Intelligent Traffic Management with Prioritized Scheduling System

A dynamic approach based on traffic density is much more feasible and efficient. Our approach lets signals handle themselves based on various real-time factors such as traffic density and emergency vehicles. The traffic analysis module uses already provided surveillance cameras to analyze the parameters by using artificial intelligence and optical character recognition through CCTV cameras. Each lane on the road is distinguished into three or more segments according to the scenario. These lines are used to determine the traffic density. Whenever the vehicles hide a part of the line in a lane, we can estimate the traffic density concerning time where the camera frames correspond to time. In this manner, we can generate real-time traffic data and implement a time sequence for the signal to clear off the traffic. The scope can be further widened by cooperating this system with Intelligent Transport Systems. The module is set so that it will be trained to get the data from the processed datasets. The advanced structure provides an embedding of a GPS module in the vehicle, which will be able to identify emergency vehicles and can also minimize the theft of vehicles. The module with the GPS sensor makes a good accurate score on the prediction. For implementing this system, we use video feed from the CCTV cameras and detect the amount of traffic density in each lane using OpenCV. Instead of fixed time updating of signals, we used a dynamic approach based on the traffic density. Whenever an emergency vehicle comes within the range of the signals, it automatically detects it and sets the green signal for the vehicle to pass swiftly and also alerts other vehicles through a mobile notification on the way of the ambulance.