Figure 1 shows the variation tree analysis (VTA) of a ship entry report situation, which can explain the relation between the vessel and VTSO using several information sources and decisions. VTSOs are frequently required to identify the route and destination of a particular vessel and contact related offices, such as pilot, port management, and ship agents, in addition to their inherent tasks of INS, NAS, and TOS. Moreover, this intelligent information should be automatically distributed and displayed at least 10 minutes in advance.
VTSOs should obtain timely information from a VTS system to reduce their workload because they perform several related tasks. In addition, they must assist with the analysis of information regarding collisions, ship targeting and tracking, situation awareness, and inference. , VTSOs prefer to provide navigation and safety information when a ship enters a VTS area. They address general functions and requirements therefore, specific functions needed to support the decisions of VTSOs should be defined by a VTS authority.Īccording to the survey results for VTSOs performed by Kim et al. The International Association of Lighthouse Authorities recommendations and guidelines provide only general principles and conceptual explanations in the domain of decision support tools for VTSOs. Finally, conclusions are presented in Section 5. Section 4 develops the prototype of the decision support tool and implements a performance evaluation. In Section 3, the proposed context-aware rules and information provisioning models are described. The remainder of this study is organized as follows: Section 2 analyzes the user requirements of VTSOs. For prediction objects, the deep neural network (DNN) is used to predict the near-collision risk and destination of ships. These objects, with the exception of prediction, can be obtained using a rule-based approach. The objects of the proposed model include the display, prediction, and calculation of objects. To display information efficiently, we developed context-based rules to display objects based on the VTSO requirement. This study enables VTSOs to focus on the primary task of vessel traffic management by reducing the workload associated with performing additional tasks. In this study, we survey a context-aware procedure in VTS and propose an information provisioning model using rule-based and deep learning techniques. They focused on grounding accident situations. proposed the detection of ship grounding candidates as a VTS decision support tool. Praetorius and Lutzhoft conducted user requirement surveys for dynamic risk management through group interviews and semi-structured interviews. In recent years, in order to reduce the workload of VTSOs and the human error rate, several decision support tools have been developed to assist the decision-making abilities of VTSOs and help them to understand vessel traffic situations and how to transfer ship-based information. These additional tasks interfere with their vessel monitoring tasks. They also support search and rescue operations (SAR) and harbor-based operations, such as cargo operation, port facilities, and navigational aids. While VTSOs monitor vessel traffic, they also frequently check the vessel entry permission, berth, and pilot schedule of inbound ships while they monitor other vessel traffic. These services are provided based on the experience of VTSOs. The tasks performed by VTSOs are primarily divided into information service (INS), navigational assistance service (NAS), and traffic organization service (TOS). In harbor and coastal water areas, vessel traffic services (VTSs) are implemented by a VTS operator (VTSO) to improve the safety and efficiency of vessel traffic and to protect the marine environment.
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