An end-to-end framework for flight trajectory data analysis based on deep autoencoder network

Zhang, Weining; Hu, Minghua; Du, Jinghan

doi:10.1016/j.ast.2022.107726

Cited by 7 publications

(2 citation statements)

References 20 publications

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“…The operator is deterministic, but only allows to consider 2-dimensional paths with simple patterns. Lazzara et al (2022) and Zhang, Hu, and Du (2022) use autoencoders as a non-linear projection operator to extract information from high-dimensional timeseries in order to facilitate their analysis. Jarry, Couellan, and Delahaye (2019) go further into the complexity of the generation method by using Generative Adversarial Networks (GAN), which are capable of reconstructing an aircraft trajectory from a random vector of a smaller dimension.…”

Section: Literature Reviewmentioning

confidence: 99%

Deep Generative Modelling of Aircraft Trajectories in Terminal Maneuvering Areas

et al. 2022

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Section: Literature Reviewmentioning

confidence: 99%

Deep Generative Modelling of Aircraft Trajectories in Terminal Maneuvering Areas

et al. 2022

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“…With the advancement of computer technology in recent years, data mining and machine learning techniques have become increasingly popular. In order to analyze potential risks from a large quantity of historical trajectory data, Zhang et al [12] proposed an end-to-end framework based on the depth automatic encoder network that can effectively identify typical spatial anomalies in a timely manner. Olive and Basora [13] proposed a framework based on automatically encoded artificial neural networks for detecting and identifying anomalies.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Trajectory Negotiation and Verification Method Based on Spatiotemporal Pattern Mining

Liu,

Wang,

Zhong

et al. 2023

International Journal of Aerospace Engineering

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In trajectory-based operations, trajectory negotiation and verification are conducive to using airspace resources fairly, reducing flight delay, and ensuring flight safety. However, most of the current methods are based on route negotiation, making it difficult to accommodate airspace user-initiated trajectory requests and dynamic flight environments. Therefore, this paper develops a framework for trajectory negotiation and verification and describes the trajectory prediction, negotiation, and verification processes based on a four-dimensional trajectory. Secondly, users predict flight trajectories based on aircraft performance and flight plans and submit them as requested flight trajectories to the air traffic management (ATM) system for negotiation in the airspace. Then, a spatiotemporal weighted pattern mining algorithm is proposed, which accurately identifies flight combinations that violate the minimum flight separation constraint from four-dimensional flight trajectories proposed by users, as well as flight combinations with close flight intervals and long flight delays in the airspace. Finally, the experimental results demonstrate that the algorithm efficiently verifies the user-proposed flight trajectory and promptly identifies flight conflicts during the trajectory negotiation and verification processes. The algorithm then analyzes the flight trajectories of aircrafts by applying various constraints based on the specific traffic environment; the flight combinations which satisfy constraints can be identified. Then, based on the results identified by the algorithm, the air traffic management system can negotiate with users to adjust the flight trajectory, so as to reduce flight delay and ensure flight safety.

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Flight Trajectory Tracking Method Based on Prediction Calculation

Liu,

Qian,

Chen

et al. 2024

Lecture Notes in Electrical Engineering

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An end-to-end framework for flight trajectory data analysis based on deep autoencoder network

Cited by 7 publications

References 20 publications

Deep Generative Modelling of Aircraft Trajectories in Terminal Maneuvering Areas

Deep Generative Modelling of Aircraft Trajectories in Terminal Maneuvering Areas

An Efficient Trajectory Negotiation and Verification Method Based on Spatiotemporal Pattern Mining

Flight Trajectory Tracking Method Based on Prediction Calculation

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