Open AccessA novel compression approach for truck GPS trajectory data
Author(s) -
Liu Sijing,
Chen Gang,
Wei Long,
Li Guoqi
Publication year - 2021
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/itr2.12005
Subject(s) - trajectory , global positioning system , computer science , data compression , compression (physics) , compression ratio , real time computing , data compression ratio , point (geometry) , algorithm , computer vision , engineering , image compression , mathematics , image (mathematics) , telecommunications , physics , materials science , geometry , astronomy , image processing , automotive engineering , composite material , internal combustion engine
Nowadays, the application of location‐aware devices, such as global positioning system (GPS)‐enabled mobile phones and personal digital assistants (PDAs) is increasing. Based on this, a new demand for efficiently storing trajectory data has arisen. Trajectory compression reduces the storage space and cost, the cost and time of data transmission by retaining critical trajectory points and effectively eliminating redundant data. Herein, a novel trajectory compression method based on stay points (TCSP) is proposed. By using the road network data and the stay points of GPS trajectory data to compress the GPS trajectory data, this method can greatly improve the ratio and accuracy of compression. Experimental results based on real data sets show that the compression rate of this method can stably reach 8.61%, and the compression effect can be restored to the original trajectory route. Compared with the critical point algorithm and the Douglas–Peucker (DP) algorithm, the TCSP method can reach a better compression effect and compression ratio.