Abstract

One of the main missions of air traffic management is to guarantee en route safety. This safety is quantified through some minimum separation distance between pairs of flying aircraft. Current systems are human-based, i.e., have human air traffic controllers assuring minimum separation is maintained and in cases a loss of separation is predicted, they take actions to prevent the occurrence of such events. The constant and rapid increment of the air traffic demand is pushing current air traffic control systems to their limits. Development of automatic decision support systems, which can be used to automate, or support aircraft conflict detection and resolution, is considered a possible solution. However, the combinatorial nature of the problem poses several challenges for such a task. Metrics or various analytical procedures to produce information about the complexity of given scenarios can be used to guide the solution search process. In this paper, we present a complexity analysis based on the spatio-temporal interdependencies identified by the use of spatio-temporal regions constructed around the aircraft conflicts.

Highlights

  • Air traffic management’s (ATM) mission is to make air transportation possible

  • IDENTIFICATION OF AIRCRAFT RELEVANT TO A CONFLICT RESOLUTION USING SPATIO-TEMPORAL REGIONS We propose, a two-step procedure, similar to [18], to detect aircraft that are relevant to a conflict resolution procedure

  • DATA AND THE PARAMETERS USED We evaluate the method using traffic data from Eurocontrol’s Demand Data Repository II (DDR II)

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Summary

Introduction

Air traffic management’s (ATM) mission is to make air transportation possible. This is attained by the means of efficient, environmentally friendly, and socially valuable systems, which have safety as their principal goal [1], [2]. INDEX TERMS Aircraft conflict, complexity metrics, continuous space-time regions.

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