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Trajectory Data Preprocessing: Methods and Models
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DOI：10.3390/electronics14234694.png)
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Abstract
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Trajectory data from GPS and sensors are increasingly available, necessitating effective preprocessing techniques for data mining. To systematically review the methods and models for trajectory data preprocessing, we conducted a systematic literature search in IEEE Xplore, Association for Computing Machinery Digital Library (ACM DL), Scopus, Web of Science, and Transport Research International Documentation published over the past several decades, using keywords related to trajectory data preprocessing. The studies were screened and selected based on predefined inclusion and exclusion criteria. We included 138 studies, summarizing techniques in data cleaning, compression, segmentation, and map matching. Key algorithms and their performance are compared. This review synthesizes current preprocessing methods and identifies future research directions, including real-time processing, semantic labeling, and privacy protection.
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