Predicting Air Traffic Controller Workload

Corver, Sifra; Unger, Dana; Grote, Gudela

doi:10.1177/0018720816639418

Cited by 18 publications

(3 citation statements)

References 32 publications

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“…Radio communication between ATCo's and pilots represents a major contribution to the total task load, besides monitoring the traffic on the radar display (traffic count n) for anticipating possible separation conflicts (Manning et al 2001;Averty et al 2004;Djokic et al 2010;Corver et al 2016). Because communication (task) load under nominal conditions increases with traffic count, it seemed appropriate to use a one-dimensional WL measure for the experiment.…”

Section: Experimental Design and Workload Assessmentmentioning

confidence: 99%

“…They took into account changing task priorities for WL management and strategies of operators, and emphasized traffic density as indirect WL predictor due to task demands such as identifying, monitoring, and instructing aircraft (AC) via radio communication. Corver et al showed (Corver et al 2016) that traffic conflict, moderated by trajectory uncertainty, mediates the positive effect of traffic density on WL. The specific question of ATC complexity as WL driver was investigated, e.g.…”

Section: Introductionmentioning

confidence: 99%

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Power law model for subjective mental workload and validation through air traffic control human-in-the-loop simulation

Fürstenau

Radüntz

2021

Cogn Tech Work

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We provide evidence for a power law relationship between the subjective one-dimensional Instantaneous Self Assessment workload measure (five-level ISA-WL scale) and the radio communication of air traffic controllers (ATCOs) as an objective task load variable. It corresponds to Stevens’ classical psychophysics relationship between physical stimulus and subjective response, with characteristic power law exponent γ of the order of 1. The theoretical model was validated in a human-in-the loop air traffic control simulation experiment with traffic flow as environmental stimulus that correlates positively with ATCOs frequency and duration of radio calls (task load, RC-TL) and their reported ISA-WL. The theoretical predictions together with nonlinear regression-based model parameter estimates expand previously published results that quantified the formal logistic relationship between the subjective ISA measure and simulated air traffic flow (Fürstenau et al. in Theor Issues Ergon Sci 21(6): 684–708, 2020). The present analysis refers to a psychophysics approach to mental workload suggested by (Gopher and Braune in Hum Factors 26(5): 519–532, 1984) that was recently used by (Bachelder and Godfroy-Cooper in Pilot workload esimation: synthesis of spectral requirements analysis and Weber's law, SCL Tech, San Diego, 2019) for pilot workload estimation, with a corresponding power law exponent in the typical range of Stevens’ exponents. Based on the hypothesis of cognitive resource limitation, we derived the power law by combination of the two logistic models for ISA-WL and communication TL characteristics, respectively. Despite large inter-individual variance, the theoretically predicted logistic and power law parameter values exhibit surprisingly close agreement with the regression-based estimates (for averages across participants). Significant differences between logistic ISA-WL and RC-TL scaling parameters and the corresponding Stevens exponents as ratio of these parameters quantify the TL/WL dissociation with regard to traffic flow. The sensitivity with regard to work conditions of the logistic WL-scaling parameter as well as the power law exponent was revealed by traffic scenarios with a non-nominal event: WL sensitivity increased significantly for traffic flow larger than a critical value. Initial analysis of a simultaneously measured new neurophysiological (EEG) load index (dual frequency head maps, DFHM, (Radüntz in Front Physiol 8: 1–15, 2017)) provided evidence for the power law to be applicable to the DFHM load measure as well.

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Section: Experimental Design and Workload Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Power law model for subjective mental workload and validation through air traffic control human-in-the-loop simulation

Fürstenau

Radüntz

2021

Cogn Tech Work

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“…As the development of 4D trajectory operation, Zohrevandi et al (2016) designed numbers of scenarios to measure how the level of 4D equipped affect controllers' task load in terminal and en route sectors. Corver et al (2016) studies how trajectory uncertainties impact controllers' workload under various traffic density and conflict situations. This line of research, despite the fresh perspective on the relationship between traffic flow and cognitive measures, are inadequate to analyze the evolutionary dynamics of "human-flow" and the mechanisms through which they interact.…”

Section: Introductionmentioning

confidence: 99%

Empirical exploration of air traffic and human dynamics in terminal airspaces

Yang

Yin

et al. 2017

Transportation Research Part C: Emerging Technologies

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Air traffic is widely known as a complex, task-critical techno-social system, with numerous interactions between airspace, procedures, aircraft and air traffic controllers. In order to develop and deploy high-level operational concepts and automation systems scientifically and effectively, it is essential to conduct an in-depth investigation on the intrinsic traffic-human dynamics and characteristics, which is not widely seen in the literature. To fill this gap, we propose a multi-layer network to model and analyze air traffic systems. A Route-based Airspace Network (RAN) and Flight Trajectory Network (FTN) encapsulate critical physical and operational characteristics; an Integrated Flow-Driven Network (IFDN) and Interrelated Conflict-Communication Network (ICCN) are formulated to represent air traffic flow transmissions and intervention from air traffic controllers, respectively. Furthermore, a set of analytical metrics including network variables, complex network attributes, controllers' cognitive complexity, and chaotic metrics are introduced and applied in a case study of Guangzhou terminal airspace. Empirical results show the existence of fundamental diagram and macroscopic fundamental diagram at the route, sector and terminal levels. Moreover, the dynamics and underlying mechanisms of "ATCOs-flow" interactions are revealed and interpreted by adaptive meta-cognition strategies based on network analysis of the ICCN. Finally, at the system level, chaos is identified in conflict system and human behavioral system when traffic switch to the semi-stable or congested phase. This study offers analytical tools for understanding the complex human-flow interactions at potentially a broad range of air traffic systems, and underpins future developments and automation of intelligent air traffic management systems.

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A Method of Evaluating Air Traffic Controller Time Workload

Dmochowski

Skorupski

2019

Communications in Computer and Information Science

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Predicting Air Traffic Controller Workload

Cited by 18 publications

References 32 publications

Power law model for subjective mental workload and validation through air traffic control human-in-the-loop simulation

Power law model for subjective mental workload and validation through air traffic control human-in-the-loop simulation

Empirical exploration of air traffic and human dynamics in terminal airspaces

A Method of Evaluating Air Traffic Controller Time Workload

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