Optimized Traffic Flow Detection With Yolov9 And Bytetrack

This project leverages YOLOv9 for vehicle detection and ByteTrack for real-time traffic tracking at a busy roundabout. The system processes live video input, identifying and tracking vehicles as they move through predefined entry and exit zones. By visualizing vehicle paths and counting the number of vehicles per zone, it provides valuable insights into traffic patterns and congestion points. The project integrates advanced object detection and tracking techniques to enable effective traffic flow analysis, making it a useful tool for urban planning and traffic management.

Key applications include monitoring common vehicle routes, optimizing traffic signals, and enhancing road safety. Future improvements could include estimating vehicle speeds, detecting traffic violations, and calculating traffic density. The system’s ability to analyze traffic in real-time makes it ideal for smart city initiatives focused on improving transportation efficiency and reducing congestion.

Keywords: YOLOv9, ByteTrack, vehicle detection, real-time traffic tracking, roundabout analysis, traffic flow, congestion points, urban planning, traffic management, vehicle paths, traffic signals, road safety, smart city, transportation efficiency, traffic density.