Traffic route analysis and prediction are both crucial to maritime security. The ability to predict a vessel position in the future is essential to provide information on upcoming events. However, accurate prediction along a route is a challenging task in the maritime domain, due to the complex nature and variability of traffic patterns.Based on the popular Ornstein-Uhlenbeck stochastic mean-reverting processes, a novel method has been recently presented that enables the accurate prediction of future positions of a vessel under the hypothesis that it is following an established traffic pattern in the area.We present a large-scale extensive validation of the Ornstein-Uhlenbeck methodology applied to target predictions along routes in the maritime domain for several classes of vessel. This validation was done using a real-world dataset recorded in the Mediterranean Sea by a network of Automatic Identification System (AIS) receivers.

Validation of the Ornstein-Uhlenbeck Route Propagation Model in the Mediterranean Sea

Millefiori, LM;Braca, P;
2015-01-01

Abstract

Traffic route analysis and prediction are both crucial to maritime security. The ability to predict a vessel position in the future is essential to provide information on upcoming events. However, accurate prediction along a route is a challenging task in the maritime domain, due to the complex nature and variability of traffic patterns.Based on the popular Ornstein-Uhlenbeck stochastic mean-reverting processes, a novel method has been recently presented that enables the accurate prediction of future positions of a vessel under the hypothesis that it is following an established traffic pattern in the area.We present a large-scale extensive validation of the Ornstein-Uhlenbeck methodology applied to target predictions along routes in the maritime domain for several classes of vessel. This validation was done using a real-world dataset recorded in the Mediterranean Sea by a network of Automatic Identification System (AIS) receivers.
2015
978-1-4799-8736-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1164852
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