How the Tower Air Traffic Controller Workload Influences the Capacity in a Complex Three-Runway Airport

Mascio, Paola Di; Carrara, Riccardo; Frasacco, Luca; Luciano, Eleonora; Ponziani, Andrea; Moretti, Laura

doi:10.3390/ijerph18062807

Cited by 8 publications

(7 citation statements)

References 17 publications

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“…Five categories contribute to collecting input data for CAPAN: environment data (e.g., route network, airspace structure, sectors), traffic data (e.g., flight plans, aircraft performances), simulation parameters (e.g., conflict detection/resolution, procedures, separation minima's), ATC tasks, and sector manning (Eurocontrol, 2016). The simulated controller position in ACC has a workload to be compared to the overload threshold of ATC (i.e., the theoretical sector capacity), which occurs when the time spent by ATC in predefined tasks reaches 70% of the absolute working time (i.e., 42 min during 1 hour) (Loft et al, 2007;Di Mascio et al, 2021b, 2021c.…”

Section: Methodsmentioning

confidence: 99%

Entry Count vs Occupancy Count to assess sector capacity with Fast Time Simulation

Di Mascio

2023

European Transport/Trasporti Europei

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An air traffic controller should manage aircraft movements per hour to ensure the safety and efficiency of the traffic system. This study proposed an innovative methodology to estimate the air traffic controllers’ workload through sector occupancy. Starting with a model for the workload of sector controllers designed by Eurocontrol for tower controllers, the authors defined a taskload model from real audio that occurred in an examined Terminal Control Area (TMA). Moreover, trombones have been implemented to sequence arrival flows in the simulated TMA. Therefore, an airside model has been reproduced using Fast Time Simulation software, and its capacity has been calculated in terms of occupancy due to approaching movements. The results permit to evaluate the impact of infrastructural and operative modifications on the sector capacity in terms of hourly entry count and occupancy. Total and maximum occupancy values have been deepened to identify the best predictive factor of controllers’ workload and to manage the airspace configuration.

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Section: Methodsmentioning

confidence: 99%

Entry Count vs Occupancy Count to assess sector capacity with Fast Time Simulation

Di Mascio

2023

European Transport/Trasporti Europei

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“…It is therefore considered admissible to consider calculation scenarios with a reduction in taxiing time of 1, 2, and 3 min (RED1, RED2, RED3, respectively), compared to the average values defined in Table 1, as these timeframes frequently occur in real operational scenarios [43]. For the Study Airport, a fast time simulation with runway capacity analyzer and airside capacity analyzer allowed modeling future operative scenarios with optimized ground handling procedures and modified layout of aprons and taxiways [44][45][46]. In particular, the conflict resolution of taxiing paths and the reduction of the departure queue at runway entry points significantly reduce TIM and emissions [47,48].…”

Section: Reducing Taxiing Timementioning

confidence: 99%

Optimization of Aircraft Taxiing Strategies to Reduce the Impacts of Landing and Take-Off Cycle at Airports

et al. 2022

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The increasing attention of opinion towards climate change has prompted public authorities to provide plans for the containment of emissions to reduce the environmental impact of human activities. The transport sector is one of the main ones responsible for greenhouse emissions and is under investigation to counter its burdens. Therefore, it is essential to identify a strategy that allows for reducing the environmental impact produced by aircraft on the landing and take-off cycle and its operating costs. In this study, four different taxiing strategies are implemented in an existing Italian airport. The results show advantageous scenarios through single-engine taxiing, reduced taxi time through improved surface traffic management, and onboard systems. On the other hand, operating towing solutions with internal combustion cause excessive production of pollutants, especially HC, CO, NOX, and particulate matter. Finally, towing with an electrically powered external vehicle provides good results for pollutants and the maximum reduction in fuel consumption, but it implies externalities on taxiing time. Compared to the current conditions, the best solutions ensure significant reductions in pollutants throughout the landing and take-off cycle (−3.2% for NOx and −44.2% for HC) and economic savings (−13.4% of fuel consumption).

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“…Instead, other studies may use the term workload to indicate task load (e.g., the number of aircrafts that must be monitored), which in our case is one of the independent variables affecting the amount of cognitive resources available to execute one or more tasks. For example, a study by Di Mascio et al [4] employed a modified CAPAN method to investigate the human element by examining TWR controller workload. Their findings suggest that exceeding the maximum manageable airside traffic volume would result in an unacceptable workload for TWR controllers.…”

Section: Introductionmentioning

confidence: 99%

Air Traffic Controllers’ Rostering: Sleep Quality, Vigilance, Mental Workload, and Boredom: A Report of Two Case Studies

Terenzi,

Tempestini,

Di Nocera

2024

Aerospace

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Fatigue in air traffic management (ATM) is a well-recognized safety concern. International organizations like ICAO and EASA have responded by advocating for fatigue risk management systems (FRMSs). EU Regulation 2017/373, implemented in January 2020, mandates specific requirements for air traffic service providers (ANSPs) regarding controller fatigue, stress, and rostering practices. These regulations are part of broader safety management protocols. Despite ongoing efforts to raise awareness about fatigue in ATC, standardized operational requirements remain elusive. To address this gap, Eurocontrol recently published “Guidelines on fatigue management in ATC rostering systems” (23 April 2024). This initiative aims to facilitate the adoption of common fatigue management standards across operations. However, neither EU Regulation 2017/373 nor existing documentation provides definitive rostering criteria. ANSPs typically derive these criteria from a combination of scientific research, best practices, historical data, and legal and operational constraints. Assessing and monitoring fatigue in the real-world ATC setting is complex. The multifaceted nature of fatigue makes it difficult to study, as it is influenced by many factors including sleep quality, circadian rhythms, psychosocial stressors, individual differences, and environmental conditions. Long-term studies are often required to fully understand these complex interactions. This paper presents two case studies that attempt to create an evidence-based protocol for fatigue risk monitoring in ATC operations. These studies utilize a non-invasive approach and collect multidimensional data. The cases involved en-route and tower (TWR) controllers from different ATC centers. The results highlight the importance of fatigue assessment in ATC and shed light on the challenges of implementing fatigue monitoring systems within operational environments.

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How the Tower Air Traffic Controller Workload Influences the Capacity in a Complex Three-Runway Airport

Cited by 8 publications

References 17 publications

Entry Count vs Occupancy Count to assess sector capacity with Fast Time Simulation

Entry Count vs Occupancy Count to assess sector capacity with Fast Time Simulation

Optimization of Aircraft Taxiing Strategies to Reduce the Impacts of Landing and Take-Off Cycle at Airports

Air Traffic Controllers’ Rostering: Sleep Quality, Vigilance, Mental Workload, and Boredom: A Report of Two Case Studies

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