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 …

In this paper, we present a motion planning algorithm for autonomous navigation in highly
constrained urban environments. Since common approaches to on-road trajectory planning …

Autonomous vehicles must be able to react in a timely manner to typical and unpredictable
situations in urban scenarios. In this connection, motion planning algorithms play a key role …

The vision of autonomous driving is piecewise becoming reality. Still the problem of
executing the driving task in a safe and comfortable way in all possible environments, for …

Recent road trials have shown that guaranteeing the safety of driving decisions is essential
for the wider adoption of autonomous vehicle technology. One promising direction is to pose …

This paper focuses on the problem of trajectory planning in an autonomous guidance
application for one-way, two-lane roads. The problem is formulated in a receding horizon …

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 …

In the last decades, a large variety of robot motion planners emerged. However,
manoeuvring in very narrow environments, eg, for common parking scenarios, cannot be …

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 …

Autonomous driving in urban environments depends on the ability to interpret the current
situation and to react accordingly. This means to continuously make decisions for certain …