France – Vocational training services – POEC Métiers de l'industrie

France – Vocational training services – Offre de Formation Collective "Développer un management participatif pour mieux travailler ensemble"

France – Education and training services – Concession de service relative à l'exploitation, la gestion et le développement du centre de formation Rungis Académie

France – Motor vehicles – CCP2025-20 Acquisition et livraison de véhicules neufs de la gamme commerciale au profit des organismes soutenus par la Direction du commissariat des forces armées en Guyane

France – Refuse and waste related services – EXPLOITATION DES DECHETTERIES

Expected Outcome: Project results are expected to contribute to all the following expected outcomes: Availability and integration of advanced, trustworthy, energy-efficient perception systems, exploiting technological advancements of Generative AI (GenAI) to enhance situational awareness and support safe decision-making; Enhanced Vulnerable Road User (VRU) safety, based on elevated, more temper-proof perception and understanding of their behaviour and intention predictions; Enhanced robustness of CCAM systems - both on-board and on the infrastructure side - in critical situations due to their training, virtual testing and validation in scenarios generated by GenAI, complementing existing scenario databases for the testing and validation of CCAM systems; Enhanced understanding of the relevance and limitations of using GenAI for CCAM; Tools and harmonised approaches for the use of GenAI in mobility technology development, training and validation, as well as for systemic applications such as traffic management and remote control, integrating them into existing approaches. Scope: Pilots and demonstrations using Level 3 and 4 vehicle services face major challenges in perception and…

Expected Outcome: Project results are expected to contribute to all the following expected outcomes: Development of systems that utilize real-time data analytics to dynamically respond to disruptions, allowing transport and infrastructure operators to adjust operations swiftly and efficiently; Development of predictive maintenance strategies applying innovative Generative AI solutions and utilizing other digital technologies to anticipate and prevent infrastructure and equipment failures; Development of guidelines and tools to support passenger transport operators and authorities to ensure minimal disruption in unexpected and critical situations and organise real life emergency simulations; Deployment of training programme for transport and infrastructure operators on how to handle transport disruption, including tools and catalogue with contingency planning for specific transport disruptions; Reduction of average passenger delay at corridor level (at least 20%) during planned disruptions, compared to the baseline and of (at least 40%) time needed from the generation to the dissemination of a response plan to different stakeholders (e.g. transport operators, passengers, citizens)…