The University of Gothenburg (GU) plays a key role in FAMER by coordinating the project and contributing across several work packages, with a strong focus on requirements engineering for safe AI-based perception systems.
Project Coordination:
GU coordinates the overall project, supports collaboration among partners, manages project activities, organizes regular meetings, and contributes to dissemination and communication.
Work Package Leadership
WP2: Requirements Representation: GU leads this work package, focusing on methods and representations for capturing, structuring, and tracing requirements for safe perception systems, including functional, non-functional, and safety-related requirements.
WP5: Project Management and Dissemination: GU leads project management and dissemination activities, ensuring coordination, communication of results, and collaboration with related initiatives.
Participation in Other Work Packages
WP1: Shared Language: GU contributes to establishing a shared language and reference information model for safe perception systems.
WP3: Annotation Requirements Verification and Validation: GU supports the definition, verification, and validation of annotation requirements to ensure alignment with system-level goals.
WP4: Multi-Party Requirements Cognition: GU contributes to training materials and focus group research to support the integration of FAMER results into distributed agile development.
Utilisation of the FAMER Scope
GU will use FAMER results to advance research on requirements engineering and architecture for large-scale, safety-critical AI systems. The outcomes will support scientific publications, strengthen teaching in areas such as Advanced Requirements Engineering and AI Engineering, and create synergies with ongoing research in Software Center and RE for AI-based systems.
Zenseact plays an important role in FAMER by supporting collaborative requirements engineering across the automotive value chain and contributing to several work packages.
Work Package Leadership
WP4: Multi-Party Requirements Cognition: Zenseact leads this work package, focusing on how FAMER results can support distributed requirements knowledge and multi-party collaboration in agile automotive development.
Participation in Other Work Packages
WP1: Shared Language: Zenseact contributes to reviewing standards, defining the reference information model, and supporting the architecture description for perception systems.
WP2: Requirements Representation: Zenseact supports the development of requirements representations, methods, and traceability models across the lifecycle.
WP3: Annotation Requirements Verification and Validation: Together with Kognic, Zenseact contributes to defining annotation needs, producing annotated data, and validating whether the data satisfies system-level and safety-related goals.
WP5: Project Management and Dissemination: Zenseact supports coordination, dissemination, and collaboration through active participation in meetings and project activities.
Utilisation of the FAMER Scope
Zenseact will apply the methods and results developed in FAMER to evaluate and improve its way of working for AI-based perception systems. The outcomes are expected to support better iteration, stronger alignment with customers, and more effective development of perception systems within complex systems-of-systems contexts.
Volvo Cars has a central role in FAMER, contributing to multiple work packages and leading the effort to establish a shared foundation for the project.
Work Package Leadership
WP1: Shared Language: Volvo Cars leads this work package, focusing on building a shared language, domain description, reference information model, and architecture description for perception systems.
Participation in Other Work Packages
WP2: Requirements Representation: Volvo Cars contributes to defining requirements representations, specification methods, and traceability across the development process.
WP3: Annotation Requirements Verification and Validation: Volvo Cars works with Kognic and Zenseact to define annotation needs and validate annotated data against system-level goals.
WP4: Multi-Party Requirements Cognition: Volvo Cars supports focus group research and the integration of FAMER results into distributed agile automotive development.
WP5: Project Management and Dissemination: Volvo Cars contributes to project coordination, dissemination, and collaboration activities.
Utilisation of the FAMER Scope
Volvo Cars will benefit from FAMER through improved shared understanding, stronger requirement traceability, and better support for safe perception-system development. The project’s results are expected to contribute to more effective integration of requirements practices in safety-critical automotive product development.
Kognic contributes to FAMER with expertise in annotation processes, annotated data, and validation in safety-critical perception system development.
Work Package Leadership / Key Contribution
WP3: Annotation Requirements Verification and Validation: Kognic plays a central role in this work package by contributing expertise in annotation needs, constraints, data generation, and validation to ensure that annotated data supports system-level and safety-related requirements.
Participation in Other Work Packages
WP1: Shared Language: Kognic contributes to the shared understanding of perception systems and annotation-related concepts.
WP2: Requirements Representation: Kognic supports the representation of annotation-related requirements and their traceability.
WP4: Multi-Party Requirements Cognition: Kognic contributes practical insights into collaboration across multiple stakeholders in the automotive value chain.
WP5: Project Management and Dissemination: Kognic supports dissemination, collaboration, and project coordination activities.
Utilisation of the FAMER Scope
Kognic will use the knowledge and results from FAMER to better guide clients in defining requirements for validation data and ground truth production. The project outcomes will also support improved understanding of requirements for annotation and data tools, enabling more reliable annotations and better iterative collaboration across the ecosystem.
RISE contributes to the FAMER project through research expertise, industrial collaboration, and support for methods related to safe and trustworthy perception systems.
Participation in Work Packages
WP1: Shared Language: RISE supports the development of common concepts, models, and architectural understanding for safe perception systems.
WP2: Requirements Representation: RISE contributes to methods for representing, structuring, and tracing requirements.
WP3: Annotation Requirements Verification and Validation: RISE supports activities related to defining and validating annotation requirements and quality.
WP4: Multi-Party Requirements Cognition: RISE contributes to knowledge sharing, training, and collaboration approaches for multi-party development.
WP5: Project Management and Dissemination: RISE supports dissemination, coordination, and engagement with relevant stakeholders and related initiatives.
Utilisation of the FAMER Scope
RISE will use FAMER results to strengthen its expertise in safety standards, safety assurance, and safe perception systems. The outcomes will support scientific dissemination, improve research and innovation services, and create synergies with national and European projects, especially in vehicle automation and safety-critical AI.