Cognitive Systems Challenges of Virtual Reality (VR) and Simulated Air Traffic Control Environment (SATCE) in Flight Training: The Purdue Case Study

Open Access
Conference Proceedings
Authors: Dimitrios ZiakkasLinda TomkoDimitra Eirini Synodinou

Abstract: Adaptive training capabilities based on AI can provide learners with a personalized learning path. It is a capability that customizes the trainee's learning experience to their identified learning preference while providing the quickest route through the pilot training program. To accomplish this, the training design and process is supported by cognitive theories, providing a succession of contextualized recommendations based on the training program goals and learner performance. The aviation industry seeks novel methods for pilot training that are more efficient. Competency-Based Training and Assessment (CBTA) is a method that proposes an assessment process to help understand how a flight crew manages both foreseen and unforeseen incidents, and uses this data to help the crew achieve a higher level of efficiency and performance. By training pilots in a virtual environment, instructors introduce evidence-based scenarios testing the pilot's performance while collecting relevant data. Biometric data allows for accurate training and assessment of pilot behaviors and performance parameters in competencies like, but not limited to, application of procedures, proper use of automation, manual flying, communication, workload management, situation awareness, decision making, and resilience. Considering communication competencies from a training perspective, AI (Virtual Reality - Simulated Air Traffic Control Environment; VR-SATCE) would allow pilots to improve their communication skills, enable pilots to ask questions with a specifically trained Generative Pre-Trained Transformer (GPT) model, and receive a validated answer. The virtual instructor updates the training scenarios in real-time and corrects the trainees instantly during the training session – in the same or better and safer way an experienced Type Rating Instructor would. Moreover, the same AI crewmember – a virtual instructor – can also function as an uncooperative co-pilot, which will enhance the student's training in managing difficult situations when lacking support from team members. The Purdue School of Aviation and Transportation Technology (SATT) case study focuses on the cognitive aspects of flight training using immersive technologies. This research aims to improve training effectiveness by incorporating immersive technologies in aviation training. Dynamic real-time visualization, automatic human (pilot) profile assessment, and adaptive training system technologies can potentially improve flight training's overall efficacy and efficiency. By using these technologies, all persons participating in flight training will obtain comprehensive insight into the participants' performance and cognitive limitations, ultimately optimizing the training lifecycle.

Keywords: Cognitive Systems, Immersive Technologies, Artificial Intelligence, Human Systems Integration, Simulated Air Traffic Control Environment (SATCE), Communication, Competency-Based Training and Assessment (CBTA)

DOI: 10.54941/ahfe1004473

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