European Journal of Intelligent Transportation Systems

A SCIENTIFIC-METHODOLOGICAL ANALYSIS OF ENSURING THE COMPETITIVENESS AND EFFICIENCY OF SHIPPING CONTAINER LINES ON SEA ROUTES

Giorgi Purtskhvanidze — 2025-04-25

The research aims to develop a methodology to justify the feasibility of creating container shipping lines in Georgia under conditions of growing external negative influences.

To achieve this goal, the following objectives were set and solved in the work: an analysis of the factors that influence the competitive positions of container lines in the Southern Sea Route transport market was carried out; the main scientific approaches to the creation of national container lines were discussed; a scientific and methodological approach to the development of a Georgian transport container line has been proposed.

THE USE OF ARTIFICIAL INTELLIGENCE FOR AUTOMATING THE MARINE CREW MANAGEMENT

Dmytro Afanasiev — 2025-07-08

This study presents a comprehensive analysis of the implementation of artificial intelligence (AI) to optimize crew management processes in the maritime industry. The article outlines the inefficiencies of traditional HR practices in shipping companies, including delays in documentation verification, manual classification, and administrative overload. A novel model of an intelligent automation system is introduced, integrating computer vision, machine learning algorithms, and API connections to international registers. The system automates extraction, classification, and real-time validation of seafarers’ documentation. Key improvements include a 70–90% increase in operational efficiency, with error rates reduced by over 90% and verification time shortened from hours to minutes. The paper also describes the patented modular system architecture, which provides multi-level verification and enables secure, scalable document workflows. Its compatibility with cloud infrastructures ensures integration flexibility for international maritime companies. The system processes over 10,000 documents monthly and delivers classification within seconds. The study demonstrates how AI technologies enhance accuracy, transparency, and accountability in HR workflows. By automating routine tasks, it reduces recruiter workload and allows for strategic human decision-making. The solution supports compliance with international standards such as STCW and IMO regulations. Findings suggest this approach enables full-cycle digital crew management, forming the foundation of smart recruiting ecosystems in maritime logistics. These ecosystems use AI-driven tools to solve challenges of operational continuity, regulatory compliance, and global workforce mobility in a digitized shipping environment. The conclusions reinforce the transformative potential of AI in modernizing crew operations, aligning maritime HRM with trends in digital innovation, automation, and secure personnel administration across the global seafaring domain. The article recommends further investigation into hybrid intelligence models that combine algorithmic precision with expert oversight, ensuring both efficiency and contextual accuracy in maritime HR decision-making processes.

ENSURING CONSISTENT TRAFFIC MANAGEMENT THROUGH INFORMATION SUPPORT ON ROAD APPROACH SECTIONS TO MAJOR CITIES

Oksana Hulchak — 2025-02-09

An increase in the number of vehicles results in higher traffic flow intensity and density, which affects the emergence of an inefficient, congested and potentially dangerous traffic regime. Under such conditions, the management of individual vehicles does not provide effective control over the functioning of the transport system as a whole. In addition, the modern needs to adapt to growing demand through the implementation of intelligent control subsystems capable of monitoring, analyzing, and performing real-time traffic control.
The growth in the intensity and density of traffic flows affects the likelihood of traffic accidents and congestion and, as a result, increases travel time. Therefore, there is a need to create a specialized control subsystem capable of managing traffic flows, analyzing them, assessing the current state of the transport system, and predicting further developments. To create such a subsystem, it is necessary to analyze and study traffic flows in more detail, create a simulation model to understand the problem and the algorithm of actions to solve it.
The article substantiates the necessity of creating such a subsystem for the sections of highway approaches to large and major cities. The stages of building a traffic simulation model are presented, the principles of the control process of algorithmization are considered, as well as the use of PTV VISSIM software for real-time simulation.