AI-assisted Cognitive Load Assessment for Mission Aviators
Unique system for assessing the cognitive load and situational awareness of Mission Aviators to improve training and ability to cope with complex operational situations
FUTURE DEFENCE AND SECURITY
Research Project
Mission Aircrew , part of the Australian Defence Force ( ADF ), work on a range of military aircraft , operating some of the world ’ s most sophisticated airborne electronic systems . Often in the backseat of a fast jet , they manage various systems , which can involve surveillance and battle management , air combat , or maritime patrol and response , demanding a high cognitive load .
To enhance the safety and efficiency of each mission , CAE and UNSW are collaborating under the Defence Trailblazer initiative to replicate complex operational tasks and training scenarios . Currently , mission aviators are trained to perform tasks such as remote piloting , sensor operation , mission planning , and weapons system operation . However , they face the risk of cognitive overload and poor situational awareness during training . If not addressed , these issues can persist in actual missions . Present training heavily relies on instructor intervention and subjective assessment . This project aims to automate the assessment of cognitive load and situational awareness with AI assistance , providing objective grading and easing the workload on instructors during formative task training .
The project addresses Defence requirements to understand the training needs for operators of systems with high cognitive load and task performance risk . The introduction of Robotics and Autonomous Systems ( RAS ) capability in Defence is expected to play a key role in sovereign capability . Such systems will require a capable workforce to operate them , collect and interpret data , and make decisions based on the provided information . Training these operators will necessitate a complementary and intelligent training ecosystem that can monitor trainee performance and provide adaptive learning strategies . This ensures progression that suits the learner , results in uniform competency standards , and minimizes attrition in training .
The need for appropriate training for RAS use has been identified in the NAVY RAS-AI strategy 2040 , the ARMY RAS Strategy V2 , and the requirement planning for projects such as AIR 5428 Phase 3 .
Key capabilities
> Decision-making of command-and-control personnel in complex operational environments
> Situational awareness in complex situations
> AI-based technology to assist with improved performance
Differentiators
> First prototype demonstration of key enablers technologies for next generating sensing , command , and control of fleets of RAS
> AI-based algorithm to assist with the training of mission aviators ’ situational awareness and decisionmaking based on different levels of cognitive load
> Project addresses Defence requirements to understand the training needs for operators of systems where there is the potential for high cognitive load and task performance risk extreme pressures
Key customers
> Royal Australian Air Force > Australian Army > Royal Australian Navy
Key partnerships
> Defence Trailblazer > CAE
dtb . solutions / cognitive-load-cae
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