How can we create an organic computing system that improves reliability in automotive networks
while reducing costs?
A promising approach for this is organic computing in distributed systems, specifically within time-triggered automotive networks. The focus is set on developing adaptive mechanisms that enhance system reliability for safety-critical operations in the context of autonomous driving — without relying solely on costly active redundancy. Instead, the project aims to achieve dependable performance while reducing hardware overhead.
Additionally, the applicability of these approaches was evaluated for various automotive functions, paving the way for more efficient and intelligent in-vehicle systems.
The SelfAutoDOC research is funded in part by the Federal Ministry for Economic Affairs and Climate Protection (BMWK) as part of the »Neue Fahrzeug- und Systemtechnologien« (New Vehicle and System Technologies) programme.
PLC2’s contribution to this project was to create redundant and fault-proof networking solutions for on-chip communications.
- High-bandwidth data transfer
- Ensuring data integrity
- Monitoring data integrity
High-Speed Video Data Offloading
- FPGA-based acceleration for high bandwidth processing
- Optimized data paths to prevent bottlenecks (iDMA)
- FPGA based test tools and validation mechanisms for ensuring data correctness
- RAM-based packet filter to prevent network overflow
FPGA-Based and Embedded Development Service
The development of the SelfAutoDOC research project, with our key contributions, was initially focused on automotive applications.
Leveraging our Development Service expertise, the underlying technologies can be adapted and extended for use in robotics, industrial automation, and safety-critical systems — core markets where PLC2 delivers tailored and high-performance FPGA-based solutions.
Other Publications and Research Results
