Periodic Reporting for period 2 - FARO (saFety And Resilience guidelines for aviatiOn)
Okres sprawozdawczy: 2021-05-01 do 2022-10-31
The high numbers of people travelling by air, coupled with an expanded range of non-conventional aircraft, including various unmanned vehicles, makes the skies ever-more challenging to manage. The European Union’s SESAR programme was set up to increase the efficiency and environmentally-friendliness of European airspace by developing and harnessing cutting edge technologies – especially those that automate operations. To quantify their likely impact SESAR applies cost-benefit analysis to key performance areas like safety, capacity and operational efficiency. To support this performance-driven approach, the FARO project, which stands for "saFety And Resilience guidelines for aviatiOn”, has developed a set of methodologies and techniques to assess air traffic management (ATM) safety and resilience.
These changes can be diverse. For example, the application of a new technology, changes in the organisations, or changes in how people operate the ATM system and the operational environment. The project was organised through four objectives, which are described as follows:
- O1 Capitalisation on the existent knowledge of safety. This objective pursued to systematically extract existent safety knowledge by applying data-driven techniques combined with a knowledge-based approach, levering the knowledge of experts within the consortium, and exploiting experience from other transport modes.
- O2 Quantification of the impact of increasing the level of automation on ATM safety levels. This objective aimed at generating predictive models of safety events as a function of the technological, organisational, human, and procedural dimensions and automation solutions defined in the scenarios considered.
- O3 Analysis of the impact of higher levels of automation on ATM resilient performance. This objective was related to the analysis of the impact on resilient performance (absorptive, restorative and adaptive capacity) of the system by characterising it as a function of performance variability, brittleness and adaptive capacity in terms of the same dimensions and automation solutions of objective O2.
- O4 Provision of design guidelines and identification of future research needs.
In summary, the main objective of this project was to contribute to the extant knowledge of safety and resilience of the ATM system by providing design guidelines for applying FARO’s approach and identifying areas of improvement and future research needs as well. As main conclusions of the project and related to the project:
1. Safety Performance Functions and the technical approach selected by the project have demonstrated provision of a non-linear safety quantification methodology, flexible, and capable of accommodating different types of precursors of safety-related occurrences, answering to O1 & O2.
2. FARO demonstrated that Resilience Engineering can adopt quantitative methods complementing the current qualitative approach. FARO showed evidence about how quantitative aspects of performance can be documented, being able to represent an understanding of the systems under study that went beyond a qualitative narrative of the strategies of the system agents and actors.
3. The integration between Safety and Resilience Engineering through the methods proposed by FARO has the potential to facilitate the understanding and evaluation of interdependencies between competing goals. These methods facilitate the understanding on how a change in the operating system (human, technology, organisations) can impact in the balance between safety and resilient performance.
These changes can be diverse. For example, the application of a new technology, changes in the organisations, or changes in how people operate the ATM system and the operational environment. The project was organised through four objectives, which are described as follows:
- O1 Capitalisation on the existent knowledge of safety. This objective pursued to systematically extract existent safety knowledge by applying data-driven techniques combined with a knowledge-based approach, levering the knowledge of experts within the consortium, and exploiting experience from other transport modes.
- O2 Quantification of the impact of increasing the level of automation on ATM safety levels. This objective aimed at generating predictive models of safety events as a function of the technological, organisational, human, and procedural dimensions and automation solutions defined in the scenarios considered.
- O3 Analysis of the impact of higher levels of automation on ATM resilient performance. This objective was related to the analysis of the impact on resilient performance (absorptive, restorative and adaptive capacity) of the system by characterising it as a function of performance variability, brittleness and adaptive capacity in terms of the same dimensions and automation solutions of objective O2.
- O4 Provision of design guidelines and identification of future research needs.
In summary, the main objective of this project was to contribute to the extant knowledge of safety and resilience of the ATM system by providing design guidelines for applying FARO’s approach and identifying areas of improvement and future research needs as well. As main conclusions of the project and related to the project:
1. Safety Performance Functions and the technical approach selected by the project have demonstrated provision of a non-linear safety quantification methodology, flexible, and capable of accommodating different types of precursors of safety-related occurrences, answering to O1 & O2.
2. FARO demonstrated that Resilience Engineering can adopt quantitative methods complementing the current qualitative approach. FARO showed evidence about how quantitative aspects of performance can be documented, being able to represent an understanding of the systems under study that went beyond a qualitative narrative of the strategies of the system agents and actors.
3. The integration between Safety and Resilience Engineering through the methods proposed by FARO has the potential to facilitate the understanding and evaluation of interdependencies between competing goals. These methods facilitate the understanding on how a change in the operating system (human, technology, organisations) can impact in the balance between safety and resilient performance.
1. The identification of a Safety and Resilience Conceptual Framework.
2. The development of Machine Learning-based algorithms for the exploitation of extant airprox reports to identify hidden factors contributing to safety and resilient performance, as well as initial models for evaluating the contribution of the different agents in safety-related occurrences.
3. The conceptual definition of the Safety Performance Functions as well as their technical representation in the form of a hyper-structures of Bayesian Belief Networks. In addition, the project showcased methodologies to exploit the safety performance functions as well as visualisation artifacts to convey the complex information to simpler forms.
4. The development of a Baseline Model for resilience in Air Traffic Management and a methodology for the definition of indicators of resilient performance indicators as an approach towards quantification in Resilience Engineering.
5. The development of a conceptual model (SEESAW) aiming for the integration of Safety and Resilient Performance. In addition, the project also developed a technical Safety and Resilience Bayesian Belief Network (SR-BBN) integrating safety and resilience variables identified as the most relevant in describing the resilient performance.
6. Finally, as a final research product of FARO, the project produced the Safety and Resilience Guidelines. This work is a set of guidelines for applying the methodologies presented in FARO.
With regard to the main achievements in terms of communications, dissemination and exploitation, FARO has participated in ten scientific conferences, including two editions of the SESAR Innovation Days, publishing papers in reputed journals and Open Europe and participating in fair trades such as the World ATM Congress. More importantly, FARO has reached key stakeholders, presenting its results to SESAR PJ19.4 Performance Management and EASA.
2. The development of Machine Learning-based algorithms for the exploitation of extant airprox reports to identify hidden factors contributing to safety and resilient performance, as well as initial models for evaluating the contribution of the different agents in safety-related occurrences.
3. The conceptual definition of the Safety Performance Functions as well as their technical representation in the form of a hyper-structures of Bayesian Belief Networks. In addition, the project showcased methodologies to exploit the safety performance functions as well as visualisation artifacts to convey the complex information to simpler forms.
4. The development of a Baseline Model for resilience in Air Traffic Management and a methodology for the definition of indicators of resilient performance indicators as an approach towards quantification in Resilience Engineering.
5. The development of a conceptual model (SEESAW) aiming for the integration of Safety and Resilient Performance. In addition, the project also developed a technical Safety and Resilience Bayesian Belief Network (SR-BBN) integrating safety and resilience variables identified as the most relevant in describing the resilient performance.
6. Finally, as a final research product of FARO, the project produced the Safety and Resilience Guidelines. This work is a set of guidelines for applying the methodologies presented in FARO.
With regard to the main achievements in terms of communications, dissemination and exploitation, FARO has participated in ten scientific conferences, including two editions of the SESAR Innovation Days, publishing papers in reputed journals and Open Europe and participating in fair trades such as the World ATM Congress. More importantly, FARO has reached key stakeholders, presenting its results to SESAR PJ19.4 Performance Management and EASA.
The project has progressed beyond the state of the art in different areas. The project advanced in three different streams: safety performance functions, resilience engineering and quantitative methods based on data exploitation, and the integration between these views.
- The Safety Performance Functions have demonstrated to provide a non-linear safety quantification methodology, flexible, and capable of accommodating different types of features.
- FARO demonstrates that Resilience Engineering can adopt quantitative methods complementing the current corpus of qualitative methods and narratives. As Hollnagel put in From Resilience Engineering to Resilient Performance, “quantitative aspects of performance can be documented and added to qualitative data to become part of the resilience narrative”. FARO showed evidence in this direction, being able to represent an understanding of the systems under study that went beyond a qualitative narrative of the strategies of the system agents.
- Finally, the integration between Safety and Resilience Engineering methods (SEESAW + SR-BBN) has the potential to facilitate the understanding and evaluation of interdependencies between competing goals. These methods facilitate the understanding on how a change in the operating system (human, technology, organisations) can impact in the balance between safety and resilient performance.
In addition, beyond these key achievements, the project has progressed beyond the state of the art in te application of NLP and ML techniques to safety-related reports. In this sense, for the automatic extraction of the safety factors and their classification according to the TOKAI taxonomy, the project leveraged on Syntactic Analysis and in the definition of a S&R Conceptual framework, which included the identification of the wide range of data dimensions to be potentially used by both safety and resilience models.
- The Safety Performance Functions have demonstrated to provide a non-linear safety quantification methodology, flexible, and capable of accommodating different types of features.
- FARO demonstrates that Resilience Engineering can adopt quantitative methods complementing the current corpus of qualitative methods and narratives. As Hollnagel put in From Resilience Engineering to Resilient Performance, “quantitative aspects of performance can be documented and added to qualitative data to become part of the resilience narrative”. FARO showed evidence in this direction, being able to represent an understanding of the systems under study that went beyond a qualitative narrative of the strategies of the system agents.
- Finally, the integration between Safety and Resilience Engineering methods (SEESAW + SR-BBN) has the potential to facilitate the understanding and evaluation of interdependencies between competing goals. These methods facilitate the understanding on how a change in the operating system (human, technology, organisations) can impact in the balance between safety and resilient performance.
In addition, beyond these key achievements, the project has progressed beyond the state of the art in te application of NLP and ML techniques to safety-related reports. In this sense, for the automatic extraction of the safety factors and their classification according to the TOKAI taxonomy, the project leveraged on Syntactic Analysis and in the definition of a S&R Conceptual framework, which included the identification of the wide range of data dimensions to be potentially used by both safety and resilience models.