This paper presents a method for high-level decision making in traffic environments. In
contrast to the usual approach of modeling decision policies by hand, a Markov Decision …

As automated vehicles begin operating on complex urban roads, precise decision making
for automated driving has been increasingly important for safe automated driving. In …

To act intelligently in dynamic environments, a system must understand the current situation
it is involved in at any given time. This requires dealing with temporal context, handling …

This paper addresses the problem of future behavior evaluation and planning for ADAS in
general traffic situations. Complex traffic situations require the estimation of future behavior …

Safety applications at road intersections require algorithms that can estimate the manoeuvre
intention of all the drivers in the scene. In this paper, the use of contextual information …

Estimating and predicting traffic situations over time is an essential capability for
sophisticated driver assistance systems and autonomous driving. When longer prediction …

In recent years, automated driving has gained the public spotlight as more prototypes are
tested amongst human drivers. Since driving is a social behavior, automated vehicles (AVs) …

This paper presents a filter that is able to simultaneously estimate the behaviors of traffic
participants and anticipate their future trajectories. This is achieved by recognizing the type …

The design of advanced driver assistance systems always aims at enabling the driver to
master today's traffic in a more safe and comfortable way. In order to judge the risks in a …

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 …