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 …

This paper addresses the problem of future behavior evaluation and planning for upcoming
ADAS, especially for inner city traffic scenarios. Situations in inner city traffic scenarios are …

This paper addresses the problem of risk assessment in dynamic traffic environments for
future behavior evaluation and planning. Risk assessment has to be driven from behavioral …

Risk estimation for the current traffic situation is crucial for safe autonomous driving systems.
The computation of risk estimates however is always uncertain, especially if the behavior of …

The estimation of risk is a central cornerstone in the evaluation of traffic scene situations for
intelligent ADAS. This applies to all levels of functions ranging from simple advices and …

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 …

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 …

In this paper, we use the concept of artificial risk fields to predict how human operators
control a vehicle in response to upcoming road situations. A risk field assigns a non …

Vehicles will be equipped with sensors and functions for highly automated driving in the
foreseeable future. A big topic of research on the way to this goal is how to convey to these …

Operation in a real world traffic requires the ability to plan motion in complex environments
(multiple moving participants) from autonomous vehicles. Navigation through such …