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Method for optimal conflict-free aircraft trajectory generation
Purpose A number of automated tools will be required for the purpose of enabling efficient services in air traffic control. The purpose of this paper is to devise an optimal flight trajectory search method that optimizes airspace system efficiency for 3D space in the presence of uncertainties. Desig...
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Published in: | Aircraft engineering 2020-01, Vol.92 (2), p.156-162 |
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Language: | English |
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cites | cdi_FETCH-LOGICAL-c314t-e149e9e364166c7987c3c47fe4d7fbeab4229f2a4a02820c31e9caaa1d566b8a3 |
container_end_page | 162 |
container_issue | 2 |
container_start_page | 156 |
container_title | Aircraft engineering |
container_volume | 92 |
creator | Han, Yun-Xiang Zhang, Jian-Wei Huang, Xiao-Qiong |
description | Purpose
A number of automated tools will be required for the purpose of enabling efficient services in air traffic control. The purpose of this paper is to devise an optimal flight trajectory search method that optimizes airspace system efficiency for 3D space in the presence of uncertainties.
Design/methodology/approach
This paper put forward an optimization model for generating applicable solutions of multi-aircraft conflict resolution problem, and the solution is based on the principle of optimality.
Findings
The conflict resolution problem between multiple aircraft can be described by spatial discretization, and the approach taken digitizes the 3D space into a grid of nodes.
Practical implications
The simulation examples are given to illustrate the validity of trajectory search model and stress on the impact of different system parameters.
Originality/value
Realistic constraints that are convenient to operate are incorporated in the system model, and the results show that it can provide reliable decision-making for conflict avoidance. |
doi_str_mv | 10.1108/AEAT-07-2018-0207 |
format | article |
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A number of automated tools will be required for the purpose of enabling efficient services in air traffic control. The purpose of this paper is to devise an optimal flight trajectory search method that optimizes airspace system efficiency for 3D space in the presence of uncertainties.
Design/methodology/approach
This paper put forward an optimization model for generating applicable solutions of multi-aircraft conflict resolution problem, and the solution is based on the principle of optimality.
Findings
The conflict resolution problem between multiple aircraft can be described by spatial discretization, and the approach taken digitizes the 3D space into a grid of nodes.
Practical implications
The simulation examples are given to illustrate the validity of trajectory search model and stress on the impact of different system parameters.
Originality/value
Realistic constraints that are convenient to operate are incorporated in the system model, and the results show that it can provide reliable decision-making for conflict avoidance.</description><identifier>ISSN: 1748-8842</identifier><identifier>EISSN: 1758-4213</identifier><identifier>EISSN: 1748-8842</identifier><identifier>DOI: 10.1108/AEAT-07-2018-0207</identifier><language>eng</language><publisher>Bradford: Emerald Publishing Limited</publisher><subject>Air rights ; Air traffic control ; Aircraft ; Airspace ; Altitude ; Conflict resolution ; Control algorithms ; Decision making ; Dynamic programming ; Energy consumption ; Graph coloring ; Kinematics ; Optimization ; Search methods ; Trajectory optimization ; Variables</subject><ispartof>Aircraft engineering, 2020-01, Vol.92 (2), p.156-162</ispartof><rights>Emerald Publishing Limited</rights><rights>Emerald Publishing Limited 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c314t-e149e9e364166c7987c3c47fe4d7fbeab4229f2a4a02820c31e9caaa1d566b8a3</citedby><cites>FETCH-LOGICAL-c314t-e149e9e364166c7987c3c47fe4d7fbeab4229f2a4a02820c31e9caaa1d566b8a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Han, Yun-Xiang</creatorcontrib><creatorcontrib>Zhang, Jian-Wei</creatorcontrib><creatorcontrib>Huang, Xiao-Qiong</creatorcontrib><title>Method for optimal conflict-free aircraft trajectory generation</title><title>Aircraft engineering</title><description>Purpose
A number of automated tools will be required for the purpose of enabling efficient services in air traffic control. The purpose of this paper is to devise an optimal flight trajectory search method that optimizes airspace system efficiency for 3D space in the presence of uncertainties.
Design/methodology/approach
This paper put forward an optimization model for generating applicable solutions of multi-aircraft conflict resolution problem, and the solution is based on the principle of optimality.
Findings
The conflict resolution problem between multiple aircraft can be described by spatial discretization, and the approach taken digitizes the 3D space into a grid of nodes.
Practical implications
The simulation examples are given to illustrate the validity of trajectory search model and stress on the impact of different system parameters.
Originality/value
Realistic constraints that are convenient to operate are incorporated in the system model, and the results show that it can provide reliable decision-making for conflict avoidance.</description><subject>Air rights</subject><subject>Air traffic control</subject><subject>Aircraft</subject><subject>Airspace</subject><subject>Altitude</subject><subject>Conflict resolution</subject><subject>Control algorithms</subject><subject>Decision making</subject><subject>Dynamic programming</subject><subject>Energy consumption</subject><subject>Graph coloring</subject><subject>Kinematics</subject><subject>Optimization</subject><subject>Search methods</subject><subject>Trajectory optimization</subject><subject>Variables</subject><issn>1748-8842</issn><issn>1758-4213</issn><issn>1748-8842</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNptkD1PwzAQhi0EEqXwA9giMRvOH7GdCVVV-ZCKWMpsOc4ZUqVxcdyh_55EZUFiuhve507vQ8gtg3vGwDwsVosNBU05MEOBgz4jM6ZLQyVn4nzapaHGSH5JroZhC8BUCWJGHt8wf8WmCDEVcZ_bnesKH_vQtT7TkBAL1yafXMhFTm6LPsd0LD6xx-RyG_trchFcN-DN75yTj6fVZvlC1-_Pr8vFmnrBZKbIZIUVCiWZUl5XRnvhpQ4oGx1qdLXkvArcSQfccBghrLxzjjWlUrVxYk7uTnf3KX4fcMh2Gw-pH19aXgqpOJNGjCl2SvkUhyFhsPs0VkpHy8BOnuzkyYK2kyc7eRoZODG4Gzt1zb_IH7XiBxn3aW4</recordid><startdate>20200122</startdate><enddate>20200122</enddate><creator>Han, Yun-Xiang</creator><creator>Zhang, Jian-Wei</creator><creator>Huang, Xiao-Qiong</creator><general>Emerald Publishing Limited</general><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7RQ</scope><scope>7TB</scope><scope>7WY</scope><scope>7XB</scope><scope>8AF</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>HCIFZ</scope><scope>K6~</scope><scope>KB.</scope><scope>L.-</scope><scope>L6V</scope><scope>L7M</scope><scope>M0F</scope><scope>M1Q</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PDBOC</scope><scope>PQBIZ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>20200122</creationdate><title>Method for optimal conflict-free aircraft trajectory generation</title><author>Han, Yun-Xiang ; Zhang, Jian-Wei ; Huang, Xiao-Qiong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c314t-e149e9e364166c7987c3c47fe4d7fbeab4229f2a4a02820c31e9caaa1d566b8a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Air rights</topic><topic>Air traffic control</topic><topic>Aircraft</topic><topic>Airspace</topic><topic>Altitude</topic><topic>Conflict resolution</topic><topic>Control algorithms</topic><topic>Decision making</topic><topic>Dynamic programming</topic><topic>Energy consumption</topic><topic>Graph coloring</topic><topic>Kinematics</topic><topic>Optimization</topic><topic>Search methods</topic><topic>Trajectory optimization</topic><topic>Variables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Han, Yun-Xiang</creatorcontrib><creatorcontrib>Zhang, Jian-Wei</creatorcontrib><creatorcontrib>Huang, Xiao-Qiong</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Career & Technical Education Database</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>STEM Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Aerospace Database</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Business Collection</collection><collection>https://resources.nclive.org/materials</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ABI/INFORM Trade & Industry</collection><collection>Military Database</collection><collection>ProQuest Science Journals</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Materials science collection</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>ProQuest Central Basic</collection><jtitle>Aircraft engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Han, Yun-Xiang</au><au>Zhang, Jian-Wei</au><au>Huang, Xiao-Qiong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Method for optimal conflict-free aircraft trajectory generation</atitle><jtitle>Aircraft engineering</jtitle><date>2020-01-22</date><risdate>2020</risdate><volume>92</volume><issue>2</issue><spage>156</spage><epage>162</epage><pages>156-162</pages><issn>1748-8842</issn><eissn>1758-4213</eissn><eissn>1748-8842</eissn><abstract>Purpose
A number of automated tools will be required for the purpose of enabling efficient services in air traffic control. The purpose of this paper is to devise an optimal flight trajectory search method that optimizes airspace system efficiency for 3D space in the presence of uncertainties.
Design/methodology/approach
This paper put forward an optimization model for generating applicable solutions of multi-aircraft conflict resolution problem, and the solution is based on the principle of optimality.
Findings
The conflict resolution problem between multiple aircraft can be described by spatial discretization, and the approach taken digitizes the 3D space into a grid of nodes.
Practical implications
The simulation examples are given to illustrate the validity of trajectory search model and stress on the impact of different system parameters.
Originality/value
Realistic constraints that are convenient to operate are incorporated in the system model, and the results show that it can provide reliable decision-making for conflict avoidance.</abstract><cop>Bradford</cop><pub>Emerald Publishing Limited</pub><doi>10.1108/AEAT-07-2018-0207</doi><tpages>7</tpages></addata></record> |
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language | eng |
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source | Emerald:Jisc Collections:Emerald Subject Collections HE and FE 2024-2026:Emerald Premier (reading list) |
subjects | Air rights Air traffic control Aircraft Airspace Altitude Conflict resolution Control algorithms Decision making Dynamic programming Energy consumption Graph coloring Kinematics Optimization Search methods Trajectory optimization Variables |
title | Method for optimal conflict-free aircraft trajectory generation |
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