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| Funder | Vinnova |
|---|---|
| Recipient Organization | University of Gothenburg |
| Country | Sweden |
| Start Date | Sep 01, 2023 |
| End Date | Aug 31, 2026 |
| Duration | 1,095 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | Swedish Research Council |
| Grant ID | 2023-00771_Vinnova |
Purpose and goal:
FAMER will establish concepts, models, and techniques of effectively building requirements knowledge for safe perception systems. FAMER approaches the requirements challenges in a systems-of-systems context, in which several organizations and disciplines (multiple parties) must be brought together and in which the complexity of the system under construction forces an iterative, collaborative approach across disciplines.
Expected results and effects:
FAMER will establish concepts, models, and techniques of effectively building requirements knowledge for safe perception systems, investigating prerequisites for machine learning. Themes of traffic-safe automation addressed by FAMER: - Safe automated vehicles (efficient verification and development methods for safe perception systems)
- Safety for traffic participants within and outside of the vehicle - Enabling methods and techniques for developing safe vehicle automation - Integrating vehicles and infrastructure into safe transportation solutions (indirectly) Approach and implementation:
The project will be coordinated by University of Gothenburg. Other partners include Kognic, RISE, Volvo Cars, and Zenseact, thus covering a highly relevant part of the automotive supply chain and enabling applied research in close contact with companies with relevant core business. A postdoctoral researcher will help to consolidate research across partners:
- A domain description and system reference architecture. - An information model to manage development of requirements knowledge. - Demonstration of integration with multi-party agile work
University of Gothenburg
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