Coordinated by:
Research Questions
GMV
Consortium members:
University of Bristol, Skysoft
Can the features of ATM systems be exploited as a complex system (uncertainty, adaptive agents, non-linearity) in the Network Management phase in order to improve ATM performance?
This project aims to improve the performances of the ATM system (e.g. predictability) in the short term planning phase by developing new models and algorithms to enable the Network Manager to better manage the two factors that account for two thirds of the ATFM delay in Europe (weather and knock-on effects), in particular by addressing the key sources of uncertainty (weather, unscheduled demand, air users response to disruptions). A Network Manager and AOC simulation prototypes (together with their underlying models and algorithms) were developed and integrated into an Evaluation Platform to carry out a set of evaluation exercises to assess the achievable ATM performance improvements.
Research Scope
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The project goal is to research how to exploit the key features of the ATM system as a complex system (uncertainty, adaptive agents, and nonlinearity) in the Network Management planning phase to benefit the ATM performance. Furthermore, this project focused on the two factors that jointly account for two thirds of the current total ATFM delay in Europe, i.e. weather and knock-on effects. The attainment of this goal was based mainly on the prototyping of a brand new decision making model (including its mathematical models and algorithms) for the Network Manager in the planning phase that takes into account as distinctive features: a) the flight connection information provided by the air users for their nominal plan, b) the uncertainty information on the unscheduled demand and the probabilistic weather forecast and c) the alternative recovery plans that the air users would prepare to deal with the adverse scenarios. A Network Manager and AOC simulation prototypes (together with their underlying models and algorithms) are developed and integrated into an Evaluation Platform to carry out a set of evaluation exercises to assess the achievable ATM performances benefits.
Research Results
The integration between two elements, the Airline Operations Centre (AOC), which calculates the necessary airspace user recovery plans to cope with adverse scenarios, and the Network Manager (NM), which solves the demand capacity balance problem incorporating uncertainty. The core research aspects are in the introduction of disturbance feedback within the Network Manager optimisation, in order to produce tailored solutions for all scenarios. he structure of a combined AOC/NM ATFM system and the integration of the two parts of the systems were discussed and results showed that the database interface defined is working well and initial iteration results are coherent. During the analysis of the NM output a single iteration demonstrated the benefits, in terms of reduced delays, of a disturbance feedback approach over a single robust plan.
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