Driver Modeling through Deep Reinforcement Learning and Behavioral Game Theory

24 Mar 2020Berat Mert AlbabaYildiray Yildiz

In this paper, a synergistic combination of deep reinforcement learning and hierarchical game theory is proposed as a modeling framework for behavioral predictions of drivers in highway driving scenarios. The need for a modeling framework that can address multiple human-human and human-automation interactions, where all the agents can be modeled as decision makers simultaneously, is the main motivation behind this work... (read more)

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