PARallele Implementierungs-Strategien für das Hochautomatisierte Fahren "PARIS" Förderprogramm "IKT 2020 – Elektroniksysteme für das vollautomatisierte Fahren (ELEVATE) des Bundesministeriums für Bildung und Forschung (BMBF)
Automated and interconnected driving is an essential ingredient of future intelligent and sustainable mobility. The implementation of fully automated driving functions especially depend on technological advances in electronics and sensory technology. Moreover, advanced driver assistance systems require real-time capable implementations of complex sensor fusion algorithms on energy-efficient platforms to reliably assess the driving and traffic situation.
Objectives and Methodological Approach
In this project, a novel parallel processor platform with optimized processor cores will be developed. Complex and computationally intensive sensor fusion algorithms shall be mapped on this platform. In particular, innovative algorithms from the field of machine learning shall be developed and applied. In order to efficiently model such algorithms, programming and verification methods based on virtual prototyping, among others, shall be developed. At the end of the project, the developed and implemented algorithms will be presented in a demonstrator vehicle in a real driving situation.
The algorithmic approaches developed in PARIS represent an important basis for scene reconstruction and interpretation. The implementation of these systems on the novel parallel platform developed in the project will pave the way for future high-performance systems for automated driving.
- Leibniz Universität Hannover
- NISYS GmbH
- Silexica GmbH
- Technische Universität Dresden
- BASELABS GmbH
- videantis GmbH
- Robert Bosch GmbH
- Elektrobit Automotive GmbH
- RWTH Aachen: ika, CVG, ICE