To operate reliably in real-world traffic, an autonomous car must evaluate the consequences
of its potential actions by anticipating the uncertain intentions of other traffic participants. This …

This paper reports on an integrated inference and decision-making approach for
autonomous driving that models vehicle behavior for both our vehicle and nearby vehicles …

Real-world autonomous driving in city traffic must cope with dynamic environments including
other agents with uncertain intentions. This poses a challenging decision-making problem …

When driving in urban environments, an autonomous vehicle must account for the
interaction with other traffic participants. It must reason about their future behavior, how its …

Interpretation of common-yet-challenging inter-action scenarios can benefit well-founded
decisions for autonomous vehicles. Previous research achieved this using their prior …

Automated driving systems need to perform according to what human drivers expect in every
situation. A different behavior can be wrongly interpreted by other human drivers and cause …

Given the current capabilities of autonomous vehicles, one can easily imagine autonomous
vehicles being released on the road in the near future. However, it can be assumed that this …

Merge scenarios confront drivers with some of the most complicated driving maneuvers in
every day driving, requiring anticipatory reasoning of positions of other vehicles, and the …

Cooperative driving behavior is essential for driving in traffic, especially for ramp merging,
lane changing or navigating intersections. Autonomous vehicles should also manage these …

Autonomous vehicles need to perform social accepted behaviors in complex urban
scenarios including human‐driven vehicles with uncertain intentions. This leads to many …