In this project we used a convolutional neural network to drive a simulated car. This is an end to end approach where the only fed to the network are 3 frames taken by 3 camras in the front of the car. The model is based on the paper published by Nvida Team. We used Udacity carsim simulator to collect data berore training the model, then we injected the model in the sumilator in autonomous mode using the drive.py file.
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DrDumbenstein/Behavioural-Clonning-Self-driving-car
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Contains Nvidia CNN model for end to end driving with the collected data from Udacity carsim and a python file to run the model.
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