Ship collisions are one of the most common types of maritime accidents. Assessing the frequency and probability of ship collisions is of great importance as it provides a cost-effective and practical way to mitigate risk. In this paper, we present a review of quantitative ship collision frequency estimation models for waterway risk assessment, accompanied by a classification of the models and a description of their main modelling characteristics. Models addressing the macroscopic perspective in the estimation of ship collision frequency on waterways are reviewed in this paper with a total of 29 models. We extend the existing classification methodology and group the collected models accordingly. Special attention is given to the criteria used to detect potential ship collision candidates, as well as to causation probability and the correlation of models with real ship collision statistics. Limitations of the existing models and future improvement possibilities are discussed. The paper can be used as a guide to understanding current achievements in this field.

In the today’s seafarer market one of the key problems is the lack of seafarers, especially experienced officers. Although the global supply of officers is increasing steadily, the demand is still above supply. An additional problem is that an increased demand may lead to a decreased quality of education. Ships and shipping technology in general have become more advanced and require well educated and trained personnel. In addition, over the next several decades it is expected that partial or fully autonomous vessels will be in commercial use, and this will require significant changes in the education and training of crew members. So, regarding the education of seafarers, the main future challenges include the ways of ensuring sufficient supply of seafarers, especially well-trained officers, and adapting the education systems for the upcoming introduction of autonomous ships. This paper analyzes the present situation of the seafarers and shipping market, and provides forecast for the near future. Also, the main challenges in education and training of seafarers will refer to observing the recommendations for improvement and adaptation to future demands.

E-learning has become a widespread form of education as it allows the users a relatively easy access to needed information. E-learning has also been present in maritime affairs, although not so ubiquitous as in other economy sectors. Sea-borne shipping is one of the most stringently controlled industries, with a number of complex regulations and standards. This paper analyses learning methodologies and discusses the economic justification of implementing e-learning systems at global level, with an emphasis on the growing e-learning industry, corporate segment of e-learning, massive open online course market, and the importance of the micro-learning concept. In addition, this study analyses the present systems of seafarers’ education and the potentials, strengths and shortcomings of the conventional learning, e-learning and m-learning. Moreover, the recent application of e-learning in maritime affairs and the need of further research of the e-learning impacts in maritime affairs are examined. Finally, the presented information and discussion result in the logic matrix analysis and the SWOT analysis of e-learning, aiming to define the strengths, weaknesses, logic of action, goals and potentials of the implementation of e-learning in maritime affairs. Keywords: E-learning, education of seafarers, STCW Convention, IMO.

In the global maritime industry, ship grounding represents about one-third of commercial groundings. Grounding is a type of accident where the hull of a ship strikes the seabed, causing damage to the hull. This type of accident can lead to damage to the hull and water penetration, but also to the pollution of the marine environment by the spillage of ship fuel or some liquid cargo carried by the ship. This paper presents a chronological overview of the contribution of ship grounding frequency, where one of the first ideas of grounding probability was presented by Macduff (1974) and Fuji (1974) in their models. Their ideas, such as grounding candidates and causing probability, laid the foundation for the development of future models. After their models, years later, other models continued to be developed; e.g., analytically (Macduff, Fujii, Amrowitcz, etc.) and statistically (Pedersen, Simonsen, etc.). To find the probability of grounding in an area of interest or in a scenario, it is necessary to have the number of grounding candidates and the causing probability. There are different internal and external factors that affect both probabilities, and in this paper, we analyze how various authors approach their grounding models and have tried to show the actual event as faithfully as possible and thus contribute to greater safety in maritime transport. The number of grounding frequency models significantly complicates their selection in practice; accordingly, the review of models in this paper should facilitate this, but also it should facilitate future research on this topic.

Automated surveillance systems based on machine learning and computer vision constantly evolve to improve shipping and assist port authorities. The data obtained can be used for port and port property surveillance, traffic density analysis, maritime safety, pollution assessment, etc. However, due to the lack of datasets for video surveillance and ship classification in real maritime zones, there is a need for a reference dataset to compare the obtained results. This paper presents a new dataset for estimating detection and classification performance which provides versatile ship annotations and classifications for passenger ports with a large number of small- to medium-sized ships that were not monitored by the automatic identification system (AIS) and/or the vessel traffic system (VTS). The dataset is considered general for the Mediterranean region since many ports have a similar maritime traffic configuration as the Port of Split, Croatia. The dataset consists of 19,337 high-resolution images with 27,849 manually labeled ship instances classified into 12 categories. The vast majority of the images contain the port and starboard sides of the ships. In addition, the images were acquired in a real maritime zone at different times of the year, day, weather conditions, and sea state conditions.

This paper analyses two different methods of estimating ship collision candidates. The first one is an analytical approach; accordingly, an overview of various analytical expressions for estimating the number of collision candidates for three main situations (encounter, overtaking, and crossing) will be presented. The second is a simulation approach: the paper will present how to simulate ship movements by replacing them with circles in order to obtain a graphical presentation of ship movements in the zone of danger, including the calculation of collision candidates. The applied simulation model will also feature three main situations, i.e. encounter, overtaking, and crossing, and the results of simulations will be compared with the results of analytical models. The results and conclusions should improve the existing models for obtaining the potential number of ship collisions and encourage new advanced simulation methods.