Analysis of Traffic Management System using YOLOv8

The identification of traffic violations plays a pivotal role in contemporary efforts to manage traffic effectively and enhance safety on the roads. Traffic violation detection holds immense significance due to its profound influence on road safety, traffic control, and the overall welfare of communities. It plays a pivotal role in molding cities that are both sustainable and adaptable, ultimately guaranteeing an enhanced quality of life for both their inhabitants and guests. The proposed model elevates traffic enforcement and surveillance through its capability to ascertain the volume of vehicles traversing a road simultaneously by affixing a label denoting the vehicle’s count and its category. Furthermore, it discerns instances of vehicles breaching red traffic signals, meticulously logging the vehicle’s count number, thereby streamlining the process of accessing comprehensive vehicle information. Our model detects the multiple vehicles at a time which violates the rules and yields 97% classification accuracy.