TECHNICAL FIELD

The present disclosure relates to the field of optimization of efficiency of a journey of a vehicle. More particularly, the present disclosure relates to systems and methods for mapping traffic.

BACKGROUND

The background description includes information that may be useful in
understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[003] Some major issues and problems confronting today's cities are crowding,
traffic and pollution. Unconnected vehicles and traffic signals make it harder to predict the traffic scenario. While driving in the city the vehicle tends to stop and start multiple times thus more energy is required to move the vehicle from rest to moving state as compared to when in motion. This also speeds up the wearing of mechanical parts. For driverless vehicles traffic light detection and signal recognition are hard problems. During winters a thin layer of snow accumulate in front of light module making difficult for both humans and machines to recognize the light state causing many fatal accidents. Sometimes the light module (specifically red or green as they have more ON time) fails giving no light status making it completely impossible for autonomous vehicle to interpret the traffic light state. Many a times the traffic light view (from vehicles site of view) is obstructed by a big vehicle ahead, sunset or a person holding red hot air balloon may cause false or not interpretation of traffic light state.
[004] Considering the ideal condition where we do not measure the traffic waiting at
the traffic light and calculating the speed using the simple formula (speed = distance/time) is
a very static approach to find solution to the problem. It will cause slowing of vehicle to wait
for traffic to clear out. Larger traffic might even make false prediction.
[005] The other possible solutions are the image processing on the population of the
vehicles, where accuracy lacks and needs a high computing processor with the detailed image processing algorithms, the training date set will be huge, most of the times it is very tough to detect hidden vehicles. So, all around the world researchers are trying to solve this problem.

[006] Efforts have been made in the past to overcome problems associated with
vehicular traffic. For example, United States Patent Number US 7702452 B2 discloses a
system and method for determining the necessary departure time to allow for an on-time or
desired arrival time at a particular location over a particular route based on the evaluation of
historic, present, and predicted road conditions. However, Christopher et al provides the first
idea of Traffic monitoring but they use various methods to collect data.
[007] United States Patent Application Number US 20150221218 Al provides an
incident report including a path segment identifier and an incident identifier is received at a computing device. The incident identifier is sent to a traffic prediction model. The traffic prediction model returns a traffic distribution value. The traffic distribution value identifies a portion of a traffic prediction distribution derived from historical data. The computing device accesses a lookup table according to traffic distribution value and the path segment identifier to receive a speed prediction. However, as per Oliver et al computing device accesses a lookup table according to traffic distribution value and the path segment identifier to receive a speed prediction.
[008] United States Patent Application Number US 20130268152 Al provides an
electric vehicle driving support system includes an acquisition unit that acquires predictive
information of traffic congestion calculated based on acceleration of an electric vehicle and
an economical driving mode output unit that outputs a control instruction to prioritize speed
maintenance or acceleration when the predictive information of traffic congestion acquired
by the acquisition unit indicates a non-congestion tendency, and that outputs a control
instruction to prioritize deceleration when the predictive information of traffic congestion
indicates a congestion tendency. However, as per Takamasa et al the imaging apparatus
includes a camera, performs a predetermined image process on an image obtained by imaging
an imaging area set in the external surrounding and use GPS/Internet support for measuring
the traffic and they do image processing for identifying the Individual vehicles.
[009] There is therefore a need in the art to provide traffic mapping system and
method that seeks to overcome or at least ameliorate one or more of the above-mentioned problems and other limitations of the existing solutions and utilize techniques, which are robust, accurate, fast, efficient, cost effective and simple.

OBJECTS OF THE PRESENT DISCLOSURE
[0010] Some of the objects of the present disclosure, which at least one embodiment
herein satisfies are as listed herein below.
[0011] It is an object of the present disclosure to provide traffic mapping system and
method.
[0012] It is another object of the present disclosure to provide traffic mapping system
and method that can assist in enhancing user driving/riding vehicle experience by avoiding
unnecessary traffic congestions
[0013] It is another object of the present disclosure to provide traffic mapping system
and method that can help enhancing fuel efficiency of a vehicle because of traffic congestion.
[0014] It is another object of the present disclosure to provide traffic mapping system
and method that can be used for reducing controlling requirement for unmanned vehicles.
[0015] It is another object of the present disclosure to provide traffic mapping system
and method that can be used by the government for better management of traffic.
[0016] It is another object of the present disclosure to provide traffic mapping system
and method that can assist users avoiding accidents when traffic lights are faulty or visibility
of the traffic lights is reduced.
[0017] It is yet another object of the present disclosure to provide traffic mapping
system and method that negates the need for unmanned vehicles to process traffic light
images to recognize stated of the traffic light.
SUMMARY
[0018] The present disclosure relates to the field of optimization of efficiency of a
journey of a vehicle. More particularly, the present disclosure relates to systems and methods for mapping traffic.
[0019] An aspect of the present disclosure provides a traffic mapping system. The
system can include: one or more optical sensors configured at one or more road intersections, the one or more road intersections forms part of a map of an area of interest, and the one or more optical sensors configured to capture one or more images of vehicular traffic on each road of a road intersection of the one or more road intersections; and control unit operatively coupled to each of the one or more optical sensors, the control unit comprises one or more processors, the one or more processors coupled with a memory storing instructions executable the one or more processors to: receive the captured one or more images; process

the received one or more images using binary image processing to generate processed one or more images; extract one or more parameters from the processed one or more images, wherein the one or more parameters corresponds to vehicular traffic on the road of the road intersection; compare the one or more parameters with a one or more predefined parameters stored in a first database; and estimate time period required for clearing out the vehicular traffic of the road of the road intersection based on any or a combination of the comparison and the determined extent of vehicular traffic, wherein a traffic map, stored in a second database, of the area of interest is updated based on the estimated time period in real time for each of the roads of the road intersection, wherein based on the updated traffic map of the area the control unit is configured to determine an average velocity a vehicle needs to maintain to avoid traffic congestion while travelling from one position to another position within the area of interest of the map.
[0020] In an embodiment, the one or more predefined parameters comprises, value of
one or more parameters at a time of day, a day of week, a month of year and weather
conditions, wherein the weather condition comprises rain, temperature and fog.
[0021] In an embodiment, the extent of vehicular traffic comprises distance of last
vehicle of the traffic congestion from the first vehicle of the traffic congestion on the road of the road intersection.
[0022] In an embodiment, the binary image processing comprises converting each of
the one or more images into two states.
[0023] In an embodiment, one or more traffic lights are installed at each of the one or
more road intersections, and wherein first time period of each of the one or more traffic lights is synced with the control unit to enable precise estimation of the time period required for clearing out the vehicular traffic of the road of the road intersection.
[0024] Another aspect of the present disclosure provides a method for mapping
traffic, the method includes: capturing, by one or more image sensors, one or more images of vehicular traffic on each road of a road intersection of one or more road intersections, the one or more optical sensors configured at each of the one or more road intersections, the one or more road intersections forms part of a map of an area of interest; receiving, by one or more processors of a control unit, the captured one or more images; processing, by the one or more processors, the received one or more images using binary image processing to generate processed one or more images; extracting, by the one or more processors, one or more parameters from the processed one or more images, wherein the one or more parameters

corresponds to vehicular traffic on the road of the road intersection; comparing, by the one or more processors, the one or more parameters with a one or more predefined parameters stored in a first database; estimating, by the one or more processors, time period required for clearing out the vehicular traffic of the road of the road intersection based on any or a combination of the comparison and the determined extent of vehicular traffic; and updating, by the one or more processors, a traffic map of the area of interest, the traffic map stored in a second database, wherein the traffic map is updated based on the estimated time period in real time for each of the roads of the road intersection.
[0025] In an aspect, the method comprises determining an average velocity a vehicle
needs to maintain while travelling from one position to another position within the area of interest of the map based on the updated traffic map.
[0026] In an aspect, the binary image processing comprises converting and
segregating the received one or more images into two categories: part of road that contains the vehicle; and part of road that does not contain the vehicle.
BRIEF DECRIPTION OF THE DRAWINGS
[0027] In the figures, similar components and/or features may have the same
reference label. Further, various components of the same type may be distinguished by
following the reference label with a second label that distinguishes among the similar
components. If only the first reference label is used in the specification, the description is
applicable to any one of the similar components having the same first reference label
irrespective of the second reference label.
[0028] FIG. 1 illustrates an exemplary network architecture in which or with which
proposed system can be implemented in accordance with an embodiment of the present
disclosure.
[0029] FIG. 2 illustrates an exemplary module diagram for mapping traffic in
accordance with an embodiment of the present disclosure.
[0030] FIG. 3 is a flow diagram illustrating a process for mapping traffic in
accordance with an embodiment of the present disclosure.
[0031] FIGs. 4A and 4B illustrates an exemplary representation of road intersection in
accordance with an embodiment of the present disclosure.

[0032] FIG. 5 illustrates an exemplary computer system in which or with which
embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure.
DETAILED DESCRIPTION
[0033] In the following description, numerous specific details are set forth in order to
provide a thorough understanding of embodiments of the present invention. It will be apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.
[0034] Embodiments of the present invention include various steps, which will be
described below. The steps may be performed by hardware components or may be embodied in machine-executable instructions, which may be used to cause a general-purpose or special-purpose processor programmed with the instructions to perform the steps. Alternatively, steps may be performed by a combination of hardware, software, firmware and/or by human operators.
[0035] Embodiments of the present invention may be provided as a computer
program product, which may include a machine-readable storage medium tangibly embodying thereon instructions, which may be used to program a computer (or other electronic devices) to perform a process. The machine-readable medium may include, but is not limited to, fixed (hard) drives, magnetic tape, floppy diskettes, optical disks, compact disc read-only memories (CD-ROMs), and magneto-optical disks, semiconductor memories, such as ROMs, PROMs, random access memories (RAMs), programmable read-only memories (PROMs), erasable PROMs (EPROMs), electrically erasable PROMs (EEPROMs), flash memory, magnetic or optical cards, or other type of media/machine-readable medium suitable for storing electronic instructions (e.g., computer programming code, such as software or firmware).
[0036] Various methods described herein may be practiced by combining one or more
machine-readable storage media containing the code according to the present invention with appropriate standard computer hardware to execute the code contained therein. An apparatus for practicing various embodiments of the present invention may involve one or more computers (or one or more processors within a single computer) and storage systems containing or having network access to computer program(s) coded in accordance with

various methods described herein, and the method steps of the invention could be
accomplished by modules, routines, subroutines, or subparts of a computer program product.
[0037] If the specification states a component or feature "may", "can", "could", or
"might" be included or have a characteristic, that particular component or feature is not required to be included or have the characteristic.
[0038] As used in the description herein and throughout the claims that follow, the
meaning of "a," "an," and "the" includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of "in" includes "in" and "on" unless the context clearly dictates otherwise.
[0039] Exemplary embodiments will now be described more fully hereinafter with
reference to the accompanying drawings, in which exemplary embodiments are shown. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. These embodiments are provided so that this invention will be thorough and complete and will fully convey the scope of the invention to those of ordinary skill in the art. Moreover, all statements herein reciting embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future (i.e., any elements developed that perform the same function, regardless of structure).
[0040] While embodiments of the present invention have been illustrated and
described, it will be clear that the invention is not limited to these embodiments only. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art, without departing from the spirit and scope of the invention, as described in the claim.
[0041] The present disclosure relates to the field of optimization of efficiency of a
journey of a vehicle. More particularly, the present disclosure relates to systems and methods for mapping traffic.
[0042] An aspect of the present disclosure provides a traffic mapping system. The
system can include: one or more optical sensors configured at one or more road intersections, the one or more road intersections forms part of a map of an area of interest, and the one or more optical sensors configured to capture one or more images of vehicular traffic on each road of a road intersection of the one or more road intersections; and control unit operatively coupled to each of the one or more optical sensors, the control unit comprises one or more

processors, the one or more processors coupled with a memory storing instructions executable the one or more processors to: receive the captured one or more images; process the received one or more images using binary image processing to generate processed one or more images; extract one or more parameters from the processed one or more images, wherein the one or more parameters corresponds to vehicular traffic on the road of the road intersection; compare the one or more parameters with a one or more predefined parameters stored in a first database; and estimate time period required for clearing out the vehicular traffic of the road of the road intersection based on any or a combination of the comparison and the determined extent of vehicular traffic, wherein a traffic map, stored in a second database, of the area of interest is updated based on the estimated time period in real time for each of the roads of the road intersection, wherein based on the updated traffic map of the area the control unit is configured to determine an average velocity a vehicle needs to maintain to avoid traffic congestion while travelling from one position to another position within the area of interest of the map.
[0043] In an embodiment, the one or more predefined parameters comprises, value of
one or more parameters at a time of day, a day of week, a month of year and weather
conditions, wherein the weather condition comprises rain, temperature and fog.
[0044] In an embodiment, the extent of vehicular traffic comprises distance of last
vehicle of the traffic congestion from the first vehicle of the traffic congestion on the road of the road intersection.
[0045] In an embodiment, the binary image processing comprises converting each of
the one or more images into two states.
[0046] In an embodiment, one or more traffic lights are installed at each of the one or
more road intersections, and wherein first time period of each of the one or more traffic lights is synced with the control unit to enable precise estimation of the time period required for clearing out the vehicular traffic of the road of the road intersection.
[0047] Another aspect of the present disclosure provides a method for mapping
traffic, the method includes: capturing, by one or more image sensors, one or more images of vehicular traffic on each road of a road intersection of one or more road intersections, the one or more optical sensors configured at each of the one or more road intersections, the one or more road intersections forms part of a map of an area of interest; receiving, by one or more processors of a control unit, the captured one or more images; processing, by the one or more processors, the received one or more images using binary image processing to generate

processed one or more images; extracting, by the one or more processors, one or more
parameters from the processed one or more images, wherein the one or more parameters
corresponds to vehicular traffic on the road of the road intersection; comparing, by the one or
more processors, the one or more parameters with a one or more predefined parameters
stored in a first database; estimating, by the one or more processors, time period required for
clearing out the vehicular traffic of the road of the road intersection based on any or a
combination of the comparison and the determined extent of vehicular traffic; and updating,
by the one or more processors, a traffic map of the area of interest, the traffic map stored in a
second database, wherein the traffic map is updated based on the estimated time period in real
time for each of the roads of the road intersection.
[0048] In an aspect, the method comprises determining an average velocity a vehicle
needs to maintain while travelling from one position to another position within the area of
interest of the map based on the updated traffic map.
[0049] In an aspect, the binary image processing comprises converting and
segregating the received one or more images into two categories: part of road that contains
the vehicle; and part of road that does not contain the vehicle.
[0050] FIG. 1 illustrates an exemplary network architecture in which or with which
proposed system can be implemented in accordance with an embodiment of the present
disclosure.
[0051] In an aspect, a system 102 implemented in any computing device and can be
configured/operatively connected with a server 108. Further, plurality of optical sensors such
as cameras 106-1, 106-2 106-N (collectively referred to as cameras 106 and individually
referred to as camera 106 hereinafter) can be communicatively coupled to the system 102 through a network 104.
[0052] Further, the network 104 can be a wireless network, a wired network or a
combination thereof. The network 104 can be implemented as one of the different types of networks, such as intranet, local area network (LAN), wide area network (WAN), the internet, Wi-Fi, LTE network, CDMA network, and the like. Further, the network 104 can either be a dedicated network or a shared network. The shared network represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), and the like, to communicate with one

another. Further the network 104 can include a variety of network devices, including routers,
bridges, servers, computing devices, storage devices, and the like.
[0053] In an embodiment, users can register themselves directly with the system 102
using any or a combination of a mobile number, date of birth, place of birth, first name and
last name, a biometric or any other such unique identifier-based input. On successful
registration, the user can be provided with a user name and password which can be used for
accessing the system 102 for providing information.
[0054] In an embodiment, the system 102 can be operatively coupled with the server
108. Further, the server 108 can be used for storing a diagrammatic representation of an area
of land or sea showing physical features, cities, roads, etc. in form of a map of the area.
[0055] In an embodiment, the system 102 can access the map of an area of interest
that can further be accessed by the users on their respective computing devices. In an
embodiment, the system 102 can enable the users to access the map of the area of interest.
[0056] In an embodiment, the cameras 106 can be configured at a road intersection
such that the camera 106 can capture clear and concise one or more images/video of traffic at
the road intersection. In an embodiment, the cameras 106 can be coupled to a street light, a
lamp post, a pillar a pole, a traffic light and the like such that the camera 106 can capture
clear and concise image of traffic.
[0057] In an embodiment, the system 102 can receive the captured images or videos
from the cameras 106 and can store the received images in a database in system or can be
sent to the server 108 for processing.
[0058] In an embodiment, the system 102 can be configured to process the received
images to generate processed images such that one or more features can be extracted from the
received images. The one or more features extracted by the system 102 can correspond to
traffic on the road.
[0059] In an embodiment, the system can be configured to compare the extracted one
or more features with pre-defined features pre-stored on a first database (not shown). It would
be appreciated that the first database can be present on a cloud/ server.
[0060] In an embodiment, the one or more features can include extent of traffic, time
period of the traffic light turning Green for indicating passage of traffic. Further, the
predefined one or more features can include values of the one or more features for following
conditions such as day of week (weekday or weekend), month of year, time of day (peak

work hours or casual hours), holiday (if any), weather (rain, hot, cold, fog), length of traffic etc.
[0061] In an embodiment, the first database and/or a second database (not shown) can
be used for storing the predefined one or more features. The system can be further configured to update the predefined one or more features after certain time period so that the efficiency of the system 102 can increase with time.
[0062] In an embodiment, based on of the comparison the system 102 can be used for
estimating or predicting time period required to clear out congestion of the traffic at the road
intersection. In an embodiment, the time period associated with the traffic lights can be
synced after certain predefined time period with the system 102 so that the changing of the
time period associated the traffic lights does not affect the efficiency of the system 102.
Further, based on the determined time period for clearing out the traffic congestion can be
stored on first database and/or the second database. Further, the system 102 can be configured
to update determined traffic information related to time period for clearing out traffic
congestion in real time with the map stored on the system 102 or the server 108.
[0063] In an embodiment, the map of the area of the interest can have one or more
road intersections and the one or more road intersections can have one or more cameras 106 configured/installed at the road intersection to capture clear and concise image of each and every road of the road intersection. Now, the map can be updated with the traffic information being determined by the system in real time such that a live update of traffic at every road intersection is updated on the traffic map.
[0064] In an embodiment, the system 102 can be configured to determine an average
velocity a vehicle needs to maintain to avoid traffic congestion while travelling from one position to another position within the area of interest of the map. For example, if the user intends to travel from place A to place B on the map of the area of interest then the user can access the system and request for the guidance assistance. The system 102 can generate a route for travelling from point A to point B and further can provide an estimate of velocity that the vehicle needs to maintain while manoeuvring through the route to avoid and/or minimize traffic congestion while following the given route.
[0065] Although in various embodiments, the implementation of system 102 is
explained with regard to the server 108, those skilled in the art would appreciate that, the system 102 can fully or partially be implemented in other computing devices operatively

coupled with network 104 such as user devices 102 with minor modifications, without departing from the scope of the present disclosure.
[0066] FIG. 2 illustrates an exemplary module diagram for mapping traffic in
accordance with an embodiment of the present disclosure.
[0067] In an aspect, module diagram 200 of the system 102 may comprise one or
more processor(s) 202. The one or more processor(s) 202 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processor(s) 202 are configured to fetch and execute computer-readable instructions stored in a memory 206 of the system 102. The memory 206 may store one or more computer-readable instructions or routines, which may be fetched and executed to create or share the data units over a network service. The memory 206 may comprise any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0068] The system 102 may also comprise an interface(s) 204. The interface(s) 204
may comprise a variety of interfaces, for example, interfaces for data input and output
devices, referred to as I/O devices, storage devices, and the like. The interface(s) 204 may
facilitate communication of system 102. The interface(s) 204 may also provide a
communication pathway for one or more components of the system 102. Examples of such
components include, but are not limited to, processing engine(s) 208 and data 210.
[0069] The processing engine(s) 208 may be implemented as a combination of
hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) 208. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) 208 may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) 208 may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) 208. In such examples, the system 102 may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but

accessible to system 102 and the processing resource. In other examples, the processing
engine(s) 208 may be implemented by electronic circuitry.
[0070] The data 210 may comprise data that is either stored or generated as a result of
functionalities implemented by any of the components of the processing engine(s) 208 or the
system 102.
[0071] In an exemplary embodiment, the processing engine(s) 208 may include an
image processing engine 212, an image-based feature extraction engine 214, a time period
estimation engine 216, a traffic map updating engine 218, and a speed recommending engine
220 and other engine(s) 222.
[0072] In an embodiment, the cameras 106 can be used for capturing one or more
images and/or video of the road. The captured one or more images or the video can be
received and the image processing engine 212 can be configured to process the received one
or more images to generate the processing images.
[0073] The processing can include binary processing of the received one or more
images wherein, the received one or more images can be converted and/or segregated in to
two states: one that includes the part of the road where the vehicle is present and other
includes the part of the road that does not have the vehicle on it.
[0074] In an embodiment, the image-based feature extraction engine 214 can extract
one or more features from the processed images. The one or more features can include
features related to traffic on the road. Further, the one or more features can be used for
determining if the part of the road captured in the images has any vehicle or the road is
empty.
[0075] In an embodiment, the image-based feature extraction engine 214 can store the
extracted one or more features on a first database that can be internally or externally coupled
with the image-based feature extraction engine 214. It would be appreciated that the first
database can be present on a cloud/ server.
[0076] In an embodiment, the time period estimation engine 216 can be used for
comparing the extracted one or more features with one or more predefined features stored in
any or a combination of the first database and a second database.
[0077] In an embodiment, the one or more features can include extent of traffic, time
period of the traffic light turning Green for indicating passage of traffic. Further, the
predefined one or more features can include values of the one or more features for following
conditions such as day of week (weekday or weekend), month of year, time of day (peak

work hours or casual hours), holiday (if any), weather (rain, hot, cold, fog), length of traffic
etc.
[0078] In an embodiment, the first database and/or a second database (not shown) can
be used for storing the predefined one or more features.
[0079] In an embodiment, based on the comparison the time period estimation engine
216 can be used for estimating or predicting time period required to clear out congestion of
the traffic at the road intersection. In an embodiment, the time period associated with the
traffic lights can be synced after certain predefined time period with the system 102 so that
the changing of the time period associated the traffic lights does not affect the efficiency of
the system 102.
[0080] In an embodiment, the traffic map updating engine 218 can be used for
updating the determined traffic information related to time period for clearing out traffic
congestion in real time with the map stored on the system 102 or the server 108.
[0081] In an embodiment, the traffic map updating engine 218 can access the map of
an area of interest that can further be accessed by the users on their respective computing
devices. In an embodiment, the system 102 can enable the users to access the map of the area
of interest.
[0082] In an embodiment, the speed recommending engine 220 can be used for
recommending the velocity that the vehicle needs to maintain throughout the journey for
travelling from one position to another position on the map of the area of interest while
manoeuvring through the route to avoid any traffic congestion. Further, the speed
recommending engine 220 can be used for optimizing the route that the vehicle need to
follow.
[0083] It would be appreciated by the person skilled in the art that the system 102 can
be configured for checking other route options for a given ride or travel and can provide an
option to the user of choosing a different route.
[0084] For example, if user is travelling from point A to point B on the map of the
area of interest with speed 50 kmph and the system 102 is able to determine a route where the
recommended speed is 60 kmph then the system 102 will provide an option to the user for
selection.
[0085] FIG. 3 is a flow diagram illustrating a process for mapping traffic in
accordance with an embodiment of the present disclosure.

[0086] In an aspect, the proposed method may be described in general context of
computer executable instructions. Generally, computer executable instructions can include
routines, programs, objects, components, data structures, procedures, modules, functions,
etc., that perform particular functions or implement particular abstract data types. The method
can also be practiced in a distributed computing environment where functions are performed
by remote processing devices that are linked through a communications network. In a
distributed computing environment, computer executable instructions may be located in both
local and remote computer storage media, including memory storage devices.
[0087] The order in which the method as described is not intended to be construed as
a limitation, and any number of the described method blocks may be combined in any order to implement the method or alternate methods. Additionally, individual blocks may be deleted from the method without departing from the spirit and scope of the subject matter described herein. Furthermore, the method may be implemented in any suitable hardware, software, firmware, or combination thereof. However, for ease of explanation, in the embodiments described below, the method may be considered to be implemented in the above described system.
[0088] In context of flow diagram 300, at block 302, one or more optical sensors can
be used for capturing one or more images of vehicular traffic on each road of a road intersection of one or more road intersections, the one or more optical sensors configured at each of the one or more road intersections, the one or more road intersections forms part of a map of an area of interest. Further, at block 304 one or more processors of a control unit can be used for receiving the captured one or more images. Further, block 306 pertains to processing the received one or more images using binary image processing to generate processed one or more images.
[0089] In an embodiment, block 308 pertains to extracting one or more parameters
from the processed one or more images, wherein the one or more parameters corresponds to vehicular traffic on the road of the road intersection. Further, block 310 pertains to comparing the one or more parameters with a one or more predefined parameters stored in a first database. Further, block 312 pertains to estimating time period required for clearing out the vehicular traffic of the road of the road intersection based on any or a combination of the comparison and the determined extent of vehicular traffic. Furthermore, block 314 pertains to updating a traffic map of the area of interest, the traffic map stored in a second database,

wherein the traffic map is updated based on the estimated time period in real time for each of the roads of the road intersection.
[0090] In an embodiment, FIGs. 4A and 4B illustrates an exemplary representation of
road intersection in accordance with an embodiment of the present disclosure. In an exemplary embodiment, the road intersection can have four cameras 402-1, 402-2, 402-3 and 402-4. Each of the four cameras 402-1, 402-2, 402-3 and 402-4 can be coupled with the four traffic lights. Further, the cameras can be used for capturing the images of traffic 406 on the road. Now, the system can process the captured images to determine the extent of traffic that can be used for determining/predicting time period required for clearing out congestion at the road intersection for each of the roads of the road intersection.
[0091] FIG. 5 illustrates an exemplary computer system in which or with which
embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure.
[0092] As shown in FIG. 5, computer system 500 can include an external storage
device 510, a bus 520, a main memory 530, a read only memory 540, a mass storage device 550, communication port 560, and a processor 570. A person skilled in the art will appreciate that computer system may include more than one processor and communication ports. Examples of processor 570 include, but are not limited to, an Intel® Itanium® or Itanium 2 processor(s), or AMD® Opteron® or Athlon MP® processor(s), Motorola® lines of processors, FortiSOC™ system on a chip processors or other future processors. Processor 570 may include various modules associated with embodiments of the present invention. Communication port 560 can be any of an RS-232 port for use with a modem based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. Communication port 560 may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which computer system connects.
[0093] Memory 530 can be Random Access Memory (RAM), or any other dynamic
storage device commonly known in the art. Read only memory 540 can be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or BIOS instructions for processor 570. Mass storage 550 may be any current or future mass storage solution, which can be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced

Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external,
e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), e.g. those available from
Seagate (e.g., the Seagate Barracuda 7102 family) or Hitachi (e.g., the Hitachi Deskstar
7K1000), one or more optical discs, Redundant Array of Independent Disks (RAID) storage,
e.g. an array of disks (e.g., SATA arrays), available from various vendors including Dot Hill
Systems Corp., LaCie, Nexsan Technologies, Inc. and Enhance Technology, Inc.
[0094] Bus 520 communicatively couples processor(s) 570 with the other memory,
storage and communication blocks. Bus 520 can be, e.g. a Peripheral Component
Interconnect (PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI),
USB or the like, for connecting expansion cards, drives and other subsystems as well as other
buses, such a front side bus (FSB), which connects processor 570 to software system.
[0095] Optionally, operator and administrative interfaces, e.g. a display, keyboard,
and a cursor control device, may also be coupled to bus 520 to support direct operator interaction with computer system. Other operator and administrative interfaces can be provided through network connections connected through communication port 560. External storage device 510 can be any kind of external hard-drives, floppy drives, IOMEGA® Zip Drives, Compact Disc - Read Only Memory (CD-ROM), Compact Disc - Re-Writable (CD-RW), Digital Video Disk - Read Only Memory (DVD-ROM). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[0096] Embodiments of the present disclosure may be implemented entirely
hardware, entirely software (including firmware, resident software, micro-code, etc.) or
combining software and hardware implementation that may all generally be referred to herein
as a "circuit," "module," "component," or "system." Furthermore, aspects of the present
disclosure may take the form of a computer program product comprising one or more
computer readable media having computer readable program code embodied thereon.
[0097] Thus, it will be appreciated by those of ordinary skill in the art that the
diagrams, schematics, illustrations, and the like represent conceptual views or processes illustrating systems and methods embodying this invention. The functions of the various elements shown in the figures may be provided through the use of dedicated hardware as well as hardware capable of executing associated software. Similarly, any switches shown in the figures are conceptual only. Their function may be carried out through the operation of program logic, through dedicated logic, through the interaction of program control and

dedicated logic, or even manually, the particular technique being selectable by the entity implementing this invention. Those of ordinary skill in the art further understand that the exemplary hardware, software, processes, methods, and/or operating systems described herein are for illustrative purposes and, thus, are not intended to be limited to any particular named.
[0098] As used herein, and unless the context dictates otherwise, the term "coupled
to" is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms "coupled to" and "coupled with" are used synonymously. Within the context of this document terms "coupled to" and "coupled with" are also used euphemistically to mean "communicatively coupled with" over a network, where two or more devices are able to exchange data with each other over the network, possibly via one or more intermediary device.
[0099] It should be apparent to those skilled in the art that many more modifications
besides those already described are possible without departing from the inventive concepts herein. The inventive subject matter, therefore, is not to be restricted except in the spirit of the appended claims. Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms "comprises" and "comprising" should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refers to at least one of something selected from the group consisting of A, B, C .... and N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.
[00100] While the foregoing describes various embodiments of the invention, other and
further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE PRESENT DISCLOSURE
[00101] The present disclosure provides traffic mapping system and method.
[00102] The present disclosure provides traffic mapping system and method that can
assist in enhancing user driving/riding vehicle experience by avoiding unnecessary traffic
congestions
[00103] The present disclosure provides traffic mapping system and method that can
help enhancing fuel efficiency of a vehicle because of traffic congestion.
[00104] The present disclosure provides traffic mapping system and method that can be
used for reducing controlling requirement for unmanned vehicles.
[00105] The present disclosure provides traffic mapping system and method that can be
used by the government for better management of traffic.
[00106] The present disclosure provides traffic mapping system and method that can
assist users avoiding accidents when traffic lights are faulty or visibility of the traffic lights is
reduced.
[00107] The present disclosure provides traffic mapping system and method that
negates the need for unmanned vehicles to process traffic light images to recognize stated of
the traffic light.

We Claim:

1. A traffic mapping system, said system comprising:
one or more optical sensors configured at one or more road intersections, the one or more road intersections forms part of a map of an area of interest, and the one or more optical sensors configured to capture one or more images of vehicular traffic on each road of a road intersection of the one or more road intersections; and
control unit operatively coupled to each of the one or more optical sensors, the control unit comprises one or more processors, the one or more processors coupled with a memory storing instructions executable the one or more processors to: receive the captured one or more images;
process the received one or more images using binary image processing to generate processed one or more images;
extract one or more parameters from the processed one or more images, wherein the one or more parameters corresponds to vehicular traffic on the road of the road intersection;
compare the one or more parameters with a one or more predefined parameters stored in a first database; and
estimate time period required for clearing out the vehicular traffic of the
road of the road intersection based on any or a combination of the comparison
and the determined extent of vehicular traffic,
wherein a traffic map, stored in a second database, of the area of interest is updated
based on the estimated time period in real time for each of the roads of the road
intersection,
wherein based on the updated traffic map of the area the control unit is configured to determine an average velocity a vehicle needs to maintain to avoid traffic congestion while travelling from one position to another position within the area of interest of the map.
2. The system as claimed in claim 1, wherein the one or more predefined parameters
comprises, value of one or more parameters at a time of day, a day of week, a month of
year and weather conditions, wherein the weather condition comprises rain, temperature
and fog.
3. The system as claimed in claim 1, wherein the extent of vehicular traffic comprises distance of last vehicle of the traffic congestion from the first vehicle of the traffic congestion on the road of the road intersection.
4. The system as claimed in claim 1, wherein the binary image processing comprises converting each of the one or more images into two states.
5. The system as claimed in claim 1, wherein one or more traffic lights are installed at each of the one or more road intersections, and wherein first time period of each of the one or more traffic lights is synced with the control unit to enable precise estimation of the time period required for clearing out the vehicular traffic of the road of the road intersection.
6. A method for mapping traffic, said method comprises:
capturing, by one or more image sensors, one or more images of vehicular traffic on each road of a road intersection of one or more road intersections, the one or more optical sensors configured at each of the one or more road intersections, the one or more road intersections forms part of a map of an area of interest;
receiving, by one or more processors of a control unit, the captured one or more images;
processing, by said one or more processors, the received one or more images using binary image processing to generate processed one or more images;
extracting, by said one or more processors, one or more parameters from the processed one or more images, wherein the one or more parameters corresponds to vehicular traffic on the road of the road intersection;
comparing, by said one or more processors, the one or more parameters with a one or more predefined parameters stored in a first database;
estimating, by said one or more processors, time period required for clearing out the vehicular traffic of the road of the road intersection based on any or a combination of the comparison and the determined extent of vehicular traffic; and
updating, by said one or more processors, a traffic map of the area of interest, the traffic map stored in a second database, wherein the traffic map is updated based on the estimated time period in real time for each of the roads of the road intersection.
7. The method as claimed in claim 6, wherein the method comprises determining an
average velocity a vehicle needs to maintain while travelling from one position to
another position within the area of interest of the map based on the updated traffic map.
8. The method as claimed in claim 6, wherein one or more traffic lights are installed at each of the one or more road intersections, and wherein first time period of each of the one or more traffic lights is synced with the control unit to enable precise estimation of the time period required for clearing out the vehicular traffic of the road of the road intersection.
9. The method as claimed in claim 6, wherein the one or more predefined parameters comprises, value of one or more parameters at a time of day, a day of week, a month of year and weather conditions, wherein the weather condition comprises rain, temperature and fog.
10. The method as claimed in claim 6, wherein the extent of vehicular traffic comprises distance of last vehicle of the traffic congestion from the first vehicle of the traffic congestion on the road of the road intersection.