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Considering the varied and dynamic workload of vessel traffic service (VTS) operators, design an adaptive rotating shift solution to prevent them from getting tired while ensuring continuous high-quality services and finally guarantee a benign maritime traffic environment.

The problem of rotating shift in VTS and its influencing factors are analyzed first, then the framework of automatic identification system (AIS) data analytics is proposed, as well as the data model to extract spatial–temporal information. Besides, K-means-based anomaly detection method is adjusted to generate anomaly-free data, with which the traffic trend analysis and prediction are made. Based on this knowledge, strategies and methods for adaptive rotating shift design are worked out.

In VTS, vessel number and speed are identified as two most crucial factors influencing operators' workload. Based on the two factors, the proposed data model is verified to be effective on reducing data size and improving data processing efficiency. Besides, the K-means-based anomaly detection method could provide stable results, and the work shift pattern planning algorithm could efficiently generate acceptable solutions based on maritime traffic information.

This is a pioneer work on utilizing maritime traffic data to facilitate the operation management in VTS, which provides a new direction to improve their daily management. Besides, a systematic data-driven solution for adaptive rotating shift is proposed, including knowledge discovery method and decision-making algorithm for adaptive rotating shift design. The technical framework is flexible and can be extended for managing other activities in VTS or adapted in diverse fields.

This study aims to analyze information on vessel traffic between the two Koreas with a probability distribution for each route/vessel type. The study will then conduct an estimate for maritime transport patterns of inter-Korean trade in the future. To analyze the flow of inter-Korean coastal shipping, this study conducted visualization analysis of shipping status between North and South Korea by year, ship type, and port using navigation data of three years from Port Logistics Information System (Port-MIS) sources during 2006 to 2008, which saw the most active exchanges between the two governments. Also, this study analyzes shipping status between the two governments as a probability distribution for each port and provides the prospects for future maritime transport for inter-Korean trade by means of Bayesian Networks and simulation. The results of the analysis are as follows: i) when North-South routes are reopened, the import volume for sand from North Korea will be increased; ii) investment in the modernization of ports in North Korea is required so that shipping companies can generate profit through economies of scale; iii) the number of the operating vessels including container ships between the two governments is expected to increase like when the tensions and conflict on the Korean Peninsula was release, especially between Busan port in South Korea and Nampo port in North Korea; and iv) among container ships, transshipment containers imported and exported through Busan Port will be shipped to North Korea by feeder transportation.

This paper is an empirical attempt to verify the interplay between political change, fleet nationality, and the evolution of shipping networks. North Korea offers a good example of a socialist maritime country that has experienced much contrasting geopolitical contexts since 1990. A database of vessel movements between North Korean ports and other ports is analyzed. Main results show differences between North Korean and foreign fleets in terms of traffic (vessel size, age, berthing time) and geographical coverage. South Korean ports tend to play a new role in the reorganization of North Korean-related flows in Northeast Asia.

This work analyses autonomous ships' specific needs of external and environmental information in restricted pilotage waters. Harbour pilots use conventional well-tested techniques when piloting the manned vessel. In this work, the authors propose technological solutions to be installed or adapted in ports to feed the autonomous ships' systems with the information considered relevant by pilots.

To investigate what pilots consider relevant, the authors submitted a questionnaire to the pilotage of Paranaguá Port. Then the authors presented a case study including the critical areas for the navigation of ships.

These technological solutions aim to allow vessels reaching critical areas in a position, a time, a speed and a course that compensates the external forces and/or avoid high-risk situations. The authors have proposed technological solutions considering those already available in the ports, particularly in Paranaguá and Antonina in Brazil.

There is little published data on navigation of ships in pilotage waters. So far, there has been little discussion on autonomous ships in restricted waters.

Evaluates the effects of shipwrecks and peoples’ reactions following them, with regard to their feelings of preventability on someone’s part. In particular to the Erika in 1989, and the Prestige in 2002. The European Union (EU), which theretofore seemed to be neglecting maritime safety appears to have developed a maritime culture. The EU seems to have adopted the International Maritime Organisation’s (IMO) attitude regarding safety protocols, which must be a right and proper thing to do. Concludes that shipping has needed, and is now receiving, a proactive approach with regard to safety from the EU which should limit, as far as possible, disasters of both a human and ecological kind for the maritime world.

The purpose of this paper is to explore how change is brought about in quality governance of Baltic maritime oil transportation.

This qualitative case-study sought to understand the underlying mechanisms of quality governance. The paper analyzed versatile empirical material (including expert interviews) to uncover how a particular constellation of public and private, binding and voluntary, internal and external quality standards impacted the process of institution building for quality management in Baltic oil shipping.

The paper shows that emergence of quality practices in oil shipping is associated not only with the development of shipping industry as a whole, but also with the dynamics within the energy value chain. The findings suggest that alignment between rules and incentives is specific to a combination of given natural, political and economic contexts as well as physical infrastructure which set applied limitations upon the governance process and, eventually, impact the set of quality governance mechanisms available for use.

The paper shows that collective action is contextually-bound, thus the mechanisms of quality shipping governance can essentially differ from one locality to another. This implies that local solutions can be found to problems conventionally identified as global.

Paper’s findings question the applicability of “one-size-fits-all” approaches to policy-making and calls for more targeted regulation. The research also stresses the role of technical modernization in prompting actual change in regards to quality practices.

This research claims that transition to sustainable transportation systems requires institutions that are capable of linking actors and contexts in a way that balances supply and demand for quality.

This paper aims to propose a machine learning-based automatic labeling methodology for chemical tanker activities that can be applied to any port with any number of active tankers and the identification of important predictors. The methodology can be applied to any type of activity tracking that is based on automatically generated geospatial data.

The proposed methodology uses three machine learning algorithms (artificial neural networks, support vector machines (SVMs) and random forest) along with information fusion (IF)-based sensitivity analysis to classify chemical tanker activities. The data set is split into training and test data based on vessels, with two vessels in the training data and one in the test data set. Important predictors were identified using a receiver operating characteristic comparative approach, and overall variable importance was calculated using IF from the top models.

Results show that an SVM model has the best balance between sensitivity and specificity, at 93.5% and 91.4%, respectively. Speed, acceleration and change in the course on the ground for the vessels are identified as the most important predictors for classifying vessel activity.

The study evaluates the vessel movements waiting between different terminals in the same port, but not their movements between different ports for their tank-cleaning activities.

The findings in this study can be used by port authorities, shipping companies, vessel operators and other stakeholders for decision support, performance tracking, as well as for automated alerts.

This analysis makes original contributions to the existing literature by defining and demonstrating a methodology that can automatically label vehicle activity based on location data and identify certain characteristics of the activity by finding important location-based predictors that effectively classify the activity status.