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2023 Journal Impact Factor - 0.7
2023 CiteScore - 1.4
ISSN 2083-6473
ISSN 2083-6481 (electronic version)
Editor-in-Chief
Associate Editor
Prof. Tomasz Neumann
Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
e-mail transnav@umg.edu.pl
Preliminary Inter-comparison of AIS Data and Optimal Ship Tracks
1 Euro-Mediterranean Center for Climate Change, Lecce, Italy
2 Marine Traffic, London, United Kingdom
2 Marine Traffic, London, United Kingdom
Times cited (SCOPUS): 4
ABSTRACT: Optimal ship tracks computed via the VISIR model are compared to tracks recorded by the Automatic Identification System (AIS). The evaluation regards 43 tracks in the Southern Atlantic Ocean, sailed during 2016-2017 by different bulk carriers. In this exercise, VISIR is fed by wave analysis fields from the Copernicus Marine Environment Monitoring Service (CMEMS). In order to reproduce vessel speed loss in waves, a new methodology is developed, where kinematic information from AIS is fusioned with wave information from CMEMS. Resulting VISIR tracks are analyzed along with AIS tracks in terms of their topological features and duration. The tracks exhibit quite diverse topological shapes, including orthodromic, loxodromic, and other paths with complex and dynamic diversions. The distribution of AIS to VISIR track durations is analyzed in terms of several parameters, such as the AIS to VISIR track length and their Fréchet distance. Model features of VISIR affecting the results are discussed and future developments suggested by the results are outlined.
KEYWORDS: Automatic Identification System (AIS), Ship Track, AIS Data, Copernicus Marine Environment Monitoring Service (CMEMS), VISIR (discoVerIng Safe and effIcient Routes), VISIR Track, VISIR Model, Optimal Ship Track
REFERENCES
Alexandersson, M. A study of methods to predict added resistance in waves. Master’s thesis, KTH Centre for Naval Architecture, 2009.
Arguedas et al. 2018. Maritime Traffic Networks: From historical positioning data to unsupervised maritime traffic monitoring. IEEE-ITS, 19(3): pp.722732. - doi:10.1109/TITS.2017.2699635
Bertram V. and Couser. P. 2017. Computational methods for seakeeping and added resistance in waves. In B. Volker (ed.), 13th International Conference on Computer and IT Applications in the Maritime Industries, Redworth, 12-14 May 2014, pages 8–16. Harburg: Technische Universität Hamburg.
IMO. MSC.1/Circ.1228 Revised guidance to the Master for avoiding dangerous situations in adverse weather and sea conditions. Technical report, International Maritime Organization, London, UK, 2007.
M.1371: Technical characteristics for an automatic identification system using time-division multiple access in the VHF maritime mobile band.” [Online]. Available: https://www.itu.int/rec/R-REC- M.1371/en
Mannarini G., Pinardi N., Coppini G., Oddo P. and Iafrati A. 2016. VISIR-I: small vessels – least-time nautical routes using wave forecasts. Geoscientific Model Development, 9(4): 1597–1625. https://www.geosci-model dev.net/9/1597/2016/gmd-9-1597-2016.pdf - doi:10.5194/gmd-9-1597-2016
Mannarini G. & Carelli L. 2019. VISIR-I.b: waves and ocean currents for energy efficient navigation. Geoscientific Model Development Discussions, (under review) - doi:10.5194/gmd-2018-292
Spiliopoulos, G., Chatzikokolakis, K., Zissis, D., Biliri, E., Papaspyros, D., Tsapelas, G. and Mouzakitis, S. 2017. Knowledge extraction from maritime spatiotemporal data: An evaluation of clustering algorithms on Big Data. In Big Data (Big Data), 2017 IEEE International Conference on (pp. 1682-1687). IEEE. - doi:10.1109/BigData.2017.8258106
Tu E., Zhang G., Rachmawati L., Rajabally E., and Huang G. B. 2018, Exploiting AIS Data for Intelligent Maritime Navigation: A Comprehensive Survey From Data to Methodology. IEEE Trans. Intell. Transp. Syst., vol. 19, no. 5, pp. 1559–1582. - doi:10.1109/TITS.2017.2724551
Tsujimoto, M., Kuroda, M. and Sogihara, N. 2013. Development of a calculation method for fuel consumption of ships in actual seas with performance evaluation. In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering (pp. V009T12A047-V009T12A047). American Society of Mechanical Engineers
Citation note:
Mannarini G., Carelli L., Zissis D., Spiliopoulos G., Chatzikokolakis K.: Preliminary Inter-comparison of AIS Data and Optimal Ship Tracks. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 13, No. 1, doi:10.12716/1001.13.01.04, pp. 53-61, 2019
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