This paper provides a close investigation into the landscape of both cyber threats and actual incidents in the maritime sector, identifying the cyber trends and challenges as they relate to safe navigation and marine shipping. As an important subset of cyber threats that impact many maritime systems, the vulnerabilities of satellite navigation systems, in particular the Global Positioning System (GPS), receive special attention. For this article, a systematic literature review was conducted, complemented by the research and analysis of a specific spoofing event. Analyzing available resources, we might summarize that a shift in mind-set is essential to direct more attention and resources toward cybersecurity as well as the necessity for manufacturers to improve the cybersecurity of their products, as shipping systems currently remain vulnerable to cybercriminals. There is a need for multiple positioning, navigation, and timing (PNT) systems onboard maritime vessels to complement GPS-only navigation. The use of multiple satellite navigation constellations, public as well as private, in combination with the terrestrial components of an enhanced LOng-RAnge Navigation (eLoran) system and ports’ laser-based aid system for berthing and docking should provide the shipping industry with the direly needed increased protection from cyber-attackers for the foreseeable future.

The application of fuzzy logic is an effective approach to a variety of circumstances, including solutions to maritime anti-collision problems. The article presents an upgrade of the radar navigation system, in particular, its collision avoidance planning tool, using a decision model that combines dynamic parameters into one decision—the collision avoidance course. In this paper, a multi-parametric decision model based on fuzzy logic is proposed. The model calculates course alteration in a collision avoidance situation. First, the model collects input data of the target vessel and assesses the collision risk. Using time delay, four parameters are calculated for further processing as input variables for a fuzzy inference system. Then, the fuzzy logic method is used to calculate the course alteration, which considers the vessel’s safety domain and International Regulations for Preventing Collisions at Sea (COLREGs). The special feature of the decision model is its tuning with the results of the database of correct solutions obtained with the manual radar plotting method. The validation was carried out with six selected cases simulating encounters with the target vessel in the open sea from different angles and at any visibility. The results of the case studies have shown that the decision model computes well in situations where the own vessel is in a give-way position. In addition, the model provides good results in situations when the target vessel violates COLREG rules. The collision avoidance planning tool can be automated and serve as a basis for further implementation of a model that considers the manoeuvrability of the vessels, weather conditions, and multi-vessel encounter situations.

The increasing traffic and complexity of navigation at sea require advanced decision support systems to ensure greater safety. In this study, we propose a novel decision support system that employs fuzzy logic to improve situational awareness and to assist navigators in collision avoidance during multi-vessel encounters. The system is based on the integration of the rules of the Convention on International Regulations for Preventing Collisions at Sea (COLREGs) and artificial intelligence techniques. The proposed decision model consists of two main modules to calculate the initial encounter conditions for the target vessels, evaluate the collision risk and navigation situation based on COLREG rules, sort the target vessels, and determine the most dangerous vessel. Fuzzy logic is used to calculate the collision avoidance maneuver for the selected ship, considering the closest point of approach, relative bearing, and the ship’s own speed. Simulation tests demonstrate the effectiveness of the fuzzy-based decision model in scenarios with two ships. However, in complex situations with multiple ships, the performance of the model is affected by possible conflicts between evasive maneuvers. This highlights the need for a cooperative collision avoidance algorithm for all vessels in high traffic areas.

The purpose of this study is to analyse data from the marine pilots’ bio-sensor readings to determine how experience affects their biometrical response during the port approach. The experiences play a significant role in the participant’s decision-making process and correlate with the repetitions. Through the repetitions of the experimental task, the participants gain experience, which correlates with the biometrical response, e.g., heart rate, electrodermal activity, etc. After exposing the two experience-distinct groups of participants to the same simulated port-approaching task, their collected biometric data is analysed and discussed. The results show that biometrical readings of the less experienced participants typically vary compared to that of the experienced participants, who take the simulated task more seriously. The study also yields insight into the workload process, involving disturbing factors during the task.

Perhaps the most problematic issue regarding navigation safety management is the unknown, or unknowable, is the navigator’s decision made in the face of a dangerous situation. This applies particularly to collision-avoidance. The aim of the article is to identify factors that influence the moment of decision during a collision-avoidance manoeuvre and to define theoretical distributions that can be used during modelling of a navigator’s behaviour. The applicable research was divided into two stages. In the first, the distance between ships and the time to closest point of approach (TCPA) were analysed. In the second, the influence of the size of the target ships and relative speed were investigated. The advantage of the paper is its use of actual observations collected in real situations. The proposed approach allows for a better understanding of the navigator’s actual decision-making, which will be instructive in measures taken to improve navigational safety.

Sediment resuspension has, among other things, negative consequences for marine flora and fauna. A solution to this problem could lie in alternative ship manoeuvres, automated mooring systems and bottom protection techniques. The paper deals with the methodology for determining sediment resuspen-sion, which consists of real-time kinematic measurements and in-situ meas-urements with (PNS-RTK) sensors. Real-time data from the manoeuvring vessel is used to determine the critical vessel rate per minute (RPM) or pro-peller jet velocity on the seabed and to identify the most common critical ves-sel manoeuvres on approach to port and departure. The Full Mission Bridge Simulator (FMBS) can be an excellent simulation tool for the analysis of real-time and on-site measurements, which is proposed for further research.