Hierarchical reasoning game theory based approach for evaluation and testing of autonomous vehicle control systems
Proceedings of the IEEE 55th Conference on Decision and Control, CDC 2016
727 - 733
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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.
Hidden Markov Model (HMM)