Reinforcement Learning Decision-Making for Autonomous Vehicles Based on Semantic Segmentation

In the complex and stochastic traffic flow, ensuring safe driving requires improvements in perception and decision-making. This paper proposed a decision-control method that leveraged the scene perception and understanding capabilities of semantic segmentation networks and the stable convergence str...

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Библиографические подробности

Главные авторы:	Jianping Gao, Ningbo Liu, Haotian Li, Zhe Li, Chengwei Xie, Yangyang Gou
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2025-01-01
Серии:	Applied Sciences
Предметы:	autonomous driving semantic segmentation deep reinforcement learning proximal policy optimization double deep Q-network CARLA simulation simulator
Online-ссылка:	https://www.mdpi.com/2076-3417/15/3/1323
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