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ADAPTIVE AND
AUTONOMOUS TRAFFIC
MANAGEMENT SYSTEM
(A.A.T.M.S.) USING
LabVIEW
DELHI TECHNOLOGICAL UNIVERSITY
National Conference on Advanced Computing and Research (NCACR)-
2015
INTRODUCTION
The Adaptive and Autonomous
Traffic Management System
(AATMS) is an Intelligent Transport
System(ITS) and is of considerable
interest because of its potential in
managing real-time multi- lane traffic
using a camera interfaced with a
microcontroller.
OUR OBJECTIVES…
Density/number
of vehicles
calculation
License plate
Detection &
Identification
Ambulance
Detection & Lane
Identification
SOFTWARE USED
NI LabVIEW 2013, NI Vision
Acquisition Express 2013, NI VDM
2013
HARDWARE USED
NI myRIO, RF Module(434Mhz)
Powered USB Hub, Switches
DENSITY/NUMBER OF VEHICLES
CALCULATION
DETECTION OF VEHICLES IN
EACH LANE
TRAFFIC LIGHTS CONTROL
ALGORITHM
DETECTION OF VEHICLES IN
EACH LANE
Original
Image
Background
Subtraction
Threshold Morphology
Particle
Analysis
RESULTS
Background Model Current Frame Subtracted Image After Morphology
After Particle Analysis
TRAFFIC LIGHTS CONTROL
ALGORITHM
The duration of active green signal depends upon the number
of vehicles/vehicle density in each lane.
The loop starts with Lane 1 and iterates till Lane 4 taking one
frame of video at a time.
If Ambulance is detected, an interrupt is generated to give
active green signal to that lane after which the loop iterates
sequentially like before.
An over-ride switch is provided. When this is active, an equal
delay is provided to each lane independent of the number of
vehicles. This is useful if cameras are to be uninstalled for
maintainance work.
The data of number of cars of each lane is stored in a 1-D
array for processing.
ASSUMPTIONS…
At a time, only one
lane has an active
green signal
Left turn is always free
The duration of
forward green signal
and right turn green
signal is same.
Illustration
RESULTS IN LabVIEW
LANE 1 LANE 2 LANE 3 LANE 4
APPLICATIONS
PREVENTION OFHEAVY
TRAFFIC JAMS
The system sets different delays for
different lanes depending upon the
number of vehicles in that lane, thus
preventing unnecessary traffic jams.
REAL TIME TRAFFIC
UPDATE
The real time traffic
information of traffic density
can be updated on the traffic
website wherein the users can
easily access that information.
SOLUTION TO
UNNECESSARY WAITING
Our system provides the
method which successfully
reduces the waiting time of
commuters at traffic junctions
even if there is no traffic.
LICENSE PLATE DETECTION
AND IDENTIFICATION
LICENSE PLATE LOCALISATION
SEGMENTATION AND OCR
LICENSE PLATE LOCALISATION
Original
Image
Color Plane
Extraction
Threshold
Binary
Inversion
Morphology
Particle
Filter
RESULTS
Original Image
Image Mask
After Binary Inversion
After Morphological Operations
After Image Mask
SEGMENTATION AND OCR
Original
Image
Image
Mask
Color Plane
Extraction
Threshold
Binary
Inversion
Morphology
RESULTS
Image
Mask
OCR
Original Image
Masked
Region
Threshold
Image
Particle
Filter
Final OCR
RESULTS IN LabVIEW
Vehicle 1Vehicle 2Vehicle 3
The above algorithm is
also implemented on Real
Time Videos which shows
the practical
implementation of our
project
APPLICATIONS
GENERATION OF DATABASE
This system automatically generates
the database of identified license
plates from which the defaulters can
be identified.
AUTOMATED PARKING SYSTEM
In Multilevel Parking Systems,
different spots can be pre-assigned
to different users. So the users is
identified via Registration Plate
detection and their vehicles are
parked automatically.
AUTOMATED TOLL
COLLECTION
The commuters can be
identified via license plate
detection and automatically
the toll can be debited from
their account.
AUTOMATIC
GENERATION OF E-
CHALLAN
The commuters can be
identified via license plate
detection and automatically
the challan can be debited
from their account.
AUTOMATIC TRACKING OF
TRAFFIC LIGHT DEFAULTERS
FUTURE SCOPE....
REAL TIME TRAFFIC INFORMATION
UPDATE ON TRAFFIC DEPARTMENT
WEBSITE
AUTOMATIC GENERATION OF E-
CHALLAN
AUTOMATIC TRACKING OF TRAFFIC
LAWS DEFAULTERS
IMPLEMENTATION OF ABOVE
SYSTEM AT NIGHT USING THERMAL
CAMERAS
DETECTION OF OTHER EMERGENCY
VEHICLES
THANK YOU

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niyantra 2014

  • 1. ADAPTIVE AND AUTONOMOUS TRAFFIC MANAGEMENT SYSTEM (A.A.T.M.S.) USING LabVIEW DELHI TECHNOLOGICAL UNIVERSITY National Conference on Advanced Computing and Research (NCACR)- 2015
  • 2. INTRODUCTION The Adaptive and Autonomous Traffic Management System (AATMS) is an Intelligent Transport System(ITS) and is of considerable interest because of its potential in managing real-time multi- lane traffic using a camera interfaced with a microcontroller.
  • 3. OUR OBJECTIVES… Density/number of vehicles calculation License plate Detection & Identification Ambulance Detection & Lane Identification
  • 4. SOFTWARE USED NI LabVIEW 2013, NI Vision Acquisition Express 2013, NI VDM 2013 HARDWARE USED NI myRIO, RF Module(434Mhz) Powered USB Hub, Switches
  • 5. DENSITY/NUMBER OF VEHICLES CALCULATION DETECTION OF VEHICLES IN EACH LANE TRAFFIC LIGHTS CONTROL ALGORITHM
  • 6. DETECTION OF VEHICLES IN EACH LANE Original Image Background Subtraction Threshold Morphology Particle Analysis RESULTS Background Model Current Frame Subtracted Image After Morphology After Particle Analysis
  • 7. TRAFFIC LIGHTS CONTROL ALGORITHM The duration of active green signal depends upon the number of vehicles/vehicle density in each lane. The loop starts with Lane 1 and iterates till Lane 4 taking one frame of video at a time. If Ambulance is detected, an interrupt is generated to give active green signal to that lane after which the loop iterates sequentially like before. An over-ride switch is provided. When this is active, an equal delay is provided to each lane independent of the number of vehicles. This is useful if cameras are to be uninstalled for maintainance work. The data of number of cars of each lane is stored in a 1-D array for processing.
  • 8. ASSUMPTIONS… At a time, only one lane has an active green signal Left turn is always free The duration of forward green signal and right turn green signal is same. Illustration
  • 9. RESULTS IN LabVIEW LANE 1 LANE 2 LANE 3 LANE 4
  • 10. APPLICATIONS PREVENTION OFHEAVY TRAFFIC JAMS The system sets different delays for different lanes depending upon the number of vehicles in that lane, thus preventing unnecessary traffic jams. REAL TIME TRAFFIC UPDATE The real time traffic information of traffic density can be updated on the traffic website wherein the users can easily access that information. SOLUTION TO UNNECESSARY WAITING Our system provides the method which successfully reduces the waiting time of commuters at traffic junctions even if there is no traffic.
  • 11. LICENSE PLATE DETECTION AND IDENTIFICATION LICENSE PLATE LOCALISATION SEGMENTATION AND OCR
  • 12. LICENSE PLATE LOCALISATION Original Image Color Plane Extraction Threshold Binary Inversion Morphology Particle Filter RESULTS Original Image Image Mask After Binary Inversion After Morphological Operations After Image Mask
  • 13. SEGMENTATION AND OCR Original Image Image Mask Color Plane Extraction Threshold Binary Inversion Morphology RESULTS Image Mask OCR Original Image Masked Region Threshold Image Particle Filter Final OCR
  • 14. RESULTS IN LabVIEW Vehicle 1Vehicle 2Vehicle 3 The above algorithm is also implemented on Real Time Videos which shows the practical implementation of our project
  • 15. APPLICATIONS GENERATION OF DATABASE This system automatically generates the database of identified license plates from which the defaulters can be identified. AUTOMATED PARKING SYSTEM In Multilevel Parking Systems, different spots can be pre-assigned to different users. So the users is identified via Registration Plate detection and their vehicles are parked automatically. AUTOMATED TOLL COLLECTION The commuters can be identified via license plate detection and automatically the toll can be debited from their account. AUTOMATIC GENERATION OF E- CHALLAN The commuters can be identified via license plate detection and automatically the challan can be debited from their account. AUTOMATIC TRACKING OF TRAFFIC LIGHT DEFAULTERS
  • 16. FUTURE SCOPE.... REAL TIME TRAFFIC INFORMATION UPDATE ON TRAFFIC DEPARTMENT WEBSITE AUTOMATIC GENERATION OF E- CHALLAN AUTOMATIC TRACKING OF TRAFFIC LAWS DEFAULTERS IMPLEMENTATION OF ABOVE SYSTEM AT NIGHT USING THERMAL CAMERAS DETECTION OF OTHER EMERGENCY VEHICLES