This article presents a comprehensive analysis of modern approaches to transport system management, based on intelligent technologies, digitalization, and mathematical modeling methods. Key develop-ment areas are examined, particularly the implementation of intelligent transport systems (ITS), which automate management processes, increase throughput, and ensure traffic safety. An important aspect is the continuous monitoring of the technical condition of transport infrastructure assets, achieved through the use of sensors, IoT solutions, and predictive analytics, which enable the prediction of po-tential failures and minimize the risk of accidents.
Particular attention is paid to the development of digital logistics platforms and transport corridors, which become the basis for integrating various modes of transport and supply chain participants. Methods for improving the efficiency and safety of transport processes are analyzed, including the use of probability theory for risk assessment, fuzzy logic for decision-making under uncertainty, and mod-ern machine learning algorithms for route optimization and flow management.