Published: June 20, 2024

We present a real-time system for vehicle detection and classification in road intersections, incorporating image processing techniques. This estimates the traffic flow at specific point, as it is capable of recognizing trajectories different vehicles an intersection, inferring whether they leave or enter city. It designed to be integrated into high-fidelity digital twin, aiding estimating environmental pollutants. Since Computational Fluid Dynamics (CFD) use estimators like average aggregate measurements, we more accurate methods estimate pollution. The implications our study are significant urban planning management. allows immediate decisions informs long-term infrastructure by providing deep understanding intersection dynamics. Our research offers comprehensive perspective on analysis, introducing data-driven management strategies efficient mobility. code developed this purpose can found \https://github.com/capo-urjc/TrackingSORT

Language: Английский