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  • Author: Rafał Szłapczyński x
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Open access

Rafał Szłapczyński and Roman Śmierzchalski

Supporting navigator's decisions by visualizing ship collision risk

The paper introduces a visualization method that enables the navigator to estimate an encounter situation and choose collision avoidance manoeuvre, if necessary. It is based on the Collision Threat Parameters Area method and offers new features: fuzzy sectors of forbidden speed and course values, the possibility to use any given ship domain and a new formula of collision risk assessment. All these elements result in a method, which enables the navigator to differentiate between varying levels of risk and to point out the direct threats. The method is fast enough to be applied in the real-time decision support system.

Open access

Marcin Życzkowski and Rafał Szłapczyński

Abstract

The paper presents a multi-objective deterministic method of weather routing for sailing vessels. Depending on a particular purpose of sailboat weather routing, the presented method makes it possible to customize the criteria and constraints so as to fit a particular user’s needs. Apart from a typical shortest time criterion, safety and comfort can also be taken into account. Additionally, the method supports dynamic weather data: in its present version short-term, mid-term and long-term term weather forecasts are used during optimization process. In the paper the multi-objective optimization problem is first defined and analysed. Following this, the proposed method solving this problem is described in detail. The method has been implemented as an online SailAssistance application. Some representative examples solutions are presented, emphasizing the effects of applying different criteria or different values of customized parameters.

Open access

Rafał Szłapczyński

ABSTRACT

In the previous paper the author presented the evolutionary ship trajectory planning method designed to support Traffic Separation Schemes (TSS). This time the extensions of this method are described which allow to combine evolutionary trajectory planning with speed reduction manoeuvres. On TSS regions with higher than usual density of traffic and smaller distances between ships, the course alterations alone are not always sufficient or effective means of collision avoidance. Therefore they must be supplemented by speed reduction manoeuvres to a larger extent than on open waters. The paper includes a brief description of the optimisation problem, descriptions of the new elements of the method (fitness function, algorithms and the evolutionary cycle) and the examples of how the extended method successfully solves the problems unsolvable without applying speed reduction.

Open access

Marcin Życzkowski, Przemysław Krata and Rafał Szłapczyński

Abstract

The article presents a method to determine the route of a sailing vessel with the aid of deterministic algorithms. The method assumes that the area in which the route is to be determined is limited and the basic input data comprise the wind vector and the speed characteristic of the vessel. Compared to previous works of the authors, the present article additionally takes into account the effect of sea waves with the resultant resistance increase on the vessel speed. This approach brings the proposed model closer to real behaviour of a sailing vessel. The result returned by the method is the sailing route, optimised based on the multi-criteria objective function. Along with the time criterion, this function also takes into account comfort of voyage and the number of performed turns. The developed method has been implemented as simulation application SaillingAssistance and experimentally verified.

Open access

Rafał Szłapczynśki and Joanna Szłapczyńska

Open access

Rafał Szłapczyński and Tacjana Niksa-Rynkiewicz

Abstract

Safety analysis of navigation over a given area may cover application of various risk measures for ship collisions. One of them is percentage of the so called near-miss situations (potential collision situations). In this article a method of automatic detection of such situations based on the data from Automatic Identification System (AIS), is proposed. The method utilizes input parameters such as: collision risk measure based on ship’s domain concept, relative speed between ships as well as their course difference. For classification of ships encounters, there is used a neuro-fuzzy network which estimates a degree of collision hazard on the basis of a set of rules. The worked out method makes it possibile to apply an arbitrary ship’s domain as well as to learn the classifier on the basis of opinions of experts interpreting the data from the AIS.