Pregled bibliografske jedinice broj: 1091736
Air Traffic Complexity Model Based on Air Traffic Controller Tasks
Air Traffic Complexity Model Based on Air Traffic Controller Tasks, 2020., doktorska disertacija, Fakultet prometnih znanosti, Zagreb
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Naslov
Air Traffic Complexity Model Based on Air Traffic
Controller Tasks
Autori
Antulov-Fantulin, Bruno
Vrsta, podvrsta i kategorija rada
Ocjenski radovi, doktorska disertacija
Fakultet
Fakultet prometnih znanosti
Mjesto
Zagreb
Datum
01.10
Godina
2020
Stranica
356
Mentor
Juričić, Biljana
Ključne riječi
air traffic complexity ; air traffic controller ; assessment ; workload ; tasks
Sažetak
Existing models for determining air traffic complexity that are based on air traffic controllers' subjective assessment are not consistent due to possible deviations in complexity assessment. The aim of this research is to create a mathematical model for air traffic complexity which is based on the air traffic controller tasks. The model will use the data on area radar air traffic controller tasks that are defined according to the traffic situation. Certain air traffic controller tasks, such as a conflict resolution, are perceived as one task, but they actually represent a set of multidimensional tasks that need to be defined precisely in order to be used later in mathematical model. Moreover, the existing models for determining air traffic complexity which use the subjective air traffic controller assessments also include the problem of subjectivity resulting from the learned mode of operation in a given airspace. For the purpose of this research new generic airspace will be created. This research introduces a new approach to design a model for determining air traffic complexity which is based on defining area radar air traffic controller tasks for the given traffic situations. Area radar air traffic controllers will be asked to decide which of the two traffic situations is more complex by using the comparison method. In this way, any inconsistency in subjective assessments will be avoided, since air traffic controllers tend to give the same complexity score for different levels of air traffic complexity. Using machine learning, inputs such as defined air traffic controller tasks and data gained through comparison method, will be used to develop a new mathematical model for determining air traffic complexity. The validation of the model will be carried out by the same comparison method using the traffic situation data on a different airspace.
Izvorni jezik
Engleski
Znanstvena područja
Tehnologija prometa i transport
POVEZANOST RADA
Ustanove:
Fakultet prometnih znanosti, Zagreb