Density-weighted ant colony algorithm for ship trajectory reconstruction. (10th March 2020)

• Record Type: Journal Article
• Authors: Zhang, Xianzhe; Wang, Jiechen; Chen, Yanming; Li, Manchun; Cheng, Liang
• Is Part Of: International journal of shipping and transport logistics. Volume 12:Number 1/2(2020)
• Page Start: 19
• Page End: 38
• Publication Date: 2020-03-10
• Subjects: AIS -- ship trajectory reconstruction -- ant colony algorithm -- ship trajectory density centreline -- rubber sheet method; Shipping -- Periodicals; Shipping -- Statistics; Logistics -- Periodicals; 387.5
• Languages: English
• ISSNs: 1756-6517

Abstract

With the development of the international ocean shipping and the increase in the automatic identification system-receiving equipment, the availability of ship trajectory data has shown explosive growth. To reduce the uncertainty in the application of sparse ship trajectory data in the open sea, this paper proposes the use of an ant colony algorithm based on node weights and edge weights for ship trajectory reconstruction. Ship trajectory is reconstructed from independent trajectory points through prior knowledge base construction, solving candidate path sets and optimal path generation. In addition, in order to further experiment the proposed method for the reconstruction of trajectory in the large-scale, this paper also uses the reconstructed trajectory to extract the distribution of ship traffic flow in the study area. The experimental results show that, the proposed trajectory reconstruction method can reconstruct ship trajectories in open seas more accurately.