The goal of SIMBAD is to develop and evaluate a set of machine learning approaches aimed at providing state-of-the-art ATM microsimulation models with the level of reliability, tractability and interpretability required to effectively support performance evaluation at ECAC level.
AICHAIN looks for enhancing ATM systems by articulating an advanced privacy-preserving federated learning architecture in which neither the training data nor the training model need to be exposed. This will be possible thanks to the combination of two emerging technologies: FedML and Blockchain technologies.
BigData4ATM is a research project within SESAR 2020 Exploratory Research which aims to investigate how new sources of passenger-centric data coming from smart personal devices can be analysed to extract relevant information about passengers’ behaviour and how this information can be used to inform ATM decision making processes.
BEACON studies the feasibility of extending UDPP (User-Driven Prioritisation Process) to allow multi-prioritisation processes in the airspace (e.g. encompassing departure slots, regulation slots, arrival manager slots), and exchange of slots between airlines.
ACCESS was a project within SESAR WPE Long Term and Innovative Research which addressed airport slot allocation from the perspective of complex adaptive systems. The project developed an agent-based model of the air transport network that was used to evaluate different designs of market-based mechanisms for airport slot allocation.
INTUIT explored the potential of a variety of visual analytics and machine learning techniques to improve our understanding of the trade-offs between Air Traffic Management KPAs, identify cause-effect relationships between performance drivers and performance indicators at different scales, and develop new decision support tools for ATM performance monitoring and management.
TRANSIT looks for developing a set of multimodal KPIs, mobility data analysis methods and transport simulation tools allowing the evaluation of the impact of a set of innovative intermodal transport solutions on the quality, efficiency and resilience of the door-to-door passenger journey.
IMHOTEP aims to develop a concept of operations and a set of data analysis methods, predictive models and decision support tools that allow information sharing, common situational awareness and real‑time collaborative decision-making between airports and ground transport stakeholders.
ITACA seeks to accelerate the development, adoption and deployment of new technologies in ATM. The project has developed a new set of methodologies and tools enabling a comprehensive assessment of policies and regulations aimed at amplifying the uptake of new technologies within ATM.