Uncertainty-aware model-based reinforcement learning: Methodology and application in autonomous driving
… is proposed and validated in autonomous driving scenarios in this … ’s learning efficiency
and performance. The proposed method is then implemented in end-to-end autonomous vehicle …
and performance. The proposed method is then implemented in end-to-end autonomous vehicle …
Highway exiting planner for automated vehicles using reinforcement learning
… In this paper, we proposed an RL-enhanced planner for autonomous vehicle exiting a highway
… In the proposed planner, reinforcement learning is used to form the basic framework and …
… In the proposed planner, reinforcement learning is used to form the basic framework and …
Combining planning and deep reinforcement learning in tactical decision making for autonomous driving
… of planning and learning, in the form of Monte Carlo tree search and deep reinforcement
learning. … & AI, and control theory, applied to human robot interaction and autonomous vehicles. …
learning. … & AI, and control theory, applied to human robot interaction and autonomous vehicles. …
Robustness and adaptability of reinforcement learning-based cooperative autonomous driving in mixed-autonomy traffic
… mixed-autonomy problem as a multi-agent reinforcement learning (… autonomous vehicles,
reinforcement learning, computer vision, and deep learning with a focus on the autonomous …
reinforcement learning, computer vision, and deep learning with a focus on the autonomous …
Deep reinforcement learning for autonomous internet of things: Model, applications and challenges
… in autonomous driving, images from an autonomous vehicle’s … In this case, the agent should
reside locally in the vehicle to … autonomous systems, ie, autonomous robots, smart vehicles, …
reside locally in the vehicle to … autonomous systems, ie, autonomous robots, smart vehicles, …
Enhancing mixed traffic flow safety via connected and autonomous vehicle trajectory planning with a reinforcement learning approach
… -driven vehicle (HDV), however, is not well understood yet. This study presents … reinforcement
learning modeling approach, named Monte Carlo tree search-based autonomous vehicle …
learning modeling approach, named Monte Carlo tree search-based autonomous vehicle …
Tactical decision-making in autonomous driving by reinforcement learning with uncertainty estimation
… Reinforcement learning Reinforcement learning is a subfield of machine learning, where an
… with autonomous vehicles using deep reinforcement learning,” in IEEE Int. Conf. on Robot. …
… with autonomous vehicles using deep reinforcement learning,” in IEEE Int. Conf. on Robot. …
Cooperative perception with deep reinforcement learning for connected vehicles
… Rus, “The impact of cooperative perception on decision making and planning of
autonomous vehicles,” IEEE Intelligent Transportation Systems Magazine, vol. 7, no. 3, pp. …
autonomous vehicles,” IEEE Intelligent Transportation Systems Magazine, vol. 7, no. 3, pp. …
Model-based reinforcement learning for eco-driving control of electric vehicles
… using reinforcement learning was applied to the eco-driving problem for electric vehicles …
use of autonomous vehicles can also contribute to increasing the vehicular fuel efficiency. In …
use of autonomous vehicles can also contribute to increasing the vehicular fuel efficiency. In …
Jamming and eavesdropping defense scheme based on deep reinforcement learning in autonomous vehicle networks
… rity challenges in Connected and Autonomous Vehicles (CAVs) network. Our work considers
the use of Distributed Kalman Filtering (DKF) and Deep Reinforcement Learning (DRL) tech…
the use of Distributed Kalman Filtering (DKF) and Deep Reinforcement Learning (DRL) tech…