In this project I develop a convolutional neural network in Keras to achieve autonomous driving of a car within a simulator provided in the Udacity environment.
A simulation shows the car completing a lap on the track succesfully.
The deliverables for the project are:
- model.py containing the script to create and train the model
- drive.py for driving the car in autonomous mode
- model.h5 containing a trained convolution neural network
- run1.mp4 containing a video demontration of my simulation
- A writeup summarizing the results
Check out the writeup for a detailed discussion on steps, challenges and results encountered in this project.
The goals / steps of this project are the following:
- Use the simulator to collect data of good driving behavior
- Design, train and validate a model that predicts a steering angle from image data
- Use the model to drive the vehicle autonomously around the first track in the simulator. The vehicle should remain on the road for an entire loop around the track.
- Summarize the results with a written report
This lab requires:
The lab enviroment can be created with CarND Term1 Starter Kit. Click here for the details.
The following resources can be found in this github repository:
- drive.py
- video.py
- writeup_template.md
The simulator can be downloaded from the classroom. In the classroom, we have also provided sample data that you can optionally use to help train your model.