Deadline: 08-Oct-2026
The Generative AI for Smarter CCAM initiative is a Horizon Europe funding opportunity supporting the development of Connected, Cooperative and Automated Mobility (CCAM) systems through advanced Generative AI technologies. With a total budget of €13 million, the program aims to improve automated vehicle perception, decision-making, safety, testing, validation, and interaction with vulnerable road users while promoting trustworthy, transparent, and energy-efficient AI solutions.
The initiative encourages the integration of Large Language Models (LLMs), Vision Language Models (VLMs), and other Generative AI technologies into automated mobility systems to enhance road safety, transport resilience, interoperability, and sustainable transportation across Europe.
Funding Overview
- Program: Generative AI for Smarter Connected, Cooperative and Automated Mobility (CCAM)
- Funding Organization: European Commission
- Framework: Horizon Europe
- Total Budget: €13,000,000
- Indicative Funding per Project: Approximately €6,500,000
- Project Type: Research and Innovation Action
- Geographic Scope: International
- Eligible Applicants: Any legal entity meeting Horizon Europe requirements
What is the Generative AI for Smarter CCAM Initiative?
The initiative supports research, development, testing, and deployment of Generative AI technologies within Connected, Cooperative and Automated Mobility systems.
The goal is to improve how automated vehicles perceive their surroundings, understand complex traffic situations, interact with road users, make decisions, and respond safely under changing conditions.
Projects are expected to develop AI-powered tools, methodologies, and validation frameworks that strengthen the performance, safety, and reliability of automated mobility solutions operating in real-world environments.
Key Focus Areas
The initiative supports projects focused on:
- Generative AI for automated mobility
- Connected and Automated Vehicles (CAVs)
- Cooperative mobility systems
- Autonomous driving technologies
- Environment perception systems
- Decision-making and reasoning
- Vulnerable Road User (VRU) protection
- Scenario generation and simulation
- Vehicle testing and validation
- Edge computing applications
- AI-powered traffic management
- Cybersecurity and resilience
- Energy-efficient AI systems
- Large Language Models (LLMs)
- Vision Language Models (VLMs)
- Vision Language Action (VLA) systems
- AI governance and ethics
- Software-defined vehicles
- Smart mobility ecosystems
Programme Objectives
The initiative aims to:
- Improve perception capabilities of automated vehicles
- Enhance decision-making in complex environments
- Increase safety for Vulnerable Road Users
- Strengthen automated vehicle validation processes
- Develop realistic AI-generated testing scenarios
- Improve operational reliability and resilience
- Reduce latency and energy consumption
- Enhance cybersecurity and privacy
- Promote trustworthy AI deployment
- Improve interoperability across transport systems
- Support sustainable mobility solutions
- Reduce road fatalities and accidents
Why This Initiative Matters
The deployment of Level 3 and Level 4 automated vehicles is increasing across Europe and globally. These systems must operate safely in highly dynamic environments where traffic conditions, weather, infrastructure, and human behaviour can change rapidly.
Traditional approaches to testing and validation often struggle to capture rare or unexpected situations. Generative AI offers the ability to create realistic edge-case scenarios, helping developers train and validate automated systems more effectively while improving safety and reliability.
The initiative seeks to ensure that automated mobility systems are not only technologically advanced but also safe, transparent, fair, and trustworthy.
Understanding Connected, Cooperative and Automated Mobility (CCAM)
Connected, Cooperative and Automated Mobility refers to transportation systems where vehicles, infrastructure, and digital platforms communicate and cooperate to improve mobility outcomes.
CCAM technologies typically include:
- Connected vehicles
- Autonomous vehicles
- Vehicle-to-Vehicle (V2V) communication
- Vehicle-to-Infrastructure (V2I) communication
- Intelligent transport systems
- Smart traffic management
- Automated public transport
- Mobility-as-a-Service platforms
The initiative supports innovation across all these areas.
Role of Generative AI in CCAM
Generative AI can significantly improve automated mobility systems by:
- Generating realistic traffic scenarios
- Predicting road user behaviour
- Enhancing environmental perception
- Improving contextual reasoning
- Supporting automated decision-making
- Accelerating training and validation processes
- Extending existing mobility datasets
- Creating simulations of rare safety-critical events
These capabilities help automated systems adapt to increasingly complex transportation environments.
Support for Vulnerable Road Users (VRUs)
A major objective is improving safety for Vulnerable Road Users.
VRUs include:
- Pedestrians
- Cyclists
- Motorcyclists
- Children
- Elderly road users
- Individuals with disabilities
Projects are expected to improve:
- Behaviour prediction
- Intention recognition
- Risk detection
- Near-collision prevention
- Real-time situational awareness
This will help reduce accidents and improve road safety outcomes.
Generative AI Technologies Supported
The initiative encourages the use of advanced AI technologies, including:
Large Language Models (LLMs)
Applications may include:
- Contextual reasoning
- Decision support
- Scenario interpretation
- Human-machine interaction
Vision Language Models (VLMs)
Applications may include:
- Scene understanding
- Visual perception
- Traffic environment interpretation
- Multi-modal data analysis
Vision Language Action (VLA) Systems
Applications may include:
- Perception-to-action workflows
- Autonomous navigation
- Dynamic decision-making
- Real-time mobility operations
Testing, Training and Validation
A key priority is improving testing and validation processes.
Projects may develop:
- Synthetic datasets
- Edge-case scenarios
- Simulation environments
- Validation frameworks
- Training tools
- Performance assessment methodologies
These resources can improve confidence in automated vehicle deployment.
Environment Perception and Decision-Making
Projects are expected to enhance:
- Object detection
- Scene understanding
- Behaviour prediction
- Path planning
- Traffic awareness
- Hazard identification
- Dynamic route optimization
- Infrastructure interaction
Solutions should function effectively across:
- On-board vehicle systems
- Edge computing platforms
- Transport infrastructure
- Cloud and back-office environments
Cybersecurity and Privacy Requirements
Projects should address:
- AI system security
- Data protection
- Privacy preservation
- Threat detection
- Secure communications
- Trustworthy AI deployment
Strong cybersecurity measures are essential for large-scale deployment of automated mobility solutions.
Responsible and Ethical AI
Projects must assess:
- Transparency
- Accountability
- Explainability
- Fairness
- Gender bias
- Ethical considerations
- Responsible AI governance
Applicants should develop practical guidelines that support trustworthy AI implementation in mobility systems.
Expected Outcomes
Successful projects are expected to deliver:
- Advanced AI-powered perception systems
- Improved automated vehicle safety
- Enhanced protection for Vulnerable Road Users
- Faster and more reliable decision-making
- Better testing and validation methodologies
- Increased interoperability across mobility systems
- Reduced environmental impact
- Improved transport resilience
- Greater public confidence in automated mobility
- Reduced road fatalities and injuries
Collaboration Requirements
Projects are encouraged to collaborate with:
- European Software-defined Vehicle Initiative
- European Connected and Autonomous Vehicle Alliance (ECAVA)
- Automotive manufacturers
- Mobility technology companies
- Research institutions
- Transport authorities
- Infrastructure operators
Collaboration will help maximize innovation and ensure alignment with European mobility strategies.
Who Can Apply?
Eligible applicants include:
- Universities and research institutions
- Private companies
- SMEs and startups
- Technology providers
- Automotive manufacturers
- Public authorities
- Transport organizations
- International organizations
- Non-associated third-country entities
Any legal entity may participate if Horizon Europe eligibility requirements are met.
How to Apply
Step 1: Confirm Eligibility
Verify that your organization meets Horizon Europe participation requirements.
Step 2: Register in the Participant Register
Organizations must register within the Horizon Europe Participant Register system.
Step 3: Obtain a Participant Identification Code (PIC)
A valid PIC is required before grant agreement preparation.
Step 4: Develop a Project Proposal
Prepare a proposal outlining:
- Technical approach
- Innovation strategy
- AI methodologies
- Validation plans
- Expected impacts
- Consortium structure
Step 5: Complete Validation Procedures
Applicants must complete all legal and financial validation requirements before grant agreement signature.
Common Application Mistakes to Avoid
- Weak connection between AI technologies and CCAM objectives
- Insufficient validation and testing plans
- Lack of attention to safety requirements
- Failure to address ethical AI concerns
- Limited stakeholder involvement
- Weak cybersecurity considerations
- Inadequate scalability strategy
- Poor integration with existing mobility frameworks
Frequently Asked Questions (FAQ)
How much funding is available?
The initiative provides a total budget of €13 million, with approximately €6.5 million available per project.
What is CCAM?
CCAM stands for Connected, Cooperative and Automated Mobility, covering technologies that enable intelligent, connected, and automated transportation systems.
What types of AI technologies are encouraged?
Projects may use Large Language Models, Vision Language Models, Vision Language Action systems, Generative AI, and related AI technologies.
Can organizations outside Europe participate?
Yes. Any legal entity, including organizations from non-associated third countries and international organizations, may participate if eligibility requirements are met.
Why is Generative AI important for automated mobility?
Generative AI can create realistic scenarios, improve perception systems, support decision-making, and enhance testing and validation processes for automated vehicles.
What are Vulnerable Road Users (VRUs)?
VRUs include pedestrians, cyclists, motorcyclists, children, older adults, and people with disabilities who face greater risks in traffic environments.
Is collaboration required?
Yes. Projects are encouraged to collaborate with key European mobility initiatives, industry stakeholders, and research organizations.
Conclusion
The Generative AI for Smarter CCAM initiative represents a major European investment in the future of automated and connected mobility. By combining Generative AI, advanced perception technologies, intelligent decision-making systems, and robust validation methodologies, the program seeks to improve road safety, transport resilience, sustainability, and competitiveness. With €13 million in funding, the initiative offers significant opportunities for organizations developing next-generation mobility technologies that can shape the future of transportation across Europe and beyond.
For more information, visit EC.