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Towards a Heuristic Optimizer for a Target Time Management System in Air Traffic Flow Management

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

Abstract. In Air Traffic Flow Management (ATFM), flights are issued arrival times during unexpected events, such as adverse weather conditions, in order to ensure smooth and safe airport operations. These target times are traditionally allocated on a first-planned, first-served basis, which often leads to inefficiencies due to the different delay costs of individual flights. The HARMONIsed network through smart technology and Collaboration (HARMONIC) project, funded by the Single European Sky ATM Research (SESAR) Joint Undertaking within the EU Horizon Europe program, therefore, explores a collaborative optimization platform to enable flight prioritization across airspace users. In this paper, we describe initial results of the development and validation of a Target-Time Management System (TTMS) in the HARMONIC project. In particular, we present different architecture options, one assuming a trusted platform provider, another option for the assumption of an honest-but-curious platform provider, using secure multi-party computation to protect the private inputs. We also present experimental results for a genetic algorithm for the optimization of assignment of target times to flights. Keywords: flight prioritization, multi-party computation, evolutionary algorithm, heuristic optimization
Original languageEnglish
Title of host publicationProceedings of the 43rd AIAA DATC/IEEE Digital Avionics Systems Conference (DASC 2024), San Diego, CA, USA, September 29 - October 3, 2024
Number of pages10
ISBN (Electronic)9798350349610
DOIs
Publication statusPublished - Sept 2024

Publication series

NameAIAA/IEEE Digital Avionics Systems Conference - Proceedings
ISSN (Print)2155-7195
ISSN (Electronic)2155-7209

Fields of science

  • 102 Computer Sciences
  • 102010 Database systems
  • 102015 Information systems
  • 102016 IT security
  • 102025 Distributed systems
  • 102027 Web engineering
  • 102028 Knowledge engineering
  • 102030 Semantic technologies
  • 102033 Data mining
  • 102035 Data science
  • 509026 Digitalisation research
  • 502050 Business informatics
  • 502058 Digital transformation
  • 503008 E-learning

JKU Focus areas

  • Digital Transformation

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