Estimation of air traffic capacity with disturbance factor in cognitive weather condition

In recent years, there has been a significant increase in air traffic demands, which has led to an increase of load on the Air Traffic Controllers. This change has caused significant delays in flights owing to traffic congestions in airports. Accurate air traffic capacity estimates depend on identif...

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Bibliographic Details
Main Author: Bhargava, Shikhar
Other Authors: Su Rong
Format: Theses and Dissertations
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/76331
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Institution: Nanyang Technological University
Language: English
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Summary:In recent years, there has been a significant increase in air traffic demands, which has led to an increase of load on the Air Traffic Controllers. This change has caused significant delays in flights owing to traffic congestions in airports. Accurate air traffic capacity estimates depend on identifying the parameters that affect it. If the trajectories of flights and all the resources of an aircraft are known with certainty, there exist possibilities to find solutions which minimize the delay cost. The weather plays a vital role in calculating the number of flights; an Air Traffic Controller can control within a sector. Since aircraft handling capacity is an index to measure the ability of the airport to deliver services to meet the air traffic demand. Accurate estimation is a foundation of the effective air traffic management and provides efficient use of aircraft and controlling resources. [17] In this research work, we propose a model where we estimate the terminal aircraft handling capacity with disturbance factors. We find disturbance parameters to measure the weather during mild, moderate and turbulent weather conditions and include them into the existing model to make the existing system more efficient. Besides, this research proposes a way to gather and process the data. Finally, through analysis and validation, we estimate the air traffic capacity with disturbance factors in different weather conditions.