The computational effort of trajectory planning for automated vehicles often increases with
the complexity of the traffic situation. This is particularly problematic in safety-critical …

This paper presents a framework for fast and robust motion planning designed to facilitate
automated driving. The framework allows for real-time computation even for horizons of …

Motion planning of automated vehicles requires dynamical models to ensure that obtained
trajectories are drivable. An often overlooked aspect is that motion planning is usually done …

Formally verified methods for motion planning are required in order to guarantee safety for
autonomous vehicles. In particular, we consider trajectory generation by considering the …

Intelligent vehicles have increased their capabilities for highly and, even fully, automated
driving under controlled environments. Scene information is received using onboard …

Numerical experiments for motion planning of road vehicles require numerous components:
vehicle dynamics, a road network, static obstacles, dynamic obstacles and their movement …

Predicting the movement of other traffic participants is an integral part in the motion planning
of most automated road vehicles. While simple predictions, eg based on assuming constant …

Self-driving vehicles will soon be a reality, as main automotive companies have announced
that they will sell their driving automation modes in the 2020s. This technology raises …

The safety validation of motion planning algorithms for automated vehicles requires a large
amount of data for virtual testing. Currently, this data is often collected through real test …

Safe motion planning for autonomous vehicles is a challenging task, since the exact future
motion of other traffic participant is usually unknown. In this article, we present a verification …