Development Of Autonomous Downscaled Model Car Using Neural Networks And Machine Learning

In this contemporary world, the number of accidents occurring has increased drastically which leads to an increase in the number of fatal deaths. This is mostly caused by the distractions that driver encounters. For example, texting and driving,less attention span of driver,etc. Due to the above reasons, autonomous cars would be a better option which takes the errors of a driver away from the equation. The proposed concept in the paper is to make an autonomous downscaled model car using a generic RC car as base. We aim to achieve the above by using image processing which is trained by using neural networks to create a model through which autonomous cars are achieved. The hardware components used in this project are Ras pberry PI 3 B microcomputer , camera module, HCSR04 ultrasonic sensor. We achieve the following features in our model, (a)Lane detection, (b)Traffic signal identification, (c)Road signs identification, (d)Obstacle detection avoidance, (e)Pedestrian Detection.