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ACHIEVING HUMAN-MACHINE COLLABORATION WITH ARTIFICIAL SITUATIONAL AWARENESS

Project description

AI assistant to help human-machine collaboration

Human-machine collaboration is becoming increasingly challenging across various sectors due to the growing introduction of AI and other data technologies. However, these collaborative efforts are often limited by machines’ inability to assess human intent. The EU-funded AWARE project aims to develop an artificial situational awareness system that enables AI to anticipate and respond to humans by understanding human intent and goals. To achieve this, they will create an AI assistant application that will be tested alongside air traffic controllers (ATCOs) to reduce workload and task complexity. The ultimate goal is to enhance ATCOs’ performance through improved collaboration systems.

Objective

The goal of the project is to enable human-machine collaboration by using an artificial situational awareness system which is enabling AI to anticipate and respond to human needs by understanding human intent and goals. While humans are extensively trained to understand the capabilities, limitations, and functionality of the machines they are using, further improvements in human-machine collaboration are currently hindered by lack of awareness of human's intent on the side of machines. The project will develop and test an AI Assistant Application providing adaptable human-centric support to enhance air traffic controller's (ATCO) performance and to reduce ATCOs workload despite high task complexity. This will be achieved by development of human-machine collaboration environment that relies on recognition of ATCO intent, ATCO situation awareness (compared to machine situation awareness) and ATCO mental load. ATCO's intent will be analysed by tracking their attention and human-machine interactions and comparing them to the tasks that need solving as assessed by the artificial situational awareness system. Adaptable support will then be provided either in solving the task they are currently focused on or solving an unrelated task autonomously. This will allow ATCOs to maintain their skills and expertise while preventing a shift towards supervisory control that has been demonstrated to undermine human capability to take-over in situations with degraded automation. A goal of the adaptable and human-aware system is to maintain ATCOs in an active role, to train their skills and expertise on the job while selectively using higher levels of automation to augment capacity. ATCOs are supported in their tasks rather than substituted by automation. It is expected that ATCOs can handle high-complexity scenarios when assisted by an attention-aware support system. ATCO workload is expected to decrease with the use of support functions.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-JU-RIA - HORIZON JU Research and Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-SESAR-2023-DES-ER-02

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Coordinator

SVEUCILISTE U ZAGREBU FAKULTET PROMETNIH ZNANOSTI
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 285 875,00
Address
VUKELICEVA 4
10000 Zagreb
Croatia

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Region
Hrvatska Grad Zagreb Grad Zagreb
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 285 875,00

Participants (7)

Partners (1)

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