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2 2015

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Vessel classification method based on vessel behavior in the port of Rotterdam

Zhou Y., Daamen W., Vellinga T., Hoogendoorn S.

Zeszyty Naukowe Akademii Morskiej w Szczecinie

2015

nr 42 (114)

86--92

AIS (Automatic Identification System) data have proven to be a valuable source to investigate vessel 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.

Operational model for vessel traffic using optimal control and calibration

Shu Y., Daamen W., Ligteringen H., Hoogendoorn S.

Zeszyty Naukowe Akademii Morskiej w Szczecinie

2015

nr 42 (114)

70--77

Due to the ever-increasing economic globalization, the scale of transportation through ports and waterways has increased sharply. As the capacity of maritime infrastructure in ports and inland waterways is limited, it is important to simulate vessel behavior to balance safety and capacity in restricted waterways. Currently many existing vessel simulation models focus mainly on vessel dynamics and maritime traffic in the open ocean. These models are, however, inapplicable to simulating vessel behavior in ports and inland waterways, because behavior in such areas can be influenced by many factors, such as waterway geometry, external conditions and human factors. To better simulate vessel behavior in ports and waterways, we developed a new maritime traffic model by adapting the theory of pedestrian models. This new model comprises two parts: the Route Choice Model and the Operational Model. The Route Choice Model has been demonstrated and calibrated in our recent study, in which the desired speed is generated. This paper presents the second part of the model, the Operational Model, which describes vessel behavior based on optimal control by using the output of the Route Choice Model. The calibration of the Operational Model is carried out as well. In the Operational Model, the main behavioral assumption is that all actions of the bridge team, such as accelerating and turning, are executed to force the vessel to sail with the desired speed and course. In the proposed theory, deviating from the desired speed and course, accelerating, decelerating and turning will provide disutility (cost) to the vessel. By predicting and minimizing this disutility, longitudinal acceleration and angular acceleration can be optimized. This way, the Operational Model can be used to predict the vessel speed and course. Automatic Identification System (AIS) data of unhindered vessel behavior in the Port of Rotterdam, the Netherlands, were used to calibrate the Operational Model. The calibration results produced plausible parameter values that minimized the objective function. The paths generated with these optimal parameters corresponded reasonably well to the actual paths.