Defining and Operationalising Cognitive Resilience in Automated Flight Operations
Developing the Crew Cognitive Resilience Index (CCRI™) to examine post-disruption recovery in commercial aviation
This research examines Cognitive Resilience (CR) in commercial aviation, with particular attention to how flight crews recover, adapt, and make decisions when highly automated flight operations become uncertain, degraded, or non-routine.
As automation increasingly shapes modern flight operations, the pilot’s role has shifted from continuous manual control towards monitoring, interpretation, intervention and recovery. In these conditions, pilots are not simply executing procedures; they are managing ambiguity, workload, automation behaviour, system feedback and operational priorities under time pressure.
The project focuses on the post-disruption recovery phase: what happens after startle, surprise or automation ambiguity has occurred. It explores how Cognitive Resilience (CR) can be conceptually defined, operationally interpreted and examined through the Crew Cognitive Resilience Index (CCRI™), a bounded diagnostic framework designed to support the analysis of resilience-relevant cognitive and behavioural indicators.
Focus Areas
Human performance during automation ambiguity and degraded modes
Post-disruption recovery in non-routine flight scenarios
Situation Awareness (SA), Decision Accuracy (DA), Adaptive Performance (AP), Cognitive Load (CL) and Trust Calibration (TC)
Workload management, attention allocation and recovery prioritisation
Human–automation interaction as a socio-technical system
Implications for simulator training, assessment, debriefing and safety assurance
Methodological Positioning
The research adopts a systems-oriented and simulation-based approach. An Integrative Literature Review (ILR) is used to synthesise relevant evidence from aviation safety, human factors, automation, psychology, training and systems thinking. This review informs the development and refinement of the Crew Cognitive Resilience Index (CCRI™).
Systems-Theoretic Process Analysis (STPA) is used as a systems-theoretic lens to examine control structures, Unsafe Control Actions (UCAs), feedback gaps and degraded automation conditions. Rather than treating pilot performance as an isolated individual issue, the research considers how performance emerges from the interaction between pilots, automation, procedures, training, feedback and organisational context.
A simulator-based study will then examine how Crew Cognitive Resilience Index (CCRI™) indicators vary during non-routine events and degraded automation conditions. The aim is not to replace existing Competency-Based Training and Assessment (CBTA), but to offer a complementary framework for interpreting how pilots recover, adapt and maintain safe performance when automation no longer behaves as expected.
