The full integration between Airport and Network Operations has still to be achieved. In particular, the management of predicted airport performance deterioration needs to be aligned with the Network. Collaborative recovery procedures and support tools in coordination with all the relevant ATM stakeholders are required to facilitate the pro-active management of predicted performance deteriorations such as airport capacity reduction. Total airport demand and capacity balancing processes and tools require further integration with the execution tools (arrivals and departure management systems and advanced surface movement guidance & control systems) and resource allocation planning tools (e.g. stand/gate allocation) with the objective of optimising the airport capacity to better comply with the traffic demand. Airport landside/airside performance monitoring and management processes need to be further integrated while the turnaround monitoring within the Airport Operations Centre (APOC) requires refinement in coordination with the Airspace Users. Impact assessment tools available to the APOC need to better integrate information about MET forecast uncertainty. Post-operations analysis processes, support tools and reporting capabilities need to be as well developed.
Scope:The solution aims at enhancing the collaborative airport performance planning and monitoring processes, in particular, through the inclusion in the airside processes of the relevant landside (passenger and baggage flow) process outputs, the consideration of connectivity and multi-modality aspects and the extension of turn-round monitoring within the APOC. The solution goal is to achieve a full and seamless interoperability with the AU operational systems and to improve the connectivity between regional airports and the NMOC.
The solution addresses the digital data management of airport performance thanks to the development and validation of rationalised predictive data driven dash boards fed with all landside and airside leading key performance airport indicators covering the TAM processes. The SESAR Solution will enable stakeholders to pro-actively identify demand and capacity imbalances, their timeframe, location and impacted trajectories and solve them supported by what-if capabilities. The solution explores data and video analytics, big data and machine learning techniques.
Expected Impact:The delivered solutions are expected to have a positive impact on :
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