COntroller adaptive Digital Assistant The CODA project involves developing a system in which hybrid human-machine teams collaboratively perform tasks. To do so, the system put together state of art from different fields: i) Prediction models to foresee future situations and have the system know which activities will be carried out by the operators and their impact on the same human performance; ii) Neurophysiological assessment of mental states to enable the system to know operators’ real current level of workload, attention, stress, fatigue, and vigilance by validating the predicted cognitive models and maximising the effectiveness of the interaction between the human and the machine by developing an HMPE (Human Machine Performance Envelope); iii) AI-based adaptable and explainable systems, to have the system act to prevent future performance or safety issues. Specifically, the project will show how a system could adapt to specific situations and react accordingly by using advanced adaptable and adaptive automation principles that will dynamically guide the allocation of tasks. The system will assess the operator's cognitive status, use current traffic data to foresee the future tasks that the operator will need to perform in the future, and calculate the impact of those tasks in terms of cognitive complexity. With this information, the system will predict the future mental state of the operator and will act accordingly by developing an adaptive automation strategy. For example, imagine an ATCO managing a complex traffic situation and experiencing a medium workload. The system is aware of this (thanks to the neurophysiological assessment). It predicts that the additional upcoming tasks the ATCO will need to take care of will increase their workload, exceeding the maximum an operator can handle. To avoid this, the system decides how to act, following an adaptation strategy: it may, for instance, increment the level of automation, enable additional AI-based tools, or request a sector splitting.

U-AGREE aims to develop an integrated risk model linking the operations of unmanned aircraft (UAS) with some negative effects they may have with regard safety, security, privacy and environment. This risk model is intended to support the airspace risk assessments required by U-space European regulation as well as an amendment to SORA methodology so that risk can be quantitatively estimated, enabling digital implementations leading to swifter operational approval processes. Moreover, the U-AGREE risk model will account for U-space services to mitigate the risk, thus reducing the burden of meeting the SORA operational safety objectives and unleashing operations and business models which are currently economically unviable. To achieve these goals, U-AGREE will start by identifying realistic scenarios where UAS operations will take place and will assess them to identify all the hazards that these operations can pose to safety, security, privacy and environment. Next, the project will agree metrics and thresholds to measure the risk due to these hazards with relevant stakeholders (especially civil aviation authorities and common information services providers). Afterwards, the team will develop mathematical models linking the hazards with their effects (either on the ground or in the air) and will define mitigation barriers using U-space services, as well as algorithms to quantify their effectiveness in terms of risk ratios. These models will be integrated into state-of-the-art U-space simulators to evaluate the applicability and relevance of the proposed integrated risk model in the representative scenarios previously identified by the project. To synchronise the project outcomes with the U-space deployment, a first version of the risk model addressing short term needs will be delivered one year after the project kick-off, whereas a second version addressing mid to long-term needs (e.g., urban air mobility or variable demand) will be delivered at the end of the project.

The resilient growth of global air travel continues to lead to ever busier skies and airports, placing growing workloads on pilots and operators both in the air and on the ground, as well as increasing the demand for pilots globally. Addressing these concerns will require technological solutions, in the form of increasingly automated assistance systems to help alleviate pilot workload (reduced crew operation, extended minimum crew operations), as well as fully autonomous solutions which can support Single Pilot Operations (SPO) in the event of pilot incapacitation. On the other side, the adoption of new operational procedures such as SPO will have an impact on the ground operations and the ATC operators responsibilities. The RESPONSE consortium led by Collins Aerospace aims to deliver one TRL2 solution: safe return to land including pilot incapacitation. The proposed solution directly support pilots’ incapacitation transition monitoring and deliver an integrated air-to-ground SPO CONOPS to enhance safe return to land operations. In the project, the Consortium delivers a technology enabler as pilot incapacitation transition monitoring to detect pilot incapacitation and map cognitive states and degradation of human performance. The solution delivered is a safe return to land CONOPS introducing the role of air-to-ground digital assistants minimizing the required changes from dual pilot operations to SPO, including dealing with pilot incapacitation in the flight deck, with the impact on ATC operators tasks and with the role of human autonomy/AI teaming to support workload reduction. RESPONSE project builds on top of the outcomes and recommendations of SAFELAND project and will enhance the execution of current projects in SESAR3 Industrial Research, actively contributing to the future preparation and delivery of a full demonstrator for safe return to land in the case of SPO.