Problem Statement: In contrast with the past, we are experiencing a lot of traffic in our metropolitan cities. At that point it becomes very difficult for us to wait in heavy traffic. Our team has come up with a solution which can resolve this problem.
Abstract: As the problem of urban traffic congestion spreads, there is a vital need for the introduction of advanced technology and equipment to improve the state-of-the-art of traffic control. Traffic problems nowadays are increasing because of the growing number of vehicles and the limited resources provided by current infrastructures. We propose a system for controlling the traffic light by image processing.
For example an important person can be stuck in heavy traffic where he has to reach in time for an important meeting. Or consider an example of ambulance, where in if traffic jam is high, one cannot make way for the ambulance to pass, in such cases it can be a question of someone’s life. For such situations an intelligent traffic control system is necessary.
Our idea is to modulate the Green light and Red light in our traffic signals according to the heavy traffic flows.
METHODOLOGY: Continuous video monitoring of vehicles is done at the traffic signals through which Image processing will be done to calculate the density if the traffic using the Pillow (python image library) and OpenCV (computer vision library). Once the densities of all the lanes at a junction is calculated, comparison of densities is done and the final output i.e. time for Green light or Red light is calculated. Hardware/Software components required: USB based web camera , Python software comprising of specialized modules that perform specific tasks.
ADVANTAGES :
1)Wastage of time by lighting green signal even when road is empty can be avoided.
2)More convenient than timers and sensors.
3)Low cost.
Final Result:
