Aircraft conflict resolution with trajectory recovery using mixed-integer programming

Bibliographic Details
Title: Aircraft conflict resolution with trajectory recovery using mixed-integer programming
Authors: Fernando Dias, David Rey
Contributors: Department of Mathematics and Systems Analysis, Operations Research and Systems Analysis, Université Côte d'Azur, Aalto-yliopisto, Aalto University
Source: Journal of Global Optimization. 90:1031-1067
Publication Status: Preprint
Publisher Information: Springer Science and Business Media LLC, 2024.
Publication Year: 2024
Subject Terms: trajectory recovery, 05 social sciences, 0211 other engineering and technologies, 02 engineering and technology, Conflict resolution, air traffic control, mixed integer programming, Trajectory recovery, Applications of mathematical programming, Air traffic control, Mixed integer programming, Optimization and Control (math.OC), 0502 economics and business, FOS: Mathematics, Mathematics - Combinatorics, conflict resolution, Combinatorics (math.CO), Mathematics - Optimization and Control
Description: To guarantee the safety of flight operations, decision-support systems for air traffic control must be able to improve the usage of airspace capacity and handle increasing demand. This study addresses the aircraft conflict avoidance and trajectory recovery problem. The problem of finding the least deviation conflict-free aircraft trajectories that guarantee the return to a target waypoint is highly complex due to the nature of the nonlinear trajectories that are sought. We present a two-stage iterative algorithm that first solves initial conflicts by manipulating their speed and heading control and then identifying each aircraft’s optimal time to recover its trajectory towards their nominal one. We extend existing mixed-integer programming formulations by modelling speed and heading control as continuous variables while recovery time is treated as a discrete variable. We develop a novel iterative approach which shows that the trajectory recovery costs can be anticipated by inducing avoidance trajectories with higher deviation, therefore obtaining earlier recovery time within a few iterations. Numerical results on benchmark conflict resolution problems show that this approach can solve instances with up to 30 aircraft within 10 min.
Document Type: Article
File Description: application/xml; application/pdf
Language: English
ISSN: 1573-2916
0925-5001
DOI: 10.1007/s10898-024-01393-1
DOI: 10.48550/arxiv.2203.11990
Access URL: http://arxiv.org/abs/2203.11990
https://aaltodoc.aalto.fi/handle/123456789/131908
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CC 0
Accession Number: edsair.doi.dedup.....7fe7b9ce735f94655f363b8daadb51a3
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  Data: Department of Mathematics and Systems Analysis<br />Operations Research and Systems Analysis<br />Université Côte d'Azur<br />Aalto-yliopisto<br />Aalto University
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  Data: <i>Journal of Global Optimization</i>. 90:1031-1067
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  Data: To guarantee the safety of flight operations, decision-support systems for air traffic control must be able to improve the usage of airspace capacity and handle increasing demand. This study addresses the aircraft conflict avoidance and trajectory recovery problem. The problem of finding the least deviation conflict-free aircraft trajectories that guarantee the return to a target waypoint is highly complex due to the nature of the nonlinear trajectories that are sought. We present a two-stage iterative algorithm that first solves initial conflicts by manipulating their speed and heading control and then identifying each aircraft’s optimal time to recover its trajectory towards their nominal one. We extend existing mixed-integer programming formulations by modelling speed and heading control as continuous variables while recovery time is treated as a discrete variable. We develop a novel iterative approach which shows that the trajectory recovery costs can be anticipated by inducing avoidance trajectories with higher deviation, therefore obtaining earlier recovery time within a few iterations. Numerical results on benchmark conflict resolution problems show that this approach can solve instances with up to 30 aircraft within 10 min.
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    Subjects:
      – SubjectFull: trajectory recovery
        Type: general
      – SubjectFull: 05 social sciences
        Type: general
      – SubjectFull: 0211 other engineering and technologies
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