Complexity in Air Traffic Control Towers: A Field Study Part 1— Complexity Factors

Koros, Anton; Della Rocco, Pamela S; Panjwani, Gulshan; Ingurgio, Victor J; D'Arcy, Jean-Francois · 2003 · ROSA P / United States. Department of Transportation. Federal Aviation Administration. William J. Hughes Technical Center

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Summary

This study investigates the factors contributing to operational complexity within Federal Aviation Administration Air Traffic Control Towers (ATCTs). Motivated by the need to improve decision-support automation and ensure safety amidst projected air traffic growth, the research aims to characterize the specific sources of complexity perceived by controllers. While previous studies focused on en route or terminal environments, this field study specifically targets the tower environment, where limited airspace and visual monitoring requirements create unique decision-making constraints. The research seeks to identify how various factors influence controller workload and strategies, providing a foundation for designing automation that aligns with actual human cognitive processes. The methodology involved a field study conducted at six selected ATCTs, chosen based on high traffic volume, traffic mix, and converging runways. The sites included Atlanta (ATL), Chicago O'Hare (ORD), Boston (BOS), Phoenix (PHX), Oakland (OAK), and Jefferson County (BJC). Sixty-two Air Traffic Control Specialists (ATCSs), including Certified Professional Controllers, Traffic Management Coordinators, and Supervisory ATCSs, participated in the study. Participants completed rating forms assessing 29 pre-defined complexity factors across nine categories, such as physical factors, aircraft characteristics, weather, and equipment. They rated each factor on two five-point scales: contribution to complexity (1–5) and frequency of occurrence (1–5). The study also incorporated semi-structured interviews to gather qualitative descriptions of these factors. Data analysis included Analysis of Variance (ANOVA) to compare ratings across sites and positions, as well as exploratory factor analysis to identify underlying groupings of complexity factors. The results indicate that the relative contribution of complexity factors is site-specific and position-specific. However, high traffic volume, frequency congestion, and runway/taxiway configuration were identified as leading complexity factors across all sites for both local and ground control positions. For local controllers, active runway crossings and aircraft differing in performance characteristics were the most highly rated factors. Conversely, ground controllers reported that runway/taxiway restrictions and Traffic Management Initiatives (TMIs) contributed more significantly to their complexity. Other top-rated factors included on-the-job training, reduced visibility due to weather, and active runway crossings. The study found that while some factors were universally complex, their incidence and impact varied depending on the specific facility characteristics and the controller's role. The significance of this study lies in its detailed characterization of tower-specific complexity, which informs the development of effective decision-support systems. By understanding the specific factors that drive complexity and the strategies controllers use to mitigate them, designers can create automation tools that better match controller needs and cognitive processes. This enhanced understanding is crucial for predicting the impact of emerging technologies on controller performance and ensuring the continued safety and efficiency of the National Airspace System. The authors recommend further data collection from additional tower facilities and other ATC domains to validate these findings and explore whether complexity sources are consistent across different operational environments.

Key finding

High traffic volume, frequency congestion, and runway configuration were the primary complexity factors across all sites, with local controllers rating active runway crossings as most complex and ground controllers rating runway restrictions as most complex.

Methodology

field_study

Sample size: 62

Provenance

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• road complexity