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A hierarchical game theoretic decision making framework is exploited to model driver decisions and interactions in traffic. In this paper, we apply this framework to develop a simulator to evaluate various existing autonomous driving algorithms. Specifically, two algorithms, based on Stackelberg policies and decision trees, are quantitatively compared in a traffic scenario where all the human-driven vehicles are modeled using the presented game theoretic approach.doi:10.1109/cdc.2016.7798354 dblp:conf/cdc/LiOZYGK16 fatcat:xl36yphow5cfrapocm2i5ja7bq