Self-evolution is indispensable to realize full autonomous driving. This...
In this paper, we propose a new reinforcement learning (RL) algorithm, c...
Autonomous driving at intersections is one of the most complicated and
a...
Safety is essential for reinforcement learning (RL) applied in the real
...
The safety constraints commonly used by existing safe reinforcement lear...
Decision and control are two of the core functionalities of high-level
a...
State estimation is critical to control systems, especially when the sta...
Merging into the highway from the on-ramp is an essential scenario for
a...
Model information can be used to predict future trajectories, so it has ...
Reinforcement learning (RL) has great potential in sequential
decision-m...
Safety is essential for reinforcement learning (RL) applied in real-worl...
Reinforcement learning has shown great potential in developing high-leve...
Safety constraints are essential for reinforcement learning (RL) applied...
The uncertainties in plant dynamics remain a challenge for nonlinear con...
Reinforcement learning (RL) has achieved remarkable performance in a var...
With the rapid development of digital multimedia, video understanding ha...
In current reinforcement learning (RL) methods, function approximation e...
Reinforcement learning (RL) algorithms have been successfully applied to...
Connected vehicles will change the modes of future transportation manage...