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Main Authors: Pelegrin, Mercedes, Cerulli, Martina
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2405.12836
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author Pelegrin, Mercedes
Cerulli, Martina
author_facet Pelegrin, Mercedes
Cerulli, Martina
contents Aircraft conflict resolution is one of the major tasks of computer-aided air traffic management and represents a challenging optimization problem. Many models and methods have been proposed to assist trajectory regulation to avoid conflicts. However, the question of testing the different mathematical optimization approaches against each other is still open. Standard benchmarks include unrealistic scenarios in which all the flights move toward a common point or completely random generated instances. There is a lack of a common set of test instances that allows comparison of the available methods under a variety of heterogeneous and representative scenarios. We present a flight deconfliction benchmark generator that allows the user to choose between (i) different predefined scenario inspired by existing benchmarks in the literature; (ii) pseudo-random traffic meeting certain congestion measurements; (iii) and randomly generated traffic. The proposed setting can account for different levels of difficulty in the deconfliction of the aircraft and allows to explore and compare the real limitations of optimization approaches for aircraft conflict resolution.
format Preprint
id arxiv_https___arxiv_org_abs_2405_12836
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Aircraft Conflict Resolution: A Benchmark Generator
Pelegrin, Mercedes
Cerulli, Martina
Optimization and Control
Aircraft conflict resolution is one of the major tasks of computer-aided air traffic management and represents a challenging optimization problem. Many models and methods have been proposed to assist trajectory regulation to avoid conflicts. However, the question of testing the different mathematical optimization approaches against each other is still open. Standard benchmarks include unrealistic scenarios in which all the flights move toward a common point or completely random generated instances. There is a lack of a common set of test instances that allows comparison of the available methods under a variety of heterogeneous and representative scenarios. We present a flight deconfliction benchmark generator that allows the user to choose between (i) different predefined scenario inspired by existing benchmarks in the literature; (ii) pseudo-random traffic meeting certain congestion measurements; (iii) and randomly generated traffic. The proposed setting can account for different levels of difficulty in the deconfliction of the aircraft and allows to explore and compare the real limitations of optimization approaches for aircraft conflict resolution.
title Aircraft Conflict Resolution: A Benchmark Generator
topic Optimization and Control
url https://arxiv.org/abs/2405.12836