Traffic pattern detection using the Hough transformation for anomaly detection to improve maritime domain awareness

Techniques for extracting traffic patterns from ship position data to generate atlases of expected ocean travel are developed in this paper. An archive of historical data is used to develop a traffic density grid. The Hough transformation is used to extract linear patterns of elevated density from t...

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Bibliographic Details
Main Authors: McAbee, Ashley, Scrofani, James, Tummala, Murali, Garren, David, McEachen, John
Format: Conference Proceeding
Language:English
Subjects:
Automated Information System
Data mining
Hough Transformation
Marine vehicles
Maritime Domain Awareness
Meteorology
Oceans
Pattern Extraction
Road transportation
Traffic control
Online Access:Request full text
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Summary:Techniques for extracting traffic patterns from ship position data to generate atlases of expected ocean travel are developed in this paper. An archive of historical data is used to develop a traffic density grid. The Hough transformation is used to extract linear patterns of elevated density from the traffic density grid, which can be considered the "highways" of the oceans. These highways collectively create an atlas that is used to define geographical regions of expected ship locations. The atlas generation techniques are demonstrated using automated information system (AIS) ship position data to detect highways in both open-ocean and coastal areas. Additionally, the atlas generation techniques are used to explore variability in ship traffic as a result of extreme weather. The development of an automatic atlas generation technique that can be used to develop a definition of normal maritime behavior is a significant result of this research.