The extraction of passenger ship routes plays a crucial role in managing and regulating passenger ship traffic and ensuring safe navigation. This paper proposes a novel method for extracting passenger ship routes based on the Gaussian process regression (GPR) model. The method utilizes the Automatic Identification System (AIS) data to obtain the berthing trajectory segments based on the behavioral characteristics of ships. Next, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is used to identify the berthing areas. The passenger ship trajectories are divided based on the identified berthing areas and are classified into different trajectory clusters based on their departure and arrival zones. The trajectory length and geographic coordinates (longitude and latitude) are modeled separately, and the GPR is employed to extract the trajectory centerline by aggregating the posterior distribution of the functions. The proposed method is evaluated by experimentation, which demonstrates its effectiveness in estimating the trajectory centerline more accurately. The research findings provide valuable support for designing and optimizing passenger ship routes and enhancing safety management.
Extraction of Ship Route Using Gaussian Process Regression for Passenger Ships
2023-08-04
2190858 byte
Conference paper
Electronic Resource
English
Ship maintenance and associated design problems -- Passenger ships
Engineering Index Backfile | 1965
|Feature 2 - Lifesaving & ship safety - FIREPROOFING passenger ships
Online Contents | 2012
Passenger ship for Channel Islands route
Engineering Index Backfile | 1960
Passenger ship technology : the international journal for cruise ships and ferries
TIBKAT | 1.2008,1(Aug./Sept.) -
British Library Conference Proceedings | 2009
|