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 language | American English |
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Title of host publication | Proceedings - 2020 IEEE International Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2020 |
Editors | Galina Rogova, Nicolette McGeorge, Alicia Ruvinsky, Scott Fouse, Mary Freiman |
Pages | 67-75 |
Number of pages | 9 |
ISBN (Electronic) | 9781728160016 |
DOIs | |
State | Published - 1 Aug 2020 |
Event | 2020 IEEE International Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2020 - Virtual, Victoria, Canada Duration: 24 Aug 2020 → 28 Aug 2020 |
Conference
Conference | 2020 IEEE International Conference on Cognitive and Computational Aspects of Situation Management, CogSIMA 2020 |
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Country/Territory | Canada |
City | Virtual, Victoria |
Period | 24/08/20 → 28/08/20 |
Keywords
- artificial intelligence
- decision making
- human systems integration
- human-automation interaction
- information processing
- intelligent systems
- mental workload
- situation awareness
- uninhabited aerial vehicles
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Human-Computer Interaction
- Management Science and Operations Research
- Control and Optimization
- Cognitive Neuroscience