Autonomous driving is a disrupting technology that is expected to reshape transportation
systems. The benefits of autonomous vehicles include, but are not limited to, safer …

This thesis focuses on motion planning algorithms for self-driving heavy-duty vehicles.
Motion planning is a fundamental part of autonomous vehicles, tasked with finding the …

Lattice-based motion planners are an established method to generate feasible motions for
car-like vehicles. However, the solution paths can only reach a discretized approximation of …

Autonomous driving has transformed road safety and navigation, alleviating the annual toll
of accidents caused by human errors. Motion planning, a critical aspect of this technology …

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 …

Lattice-based planning techniques simplify the motion planning problem for autonomous
vehicles by limiting available motions to a pre-computed set of primitives. These primitives …

Motion planning is essential for an autonomous vehicle to perform safe and human-like
driving behaviors, especially in highly dynamic scenarios such as dense urban and highway …

The Institute of Measurement, Control, and Microtechnology at Ulm University has
investigated advanced driver assistance systems for decades and concentrated, in large …

In this paper, we propose a framework for generating motion primitives for lattice-based
motion planners automatically. Given a family of systems, the user only needs to specify …

The deployment of future self-driving vehicles is expected to have a major socioeconomic
impact due to their promise to be both safer and more traffic-efficient than human-driven …