@article{147f69aa043f4b27a67150748491c81b,
title = "A Decision-Making Model for Autonomous Vehicles at Intersections Based on Hierarchical Reinforcement Learning",
abstract = "By aiming at addressing the left-turning problem of an autonomous vehicle considering the oncoming vehicles at an urban unsignallized intersection, a hierarchical reinforcement learning is proposed and a two-layer model is established to study behaviors of left-turning driving. Compared with the conventional decision-making models with a fixed path, the proposed multi-paths decision-making algorithm with horizontal and vertical strategies can improve the efficiency of autonomous vehicles crossing intersections while ensuring safety.",
keywords = "Autonomous vehicles, decision-making model, deep deterministic policy gradient, hierarchical reinforcement learning, urban intersections",
author = "Chen, {Xue Mei} and Xu, {Shu Yuan} and Wang, {Zi Jia} and Zheng, {Xue Long} and Han, {Xin Tong} and Liu, {En Hao}",
note = "Publisher Copyright: #c World Scientific Publishing Company.",
year = "2024",
month = jul,
day = "1",
doi = "10.1142/S2301385024500122",
language = "English",
volume = "12",
pages = "641--652",
journal = "Unmanned Systems",
issn = "2301-3850",
publisher = "World Scientific",
number = "4",
}