Risk-based system to control safety level of flooded passenger ships

Predicting the consequences of flooding is a key issue that may help the ship master of a large passenger ship to make rational decisions in emergency situations. To this end, the Delphi Emergency Decision Support System (Delphi EDSS) has been designed and is under implementation to continuously assess ship's state of survivability. Analyses are performed by means of a time-domain simulation program, where transient stages of flooding are investigated and stored off-line for all the potential damage scenarios. The Delphi EDSS evaluates the ship risk level including the most important aspects related to safety state while establishing the time-to-capsize which is of primary concern for the safe evacuation of the damaged ship. The methodology is based on a scientific approach, setting an overall platform for rational assessment of non-survivability risk. Determination of the global risk level and its components requires solution of a multicriterial problem, where the level of importance of each criterion contributing to determination of a global risk index is combined with fuzzified contributors to risk calculated at lower levels

Path planning and collision avoidance for autonomous surface vehicles II: a comparative study of algorithms

Artificial intelligence is an enabling technology for autonomous surface vehicles, with methods such as evolutionary algorithms, artificial potential fields, fast marching methods, and many others becoming increasingly popular for solving problems such as path planning and collision avoidance. However, there currently is no unified way to evaluate the performance of different algorithms, for example with regard to safety or risk. This paper is a step in that direction and offers a comparative study of current state-of-the art path planning and collision avoidance algorithms for autonomous surface vehicles. Across 45 selected papers, we compare important performance properties of the proposed algorithms related to the vessel and the environment it is operating in. We also analyse how safety is incorporated, and what components constitute the objective function in these algorithms. Finally, we focus on comparing advantages and limitations of the 45 analysed papers. A key finding is the need for a unified platform for evaluating and comparing the performance of algorithms under a large set of possible real-world scenarios

Automatic Control and Routing of Marine Vessels

Due to the intensive development of the global economy, many problems are constantly emerging connected to the safety of ships’ motion in the context of increasing marine traffic. These problems seem to be especially significant for the further development of marine transportation services, with the need to considerably increase their efficiency and reliability. One of the most commonly used approaches to ensuring safety and efficiency is the wide implementation of various automated systems for guidance and control, including such popular systems as marine autopilots, dynamic positioning systems, speed control systems, automatic routing installations, etc. This Special Issue focuses on various problems related to the analysis, design, modelling, and operation of the aforementioned systems. It covers such actual problems as tracking control, path following control, ship weather routing, course keeping control, control of autonomous underwater vehicles, ship collision avoidance. These problems are investigated using methods such as neural networks, sliding mode control, genetic algorithms, L2-gain approach, optimal damping concept, fuzzy logic and others. This Special Issue is intended to present and discuss significant contemporary problems in the areas of automatic control and the routing of marine vessels

Прецедентний метод визначення розпливчатих меж безпечних областей у разі спільного руху засобів пересування

The case-based assessment method of determining the vague boundaries of safety domains inuncertainty situations using the rough set approach is considered. The construction of spatialconfigurations are described, method of determining the spatio-temporal similarity function is proposed.The proposed method is not sensitive to imprecise and incomplete observations due to using the roughsets to determine dynamic safety domainsРассмотрен прецедентный метод оценивания для определения расплывчатых границ областей безопасности вситуациях неопределенности с использованием подхода на основе приближенных множеств. Описано построение пространственных конфигураций, предложен способ определения пространственно-временнойфункции сходства. Предложенный метод является не чувствительным к неточным и неполным наблюдениям вследствие использования приближенных множеств для определения динамических доменов безопасностиРозглянуто прецедентний метод оцінювання для визначення розпливчатих меж областей безпеки в ситуаціях невизначеності з використанням підходу на основі наближених множин. Описано побудову просторових конфігурацій, запропоновано спосіб визначення просторово-часової функції подібності. Запропонований метод є не чутливим до неточних і неповних спостережень внаслідок використання наближених множин для визначення динамічних доменів безпек

A Fuzzy Logic Approach for Separation Assurance and Collision Avoidance for Unmanned Aerial Systems

In the coming years, operations in low altitude airspace will vastly increase as the capabilities and applications of small Unmanned Aerial Systems (sUAS) continue to multiply. Therefore, solutions to managing sUAS in highly congested airspace must be explored. In this study, a Fuzzy Logic based approach was used to help mitigate the risk of collisions between aircraft using separation assurance and collision avoidance techniques. The system was evaluated for its effectiveness to mitigate the risk of mid-air collisions between aircraft. This system utilizes only current state information and can resolve potential conflicts without knowledge of intruder intent. The avoidance logic was verified using formal methods and shown to select the correct action in all instances. Additionally, the Fuzzy Logic Controllers were shown to always turn the vehicles in the correct direction. Numerical testing demonstrated that the avoidance system was able to prevent a mid-air collision between two sUAS in all tested cases. Simulations were also performed in a three-dimensional environment with a heterogenous fleet of sUAS performing a variety of realistic missions. Simulations showed that the system was 99.98 effective at preventing mid-air collisions when separation assurance was disabled (unmitigated case) and 100 effective when enabled (mitigated case)