[FULL PROGRAM] Traffic Density Estimation Using the Yolo V8 Method

Published: 01 January 1970
on channel: RnF Channel

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Currently, the automotive industry is developing rapidly, relying on robotics technology to make motor vehicle manufacturing faster and easier. This has led to an increase in the number of motorized vehicles at affordable prices. Another impact is that people are increasingly inclined to purchase private vehicles, leading to a rapid increase in vehicle volume and congestion on roads.
To address traffic congestion, traffic police officers are deployed to control the traffic situation by implementing traffic engineering or overriding traffic lights. However, if traffic conditions at certain times cause uncontrolled vehicle volume, other methods are needed to mitigate traffic congestion. In this final project, a camera that can monitor vehicle numbers using video images is processed using the SAD algorithm, which works by comparing the distance values of two reference frames and a specific current frame to generate a traffic condition statement. With
combining the SAD algorithm and White Pixels calculations can detect vehicles and
calculating the number of vehicles in a section of road in traffic.
Keywords: volume, override, distance, SAD algorithm, frame, White Pixels

In the development of the Automotive Industries nowaday, people begin relying on robotic technology for
vehicles manufacturing, so it makes it fast and easy for creating vehicles. This phenomenon makes the number of vehicles
is increasing but comes with affordable prices. Another impact from this phenomenon is that people are starting to buy
vehicles for personal use which cause the volume of traffic increased rapidly and traffic density is everywhere.
To overcome this situation, traffic police officers were deployed to control the traffic situation by performing
override the traffic lights. But if the traffic conditions at several certain times cause uncontrolled volume of
vehicles. In this research, we tried to place a camera that can monitor the number of vehicles by using SAD
(Sum of Absolute Differences) algorithm. It works by comparing the value between frames in order to generate a
statement of a traffic. By combining the SAD algorithm and calculating White Pixels, we can detect vehicles and
calculate the number of vehicles in a road section in the traffic

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