Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering
Terminal-area aircraft intent inference (T-AII) is a prerequisite to detect and avoid potential aircraft conflict in the terminal airspace. T-AII challenges the state-of-the-art AII approaches due to the uncertainties of air traffic situation, in particular due to the undefined flight routes and fre...
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| Format: | Online |
| Language: | English |
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Hindawi Publishing Corporation
2015
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4479131/ |
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pubmed-4479131 |
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oai_dc |
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pubmed-44791312015-07-13 Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering Yang, Yang Zhang, Jun Cai, Kai-quan Research Article Terminal-area aircraft intent inference (T-AII) is a prerequisite to detect and avoid potential aircraft conflict in the terminal airspace. T-AII challenges the state-of-the-art AII approaches due to the uncertainties of air traffic situation, in particular due to the undefined flight routes and frequent maneuvers. In this paper, a novel T-AII approach is introduced to address the limitations by solving the problem with two steps that are intent modeling and intent inference. In the modeling step, an online trajectory clustering procedure is designed for recognizing the real-time available routes in replacing of the missed plan routes. In the inference step, we then present a probabilistic T-AII approach based on the multiple flight attributes to improve the inference performance in maneuvering scenarios. The proposed approach is validated with real radar trajectory and flight attributes data of 34 days collected from Chengdu terminal area in China. Preliminary results show the efficacy of the presented approach. Hindawi Publishing Corporation 2015 2015-06-10 /pmc/articles/PMC4479131/ /pubmed/26171417 http://dx.doi.org/10.1155/2015/671360 Text en Copyright © 2015 Yang Yang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Yang, Yang Zhang, Jun Cai, Kai-quan |
| spellingShingle |
Yang, Yang Zhang, Jun Cai, Kai-quan Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering |
| author_facet |
Yang, Yang Zhang, Jun Cai, Kai-quan |
| author_sort |
Yang, Yang |
| title |
Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering |
| title_short |
Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering |
| title_full |
Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering |
| title_fullStr |
Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering |
| title_full_unstemmed |
Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering |
| title_sort |
terminal-area aircraft intent inference approach based on online trajectory clustering |
| description |
Terminal-area aircraft intent inference (T-AII) is a prerequisite to detect and avoid potential aircraft conflict in the terminal airspace. T-AII challenges the state-of-the-art AII approaches due to the uncertainties of air traffic situation, in particular due to the undefined flight routes and frequent maneuvers. In this paper, a novel T-AII approach is introduced to address the limitations by solving the problem with two steps that are intent modeling and intent inference. In the modeling step, an online trajectory clustering procedure is designed for recognizing the real-time available routes in replacing of the missed plan routes. In the inference step, we then present a probabilistic T-AII approach based on the multiple flight attributes to improve the inference performance in maneuvering scenarios. The proposed approach is validated with real radar trajectory and flight attributes data of 34 days collected from Chengdu terminal area in China. Preliminary results show the efficacy of the presented approach. |
| publisher |
Hindawi Publishing Corporation |
| publishDate |
2015 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4479131/ |
| _version_ |
1613239650402435072 |