Driving Decision and Control for Autonomous Lane Change based on Deep Reinforcement Learning

We apply Deep Q-network (DQN) with the consideration of safety during the task for deciding whether to conduct the maneuver. Furthermore, we design two similar Deep Q learning frameworks with quadratic approximator for deciding how to select a comfortable gap and just follow the preceding vehicle. F...

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Bibliographische Detailangaben

Hauptverfasser:	Shi, Tianyu, Wang, Pin, Cheng, Xuxin, Chan, Ching-Yao, Huang, Ding
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Computer Science - Robotics Statistics - Machine Learning
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