Abstract
Traffic congestion is a persistent problem in many metropolises worldwide. Despite the existence of traffic control systems, they are not always efficient enough to manage the ever-changing traffic density environment. The traditional approach of allocating specific times to each lane with the green light, regardless of the traffic situation, has not been very effective. In fact, it often can make the traffic congestion worse. Thus, the need for a more sophisticated system has emerged to simulate and optimize traffic control. This paper proposes the use of computer vision technology to develop a traffic control system that is based on periodic still photo feeds and compares different object detection models to find the best model for vehicle detection in our system . The system aims to enhance traffic flow by dynamically adjusting the traffic light cycles based on real-time traffic conditions.
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