Researchers from Louisiana State University Provide Details of New Studies and Findings in the Area of Risk Management (Detection of driver…

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Researchers from Louisiana State University Provide Details of New Studies and Findings in the Area of Risk Management (Detection of driver engagement in secondary tasks from observed naturalistic driving behavior)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Research findings on Risk Management are discussed in a new report. According to news reporting from Baton Rouge, Louisiana, by VerticalNews journalists, research stated, "Distracted driving has long been acknowledged as one of the leading causes of death or injury in roadway crashes. The focus of past research has been mainly on the impact of different causes of distraction on driving behavior."

Financial support for this research came from Louisiana Transportation Research Center (LTRC) under state project number.

The news correspondents obtained a quote from the research from Louisiana State University, "However, only a few studies attempted to address how some driving behavior attributes could be linked to the cause of distraction. In essence, this study takes advantage of the rich SHRP 2 Naturalistic Driving Study (NDS) database to develop a model for detecting the likelihood of a driver's involvement in secondary tasks from distinctive attributes of driving behavior. Five performance attributes, namely speed, longitudinal acceleration, lateral acceleration, yaw rate, and throttle position were used to describe the driving behavior. A model was developed for each of three selected secondary tasks: calling, texting, and passenger interaction. The models were developed using a supervised feed-forward Artificial Neural Network (ANN) architecture to account for the effect of inherent nonlinearity in the relationships between driving behavior and secondary tasks. The results show that the developed ANN models were able to detect the drivers' involvement in calling, texting, and passenger interaction with an overall accuracy of 99.5%, 98.1%, and 99.8%, respectively. These results show that the selected driving performance attributes were effective in detecting the associated secondary tasks with driving behavior."

According to the news reporters, the research concluded: "The results are very promising and the developed models could potentially be applied in crash investigations to resolve legal disputes in traffic accidents."

For more information on this research see: Detection of driver engagement in secondary tasks from observed naturalistic driving behavior. Accident Analysis and Prevention, 2017;106():385-391. 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 O.A. Osman, Louisiana State University, Dept. of Civil & Environm Engn, Baton Rouge, LA 70803, United States. Additional authors for this research include M.Q. Ye, S. Ishak and B. Hashemi.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.aap.2017.07.010. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

Keywords for this news article include: Baton Rouge, Louisiana, United States, North and Central America, Risk Management, Louisiana State University.