Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering
Joint Authors
Yang, Yang
Zhang, Jun
Cai, Kai-quan
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-06-10
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Yang, Yang& Zhang, Jun& Cai, Kai-quan. 2015. Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering. The Scientific World Journal،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1078969
Modern Language Association (MLA)
Yang, Yang…[et al.]. Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering. The Scientific World Journal No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1078969
American Medical Association (AMA)
Yang, Yang& Zhang, Jun& Cai, Kai-quan. Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering. The Scientific World Journal. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1078969
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1078969