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A Novel Vector Processing-Based Online Trajectory Data Indexing Approach
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AI
DOI：10.1109/TITS.2025.3646702.png)
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Abstract
En 中文
With the rapid development of geolocation technology, the volume of spatio-temporal trajectory data has surged. This data is widely used in fields such as geographic information systems and mobile computing, but its storage and query processing present significant challenges. Current methods of offline indexing are inefficient and cannot be updated in real-time. To address this issue, this paper proposes a concept of the online index that supports real-time storage and indexing of trajectory data and significantly reduces indexing time and storage space requirements. Based on this concept, two vector-based online trajectory indexing methods are proposed in this paper. The first is an online trajectory indexing method based on vector extraction (VBIndex), which offers the advantages of high efficiency and less storage space. The second is an online trajectory indexing method based on road-network matching (RAIndex), which further improves the vector-based indexing efficiency when road network involved. Through experiments with real datasets, the proposed algorithms were evaluated, confirming their superiority in terms of indexing construction time and storage space. Furthermore, we have theoretically proven that queries based on this index are accurate, and statistical analysis is feasible. Both algorithms have a time complexity of $O(N)$ in indexing construction, demonstrating good performance.
Keywords:
Online index
vector
trajectory data
indexing time
storage space
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