In order to protect vulnerable road users (VRUs), such as pedestrians or...
Reinforcement learning (RL) has recently been used for solving challengi...
Decision making under uncertainty can be framed as a partially observabl...
Estimating the current scene and understanding the potential maneuvers a...
Reinforcement learning is nowadays a popular framework for solving diffe...
Behavior planning and decision-making are some of the biggest challenges...
Estimating and understanding the current scene is an inevitable capabili...
In this work, we present LocGAN, our localization approach based on a
ge...
We propose a deep convolutional object detector for automated driving
ap...
Higher level functionality in autonomous driving depends strongly on a
p...
Provable safety is one of the most critical challenges in automated driv...
While motion planning approaches for automated driving often focus on sa...
Trajectory and intention prediction of traffic participants is an import...
Knowledge about the location of a vehicle is indispensable for autonomou...
We present an improved model for MRF-based depth upsampling, guided by i...
Accurate traffic participant prediction is the prerequisite for collisio...