Terminal area prevailing traffic flow recognizing method based on track spectral clusters

Abstract

The invention relates to a terminal area prevailing traffic flow recognizing method based on track spectral clusters. The method includes the steps of firstly, analyzing a given airport pavement to obtain flight path data, and conducting dividing to obtain feature track points and normal track points; secondly, setting up a space rectangular coordinate system; thirdly, putting forward an occupation degree concept according to the distance between a track and the center of a space grid, and enabling the occupation degree concept to be used for representing the occupation degree of the track in the space grid; fourthly, setting up an inter-track overall similarity model on the basis of a track partial similarity model; fifthly, constructing an Laplacian similarity matrix, and then analyzing the clusters through the spectral cluster algorithm; sixthly, conducting prevailing traffic flow recognition on the clusters obtained in the fifth step through the nuclear density estimation method; seventhly, displaying the recognition result in a displaying and interaction module. The terminal area prevailing traffic flow recognizing method has the advantages that a prevailing traffic flow track and an abnormal track can be simultaneously obtained through the spectral cluster algorithm, therefore, related personnel are assisted in scientifically and reasonably planning a terminal area and improving airport entering and leaving air lines, and the capacity of the terminal area is improved.

Description

technical field [0001] The invention relates to the field of airspace planning, in particular to a method for identifying prevailing traffic flow in a terminal area based on trajectory spectrum clustering. The application of the method can provide a technical basis for the redesign of the airspace in the terminal area and the design of incoming and outgoing routes. Background technique [0002] The airspace of the terminal area is the most dense and complex airspace with air traffic, and it is the bottleneck of increasing the capacity of the entire airspace. How to rationally and efficiently utilize limited terminal airspace resources has become an urgent problem that airspace management departments need to solve, and it is also a hot issue for scholars in the field of airspace planning. At present, the airspace design and the design of the arrival and departure routes of most countries are carried out in accordance with the relevant documents of the International Civil Avia...

AI Technical Summary

Problems solved by technology

[0003] Although there are currently some trajectory clustering methods for traffic flow in terminal areas, they are mainly developed around the horizontal profile without considering the spatial characteristics of aircraft trajectories, and the historical radar trajectories usually contain some abnormal trajectories, because abnormal trajectories are very important for generating The representative track has a great influence, and the constructed central track is completed on the basis of manually eliminating abnormal tracks. Not only is the degree of automation not high, but the identification of abnormal tracks has a great influence on the results.

In addition, most of the existing studies focus on track points or segmented trajectories, which cannot reflect the characteristics of complete trajectories.

Therefore, it cannot fully meet the needs of representative traffic flow identification in the planning and design of the terminal area

[0004] Considering the status quo of traffic flow trajectory clustering in the existing terminal area, there is still a lack of a fast, effective and practical method for identifying prevailing traffic flow

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