Multi-Criteria Selection of Surface Units for SAR Operations at Sea Supported by AIS Data

Abstract

The authors discuss currently conducted research aimed at improving the planning and performance of search and rescue (SAR) operations at sea. The focus is on the selection of surface units in areas of high traffic density. A large number of ships in the area of distress can make the process of selection of best suited vessels longer. An analysis of features which may render a vessel unsuitable for the job, depending on the area and type of operation, has been conducted. Criteria of assessment and selection of ships have been described, preceded by an expert analysis. The selection process has been made using Multi-Criteria Decision Analysis (MCDA). The authors propose to apply officially available data from the Automatic Identification System (AIS)—a sensor for the ECDIS and other electronic chart systems—in the analysis of the availability of ships. Algorithms filtering available units have been built and applied in a simulation, using real AIS data, of one of the most common types of SAR operations. The method is proposed as an enhancement of decision support systems in maritime rescue services.