Abstract

This paper outlines a human error identification (HEI) technique called TRACEr—technique for the retrospective and predictive analysis of cognitive errors in air traffic control (ATC). The paper firstly considers the need for an HEI tool in ATC, and key requirements for the technique are noted. The technique, which comprises a number of inter-related taxonomies, based around a simple cognitive framework, is then described. A study concerning a real-world application of TRACEr is outlined—the evaluation of several options for reduced separation minima in unregulated UK airspace. In this study, TRACEr was used predictively and retrospectively, looking forward to pre-empt potential problems and looking back to learn from experience. The paper concludes that TRACEr is a valuable aid to design, development and operations in UK ATC, and has indeed been used as a basis for further applications in ATC both in Europe and the USA.

Why air traffic control needs a human error identification tool

Air transport is seeing increasing growth year by year, with passenger air transport, in particular, becoming more affordable and feasible for both short journeys and long haul flights. This has resulted in a growth in air traffic movements by 6–۷% per year in the UK, which is ultimately reflected in an increase in workload for air traffic controllers. Thankfully, there have been few midair collisions in controlled airspace in the world’s aviation history. Indeed, Richard Profit, Group Director Safety Regulation, UK Civil Aviation Authority, has stated that the fatal accident record for UK public transport operations generally is four times better than the world average, with a flight safety record among the best in the world (Profit, 2001).