Modelling the Human Air Traffic Controller, Part 1: Expert-Trainee Differences in Conflict Detection

Abstract

The provision of air traffic management services is highly dependent on the ability of controllers to ascertain whether or not aircraft will lose separation (known as conflict detection). Due to flight environmental factors there is an inherent uncertainty involved in predicting aircraft trajectory. A model of conflict detection is presented that assumes that controllers predict aircraft progress between a minimum and maximum speed and climb/descent rate, depending on error bounds placed on nominal values. An initial study is reported to calibrate this model. Controllers indicated whether they would intervene to assure separation between pairs of converging aircraft at cruising altitude. A 5nm lateral separation standard was used. Based on nominal speeds, minimum lateral distance of separation varied from 0nm to 20nm. Experts were more likely to intervene than trainees. The effects of expertise are captured by assuming that experts are sensitive to greater uncertainty in the minimum and maximum speed of aircraft than trainees. Directions for future research are outlined

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