How to Build Self-Driving Cars From Scratch, Part 2: A Step-by-Step Guide to Creating Autonomous Vehicles With Python
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About this ebook
This is part 2 of my 3-part training guide on how to build self-driving cars from scratch. This guide is bundled with a repository containing simulations, python scripts, graphics, and other useful assets. In this step-by-step guide, I teach you how to make an app that you can use to create a simulation where cars learn how to d
Bolakale Aremu
My educational background is in software development. I work with a few colleagues who are software developers and system engineers. I spent over 17 years as a software developer, and I've done a bunch of other things too. I've been involved in SDLC/process, data science, operating system security and architecture, and many more. My most recent project is serverless computing where I simplify the building and running of distributed systems. I always use a practical approach in my projects and courses. Cheers, Bolakale Aremu (Self-publisher and CEO).
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Book preview
How to Build Self-Driving Cars From Scratch, Part 2 - Bolakale Aremu
How to Build
Self-Driving Cars
From Scratch
Part 2
Neural Network & Genetic Algorithm
A Step-by-Step Guide to
Creating Autonomous Vehicles With Python
Simulations, scripts, graphics
and other assets included
By
Bolakale Aremu
How to Build Self-Driving Cars From Scratch
A Step-by-Step Guide to Creating Autonomous Vehicles with Python
Copyright © AB Publisher LLC
All rights reserved
ISBN:: 979-8-3302-3182-9
Published in the United States
Limit of Liability/Disclaimer of Warranty
This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. All information given in this book is based on the author’s own research and does not constitute technical, financial or professional advice. The author and publisher have attempted to trace the copyright holders of all material reproduced in this publication, and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint.
Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publisher.
Table of Contents
0. Introduction
0.1. Getting Started
0.2. The Target Audience
0.3. How to Use This Guide
0.4. Who am I?
0.5. The Tool You Need
1. First Track
2. Neural Network
3. Car Sensors
4. Checkpoints
5. Second Track
6. The Genetic Algorithm
7. Fitness Function
8. Neural Network is Separated from Genetic Algorithm
9. Selection
10. Crossover
11. Mutation
12. Tweaking the System
13. How to Download Simulations, Python Scripts, Graphics & Other Assets
13.1. Download link
13.2. How to Get Further Help & Support
13.3. Overview of Part 3
0. Introduction
This is part 2 of my 3-part training guide on how to build self-driving cars from scratch. This guide is bundled with a repository containing simulations, python scripts, graphics, and other useful assets. In this step-by-step guide, I teach you how to make an app that you can use to create a simulation where cars learn how to drive autonomously over racing tracks. Here’s a break down of the contents of this guide.
Part 1: Car mechanics. In this part, you’ll learn how to draw the car and control it with the keyboard. You will use a multimedia library for Python called Pyglet. (https://pyglet.org/). This is the only library you will use in this guide. This is a cross-platform windowing and multimedia library for Python. It’s a powerful yet easy-to-use Python library for building games and other visually rich applications on Windows, macOS, and Linux.
Part 2: Neural network and genetic algorithm. You’ll learn how to create the AI where you combine a neural network and genetic algorithm. You’ll learn how to add sensors to the car and get output from them. To prevent the untrained network from car crashes, a genetic algorithm will be used to train the cars. This will help the cars to drive simple tracks.
Part 3: Challenges. You’ll add some challenges to the system. Tracks get more complicated and will take advantage from the previous track training by storing and retrieving the car brains.
By the end of this training, you will have created self-driving cars that are capable of driving on unknown tracks by understanding how to