Optimum airspace sectorisation with hexagonal cell-based workload modelling

The increase in demand for air travel, and burgeoning emphasis on aviation safety has increased the importance of well-distributed workload on Air Traffic Controllers (ATCos), so that they have optimal concentration on tasks at hand. In this aspect, increasing amount of research are being conducted...

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Main Author: Tong, Grace Jing Ying
Other Authors: Mao Jianfeng
Format: Final Year Project
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/68699
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-686992023-03-04T18:24:16Z Optimum airspace sectorisation with hexagonal cell-based workload modelling Tong, Grace Jing Ying Mao Jianfeng School of Mechanical and Aerospace Engineering DRNTU::Engineering The increase in demand for air travel, and burgeoning emphasis on aviation safety has increased the importance of well-distributed workload on Air Traffic Controllers (ATCos), so that they have optimal concentration on tasks at hand. In this aspect, increasing amount of research are being conducted by aviation authorities and institutes on new software and optimization models. These researches are carried out in both flight routing procedures and sectorisation. One particular area of focus in the research on sectorisation is hexagonal cell based modeling. The objective of hexagonal cell based modeling is to enable use of optimization techniques for airspace sectorisation. This research adapts the model introduced by Yousefi. An amalgation of Yousefi’s models and common constraints in air traffic sectorisation are further explored and the effectiveness of the model was studied. Findings demonstrate the feasibility of Yousefi’s hexagonal cell-based modeling in sectorisation using Genetic Algorithm. Bachelor of Engineering (Aerospace Engineering) 2016-05-31T01:42:44Z 2016-05-31T01:42:44Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/68699 en Nanyang Technological University 77 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Tong, Grace Jing Ying
Optimum airspace sectorisation with hexagonal cell-based workload modelling
description The increase in demand for air travel, and burgeoning emphasis on aviation safety has increased the importance of well-distributed workload on Air Traffic Controllers (ATCos), so that they have optimal concentration on tasks at hand. In this aspect, increasing amount of research are being conducted by aviation authorities and institutes on new software and optimization models. These researches are carried out in both flight routing procedures and sectorisation. One particular area of focus in the research on sectorisation is hexagonal cell based modeling. The objective of hexagonal cell based modeling is to enable use of optimization techniques for airspace sectorisation. This research adapts the model introduced by Yousefi. An amalgation of Yousefi’s models and common constraints in air traffic sectorisation are further explored and the effectiveness of the model was studied. Findings demonstrate the feasibility of Yousefi’s hexagonal cell-based modeling in sectorisation using Genetic Algorithm.
author2 Mao Jianfeng
author_facet Mao Jianfeng
Tong, Grace Jing Ying
format Final Year Project
author Tong, Grace Jing Ying
author_sort Tong, Grace Jing Ying
title Optimum airspace sectorisation with hexagonal cell-based workload modelling
title_short Optimum airspace sectorisation with hexagonal cell-based workload modelling
title_full Optimum airspace sectorisation with hexagonal cell-based workload modelling
title_fullStr Optimum airspace sectorisation with hexagonal cell-based workload modelling
title_full_unstemmed Optimum airspace sectorisation with hexagonal cell-based workload modelling
title_sort optimum airspace sectorisation with hexagonal cell-based workload modelling
publishDate 2016
url http://hdl.handle.net/10356/68699
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