What Matters to Enhance Traffic Rule Compliance of Imitation Learning for Automated Driving

arXiv:2309.07808v2 Announce Type: replace-cross
Abstract: More research attention has recently been given to end-to-end autonomous driving technologies where the entire driving pipeline is replaced with a single neural network because of its simpler structure and faster inference time. Despite this appealing approach largely reducing the components in the driving pipeline, its simplicity also leads to interpretability problems and safety issues. The trained policy is not always compliant with the traffic rules and it is also hard to discover the reason …

arxiv automated compliance cs.ai cs.cv cs.lg cs.ro driving imitation learning traffic type