Research on ship trajectory compression based on a Dynamic Programming algorithm

The Automatic Identification System (AIS) is extensively used in monitoring vessel traffic, and ship navigation related information can be obtained from the AIS data. However, AIS data contain extensive redundant information, which leads to the general need to compress the data when applying it in practice or conducting research. In this paper, a three-dimensional compression of ship trajectories using the Dynamic Programming algorithm has been proposed. The AIS data near the ports of Long Beach and San Francisco in the United States were used to test and compare the Dynamic Programming algorithm with the Top-down Time-ratio algorithms. The experimental results show that the proposed algorithm can better retain the position and time information at low compression ratio such as 1%, 20% and 40%. Moreover, the algorithm is applicable to ship trajectories with different motion modes such as steering, mooring and straight ahead. The results show that the proposed algorithm can reasonably solve the problem of AIS data redundancy and ensure the quality of data, which is of practical significance for water transport, transport planning and other related research.