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Validation of the Ornstein-Uhlenbeck route propagation model in the Mediterranean Sea
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.
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An unsupervised graph-based methodology has been developed to identify the spatiotemporal dynamics of ship routes and efficiently extract a compact representation of global maritime patterns from large volumes of historical AIS data in the form of a maritime traffic graph.
“Successful advancements on vector-based knowledge discovery [21], [22] have recently led to the development of an unsupervised graph-based methodology to identify the spatiotemporal dynamics of ship routes, and efficiently extract a compact representation of global maritime patterns from large volumes of historical AIS data, in the form of a maritime traffic graph (MTG).”
From Space-Based Global Maritime Surveillance. Part II: Artificial Intelligence and Data Fusion Techniques (2021) · cites this paper as [21]
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Soldi, G., Gaglione, D., Forti, N., Millefiori, L. M., Braca, P., Carniel, S., Simone, A. D., Iodice, A., Riccio, D., Daffina, F. C., et al. (2021) · IEEE Aerospace and Electronic Systems Magazine · doi:10.1109/maes.2021.3070884 · Cited by 44
“This approach, extensively validated against real-world datasets [17], [26], relies on model parameters that change only at waypoints (places where ships regularly stop or change their velocity).”
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Metadata
- Authors
- Millefiori, L. M., Pallotta, G., Braca, P., Horn, S., & Bryan, K.
- Affiliations
- NATO Centre for Maritime Research and Experimentation (IT)
- Venue
- OCEANS 2015 - Genova
- Publisher
- IEEE
- Published
- 2015-05
- Pages
- 1-6
- OpenAlex
- W1589221530
- Cited by
- 13
- References
- 0
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 1 · 2021: 3 · 2020: 1 · 2017: 1 · 2016: 3
- FWCI
- 2.36
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- MTS/IEEE OCEANS Conference (OCEANS) (publishedVersion)
- CINECA IRIS Institutial research information system (University of Pisa) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Ocean Engineering › Maritime Navigation and Safety
- Physical Sciences › Computer Science › Artificial Intelligence › Target Tracking and Data Fusion in Sensor Networks
- Social Sciences › Political Science and International Relations › Maritime Security and History
- Keywords
- Ornstein-Uhlenbeck process, shipping activity, maritime security, Automatic Identification System, Mediterranean Sea, traffic pattern analysis
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