How can we ensure Situational Awareness for different human in the loop actors in autonomous aviation?

Background

The improve transport for the user strategic priority is critical in ensuring the department delivers and maintains a transport system that meets the needs of the public and addresses what they care about most. It puts the needs and expectations of current and potential users (both passengers and freight customers) at the heart of the operation of the transport system and considers about end-to-end journeys, not just individual transport modes. It is focused on ensuring that our infrastructure and the services which use it meet the varied needs of businesses and the public, are attractive, affordable, sustainable, and resilient is a crucial goal for the department.

Next steps

Get in touch with bridgetoresearch@dft.gov.uk

Source

This question was published as part of the set of ARIs in this document:

DFT-Areas of research interest 2023 GOV UK

Related UKRI funded projects

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    Funded by: Horizon Europe Guarantee

    Lead research organisation: L3HARRIS FLIGHT DATA SERVICES LIMITED

    Why might this be relevant?

    The project focuses on human factors and safety in the integration of AI tools into aviation operations, which partially addresses the question of situational awareness for human actors in autonomous aviation.

  • Towards More Autonomy for Unmanned Vehicles: Situational Awareness and Decision Making under Uncertainty

    It is anticipated that unmanned vehicles will be widely used within military and civilian operations and have a profound influence in our daily life in near future. Before fully realising the potential that unmanned vehi...

    Funded by: EPSRC

    Lead research organisation: Loughborough University

    Why might this be relevant?

    The project focuses on situational awareness and decision making for unmanned vehicles, which is relevant to ensuring situational awareness for different human in the loop actors in autonomous aviation.

  • Advancing Probabilistic Machine Learning to Deliver Safer, More Efficient, and Predictable Air Traffic Control

    The ambition of this partnership between NATS and The Alan Turing Institute is to develop the fundamental science to deliver the world's first AI system to control a section of airspace in live trials. Our research will...

    Funded by: EPSRC

    Lead research organisation: The Alan Turing Institute

  • Safe Flight

    As unmanned and autonomous systems evolve at pace, uncertainty remains around how to integrate autonomous systems in shared airspace in a safe manner. This proposal, entitled Safe Flight, develops and integrates safe nov...

    Funded by: ISCF

    Lead research organisation: GKN AEROSPACE SERVICES LIMITED

  • Autonomy and Decision Making Project

    The ASTRAEA II (Autonomous Systems Technology Related Airborne Evaluation & Assessment) programme will establish the route to operate Unmanned Air Systems (UAS) in civil airspace. The outcome of ASTRAEA will be both ...

    Funded by: Innovate UK

    Lead research organisation: COBHAM MISSION SYSTEMS WIMBORNE LIMITED

  • AI Flight Controllers for Improved Flight Characteristics and Fault Tolerance

    AI systems have a role to play in making flight control systems safer, more robust and cost-effective. Luffy AI has developed adaptive neural networks that allow real-time onboard learning and adaption. In this project, ...

    Funded by: Innovate UK

    Lead research organisation: LUFFY AI LIMITED

  • Human-Autonomous Systems Collective Capability (HASCC)

    Human-Autonomous Systems (HAS) are collections of human and autonomous agencies of great importance to, defence, disaster and emergency response, transport, and energy services (especially in hostile/inhospitable environ...

    Funded by: EPSRC

    Lead research organisation: University of Bath

  • Thales-Bristol Partnership in Hybrid Autonomous Systems Engineering (T-B PHASE)

    Hybrid autonomous systems are those where groups of people are in direct, ongoing interaction with groups of autonomous robots or autonomous software. One prominent current example involves rush-hour traffic made up of...

    Funded by: UUI

    Lead research organisation: University of Bristol

  • DISTRIBUTED SENSING, CONTROL AND DECISION MAKING IN MULTIAGENT AUTONOMOUS SYSTEMS

    Autonomous intelligent systems will find important applications in our future society. Initial applications will be in the following areas: surveillance, intelligence gathering and operational control in the areas of dis...

    Funded by: EPSRC

    Lead research organisation: University of Sheffield

  • Shared Autonomy via Robust Task Planning and Argumentation (SHARPA)

    The overarching objective of this project is to endow autonomous systems with advanced decision-making capabilities and collaboration skills. We aim to build artificial systems that, in real-world environments, are capab...

    Funded by: EPSRC

    Lead research organisation: Royal Holloway University of London

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