Ekim Yurtsever

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This paper presents a novel method for integrating driving behavior and traffic context through signal symbolization in order to summarize driving semantics from sensor outputs. The method has been applied to risky lane change detection. Language models (nested Pitman-Yor language model) and speech recognition algorithms (hidden Markov Model) have been(More)
This paper proposes a novel approach for extracting the traffic trajectory history, with the use of GPS data collected over a certain period of time, to be used as an input for driver models. In this approach, driving curvature is distinguished from actual road shape curvature with the use of real driving data. After sufficient amount of drive data has been(More)
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