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Closed-loop feedback optimization for autonomous vehicles using deep reinforcement learning

delete2026-02-12
delete0
PRE
AI
S
Sifan Wu
X
Xuting Duan
J
Jianshan Zhou
D
Dezong Zhao
D
Dongpu Cao
D
Daxin Tian
DOI：10.1016/j.eswa.2026.131383delete
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摘要

摘要

En 中文
• 一种新颖的闭环反馈框架优化了运动规划轨迹，并实时更新决策制定。 • 一种双值优先采样策略从高奖励和低奖励经验中识别高价值样本。 • 一种混合动作选择机制整合了MOBIL模型以引导探索。 • 该框架超越了当前最先进的模型，并展示了其在实际应用中的强大潜力。
Keyword:
closed-loop feedback
deep reinforcement learning
motion planning
trajectory optimization
autonomous vehicles

期刊

Expert Systems with Applications 封面图
Expert Systems with Applications
IF:
7.5
论文数:
3.0W
被引数:
10.2W

机构

B
beihang university
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5.2K
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被引数: 21
U
university of glasgow
学者数:
3.5W
论文数: 3.1W
被引数: 37
U
University of Waterloo
学者数:
2.2W
论文数: 2.3W
被引数: 3.3W
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