Pseudo-pilots work in real-time simulations in air traffic control training and carry out an important task to ensure appropriate training for the trainee controllers. They are in constant communication with controllers during the training and are responsible for fulfilling the instructions given by the controllers. Unlike real operations, pseudo-pilots are required to monitor many aircraft simultaneously on the simulator’s radar screen and perform various interventions. This situation can be challenging, and the impact of such situations on their workload is usually neglected. In the literature, various studies have revealed the factors affecting controller workload; however, the factors affecting the workload of pseudo-pilots have not been emphasized. In this study, statistical analyses were carried out using the data obtained from real-time simulations and NASA-TLX surveys. As a result, the number of aircraft, controller performance, and the interruption duration were determined as the key factors that affect the overall workload of pseudo-pilots.
This study presents a mathematical model that schedules arrival aircraft regarding RECAT-EU that is new categorisation for applying separation minima and analyses its effect on the performance of the Point Merge System (PMS) at Sabiha Gökcen International Airport (LTFJ). There are two main scenarios: one of them uses RECAT-EU and the other employs the ICAO wake turbulence category. Both scenarios have ten different test problems to examine the mathematical model. The model applies RECAT-EU wake turbulence categories and compares the outcome with the ICAO wake turbulence categories. The model aims to minimise flight duration on the sequencing leg and ground delay in the departure queue using the RECAT-EU and ICAO wake turbulence categories individually. The results were analysed to reveal the PMS performance using the two different approaches to turbulence categories. Statistical analysis was also carried out to compare the means of the two groups in the model.
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