Artificial intelligence techniques for enhanced tracking performance VTS radars

Background/Objectives: Ship trajectories in Vessel Traffic Service (VTS) system are generated by integrating the Automatic Identification System (AIS) or Radar system. However, the AIS system has missing data section caused by AIS device problems, radio jamming, and so on. These data have been confusing ship navigators and VTS operators.Methods/Statistical analysis: In order to extract missing AIS data, time intervals of sequent points from each ship trajectory are calculated. The section with missing AIS data is above a threshold time limit defined by characteristics. Using k-means algorithm, missing AIS data were clustered into several clusters stored by ship’s ID and sailing direction. Using association rule mining analysis, meaningful association pattern were calculated by missing AIS dataset.Findings: As a result of the association rule mining, we found several missing AIS situation patterns. In case of the west route, the probability of missing AIS situation is high when they enter the east and passenger routes. Also, the probability of missing AIS situation of passing the passenger route is high when that ship enter the LNG, east and west routes.Improvements/Applications: These results can be used to predict the probability of missing AIS data in VTS system.

The Taiwan Strait, to the west of Taiwan, is rich in wind energy resources and has the greatest offshore wind power potential in the world. Therefore, Taiwan has been actively expanding its offshore wind power industry in this area in recent years and expects to achieve the total installed capacity to 15.6 GW by 2035. Due to the large vessel traffic flow in Western Taiwan’s sea area, wind farms will inevitably reduce the navigable space and shadow some existing marine aids to navigation, thus worsening navigation safety. An approach using a fault tree analysis was used to carry out analysis of collision risk between ship-to-ship and ship-to-turbine. The vessel density distribution and traffic flow within the open sea of offshore wind farms would further increase to curtail the available navigable space. The shadowing effects along navigation channels would thereafter be worsened to raise the probability of collision risks in the sea. The results of the fault tree analysis revealed that if the ship is out of control, the time allowed to provide assistance is rather short, leading to the increase of collision risk extent between ships and wind turbines. Moreover, the study also found that unfit functions of the Vessel Traffic Service System and navigation aids and frequently and arbitrarily crossing the navigation channel of fishery vessels are the main causes of ship collisions. In order to effectively improve the navigation safety, competitive strategies for navigation safety are investigated and evaluated in this study. These strategies include making a complete plan for utilizing the whole sea, integrating the offshore vessel traffic service and management system, providing remote pilotage services, and building salvage vessels. The above promising strategies would enhance the navigation safety within the open sea. Collision risk might occur once marine accident occurs and no salvage vessel is available.

In large harbours and long channels where congested traffic and critical weather are present, VTS (vessel traffic service) systems are needed for traffic management and control. The requirements for these systems become more and more demanding because of the continuous increase of traffic and adverse meteorological conditions; reliable systems which can help the operators to avoid accidents which can jeopardise the security of people and goods have to be used to increase safety and efficiency. These systems employ mainly radar sensors, suitably placed in order to have a complete coverage of the area to be controlled, because a 24-hours operation in all weather conditions must be assured. In this paper a new methodology to process digitised radar images to extract object features (size, heading, etc.) is presented. Considering that ships arriving to, or departing from, harbours are big objects moving in narrow channels or waterways, information such as length and bow position are fundamental to control the ship movements, to evaluate the distance between two vessels, or between the vessel and fixed objects such as buoys or wharves. Results of extensive measurement campaign carried out in Naples, Leghorn and Genoa harbours are reported.

Maritime accident prediction in busan port using machine learning: An integrated approach with maritime accident reports and VTS data

Vessel Traffic Services (VTS) is one of the most important aids for ships in the dangerous waters. Due to the ever-increasing sea transport and thus the number of ships in this service, the importance of the services offered by VTS has increased more in the course of time. Despite the advanced technological infrastructure and the improved VTS, however the safety of sea traffic is still mostly based on human factor. Although in the relevant literature there have been some studies revealing the effects of VTS on the safety, there has been no research on the service quality. The aim of this study is, considering the views of ship masters, to analyze the effects of the VTS service quality perceptions on the corporate image. The process of this study has been two-fold; developing a VTS service quality scale for shipmasters and the required through this scale measuring the perceptions of the service quality of the Turkish Straits Vessel Traffic Services (TSVTS) and the effects of these perceptions on the corporate image. Developing the model of study has been based on the relevant literature, and SERVQUAL model has been chosen. Firstly, in analyzing the perceptions, 20 experts from four diverse field have been interviewed and a pilot study has been carried out with shipmasters (n=72). The questionnaire, which has been conducted through shipmasters (n=192) who have used the Turkish Straits, has comprised 25 statements constituting two dimensions as “Perceived Service Quality (PSQ)” and “Corporate Image (CI)”. The results reveal that there is a strong interrelationship between the perceptions of the TSVTS’ service quality and corporate image for shipmasters. The VTS-PSQ scale develop through this research is expected to contribute to evaluating the VTS service quality and thus to the safe navigation through the relevant sea ways.

Recently, the Vessel Traffic Service (VTS) coverage has expanded to include coastal areas following the increased attention on vessel traffic safety. However, it has increased the workload on the VTS operators. In some cases, when the traffic volume increases sharply during the rush hour, the VTS operator may not be aware of the risks. Therefore, in this paper, we proposed a new method to recognize ship movement anomalies automatically to support the VTS operator’s decision-making. The proposed method generated traffic pattern model without any category information using the unsupervised learning algorithm.. The anomaly score can be calculated by classification and comparison of the trained model. Finally, we reviewed the experimental results using a ship-handling simulator and the actual trajectory data to verify the feasibility of the proposed method.

This study presents enhanced collision detection model in a Vessel Traffic Services (VTS) area. The proposed detection method of collision situations is based on the assumption that VTS station is provided with passage plans of all the vessels in a monitored area. By using an early detection model for prediction of possible collision situations, VTS stations could switch from the area-monitoring concept to the passage-monitoring system. An early detection model of collision risks in a VTS area uses vessels’ dynamic characteristics as inputs (vessels’ position, course over ground and speed), and delivers prediction of their future positions as output. In order to achieve the desired accuracy, the model takes into the account the intended course alterations and the impending environmental loads. The model is able to provide the outputs as early as the passage plans are submitted to a VTS monitored area. Hence, when discussing model’s capability for early detection of collision situations, improved VTS operating standards could be developed in order to achieve safer passages through enhanced collision avoidance strategies. Simulation results clearly show the advantages of the proposed model as a decision support tool for a VTS operator when combining passage plans with the analysis of environmental loads.

Research on detection mechanism of vessel abnormal behavior based on immune genetic spectral clustering algorithm

The Sea Traffic Management (STM) Validation Project is a European-based initiative with ambitions to improve maritime safety and efficiency through information sharing in real time. The purpose of this paper is to evaluate the “STM services,” which can be categorized as low-level automated functions designed to improve information exchange between ship and shore. Full-scale simulated scenarios were developed and tested on 16 professional vessel traffic service (VTS) operators comparing VTS operations as they are today with the added STM functionality. Data collection involved observations which assessed the frequency and type of interactions between ships and VTS, followed by questionnaires to provide an overall assessment of the user experience. The results indicate that the frequency and method of communication patterns between VTS operators and ships will be affected by the integration of the STM services. Additional access to navigational information could change the role of VTS operators in traffic situations compared with traditional operations. This paper discusses the findings from a socio-technical systems perspective while also addressing the individual STM services and their potential impact on VTS operations. This research provides valuable information for European VTS centers that could be affected by the implementation of e-Navigation and, specifically, the STM services.

With the fast development of transportation at sea, establishing vessel traffic services (VTS) is reaching a new high tide in order to more effectively guarantee vessel traffic safety, protect maritime environment and increase traffic efficiency. Formal safety assessment (FSA) has been considered a powerful tool that can help ensure that limited resources are allocated scientifically for these purposes. This paper introduces the application of FSA on planning VTS.

The functions of VTS are to ensure the security of waterways in the port, improve the efficiency of vessel navigation and avoid the pollution of the water, which is an important approach to water traffic management. It has apparent achievements in enhancing port operation efficiency and promoting the development of related industries. As a public service, the investment and operation cost of VTS is high. It has significant indirect economic and social benefits but relatively small direct economic benefits or profits. There is a lack of a unified method for the quantitative assessment of the VTS economic benefits. It is a meaningful topic that should be further explored in theoretical research. This paper analyzes and evaluates the connotation of VTS economic benefits and defines the scope of direct and indirect economic benefits. The direct economic benefits are classified with the specific business of VTS to establish a basic model, and sampling analysis is used to measure them in the application. For indirect economic benefits, the Input-Output Analysis (I-O) is used to measure them. The operational data of the Tianjin VTS is used as an example for verification. The correct understanding and evaluation of direct and indirect economic benefits generated by VTS is an inherent requirement to reflect the operational performance of VTS objectively and provides a scientific decision-making basis for the continuous investment and operation of VTS.

Vessel Traffic Service (VTS) plays an important role in maintaining the safety and order of ship traffic, especially in congested water areas such as the West Shipping Channel of Surabaya. With this system, it is hoped that the movement of ships can be more organized, so that the risk of accidents and violations can be minimized. However, the effectiveness of VTS in supporting the monitoring of the order of ship movement and berth areas still needs to be further studied. This study aims to analyze the effectiveness of Vessel Traffic Service (VTS) in supporting the monitoring of the order of ship movement and the berth area in the West Shipping Channel of Surabaya. This study uses a quantitative method with a simple linear regression approach. Data was collected through observation and analysis of secondary data, then processed using the SPSS 22 application. The results showed that the effectiveness of VTS had a significant effect on order monitoring, with a significance value of 0.001 less than 0.05. The value of the determination coefficient is 29.1% which means that the effectiveness of VTS contributes to the orderliness of ship movements and the berth area, and from the regression equation obtained it shows that every increase in the effectiveness of VTS by one unit will increase the monitoring of order by 0.470 units.

The growing adoption of autonomous technologies in the maritime industry creates a critical challenge for safe navigation: a communication gap between Maritime Autonomous Surface Ships (MASS) and human operators, both on conventionally crewed vessels and in shore-based control centers like Vessel Traffic Services (VTS). This gap is particularly pronounced in voice-based Very High Frequency (VHF) radio communication, which remains essential for mutual intent-sharing, conflict resolution, and coordinated navigation in a mixed-fleet environment. This paper introduces a forward-looking vision for an artificial intelligence (AI) powered framework aimed at achieving fully digitized maritime radio communication for MASS. The proposed system is structured around four tightly integrated modules: Sensory Input Stage, Text and Context Extraction, Contextualization and Reasoning - LLM Agent Loop, and Response Generation and Broadcasting. These components work cohesively to transform traditional voice radio exchanges into a machine-interpretable and protocol-compliant communication pipeline. This paper presents a comprehensive exposition of the framework’s architecture, accompanied by a structured development roadmap and appropriate evaluation methodologies for each module. It also introduces a novel concept of tiered autonomy levels for digital radio communication, emphasizing the critical role of human-in-the-loop supervision. By enabling autonomous ships to interpret, process, and respond to VHF transmissions in real time, this framework not only enhances operational efficiency but also contributes to the safe and standardized integration of autonomous technologies within the complex maritime ecosystem.

선박교통류 평가는 대상해역 해상교통특성 파악을 통하여 정량화된 체계화된 교통관리를 수행함으로써 해양사고를 예방하는데 중요하다. 해상교통류의 특성은 선박자동식별장치(AIS, Automatic Identification System)가 선박에 설치됨에 따라 이 장치에서 수신된 정보를 토대로 평가할 수 있다. 본 연구에서는 해상교통관제센터(VTS, Vessel Traffic Services)에서 선박으로부터 수집된 위치, 속력, 침로, 시간 정보로부터 항로상에 해상교통류를 평가하기 위한 시뮬레이터를 구현하였다. 그 결과 해상교통관제센터에서 수집된 데이터로부터 선박 통항량, 통항분포, 선박속력분포, 기하학적 충돌빈도가 계산되어 표시된다. 이러한 해상교통류평가 평가는 해상교통관제사가 해상교통관리의 관점에서 해상안전을 위한 서비스를 제공하는데 유효하게 활용될 수 있을 것으로 사료된다. Maritime traffic assessment is important to understand the characteristics of maritime traffic and to prevent maritime accidents. The maritime traffic assessment can be calculated from the ship trajectory data observed by using AIS(Automatic Identification System). This paper developes a maritime traffic assessment tool using ship's position and speed, course, time data from ships navigating waterways. The results are represented in terms of the number of traffic quantity and traffic distribution, speed distribution, geometric collision candidates. The developed tool will contributes to advance maritime traffic safety by VTS(Vessel Traffic Services).

This paper presents an intellectual decision making system for the vessel traffic service (VTS). Its aim is to increase the safety and efficiency of the traffic and the effectiveness of VTS. In general, the navigational decision making process in a traffic control system is based on radar and navigation information although other systems, such as automatic identification systems, GPS can be used with good effect. The application of an intellectual component during a decision making process increases safety and economic effects of the shipping as well as reduces the operator's workload.