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Automated Driving Car using RPI Board and CNN Algorithm

Mr. Prashant Holla, Ms. Suveda N, Mr. Sharan C, Mr. Nithyanand S N, Ms. Apsara M B


Self-driving vehicles will provide more than a luxury in this era. In this study, we are implementing an upcoming technology in Machine learning and neural networks called Autonomous cars or self-driven cars. It provides relief to humans from travelling stress and helps reduce traffic congestion and accidents.This study produces a successful model that navigates through the traffic and tackles all the obstacles placed in its path. This self drive car is implemented using Machine Learning algorithms and Convolutional neural networks in a way that provides complete automation to the driver. This car performs the following functions: self-parks, avoids traffic congestion, follows lane markings, avoids obstacles and detects vehicles and moves accordingly based on its distance from other vehicles.Previously, designs were made in such a way that all these functions were implemented in separate vehicles. But this car design integrates all these functions in a single model which increases its effectiveness, efficiency and reduces the cost of building it separately.

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