SIMULATION OF SELF-DRIVING CAR USING DEEP LEARNING

SIMULATION OF SELF-DRIVING CAR USING DEEP LEARNING

The rapid development of Artificial Intelligence has revolutionized the area of autonomous vehicles by incorporating complex models and algorithms. Self-driving cars are always one of the biggest inventions in computer science and robotic intelligence.11

The neural network architecture is used to detect path in a video segment, linings of roads, locations of obstacles, and behavioural cloning is used for the model to learn from human actions in the video.11

CONCEPTS INVOLVED:

Convolutional Neural Network (convnet/CNN): Inspired by The organization of Visual Cortex, cnns take an image as Input, assigns importance to different features/objects of the Image, thereby learning about its characteristics.11

ADVANTAGES:11

·  Initially the dataset contained around 4053 frames along with the respective labels

·  The Deep Learning model was trained for 20 epochs using Mean Square Error as loss function.