Abstract
One of the ways to prevent accidents at sea is to detect risks caused by humans and to counteract them. These tasks can be executed through an analysis of ship maneuvers and the identification of behavior considered to be potentially dangerous, e.g., based on data obtained online from the automatic identification system (AIS). As a result, additional measures or actions can be taken, e.g., passing at a distance greater than previously planned. The detection of risks at sea requires a prior definition of behavior patterns and the criteria assigned to them. Each pattern represents a specific navigator’s safety profile. The criteria assigned to each pattern for the identification of the navigator’s safety profile were determined from previously recorded AIS data. Due to a large amount of data and their complex relationships, these authors have proposed to use data mining tools. This work continues previous research on this subject. The conducted analysis covered data recorded in simulation tests done by navigators. Typical ship encounter situations were included. Based on additional simulation data, the patterns of behavior were verified for the determination of a navigator’s safety profile. An example of using the presented method is given.
Highlights
All modes of transport should assure safe and cost-effective transport of cargo and passengers
An important direction of measures aimed at raising the safety of cargo and passenger transport is reducing human errors, the major cause of accidents
This refers to sea transport, where the human error is claimed to be the main cause or one of the causes of nearly 80% of accidents at sea
Summary
An important direction of measures aimed at raising the safety of cargo and passenger transport is reducing human errors, the major cause of accidents. Like in other modes of transport, increasingly more attention is paid to the identification of the psychophysical characteristics of navigators The impact of these characteristics on navigational safety is subject to scientific investigation, because these characteristics are of particular importance in difficult and complex situations and when the navigator’s workload is excessive. Attempts are made to increase the situational awareness by obtaining and presenting information that is essential for decision making This function is performed by various indicators of the present situation, including indicators of the risk of collision, e.g., based on the current value of the closest point of approach (CPA) and time to reaching CPA. The second one—identification of mental and physical characteristics of navigators and their impact on collision risk— known before, has been gaining importance Such analyses are possible owing to modern technologies, information technology in particular
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