IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v9y2024i12p140-d1533382.html
   My bibliography  Save this article

Algorithm for Trajectory Simplification Based on Multi-Point Construction in Preselected Area and Noise Smoothing Processing

Author

Listed:
  • Simin Huang

    (College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China)

  • Zhiying Yang

    (College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China)

Abstract

Simplifying trajectory data can improve the efficiency of trajectory data analysis and query and reduce the communication cost and computational overhead of trajectory data. In this paper, a real-time trajectory simplification algorithm (SSFI) based on the spatio-temporal feature information of implicit trajectory points is proposed. The algorithm constructs the preselected area through the error measurement method based on the feature information of implicit trajectory points (IEDs) proposed in this paper, predicts the falling point of trajectory points, and realizes the one-way error-bounded simplified trajectory algorithm. Experiments show that the simplified algorithm has obvious progress in three aspects: running speed, compression accuracy, and simplification rate. When the trajectory data scale is large, the performance of the algorithm is much better than that of other line segment simplification algorithms. The GPS error cannot be avoided. The Kalman filter smoothing trajectory can effectively eliminate the influence of noise and significantly improve the performance of the simplified algorithm. According to the characteristics of the trajectory data, this paper accurately constructs a mathematical model to describe the motion state of objects, so that the performance of the Kalman filter is better than other filters when smoothing trajectory data. In this paper, the trajectory data smoothing experiment is carried out by adding random Gaussian noise to the trajectory data. The experiment shows that the Kalman filter’s performance under the mathematical model is better than other filters.

Suggested Citation

  • Simin Huang & Zhiying Yang, 2024. "Algorithm for Trajectory Simplification Based on Multi-Point Construction in Preselected Area and Noise Smoothing Processing," Data, MDPI, vol. 9(12), pages 1-21, November.
  • Handle: RePEc:gam:jdataj:v:9:y:2024:i:12:p:140-:d:1533382
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/9/12/140/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2306-5729/9/12/140/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jdataj:v:9:y:2024:i:12:p:140-:d:1533382. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.