The 6th European Conference on Connected and Automated Driving (EUCAD 2027) will consist of a series of policy-oriented and technical sessions to discuss specific R&I challenges and opportunities for CCAM (in parallel with an exhibition and demonstrations of European and national CCAM projects and solutions).
A call for sessions is organised to receive proposals for the organisation of conference sessions related to one of the selected topics for EUCAD 2027. Applications must respect the Submitters’ Guidelines and be submitted through the online submission form ─ which includes instructions for the session proposal description ─ by July 31st 2026.
For further enquiries, please contact eucad@connectedautomateddriving.eu
Topics
1. CCAM Large-Scale Demonstrations and flagship pilots in Europe and beyond
Large-scale demonstrations and flagship pilots are essential to advance Cooperative, Connected and Automated Mobility (CCAM) from testing to sustainable deployment. Across Europe and beyond, EU-funded large-scale demonstrations, national pilots, emerging European cross-border test beds, and Important Projects of Common European Interest (IPCEI) on autonomous mobility are expected to shape future CCAM ecosystems. A key challenge is creating stronger synergies between EU and national activities to maximise impact and avoid fragmentation.
This topic therefore focuses on programme‑level, cross‑initiative and ecosystem‑level learning from large‑scale CCAM demonstrations, rather than on the deployment of a specific automation level or individual services. Sessions can address coordination mechanisms, scaling and replication approaches, and governance models, with a strong emphasis on cross‑project learning, stakeholder engagement and assessment.
Sub-topics
- CCAM large‑scale demonstrations as learning environments
Programme‑level perspectives on CCAM large‑scale demonstrations across Europe and internationally, including use cases, test sites and corridors for individual mobility, public transport and logistics, with a focus on system‑level insights rather than individual deployments. - Alignment, synergies and scaling across CCAM initiatives
Coordination and learning across EU‑funded projects, cross‑border test beds, national pilots and IPCEIs, highlighting lessons learnt, cross‑project comparability, and pathways and mechanisms enabling scaling and replication across programmes and regions. - Enabling frameworks for sustainable and scalable CCAM implementation
Harmonised governance and frameworks, along with early and continuous stakeholder engagement, to build trust, ensure comparability of results and support the transition from CCAM pilots to sustainable, user‑centred solutions embedded in existing mobility systems.
2. Autonomous Driving Level 4 Deployment
Highly automated driving at SAE Level 4 is transitioning from controlled pilots to real-world deployment in selected use cases and environments. While significant technological progress has been achieved, large-scale deployment still faces challenges related to key enabling elements, safety validation, regulatory approval, deployment rules, Operational Design Domains (ODDs) vs Target Operational Domains (TOD), remote interaction and user acceptance.
In this regard, a key factor is exploring the current state and future outlook of Level 4 automation deployment, with a focus on concrete deployment experiences of SAE Level 4 automated driving services, scalability, and integration into existing mobility systems. Equally important is providing a comprehensive and comparative perspective on Level 4 Deployment across the European Union and globally, highlighting emerging patterns, key actors, and implementation strategies.
This topic focuses on the concrete deployment of SAE Level 4 automated driving services, including technical, regulatory, operational and business aspects at service and fleet level, rather than on programme level demonstration coordination. Robotaxis, shuttles, ODD and operations could be addressed under this topic.
Sub-topics
- Deployment use cases
Robotaxis, automated shuttles, freight and logistics applications, public transport integration and first/last-mile services, controlled environments vs. open-road deployment. - Operational Design Domain (ODD) vs Target Operational Domain (TOD)
Definition, limitation, and expansion strategies, weather, traffic, and geographic constraints, tools and methodologies for ODD and TOD validation. - Operations and business models
Fleet operations, remote supervision, and maintenance, cost structures and commercialization strategies, partnerships and ecosystem development. - Scaling up deployment
Transition from pilots to commercial services, replicability of L4 services across cities and regions, including operational and regulatory transferability, international experiences and benchmarking.
3. Governance enabling AVs
The development of automated driving technologies raises a number of policy questions related to road safety, traffic management, environmental performance, liability, cybersecurity, and the governance of vehicle-generated data. As testing and deployment activities expand, public authorities are required to adapt regulatory frameworks while ensuring that adequate safeguards are in place for users and society. Sessions proposed under this topic could address different levels of regulations (UNECE, EU, MS, local, passenger transport, etc.) as well as other enabling conditions such as, among others, public procurement.
Sub-topics
- (Global) The first 6 months with the new UN/ECE ADS regulation – what has changed?
The UN Regulation on Automated Driving Systems (ADS) is supposed to come into effect in November 2026, making it possible to type-approve SAE Level 4 vehicles. This means that there is now a framework for such vehicles to get access to market across Europe and beyond. What has changed? - (EU- MS-level) European reality and national access to roads
EU Member States (MS) must adapt their national legislation to accommodate ADS on their public roads. The European Forum for Automated Transport (EFAT), an informal working group for legal and policy experts at national level was established in 2024 for coordination and knowledge sharing. What needs to be adapted at the national level except for the traffic rules to allow ADS on the European public roads and where are we at? - (Regional/municipality level) Deploying AVs at regional/municipality level – what is needed
Successful regional and municipal AV deployment demands deep integration with the existing fabric of urban life. Cities must evaluate how AVs interact with established traffic patterns involving a broad range of road users. Infrastructure planning must account for practical realities like AV parking and servicing within constrained municipal spaces. Close coordination with first responders is needed to ensure effective interaction with AVs. - Public procurement as a driver
Public procurement can be a powerful tool for policymakers to create a market for new technologies. The EU is currently revising its 2014 public procurement directives to simplify rules, enhance strategic use of procurement, and align with green, social, and innovation objectives, with adoption expected in Q2 2026. Preferential procurement could also be used to achieve reduction of strategic dependencies in domains that are essential for public safety, resilience, and long-term industrial sovereignty.
4. Safety by design
Coming soon
Sub-topics
- TBD
- TBD
5. NextGen technologies for AD
Technological developments in the domain of automated driving are advancing at an increased pace. In this strategic field of technological development, the existing ecosystem – with automotive manufacturers, suppliers, mobility service providers and research organisations – is being enriched with new actors from e.g. digital and software domains. These actors bring in expertise new to the automotive industry. New and emerging technologies, from the mobility domain or other domains, can rapidly advance CCAM applications, e.g., new types of AI, cyber security and data handling. These often need to be made sector specific. This contextualisation demands close collaboration between CCAM experts and the experts from digital and software sectors who tend to focus on sector agnostic technology development.
Sessions under this topic should focus on such NextGen technologies, both coming and expected, and how to effectively absorb them in automated driving technologies.
Sub-topics
- Approaches and lessons learnt regarding contextualisation of NextGen technologies for AD
- NextGen technologies from other sectors, e.g. photonics and post-quantum encryption
- Validation of CCAM solutions incorporating NextGen technologies
6. Value-Based Deployment of CCAM Systems
Clearly defined societal priorities can guide targeted technological development and accelerate market uptake. Such societal values and priorities, typically expressed by public actors at EU, national, regional and city levels, are often not consistently translated into technological and industrial development, reflecting limited alignment between policy objectives and industry incentives. As global industrial competition intensifies, Europe risks shifting towards a value-agnostic technology race to catch up internationally, with uncertain outcomes.
This topic proposes to reconnect societal values with technological and service development. It explores how key societal trends such as sovereignty, climate objectives, safety needs, ageing populations and labour market transformations can be translated into operational competitive values and concrete design guidelines for CCAM systems. It also examines how enabling technologies for CCAM deployment (e.g. software-defined vehicles, AI-driven systems, data platforms) and policy frameworks can support value-based deployment across passenger and freight transport.
Sub-topics
- Which societal trends (e.g. ageing, safety, jobs, climate, convenience, sovereignty) will most strongly shape future CCAM demand in Europe, and how can these be translated into operational values, deployment parameters, and concrete design requirements for CCAM systems?
- What are the implications of different value priorities (e.g. safety, accessibility, sustainability, liveability, workforce resilience) for deployment approaches of CCAM services?
- How can emerging technologies supporting CCAM, such as software-defined vehicles, AI-based decision-making and fleet management, and data-driven mobility platforms, be aligned with value-driven deployment pathways?
- What role can policy, procurement, and regulation play in translating societal values into investment priorities and deployment strategies?
7. Building Trust in Automated Mobility: Safety, Liability, and Societal Readiness
Public trust is a critical enabler for the large-scale deployment of Connected, Cooperative and Automated Mobility (CCAM). As automated systems move from controlled environments into everyday public use, societal readiness becomes as important as technological readiness. Whilst Europe continues to advance through pilots and regulatory preparation, large-scale commercial deployment is already a reality in other parts of the world – offering invaluable lessons for public acceptance, safety assurance and governance. By 2027, significant deployments may also be underway within Europe.
This topic explores the drivers, barriers, and dynamics of trust across different user groups and societal contexts, whilst addressing the ethical and regulatory frameworks that will define the future of autonomous mobility. It examines how governance, transparency, real-world performance and safety assurance collectively shape public confidence, as well as the requirements to achieve responsible development and deployment of automated vehicles.
Sub-topics
- Determinants of trust in AVs (safety perception, reliability, transparency and explainability)
- Trust differences across user groups (drivers, passengers, pedestrians, vulnerable road users and non-users)
- The role of real-world demonstrations, pilots and living labs in trust-building – and what Europe can learn from markets where AVs are already operating at scale
- Technological aspects of trust and the role of multi-pillar safety assurance in building institutional confidence
How could we technically define “trust” for instance in shared data between different actors in the mobility system (vehicle, infra, cloud, etc.), how to deal with that, and what are the impacts on safety and safety assurance. - The 2027 regulatory landscape
Are ethical and standards frameworks complete enough to support broad deployment? - Public perception, liability and the ethics of autonomous decision making
- The impact of incidents, media coverage and crisis communication on public confidence
- Measuring and monitoring trust over time: metrics, methods and insights
8. Inclusion of digital infrastructure in autonomous driving
Autonomous driving is enabled by several digital services, which are required to maintain a robust system. The range of such digital services is broad, including update services for the autonomous driving functions, remote operation functionalities, fleet monitoring, inclusion of traffic management services, ODD monitoring, the use of sensors outside of the vehicles, general cloud services for enhancing the trips themselves, etc. But the inclusion of such services in autonomous driving is challenging, due to cyber-security aspects, but also due to complex homologation and regulatory approval conditions. This is especially true when the infrastructure is not limited to low-level support of autonomous or connected driving, but when it also takes part in agreement-seeking or even prescriptive interaction with autonomous vehicles, according to SAE J3216.
Sub-topics
- How digital infrastructure enhances autonomous driving
Collection of different approaches and already identified impact - Cyber-security aspects of digital infrastructure components in autonomous driving
Ways to make digital infrastructure service trustworthy - Homologation and approval of autonomous driving functions using digital infrastructure
Which kind of inclusion is simple, where are boundaries (e.g. related to ISO 26262, SOTIF, etc.)?
9. Data and AI for automated driving
Data and AI are the twin engines driving the next leap in automated mobility. The capacity to collect, share, process, and learn from vast and diverse datasets, from sensor streams to simulation environments, is increasingly what separates research-grade systems from deployment-ready ones. At the same time, the rise of end-to-end AI architectures and foundation models is reshaping how automated driving systems are designed, validated, and operated, blurring the boundary between perception, planning, and control. Europe faces a dual challenge: keeping pace with rapid technological developments in AI and data infrastructure while building frameworks that ensure trustworthiness, data sovereignty, and competitive fairness.
This topic brings together the technical, governance, and strategic dimensions of data and AI in CCAM, from federated data provisioning and cooperative driving architectures to simulation pipelines and V2X-integrated AI models, to safety of AI (by both design and assessment).
Sessions under this theme should address not only the state of the art, but the concrete steps needed to turn data and AI assets into safe, scalable, and sovereign European capabilities.
Sub-topics
- Federated data provisioning and data spaces for AD
Training robust automated driving models requires access to vast, diverse, and well-annotated datasets ─ a challenge no single organisation can address alone. This sub-topic examines technical architectures (including CCAM Data Spaces, Gaia-X, Catena-X, and Eclipse Data Space Connector) and governance models enabling trustworthy, cross-organisational data sharing while preserving competitive sensitivity and complying with data sovereignty requirements.
Key questions include:
– What legal and incentive frameworks can support pre-competitive data sharing in Europe?
– How do we ensure data quality and annotation pipelines at scale? - Data and simulation pipelines as enabling infrastructure
Behind every capable automated driving model lies an equally capable data and simulation infrastructure. This sub-topic explores the role of sensor simulation, synthetic data generation, and data pipelines in accelerating AV development ─ including quality standards, scalability, and the integration of simulation into validation workflows.
Key questions include:
– How can Europe build shared, open, or federated simulation infrastructure to reduce duplicated effort across projects and organisations? - AI models in vehicles and V2X
From onboard perception and decision-making to vehicle-to-everything communication, AI is becoming deeply embedded in the driving stack and in the broader traffic system. This sub-topic addresses the development and deployment of sector-specific AI models for automotive and V2X contexts, including challenges of real-time inference, model updates over-the-air, and integration with connected infrastructure. - Cooperative driving and end-to-end AI systems
End-to-end AI systems replicate human driving behaviour primarily from visual sensor data, while cooperative driving functions leverage vehicle-to-vehicle and vehicle-to-infrastructure communication to improve systemic traffic outcomes. This sub-topic explores how both paradigms can coexist and complement each other, technically and operationally. - Safety of AI by design and assessment
Ensuring safety of End-to-end AI based systems, and or more generically, systems that are subject to change in their behaviour during their operational lifetime, requires not only a different perspective on how to assess these, but also in their architectural design. This sub-topic addresses different approaches, architectures, and methodologies towards safe solutions. - Data pooling: incentives, standards, and governance
Beyond the technical architecture, data sharing in CCAM requires aligned incentives, common standards, and clear governance rules. This sub-topic addresses the practical barriers to data pooling ─ including competitive concerns, liability, intellectual property, and fragmented standards ─ and explores models (e.g. data trustees, labelling standards, sandbox agreements) that can unlock collective value from distributed data assets.
10. Out-of-the box
We also welcome submissions that do not correspond to any of the selected topics for EUCAD 2027, and yet are interesting, innovative and highly relevant for CCAM. It is however imperative to use this topic ONLY if the session subject cannot be linked with any of the other topics. Submissions incorrectly received under this topic shall not be considered.