Maritime traffic

The presented method reconstructs a network (a graph) from AIS data, which reflects vessel traffic and can be used for route planning. The approach consists of three main steps: maneuvering points detection, waypoints discovery, and edge construction. The maneuvering points detection uses the CUSUM method and reduces the amount of data for further processing. The genetic algorithm with spatial partitioning is used for waypoints discovery. Finally, edges connecting these waypoints form the final maritime traffic network. The approach aims at advancing the practice of maritime voyage planning, which is typically done manually by a ship’s navigation officer. The authors demonstrate the results of the implementation using Apache Spark, a popular distributed and parallel computing framework. The method is evaluated by comparing the results with an on-line voyage planning application. The evaluation shows that the approach has the capacity to generate a graph which resembles the real-worl...

NatĊĪenie ruchu statków na Baátyku regularnie wzrasta. Pojawiają siĊ nowe, znacznie wiĊksze statki przewoĪące áadunki niebezpieczne. W zaistniaáej sytuacji dotychczasowe uregulowania w zakresie uporządkowania ruchu statków są niewystarczające. Dotyczy to zwáaszcza dostĊpu do portów polskich. Niezwykle pilną sprawą jest wiĊc opracowanie staáych tras dla statków przewoĪących áadunki niebezpieczne w tym planowanie tras dla gazowców LNG dostarczających gaz w postaci Sáynnej do Polski. Zaniedbanie tego ...

The presented method reconstructs a network (a graph) from AIS data, which reflects vessel traffic and can be used for route planning. The approach consists of three main steps: maneuvering points detection, waypoints discovery, and edge construction. The maneuvering points detection uses the CUSUM method and reduces the amount of data for further processing. The genetic algorithm with spatial partitioning is used for waypoints discovery. Finally, edges connecting these waypoints form the final maritime traffic network. The approach aims at advancing the practice of maritime voyage planning, which is typically done manually by a ship’s navigation officer. The authors demonstrate the results of the implementation using Apache Spark, a popular distributed and parallel computing framework. The method is evaluated by comparing the results with an on-line voyage planning application. The evaluation shows that the approach has the capacity to generate a graph which resembles the real-worl...

Structural optimization regularly involves conflicting objectives, where beside the eligible weight reduction, increase in e.g. safety or reliability is imperative. For large structures, such as ships, to obtain a well-developed Pareto frontier can be difficult and time-demanding. Non-linear constraints, involving typical failure criteria, result in complex design space that is difficult to investigate. Evolutionary algorithms can cope with such problems. However they are not a fast optimization method. Here we aim to improve their performance by guiding the search to a particular part of Pareto frontier. For this purpose we use a genetic algorithm called VOP, and use it for optimization of the 40 000 DWT chemical tanker midship section. Beside weight minimization, increase in safety is investigated through stress reduction in deck structure. Proposed approach suggests that in the first stage one of the objectives is optimized alone, preferably more complicated one. After obtaining satisfactory results the other objective is added to optimization in the second stage. The results of the introduced approach are compared with the conventional concurrent optimization of all objectives utilizing widespread genetic algorithm NSGA-II. Results show that the guided search brings benefits particularly with respect to structural weight, which was a more demanding objective to optimize. Salient optimized alternatives are presented and discussed.

Seasonal maritime traffic was investigated in relation to cetaceans, through direct observations (July 2013-June 2015) along three fixed transects in Western Mediterranean. Visually obtained vessel abundance was compared with Automatic Identification System data to explore if the two methods provided different results. Traffic intensity and composition were characterised by seasons and vessel categories. Finally, cetacean presence was investigated in relation to traffic by measuring the difference of vessel abundance in the presence and absence of animal sightings. Results showed that visual sampling was consistent with AIS data, providing more information on small-medium vessels. Traffic was more intense and diverse in Spring/Summer, and the highest vessel abundance and seasonal variations in composition emerged for inshore subareas. The difference of traffic in the presence and absence of cetaceans was higher in most offshore subareas in Spring/Summer, verified for B. physalus and S. coeruleoalba; in inshore waters, mostly occupied by T. truncatus, no significant differences emerged.