A paper written by RSG Consultant, Jeff Keller has been awarded first place overall in the Transportation Research Board (TRB) Data Competition. Jeff’s paper titled, “Using Random Forest Machine Learning to Predict Driver Behavior in a Dilemma Zone,” describes a means for applying the Random Forest machine learning method to vehicle operating environment data in order to identify drivers of behavior and to predict that behavior. These are desirable outcomes for policymakers who wish to recommend legislation regarding various distraction activities, such as texting or making phone calls, while driving. Automakers have also expressed interest in being able to predict, in real-time, events that may put the safety of vehicle occupants at risk. Jeff will present his findings on Sunday, January 12, at the annual TRB meeting in Washington, DC.