Let’s meet in Brussels on 17 and 18 November 2025, at Autoworld (Parc du Cinquantenaire, 11) and experience Trustworthiness in AI-driven Automated Vehicle User Interactions!
Through collaborative research, AI4CCAM contributed to the CCAM ecosystem by addressing trustworthy AI in automated driving.
What to expect over the two days?
17 November
AI4CCAM Stakeholder Forum
The AI4CCAM Stakeholder Forum #2 is a side event focusing on challenges & opportunities for CCAM integration into public transport and shared mobility: from technological development to service deployment, the aim is to connect advancements with real-world applications to ensure research outcomes meet industry needs and help operators to deploy AI-driven CCAM. This will be a half day in-person event, accessible only by invitation and with the participation confirmed at a further stage.
Networking drink
From 18 to 19.30 those who have registered for the AI4CCAM final event on the day after, will meet for some nice networking to warm up the engines (well, we will be at the Autoworld!) for the next day!
18 November
AI4CCAM final event
The AI4CCAM final event will be the perfect day to discover project insights and the demonstrations developed from the very beginning up to now, highlighting key innovations in the use of artificial intelligence for safer, more ethical automated mobility, and also reflecting the project’s multidisciplinary approach and commitment to open-source tools, scalable validation environments, and human-machine interaction research:
• A session on AI4CCAM user acceptance, focusing on the project Participatory Space, on levels and barriers of automated vehicle user acceptance, and on the interoperable data-driven digital framework
• A panel discussion on Advancing the state of the art in research in trustworthy AI for CCAM
• An Innovation Corner
• An exhibition with demo booths to experience virtual reality
will accompany you to discover progress AI4CCAM brought to the CCAM sector!
Read and download the full agenda!
Registrations are open! Book your place here!
Get the practical information here!
The AI4CCAM Participatory Space continues its work on the creation of a glossary of capital and common terms used in the project.
This participatory process is aimed to create a glossary of terms with the involvement of different CCAM stakeholders. The process consists of proposals of terms to be included along their definitions. Later on, discussions about the correctness of these definitions take place and a final survey to decide the best option is performed. Results are monitored and agreed definitions are incorporated to a document that represents the glossary.
A first release of terms and definitions related to Model Development is now available: participants will be asked to share feedback on the correctness and understandability of the proposed definitions.
Another step towards safer roads!
Within AI4CCAM, Virtual Vehicle has been working on a new way to test ADAS in safety-critical VRU scenarios.
By integrating a VR headset with the open-source simulator CARLA, we enable real human agents to take on the role of pedestrians and interact directly with an AI-equipped ego car.
This approach makes it possible to safely validate new ADAS features against realistic pedestrian behavior in dynamic traffic environments – a key step toward safer, more effective systems for real-world use.
AI4CCAM and Virtual Vehicle had the great opportunity to share all this in ADAS & Autonomous Vehicle International. Read more!
The AI4CCAM Participatory Space is working on the creation of a glossary of capital and common terms used in the project.
This participatory process is aimed to create a glossary of terms with the involvement of different CCAM stakeholders. The process consists of proposals of terms to be included along their definitions. Later on, discussions about the correctness of these definitions take place and a final survey to decide the best option is performed. Results are monitored and agreed definitions are incorporated to a document that represents the glossary.
A new set of definitions for the glossary regarding Data and Datasets has been released: participants will be asked to share feedback on the correctness and understandability of the proposed definitions.
Simula Research Laboratory recently contributed to IEEE IV 2025 with two papers presented during the AI4CCAM-sponsored workshop entitled “Advancing AD in Highly Interactive Scenarios through Behaviour Prediction, Trustworthy AI, and Remote Operations“, which were also accepted for presentation as posters in the main Conference. These papers both relate to scene understanding using qualitative spatio-temporal representations:
Automatic Cause Determination in Road Scene Understanding Using Qualitative Reasoning and Four-Valued Logic
Road scene understanding in automated driving (AD) aims to build a comprehensive analysis of video sequences taken on the road by embedded or fixed cameras (e.g., mounted on vertical road signals). One goal is to identify the relevant actors in the scene and another goal is to determine the causes that have triggered a specific action of the ego car (i.e., stop, slow down, turn left, etc.). In a complex urban environment, these causes can be multiple, confusing, possibly contradictory to other causes and not easily expressible using simplistic reasoning. Still, providing accurate automatic cause determination supports a) user acceptance by providing appropriate explanations to the car passengers and road users; b) increased road safety by providing detailed road scene understanding to traffic. In this paper, AI4CCAM proposes using spatiotemporal reasoning and Belnap’s four-valued logic to formulate complex causes of AD action in a road scene.
Explainable Scene Understanding with Qualitative Representations and Graph Neural Networks
This paper investigates the integration of graph neural networks (GNNs) with Qualitative Explainable Graphs (QXGs) for scene understanding in automated driving. Scene understanding is the basis for any further reactive or proactive decision-making. Scene understanding and related reasoning is inherently an explanation task: why is another traffic participant doing something, what or who caused their actions? While previous work demonstrated QXGs’ effectiveness using shallow machine learning models, these approaches were limited to analysing single relation chains between object pairs, disregarding the broader scene context. AI4CCAM proposes a novel GNN architecture that processes entire graph structures to identify relevant objects in traffic scenes.
AI4CCAM held its 5th General Assembly in Barcelona, Spain, 8 and 9 July, hosted by the project partner
Barcelona Supercomputing Center (BSC)
Two intense days with a packed agenda! But AI4CCAM is coming to an end, and it’s important to take stock and prepare for the final event.
The meeting was opened by Simula Research Laboratory, the project coordinator, and IRTSX, technical coordinator, with a project roadmap showing milestones and results achieved so far and the next steps.
So plenty of space to Uses Cases and technical updates, as well as to communication and financial aspects.
The partners had the opportunity to discuss in depth the organization of the project’s final event, which will be held on November 17th and 18th in Brussels.
A visit to MareNostrum 5 was also organized by BSC: a pre-exascale EuroHPC supercomputer hosted at BSC-CNS. The system is supplied by Bull SAS combining Bull Sequana XH3000 and Lenovo ThinkSystem architectures and it has a total peak computational power of 314PFlops. The system will provide 4 partitions with different technical characteristics that jointly can fulfil the requirements of any HPC user.
News and updates from the AI4CCAM Participatory Space!
The AI4CCAM Participatory Space is working on the creation of a glossary of capital and common terms used in the project.
This participatory process is aimed to create a glossary of terms with the involvement of different CCAM stakeholders. The process consists of proposals of terms to be included along their definitions. Later on, discussions about the correctness of these definitions take place and a final survey to decide the best option is performed. Results are monitored and agreed definitions are incorporated to a document that represents the glossary.
A new set of definitions for the glossary regarding Ethics and Governance was released and participants will be asked to share feedback on the correctness and understandability of the proposed definitions.
A second update is about the publication of a user acceptance survey!
Do you work in transportation, cybersecurity, AI, automotive, or are just concerned about how current innovation shapes future forms of mobility?
We’d be glad to read you out, if you would like to take 8 minutes to participate to our quick survey about road user acceptance of automated mobility.
Your answers will help AI4CCAM better understand different views and perception of this topic, and you might learn something interesting along the way…
The IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV 2025) is the premier annual forum organized by the IEEE Intelligent Transportation Systems Society (ITSS). IV 2025 took place in Cluj-Napoca, Romania, 22-25 June, and AI4CCAM was there!
Researchers, academics, and practitioners from universities, industry, and government agencies shared their latest research papers, simulation challenges, and applications on Intelligent Vehicles and Intelligent Vehicle Infrastructures. The symposium featured Plenary Talks, Technical Sessions, Poster Sessions, Tutorials, Workshops, Exhibitions, and Industrial Demonstrations and Challenges.
Simula Research Laboratory, the AI4CCAM coordinator, contributed to IEEE IV 2025 with two papers presented during the AI4CCAM-sponsored workshop entitled “Advancing AD in Highly Interactive Scenarios through Behaviour Prediction, Trustworthy AI, and Remote Operations”, which were also accepted for presentation as posters in the main Conference. These papers both relate to scene understanding using qualitative spatio-temporal representations.
From 29th June to 3rd July, Athens hosts the International Symposium on “Navigating the Future of Traffic Management”, organized locally by the Institute of Communication and Computer Systems (ICCS) of the National Technical University of Athens (NTUA) in collaboration with leading global and European organisations at the forefront of traffic management research and operations.
The Symposium aims to explore and highlight innovative solutions for dynamic traffic management, strategies to improve traffic flow with a focus on safety, sustainable and environmentally conscious practices, as well as future research directions and needs in the field.
AI4CCAM will be there!
INLECOM will participate in the session “Navigating the Challenges of Data Management and TMS Assets” with Konstantinos Loupos, sharing valuable insights on “Artificial Intelligence and Digital Solutions for Transport Infrastructure Resilience” and highlighting the methodologies developed within AI4CCAM.
AI4CCAM will also be at the Mini Exhibition taking place: Tuesday, 1 July & Wednesday, 2 July 2025. Visit us to find out more about the project!
Bringing together more than 100 international speakers and representatives from leading institutions in transport, technology, and public policy, the symposium will cover five key tracks shaping modern transportation management. The Symposium will spotlight innovative solutions to some of the most persistent urban challenges — including traffic congestion, road safety, environmental sustainability, and the integration of smart infrastructure. Topics will include intelligent traffic signal systems, dynamic toll pricing, real-time traffic monitoring, and integrated traffic control platforms.
For more information on the event, click here
