Out-of-distribution lane detector on a low-cost cyber-physical AV test bed - Gan, Shyan (Nanyang Technological University, 2023)
Safety and reliability are major challenges for machine learning systems deployed on safety critical real-time Cyber-Physical Systems (CPSs). One critical task is to monitor when testing data distribution shifts away from the distribution of training data, which may lead to erratic and unsafe outputs from the machine learning systems. Much progress has been made on Out-of-Distribution (OOD) detectors which are used to separate In-Distribution (ID) data from OOD data. Deep neural network based Variational Autoencoder (VAE) detectors are especially promising on CPS with limited computational resources which also require short inference times