Automation on board transport aircraft has evolved to the point where the pilot’s role is becoming increasingly supervisory and managerial in nature. However, its complexity has led to the risk of pilots becoming less aware of how the automation is behaving. In addition, automation may become disengaged in abnormal and emergency situations and this may result in an undesirable significant increase in crew workload.

SMARTAP proposed a novel concept of automation, whereby Artificial Intelligence (AI) and Machine Learning (ML) algorithms were developed to automatically (a) recover an aircraft from Loss of Control (LOC) situations, such as aerodynamic stalls and (b) identify airports and runways in real-time on the basis of aerial images captured during approach and landing. In this way, SMARTAP aimed to contribute to increased safety of air transport. SMARTAP was carried out in collaboration with QuAero Ltd.