Safe and Generalized end-to-end Autonomous Driving System with Reinforcement Learning and Demonstrations

arXiv:2401.11792v5 Announce Type: replace-cross
Abstract: An intelligent driving system should be capable of dynamically formulating appropriate driving strategies based on the current environment and vehicle status, while ensuring the security and reliability of the system. However, existing methods based on reinforcement learning and imitation learning suffer from low safety, poor generalization, and inefficient sampling. Additionally, they cannot accurately predict future driving trajectories, and the accurate prediction of future driving trajectories is a precondition for making optimal decisions. To solve these …

abstract arxiv autonomous autonomous driving autonomous driving system cs.ai cs.lg cs.ro current driving environment generalized however imitation learning intelligent low reinforcement reinforcement learning reliability security strategies type