On navigational situation evaluation under ambiguity and partial evidence

• Autorzy: Filipowicz W.
• Języki publikacji: EN

Abstrakty

EN

The paper depicts new approach involving navigational situation assessment. Nowadays operator at maritime traffic monitoring station have access to a great amount of various quality data. Information come from different sources and the data are generated by multiple of sensors. Multiple sources of data create new challenge regarding data association. The challenge is met by technology called data fusion. By means of fusion, different sources of information are combined to arrive at proper decision. Ships safety factors were introduced to enable vessels' classification regarding potential consequences of an accident. It is assumed that safety factors are fuzzy, imprecise values. Small ranges of value were assigned to small craft without dangerous cargo. The largest intervals are reserved for huge crude carriers. Fuzzy factors (SF) depend on subjective evaluation of ships tonnage and on amount as well as harmfulness of their cargo. Extended scope of the SFs is introduced and reasoning on subjective classification discussed. Included numerical example illustrates presented material.

Słowa kluczowe

EN

navigational risk prediction; ships' safety maritime

PL

przewidywanie ryzyka nawigacyjnego; bezpieczeństwo morskie statku

• Wydawca: Polskie Forum Nawigacyjne
• Czasopismo: Annual of Navigation
• Rocznik: 2009
• Tom: No. 15
• Strony: 25--32
• Opis fizyczny: Bibliogr. 4 poz., rys., tab.

Twórcy

autor

Filipowicz W.

• Gdynia Maritime University

Bibliografia

• [1] Anderson, D. & Lin, X. G. 1999. A Collision Risk Model for a Crossing Track Separation Methodology. Journal of Navigation. Vol. 49/3
• [2] Wawruch, R. Mikulski, J. (ed.) 2007. Advances in Transport Systems Telematics. Utilization of the Automatic Identification System for Collision Avoidance and Traffic Monitoring: 337-346. Katowice
• [3] Filipowicz, Wl. Weintrit, A. (ed.) 2007. Advances in Marine Navigation and Safety of Sea Transportation. Intelligent VTS: 151-159, Gdynia
• [4] Denoeux, T. Fuzzy Sets and Systems, Modelling vague beliefs using fuzzy valued belief structures, 1999