Modelling urban infrastructure using graph algorithms

This article explores methods for modeling urban infrastructure using graph algorithms. The primary focus is on building a graph-based model of the road network from Open Street Map (OSM) data, which includes intersections, roads, and their characteristics such as length and direction. Shortest path algorithms, including Dijkstra and A*, are implemented to optimize traffic flows. A comparative analysis of the algorithms' performance is conducted on the real-world road network of Moscow. Python, OSMnx, NetworkX, and matplotlib were utilized for data processing and visualization. The study results demonstrate the efficiency of graph algorithms in minimizing travel time and route planning, making this approach promising for transport planning and urban environment optimization.