Dynamically changing environments, unreliable state estimation, and operation under
severe resource constraints are fundamental challenges that limit the deployment of small …

This study develops an autonomous vehicle control method that enables it to perform a drift
maneuver which is an expert driving technique consisting of sliding the rear wheel …

Autonomous vehicles will generate data from the variety of sensors they employ to track the
surrounding environment. This data is inherently valuable, as it gives algorithm designers …

One of the key aspects in racing is the ability of the driver to find the handling limits of the
vehicle to minimize the resulting lap time. Many approaches for raceline optimization …

A model-based, data-driven control framework is introduced within the context of
autonomous driving in this study. We propose a data-driven control algorithm that combines …

In every timed car race, the goal is to drive through the racing track as fast as possible. The
total time depends on selection of the racing line. Following a better racing line often …

Technological advancements have positively impacted the automotive industry, leading to
the development of autonomous cars, which aim to minimize human intervention during …

A model-based, data-driven control framework is introduced within the context of
autonomous driving in this study. We propose a data-driven control algorithm that combines …

Der Beitrag beschreibt eine zeitoptimale Trajektorienplanung, die eine simultane Quer-und
Längsplanung auf Basis eines nichtlinearen Einspurmodells durchführt. Das …

Um ein Gesamtsystem zum automatisierten Fahren bis in den fahrdynamischen
Grenzbereich zu entwickeln und zu testen, eignet sich eine zeitoptimale …