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It seems justified to analyze the safety of naviga-
tion on the basis of the numbers of both accidents
and near-miss situations. Such a combination of
analyses may better reflect the collision hazard, as
pointed out by (Inoue et al. 2004) and (Inoue and
Kawase 2007).
In air transportation there has been a tendency to
seek out proxy for aviation safety. One commonly
used measure is that of the ”air-miss”, often called a
”near-miss”. According to (Button and Drexler
2006) ”a near-miss involves an aircraft intruding
upon a predetermined safety zone or envelope
around another aircraft”. The reporting procedures
of near-miss in aviation are well founded providing
valuable statistics. In the maritime sector similar
procedures are missing, thus the near-miss can be
detected only by analysis of recorded data and back
propagation of recorded events.
Following this idea, this paper proposes also a
methodology to evaluate the occurrence of near
ship-ship collisions in an open sea area, based on the
AIS data. The method for near-collisions analysis
presented in this work is rooted in a well-established
concept of a ship domain proposed by (Fujii and
Tanaka 1971). An overview of the near collision de-
tection method is then given and applied to the
summer traffic in the Gulf of Finland.
Finally, we compare the results obtained from the
MDTC model, expressed as the number of ”collision
candidates” with the number of near-collisions and
the number of accidents recorded in the chosen area
of the Gulf of Finland. This approach allows us to
quantify the number of modelled ”collision candi-
dates”, with blind navigation assumption behind, to
the number of cases that ended up as close encoun-
ters, where collision evasive actions were taken.
Such quantification is carried out for three major
types of meeting scenario (crossing, head-on, over-
taking). By combining this accurate enough data
with an average annual number of accidents that
happened (which are random, and almost non pre-
dictable), the causation factor for the MDTC model
is obtained.
2 RESEARCH MODEL
2.1 Accident analysis
The annual number of ship-ship collisions in the an-
alyzed location of the Gulf of Finland (the water-
ways junction between Helsinki and Tallinn) is ob-
tained from HELCOM database, that covers a time
period between 1987 and 2007 (Pettersson et al.
2010). During this time, three accidents of this type
took place. Two of them happened during summer
time, and one was related to the ice conditions,
which are out of scope of the analysis presented in
this paper.
According to the aforementioned statistics there
was, on average, one summer collision per ten years.
This assumption is simplified, as the rate of collision
occurence is random, as the first collision happened
in 1996, second in 2001 and between the years 2001
and 2007 no summer collision happened in the area
of investigation. Notwithstanding, we assume that
the annual ship-ship collision frequency in the ana-
lyzed area equals 0.1.
Unfortunately, the database provided by HEL-
COM does not contain any information regarding
type of ship-ship encounter, at which the accident
took place. Thus it is not feasible to compare a mod-
elled number of collision candidates in given en-
counter type (crossing, head-on, overtaking) with an
appropriate number of the accidents. At this point
the results of near- collisions analysis are utilized
and considered a proxy between a model and the
recorded accident data.
Figure 1: The ship domain applied in the near-collision analy-
sis, with the following axes: a = 1.6LOA, b = 4LOA (Wang et
al. 2009)
2.2 Near-collisions analysis
The near-collision analysis applied in this paper is
based on a concept of a ship domain, which accord-
ing to definition given by (Goodwin 1975), is the ar-
ea around the vessel which the navigator would like
to keep free of other vessels, for safety reasons.
Since the first introduction of the ship domain
concept by (Fujii and Tanaka 1971), various re-
searchers have attempted to quantify the size of this
domain. An overwiev of the different proposed do-
mains is given in (Wang et al. 2009). Even though
the ship domain is a well established concept, certain
problems with the application can be identified as
pointed out by (Jingsong et al. 1993). Domains can
be classified by their shape: circular, elliptical and
polygonal domains. A distinction can also be made
between fuzzy domains and crisp domains. Fuzzy
domains such as that proposed by (Pietrzykowski
2008) and (Wang 2010) seem preferable in terms of