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Vessel Trajectory Online Multi-Dimensional Simplification Algorithm

Published online by Cambridge University Press:  22 August 2019

Yuan-qiang Zhang
(Navigation College, Dalian Maritime University, Dalian116026, China) (Faculty of Maritime and Transportation, Ningbo University, Ningbo315211, China)
Guo-you Shi*
(Navigation College, Dalian Maritime University, Dalian116026, China)
Song Li
(Faculty of Maritime and Transportation, Ningbo University, Ningbo315211, China)
Shu-kai Zhang
(Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China)


Facilitated by the establishment of terrestrial networks and satellite constellations of Automatic Identification System (AIS) receivers, large quantities of spatial and temporal information that trace ships' paths have been collected. The exponential increase in the amount of AIS data has caused expensive and time-consuming transmission, calculation and storage problems. Using appropriate trajectory simplification methods in a timely manner to compress redundant information while minimising the loss of importation information is important. To minimise the simplification error, this paper proposes an online multi-dimensional simplification algorithm for AIS trajectory streaming data. The simplification algorithm takes into account position, direction and speed preservation. Finally, a comparison experiment with other algorithms is made to examine the effectiveness of this algorithm. The results indicate that the proposed online multi-dimensional simplification algorithm can effectively preserve a ship's motion state, including its position, speed and course.

Research Article
Copyright © The Royal Institute of Navigation 2019

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