Prevention of Aviation Accidents with Prediction of Cognitive States

Aviation has long been a high-level industry along with its advanced technical and technological processes and operations. Latest advances made it possible to possess larger and faster aircraft than before, resulting in a huge increase in the demand for air transportation. Aviation accidents have also increased largely due to the growth in traffic volume. In particular, human-induced errors, alone or together with other factors, are determined as the main factor in the vast majority of accidents. In this study, some theories and methods that include human errors are examined. Among human-induced errors, the conditions that lead to unsafe actions in which situational awareness decreases and cognitive state changes occur are discussed. The study proposes a cognitive information system framework to identify cognitive states. Our preliminary experiment revealed that it is possible to design a real-time cognitive state identification scheme without the need for extensive signal processing.