… the safe operation of autonomous vehicles … learning of lane keeping for autonomous cars
[89]. Recently, researchers have now started working on utilizing deep reinforcement learning (…

… deep-reinforcement-learning approaches. We demonstrate the effectiveness of our approach
by testing a highly automated vehicle … vehicles with physical road infrastructure and a real …

… on autonomous driving (AD), improving driving safety while … Recently, deep learning (DL)
approaches have solved … -of-theart strategies for safe AD, with their major achievements and …

… 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 …

… of autonomous vehicles, with a special focus on software. One of the major challenges we
further elaborate on is using machine learning … guaranteeing safety in autonomous vehicles as …

… The motion control is done by way of steering control & suitable acceleration to produce
safe motion paths for the automated vehicle. The principle of nominal interference decides the …

… 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. …

… Peng, “Safe reinforcement learning for autonomous vehicles through parallel constrained
policy optimization,” 2020, arXiv:2003.01303. [Online]. Available: http://arxiv.org/abs/…

… a car-following model for autonomous velocity control based on reinforcement learning (RL)…
This model directly optimizes driving safety, efficiency, and comfort, by learning from …

… introduce— before autonomous vehicles enter our roads in large numbers. In mixed … deep
learning-based traffic safety solution to support a mixture of autonomous and manual vehicles …