Methods of cluster analysis of road networks for bottleneck detection and traffic optimization

The article studies the spatial organization of road networks using modern methods of network analysis and clustering. The goal of the work is to identify stable functional structures of the transport network and analyze their changes under the influence of different levels of congestion. The application of modern algorithms of network analysis and clustering on street and road networks of large cities is proposed. Special attention is paid to the analysis of cluster dynamics in conditions of different traffic intensity. Experiments are carried out on real data of traffic flows and include estimation of changes in topological characteristics of the network under varying levels of congestion. The results show that the proposed approaches allow to effectively identify stable functional areas of the network and capture their transformations under changing traffic conditions. Regularities of flow redistribution during peak load periods and formation of potential bottlenecks were revealed. The spatial patterns of clusters show correlation with the nature of network congestion and the topography of the city. The practical significance of the work lies in the possibility of using the proposed methodology for decision support in the field of transportation planning and traffic flow management. The results obtained can be used to optimize routing, improve the sustainability of transport infrastructure and prevent congestion on key sections of the network. The study highlights the value of applying network analysis and clustering methods to study the dynamics of transport systems and form strategies for effective traffic management in the conditions of a modern city.