Smart Traffic Management System using Background Subtraction

The development of an intelligent and adaptive traffic signal management system lies in the challenges associated with urban traffic congestion and the need for efficient emergency vehicle passage. Urbanization and population growth have led to increased vehicular traffic, resulting in congestion during peak hours. An automated traffic monitoring system at the junctions with the count of the vehicles can help to achieve a dynamic allocation of timing for vehicles for achieving a smooth and congestion - free traffic movement. The proposed system can help in adjusting traffic signal timings based on the density of vehicles in each lane while prioritizing emergency vehicles. A common approach for vehicle detection is background subtraction. Background subtraction is a popular computer vision technique used to extract the foreground objects from a given video or image sequence. The main goal of this process is to differentiate the moving objects from a relatively static background. Detecting the approach of emergency vehicles can be done using RFID reader and tags. The primary goal of this system is to reduce traffic congestion by allocating time slots for each lane based on their current density, thereby optimizing overall traffic flow. Additionally, the system is designed to prioritize the passage of emergency vehicles, like ambulances, through intelligent detection mechanisms, ensuring swift and unobstructed access to critical locations.