This article describes a mitigation strategy against the risks potentially caused by RPAS capable of performing Specific Category of operations within not segregated airspace. A selection of hazards has been associated to these RPAS and it has been assessed thus obtaining a risk matrix. Considering the basic principles of risk analysis management based on Safety Management System theory, after having implemented the matrix (risks identification and ranking), a new mitigation strategy has been defined in order to maintain constantly the hazards consequences at or below an acceptable level. A strategy based on ‘Expert Systems’ has been chosen. ‘Expert Systems’ are computer systems capable of suggesting solutions to problems emulating human expertise in a given field of knowledge. There are many typologies of ‘Expert Systems’; the ones considered in this article are the rule-based ‘Expert Systems’. They are characterized by a basis of knowledge built from set of rules expressed as ‘IF’-‘THEN’ statements. In this case, each statement has been directly implemented from the operational risks contained in the matrix with a one-to-one correspondence between mitigating rules and hazards for a given RPAS capable of performing Specific Category of operations. The novelty of this process is deemed to be the idea of laying down the basis for the implementation of a software based on artificial intelligence (the ‘Expert System’) to be integrated with the Flight Control System/Autopilot Subsystem of the RPASs object of the original risk assessment in order to recognize risks and promptly mitigate them during the execution of operational sorties within not segregated airspace. Two levels of integration (basic and advanced) are described and discussed in the article.

Specific Category Operations Within the U-Space: Expert Systems Embedded Within RPAS as an Original Mean of Mitigation of Operational Safety Risks / Bonfante, F.; Maggiore, P.; Grimaccia, F.; Filippone, E.; Dalla Vedova, M. D. L.. - In: INTERNATIONAL REVIEW OF AEROSPACE ENGINEERING. - ISSN 1973-7459. - ELETTRONICO. - 14:3(2021).

Specific Category Operations Within the U-Space: Expert Systems Embedded Within RPAS as an Original Mean of Mitigation of Operational Safety Risks

F. Bonfante;P. Maggiore;M. D. L. Dalla Vedova
2021

Abstract

This article describes a mitigation strategy against the risks potentially caused by RPAS capable of performing Specific Category of operations within not segregated airspace. A selection of hazards has been associated to these RPAS and it has been assessed thus obtaining a risk matrix. Considering the basic principles of risk analysis management based on Safety Management System theory, after having implemented the matrix (risks identification and ranking), a new mitigation strategy has been defined in order to maintain constantly the hazards consequences at or below an acceptable level. A strategy based on ‘Expert Systems’ has been chosen. ‘Expert Systems’ are computer systems capable of suggesting solutions to problems emulating human expertise in a given field of knowledge. There are many typologies of ‘Expert Systems’; the ones considered in this article are the rule-based ‘Expert Systems’. They are characterized by a basis of knowledge built from set of rules expressed as ‘IF’-‘THEN’ statements. In this case, each statement has been directly implemented from the operational risks contained in the matrix with a one-to-one correspondence between mitigating rules and hazards for a given RPAS capable of performing Specific Category of operations. The novelty of this process is deemed to be the idea of laying down the basis for the implementation of a software based on artificial intelligence (the ‘Expert System’) to be integrated with the Flight Control System/Autopilot Subsystem of the RPASs object of the original risk assessment in order to recognize risks and promptly mitigate them during the execution of operational sorties within not segregated airspace. Two levels of integration (basic and advanced) are described and discussed in the article.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2912716