Route prediction for a person in water drifting in chosen basins using graph theory

• Autorzy: Kijewska M.

Identyfikatory

DOI

10.17402/215

• Języki publikacji: EN

Abstrakty

EN

In this paper, the route prediction for a person in water was performed on the basis of a developed graph algorithm. This person drifted in water under the influence of surface currents and wind. The total drift route for the person in water was established as the route in a weighted directed graph. Vertices of this graph correspond to given points within a given basin. Additionally, the graph’s edges show possible directions of the overall human drift. The weight of the given edge describes the difference between the gradient of the edge and the total drift direction calculated on the basis of surface current field data and wind field data. An application has been created on the basis of a given algorithm which might be used to support the search for survivors in coastal areas (e.g. port basins, basins adjacent to the port, bays and sea areas) for which hydrodynamic models reliably reflect local phenomena.

Słowa kluczowe

EN

route prediction; trajectory prediction; object movement; search planning; survivor; person in water; search and rescue; graph theory

• Wydawca: Wydawnictwo Naukowe Akademii Morskiej w Szczecinie
• Czasopismo: Zeszyty Naukowe Akademii Morskiej w Szczecinie
• Rocznik: 2017
• Tom: nr 50 (122)
• Strony: 45--51
• Opis fizyczny: Bibliogr. 8 poz., rys., tab.

Twórcy

autor

Kijewska M.

• Maritime University of Szczecin, Institute of Marine Technologies 1–2 Wały Chrobrego St., 70-500 Szczecin, Poland

Bibliografia

• 1. Allen, A.A. & Plourde, J.V. (1999) Review of Leeway: Field Experiments and Implementation. Final Report No. CG-D-08-99. US. Coast Guard Research and Development Center
• 2. BHMW/HOPN (2009) Baltic Sea Pilot. Polish Coast. P502. 9th ed. Gdynia: Hydrographic Office of the Polish Navy.
• 3. Funquist, L. & Kleine, E. (2007) HIROMB, An introduction to HIROMB, an operational baroclinic model for the Baltic Sea. Report Oceanography. 37. Norrköping: SMHI.
• 4. ICAO & IMO (2013) International Aeronautical and Maritime Search and Rescue Manual. IAMSAR MANUAL, Mission Co-ordination. II. London: IMO/ICAO.
• 5. Kijewska, M. (2016) A graphical model to determine the influence of surface currents on small objects immersed in water. Scientific Journals of the Marine University of Szczecin 47 (119), pp. 170–175.
• 6. Kowalewski, M. (1997) A tree-dimensional hydrodynamic model of the Gulf of Gdańsk. Oceanological Studies 26 (4), pp. 77–98.
• 7. Pyrchla, J. (2008) Zastosowanie teorii zbiorów rozmytych do reprezentacji informacji wzrokowych wspomagają- cych lokalizację obiektów na powierzchni morza. Kraków: Uczelniane Wydawnictwa Naukowo-Dydaktyczne AGH, 184. pp. 114–115.
• 8. Pyrchla, J. & Kowalewski, M. (2009) Accuracy of hydrodynamic models of the Baltic Sea and safety in the Polish SAR responsibility area. Archiwum Fotogrametrii, Kartografii i Teledetekcji 19, pp. 373–385.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)