Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations
This study targets the scenario where centralized tracking systems provide tactical conflict detection for urban air mobility (UAM) flights. In this scenario, the interaction between airspace design and tracking system performances, and its impact on the effectiveness of conflict detection have not...
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sg-ntu-dr.10356-1729162024-01-09T15:31:11Z Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations Dai, Wei Quek, Zhi Hao Low, Kin Huat School of Mechanical and Aerospace Engineering Air Traffic Management Research Institute Engineering::Aeronautical engineering Urban Air Mobility Conflict Detection This study targets the scenario where centralized tracking systems provide tactical conflict detection for urban air mobility (UAM) flights. In this scenario, the interaction between airspace design and tracking system performances, and its impact on the effectiveness of conflict detection have not been addressed in the literature. To overcome this gap, this study aims at achieving probabilistic modeling and reasoning analysis, to provide references for stakeholders in the design of urban airspace and the deployment of flight tracking systems. A framework integrating multiple probabilistic methods is established. We formulate the event tree of pair-wise aircraft encounters with conflict detection provided by the tracking system. Then Monte Carlo simulation is performed by using an agent-based tool that we develop, to quantify the probability of event occurrences. Finally, Bayesian Networks models are built to infer the dependencies of conflict detection effectiveness on the airspace design and tracking system performances. The outcomes of this study demonstrate improvement in conflict detection that better tracking system performances can provide, and the impact of airspace design under different tracking configurations. The results can be used in the UAM traffic network planning, and systems standardization for UAM flight tracking, towards safe urban air traffic. Civil Aviation Authority of Singapore (CAAS) National Research Foundation (NRF) Submitted/Accepted version This research is supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme. 2024-01-03T05:52:19Z 2024-01-03T05:52:19Z 2023 Journal Article Dai, W., Quek, Z. H. & Low, K. H. (2023). Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations. Reliability Engineering & System Safety. https://dx.doi.org/10.1016/j.ress.2023.109908 0951-8320 https://hdl.handle.net/10356/172916 10.1016/j.ress.2023.109908 en Reliability Engineering & System Safety © 2023 Elsevier Ltd. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the copyright holder. The Version of Record is available online at http://doi.org/10.1016/j.ress.2023.109908. application/pdf |
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Engineering::Aeronautical engineering Urban Air Mobility Conflict Detection Dai, Wei Quek, Zhi Hao Low, Kin Huat Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations |
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This study targets the scenario where centralized tracking systems provide tactical conflict detection for urban air mobility (UAM) flights. In this scenario, the interaction between airspace design and tracking system performances, and its impact on the effectiveness of conflict detection have not been addressed in the literature. To overcome this gap, this study aims at achieving probabilistic modeling and reasoning analysis, to provide references for stakeholders in the design of urban airspace and the deployment of flight tracking systems. A framework integrating multiple probabilistic methods is established. We formulate the event tree of pair-wise aircraft encounters with conflict detection provided by the tracking system. Then Monte Carlo simulation is performed by using an agent-based tool that we develop, to quantify the probability of event occurrences. Finally, Bayesian Networks models are built to infer the dependencies of conflict detection effectiveness on the airspace design and tracking system performances. The outcomes of this study demonstrate improvement in conflict detection that better tracking system performances can provide, and the impact of airspace design under different tracking configurations. The results can be used in the UAM traffic network planning, and systems standardization for UAM flight tracking, towards safe urban air traffic. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Dai, Wei Quek, Zhi Hao Low, Kin Huat |
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Article |
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Dai, Wei Quek, Zhi Hao Low, Kin Huat |
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Dai, Wei |
title |
Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations |
title_short |
Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations |
title_full |
Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations |
title_fullStr |
Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations |
title_full_unstemmed |
Probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations |
title_sort |
probabilistic modeling and reasoning of conflict detection effectiveness by tracking systems towards safe urban air mobility operations |
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2024 |
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https://hdl.handle.net/10356/172916 |
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