The AI4CCAM (Trustworthy AI for CCAM) project has reached its two-year mark. From immersive virtual reality demonstrations to a pioneering Trustworthy AI Documentation Framework, the project continues to shape the future of connected and automated vehicles.
Involving 14 partners, the €6 million project, funded under the EU’s Research and Innovation Programme Horizon Europe, AI4CCAM will provide automated driving scenarios involving ethical, social and cultural choices, digging into advanced AI models for predicting vulnerable road users’ behavior and user acceptance of self-driving vehicles.
What is AI4CCAM working on?
- Driving innovation through virtual reality
- Pioneering trustworthy AI
- Spreading the word of AI and automated mobility
“As we celebrate the two-year milestone of our AI4CCAM research and innovation project, I am thrilled to acknowledge the remarkable achievements and progress made by our consortium. One of the highlights is a virtual reality-based demonstration of AD user acceptance, built on meticulously modelled scenarios with ethical issues and utilizing cutting-edge trustworthy AI/ML models developed within the project. Additionally, the upcoming launch of the AI4CCAM participatory space, complete with comprehensive content on user acceptance, cybersecurity, and ethical guidelines, fills me with immense pride. These accomplishments showcase our collective efforts and the professionalism of all AI4CCAM participants. Thank you to everyone involved in AI4CCAM for the continued hard work and commitment.“, says Arnaud Gotlieb, Coordinator of the AI4CCAM project.
As AI4CCAM enters its final year, the consortium is poised to deliver groundbreaking advancements. Follow our journey for more updates in the months ahead.
Arnaud Gotlieb, Simula Research Laboratory, AI4CCAM coordinator, had the chance to present the project during the recent UITP Working Group on Artificial Intelligence, held online on 11 December.
Artificial Intelligence (AI) is growing its importance in every sector, including public transport. The use of AI applications in public transport could be one of the critical solutions that efficiently unlocks the value of data to improve the quality and efficiency of the public transport sector.
UITP, AI4CCAM partner, wants to raise awareness, demystify the technology and outline the current landscape of AI applications in public transport. This is the aim of the Working Group.
Arnaud underlined the importance of AI in automated vehicles: a formidable opportunity to increase passenger and road user safety, improve traffic, efficiency, reduce pollution, improve passenger comfort. However, possible threats must be taken into account too. This is what AI4CCAM works on thanks to 9 simulated scenarios including ethical issues and indicators.
Arnaud also announced the launch of the AI4CCAM Participatory Space, early 2025, to build a community of CCAM stakeholders.
AI4CCAM organised a successful workshop on cybersecurity, on December 4th in Rome, Italy, with more than 30 participants as a part of the UITP Cybersecurity committee meeting. Representatives of UITP Working Group on Artificial Intelligence (AI) were invited too.
The main goal of the workshop was to develop skills in responding to cybersecurity incidents in autonomous vehicles and intelligent transportation systems (ITS).
The workshop started with discussions on AI applications for the public transport sector, focusing on the evolution of vehicles and the current Cooperative Connected Automated Mobility (CCAM) and ITS ecosystems. The security risks introduced by these emerging technologies were discussed too.
After that, Badis Hammi, Telecom SudParis, presented AI4CCAM and introduced the issue of cybersecurity in building Trustworthy AI for Connected, Cooperative and Automated Mobility.
The workshop discussions were focused on incident response simulation where participants were split into groups to analyse the cybersecurity incidents in autonomous vehicles/intelligent transport systems and develop appropriate responses to such issues.
Participants were divided into four groups (one of which was online), with approximately 50 participants in total. Each group worked on a specific attack scenario:
- Traffic signal manipulation
- GPS spoofing attack
- Fleet-wide command injection
Participants had 45 minutes to prepare their work, divided into three key phases:
- Incident analysis
- Response planning
- Recovery and communication.
Then, up to to 15 minutes were left to present the findings.
During the concluding session, participants identified several crucial actions for incident response:
- To identify and isolate affected systems (e.g., CCAMs, traffic signals) and deploy containment measures
- To ensure the availability of backup systems and activate them as needed
- To alert relevant stakeholders promptly to coordinate an effective response.
VDI/VDE Innovation + Technik GmbH as part of the stakeholder engagement activities of the FAME project organised, on 18 November, a Live Talk on how data and AI are transforming the CCAM ecosystem.
Moderated by Oihana Otaegui Madurga (Director of Transport & Security Division, Vicomtech), the session bridged the gap between application-driven solutions and the more transversal, generic and research-oriented AI advancements.
Among the panellists, Margriet van Schijndel, Program Director Responsible Mobility, TU Eindhoven, CCAM Partnership, and member of the AI4CCAM Ethical and Scientific Advisory Board who also mentioned AI4CCAM when dealing with different perspectives on AI and data in CCAM, from transversal AI developments that promise broad, cross-sector impact to tailored, application-driven solutions addressing specific mobility needs.
Bernhard Peischl (Innovation Manager, AVL List GmbH) was a further panellists.
A groundbreaking cluster of EU-funded projects has been formed to revolutionise road safety, automated mobility, and the interaction between drivers and vulnerable road users (VRUs). This collaborative effort brings together five ambitious initiatives – AI4CCAM, HEIDI, EVENTS, PHOEBE, and SOTERIA – to develop cutting-edge solutions addressing the growing complexity of urban transport systems, forming a cluster on “Road safety in complex urban environments”.
The cluster aims to promote a safe, inclusive, and sustainable mobility system that is resilient, trustworthy, and road user-centric. By uniting efforts across these projects, this initiative is set to transform European transport research and establish new standards for road safety and automated driving.
Cluster Overview
At the heart of the cluster’s mission is a shared vision for establishing the “safe system” approach. This shifts the focus from placing responsibility solely on road users to a holistic strategy where every stakeholder—from infrastructure designers to transport operators—plays a role in creating safer environments. The projects will work together to ensure that automated mobility technology is not only efficient but also transparent, inclusive, and adaptable to real-world road conditions.
The five projects are exploring how advanced technologies like artificial intelligence (AI), simulation environments, predictive analytics, and human-machine interfaces (HMIs) can enhance urban road safety for all road users, particularly vulnerable groups such as pedestrians, cyclists, and individuals with reduced mobility.
Projects Highlights
AI4CCAM leverages the potential of AI to create trustworthy and ethical models for predicting the behavior of vulnerable road users in urban environments. Its focus on user acceptance of automated vehicles and ethical dilemmas ensures the development of AI systems that people can trust.
EVENTS seeks to overcome the limitations of current Connected and Automated Vehicles (CAVs) by developing a robust and resilient perception and decision-making system that can manage unexpected “events” like adverse weather/light conditions, unstructured road environment, imperfect data, sensor/communication failures, etc., ensuring continuous safe operation in dynamic environments.
HEIDI is breaking new ground by designing a cooperative HMI that connects drivers and pedestrians in dangerous situations. With internal and external HMIs, HEIDI adapts in real time to the behaviors and needs of drivers and VRUs.
PHOEBE aims to support urban transport planning with an evidence-based framework for predictive road safety. This project offers a blueprint for cities to manage safety risks effectively, integrating human behavior modeling and transport system simulations to prevent accidents.
SOTERIA focuses on creating a data-driven safety intelligence framework that integrates electric micro-mobility services in urban environments. It emphasises inclusivity by fostering a co-creation process with local communities and vulnerable road users.
Collective Strengths
The cluster of projects is founded on several shared strengths:
Human-Centric and Inclusive: Prioritising the needs of all road users, including vulnerable populations such as children, elderly, and those with reduced mobility.
Ethical and Trustworthy AI: Developing AI models and decision-making systems that are transparent, reliable, and capable of handling complex ethical issues.
Advanced Simulation Technologies: Leveraging co-simulation environments, hybrid testing, and machine learning to safely evaluate and validate new technologies.
Scalability and Resilience: Ensuring that solutions are adaptable across various transport modes, from micro-mobility services to automated vehicles, and capable of handling unexpected events and system failures.
Impact and Future Directions
By integrating innovative technologies and road user-centered approaches, this EU-funded cluster of projects aims to deliver substantial advancements in road safety and automated mobility. The initiative will not only contribute to the development of safer transportation systems but also foster public trust and acceptance of emerging mobility solutions.
In particular, the exchange of knowledge and practices between projects regarding AI and simulation technologies could further amplify their positive impact, fostering innovation and improving outcomes across the board. Through close collaboration, these projects will offer new methodologies, standards, and tools to help urban planners, policymakers, and transport operators create safer and more efficient mobility networks across Europe.
On 16 October, a new online meeting was organised to talk about progresses and next steps the Use Case 3 (UC3) in AI4CCAM, mainly involving CNRS and TTS Italia in the discussion.
The purpose of UC3 is to assess the degree of Vulnerable Road Users’ (VRUs) acceptance of Connected and Automated Vehicles exploring their interaction dynamics in a number of increasingly complex urban settings, where users will be immersed through a purposely designed experiment. When interacting with CAVs, VRUs will be prompted to take decisions (e.g., street crossing decisions when a CAV is approaching), while semi-quantitative data, also including physiological indicators, will be collected to assess acceptance rates in diverse scenarios.
The recent meeting highlighted the continued progress on UC3 user acceptance, with a focus on refining urban traffic environments and addressing challenges related to CARLA tool constraints, an open-source autonomous driving simulator used in AI4CCAM to create scenarios and attempt experiences.
TTS Italia, leading this Use Case, is playing a pivotal role in defining the environment descriptions and scenario dynamics, focusing on how vulnerable road users (VRUs) and connected automated vehicles (CAVs) will interact during experiments. TTS is also working on the methodologies for measuring key metrics using advanced devices like EMG and GSR, ensuring precise data collection.
CNRS is actively working on creating optimized urban traffic environments that meet the project’s requirements, exploring alternative setups to ensure efficient communication metrics and enhancing the VR scenarios. Despite some challenges, such as device limitations and physiological measurement dynamics, CNRS is making headway in overcoming these obstacles.
IRTSX took part in the discussion too, contributing to enhance scenario dynamics description.
On the 10th of October, the CCAM (Connected, Cooperative, and Automated Mobility) Multicluster Meeting took place in Brussels, focusing on enhancing collaboration between large-scale demonstrations and various clusters within the CCAM Partnership.
AI4CCAM project, being a part of “Cluster 5: Key Enabling Technologies”, contributed to the discussion on how the project’s outcomes can support large-scale demonstrations across Europe.
The project contribution is centered on four major results expected from AI4CCAM:
- Methodology Input: Integration of EU Trustworthy AI guidelines into CCAM applications.
- Road Scenarios in MOSAR: Modelling of ethical issues within road scenarios.
- Participatory Space: Creation of a collaborative platform bringing together the general public and industry experts.
- Research on Scene Understanding: Contributions to pedestrian and vehicle trajectory prediction, including model definition and validation.
These project results have the potential to be scaled up and transformed into building blocks for large-scale demonstrations. Not only do they offer a qualitative understanding of scene dynamics and address ethical challenges in road scenarios, but they also provide an inclusive Participatory Space—designed to gather feedback from both users and citizens to enhance the public’s perception of CCAM technologies.
AI4CCAM presented the paper “Toward a Meet-in-the-Middle Methodology for Trustworthy AI for CCAM” during the last edition of the International Conference on Intelligent Traffic and Transportation (ICITT), held in Florence, Italy, 16-18 September 2024.
The International Conference on Intelligent Traffic and Transportation (ICITT) is a major event for academics, researchers, and industrialists who are engaged in Intelligent Traffic and Transportation research. Held annually since the late 2010, the conference is renowned as a friendly and inclusive platform that brings together a broad community of researchers who share a common goal: developing and managing engineering and technologies revolution of Transportation Systems, and operations which are key to sustaining the success of Intelligent Traffic and Transportation industries.
The publication presented by the AI4CCAM project, a collaboration between IRT SystemX, Barcelona Supercomputing Center (BSC), INLECOM, pushes the first iteration for a meet-in-the middle methodology for trustworthy Artificial Intelligence in Cooperative Connected and Automated Mobility (CCAM). In this result of AI4CCAM, IRT SystemX brings the scenario approach and a first pipeline of the methodology inspired in the Confiance.ai program, BSC brings the expertise on ethics and responsible AI and INLECOM leads the validation of use cases in the project that drive the modeled scenarios. The purpose is to leverage existing and proven practices as the integration of trustworthiness guidelines for AI is modeled and assessed.
The next CCAM Partnership Multi-cluster meeting is scheduled on 10 October 2024, in Brussels, and AI4CCAM, represented by the Arnaud Gotlieb, Simula Research Laboratory, the project coordinator, will be among the speakers fo the day.
The meeting will focus on the preparation of the future Work Programme 2026-27, especially the large-scale demonstration calls for projects.
AI4CCAM will be especially involved in the Breakout session on “What projects’ results can be integrated into large-scale demonstrations? What research needs can be postponed till the next Framework Programme?”, including CCAM Cluster 5 Group on Key Enabling Technologies, eager to learn more about the outcomes and results of the project, and understand how these could potentially be exploited within the future CCAM Large-scale demonstration projects.
