Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - Domino (Novel tools to evaluate ATM systems coupling under future deployment scenarios)

Teaser

Domino, “Novel tools to evaluate ATM systems coupling under future deployment scenarios”, is a SESAR Exploratory Research project funded through Horizon 2020. The project consortium is led by the University of Westminster with partners: EUROCONTROL, University of Trieste...

Summary

Domino, “Novel tools to evaluate ATM systems coupling under future deployment scenarios”, is a SESAR Exploratory Research project funded through Horizon 2020. The project consortium is led by the University of Westminster with partners: EUROCONTROL, University of Trieste, University of Bologna and Innaxis Research Institute.

In air traffic management (ATM) systems, the massive number of interacting entities makes it difficult to predict the system-wide effects that innovations might have. Domino is assessing such effects and will identify the impact that innovations might bring for the different stakeholders, based on agent-based modelling and complex network science. Domino is modelling scenarios that mirror different system innovations which change the agents’ actions and behaviour. Suitable network metrics are also needed to evaluate the effect of innovations on the network functioning.

The overall objective of Domino is to develop a set of tools, a methodology and a platform to assess the coupling of ATM systems from a flight and a passenger perspective. The platform will allow ATM system designers to gain insight on the impact of applying new mechanisms. It will provide a view of the impact of deploying solutions in different manners, e.g. harmonised vs. local/independent deployment, and information on the criticality of elements in the system and how this might be different for different stakeholders.

Work performed

During the first year of the project, progress has been made in the core technical workpackages, in addition to more wide-ranging tasks that cover all activities (such as data management). Highlights include:

* A technical model description, that follows a well-known and proven agent-based specification and design methodology (Gaia), has been prepared to provide a detailed agent-based model capable of capturing the interactions between the elements in the system. Further implementation aspects, such as the type of simulation (event driven), the definition of event types and messages triggered by them or the type of communications, have also been detailed. This is a roadmap for the development of the model that is used by Domino but that could be used as a baseline for any further research (i.e. contributing to the dissemination of the project). Helped by the detailed software specification and design activities, the baseline implementation of the model has been achieved.

* The definition of a set of case studies to test the methodology. Three mechanisms have been selected (4D trajectory adjustment, flight prioritisation and flight arrival coordination). For each mechanism three levels of maturity are considered: Level 0 current operations; Level 1 further capabilities from technological and operational improvements; and Level 2, the most advanced case which might require further research (more prospective). This approach was also subject to a consultation with experts. Finally, for each mechanism, different deployment scopes are considered (uptake). With all these considerations, case studies have been described and prioritised.

* The project has advanced towards the identification, test and validation of metrics based on complexity science. This has been done by reviewing classic and network metrics, revealing that existing centrality and causality metrics are insufficient for the scope of Domino. Suggestions have been provided on how to improve these metrics to better serve Domino’s purposes. Some of these findings were reported in a paper presented at the SESAR Innovation Days 2018 conference.

Final results

Domino has already tested known metrics for the identification of centrality and causality, proven their limitations and developed new, more suitable ones. An agent-based model, which includes flights and passengers whilst considering all operations in the ECAC region, has been implemented. Advanced new mechanisms (Level 2) have been identified.

By the end of the project, the metrics will be applied to the different scenarios and a methodology developed to allow the evaluation of the impact of changes in the system which consider the network effects for both flights and passengers.

Website & more info

More info: http://omino-eu.com.