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OBJECTIVE In this study, the authors used algorithms to estimate driver distraction and predict crash and near-crash risk on the basis of driver glance behavior using the data set of the 100-Car Naturalistic Driving Study. BACKGROUND Driver distraction has been a leading cause of motor vehicle crashes, but the relationship between distractions and crash(More)
Driver distraction represents an increasingly important contributor to crashes and fatalities. Technology that can detect and mitigate distraction by alerting distracted drivers could play a central role in maintaining safety. Based on either eye measures or driver performance measures, numerous algorithms to detect distraction have been developed.(More)
The purpose of this research project performed for The Minnesota Department of Transportation is to find the optimal length of right and left turn lanes at intersections from a system design point of view. This research project will also determine and quantify the influence of the factors that need to be considered when estimating turn lengths on specific(More)
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