Research Projects

CentralCarServer (CeCaS)

Supercomputing for Automotive

Start: 12/2022

End: 11/2025

Vehicle automation and networking create new opportunities for mobility. At the same time, the amount of data and functions in vehicles is increasing rapidly and needs to be processed in near real-time and in a safety-qualifiable manner. The high demands on computing power, flexibility and efficiency require new approaches in microelectronics as well as in computing and software architecture.

Developing a supercomputing platform for highly automated vehicles is the mission of the CeCaS project. The aim is to handle complex calculations and large data volumes in the car.

The central computing unit will be based on innovative high-performance automotive-qualified processors. Application-specific hardware accelerators and a real-time-capable software platform will complement the processors.

Role of the FZI in the CeCas project

In the CeCaS project, the FZI Research Center for Information Technology is working on the analysis of distributed and central EE on-board networks with a focus on neuromorphic AI accelerators and real-time capable software platforms for the CentralCarServer:

  • The FZI is designing a neuromorphic accelerator for processing sensor data from an automotive radar using spiking neural networks. The researchers are also investigating how neuromorphic training methods can be specially adapted for this hardware to optimize efficiency further. In doing so, the FZI is directly contributing to the project goal of improving the performance of accelerators.
  • The FZI is working on concepts and mechanisms for the real-time execution of AI functions. Here, the technologies between the hardware and application layers are examined (hardware abstraction, firmware, hypervisor, virtualization, runtime environment, etc.). The aim is to enable real-time, efficient, and transparent use of hardware resources. The connection of particular processors or hardware accelerators is vital in this context. With this, the FZI contributes to the project goal of integrating the software platform for the Central Car Server.


Dr- Ing. Victor Pazmino Betancourt

Vice Division Manager
Embedded Systems and Sensors Engineering

Research Focus

Applied Artificial Intelligence

In this research focus of the FZI, the emphasis is on Human-centered Artificial Intelligence and Artificial Intelligence for prediction. The FZI also addresses questions on dedicated AI hardware and AI engineering.

Intelligent Transportation Systems and Logistics

Intelligent solutions for transporting people and goods are a focus of FZI application research. The focus here is on public transport, the application of artificial intelligence, further development of vehicle functions and their security, as well as on Open Source & Open Data.

Funding notice:
The CeCaS joint project is funded by the Federal Ministry of Education and Research (BMBF).

Project partners:

Over 25 partners from science and industry

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