In this paper, we describe an integrated framework for autonomous decision making in a dynamic and interactive environment. We model the interactions between the ego agent and its operating environment as a two-player dynamic game, and integrate cognitive behavioral models, Bayesian inference, and receding-horizon optimal control to define a dynamically-evolving decision strategy for the ego agent. Simulation examples representing autonomous vehicle control in three traffic scenarios where the autonomous ego vehicle interacts with a human-driven vehicle are reported.
@article{arxiv.1908.04005,
title = {Decision making in dynamic and interactive environments based on cognitive hierarchy theory, Bayesian inference, and predictive control},
author = {Sisi Li and Nan Li and Anouck Girard and Ilya Kolmanovsky},
journal= {arXiv preprint arXiv:1908.04005},
year = {2019}
}