In this article, we present an efficient planning system for automated vehicles in highly
interactive environments (EPSILON). EPSILON is an efficient interaction-aware planning …

Generating safe and non-conservative behaviors in dense, dynamic environments remains
challenging for automated vehicles due to the stochastic nature of traffic participants' …

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 …

Automated driving requires decision making in dynamic and uncertain environments. The
uncertainty from the prediction originates from the noisy sensor data and from the fact that …

Motion planning algorithms for urban automated driving must handle uncertainty due to
unknown intention and future motion of Dynamic Obstacles (DOs). Considering a single …

Recently, automated driving has more and more been transformed from an exciting vision
into hands on reality by prototypes. While drivers are used to assistance and maybe even …

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 …

To reduce the number of collision fatalities at crossroads intersections, many countries have
started replacing intersections with non-signalized roundabouts, forcing the drivers to be …

Recently significant progress has been made in vehicle prediction and planning algorithms
for autonomous driving. However, it remains quite challenging for an autonomous vehicle to …

Path planning is an essential function in an intelligent vehicle, especially when driving in
scenarios cluttered by large-scale static obstacles. Traditional path planners often struggle …