AIGGREGATE addresses the critical challenges of automated driving by enhancing safety, resilience, and human-like control in CCAM (Connected, Cooperative, and Automated Mobility) systems. While AI has advanced many driving functions, complete automation still faces significant hurdles, particularly in complex and dynamic traffic scenarios. AIGGREGATE will bridge these gaps by developing an integrated solution for the entire action chain for collective decision-making, using hybrid intelligence and human-like control. By integrating external data from vehicles, infrastructure, and other sources (V2X), the project will create a resilient collective situational awareness that goes beyond mere perception, and will include a comprehension and understanding of the traffic environment. This enhanced awareness will feed into algorithms for predicting the behaviour of road users (including the driver and VRUs) and collective decision-making. Combined, these solutions allow automated systems to anticipate and adapt to the actions of other road users, even in complex urban traffic. The user-centric design and ethical framework will ensure a human-like control which increases the acceptance. The project will develop new functionalities for automated driving, focusing on complex, real-life scenarios that require the integration of external data. This approach marks a shift from traditional systems reliant on onboard sensors only towards collective perception and decision-making. The project includes a development platform for the integration of software and physical demonstrations. The project partners include the Eindhoven University of Technology as the coordinator, along with Vicomtech, TNO, KU Leuven, University of Warwick, RWTH Aachen, IDIADA and CERTH as research partners, Infineon, Valeo France and Germany, Continental and MAPTM as industrial partners, and PAVE to support the dissemination.