Dynamic collision avoidance for maritime autonomous surface ships based on deep Q-network with velocity obstacle method

To address the dynamic obstacle environment collision avoidance challenge of the marine autonomous surface ships (MASS), a decision-making method based on the deep Q-learning (DQN) and velocity obstacle (VO) algorithm is proposed. Firstly, the encounter situation identification criteria are optimize...

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Veröffentlicht in:	Ocean engineering Jg. 320; S. 120335
Hauptverfasser:	Li, Yuqin, Wu, Defeng, Wang, Hongdong, Lou, Jiankun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.03.2025
Schlagworte:	Collision avoidance COLREGs Deep Q-network algorithm Random collision scenario generation Velocity Obstacle algorithm COLREGs Deep Q-network algorithm Collision avoidance Random collision scenario generation Velocity Obstacle algorithm
ISSN:	0029-8018
Online-Zugang:	Volltext
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