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Historical AIS Data-Driven Unsupervised Automatic Extraction of Directional Maritime Traffic Networks
استخراج خودکار بدون نظارت داده های AIS از شبکه های ترافیکی دریایی جهت دار-2020 Vessel experience route analysis can provide
empirical support for maritime traffic management. Recently,
the application of the Automatic Identification System (AIS)
provides multi-dimensional data about voyages and vessels.
However, traditional route extraction methods do not take into
account information such as the vessel traffic pattern and the
density distribution in the channel. The experience routes
obtained is not accurate enough. This paper proposes an
unsupervised method for extracting vessel experience routes
from historical AIS data. The method consists of three parts:
vessel traffic pattern extraction, channel boundary extraction,
channel triangle network construction and hottest route
extraction. The method comprehensively considers the spatiotemporal
information and density distribution of the vessel
trajectories, and constructs a directional maritime traffic
network which can effectively convert historical data into
information supporting decision-making. Keywords : AIS | Traffic Pattern | Triangular Network | Directional Maritime Traffic Network |
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