An Artificial Intelligence Algorithm to Automate Situation Management for Operators of Unmanned Aerial Vehicles

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Unmanned Aerial Vehicle (UAV) operators must maintain high levels of situation awareness on their area of operation. To achieve this, they use the a Command and Control (C2) map, which is shared among forces, and regularly overloaded with data that is irrelevant to their operational mission. Operators require distilled information at the right timing. Yet, the existing filtering mechanisms for C2 maps are layer-based and insufficient. We propose a new approach to automatically and dynamically filter information items on the map based on environmental and mission context. To achieve this, we introduce a three-tiers artificial intelligence (AI) based algorithm (GiCo-MAF), where we delineate the use of machine learning (ML) models to support UAV missions. For the GiCoMAF development, tagged data was collected in simulated experimental runs with professional UAS operators. Different types of ML models were evaluated and fitted into the algorithm. The models achieved a relatively high accuracy at modeling human preference and area of interest. The approach presented in this study can be further implemented to support time-critical spatial-temporal operational problems.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE International Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2020
EditorsGalina Rogova, Nicolette McGeorge, Alicia Ruvinsky, Scott Fouse, Mary Freiman
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages67-75
Number of pages9
ISBN (Electronic)9781728160016
DOIs
StatePublished - 1 Aug 2020
Event2020 IEEE International Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2020 - Virtual, Victoria, Canada
Duration: 24 Aug 202028 Aug 2020

Conference

Conference2020 IEEE International Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2020
Country/TerritoryCanada
CityVirtual, Victoria
Period24/08/2028/08/20

Keywords

  • artificial intelligence
  • decision making
  • human systems integration
  • human-automation interaction
  • information processing
  • intelligent systems
  • mental workload
  • situation awareness
  • uninhabited aerial vehicles

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Management Science and Operations Research
  • Control and Optimization
  • Cognitive Neuroscience

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