behavior. The analysis of AIS data provides a possibility to recognize vessel behavior patterns in a waterway
area. Furthermore, AIS data can be used to classify vessel behavior into several categories. The analysis
results would help the port authority and other equivalent parties in port design and optimization or marine
traffic management. For researchers, it provides a systematic way to understand, simulate and predict vessel
behavior. This paper focuses on vessel classification in the Botlek area, Rotterdam from the perspective of
vessel behavior.
In this paper, the vessel properties, including vessel type, GT (Gross Tonnage), length and beam, have been
analyzed to investigate the vessel behavior, which is described by four factors including heading, COG
(Course over Ground), SOG (Speed over Ground), and position. In order to discover the behavior patterns in
normal situations, several thresholds are set in order to filter the collected AIS data to define such situations.
By plotting the AIS data, behavioral changes with the changes of properties have been observed. Hence, the
correlations between vessel behavior and different vessel properties are investigated. The results reveal that
a vessel’s sailing position and COG are both strongly determined by beam, while SOG is affected by GT. For
the heading of a vessel, no obvious correlation with any vessel property is found. Each behavioral factor is
clustered according to the correlated vessel property. This way, the criteria to classify the vessels are
determined. The vessel classification results based on their behavior would likely to lead to more consistency
in the analysis, simulation and prediction of the vessel behavior. The reason is that the development of such
a simulation model is based on a systematic recognition of the vessel behavior patterns.