Modelling Subjective Complexity through Cognitive Transitions: Extended Framework

Measuring the operational complexity of arrival traffic is critical for supporting decision-making and enhancing traffic management. In our previous work, we proposed a subjective complexity metric that captures transitions in con- trollers’ workload. However, it has certain limitations, as it does not fully integrate domain-specific knowledge—such as the airspace structure of the terminal maneuvering area—and lacked a systematic approach for defining decision boundaries between complexity levels. This study addresses these limitations through two key en- hancements. First, the airspace structure information is incorpo- rated into trajectory analysis, enabling a better characterization of arrival traffic dynamics. Second, a systematic method is devel- oped for automatically determining decision boundaries between complexity levels, thereby reducing reliance on subjective human judgment. Using real-world traffic data, the enhanced metric outper- forms the baseline in capturing workload variations associated with additional controller-issued manoeuvres. Besides, the au- tomatic boundary determination produces results comparable to manually defined boundaries while improving measurement consistency. Together, these enhancements provide a more reliable assessment of controller workload.