2024
DOI: 10.1371/journal.pone.0297192
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An automatic driving trajectory planning approach in complex traffic scenarios based on integrated driver style inference and deep reinforcement learning

Yuchen Liu,
Shuzhen Diao

Abstract: As autonomous driving technology continues to advance and gradually become a reality, ensuring the safety of autonomous driving in complex traffic scenarios has become a key focus and challenge in current research. Model-free deep reinforcement learning (Deep Reinforcement Learning) methods have been widely used for addressing motion planning problems in complex traffic scenarios, as they can implicitly learn interactions between vehicles. However, current planning methods based on deep reinforcement learning … Show more

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