offers unparalleled insight into these factors, but requires identification of situations where crashes are present within large volumes of data."

The news reporters obtained a quote from the research from Virginia Tech, "Sensitivity and specificity of these identification approaches are key to minimizing the resources required to validate candidate crash events. This investigation used data from the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS) and the Canada Naturalistic Driving Study (CNDS) to develop and validate different kinematic thresholds that can be used to detect crash events. Results indicate that the sensitivity of many of these approaches can be quite low, but can be improved by selecting particular threshold levels based on detection performance."

According to the news reporters, the research concluded: "Additional improvements in these approaches are possible, and may involve leveraging combinations of different detection approaches, including advanced statistical techniques and artificial intelligence approaches, additional parameter modifications, and automation of validation processes."

For more information on this research see: Performance of basic kinematic thresholds in the identification of crash and near-crash events within naturalistic driving data. Accident Analysis and Prevention, 2017;103():10-19. 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 correspondents report that additional information may be obtained by contacting M.A. Perez, Virginia Technical, Transportat Inst, Blacksburg, VA 24060, United States. Additional authors for this research include J.D. Sudweeks, E. Sears, J. Antin, S. Lee, J.M. Hankey and T.A. Dingus.

Keywords for this news article include: Blacksburg, Virginia, United States, North and Central America, Risk Management, Virginia Tech.

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