Incidences of Fatal Pedestrial Collisions and Vehicle Speed Control with Tsod Algorithm

Authors

  • M. Natrajan, S. Rajapriya, M. Suvalakshmi, J. Suwethasree

Abstract

Many Applications use Agent-based approach and reinforcement algorithms in machine learning, but it is not much suitable for current advancement in traffic systems. Here we use Artificial Intelligence (AI) the technique to train machines to act like human. This paper proposes automatic speed control for fatal pedestrian areas and restricted zones through traffic sign recognition. It undergoes four main phases. In the first phase of image processing by the use of camera the external environment is captured and converted into frames. The frames forms the neural network through deep learning Traffic Signs Object Detection(TSOD) algorithm, on phase two the image are analysis and compared for accurate outcome by using Open CV. Proper indication is displayed through LCD display and if speed is not reduced accordingly automatic speed reduction takes place with the help of Pulse Width Modulation (PWM) algorithm. TSOD algorithm is more accurate and efficient for image processing. The main advantage is automatic reduction of vehicle speed and it reduces Ignorance of traffic rules and collisions.

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Published

2020-05-18

Issue

Section

Articles