One exciting challenge for future scientists and engineers will be to contribute to the
development and introduction of self-driving cars. Under the objective of making young …

The Carolo-Cup 1 is an annual international student competition in the field of automated
driving. Inspired from the Darpa Urban Challenge in 2007, interdisciplinary student teams …

Nonlinear manifold embedding has attracted considerable attention due to its highly-desired
property of efficiently encoding local structure, ie intrinsic space properties, into a low …

Engineering software for smart cyber-physical systems (sCPS) challenges developers as
they have to deal with uncertain and volatile stimuli data perceived by sensors. Regression …

In modern vehicles a variety of sensors like radar, camera and lidar are combined in order to
precisely sense the environment. This data is utilized by advanced driver assistance …

Artificial Intelligence (AI) methods need to be evaluated thoroughly to ensure reliable
behavior. In applications like autonomous driving, a complex environment with an …

In this paper we look at Deep Learning methods using TensorFlow for autonomous driving
tasks. Using scale model vehicles in a traffic scenario similar to the Audi Autonomous …

In the current state of autonomous driving machine learning methods are dominating,
especially for the environment recognition. For such solutions, the reliability and the …

Einparken, Vorfahrt gewähren, den Fahrstreifen wechseln und ihm folgen, auch wenn keine
Markierungen vorhanden sind: Das ist nur ein kleiner Ausschnitt an Szenarien, mit denen …

Autonomes oder teilautonomes Fahren im Miniaturmaßstab erfordert auf geringen Platz und
eingeschränkte Ressourcen spezialisierte Mechanik, Elektronik sowie Soft-und Hardware …