The document discusses the rise of autonomous vehicles (AVs), predicting that 10 million will be on the roads by 2022 and that they will generate a $7 trillion annual revenue stream by 2050 while potentially reducing vehicle crashes by 90%. It details the technology behind AVs, including sensors like lidar and radar, and the complex algorithms that enable them to navigate safely. The document also highlights legal and societal implications, including liability issues and potential job losses, raising questions about the future of driving and regulation.

1. “Self-driving cars are the natural extension of active safety and obviously
something we should do”
-Elon Musk
AUTONOMOUS CAR

2. • 10 million autonomous vehicles will hit the roads by 2022
• In 10 years fully autonomous vehicles will be the norm
• AVs will generate a $7 trillion annual revenue stream by 2050
• Widespread adoption of AVs could lead to a 90% reduction in
vehicle crashes.
Introduction

3. The Context
Autonomous Vehicles: Vehicles that can guide themselves from an origin point
to a destination point desired by the individual.
As an autonomous vehicle, it can sense its environment and navigating without
human input.
Individual yields near-full or partial control to artificial intelligence technology
• Individual decides an activity-travel plan (or tour-specific information)
• The plan is keyed into the car’s intelligence system
• The car (or an external entity connected to the car) decides on a routing and
circuit to complete the plan

4. History

5. Vehicle Hardware
Radar Lidar GPS
Processor Wheel Speed
Sensor
Optics

6. Continue…
GPS
A Global Positioning System keeps
the car on its intended route with an
accuracy of 30 centimeters.

7. Radar
• Traditional RADAR sensors are used to detect dangerous objects in the vehicle’s path that are
more than 100 meters away.
• Accident-Prevention systems trigger alerts when they detect something in a blind car’s blind spot.
• The radar chirps between 10 and 11 GHz over a 5-millisecond period, transmitting the radar signal
from a centrally located antenna cone.
• Two receive cones, separated by approximately 14 inches, receive the reflected radar energy.

8. Lidar
• The Light Detection And Ranging (LIDAR) which is mounted on the roof of the vehicle is the most
important device in the Autonomous vehicles.
• The LIDAR consists of an emitter, mirror and receiver.
• The emitter sends out a LASER beam that bounces off a mirror that is rotating along with the
cylindrical housing at 10 revolutions per minute.
• After bouncing off objects, the LASER beam returns to the mirror and is bounced back towards the
receiver, where it can be interpreted into data.
• The vehicle can then generate a map of its surroundings and use the map to avoid objects.

9. Optics
• A camera mounted near the rear-view mirror build a real-time 3D images of the road ahead,
spotting hazards like pedestrians and animals.
• It is also used to identify road markings and traffic signals.
• Self-driving cars see better with cameras that mimic mantis shrimp vision.
• Types of optics used in AVs are:
• Night vision
• longwave infrared (LWIR)
• RGB camera

10. GPS
• An autonomous car navigation system based on Global Positioning System (GPS) is a new and promising
technology, which uses real time geographical data received from several GPS satellites to calculate
longitude, latitude, speed and course to help navigate a car.
• A Global Positioning System keeps the car on its intended route with an accuracy of 30
centimeters.
• The goal of the project is to make an auto-navigational car model that can route through known or
pre-programmed co-ordinates autonomously without any control by human.

11. Processor
• Full Self-Driving Chip (FSD Chip, previously Autopilot Hardware 3.0) is an autonomous driving
chip designed by Tesla and introduced in early 2019 for their own cars.
• Tesla claims the chip is aimed at autonomous levels 4 and 5. Fabricated on Samsung's 14 nm
process technology, the FSD Chip incorporates 3 quad-core Cortex-A72 clusters for a total of 12
CPUs operating at 2.2 GHz, a GPU operating 1 GHz, 2 neural processing units operating at 2
GHz, and various other hardware accelerators. The FSD supports up to 128-bit LPDDR4-4266
memory.

12. Wheel Speed Sensor
• Wheel Speed Sensors measure the road-wheel speed and direction of rotation.
• These sensors provide input to several different automotive systems including the anti-lock brake
system and electronic stability control.

13. Working
• Autonomous cars rely on sensors, actuators, complex algorithms, machine learning
systems, and powerful processors to execute software.
• Autonomous cars create and maintain a map of their surroundings based on a
variety of sensors situated in different parts of the vehicle.
• Radar sensors monitor the position of nearby vehicles.
• Video cameras detect traffic lights, read road signs, track other vehicles,
and look for pedestrians.
• Lidar (light detection and ranging) sensors bounce pulses of light off the
car’s surroundings to measure distances, detect road edges, and identify
lane markings.

14. Working
• Ultrasonic Sensors – Uses high-frequency sound waves and bounce-back
to calculate distance. Best in close range.
• DRSC - Based Receiver – Communications device permitting vehicle to
communicate with other vehicles (V2V) using DSRC, a wireless
communication standard that enables reliable data transmission in active
safety applications. NHTSA has promoted the use of DSRC.
• Sophisticated software then processes all this sensory input, plots a path, and
sends instructions to the car’s actuators, which control acceleration, braking, and
steering. Hard-coded rules, obstacle avoidance algorithms, predictive modeling, and
object recognition help the software follow traffic rules and navigate obstacles.

15. Continue…

16. Simulation
Footage of a Tesla car autonomously driving around along with the sensing and perception involved. (source)
Note: watch it in slide show...!!!

17. Applications

18. Case Study - Uber
The death of Elaine Herzberg (August 2, 1968 – March 18, 2018) was the first
recorded case of a pedestrian fatality involving a self-driving (autonomous) car,
after a collision that occurred late in the evening of March 18, 2018.
Herzberg was pushing a bicycle across a four-lane road in Tempe, Arizona,
United States, when she was struck by an Uber test vehicle, which was operating
in self-drive mode with a human safety backup driver sitting in the driving seat.
Accident Causes:
• Environment
• Software issues
• Sensor issues
• Distraction
• Other factors

19. Legal Issues
• Liability for damage.
• Who pays when a driverless car crashes?
• Cyber Security
• Implementation of legal framework and establishment of government
regulations for self-driving cars
• Loss of driver-related jobs
• Loss of privacy.
• Autonomous cars relying on lane markings cannot decipher faded, missing, or
incorrect lane markings.
• Determination of the severity of traffic lane obstacles, as in the question of
safely straddling a pothole or debris

20. Self-driving car firms

21. Self vs Human driven car

22. Conclusion
In conclusion, upon addressing the mechanics of the driverless car as well as its
benefits and potential issues, it is quite interesting to see how the world will
actually become by the year 2040. Is IEEE correct? Will the rite of passage of
attaining one’s driver license cease to exist? It is truly in the reader’s discretion to
determine and weigh the impacts that the driverless car will have on society in the
future. Until then, it is fascinating to see the effects this creation will have on the
states in which it is legalized as well as on the people that have chosen to
experiment with it.

23. Learning Resources
https://www.coursera.org/specializations/self-driving-cars
https://www.udacity.com/course/self-driving-car-engineer-nanodegree--nd013
https://www.udemy.com/course/applied-deep-learningtm-the-complete-self-drivin
g-car-course/
https://www.udacity.com/course/intro-to-self-driving-cars--nd113
https://www.coursera.org/learn/state-estimation-localization-self-driving-cars