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Safe Reinforcement Learning for Autonomous Lane Changing Using Set-Based Prediction 
Krasowski, Hanna; Wang, Xiao; Althoff, Matthias 
Machine learning approaches often lack safety guarantees, which are often a key requirement in real-world tasks. This paper addresses the lack of safety guarantees by extending reinforcement learning with a safety layer that restricts the action space to the subspace of safe actions. We demonstrate the proposed approach using lane changing in autonomous driving. To distinguish safe actions from unsafe ones, we compare planned motions with the set of possible occupancies of traffic participant...    »
Publisher / Institution:
IEEE International Conference on Intelligent Transportation Systems (ITSC)