This document proposes developing a low-cost self-driving car system to reduce the over 1.2 million annual road deaths worldwide. It would use sensors like ultrasonic sensors and cameras along with neural networks and AI to process sensory input and control systems like steering and braking. The methodology involves developing, testing, and training the system to recognize situations and communicate between vehicles. The goal is to create a reliable and efficient self-driving system that could help reduce accidents caused by human error and benefit those unable to drive like the blind.

1. LOW COST SELF-
DRIVEN CAR
SYSTEM
M.K.H. GUNASEKARA
CSC 363 1.5 Research Methodologies and Scientific
Computing
Department of Computer Science and Statistics , USJP
AS2010377
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2. Practical Problem
 Road accidents are among the leading causes
of death today.
 There are over 1.2 million people died
annually from road accidents.[1]
 There are over 50 million people injured.[1]
 Careless driving is the most common reason
for road accidents.
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3. Practical Problem
 Total worldwide death toll of Tsunami of 2004
was about 230,000.
 But the annual worldwide death toll of Road
Accidents more than1,200,000 !!!
 It’s more than 5 times tsunami toll
 One child is killed in Road Accidents, every
three minutes in the World.[2]
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4. Road Accident photos
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5. Road Accident photos
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6. Road Accident photos
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7. Research Question
 How can we reduce road accidents ?
 How can we reduce this careless driving?
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8. Research Problem
 We need to find a mechanism to make good
drivers.
 We need to find a method to make drivers
always alert.
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9. Low cost self-driven car
system
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10. Aim
 To develop, implement and evaluate a low cost
self-driven car system to reduce car accidents
using immerging technologies, Artificial
Intelligence methods, Neural Network
Algorithms, Mechatronics components.
 To make very reliable and efficient.
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11. Methodology
 Phase 1 : Development and construction of the
system.
 Phase 2 : Testing the data patterns of sensory
system.
 Phase 3 : Identify information patterns for different
inputs.
 Phase 4 : Make necessary algorithms to perform
actions by processing system.
 Phase 5 : Task base assessment.
 Phase 6 : Train the system with different situations.
 Phase 7 : Develop vehicle to vehicle
communication.
 Phase 8 : Develop voice commanding system.
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12. Sensory System
 Ultrasonic sensors
 Infrared Sensors
 Rotating electromagnetic ray beam
 Weather detection sensors
 Front and rear cameras
 Global position system
 Microphones
 Other Sensors
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13. Processing System
 Neural Networks
 Artificial Intelligence
 Pattern recognition
 Immerging Technologies
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14. Execution System
 Mechatronic Components
 Power Steering Actuators & Motors
 Engine Management Systems
 Brake Management Systems
 Signal Management systems
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15. Communication system
 Ad Hoc Wireless Network System – V2V
 Bluetooth 2450 MHz band
 HIPERLAN 5800 MHz band
 IEEE 802.11/WiFi 2450 MHz and 5800 MHz
bands
 Internet Connectivity
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16. Model – Toyota Corolla 2012
sensors
sensors
Ultrasonic sensors
Rear camera
360 rotating
electromagnet
ic ray beam
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17. How system works
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18. Conclusion
 Very good for blind people.
 Reduce car accidents
 Fuel consumption is minimum
 Reduce road traffic
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19. References
[1] Margie Peden, Richard Scurfield, David Sleet, Dinesh Mohan, Adnan A. Hyder, Eva
Jarawan. 2004, World report on road traffic injury prevention. World Health
Organization, Geneva. 97(22), pp.63-64.
[2] USACoverage, 2005. How Many Driving Accidents Occur Each Year?[online]
Available at :www.usacoverage.com/auto-insurance/how-many-driving-accidents-occur-
each-year.html
[Accessed 15 August 2013].
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