Content area
This study addresses the challenges of maritime traffic management in the western waters of Taiwan, a region characterized by substantial commercial shipping activity and ongoing environmental development. Using 2023 Automatic Identification System (AIS) data, this study develops a robust feature extraction framework involving data cleaning, anomaly trajectory point detection, trajectory compression, and advanced processing techniques. Dynamic Time Warping (DTW) and the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithms are applied to cluster the trajectory data, revealing 16 distinct maritime traffic patterns, key navigation routes, and intersections. The findings provide fresh perspectives on analyzing maritime traffic, identifying high-risk areas, and informing safety and spatial planning. In practical applications, the results help navigators optimize route planning, improve resource allocation for maritime authorities, and inform the development of infrastructure and navigational aids. Furthermore, these outcomes are essential for detecting abnormal ship behavior, and they highlight the potential of route extraction in maritime surveillance.
Details
Radio communications;
Spatial planning;
Accuracy;
Shipping;
Wind farms;
Navigation;
International trade;
Data processing;
Data science;
Operations management;
Research & development--R&D;
Energy consumption;
Ship accidents & safety;
Data compression;
Efficiency;
Statistical analysis;
Environmental management;
Big Data;
Spatial data;
Emergency preparedness;
Traffic management;
Navigation behavior;
Clustering;
Route planning;
Navigational aids;
Algorithms;
Compression;
Methods;
Traffic analysis;
Fisheries management
; Man-Chun, Lee 2 ; Chang, Li 2 ; Juan-Chen, Huang 3
1 Maritime Development and Training Center, National Taiwan Ocean University, Keelung 202301, Taiwan;
2 Department of Merchant Marine, National Taiwan Ocean University, Keelung 202301, Taiwan;
3 Maritime Development and Training Center, National Taiwan Ocean University, Keelung 202301, Taiwan;