AI and Cloud-Enabled Flight Simulation
Competency-Based Training and Assessment (CBTA) seeks to address many problems facing aviation today: a shortage of qualified pilots, the changing role of the pilot in the face of increasing automation, and the increasing costs of training.
An evolution of evidence-based training (EBT), CBTA shifts the focus onto core
competencies instead of task proficiency or training hours. In theory, more pilots could be trained in less time while improving safety.
Problems remain: How to measure competency without increasing instructor
workload? How to maximize instructor visibility of pilot behavior, especially details that are easily missed? How to eliminate bias and subjectivity in assessment? How to standardize training delivery?
We propose that applications of artificial intelligence in pilot training could help address these problems. One approach is to turn simulators into cloud-enabled smart devices and collect relevant pilot performance data. Cloud platforms can provide security, scalability, and reliability while storing the vast quantities of simulator telemetry.
Working together with pilots and instructors, machine learning models can be trained to recognize the patterns of competency embedded within the data stream. These training analytics are then made available via intelligent dashboards.
Our vision is to see operators provided with a complete CBTA training “ecosystem” that is fully integrated into the Instructor Operating Station (IOS). The IOS will facilitate easy recording of observations as well as visualizing the training needs. This can be achieved using 3rd-party assessment applications such as those of Paladin AI.
These same training needs will also be visualized in a scenario manager, where preconfigured scenarios with different variations could then be loaded into the IOS, offering both standardization and resilience training.
We present a pragmatic approach to AI-powered training that produces data in support of EBT and facilitates CBTA implementation, while also safeguarding pilot data privacy.