Vessel Traffic Service Operators Research Articles

Vessel Trajectory Prediction at Inner Harbor Based on Deep Learning Using AIS Data

This study aims to improve vessel trajectory prediction in the inner harbor of Busan Port using Automatic Identification System (AIS) data and deep-learning techniques. The research addresses the challenge of irregular AIS data intervals through linear interpolation and focuses on enhancing the accuracy of predictions in complex port environments. Recurrent neural network (RNN), Long Short-Term Memory (LSTM), Bidirectional LSTM, Gated Recurrent Unit (GRU), and Bidirectional GRU models were developed, with LSTM delivering the highest performance. The primary scientific question of this study is how to reliably predict vessel trajectories under varying conditions in inner harbors. The results demonstrate that the proposed method not only improves the precision of predictions but also identifies critical areas where Vessel Traffic Service Operators (VTSOs) can better manage vessel movements. These findings contribute to safer and more efficient vessel traffic management in ports with high traffic density and complex navigational challenges.

A Formalism for Scalable Maritime Traffic Monitoring and Explainable Anomaly Detection and Resolution at Vessel Traffic Services

Abstract Vessel traffic service (VTS) centres around the globe monitor and manage the ship traffic in their areas of responsibility and respond to arising unsafe or inefficient situations. Decision support tools (DST) help vessel traffic service operators (VTSO) to enhance their situational awareness and decision-making process, thus to recognise and assess dangerous situations. However, current DST have unsophisticated features and require manual configuration by the operator. Firstly, triggers for alerts are mostly based on the creation of geographical polygons for spatial-dependent assignment of rules, thresholds, ranges and limits for specific features. Secondly, calculations for the detection of safety-critical situations rely on measurements based on the closest point of approach (CPA) without taking contextual information into account. Thirdly, trajectory predictions are performed considering a constant velocity model (CVM) which does not depict reality. Due to these and other peculiarities, current DST are prone to false alerts. This results into a high workload where unsafe situations may be overlooked. In this paper, we propose a hierarchical formalism as foundation for an anomaly detection and resolution which generates less false alerts. The formalism consists of three hierarchical layers which represent, objects, measurements and situations. The formalism ensures adaptability and extensibility to various VTS areas and traffic patterns. Moreover, due to the given structure, the presented formalism is easily implementable, adaptable and scalable taking the currently available technological capabilities at VTS centres into account. We demonstrate the feasibility of this formalism by implementing a proof-of-concept and assessing it with realistic scenarios. Our implementation utilizes a rule-based system as central framework and it is configured through statistical methods, e.g. machine learning. Given this hybrid approach, the implementation provides reasonable and explainable results. This enables comprehensibility and verifiability by authorities and operators which is crucial for acceptance.

Traffic advisory for ship encounter situation based on linear dynamic system

Enhancing Situation Awareness (SA) is crucial for maritime traffic safety. Various indicators have been developed to assess risks in encounter situations and support the SA of Vessel Traffic Service Operators (VTSOs) and Officers on Watch (OOW), including collision risk and traffic complexity. Despite the widespread use of these navigational aids, ship collision incidents have not been effectively reduced. This paper abstracts ship encounter situations as linear dynamic systems to enhance the understanding of traffic situations. A traffic advisory framework based on the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) is proposed by integrating complexity metrics with risk indicators. The proposed method is validated through simulations of head-on, overtaking, and crossing scenarios, demonstrating its ability to accurately assess encounter complexity and issue advisories for free navigation, complexity, and resolution. Finally, we discuss the practical application of the proposed method through real-world experiments conducted in the waters of Qiongzhou Strait. The results indicate that the proposed method effectively quantifies the complexity of ship encounter situations and identifies high-collision-risk vessels from a microscopic perspective while providing insights into maritime traffic surveillance from a macro perspective.

An improved maritime traffic situation complexity model for intelligent maritime management in the inland ferry area

In increasingly busy inland ferry waterways, traditional maritime traffic situation awareness mainly relies on the experience of Officers on Watch (OOW) and Vessel Traffic Service Operators (VTSOs). Although advancements in science and technology can provide more navigational data to OOW and VTSOs, they often find it difficult to intuitively perceive navigation risks from the massive amounts of heterogeneous data. Current maritime traffic situation models mostly used in open waters make it hard to objectively grasp and understand the overall complexity of ferry water area traffic and to capture the most critical ship targets in local areas. Therefore, this study proposes an improved complexity model for maritime traffic situations in inland waters. It selects dynamic traffic density factor, ship approaching factor, and conflict area to assess the local complexity between ships. Then, the global complexity of traffic in the ferry water areas can be evaluated using the entropy weighting method. These promising results suggest that assessing maritime traffic complexity on different levels can help OOW and VTSOs manage traffic in ferry water areas and identify target vessels that require traffic services and control. The application of this method supports the construction of smart maritime management, enhancing the efficiency and automation of ferry water areas.

Evaluation Of The Implementation Of Traffic Separation Scheme (TSS) In The Sunda Strait

The sea traffic separation chart or what is commonly called the Traffic Separation Scheme (TSS) is generally used to assist international shipping navigation and is also part of a country’s maritime zone as mandated in UNCLOS 1982. In this case, Indonesia has implemented TSS in the Sunda Strait and in the Lombok Strait on 1 July 2020. The Directorate General of Sea Transportation, the Ministry of Transportation is the leading agency responsible for enforcement of the scheme through the Directorate of Navigation and the Directorate has established the Merak Vessel Traffic Service (VTS) system in the Province of Banten to monitor the Sunda Strait and VTS Benoa in the Province of Bali to monitor the Lombok Strait. Since the implementation of the TSS in the Sunda Strait until now, it turns out that there are still many ships that do not comply with the traffic procedures in the TSS as regulated in such a way. The research suggestion that violations in addition to administrative sanctions for those ships who commit violations, also implement a violation reporting system application to speed up the process of reports from VTS Operators to related officials.

Bibliometric and Qualitative Analysis of Workload Studies in the Maritime Sector

Maritime traffic is a socio-technical system that requires the collaboration of many elements such as stakeholders, equipment, environment, and technology. The workload for stakeholders in marine traffic has increased due to the growing number of monitored ships in coastal areas, as well as the variety and amount of operations. This study aims to conduct a comprehensive analysis of workload studies conducted in the maritime domain, encompassing all stakeholders. In doing so, the goal is to reveal changes over the years, identify collaborative areas, and enhance the understanding of the concept. The Scopus and Web of Science (WoS) databases were used as the data collection tool. A search was conducted with keywords associated with the concept of 'workload in maritime,' leading to the analysis of 372 relevant documents. VOSviewer Bibliometric Data Analysis Tool and MAXQDA Analytics Pro 22 Software were employed in the analyses. After the data from the two databases were combined, it was found that the authors with the most publications (P) and citations (C) in this field are Murai K. (P-41; C-200), Hayashi Y. (P-30; C-196), and Okazaki T. (P-15; C-82). With 56 publications, Japan is in first place, followed by the US (39), China (35), and the UK (27). Additionally, Japan and the US are two countries in collaboration. Among the commonly used terms in this research are mental workload, vessel, safety, performance, human factors, tiredness, simulator, and physiological measuring techniques including heart rate, nasal temperature, EEG, and salivary amylase. In workload studies, psychosocial variables were most prominently expressed in 2021. While the analysis of workload studies indicates a focus on “mental workload” studies involving Vessel Traffic Services Operators (VTSOs), research related to seafarers, cadets, marine pilots, and ship masters is seen to dominate this field which is “bridge team”.

Selection and recruitment process of Vessel Traffic Services Operators

ABSTRACT Vessel Traffic Service Operators (VTSOs) provide quality services in a certain standard and systematic way worldwide. Moreover, authorities should design all VTSO training by international standards and existing training techniques/trends to achieve this at the international level. Therefore, this research is focused on the training of the operators, which is the most crucial element for safer, timely, and effective services. However, the research results reveal that the job application criteria and selection techniques directly or indirectly affect the training program and syllabus. Hereof, this study aims to identify factors affecting the selection and recruitment process of VTSOs. In addition, face-to-face interviews were conducted through VTSOs, trainers, and observations in training centres for further thought. Likewise, novel approaches, methods and recommendations bring forward a proposal for selecting and recruiting VTSOs and training models, curricula, and techniques. The findings and outputs also indicate the need for new and detailed studies.

A Contextually Supported Abnormality Detector for Maritime Trajectories

The analysis of maritime traffic patterns for safety and security purposes is increasing in importance and, hence, Vessel Traffic Service operators need efficient and contextualized tools for the detection of abnormal maritime behavior. Current models lack interpretability and contextualization of their predictions and are generally not quantitatively evaluated on a large annotated dataset comprising all expected traffic in a Region of Interest. We propose a model for the detection of abnormal maritime behaviors that provides the closest behaviors as context to the predictions. The normalcy model relies on two-step clustering, which is first computed based on the positions of the vessels and then refined based on their kinematics. We design for each step a similarity measure, which combined are able to distinguish boats cruising shipping lanes in different directions, but also vessels with more freedom, such as pilot boats. Our proposed abnormality detection model achieved, on a large annotated dataset extracted from AIS logs that we publish, an ROC-AUC of 0.79, which is on a par with State-of-the-Art deep neural networks, while being more computationally efficient and more interpretable, thanks to the contextualization offered by our two-step clustering.

A Novel Ship Speed and Heading Estimation Approach Using Radar Sequential Images

This paper proposes an approach to estimate ship dynamic features (i.e., speed and heading) using radar sequential images, which can be used to assess the ship-ship collision risk in vessel traffic service (VTS) center. The proposed approach estimates the ship speed and heading in three steps, including ship detection, tracking, and data fusion. First, the ship target, together with its center coordinate, is detected by introducing the background subtraction detector in each radar image. Second, the ship position in one frame is mapped to the consecutive frame, and ship trajectory distribution is established using the Kalman filter and Hungarian algorithms. Third, fuzzy logic is introduced to fuse data from radar and AIS. Specifically, input variables include two parameters, which are the ship speed/heading difference in consecutive frames using radar and AIS, respectively. The variance of ship speed distribution is 1.30 at 10s sampling frequency, and the variance of ship heading distribution is 26.53, the experimental results indicate that the proposed approach can accurately estimate ship speed and heading in the radar sequential images of the Yangtze River. The strength of the proposed approach is its capability to estimate the ship speed and heading quantitatively from radar sequential images, which is interactive and interpretable for VTS operators.

Organization of Vessel Traffic on Dredged Świnoujście-Szczecin Fairway: VTS Operators’ Viewpoint on the Use of Infrastructure for Ships Passing

Organization of Vessel Traffic on Dredged Świnoujście-Szczecin Fairway: VTS Operators’ Viewpoint on the Use of Infrastructure for Ships Passing

A rule-based maritime traffic situation complex network approach for enhancing situation awareness of vessel traffic service operators

The development of the shipping industry has led to increasingly busy traffic near many port areas, which leads to higher demands for vessel traffic service operators (VTSOs), and challenges to maintain situational awareness. However, an effective rule-based method for analyzing waterway traffic from a systemic perspective to improve situational awareness is lacking. Therefore, this article proposes a method to assess the maritime traffic situation complexity for this purpose. Referring to the COLREGs, a rule-based maritime traffic situation complex network (R-MTSCN) model is established by taking ships as nodes, and the collision avoidance relationship between ships as the directed edges. In addition, network topology features such as degree, vertex strength, and vertex strength distributions are used to statistically characterize the evolution of the complexity of maritime traffic systems. By analyzing the AIS data of ships navigating the Yangtze River estuary, the concept of the proposed model is demonstrated, thus providing a pathway to develop intelligent, digital, and data-driven Vessel Traffic Services, aiming to enhance efficiency of vessel traffic management and improve maritime safety.

Maritime Anomaly Detection for Vessel Traffic Services: A Survey

A Vessel Traffic Service (VTS) plays a central role in maritime traffic safety. Regulations are given by the International Maritime Organization (IMO) and Guidelines by the International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA). Accordingly, VTS facilities utilize communication and sensor technologies such as an Automatic Identification System (AIS), radar, radio communication and others. Furthermore, VTS operators are motivated to apply Decision Support Tools (DST), since these can reduce workloads and increase safety. A promising type of DST is anomaly detection. This survey presents an overview of state-of-the-art approaches of anomaly detection for the surveillance of maritime traffic. The approaches are characterized in the context of VTS and, thus, most notably, sorted according to utilized communication and sensor technologies, addressed anomaly types and underlying detection techniques. On this basis, current trends as well as open research questions are deduced.

Deriving Optimal Capacity for Typhoon Shelters—An Analysis of the Jinhae Bay Typhoon Shelter in South Korea

Jinhae Bay in South Korea is a common typhoon shelter, but there are no established criteria for the area or vessel capacity. The aim of this study was to determine the optimal capacity and arrangement of typhoon shelters for vessels in the sea area surrounding Jinhae Bay. The study identified several areas that could serve as typhoon shelters and conducted a survey with experienced VTS operators and ship operators to identify the best typhoon avoidance areas. The study found that the Japanese and Spanish design criteria for anchoring in strong winds were useful in computing the optimal capacity of typhoon shelters. A nesting algorithm based on the genetic algorithm and the No-Fit-Polygon theory was used to optimize the arrangement of shelters. The study found that the Jinhae Bay typhoon shelter can be effectively managed by arranging shelter-seeking vessels based on the nesting algorithm. The study contributes to supporting quantitative methodology-based decision-making and has practical significance for managing typhoon shelters in the Jinhae Bay area. Further research is needed to evaluate the proposed arrangement plan for typhoon shelters and confirm the validity of the results through simulation and practical implementation. Additionally, the time complexity for vessels to approach the anchorage should be considered in future studies.

Statistical Model of Ship Delays on the Fairway in Terms of Restrictions Resulting from the Port Regulations: Case Study of Świnoujście-Szczecin Fairway

The article describes a study of ship delays on the Świnoujście-Szczecin waterway observed by the VTS operator. The research has led to an understanding of the factors that affect delays of ships calling at the ports of Szczecin and Police, as well as the possibilities of predicting and preventing these delays. This article presents the results of the study on the traffic intensity on the investigated waterway and the process of identifying the port regulation that causes the most frequent delays. Based on the obtained results from the statistical analysis and from using multiple regression, a statistical model has been developed that has the ability to estimate expected delays. Additionally, the model has been expanded to calculate financial losses resulting from delays, taking into account the daily cost of maintaining the studied ships. The study took place during ongoing project “Modernization of the Świnoujście-Szczecin waterway to a depth of 12.5 m” but does not include delays resulting from this project.

Professional Identity of Indonesian VTS Operators

The research aims to identify the attitude of Indonesian VTS operators toward their profession. Thus, it focuses on identifying several factors that affect the construction of their professional identity (PI) to understand better their reason for pursuing the job. The analysis is based on factors, i.e., self-image, social recognition, attitude toward change, professional competence, and expectations about the profession in the future. It employs a qualitative approach, using an open-ended questionnaire to obtain the data from 12 VTS operators who participated in a VTS supervisor training program. The results indicate that the participants have positive attitude towards their profession. Participants are found to demonstrate strong professional identity. The VTS operators are driven by their self-recognition, how they see their job as a calling instead of just a job. It is mainly shaped by the skills and efforts of the VTS operators reflecting their willingness and courage to embrace the profession.

Fatigue as a key human factor in complex sociotechnical systems: Vessel Traffic Services.

Vessel Traffic Services (VTS) are considered a subsystem of people, whose mission is to improve the effectiveness and efficiency of maritime transport within the maritime system. VTS operate as a control system where Vessel Traffic Services Operators (VTSOs) must cope with a complex environment to make up for safe and efficient maritime transport, so it is essential to understand how these operators maintain control through adapting to the uncertain and dynamic environment of maritime traffic. This multidisciplinary study explores how human factors within this complex sociotechnical system, means VTS, play a role in maritime safety, specifically focusing on fatigue, which is considered a key variable for VTSOs' performance. In this context, the research has focused on the assessment of fatigue with psychological and operational instruments to highlight the importance of the human element in CSSs. To study the intra and inter-individual differences in fatigue ratings and their relationships with other personal and environmental variables: mental workload, work shifts, reaction time, and hours of usual sleep. The study was conducted in two of the 19 Spanish Maritime Rescue Coordination Centers (MRCCs) with a sample of 23 active VTSOs (82.14% of the staff). Both objective and standardized subjective measures were used to assess fatigue and associated sleepiness (Borg RPE, Nasa-TLX, Stanford Sleepiness Scale, and Self-Assessment Manikin Scale). A significant positive correlation between fatigue and mental workload was found, being more prevalent in the night shift, which shows a bigger variation in these variables. A significant difference was found in the increase in fatigue experienced throughout the shift depending on the hours of usual sleep, being smaller in the group of subjects reporting to sleep more. The human element is key to maritime safety related to Vessel Traffic Services, so it is of paramount importance to consider certain measures to counteract the negative effects of fatigue. A proper organization of duties on/off periods, assessment of work and rest schedules, and the implementation of fatigue management programs based on sleep education are recommended.

Conflicts Encountered with Bridge Team from the Perspective of Vessel Traffic Service Operators: A Research Within E-Navigation Concept

The hazards that threaten marine navigation safety in the intensive routes and critical straits need to be managed effectively. To manage these risks, the concept of e-navigation has been offered to all stakeholders of marine transportation. E-navigation basically aims to organize, serve, and exchange marine information systematically. It is considered that the relations between the stakeholders may constitute significant conflicts in exchanging marine information. The main purpose of this study is to reveal the sources of conflicts and risk scores on navigation operations encountered with the bridge team from the perspective of vessel traffic services operators (VTSOs). In order to determine the sources of the conflicts, the conflict-related literature has been thoroughly reviewed, a semi-structured interview form was developed, and the VTS supervisors have been interviewed. In discovering the sources of conflicts, content analysis has been carried out from the interviews. The findings have been discussed with the relevant experts, and risk scales have been developed to evaluate the risks of conflicts. The frequency of conflicts and the results have been evaluated by the VTSOs employed at the Center of VTS in İstanbul, and risk scores have been defined. The risk scores related to the conflicts indicated on the risk matrix and e-navigation designed solutions have been compared and discussed. The findings reveal that there are certain similarities between the high-scored risks regarding communication quality and reporting systems. Although e-navigation solutions focus on improving technical issues. Conflicts caused by interpersonal, cognitive, and personal features that are not covered by e-navigation solutions have an important place among the conflict sources.

Development of Priority Index for Intelligent Vessel Traffic Monitoring System in Vessel Traffic Service Areas

Recognizing dangerous situations in advance and determining priority is essential in vessel traffic surveillance. The traffic management priority is determined by the vessel traffic service operator (VTSO) employing the closest point of approach (CPA) and the time to CPA (TCPA) of the targets considering their current navigational data. Various environmental conditions influence CPA and TCPA, which affects the importance of surveillance. This study aims to support vessel traffic prioritization in the navigation surveillance of VTSO from the observer side. The vessel tracks were clustered based on density, and a priority index of the vessel surveillance was developed in the VTS area by reflecting regional navigation characteristics. Density-based spatial clustering of applications with noise (DBSCAN) was used for data clustering to classify the surveillance area. A fuzzy membership function was constructed based on the CPA and TCPA belonging to each cluster, and a dataset for determining priorities was constructed, yielding 17 clusters, fuzzy rules, and tables, with the priority index extracted for all vessel pairs to visualize the priority. The results indicated prior recognition of all dangerous situations. The proposed method facilitates vessel surveillance priority determination in high-density areas and predicts the risk in advance, thereby contributing to traffic management.

Node importance evaluation in marine traffic situation complex network for intelligent maritime supervision

Vessel Traffic Services (VTS) aims to improve the safety and efficiency of water transportation, yet its operation relies heavily on the work of Vessel Traffic Services Operators (VTSOs). Enhancing VTSO's situational awareness help improve VTS performance while relieving the workload of VTSOs. However, an effective method of analysing the water traffic from a systemic perspective to improve situational awareness among VTSOs is lacking. Therefore, we propose a method to evaluate the node importance of ships based on the marine traffic situation complex network (MTSCN) to enhance the situational awareness of VTSO. The node importance of ships reflects the conflicting risk and the complexity of the traffic structure. Several case studies were conducted to demonstrate the feasibility of applying this proposed method to promote the performance of VTS. The promising results show that the identification of key ships with high node importance can help VTSOs identify targeted ships in need of traffic service and control and determine the priority in which these targeted vessels are to be supervised. The application of this proposed method supports the construction of intelligent VTS to improve its efficiency and automation in controlling and serving water traffic.

A Systematic Review on Human Factors Related to Safety Affecting Performance of Vessel Traffic Service Operators

A Systematic Review on Human Factors Related to Safety Affecting Performance of Vessel Traffic Service Operators