TRAFFIC MANAGEMENT THROUGH SATELLITE IMAGING -- Part 1

RV College of
Engineering Go, change the world
RV College of
Engineering
Go, change the world
Intelligent Systems
PART 1 presentation
TRAFFIC MANGAMENT
THROUGH SATELLIE IMAGES

RV College of
 INTRODUCTION
 STANDARD TRAFFIC CONTROL SYSYTEMS
 LITERATURE REVIEW
 RESEARCH GAP
 OBJECTIVES
 REFERENCES
CONTENT

RV College of
 IN MODERN LIFE WE HAVE TO FACE WITH MANY PROBLEMS ONE OF
WHICH IS TRAFFIC CONGESTION BECOMING MORE SERIOUS DAY AFTER
DAY.
 THE MAJOR CAUSE LEADING TO TRAFFIC JAM IS THE HIGH NUMBER OF
VEHICLE WHICH WAS CAUSED BY THE POPULATION AND THE
DEVELOPMENT OF ECONOMY.
 PARTICULARLY, IN SOME ASIAN COUNTRIES SUCH AS VIETNAM, THE LOCAL
AUTHORITIES PASSED LAW LIMITING TO THE NUMBER OF VEHICLES FOR
EACH FAMILY.
 IT IS SAID THAT LARGE NUMBER OF VEHICLES, THE SCANTY
INFRASTRUCTURE AND THE IRRATIONAL DISTRIBUTION OF THE
DEVELOPMENT ARE MAIN REASONS FOR AUGMENTED TRAFFIC JAM.
INTRODUCTION

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• MANUAL CONTROLLING : MANUAL CONTROLLING REQUIRES MAN
POWER TO CONTROL THE TRAFFIC. DEPENDING ON THE COUNTRIES AND
STATES THE TRAFFIC POLICES ARE ALLOTTED FOR A REQUIRED AREA OR
CITY TO CONTROL TRAFFIC.
 AUTOMATIC CONTROLLING : AUTOMATIC TRAFFIC CONTROLLING IS
MAINLY DONE BY THE TIMERS AND ELECTRIC SENSORS. TRAFFIC LIGHTS
AUTOMATICALLY SWITCHES TO ON AND OFF DEPENDING ON THE TIMER
STANDARD TRAFFIC CONTROL SYSYTEMS

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• In the manual controlling system we need more man power. As we
have poor strength of traffic police we cannot control traffic manually
in all area of a city or town. So we need a better solution to control
the traffic.
• Satellite images have much more advantages over surveillance
camera images. Even the images taken from the satellite have quite a
disadvantage.
• Images taken from surveillance camera are not that perfect and even
the resolution is not upto the mark when compared to satellite
images.
• Surveillance camera require maintenance frequently and are not that
reliable compared to satellite images.
• So to eliminate such a situation we need an advanced technology or
methods.

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TITLE AUTHORS DATE OF
PUBLICATION
METHOD / TOOL USED
1)Vehicle
Extraction And
counting from
digital aerial
images
Hual Tyaa ,Kim Gill
Soo, Kll to chong
Feb 14th 2018  Before the method used based on shallow
learning and deep learning approaches
 And they proposed Convolution neural
network regress a Vehicle density map
across the aerial images
 dataset used are munich and overhead
imagery research dataset
 They have usome areial camera
2) An Intelligent
Automatic Traffic
Light Controller
using Embedded
Systems
G.Monika, N.Kalpana,
Dr.P.Gnanasundari
20TH MARCH
2016
 The present traffic control uses AT89C51
microcontroller
 It dosen't have ADC and predefined
algorithm
 They proposed AVR 32 microcontroller
 These has 10 bit ADC for IR input
 They have used geneetic alogorthim
 They resolved emergence vehicle detection
LITERATURE REVIEW

RV College of
TITLE AUTHOR DATE OF
PUBLICATION
METHOD/TOOL USED
3) Intelligent Traffic
Management System
for Cross Section of
Roads Using Computer
Vision.
Tousif Osman,
Shahreen
Shahjahan
Psyche
OCTOBER
2017
 In these research they take advantage on
computer vision And image processing techniques
 It can detect vehicle cond on road and auto adjust
the system
 They have used matlab tool for the processing
 They are trying to enhance with machine learning
4)Road extraction from
remote sensing images
Weixing Wang
Nan Yang
Yi Zhang
2016  in these paper they used knowledge base method ,
mathematical morphology , active contour control
for road extraction
 At first they used road features and road models
for road extraction ere analysed
 And secondly they performed principle of road
achievements
 They used (ANN,SVM,MRF's,mean shift)algorithms
were used
 THEy have used high resolution Rs image such as
IKONOS,quick bird,world view ,Geo eye
LITERATURE REVIEW

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PUBLICATION
METHOD/TOOL USED
5)An artificial immune
approach for vehicle
detection from high
resolution space
imagery
Honz zheng
Li Li
July 2016  An artificial immune approach to extract vehicle
targets from panchrimatic satellite imagery
 They have used antibodies network concept for
vehicle detection
 A morphology based preprocessing algorithm is
used
 they have used from images from quick bird
satellite ehich has 0.6m resolution
6)Traffic Control Using
Digital Image
Processing
Chandrasekhar.M,
Saikrishna.C,
Chakradhar.B,
phaneendra
kumar.p
May 2013  In these paper they sugested a sysytem that
implement image processing algorithm in real
time traffic light control
 They have used web camera in each stage of
traffc light
 And they used image matching technique with
the refrence road(empty raod) the trafficb is
governed acc to %matching
 They have used matlab tool for processing
LITERATURE REVIEW

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PUBLICATION
METHOD/TOOL USED
7)Automatic Traffic
monitoring from An
airborne wide angle
camera system for
estimation of travel
time
S suri , U Thomas
B Charmette
2015  For automatic estimation travel times based on
image series acquired optical wide angle frame
sensor
 camera consist of(CANON EOS 1D's Marhll ,16MP)
 Theybhave used edge detection method
 For vehicle detection theu proposed knowledge
based algorithm (k means algorithm)
 For future they methodology eastimation of min
velocity
8)A Critical Appraisal
on Traffic Signal
Timing Optimization
Techniques Recently
Used Worldwide
Prof. Jayesh
Juremalani and
Dr. Krupesh A.
Chauhan
2014  Handling congestion in urban traffic through through
next generation AI techniques
 They used fuzzy approaches, nural network and
genetic algorithms , ant colony algorithm and many
more
 The effect of pedestrian traffic on the optimization of
the signal timing is not fully understood yet.
 Potential of spatial technology such as GPS, GRS and
RS is not fully utilized for optimization process of
LITERATURE REVIEW

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LITERATURE REVIEW
PUBLICATION
METHOD/TOOL USED
9)Automatic Traffic
Monitoring from
satellite images Using
Artificial Immune
System
Mehrad Eslami,
Karim Faez
2010 • This article presents a new approach for recognizing the vehicle
and the road in satellite high resolution images.
• For road recognition , feature extraction and image processing
techniques like Hough transform, Gradient, and thresholding
operation are used.
• NAVTEQ panchromatic data set is used in this study which was
collected from Space Imaging Inc. web site .
• This artificial immune approach is effective in controlling traffic
jam and in recognizing the traffic density accurately.
10)Road-Following and
Traffic Analysis using
High-Resolution
Remote Sensing
Imagery
Seyed Mostafa
Mousavi Kahaki ,
Mahmood Fathy
2and Mohsen Ganj
30sept 2014 • Real time extraction and localization of a road from an aerial
image is an emerging research area and can be applied for
navigation of unmanned vehicles
• Threshold techniques, Hough transform and learning algorithm
are used for the road extraction and car detection.
• as these images are highly complex, explicitly formulated scale
dependent models are used in order to deal with them

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PUBLICATIO
N
METHOD/TOOL USED
11)Adaptive Predictive
Traffic Timer Control
Algorithm
Naren
Athmaraman and
Srivathsan
Soundararajan
August 2005 Introduced an adaptive predictive signal control system that performed real time queue
length estimation and employed an efficient signal coordination algorithm with APTTCA-
based system.
12) Traffic Monitoring
using Very High
Resolution Satellite
Imagery
Siri Øyen Larsen,
Hans Koren, and
Rune Solberg
2009 • The QuickBird satellite with 0.6 m ground resolution in the panchromatic band is used to
obtain the images
• Road masks are applied to the images in order to restrict vehicle detection to roads
• The panchromatic image is thresholded in two stages, for dark and bright segments,
respectively
• Hysteresis thresholding is performed to remove the unwanted objects like road marks
• Various features like mean intensity of the object, mean gradient of the object, standard
deviation of the intensity within the object ,object length, the spatial spread of the
object are examined to describe the segments
• The well known maximum livelihood method is used to classify the segments
• The proposed segmentation routine fails to capture vehicles of very low contrast to the
local background, especially when the low contrast segments are only slightly brighter
than the road. Lowering the threshold for bright segments may yield a lot more road
marks to become included as segments
LITERATURE REVIEW

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PUBLICATION
METHOD/TOOL USED
13)An IoT
based smart
architecture
for traffic
managemen
t
Harkiran
Kaur,
Jyoteesh
Malhotra
July,2017 • Represents an effective architecture for controlling and manages the smart
traffic system using IoT, cloud and WSN.
• IoT and Cloud are used to manage the huge amount of real-time data which
can be collected as well as proceed.
• Fuzzy logic is used to instant and accurate result which makes the
performance of the system more reliable and efficient.
14)Integrate
d Traffic
Manageme
nt Platform
Design
using GIS-T
Yi FU,
Zhiheng LI,
Kezhu SONG,
Zhigang QIU,
Xuhui MA
2006 • The traffic management system based on GIS-T connects multi control
systems, completes the task of real time traffic management, distributes
traffic flow information, and manages the traffic static information, such as
intersection lights and signal controllers.
LITERATURE REVIEW

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LITERATURE REVIEW
PUBLICATION
METHOD/TOOL USED
15)Traffic
Management
through VANET
Farza Baber,
Muhammad Rizwan
February 2019 • VANET (Vehicular ad-hoc network) is a major component of
Intelligent Transport System.
• VANET allows vehicles to communicate to avoid accident, to
inform about road blocks, ensures about blocked areas.
• The proposed solution is basically redefining the A-star
routing protocol.
16)Smart Traffic
Management
system using
Internet of Things
Sabeen Javaid, Ali
Sufian, Saima
Pervaiz, Mehak
Tanveer
February 2018 • The proposed system is designed to govern traffic at road
networks, sensing through sensors, surveillance cameras,
and RFIDs which are embedded on roadsides.
• It also tackles emergency vehicles such as ambulance, fire
brigade. it also helps the users to know the congestion status
at a road through prediction

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PUBLICATION
METHOD/TOOL USED
17)A New Genetic
Algorithm Based Lane-
By-Pass Approach for
Smooth Traffic Flow on
Road Networks
Shailendra Tahilyani ,
Manuj Darbari , Praveen
Kumar Sh
2012 • Developed a new lane bypass algorithm for
route diversion given a result in smooth
traffic flow on the urban road network.
• Genetic algorithms are utilized for the
parameter optimization.
• Tool used are GIS.
18) FPGA
implementation of
intelligent traffic signal
controller based on
neuro fuzzy system
Ramteke Mahesh K.,
Nikalaje Mahesh J. ,
Prof.D.B.Rane
March, 2014 • Proposed FPGA controller based on Neuro-
Fuzzy system thought provided effective
solution for Traffic Control.
• It can used to minimize drawbacks of the
conventional traffic controllers with the
accuracy of provided variation in green cycle
intervals based on the heavy traffic loads
that changed at every lane in a four leg
intersection.
LITERATURE REVIEW

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LITERATURE REVIEW
PUBLICATION
METHOD/TOOL USED
19)Road traffic
monitoring by satellite
Erling Kristiansen
Claude Loisy
Willem v.d. Bosch
august 2003 • The RTMS project has shown that
the collection of valid and valuable
traffic information by means of
satellite is feasible.
• RTMS will enable road authorities
to cover the whole road network -
not just the bottlenecks - without
huge investments in infrastructure
such as loop detectors, video
detectors and the corresponding
cabling.
20) SATELLITE IMAGE
PROCESSING
ALOK KUMAR
SAMANTARAY
2010 • Satellite image processing has a
good application in future.
• It can be used for analysis of
various images taken from
satellites and air crafts of ground.
• It uses sensors and also accesses
various dangerous locations with
quality resolution.

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LITERATURE REVIEW
PUBLICATION
METHOD/TOOL USED
21) Image processing
through road traffic
analysis
R.Blake
M.Kazimianec
November 18,2015 • Roadmasking,
• Lane masking
• background elimination are done
• Tool used are GPRS, cameras , C++
• Traffic flow monitoring and analysis
is done based on computer vision
techniques.
• computer algorithms are used
22)A model and genetic
algorithm for area-wide
intersection signal
optimization under user
equilibrium traffic
Jianhua Guo, Ye Kong,
Zongzhi Li, Wei Huang
2017 • A genetic algorithm was developed
to derive the model solution.
• A simulation control protocol
embedded in PARAMICS software
tool.
• Capable of conducting area-wide
micro simulation is adopted to design
the logic frame and function module
of the area-wide traffic signal control
system

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LITERATURE REVIEW
TITLE AUTHOR DATE OF PUBLICATION METHOD/TOOL USED
23) Truck traffic
monitoring with
satellite images
Lynn H.Kaack
George H. Chen
M.Granger Morgan
November 28,2018 • Object detection network is used to count
the trucks using satellite images.
• They take advantage of recent advances in
deep convolutional neural network for obj.
detection.
• This method was successful and
identification of trucks became easy.
• In deed identifying them and controlling
them for a certain period of time mainly
during peak hours, traffic can be controlled.
24) Vehicle queue
detection in urban
areas through
satellite images
J.Lietloff
S.Hinz
U.Stilla
August 2016 • The main objective is focusing on the
vehicle queue in urban areas.(Quick bird
images )
• Here in this method single vehicles are
merged into dark or bright lines for easy
identification.
• The queues are extracted as dotted lines
using differential geomettical approach.
• Tool used is simulated GIS

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Title of the paper Authors of the
paper
Year Key Learning's
25. Truck Traffic
Monitoring with
Satellite Images
Lynn H.
Kaack1,George H.
Chen , and M.
Granger Morgan
17 July 2019 • The detection model counts the number of vehicles on roads
in a satellite image, and the monitoring model translates these
counts into an AADTT estimate. Model takes as input an
estimated vehicle count along with the timestamp for the
satellite image; the traffic monitoring model’s output is an
AADTT estimate(vehicle count averaged over time)
• Truck detection model.
• Traffic monitoring model
• Proposing a remote sensing approach to monitor freight
vehicles through the use of high-resolution satellite images.
Literature Review

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Title of the paper Authors of the paper Year Key Learning's
26.Automatic Traffic
Monitoring from
Satellite Images
Using Artificial
Immune System
Mehrad Eslami and
Karim Faez
2010 • The algorithm implements morphology operations on images to
enhance vehicle features.
• Proposing the technique using the artificial immune network
concept to extract the vehicle targets and using Hough transform
and parallel lines detection to extract roads and then recognize
traffic in space imagery
27.Traffic
Monitoring using
Very High
Resolution Satellite
Imagery
Siri Oyen Larsen,
Hans Koren, and
Rune Solberg
July 2009 • Proposes a new approach for prediction of vehicle shadows
• The shadow information is used as a contextual feature in order to
improve classification
• The algorithm consists of a segmentation step followed by object-
based maximum likelihood classification
Literature Review

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Title of the paper Authors of the paper Year, Name of the
Journal
Key Learning's
28. Road-Following
and Traffic Analysis
using High-
Resolution Remote
Sensing Imagery
Seyed Mostafa
Mousavi Kahaki 1,
Mahmood Fathy 2
and Mohsen Ganj
2009 • This paper proposed an integrated approach for automatic road
extraction from remotely sensed imagery by combining digital
image processing, remote sensing and Geographic Information
System (GIS) technologies
• It focuses on the issue of vehicle detection and road extraction
from high resolution satellite imagery for traffic analysis
29.TRAFFIC
MANAGEMENT WITH
STATE-OF-THE-ART
AIRBORNE IMAGING
SENSORS
C. K. Totha , D.
Grejner-Brzezinska
2004 • This paper provides a review of research using state-of-theart
remote sensing sensors to support traffic flow extraction using
LiDAR and digital camera sensors installed on airborne platforms
• Airborne sensors, LiDAR and frame imagery in particular, provide
high spatial and temporal resolution data that can effectively
support modeling and management of traffic flows
30.SUPPORTING
TRAFFIC FLOW
MANAGEMENT WITH
HIGH-DEFINITION
IMAGERY
C. K. Totha , D. G-
Brzezinska b, C.
Merry b
2004 • This paper proposes aspects of using high-resolution imagery to
support traffic flow monitoring and management.
• digital cameras and LiDAR systems, supported by state-of-the-art
GPS/IMU-based direct georeferencing, for airborne surveying
Literature Review

RV College of
Journal/Conference
Key Learning's
• Discuss about the algorithm / model / tool / technique used.
• Main focus of the paper in couple of sentences
Supporting Traffic
Flow Management
with High-Definition
Imagery
C. K. Totha, D. G-
Brzezinska , C. Merry
Usage of high resolution
digitized cameras,
LiDAR systems, state of
the art GPS/IMU based
direct Geo Referencing,
INPHO for processing
High definition airborne imagery useful
to determine traffic flow, turning
volumes, vehicles at intersections, and
even rural roads, speeds of moving
vehicles
Satellite Imagery
Applications of Urban
Road Inventory, Traffic
Flow Attributes, and
Road Capacity
Assessment
International Journal
of Recent Development
in Engineering and
Technology,
Literature Review
paper
Year, Name of the
Journal/Conference
Key Learning's
• Discuss about the algorithm / model / tool / technique
used.
31)SUPPORTING TRAFFIC FLOW
MANAGEMENT WITH HIGH-
DEFINITION IMAGERY
C. K. Totha, D. G-
Brzezinska , C.
Merry
OSU, Center of Mapping,
Columbus, USA
digitized cameras(1.5m),
LiDAR systems, state of the art
GPS/IMU based direct Geo
Referencing, INPHO for
processing
High definition airborne
imagery useful to
determine traffic flow,
turning volumes, vehicles at
intersections, and even
rural roads, speeds of
moving vehicles
32)SATELLITE IMAGERY
APPLICATIONS OF URBAN ROAD
INVENTORY, TRAFFIC FLOW
ATTRIBUTES, AND ROAD CAPACITY
ASSESSMENT
W. Uddin, A.
Ahmed, M.S. Ali
International Journal of
Recent Development in
Engineering and
Technology, December
2013,
0.6m precision Quickbird 2
imagery, processing using
Photogrammetric tools like
SOCET SET
Creating traffic volume
maps, Image based traffic
flow attributes, and analysis
of traffic problems of
specific cities like Karachi,
Pakistan
33)AUTOMATIC TRAFFIC
MONITORING FROM SATELLITE
IMAGES
USING ARTIFICIAL IMMUNE SYSTEM
Mehrad Eslami
and Karim Faez
E.R. Hancock et al. (Eds.):
SSPR & SPR 2010, LNCS
6218, pp. 170–179, 2010.
0.6m-1m precision imagery
using NAVTEQ satellite, and
IKONOS. Image is processed
Preferably for non urban
roads and without cross
roads, to track the vehicular
movement
This surveillance helped
police track the vehicular
movements and alert the
local points for cases of
overspeeding, number of
vehicles.

RV College of
Journal/Conference
Key Learning's
Supporting Traffic
Flow Management
Imagery
C. K. Totha, D. G-
digitized cameras,
vehicles
Satellite Imagery
Road Capacity
Assessment
in Engineering and
Technology,
Literature Review
paper
Year, Name of the
Journal/Conference
Key Learning's
34)VEHICLES DETECTION FROM VERY
HIGH RESOLUTION SATELLITE
IMAGERY
A. Gerhardinger,
D. Ehrlich , M.
Pesaresi
IPSC, Joint Research Centre,
21020 Ispra, Italy
IKONOS and QUICKBIRD
satellite imagery, geometric
rectification of images,
digitizing the roads into pixels
(5-20) and calibration to find
objects (vehicles)
Vehicle detection of very
high resolution irrespective
of atmospheric conditions,
but using pre processed
images which is not
economically viable
35)FULLY CONVOLUTIONAL
NETWORK FOR AUTOMATIC ROAD
EXTRACTION FROM SATELLITE
IMAGERY
Alexander Buslaev,
Selim Seferbekov,
Vladimir Iglovikov,
Alexey Shvets
IEEE Explore ResNet-34 pre-trained U-Net,
DEEPGLOBE – CVPR road
extraction sub-challenge. GTX
1080 or 1080ti video
Cards, IKONOS imagery
This module aims at
automated high resolution
and precise road extraction
from satellite images using
neural networks. It involves
photogrammetry of the
images and used to obtain
roads
36)TRUCK TRAFFIC MONITORING
WITH SATELLITE IMAGES
Lynn H.
Kaack,George H.
Chen, and M.
Granger Morgan
arXiv:1907.07660v1 [cs.CY] ,
Jul 2019
Faster Neural Network, SSD,
Region based fully
convolutional neural network,
Tensorflow object detection
API, Res-Net 34, IKONOS and
Quickbird imagery
Truck Monitoring is also
required for economic
analyses and road
maintenance, done using conv.
Neural network and filtering
out trucks from existing

RV College of
Journal/Conference
Key Learning's
Supporting Traffic
Flow Management
Imagery
C. K. Totha, D. G-
digitized cameras,
vehicles
Satellite Imagery
Road Capacity
Assessment
in Engineering and
Technology,
Literature Review
paper
Year, Name of the
Journal/Conference
Key Learning's
37)AUTOMATIC MOVING VEHICLE’S
INFORMATION EXTRACTION FROM
ONE-PASS WORLDVIEW-2 SATELLITE
IMAGERY
Rakesh Kumar
Mishra
International Archives of
the Photogrammetry,
Remote Sensing and Spatial
Information Sciences, 2012
WorldView 2 Satellite imagery,
(low accuracy 2m), extraction
using image resampling, edge
detection, filtering
The images are obtained
using World View 2 images,
then resampled, which is
later passed through edge
detection, filtering and
interpretaion
38)TRAFFIC MONITORING USING
VERY
HIGH RESOLUTION SATELLITE
IMAGERY
Siri Qyen Larsen,
Hans Koren, and
Rune Solberg
Photogrammetric
Engineering & Remote
Sensing, 2009
Quickbird imagery,
Convolutional Neural network,
IKONOS imagery, Image
processing using TensorFlow
Detection APIs
The images are obtained by
the satellite for the primary
reason of regular
surveillance, road
maintenance by statistically
collecting road data of inner
roads in particular
39)INCORPORATING SATELLITE
IMAGERY
IN TRAFFIC MONITORING PROGRAMS
Mark R. McCord
Carolyn J. Merry
Prem Goel
North American Travel
Monitoring Exhibition and
Conference
Charlotte, North Carolina
USA,1998
Mcord, EarlyBird imagery,
ORBIMAGE Spacecraft control
center,
This was a break into the topic
of introducing satellite
photogrammetry and remote
sensing concepts to traffic
surveillance to help automate
the process and help the

RV College of
RESEARCH GAP
• Vehicles are usually missed due to local variations in lighting conditions or obstructed
view of the road due to vegetation. The main source of non-vehicle segments that are
confused with vehicles is road segments, which (after segmentation) come in a wide
variation of shapes and shades.
• It is desirable to be able to discriminate a larger part of the noise objects, i.e., objects that
do not belong to any of the defined classes.
• The proposed segmentation routine fails to capture vehicles of very low contrast to the
local background, especially when the low contrast segments are only slightly brighter
than the road.
• Quick and efficient extraction of road from RS images is a significant area of research.
• Satellites cannot capture images in rainy, cloudy or other harsh climatic conditions.
• The use of VANET technology fails in recovery strategy in order to reduce end to end
delay.
• All road networks including marked and unmarked roads have to be mapped in order to
avoid accidents.

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OBJECTIVES
• By using micro controller There will be no information avilable of real time traffic
• Prediction of Vehicle Shadows ,Many of the segments represent vehicles shadows. These are of concern to
us, because we need to separate them from the vehicles during classification.
• Weather consideration: In this project, weather was not considered. So when there is fog it might not get the
accurate results and provide proper signaling message. Also, at night this type of problems may occur. So, in
future research on Image Processing can be done with the consideration of weather by edge detecting.
• In case where surrounding objects like water , buildings , trees, grass and cars occulude the road and cast
shadows ,especially with influence of spatial structures such as overpass ,the road extraction often fails
,resulting in gaps and discontinuities in the detected roa.Hence,how to extract road from Rs images quickly
and efficiently is of significance
• The implementation of different advanced techniques for traffic signals management shows great promise to
solve the problems of “Traffic Signals Management” by changing from ordinary control of it that is based on
(queue length and wait time) to more smart control that is based on existing of vehicles at intersections.

RV College of
Objectives
• To effectively process satellite Imagery clicked specifically for traffic surveillance using
software processing tools like python/OpenCV/Tensorflow etc
• To obtain statistical data on vehicular movement, speeds of vehicles, categorize as heavy
vehicles, light vehicles
• To aid emergency situations as a means of effective and quick communication
• Ensure reliable and safe operation of transport.
• Ensure fair allocation of infrastructure space (road space, rail slots, etc.) among competing users.
• Improving the travelling mobility.
• Conserving the energy while protecting the environment.

RV College of
REFERENCES
1. M. R. Islam, N. I. Shahid, D. T. ul Karim, A. A. Mamun and M. K. Rhaman, "An efficient algorithm for detecting traffic
congestion and a framework for smart traffic control system," 2016 18th International Conference on Advanced
Communication Technology (ICACT), Pyeongchang, 2016, pp. 802-807, doi: 10.1109/ICACT.2016.7423566.
2. G.Monika, N.Kalpana, Dr.P.Gnanasundari,” An Intelligent Automatic Traffic Light Controller using Embedded Systems “
3. T. Osman, S. S. Psyche, J. M. Shafi Ferdous and H. U. Zaman, "Intelligent traffic management system for cross section of
roads using computer vision," 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), Las
Vegas, NV, 2017, pp. 1-7, doi: 10.1109/CCWC.2017.7868350.
4. Smart Traffic Management System for Congestion Control and Warnings Using Internet of Things (IoT)
5. Vadrevu S. V. S. R. Pavan Kumar, Dr. M. Kamala kumara,” A Novel Application of Adaptive Traffic Control System for
India”, IJSETR,5,(7),ISSN 2278-7798,JULY 2016
6. Chandrasekhar.M, Saikrishna.C, Chakradhar.B, phaneendra kumar.p, sasanka.c, “Traffic Control Using Digital Image
Processing” , International Journal of Advanced Electrical and Electronics Engineering ISSN 2278-8948, Vol.2, May 2013
7. Sharma, Ishant & Gupta, Pardeep. (2017). STUDY OF AUTOMATIC TRAFFIC SIGNAL SYSTEM FOR CHANDIGARH.
10.13140/RG.2.2.28390.83526.
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