BUBBLES is a project targeting the formulation and validation of a concept of separation management for UAS (Unmanned Aircraft Systems) in the U-space. U-space is a set of new services relying on a high level of digitalisation and automation of functions and specific procedures designed to support safe, efficient and secure access to airspace for large numbers of drones. BUBBLES will develop Artificial Intelligence (AI) based algorithms to compute the collision risk of UAS leading to separation minima and methods so that a Target Level of Safety (TLS) stated in terms of overall probability of collision can be defined and maintained. These algorithms will be applied to a set of generic ConOps for UAS operations defined by BUBBLES, detailed enough to cover most of the envisaged applications, but generic enough not to be linked to any particular one. They will be classified in terms of risk using the SORA methodology. These separation minima and methods will be assigned to the ConOps using AI techniques, leading to the definition of a set of generic OSEDs from which safety and performance requirements for the CNS systems will be derived applying a performance-based approach.
H2020-SESAR
Start date: 2020-05-01     End data: 2022-10-31
Project page

BUBBLES is a project targeting the formulation and validation of a concept of separation management for UAS (Unmanned Aircraft Systems) in the U-space. U-space is a set of new services relying on a high level of digitalisation and automation of functions and specific procedures designed to support safe, efficient and secure access to airspace for large numbers of drones. BUBBLES will develop Artificial Intelligence (AI) based algorithms to compute the collision risk of UAS leading to separation minima and methods so that a Target Level of Safety (TLS) stated in terms of overall probability of collision can be defined and maintained. These algorithms will be applied to a set of generic ConOps for UAS operations defined by BUBBLES, detailed enough to cover most of the envisaged applications, but generic enough not to be linked to any particular one. They will be classified in terms of risk using the SORA methodology. These separation minima and methods will be assigned to the ConOps using AI techniques, leading to the definition of a set of generic OSEDs from which safety and performance requirements for the CNS systems will be derived applying a performance-based approach.
H2020-SESAR
Start date: 2020-05-01     End data: 2022-10-31
Project page

BUBBLES is a project targeting the formulation and validation of a concept of separation management for UAS (Unmanned Aircraft Systems) in the U-space. U-space is a set of new services relying on a high level of digitalisation and automation of functions and specific procedures designed to support safe, efficient and secure access to airspace for large numbers of drones. BUBBLES will develop Artificial Intelligence (AI) based algorithms to compute the collision risk of UAS leading to separation minima and methods so that a Target Level of Safety (TLS) stated in terms of overall probability of collision can be defined and maintained. These algorithms will be applied to a set of generic ConOps for UAS operations defined by BUBBLES, detailed enough to cover most of the envisaged applications, but generic enough not to be linked to any particular one. They will be classified in terms of risk using the SORA methodology. These separation minima and methods will be assigned to the ConOps using AI techniques, leading to the definition of a set of generic OSEDs from which safety and performance requirements for the CNS systems will be derived applying a performance-based approach.
H2020-SESAR
Start date: 2020-05-01     End data: 2022-10-31
Project page

BUBBLES is a project targeting the formulation and validation of a concept of separation management for UAS (Unmanned Aircraft Systems) in the U-space. U-space is a set of new services relying on a high level of digitalisation and automation of functions and specific procedures designed to support safe, efficient and secure access to airspace for large numbers of drones. BUBBLES will develop Artificial Intelligence (AI) based algorithms to compute the collision risk of UAS leading to separation minima and methods so that a Target Level of Safety (TLS) stated in terms of overall probability of collision can be defined and maintained. These algorithms will be applied to a set of generic ConOps for UAS operations defined by BUBBLES, detailed enough to cover most of the envisaged applications, but generic enough not to be linked to any particular one. They will be classified in terms of risk using the SORA methodology. These separation minima and methods will be assigned to the ConOps using AI techniques, leading to the definition of a set of generic OSEDs from which safety and performance requirements for the CNS systems will be derived applying a performance-based approach.
H2020-SESAR
Start date: 2020-05-01     End data: 2022-10-31
Project page

BUBBLES is a project targeting the formulation and validation of a concept of separation management for UAS (Unmanned Aircraft Systems) in the U-space. U-space is a set of new services relying on a high level of digitalisation and automation of functions and specific procedures designed to support safe, efficient and secure access to airspace for large numbers of drones. BUBBLES will develop Artificial Intelligence (AI) based algorithms to compute the collision risk of UAS leading to separation minima and methods so that a Target Level of Safety (TLS) stated in terms of overall probability of collision can be defined and maintained. These algorithms will be applied to a set of generic ConOps for UAS operations defined by BUBBLES, detailed enough to cover most of the envisaged applications, but generic enough not to be linked to any particular one. They will be classified in terms of risk using the SORA methodology. These separation minima and methods will be assigned to the ConOps using AI techniques, leading to the definition of a set of generic OSEDs from which safety and performance requirements for the CNS systems will be derived applying a performance-based approach.
H2020-SESAR
Start date: 2020-05-01     End data: 2022-10-31
Project page

BUBBLES is a project targeting the formulation and validation of a concept of separation management for UAS (Unmanned Aircraft Systems) in the U-space. U-space is a set of new services relying on a high level of digitalisation and automation of functions and specific procedures designed to support safe, efficient and secure access to airspace for large numbers of drones. BUBBLES will develop Artificial Intelligence (AI) based algorithms to compute the collision risk of UAS leading to separation minima and methods so that a Target Level of Safety (TLS) stated in terms of overall probability of collision can be defined and maintained. These algorithms will be applied to a set of generic ConOps for UAS operations defined by BUBBLES, detailed enough to cover most of the envisaged applications, but generic enough not to be linked to any particular one. They will be classified in terms of risk using the SORA methodology. These separation minima and methods will be assigned to the ConOps using AI techniques, leading to the definition of a set of generic OSEDs from which safety and performance requirements for the CNS systems will be derived applying a performance-based approach.
H2020-SESAR
Start date: 2020-05-01     End data: 2022-10-31
Project page

BUBBLES is a project targeting the formulation and validation of a concept of separation management for UAS (Unmanned Aircraft Systems) in the U-space. U-space is a set of new services relying on a high level of digitalisation and automation of functions and specific procedures designed to support safe, efficient and secure access to airspace for large numbers of drones. BUBBLES will develop Artificial Intelligence (AI) based algorithms to compute the collision risk of UAS leading to separation minima and methods so that a Target Level of Safety (TLS) stated in terms of overall probability of collision can be defined and maintained. These algorithms will be applied to a set of generic ConOps for UAS operations defined by BUBBLES, detailed enough to cover most of the envisaged applications, but generic enough not to be linked to any particular one. They will be classified in terms of risk using the SORA methodology. These separation minima and methods will be assigned to the ConOps using AI techniques, leading to the definition of a set of generic OSEDs from which safety and performance requirements for the CNS systems will be derived applying a performance-based approach.
H2020-SESAR
Start date: 2020-05-01     End data: 2022-10-31
Project page

BUBBLES is a project targeting the formulation and validation of a concept of separation management for UAS (Unmanned Aircraft Systems) in the U-space. U-space is a set of new services relying on a high level of digitalisation and automation of functions and specific procedures designed to support safe, efficient and secure access to airspace for large numbers of drones. BUBBLES will develop Artificial Intelligence (AI) based algorithms to compute the collision risk of UAS leading to separation minima and methods so that a Target Level of Safety (TLS) stated in terms of overall probability of collision can be defined and maintained. These algorithms will be applied to a set of generic ConOps for UAS operations defined by BUBBLES, detailed enough to cover most of the envisaged applications, but generic enough not to be linked to any particular one. They will be classified in terms of risk using the SORA methodology. These separation minima and methods will be assigned to the ConOps using AI techniques, leading to the definition of a set of generic OSEDs from which safety and performance requirements for the CNS systems will be derived applying a performance-based approach.
H2020-SESAR
Start date: 2020-05-01     End data: 2022-10-31
Project page

BUBBLES is a project targeting the formulation and validation of a concept of separation management for UAS (Unmanned Aircraft Systems) in the U-space. U-space is a set of new services relying on a high level of digitalisation and automation of functions and specific procedures designed to support safe, efficient and secure access to airspace for large numbers of drones. BUBBLES will develop Artificial Intelligence (AI) based algorithms to compute the collision risk of UAS leading to separation minima and methods so that a Target Level of Safety (TLS) stated in terms of overall probability of collision can be defined and maintained. These algorithms will be applied to a set of generic ConOps for UAS operations defined by BUBBLES, detailed enough to cover most of the envisaged applications, but generic enough not to be linked to any particular one. They will be classified in terms of risk using the SORA methodology. These separation minima and methods will be assigned to the ConOps using AI techniques, leading to the definition of a set of generic OSEDs from which safety and performance requirements for the CNS systems will be derived applying a performance-based approach.
H2020-SESAR
Start date: 2020-05-01     End data: 2022-10-31
Project page