Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patterns

arXiv:2404.07685v1 Announce Type: new
Abstract: Monitoring the integrity of object detection for errors within the perception module of automated driving systems (ADS) is paramount for ensuring safety. Despite recent advancements in deep neural network (DNN)-based object detectors, their susceptibility to detection errors, particularly in the less-explored realm of 3D object detection, remains a significant concern. State-of-the-art integrity monitoring (also known as introspection) mechanisms in 2D object detection mainly utilise the activation patterns in the final layer of the DNN-based detector's …

3d object 3d object detection abstract ads arxiv automated cs.ai cs.cv cs.ro deep neural network detection detectors dnn driving errors integrity layer monitoring network neural network object patterns perception safety systems type