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VOLTCom: A Novel Online Trajectory Compression Method Based on Vector Processing

delete2023-12-01
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PRE
AI
才智 (Zhi Cai)
Q
Qian Dong
石美惠 cover
石美惠 (Meihui Shi) *
苏醒 (Xing Su)
L
Limin Guo
Z
Zhiming Ding
DOI:10.1109/TITS.2023.3294941delete
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Abstract

Abstract

En 中文
With the widespread use of the Global Positioning System (GPS) in the fields such as traffic monitoring, sports navigation, and track recording, the trajectory data recording users' spatial and temporal information has grown dramatically. The huge volume of trajectory data causes high cost and poses a great challenge to data storage, network transmission, query and analysis. Therefore, the compression of trajectory data becomes a crucial issue. This paper proposes an online trajectory compression algorithm based on vector extraction (VOLTCom), which aims to achieve efficient data compression while retaining more effective information, and is mainly applied to trajectory recording and analysis in the traffic field. VOLTCom first generates vectors for trajectory data according to customized vector features, and then performs real-time vector extraction to achieve online trajectory compression. The vector extraction of the trajectory data ensures the stability of the compression time per unit and achieves efficient compression. Experiments on real datasets show that VOLTCom can retain the information of object velocity variation by vector density and outperforms traditional algorithms in terms of error, compression rate, and execution time. The algorithm is $O(1)$ in compression time complexity and has better compression performance.
Keywords:
Online trajectory compression
vector
synchronous Euclidean distance
trajectory compression ratio

Journal

IEEE Transactions on Intelligent Transportation Systems cover
IEEE Transactions on Intelligent Transportation Systems
IF:
8.4
Papers:
9.5K
Citations:
6.3W

Organization

B
Beijing University of Technology
Scholars:
2.8W
Papers: 2.1W
Citations: 2.7W