This paper presents a practical trajectory planning framework towards fully autonomous
driving in urban environments. Firstly, based on the behavioral decision commands, a …

This study proposes a new integrated approach to the motion control of autonomous
vehicles, which differs from the conventional method of treating planning and tracking tasks …

Trajectory planning plays a crucial role in autonomous driving systems, as it is tasked to
generate feasible trajectories under highly dynamic scenarios within the time constraint. This …

There are few open source autonomous driving planners that are general enough to be
used directly, or which could be easily customized to suit a particular application …

The Volkswagen AutoUni offers scientists and PhD students of the Volkswagen Group the
opportunity to publish their scientific results as monographs or doctor's theses within the …

In this paper, we develop a motion planner for on-road autonomous swerve maneuvers that
is capable of learning passengers' individual driving styles. It uses a hybrid planning …

Trajectory planning methods for on-road autonomous driving are commonly formulated to
optimize a Single Objective calculated by accumulating Multiple Weighted Feature terms …

Velocity planning on a path to be followed by a wheeled autonomous vehicle may be difficult
when high curvatures and velocities are allowed. A fast, straightforward algorithm to address …

Laser Guided Vehicles (LGV) are largely used in industrial contexts for the autonomous
dispatching of huge loads. LGVs of automated warehouses are driven by supervisory …

This paper presents a framework for generating explicit quintic polynomial curves as the
trajectory of autonomous vehicles. The method is called SCR-Normalize and is founded on …