Conditional Predictive Behavior Planning With Inverse Reinforcement Learning for Human-Like Autonomous Driving

Making safe and human-like decisions is an essential capability of autonomous driving systems, and learning-based behavior planning presents a promising pathway toward achieving this objective. Distinguished from existing learning-based methods that directly output decisions, this work introduces a...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems 2023-07, Vol.24 (7), p.7244-7258
Hauptverfasser:	Huang, Zhiyu, Liu, Haochen, Wu, Jingda, Lv, Chen
Format:	Artikel
Sprache:	eng
Schlagworte:	autonomous driving Autonomous vehicles Behavior planning Behavioral sciences conditional motion prediction Decisions inverse reinforcement learning Maximum entropy Modules Planning Prediction models Predictive models Proposals Reinforcement learning Trajectory
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