Reinforcement Learning for Online Testing of Autonomous Driving Systems: a Replication and Extension Study

arXiv:2403.13729v1 Announce Type: cross
Abstract: In a recent study, Reinforcement Learning (RL) used in combination with many-objective search, has been shown to outperform alternative techniques (random search and many-objective search) for online testing of Deep Neural Network-enabled systems. The empirical evaluation of these techniques was conducted on a state-of-the-art Autonomous Driving System (ADS). This work is a replication and extension of that empirical study. Our replication shows that RL does not outperform pure random test generation in a comparison conducted …

abstract arxiv autonomous autonomous driving autonomous driving systems combination cs.ai cs.lg cs.ro cs.se deep neural network driving evaluation extension network neural network random reinforcement reinforcement learning replication search study systems testing type