… and autonomous vehicles is a disruptive technology that has the potential to transform the
current transportation system by reducing traffic accidents and enhancing driving safety. One …

… in the field of deep learning and impressive performance of deep neural networks (DNNs) …
demand for their use in automated driving (AD) systems. The safety of such systems is of …

… In this paper we apply deep reinforcement learning to the problem of forming long term
driving strategies. We note that there are two major challenges that make autonomous driving …

… In this article, a safe motion planning algorithm for autonomous vehicles is developed by
combining the method, which utilizes a neural network to predict collision probability with the …

… the safety of highly automated driving functions which make use of machine learning …
considerations when applying machine learning methods for highly automated driving. Particular …

… safety evaluation, we design 10 driving routes for each safety-critical scenario. Each driving
route … We particularly focus on reinforcement learning-based self-driving methods, since they …

… Testing and validation on these data sets thus also provide a measurement of robustness
of detection techniques including the machine learning algorithms we propose and test in …

… To ensure driving safety, we proposed a lane change … deep reinforcement learning to find
a risk-aware driving decision strategy with the minimum expected risk for autonomous driving. …

… deep learning approaches solve the safety problems in the interaction between autonomous
vehicles … and identify safe interactions between autonomous vehicles and pedestrians. …

… We believe that autonomous vehicles will bring many ben… research challenges to the artificial
intelligence community. In this … a safe system, we suggested Bayesian deep learning which …