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Deep drive
Bharath Chava
CONTENTS
Introduction & history
Levels of Autonomy
Hardware
Software
Teaching car to drive
Various approaches
Future work & Conclusion
An autonomous car also known as a driverless car, self-driving
car, robotic car and unmanned ground vehicle is a vehicle that
is capable of sensing its environment and navigating without
human input
 The DARPA challenge is the kick start of modern
autonomous car
List of companies that are working on autonomous cars
 NVidia
 Volkswagen
 Baidu
 Uber
 Volvo
 Fiat Chiseler
Motors
 Apple
 Intel
 BMW
 Audi
 Google
 Nutonomy
 Bosch
 Waymo
 Aptiv
 Tesla
 Ford
 Five Ai
 Toyota
 Nissan
 General
Motors
 Daimler
(Trucks)
 Honda
 22. Hyundai
 Psa Group
 Faraday Future
 Le Eco
 Benz
 The University
Of Waterloo
 Aurora
 Argo Ai
 Cisco
 Clarion
 Delphi
 Green Hills
Software
 Keolis
 Lyft
 Navya
 Qualcomm
 Renesas
Electronics
 Transdev'
 Torc
 Waymo
LEVELS IN AUTONOMY
Hardware required
• LiDAR (Light Imaging, Detection, And Ranging)
• High Definition video camera
• GPS (Global Positioning System)
• Ultrasonic sensors
• Odometry sensors
• Radars
• GPU (Graphics processing unit)
• CPU (Central processing unit
Autonomous car Working (Deep learning)
Autonomous car Working (Deep learning)
High Definition camera with image recognition
EVOLUTIONARY AUTONOMOUS CAR
Google level 5
autonomous car
LiDAR
HIGH LATENCY
Autonomous car Working (Deep learning)
Software required
• UI (User interface)
• AI (Artificial intelligence)
• Deep learning
• Big Data
Tesla Model S.
Infotainment system
Autonomous car Working (Deep learning)
Deep learning: Deep learning (also known as deep structured learning or hierarchical learning) is part
of a broader family of machine learning methods based on learning data representations, as opposed to
task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised
• Supervised
• Unsupervised
• Reinforcement
Artificial neural networks key to this machine learning system
Simple artificial neural network
High level convolutional neural network (cnn)
Autonomous car Working (Deep learning)
Stages of teaching a car how to drive
1. Training Phase
2. Validation Phase
3. Test Phase
4. Continuum Phase
All this is carried out by using simultaneous localization and mapping
(SLAM)
Autonomous car Working (Deep learning)
Autonomous car Working (Deep learning)
Autonomous car Working (Deep learning)
Issues with continuum phase
Autonomous car Working (Deep learning)
Various Approaches
SWARM INTELLIGENCE V/S CONTROLLED TRAINING
Tesla is leading the autonomous pack with the technology enabled called swarm intelligence. Every
car that is sold after 2014 quarter 3 is enabled with Auto pilot system. An advanced driving
assistance system that hasn’t seen only any car before. So, the whole Tesla fleet operates as a
network. When one car learns something, they all learn it. when it comes to the autopilot software,
each driver using the autopilot system essentially becomes an “expert trainer for how the autopilot
works.
EVOLUTIONARY V/S REVOLUTIONARY
LIDAR V/S IMAGE RECOGNITION CAMERAS
As we have seen in the previous chapter. Lidar and HD cameras are used in making the
AI car possible. As the lidars are extremely costly. Which restricts in making the mass
market car in future kind of impossible. To overcome this tesla and other startup
16
companies are just using HD cameras with image recognition. These help in decreasing
the costs of car by a big margin. And make the Driver less car possible.
IS THE FUTURE
MODULAR TRANSPORT
THANK YOUQUERIES
?

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Autonomous car Working (Deep learning)

  • 2. CONTENTS Introduction & history Levels of Autonomy Hardware Software Teaching car to drive Various approaches Future work & Conclusion
  • 3. An autonomous car also known as a driverless car, self-driving car, robotic car and unmanned ground vehicle is a vehicle that is capable of sensing its environment and navigating without human input  The DARPA challenge is the kick start of modern autonomous car
  • 4. List of companies that are working on autonomous cars  NVidia  Volkswagen  Baidu  Uber  Volvo  Fiat Chiseler Motors  Apple  Intel  BMW  Audi  Google  Nutonomy  Bosch  Waymo  Aptiv  Tesla  Ford  Five Ai  Toyota  Nissan  General Motors  Daimler (Trucks)  Honda  22. Hyundai  Psa Group  Faraday Future  Le Eco  Benz  The University Of Waterloo  Aurora  Argo Ai  Cisco  Clarion  Delphi  Green Hills Software  Keolis  Lyft  Navya  Qualcomm  Renesas Electronics  Transdev'  Torc  Waymo
  • 6. Hardware required • LiDAR (Light Imaging, Detection, And Ranging) • High Definition video camera • GPS (Global Positioning System) • Ultrasonic sensors • Odometry sensors • Radars • GPU (Graphics processing unit) • CPU (Central processing unit
  • 9. High Definition camera with image recognition
  • 14. Software required • UI (User interface) • AI (Artificial intelligence) • Deep learning • Big Data
  • 17. Deep learning: Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised • Supervised • Unsupervised • Reinforcement Artificial neural networks key to this machine learning system
  • 19. High level convolutional neural network (cnn)
  • 21. Stages of teaching a car how to drive 1. Training Phase 2. Validation Phase 3. Test Phase 4. Continuum Phase All this is carried out by using simultaneous localization and mapping (SLAM)
  • 28. SWARM INTELLIGENCE V/S CONTROLLED TRAINING Tesla is leading the autonomous pack with the technology enabled called swarm intelligence. Every car that is sold after 2014 quarter 3 is enabled with Auto pilot system. An advanced driving assistance system that hasn’t seen only any car before. So, the whole Tesla fleet operates as a network. When one car learns something, they all learn it. when it comes to the autopilot software, each driver using the autopilot system essentially becomes an “expert trainer for how the autopilot works.
  • 30. LIDAR V/S IMAGE RECOGNITION CAMERAS As we have seen in the previous chapter. Lidar and HD cameras are used in making the AI car possible. As the lidars are extremely costly. Which restricts in making the mass market car in future kind of impossible. To overcome this tesla and other startup 16 companies are just using HD cameras with image recognition. These help in decreasing the costs of car by a big margin. And make the Driver less car possible.