Self-driving cars use sensors like radar, GPS, and computer vision to detect their environment without human input. Advanced control systems interpret sensory data to identify paths and obstacles. Technologies used include anti-lock brakes, adaptive cruise control, and lidar systems. Algorithms like edge detection are used to locate intensity contrasts and track objects over image sequences. Self-driving cars aim to increase road capacity, relieve drivers, avoid accidents, and minimize loss of control compared to human drivers.

1. Puranam Revanth
Kumar
CB.EN.P2CIN17005
Control and Instrumentation
Engineering
Self Driving Car
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2. • Introduction
• Technology
• Types of Algorithms
• Conclusion
Contents
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3. INTRODUCTION

4. To begin, a self-driving car (driverless, autonomous, robotic car) is
a vehicle that is capable of sensing its environment and navigating without
human input.
Self-driving cars can detect environments using a variety of techniques
such as radar, GPS and computer vision.
Advanced control systems interpret sensory information to identify
appropriate navigational paths, as well as obstacles and relevant signage.
Self-driving cars have control systems that are capable of analyzing
sensory data to distinguish between different cars on the road. This is very
useful in planning a path to the desired destination.
Introduction
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5. TECHNOLOGY

6. The Technology of the Car
Puranam Revanth Kumar
Anti-Lock Brakes
Electronic Stability control
Adaptive cruise control
Lane-departure warning system
Self parking
Automated guided vehicle
systems
Lidar-Systems(with google cars)
or Cruise Automated
Systems(Audi)
Infrared cameras.
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7. The Lidar System
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Features:
Vertical and horizontal setup of the system
possible
Image acquisition with fully integrated
NIKON DSLR camera.
3D mode of the VZ scanner with continuous
rotation of the scanning head for highly
efficient mobile data acquisition.
360 degree static scanning.
Mainly used by Google Inc. for detecting
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8. Infrared cameras
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 Detect traffic lights, read road signs,
keep track of the position of other
vehicles and look out for pedestrian's
and obstacles on the road.
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9. Radar Sensors
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Four standard automotive radar sensors, three in
front and one in the rear which helps in
determining the position of distant objects.
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10. Ultrasonic Sensor
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 It is used to measure the position of
objects very close to the vehicle,
such as curbs and other vehicles
when parking.
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11. Central Computer
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Information from all the sensors is analyzed by a central computer that
manipulates the steering, accelerator and brakes. Its software must
understand the rules of the road both formal and informal.
Based on the information received the software takes self driving
decisions.
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12. TYPES OF
ALGORITHMS

13. Software block diagram of self-driving cars
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14. Types of Algorithms for Localization and Mapping
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The combination of:
3-D imaging with multiple 1064 nm
lasers.
Edge-Detection Algorithm
Motion-Detection algorithm
Tracking algorithm
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15. Edge Detection Algorithm
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Locating areas with strong intensity contrasts.
Reduce unnecessary information in the image while preserving the
structure of the image.
Extract important features of an image
•Corners
•Lines
•Curves
Recognize objects, boundaries, segmentation.
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16. To track an object over a sequence of images.
A method of following an object through successive image frames to
determine its relative movement with respect to other objects.
Object Tracking
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17. Advantages
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Managing traffic flow to increase road capacity.
Relieving vehicle occupants from driving allowing them to concentrate on
other tasks or to rest during their journeys.
To avoid accidents .
Increasing roadway capacity by reducing the distances between cars.
The current location of vehicle can be determined using Global Positioning
System (GPS) .
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18. The driver less car’s technologies improves vehicle's stability helps to
minimize loss of control.
Driver less cars are designed to minimize accidents by addressing the main
causes of collisions: driving error, distraction and drowsiness.
Conclusion
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