This article describes a method for real-time integrated motion planning and control aimed at
autonomous vehicles. Our method leverages feedback control, positive invariant sets, and …

This paper develops a method for safe lane changes. We leverage feedback control and
constraint-admissible positively invariant sets to guarantee collision-free closed-loop …

This paper discusses some of the current state-of-the-art and remaining challenges in
research on path planning and vehicle control of autonomous vehicles. Reliable path …

High-end vehicles are already equipped with safety systems, such as assistive braking and
automatic lane following, enhancing vehicle safety. Yet, these current solutions can only …

Motion planning for autonomous vehicles requires spatio-temporal motion plans (ie state
trajectories) to account for dynamic obstacles. This requires a trajectory tracking control …

Current state-of-the-art vehicle safety systems, such as assistive braking or automatic lane
following, are still only able to help in relatively simple driving situations. We introduce a …

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 …

This paper adapts the invariant-set motion-planner to systems with unicycle-like dynamics.
The invariant-set motion-planner is a motion-planning algorithm that uses the positive …

This article presents a non-optimization-based framework for path planning and tracking for
evasive maneuvers in autonomous cars. The framework exploits a two-layer approach …

In this paper a generic framework for sampling-based partial motion planning along a
reference path is presented. The sampling mechanism builds on the specification of a …