Driving autonomous vehicles safely through a complex urban environment remains a
difficult task. The sensor limitations, as well as the various occlusions in the urban …

Driving through dense urban environments is difficult for autonomous vehicles because they
must reason about the unknown intentions of a large number of road users while also …

Efficient intersection planning is one of the most challenging tasks for an autonomous
vehicle at present. Politeness to other traffic participants and reaction to surrounding …

Autonomous vehicles (AVs) need to interact with other traffic participants who can be either
cooperative or aggressive, attentive or inattentive. Such different characteristics can lead to …

Decision making under uncertainty is a key challenge in automated driving. A source of
uncertainty is the unknown driving behavior of other traffic participants surrounding the …

Behavior planning in urban environments must consider the various existing uncertainties in
an explicit way. This work proposes a behavior planner, based on a POMDP formulation …

Uncertainties in dynamical driving environments are crucial to the decision making and
trajectory planning modules for autonomous vehicles. Without proper handling of such …

On highways, the interaction with surrounding vehicles is very crucial for the decision-
making and planning of autonomous vehicles. However, the multi-modal driving intentions …

Navigating safely through occlusion scenarios remains challenging for Autonomous
Vehicles (AVs) due to onboard sensors with obstructed Fields of View (FoVs). Integrating …

For autonomous vehicles, scene understanding is still one of the major challenges, which
needs to be well handled to avoid jittery decisions and unsmooth trajectories. Furthermore …