European UnionNon-profit, Private Business, Research Institution, Public Institution
Approaches, verification and training for Edge-AI building blocks for CCAM Systems (CCAM Partnership)
HORIZON-CL5-2026-01-D6-05
Funding Amount
€4.0M - €4.0M
Deadline
20/01/2026
Eligible Organization Types
Non-profit, Private Business, Research Institution, Public Institution
Trusted by
What is the Approaches, verification and training for Edge-AI building blocks for CCAM Systems (CCAM Partnership) Call?
Grant Description
This Horizon Europe Research and Innovation Action aims to develop and demonstrate optimized edge artificial intelligence solutions for connected, cooperative and automated mobility. It addresses limitations of general-purpose hardware by tailoring AI models for edge computing in safety-critical vehicle applications, reducing power consumption, latency, and improving speed, accuracy, security and privacy. Projects will cover the full chain from sensing and perception to decision making and actua...
Required Results for Successful Funding
Expected Outcomes
Project results are expected to contribute to:
• CCAM hardware and software solutions with reduced power consumption, lower latency, and improved processing speed and AI accuracy, by adapting sector-agnostic AI/cloud-edge-IoT advancements for CCAM.
• Enhanced levels of safety, cybersecurity, privacy and ethical standards in data-driven CCAM functionalities through edge-AI applications.
• Well-balanced distribution of AI computation across edge, cloud and in-vehicle systems, optimising trade-offs between speed, latency, energy use, cost, data sharing and storage.
• Validated approaches for integrating edge-AI into the full action chain (perception → decision-making → actuation) for advanced CCAM, both on-board vehicles and on infrastructure (e.g. traffic management, remote control).
• Tools and methodologies for training, verifying and optimising edge-AI models to ensure they meet safety-critical performance requirements in CCAM contexts.
• CCAM hardware and software solutions with reduced power consumption, lower latency, and improved processing speed and AI accuracy, by adapting sector-agnostic AI/cloud-edge-IoT advancements for CCAM.
• Enhanced levels of safety, cybersecurity, privacy and ethical standards in data-driven CCAM functionalities through edge-AI applications.
• Well-balanced distribution of AI computation across edge, cloud and in-vehicle systems, optimising trade-offs between speed, latency, energy use, cost, data sharing and storage.
• Validated approaches for integrating edge-AI into the full action chain (perception → decision-making → actuation) for advanced CCAM, both on-board vehicles and on infrastructure (e.g. traffic management, remote control).
• Tools and methodologies for training, verifying and optimising edge-AI models to ensure they meet safety-critical performance requirements in CCAM contexts.
Funded areas
Scope Requirements
Projects must address all of the following:
1. Embedding large, complex AI models into resource-constrained edge hardware for CCAM, reshaping approaches and building blocks to meet size, power and real-time constraints.
2. Demonstrate use cases focused on time-critical chains of collective perception, decision-making and actuation, using real-world CCAM datasets (e.g. SYNERGIES) and linked to AI4CCAM and AIthena results.
3. Optimise edge-AI models for deployment: apply model quantisation, pruning, knowledge distillation; develop training and verification workflows; implement OTA update strategies.
4. Develop edge-AI model monitoring and management tools to ensure resilience, detect failures or attacks, and validate output accuracy under changing conditions.
5. Incorporate cybersecurity measures, robust connectivity solutions and full compliance with GDPR, data protection rules, ethical standards, explainable AI principles and the EU AI Act; account for gender and other social categories where relevant.
6. Leverage existing SDVoF building blocks, interfaces and tools; consider complementarities with Cluster 4 “Digital Industry and Space” projects and JRC’s Sustainable, Smart and Safe Mobility Unit activities.
7. Organise formal reporting to the CCAM Partnership, apply the EU-CEM methodology for impact assessment, and contribute to Partnership KPI monitoring.
8. Plan for and engage in international cooperation, particularly with Japan, the United States and other strategic partners in third countries.
1. Embedding large, complex AI models into resource-constrained edge hardware for CCAM, reshaping approaches and building blocks to meet size, power and real-time constraints.
2. Demonstrate use cases focused on time-critical chains of collective perception, decision-making and actuation, using real-world CCAM datasets (e.g. SYNERGIES) and linked to AI4CCAM and AIthena results.
3. Optimise edge-AI models for deployment: apply model quantisation, pruning, knowledge distillation; develop training and verification workflows; implement OTA update strategies.
4. Develop edge-AI model monitoring and management tools to ensure resilience, detect failures or attacks, and validate output accuracy under changing conditions.
5. Incorporate cybersecurity measures, robust connectivity solutions and full compliance with GDPR, data protection rules, ethical standards, explainable AI principles and the EU AI Act; account for gender and other social categories where relevant.
6. Leverage existing SDVoF building blocks, interfaces and tools; consider complementarities with Cluster 4 “Digital Industry and Space” projects and JRC’s Sustainable, Smart and Safe Mobility Unit activities.
7. Organise formal reporting to the CCAM Partnership, apply the EU-CEM methodology for impact assessment, and contribute to Partnership KPI monitoring.
8. Plan for and engage in international cooperation, particularly with Japan, the United States and other strategic partners in third countries.
Additional Conditions for Applicants
Special Conditions
- This topic implements the co-programmed European Partnership on CCAM; projects must report results in support of Partnership KPI monitoring.
• Projects are required to apply the European Common Evaluation Methodology (EU-CEM) for CCAM.
• Grant format: HORIZON Lump Sum Grant (HORIZON-AG-LS), single-stage deadline.
• Solutions should reuse, where feasible, SDVoF initiative building blocks, interfaces and software tools.
• Full compliance with GDPR, the EU AI Act, Explainable AI requirements, and intersectional considerations (gender, disability, age, socioeconomic status, ethnic origin, etc.).
• International cooperation is strongly encouraged (notably with Japan, USA and other strategic third-country partners).
• Projects are encouraged to establish formal collaboration with the European Commission’s Joint Research Centre’s Sustainable, Smart and Safe Mobility Unit.
• Complementarity with Cluster 4 “Digital Industry and Space” projects is expected, particularly for translating sector-agnostic innovations to CCAM specifics.
• Projects are required to apply the European Common Evaluation Methodology (EU-CEM) for CCAM.
• Grant format: HORIZON Lump Sum Grant (HORIZON-AG-LS), single-stage deadline.
• Solutions should reuse, where feasible, SDVoF initiative building blocks, interfaces and software tools.
• Full compliance with GDPR, the EU AI Act, Explainable AI requirements, and intersectional considerations (gender, disability, age, socioeconomic status, ethnic origin, etc.).
• International cooperation is strongly encouraged (notably with Japan, USA and other strategic third-country partners).
• Projects are encouraged to establish formal collaboration with the European Commission’s Joint Research Centre’s Sustainable, Smart and Safe Mobility Unit.
• Complementarity with Cluster 4 “Digital Industry and Space” projects is expected, particularly for translating sector-agnostic innovations to CCAM specifics.
Important dates
Open from: 16/09/2025
Deadline:20/01/2026
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