Dynamic Path Planning for Vehicles Based on Causal State-Masking Deep Reinforcement Learning

Dynamic Path Planning for Vehicles Based on Causal State-Masking Deep Reinforcement Learning

Dynamic path planning enables vehicles to autonomously navigate in unknown or continuously changing environments, thereby reducing reliance on fixed maps. Deep reinforcement learning (DRL), with its superior performance in handling high-dimensional state spaces and complex dynamic environments, has...

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Bibliographic Details
Main Authors: Xia Hua, Tengteng Zhang, Jun Cao
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Algorithms
Subjects:
dynamic path planning
vehicles
deep reinforcement learning
causal inference mechanism
state masks
Online Access:https://www.mdpi.com/1999-4893/18/3/146
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