Aircraft Conflict Resolution: A Benchmark Generator

Mercedes Pelegrín () and Martina Cerulli ()
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Mercedes Pelegrín: Laboratoire d’Informatique de l’X, École Polytechnique (LIX), 91128 Palaiseau, France
Martina Cerulli: Information Systems, Decision Sciences and Statistics Department, ESSEC Business School of Paris, 95000 Cergy-Pontoise, France

INFORMS Journal on Computing, 2023, vol. 35, issue 2, 274-285

Abstract: 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.

Keywords: air traffic management; conflict resolution; optimization; benchmarks (search for similar items in EconPapers)
Date: 2023
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