Thanks to their road safety potential, automated vehicles are rapidly becoming a reality. In
the last decade, automated driving has been the focus of intensive automotive engineering …

The personal mobility of the future will be changed significantly by autonomous driving. To
realize this vision, the complex task of trajectory planning needs to be solved. In this article …

We consider a local planner that utilizes model predictive control to locally deviate from a
prescribed global path in response to dynamic environments, taking into account the system …

Reinforcement Learning (RL) methods are regarded as effective for designing autonomous
driving policies. However, even when RL policies are trained to convergence, ensuring their …

Extracted driving behavior of human driven vehicles can benefit the development of various
applications like trajectory prediction or planning, abnormal driving detection, driving …

The choice of the reference point in automated vehicles impacts the vehicle's driving
behavior. However, this influence is often not considered for planning and control tasks. To …

In the joint research project PRORETA 5, building blocks for automated driving in urban
areas have been developed, implemented, and tested. The developed blocks involve an …

Autonomous vehicles need to plan at the task level to compute a sequence of symbolic
actions, such as merging left and turning right, to fulfill people's service requests, where …

Autonomes Fahren wird die persönliche Mobilität der Zukunft maßgeblich verändern. Doch
bis diese Vision Wirklichkeit wird, ist noch einige Forschungs-und Entwicklungsarbeit nötig …