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Applied Deep Learning and Computer Vision for Self-Driving Cars

You're reading from   Applied Deep Learning and Computer Vision for Self-Driving Cars Build autonomous vehicles using deep neural networks and behavior-cloning techniques

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781838646301
Length 332 pages
Edition 1st Edition
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Authors (3):
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Dr. S. Senthamilarasu Dr. S. Senthamilarasu
Author Profile Icon Dr. S. Senthamilarasu
Dr. S. Senthamilarasu
Balu Nair Balu Nair
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Balu Nair
Sumit Ranjan Sumit Ranjan
Author Profile Icon Sumit Ranjan
Sumit Ranjan
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Toc

Table of Contents (18) Chapters Close

Preface 1. Section 1: Deep Learning Foundation and SDC Basics
2. The Foundation of Self-Driving Cars FREE CHAPTER 3. Dive Deep into Deep Neural Networks 4. Implementing a Deep Learning Model Using Keras 5. Section 2: Deep Learning and Computer Vision Techniques for SDC
6. Computer Vision for Self-Driving Cars 7. Finding Road Markings Using OpenCV 8. Improving the Image Classifier with CNN 9. Road Sign Detection Using Deep Learning 10. Section 3: Semantic Segmentation for Self-Driving Cars
11. The Principles and Foundations of Semantic Segmentation 12. Implementing Semantic Segmentation 13. Section 4: Advanced Implementations
14. Behavioral Cloning Using Deep Learning 15. Vehicle Detection Using OpenCV and Deep Learning 16. Next Steps 17. Other Books You May Enjoy

Benefits of SDCs

Indeed, some people may be afraid of autonomous driving, but it is hard to deny its benefits. Let's explore a few of the benefits of autonomous vehicles:

  • Greater safety on roads: Government data identifies that a driver's error is the cause of 94% of crashes (https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812115). Higher levels of autonomy can reduce accidents by eliminating driver errors. The most significant outcome of autonomous driving could be to reduce the devastation caused by unsafe driving, and in particular, driving under the influence of drugs or alcohol. Furthermore, it could reduce the heightened risks for unbelted occupants of vehicles, vehicles traveling at higher speeds, and distractions that affect human drivers. SDCs will address these issues and increase safety, which we will see in more detail in the Levels of autonomy section of this chapter.
  • Greater independence for those with mobility problems: Full automation generally offers us more personal freedom. People with special needs, particularly those with mobility limitations, will be more self-reliant. People with limited vision who may be unable to drive themselves will be able to access the freedom afforded by motorized transport. These vehicles can also play an essential role in enhancing the independence of senior citizens. Furthermore, mobility will also become more affordable for people who cannot afford it as ride-sharing will reduce personal transportation costs.
  • Reduced congestion: Using SDCs could address several causes of traffic congestion. Fewer accidents will mean fewer backups on the highway. More efficient, safer distances between vehicles and a reduction in the number of stop-and-go waves will reduce the overall congestion on the road.
  • Reduced environmental impact: Most autonomous vehicles are designed to be fully electric, which is why the autonomous vehicle has the potential to reduce fuel consumption and carbon emissions, which will save fuel and reduce greenhouse gas emissions from unnecessary engine idling.

There are, however, potential disadvantages to SDCs: 

  • The loss of vehicle-driving jobs in the transport industry as a direct impact of the widespread adoption of automated vehicles. 
  • Loss of privacy due to the location and position of an SDC being integrated into an interface. If it can be accessed by other people, then it can be misused for any crime.
  • A risk of automotive hacking, particularly when vehicles communicate with each other.
  • The risk of terrorist attacks also exists; there is a real possibility of SDCs, charged with explosives, being used as remote car bombs.

Despite these disadvantages, automobile companies, along with governments, need to come up with solutions to the aforementioned issues before we can have fully automated cars on the roads.

You have been reading a chapter from
Applied Deep Learning and Computer Vision for Self-Driving Cars
Published in: Aug 2020
Publisher: Packt
ISBN-13: 9781838646301
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