The document discusses an automatic train collision and accident avoidance system, highlighting the need for automated braking, real-time train monitoring, and an alert system using pattern recognition. It provides an overview of historical rail accidents and emphasizes the technology's potential to significantly reduce collision rates. Proposed solutions include installing ultrasonic sensors and implementing image pattern recognition to detect obstacles and alert control personnel.

1. Automatic Train Collision
and
Accident Avoidance System
By
R.Pradeep Raj
(pradeeprajr93@gmail.com)

2. Contents
• Importance of this topic
• Rail accidents – An overview
• Ideas suggested :
– Automated Braking in Trains
– Real-time Train monitoring
– Alert system using Pattern Recognition

3. Why this topic..?
Survey on Train Accidents
40
35
1890's
30
1900's
25
1950's
20
1970's
15
1980's
1990's
10
2000's
5
2011-13
0
Year

4. Rail accidents
• 4 January 1961 - Frontal collision of two passenger trains near
Umeshnagar. 35 dead, 61 wounded.
• 13 August 1998: Nineteen killed and 27 injured as a bus rams
into the Chennai–Madurai Express train at an unmanned
level-crossing.
• 13 November 2013 - A herd of 40 elephants was struck by a
passenger train in Chapramari Wildlife Sanctuary.

5. 1. Automated braking
Need :
• To detect the presence of
obstacle even from a long
range
• Human inaccuracy
• Optimal level of brake
application

6. Braking System
Types :
• Vacuum brake (obsolete)
• Air brake (currently in use) - Westinghouse Brake
The average braking distance of a train moving
at a speed of 100 km/hr is about 300m.
Dynamic Braking

7. Westinghouse Brake
Lever

8. Ultrasonic Transducer
 Production of high frequency sound waves around
18,000 hertz
 Works on the principle of Piezo-electric Effect
 Generated by Piezo-electric crystal
 Also produced by Magneto-striction effect
Time interval between sending and reception

9. Generation :
Transceiver :

10. T
R
A
N
C
E
I
V
E
R
ADC
Intimate the
Loco-driver
Microcontroller
Application of
Brakes
O
B
S
T
A
C
L
E
Driver circuit and
Actuator

11. 2. Real-time Train Monitoring
 Placing for every 300m – 500m in unmanned level crossing
and accident prone zones.
 It gives the real time parameters of train :
 Speed of the train
 Direction of the train
 Location of the train

12. Piezo-electric sensor
To measure
• Changes in pressure
• Acceleration
• strain or force
by converting to
electrical signals

13. Block Diagram

14. What can we achieve?
• An easiest way to get the real-time
parameters
• Intelligent alert system at crossing
• Best way to eradicate Train-Vehicle collision

15. 3. Pattern Recognition
An Application of
Digital Image Processing
Based on Bayesian
Decision Theory
Types :
1. Statistical Pattern Recognition
2. Structural Pattern recognition

16. Alert using Pattern Recognition
• It compare the
sensed image with
predefined image
pattern which is
stored and takes
decision.

17. Ecological Gateway
A geographical location along or between
the forest where migration of animals occurs.

18. What we planned ?
• Image pattern of track is predefined in Image
processor and monitored regularly.
• If any major change in image pattern is sensed
it will alert personnel in control room.

19. START
FLOW CHART :
CAMERA MONITORS THE
TRACK
NO
IF
CHANGE
OCCURS
YES
NO ACTION
(IDLE STATE)
ALERTS THE DETECTION
TO CONTROL ROOM
DECISION WAS TAKEN
STOP

20. Pros of the Idea
• No need to monitor the track for 24*7
• Animal collision is greatly reduced
• Needs to be installed only in specified area

21. Conclusion
When these ideas are implemented in the future,
surely the rate of rail-accidents due to collision can be
drastically reduced.
40
30
20
10
0
Year
1890's
1900's
1950's
1970's
1980's
1990's
2000's
2011-13
2020's