The computers helping with flight control and collision avoidance can now consider how pilots are thinking and feeling as part of their decision-making, said intelligent transport and mission systems research group leader Professor Roberto Sabatini.
The new Cognitive Human-Machine Interface and Interaction (CHMI²) system analyses data on the pilot’s eye-movement, facial expression, brain activity, body temperature, voice patterns, posture and exertion as well as emotional stress indicators like those used in lie-detector tests. It uses this information to determine the pilot’s state of mind – for example how tired, stressed or distracted they are – and decide how much computer support is required to fly the plane.
"If computers are helping us fly planes they need to consider more than just weather conditions and other aircraft movements, they also need to understand the condition of the pilot they’re working alongside and change the balance of human-computer control accordingly," Professor Sabatini said.
The system can also be used to support air traffic controllers and may have applications for single person control of multiple unmanned aircraft.
Algorithms and neural networks modelled on the human brain allow the system to learn and improve over time so the more a person interacts with it, the better it performs with them, like with the development of a real human partnership.
Professor Sabatini said, "This is a significant step forward in enabling true, two-way collaboration between humans and machines. The emerging concept of human-machine teaming has massive potential to extend our abilities and performance in aerospace, defence, healthcare and a whole range of industries."
At the latest IEEE International Workshop on Metrology for Aerospace, the team’s paper, Cognitive Human-Machine Interfaces and Interactions for Avionics and Air Traffic Management Systems, was awarded the Best Paper prize on the grounds of quality, technical merit, originality and potential impact in the field.
"Both need to work together to achieve optimum performance and that’s where we’re taking this exciting technology – towards a whole range of real-life applications," Professor Sabatini said.