Relational Complexity Network and Air Traffic Controllers' Workload and Performance

摘要

This paper makes a review on current workload models of air traffic controllers. Lack of proper aggregation method and ecological validity were identified as major inadequacies. We introduce the relational complexity network (RCN) framework which is formed on two ideas: (1) using a network approach to represent the aircraft pattern matches the information structure and action space of controllers; (2) controllers will proactively utilize this structure to perform their task. As a theory-driven computational model, the RCN framework can be used to (1) add extra predictive power to the controllers' workload models based on aircraft-level or pair-level information; (2) predict controllers' overt operational behaviors; and (3) understand various effects from visual grouping to operational constraints.