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Public Deliverables

The Deliverable “D2.1: Project Scope” is the first of the deliverables planned within WP2 “Safety and Resilience Conceptual Framework”.

This document establishes the theoretical basis of the work to be performed within FARO project. It presents the main objectives of the project as well as a summary of the work to be conducted after alignment of the interests of all stakeholders involved, including the
SJU, in the form of entry and exit criteria for each of the Work Packages of the project.

Additionally, it provides a review of the State of the Art in Safety and Resilience domains and in other transportation modes (such as train, maritime and road), as well as the complete list of other SESAR projects that are related to FARO.

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Description of the case studies which will be used to validate the safety and resilience performance models. In addition, it includes the definition of the safety and resilience indicators, and finally, the identification of the dimensions of the data which will be required to develop the case studies.

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This document describes the FARO Data Hub (FDH) pipeline created to support the research & development activities during the SESAR Joint Undertaking project FARO.

This FDH is the pipe through which data will be collected, stored and transferred for all FARO research activities and this document describes its architecture, organisation and connectivity. Additionally, this document provides a detailed description of the data sources introduced into the FDH as raw materials for the research activities of FARO.

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Report describing the NLP and ML techniques used to extract meaningful knowledge from the safety reports. The results will include the identification of safety performance indicators and dimensions derived from the analysis of the results of the application of the NLP to a variety of safety reports.

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FARO WP4 aims at generating predictive models of safety events (Safety Performance Functions – SPFs) by using organisational, technical, human, and procedural precursors to characterise and predict airspace Separation Minima Infringement (SMI), as a function of those precursors.

Deliverable 4.1 is tasked with developing a baseline model of the SPF for the characterization and prediction of airspace Separation Minima Infringement (SMI) in particular ATC sectors. This report covers the research conducted in T4.1 and T4.2.

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FARO WP4 aims at generating predictive models of safety events (Safety Performance Functions – SPFs) by using organisational, technical, human, and procedural precursors to characterise and predict airspace Separation Minima Infringement (SMI), as a function of those precursors.

Deliverable 4.2 is tasked with the adaptation of the generic SPF baseline model to the characteristics of the sectors analyzed in Use Cases 1 and 2, as well as with the derivation of the most Influencing Factors and Applicability Thresholds in each of the models, and the development of a graphical schemeto present, in a synthetic way, the outcomes of the models.

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The Deliverable 5.1 under the FARO project contributes to the ‘Analysis of the impact of higher levels of automation on ATM resilience’.
Deliverable 5.1 delivers a Resilience Model Description for the ATM system through use of resilience engineering and systems theory to assess and understand resilient performance of the work system
and the strategies that are used by all actors to adapt to changing and varying operating conditions and states.

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FARO WP5 contributes to the FARO project by introducing the perspective of resilience engineering and resilient performance to explore and develop an understanding of the characteristics of complex socio-technical systems. With this understanding, WP5 develops a baseline model of resilient performance that can be used to assess changes in the way that the work system design evolves. With this knowledge, assessment of an envisaged design can be explored in terms of resilient performance.
Using this knowledge and understanding, an assessment of resilient performance can be undertaken.

The results of this assessment can be used to derive metrics and indicators of resilient performance. D5.2 reports further on the research undertaken and reported in D5.1 which developed a baseline model for the assessment of resilient performance of socio-technical systems using the ATM system as an exemplar. Resilience engineering is inherently qualitative in nature and character. WP5 also aims to transform qualitative results and findings into a form that can be used for data science applications.

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Deliverable “D6.1: Validation plan” is framed within WP6 of FARO project, and it covers the activities contained in the task T6.1. The purpose of this task is to combine Safety Performance Functions (SPF) from WP4 with resilience model output from WP5 with the aim to demonstrate their usability on selected current and future ATM concepts.

The plan sets the basis for demonstration of usability that will be performed on preselected current and future concept use cases. Analysis of demonstration results will show SPF and resilience model combined use benchmarking and predictive potentials in D6.2.

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Deliverable “D6.2: Validation report” is framed within WP6 of FARO project, and it covers the activities
contained in the task T6.1. The purpose of this task is to combine Safety Performance Functions (SPF)
from WP4 with resilience model output from WP5 with the aim to demonstrate their usability on
selected current and future ATM concepts.

Validation report follows the validation plan set in D6.1 and aims at showing usability and validation
of the safety and resilience models proposed in FARO, on preselected current and future concept use
cases, and scenarios addressing different traffic loads, before and after change environment,
disturbance events etc.

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Do you plan to introduce changes to your ANS/ATM system? How would these changes affect the
safety of your operations? Would they increase resilient performance of the system?

Deliverable “D6.3: Safety and Resilience Integration Guidelines” is framed within FARO WP6 and is
related to FARO project objective “Provision of design guidelines and identification of future research
needs” (O4). Deliverable ultimately provided a description of the Safety and Resilience integration
process and covers the:

  1. overview of how possible changes introduced in ANS/ATM system can impact safety and resilience
    of operations,
  2. description of safety and resilience integration process containing five steps, as well as
    introduction to SEESAW concept and SR-BBN model both proposed by FARO project for the
    integration of safety and resilience, and
  3. recommendations related to data, safety and resilience performances, SEESAW concept and SRBBN model.

This deliverable is written in a way to be used as standalone document providing enough information
to interested stakeholders and referring to other deliverables for more details.

Finally, the Deliverable “D6.3: Safety and Resilience Guidelines” has been renamed as agreed with
the SESAR 3 JU to avoid confusion with the Final Project Results Report (D1.3), which gathers the
project results and next steps in the research.

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Scientific and other publications

Videos

Safety And Resilience Guidelines for Aviation – FARO (Video teaser)

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Scientific publications

 

– Natural language processing for aviation safety: extracting knowledge from publicly-available loss of separation reports (Open Research Europe)

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– Natural Language Processing and Data-Driven Methods for AviationSafety and Resilience: from Extant Knowledge to Potential Precursors (11th SESAR Innovation Days)

Scientific publications

 

– Safety Performance Functions to predict Separation Minima Infringements in en-route airspace (11th EASN International & Esmerald Insight)

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Posters

 

– Analysing the Impact of Automation on ATM Resilience – Methodological Approach to Transforming Qualitative data to Numerical Indicators of Resilient Performance (11th SESAR Innovation Days)

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Posters

 

– Proposal for safety and resilience validation of the new concepts (11th SESAR Innovation Days)

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WP4: Predictive Safety Models for More Autonomous Systems in ATM

WP4: Most influential factors in the detection of potential conflicts between en-route aircraft by ATCO

WP6: Influence of automaion changes on go-around operations: a data-driven approach