Connected automated vehicles have shown great potential to improve the
e...
Accomplishing safe and efficient driving is one of the predominant chall...
This paper considers mixed traffic consisting of connected automated veh...
A novel way of using neural networks to learn the dynamics of time delay...
This work presents a theoretical framework for the safety-critical contr...
Balancing safety and performance is one of the predominant challenges in...
Safe longitudinal control is discussed for a connected automated truck
t...
This work gives introduction to traffic control by connected automated
v...
Bringing dynamic robots into the wild requires a tenuous balance between...
Endowing nonlinear systems with safe behavior is increasingly important ...
We take the first step in using vehicle-to-vehicle (V2V) communication t...
Dealing with high variance is a significant challenge in model-free
rein...
Reinforcement Learning (RL) algorithms have found limited success beyond...