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A Distributed Mining Method for Traffic Trajectory Patterns

A distributed and trajectory technology, applied in the field of big data, can solve problems such as performance bottlenecks, high computing resources, and inability to reflect changes in airspace operations in real time, and achieve fast response, efficient analysis and calculation, and improved data throughput.

Active Publication Date: 2021-07-30
CHECC DATA CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional track pattern recognition is mainly based on historical data analysis, which cannot reflect changes in airspace operations in real time. At the same time, there are performance bottlenecks. When facing massive track data, the required computing resources are high.

Method used

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  • A Distributed Mining Method for Traffic Trajectory Patterns
  • A Distributed Mining Method for Traffic Trajectory Patterns
  • A Distributed Mining Method for Traffic Trajectory Patterns

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Embodiment Construction

[0037] In order to understand the above-mentioned purpose, features and advantages of the present invention more clearly, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the case of no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0038] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described here. Therefore, the protection scope of the present invention is not limited by the specific details disclosed below. EXAMPLE LIMITATIONS.

[0039] The present invention designs a distributed mining method for traffic track patterns, improves the distance measurement method between tracks, uses streaming big data technology, optimizes the c...

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Abstract

The invention provides a distributed mining method for traffic track patterns, which receives real-time track data, performs data preprocessing and resampling on the track data in the geo-fence under investigation, and then conducts pattern analysis on all track data through cluster analysis. identify. The method of the invention can process track data within a certain geographical fence range, and carry out track reconstruction and pattern recognition on the real-time track data under the combination of part of historical data information. The algorithm has low complexity, strong real-time performance, and timely dynamic response to the results. When facing the challenge of streaming big data, it can efficiently analyze the trajectory pattern and provide strong support for air traffic controllers to grasp the flight operation status in real time and evaluate the flight operation efficiency.

Description

technical field [0001] The invention belongs to the field of big data technology, and in particular relates to a distributed mining method for traffic track patterns, specifically, a method for analyzing track patterns in real time by using distributed technology in a streaming big data scene. Background technique [0002] With the rapid growth of China's civil aviation transportation volume, airspace resources are becoming more and more tense, and the pressure on air traffic control is also increasing. At the same time, the continuous improvement of flight operation monitoring methods including ADS-B, secondary radar and other technologies has laid a foundation for pattern analysis based on massive track data. Analyzing and identifying different trajectory patterns from massive trajectory data can support air traffic control departments to regulate flights and evaluate flight operating efficiency, thereby improving the level of air traffic control automation and optimizing ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/2458G06F16/29G06F17/16G06K9/62
CPCG06F16/2471G06F16/2465G06F16/29G06F17/16G06F18/23
Inventor 佟路田旺曹先彬杜文博朱熙
Owner CHECC DATA CO LTD
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