@article{ref1,
title="Hierarchical and game-theoretic decision-making for connected and automated vehicles in overtaking scenarios",
journal="Transportation research part C: emerging technologies",
year="2023",
author="Ji, Kyoungtae and Li, Nan and Orsag, Matko and Han, Kyoungseok",
volume="150",
number="",
pages="e104109-e104109",
abstract="This paper presents a hierarchical and game-theoretic decision-making strategy for connected and automated vehicles (CAVs). A CAV can receive preview information using vehicle-to-everything (V2X) communication systems, and the optimal short- and long-term trajectory can be planned using this information. Specifically, in this study, the aggressiveness of all preceding vehicles in the car-following scenario can be estimated globally by monitoring the history of their time-series behaviors, before the CAV initiates a particular action, which is performed at the upper layer of the proposed decision-making structure. If it is determined that initiating a specific action is advantageous, the action is initiated, and the CAV then interacts with the vehicles locally to achieve its driving goal in a game-theoretical manner at the lower layer. In multiple test scenarios, we demonstrate the usefulness of our approach compared to the conventional decision-making approaches, and it shows a significant improvement in terms of success rates.<p /> <p>Language: en</p>",
language="en",
issn="0968-090X",
doi="10.1016/j.trc.2023.104109",
url="http://dx.doi.org/10.1016/j.trc.2023.104109"
}