Real-Time Traffic Management Using Graph Models

Abstract

Traffic management, especially in highly populated cities with delays and congestion as part of daily life, is crucial for the successful functioning of urban settings. Since modern traffic is dynamic and complicated, traditional traffic management systems based on manual interference and static models have become less efficient. Real-time traffic management using graph theory is discussed in this chapter. Typical representations of urban road networks are graphs of roadways (edges) and intersections (nodes). Graph models enable traffic flow analysis, optimization of routing decisions, and real-time adaptation to traffic conditions. The dynamic pathfinding, event detection, and adaptive signal regulation cover some critical algorithms based on graphs: Dijkstra's and A*. It also looks at how IoT sensors, cameras, and GPS systems will integrate real-time traffic information and illustrate how these technologies have greatly enhanced the accuracy and speed of traffic management systems.