[001] The present application does not claim priority from any patent application.
TECHNICAL FIELD
[002] The present disclosure in general relates to the field of communication. More particularly, the present subject matter relates to a system and a method for determining a length of traffic congestion in front of a vehicle.
BACKGROUND
[003] Traffic congestion is a condition on transport networks that occurs as use increases, and is characterized by slower speeds, longer trip times, and increased vehicular queueing. The most common example is the physical use of roads by vehicles. When traffic demand is great enough that the interaction between vehicles slows the speed of the traffic stream, this results in some congestion. As demand approaches the capacity of a road, extreme traffic congestion sets in. When vehicles are fully stopped for long time, this is colloquially known as a traffic jam or traffic snarl-up. Typically, traffic congestion can lead to drivers becoming frustrated and engaging in road rage.
[004] Generally, a traffic congestion had been a major problem primarily in urban areas as it consumes many productive hours of commuters and creates mental stress & frustration. Moreover, traffic congestions also leads to wasted fuel increasing air pollution and carbon dioxide emissions owing to increased idling, acceleration and braking. Typically, conventional system and methods provide real time traffic info on different routes in term of green, orange or red so as to enable a commuter determine the route he/she wants to opt for a trip. However, most of such conventional system and methods demand the internet connectivity on the devices via GSM/GPRS. In addition, the conventional system and methods fail to provide various parameters associated with the traffic congestion in real time.
SUMMARY
[005] Before the present a system and a method for determining a length of traffic congestion in front of a vehicle, are described, it is to be understood that this application is not limited to the particular system, systems, and methodologies described, as there can be multiple possible embodiments, which are not expressly illustrated in the present disclosures. It is also to be understood that the terminology used in the description is for the purpose of describing the particular implementations, versions, or embodiments only, and is not intended to limit the scope of the present application. This summary is provided to introduce aspects related to a system and a method for determining a length of traffic congestion in front of a vehicle. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.
[006] In one embodiment, a method for determining a length of traffic congestion in front of a vehicle is disclosed. In the embodiment, the method may comprise receiving data from a first set other vehicle. In one example, the data may be received over a vehicle-to-vehicle communication network by a Dedicated Short Range Communication (DSRC) module installed in a vehicle. In one other example, the data may comprise one or more of a message type, a GPS location of the other vehicles, a traffic length ahead of the other vehicle, a time elapsed in the traffic congestion, and a cause of traffic congestion. Upon receiving, the method may comprise determining if the vehicle is within the traffic congestion based on comparison of an average speed of the vehicle with a predetermined threshold for a predetermined time duration and identifying a second set of other vehicles, ahead of the vehicle and moving in the direction of the vehicle, from the first set of other vehicles. In one example, the second set of other vehicles may be identified based on a comparison of the GPS location of the vehicle and the GPS location of each of the first set of other vehicles. Further to identifying, the method comprises identifying target data from the data based on the second set of other vehicles, computing, by the processor, at a length of traffic congestion in front of the vehicle based on the target data and a total time required to travel the traffic congestion based on the length of traffic congestion and an average speed of traffic congestion.
[007] In another embodiment, a system for determining a length of traffic congestion in front of a vehicle is disclosed. The system comprises a memory and a processor coupled to the memory, further the processor may be configured to execute programmed instructions stored in the memory. In one embodiment, the system may receive data from a first set other vehicle. In one example, the data may be received over a vehicle-to-vehicle communication network by a Dedicated Short Range Communication (DSRC) module installed in a vehicle. In one other example, the data may comprise one or more of a message type, a GPS location of the other vehicle, a traffic length ahead of the other vehicle, a time elapsed in the traffic congestion, and a cause of traffic congestion. Upon receiving, the system may determine if the vehicle is within the traffic congestion based on comparison of an average speed of the vehicle with a predetermined threshold for a predetermined time duration and identify a second set of other vehicles, ahead of the vehicle and moving in the direction of the vehicle, from the first set of other vehicles. In one example, the second set of other vehicles may be identified based on a comparison of the GPS location of the vehicle and the GPS location of each of the first set of other vehicles. Further to identifying, the system may identify target data from the data based on the second set of other vehicles, and compute a length of traffic congestion in front of the vehicle based on the target data and a total time required to travel the traffic congestion based on the length of traffic congestion and an average speed of traffic congestion.
BRIEF DESCRIPTION OF DRAWINGS
[008] The foregoing detailed description of embodiments is better understood when read in conjunction with the appended drawings. For the purpose of illustrating of the present subject matter, an example of construction of the present subject matter is provided as figures; however, the present subject matter is not limited to the specific method and system disclosed in the document and the figures.
[009] The present subject matter is described detail with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to refer various features of the present subject matter.
[0010] Figure 1A illustrates an embodiments of a network implementation of a system for determining a length of traffic congestion in front of a vehicle, in accordance with an embodiment of the present subject matter.
[0011] Figure 1B illustrates another embodiments of a network implementation of a system for determining a length of traffic congestion in front of a vehicle, in accordance with an embodiment of the present subject matter.
[0012] Figure 1C illustrates an example for computing a length of traffic congestion in front of a vehicle, in accordance with an embodiment of the present subject matter.
[0013] Figure 1D illustrates an example for identifying a second set of other vehicle, in accordance with an embodiment of the present subject matter.
[0014] Figure 1E an example for identifying a third set of other vehicles, in accordance with an embodiment of the present subject matter.
[0015] Figure 2 illustrates the system for determining a length of traffic congestion in front of a vehicle, in accordance with an embodiment of the present subject matter.
[0016] Figure 3 illustrates a method for determining a length of traffic congestion in front of a vehicle, in accordance with an embodiment of the present subject matter.
DETAILED DESCRIPTION
[0017] Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words "comprising," "having," "containing," and "including," and other forms thereof, are intended to be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Although any a system and a method for determining a length of traffic congestion in front of a vehicle, similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the exemplary, a system and a method for determining a length of traffic congestion in front of a vehicle are now described.
[0018] Various modifications to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to other embodiments for determining a length of traffic congestion in front of a vehicle. However, one of ordinary skill in the art will readily recognize that the present disclosure for determining a length of traffic congestion in front of a vehicle is not intended to be limited to the embodiments described, but is to be accorded the widest scope consistent with the principles and features described herein.
[0019] The present subject matter relates to a system and method for determining a length of traffic congestion in front of a vehicle. In another embodiment, data may be received from a first set other vehicle. In one example, the data may be received over a vehicle-to-vehicle communication network by a Dedicated Short Range Communication (DSRC) module installed in a vehicle. In one other example, the data may comprise one or more of a message type, a GPS location of the other vehicle, a traffic length ahead of the other vehicle, a time elapsed in the traffic congestion, and a cause of traffic congestion. Further to receiving, it may be determined if the vehicle is within the traffic congestion based on comparison of an average speed of the vehicle with a predetermined threshold for a predetermined time duration. Upon determining, a second set of other vehicles, ahead of the vehicle and moving in the direction of the vehicle, from the first set of other vehicles and target data from the data based on the second set of other vehicles may be identified, wherein the second set of other vehicles is identified based on a comparison of the GPS location of the vehicle and the GPS location of each of the first set of other vehicles. In one example, the target data may be associated with the second set of other vehicles. Subsequent to identifying, a length of traffic congestion in front of the vehicle may be computed based on the target data and a total time required to travel the traffic congestion based on the length of traffic congestion and an average speed of traffic congestion.
[0020] Referring now to Figure 1A, an embodiment of a network implementation 100 of a system 102 for determining a length of traffic congestion in front of a vehicle 108, is disclosed. Referring now to Figure 1B, another embodiment of a network implementation of a system 102 for determining a length of traffic congestion in front of a vehicle108, is disclosed. Although the present subject matter is explained considering that the system 102 is implemented on a Dedicated Short Range Communication (DSRC) module 106 installed within one or more vehicles 108, 110, 112, and 114. Further, the present subject has been explained considering one of the vehicle 108, but it may be understood that any/all vehicles 108, 110, 112, and 114 comprising the DSRC module 106 may be capable of performing the present subject matter.
[0021] It will be understood that multiple users may access the system 102 through one or more user device or applications residing on the user device 104-1… 104-N, herein after individually or collectively referred to as 104. Examples of the user device 104 may include, but are not limited to, a portable computer, a personal digital assistant, a handheld system, in care entertain system, in car navigation system and a workstation.
[0022] Further, in the embodiment, the vehicles 108, 110-1… 110-N, 112-1….112-N, and 114-1…. 114-N may be configured to communicate with each other using the DSCR module 106 via a vehicle-to-vehicle communication framework. In one example, different types of protocols may be utilized in v2v communication such as 802.11p. Further, the DSRC module 106 with 802.11p protocol may provide a range of ~1000m.
[0023] In the embodiment, a system 102 for determining a length of traffic congestion in front of a vehicle 108 is disclosed. In the said embodiment, the system 120 may reive data from a first set other vehicle 110-1… 110-N and 112-1….112-N, 114-1…. 114-N. In one example, a Dedicated Short Range Communication (DSRC) module 106 installed in a vehicle 108 receives the data over a vehicle-to-vehicle communication network. In one more example, the data may comprise one or more of a message type, a GPS location of the other vehicle 110-1… 110-N, 112-1….112-N, and 114-1…. 114-N, a traffic length ahead of the other vehicle 110-1… 110-N, 112-1….112-N, and 114-1…. 114-N, a time elapsed in the traffic congestion, and a cause of traffic congestion. Upon receiving, the system 102 may determine if the vehicle 108 is within the traffic congestion based on comparison of an average speed of the vehicle 108 with a predetermined threshold for a predetermined time duration. Further to determination, the system may identify a second set of other vehicles vehicle 110-1… 110-N, and 112-1….112-N ahead of the vehicle and moving in the direction of the vehicle, from the first set of other vehicles. IN one example, the second set of other vehicles 110-1… 110-N, and 112-1….112-N may be identified based on a comparison of the GPS location of the vehicle 108 and the GPS location of each of the first set of other vehicles 110-1… 110-N, 112-1….112-N, and 114-1…. 114-N. Subsequently, the system 102 may identify target data from the data based on the second set of other vehicles 110-1… 110-N, and 112-1….112-N. Finally, the system 102 may compute a length of traffic congestion in front of the vehicle 108 based on the target data and a total time required to travel the traffic congestion based on the length of traffic congestion and an average speed of traffic congestion.
[0024] In one example, the average speed of the traffic congestion may be received by the system 102 from a vehicle exiting the traffic congestion 110. In the example of receiving, the vehicle exiting the traffic congestion 110 may compute the average speed of traffic congestion based on a length of traffic congestion travelled by the vehicle exiting the traffic congestion and time taken to travel the length. In one other example, the system 102 may compute the average speed of traffic congestion based on the total length travelled by the vehicle 108 (itself) in the traffic congestion in a predefined time interval for example 15 min. In one more example, the system 102 may take an average of the average speed of traffic congestion received from the vehicle 110 exiting the traffic congestion and the average speed of traffic congestion computed by itself 108.
[0025] Referring now to Figure 1C, an example for computing a length of traffic congestion in front of a vehicle, is disclosed. Refereeing to Figure 1D an example for identifying a second set of other vehicle, is disclosed. Referring to Figure 1E an example for identifying a third set of other vehicles, is disclosed. Referring now to Figure 2, the system 102 for determining a length of traffic congestion in front of a vehicle is illustrated in accordance with an embodiment of the present subject matter. It must be noted that the subsequent section the present subject is described referring the Figure 1C, Figure 1D, Figure 1E, and Figure 2.
[0026] In the embodiment, the system 102 may include at least one processor 202, an input/output (I/O) interface 204, and a memory 206. The at least one processor 202 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any systems that manipulate signals based on operational instructions. Among other capabilities, at least one processor 202 may be configured to fetch and execute computer-readable instructions stored in the memory 206.
[0027] The I/O interface 204 may include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface, and the like. The I/O interface 204 may allow the system 102 to interact with the user directly or through the user device 104. Further, the I/O interface 204 may enable the system 102 to communicate with other computing systems, such as web servers and external data servers (not shown). The I/O interface 204 may facilitate multiple communications within a wide variety of networks and protocol types, including wired networks, for example, LAN, cable, etc., and wireless networks, such as WLAN, cellular, or satellite. The I/O interface 204 may include one or more ports for connecting a number of systems to one another or to another server.
[0028] The memory 206 may include any computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes. The memory 206 may include modules 208 and data 210.
[0029] The modules 208 may include routines, programs, objects, components, data structures, and the like, which perform particular tasks, functions or implement particular abstract data types. In one implementation, the module 208 may include a receiving module 212, a determination module 214, an identification module 216, a computation module 218, a transmission 220 and other modules 224. The other modules 224 may include programs or coded instructions that supplement applications and functions of the system 102.
[0030] The data 210, amongst other things, serve as a repository for storing data processed, received, and generated by one or more of the modules 208. The data 210 may also include a system data 226, and other data 228. In one embodiment, the other data 228 may include data generated because of the execution of one or more modules in the other module 224.
[0031] In one implementation, a user may access the system 102 via the I/O interface 204. The user may be registered using the I/O interface 204 in order to use the system 102. In one aspect, the user may access the I/O interface 204 of the system 102 for obtaining information, providing inputs or configuring the system 102.
[0032] In the implementation, the receiving module 212 may receiving data from a first set other vehicle. In one example, the data may be received over a vehicle to vehicle communication network by a Dedicated Short Range Communication (DSRC) module installed in a vehicle. In the example, the data comprises one or more of a message type such as traffic congestion or no congestion, a GPS location of the other vehicle such as latitude and longitude, a traffic length ahead of the other vehicle, a time elapsed in the traffic congestion, and a cause of traffic congestion such as accident.
[0033] Upon receiving the data, the determination module 214 may determine if the vehicle is within the traffic congestion based on comparison of an average speed of the vehicle with a predetermined threshold for a predetermined time duration. In one example, the predetermined threshold of the average speed may be 10 km/hour and predetermined time may be 15 minutes. In the implementation, the determination module 214 may determine one of in traffic congestion or out of traffic congestion.
[0034] In one other example, the determination module 214 may determine the vehicle is within the traffic congestion based on the signal from an initiator vehicle. In the embodiment, the initiator vehicle may be configured to initiate a signal data indicative of a start of a traffic congestion. In one example, the initiator vehicle may be understood as the vehicle closest to the cause of traffic congestion or the vehicle about to exist the traffic congestion or the vehicle that detects the traffic congestion first.
[0035] Further to determination, the transmission module 220 may transmit a message using the Dedicated Short Range Communication (DSRC) module if the vehicle is determined to be in the traffic congestion. In one example, the message comprises at least one of a GPS location of the vehicle, type of message and current speed. In one example, in the first instance of transmission by the transmission module 220 after determination of being in the traffic congestion, may not include or include zero as a length of traffic before the vehicle. In one example, the zero or no traffic length may be transmitted when it is the first transmission.
[0036] In the implementation, upon determination, the identification module 216 may identify a second set of other vehicles, ahead of the vehicle and moving in the direction of the vehicle from the first set of other vehicles. In one example, the second set of other vehicles may be identified based on a comparison of the GPS location of the vehicle and the GPS location of each of the first set of other vehicles. Subsequently, the identification module 216 may identify target data from the data based on the second set other vehicles.
[0037] Further, the identification module 216 may compute an angle between the second set of other vehicles and the vehicle based on the comparison of the GPS location of the vehicle and the GPS location of each of the first set of other vehicles and determining a third set of other vehicles from the second set of other vehicles based on a comparison of the angel with a predefined threshold angel for example 10o degree. (as shown in figure 1D, and 1E) In one example, the third set of other vehicle may comprises vehicles that are within 10o degree angle of the vehicle. Subsequently, the identification module 216 may filter the target data based on the third set of other vehicles.
[0038] In the implementation, upon identifying the target data the computation module 218, may compute a length of traffic congestion in front of the vehicle based on the target data and on the filtered target data. In one example, the computation module 218 may use the equation 1 to 5, and as illustrated in fig 1C, for computing the length.
dlat = lat2 - lat1 …………. (1)
dlon = lon2 - lon1 …………. (2)
A = (sin (dlat/2)) ^2 + cos (lat1) * cos (lat2) * sin (dlon/2)) ^2 …………. (3)
C = 2* atan2 (sqrt (A), sqrt (1-A)) …………. (4)
D = R * C ………….. (5)
Wherein:
(lat1, lon1): latitude and longitude of other vehicle
(lat2, lon2): latitude and longitude of the vehicle
R: earth radius in kilometre.
D: distance.
[0039] In one other implementation, the computation module 218 may also compute an average speed of the traffic congestion based on the length of traffic congestion and a total time required to travel the length of traffic congestion. In one example, the average speed of the traffic congestion may be received from a vehicle exiting the traffic congestion. In the example, the vehicle exiting the traffic congestion may compute the average speed of the traffic congestion based on the length of the traffic congestion cover by the exiting vehicle, and the time taken to cover the length.
[0040] In one more implementation, the receiving module 212 may receive an average speed of the traffic congestion, and a cause of the traffic congestion from at least one of the second set of other vehicles or from a vehicle exiting the traffic congestion. In one other example, the receiving module 212 may receive an average speed of the traffic congestion, from more than one of the second set of other vehicles. In such example, the receiving module 212 may compute and average of all the received average speed of the traffic congestion for further computation. Further to receiving, the computation module 218 may compute the total time required by the vehicle to travel the traffic congestion based on the average speed of the traffic congestion and the length of the traffic congestion.
[0041] Construe an example, where the vehicle receives, GPS co-ordinates, length of traffic congestion equal to 1 KM and average speed of the traffic congestion is 05 Km/h from one of the other vehicles. In the example, computing module 218 may compute a distance between the other vehicle and the vehicle utilizing GPS data and the equations 1 to 5, for example, distance is 20m. The computation module 218 may compute a length in front of itself using the distance and the length of traffic congestion in from of the other vehicle for example 1.02Km or 1020m. Further the computation module 218 may compute the approx. time to clear the jam can be calculated as below:
Time = distance/avg speed ………….. (6)
Time = 1.02/05 hr. or 1020/1.38 s ………….. (7)
Time = 739 s or 12 minute ………….. (8)
Approx. time is 12 minute to clear the traffic. ………….. (9)
[0042] Further to computing, the computation module 218 may display the total time required, the length of traffic congestion in front of the vehicle, and the cause to a driver of the vehicle.
[0043] Upon computing, the transmission 220 may transmit the congestion data associated with the vehicle using the Dedicated Short Range Communication (DSRC) module installed in the vehicle. In one example, the congestion data may comprise one or more of a message type, a GPS location of the other vehicle, the length of traffic congestion in front of the vehicle, a time elapsed in the traffic congestion, a cause of traffic congestion and the average speed of the traffic congestion. In one example, a vehicle approaching the traffic congestion may utilize the congestion data for taking an alternate route.
[0044] In one other implementation, the Dedicated Short Range Communication (DSRC) module may be configured to transmit and receive at a predefined time interval, and at a predefined transmission power for optimizing the DSRC module. In one example, the frequency of broadcast by a DSRC module may defined for example10 seconds that is each DSRC module will broadcast the packet every 10 seconds. In one other example, the packet receiving / processing frequency may be defined for example 10 seconds i.e. if the DSRC module receives a packet before 10 seconds of last processing, it will discard the same. In one more example, the transmission power of the DSRC module may be limited.
[0045] Exemplary embodiments for determining a length of traffic congestion in front of a vehicle discussed above may provide certain advantages. Though not required to practice aspects of the disclosure, these advantages may include those provided by the following features.
[0046] Some embodiments of the system and the method reduction in wastage time of motorists and passengers.
[0047] Some embodiments of the system and the method enable forecasting travel time accurately.
[0048] Some embodiments of the system and the method enables accurate and efficient prescription processing.
[0049] Some embodiments of the system and the method enables reduction in fuel wastage, air pollution and carbon dioxide emissions due to decreased idling, acceleration and braking.
[0050] Some embodiments of the system and the method enables reduction in Wear and tear on vehicles because of decreased idling in traffic and frequent acceleration and braking.
[0051] Some embodiments of the system and the method enables reduction in Stressed and frustrated motorists, road rage.
[0052] Some embodiments of the system and the method enables forecasting and effective delivery of emergency services during traffic congestion.
[0053] Referring now to figure 3, a method 300 for determining a length of traffic congestion in front of a vehicle, is disclosed in accordance with an embodiment of the present subject matter. The method 300 for determining a length of traffic congestion in front of a vehicle may be described in the general context of device executable instructions. Generally, device executable instructions can include routines, programs, objects, components, data structures, procedures, modules, functions, and the like, that perform particular functions or implement particular abstract data types. The method 300 for determining a length of traffic congestion in front of a vehicle may also be practiced in a distributed computing environment where functions are performed by remote processing systems 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 systems.
[0054] The order in which the method 300 for determining a length of traffic congestion in front of a vehicle is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method 300 or alternate methods. Additionally, individual blocks may be deleted from the method 300 without departing from the spirit and scope of the subject matter described herein. Furthermore, the method 300 can be implemented in any suitable hardware, software, firmware, or combination thereof. However, for ease of explanation, in the embodiments described below, the method 300 for determining a length of traffic congestion in front of a vehicle may be considered to be implemented in the above-described system 102.
[0055] At block 302, data may be received from a first set other vehicle. In one example, the data may be received over a vehicle to vehicle communication network by a Dedicated Short Range Communication (DSRC) module installed in a vehicle. In one other example, the data may comprise one or more of a message type, a GPS location of the other vehicle, a traffic length ahead of the other vehicle, a time elapsed in the traffic congestion, and a cause of traffic congestion. In one embodiment, the receiving module 212 may receive data from a first set other vehicle. Further, the receiving module 212 may store the data in the system data 226.
[0056] At block 304, it may be determined if the vehicle is within the traffic congestion based on comparison of an average speed of the vehicle with a predetermined threshold for a predetermined time duration. In one embodiment, the determination module 214 may determine if the vehicle is within the traffic congestion. Further, the determination module 214 may store the output of the determination in the system data 226.
[0057] At block 306, a second set of other vehicles, ahead of the vehicle and moving in the direction of the vehicle may be identified from the first set of other vehicles. In one example, the second set of other vehicles may be identified based on a comparison of the GPS location of the vehicle and the GPS location of each of the first set of other vehicles. In one embodiment, the identification module 216 may a second set of other vehicles. Further, the identification module 216 may store the identified second set of other vehicles in the system data 226.
[0058] At block 308, target data may be identified from the data based on the second set of other vehicles. In one example, the target data is associated with the second set of other vehicles. In one embodiment, the identification module 216 may identify a target data and store the identified target data in the system data 226.
[0059] At block 310, a length of traffic congestion in front of the vehicle based on the target data and a total time required to travel the traffic congestion based on the length of traffic congestion and an average speed of traffic congestion may be computed. In one embodiment, the computation module 218 may compute a length of traffic congestion and a total time required to travel the traffic congestion and store the length in the system data 226.
[0060] Although implementations for methods and systems for determining a length of traffic congestion in front of a vehicle have been described in language specific to structural features and/or methods, it is to be understood that the appended claims are not necessarily limited to the specific features or methods for determining a length of traffic congestion in front of a vehicle described. Rather, the specific features and methods are disclosed as examples of implementations for determining a length of traffic congestion in front of a vehicle.

Claims:1. A method for determining a length of traffic congestion in front of a vehicle using vehicle to vehicle communication, the method comprises steps of:
receiving, by a processor, data from a first set other vehicle, wherein the data is received over a vehicle to vehicle communication network by a Dedicated Short Range Communication (DSRC) module installed in a vehicle, wherein the data comprises one or more of a message type, a GPS location of the other vehicle, a traffic length ahead of the other vehicle, a time elapsed in the traffic congestion, and a cause of traffic congestion;
determining, by the processor, if the vehicle is within the traffic congestion based on comparison of an average speed of the vehicle with a predetermined threshold for a predetermined time duration;
identifying, by the processor, a second set of other vehicles, ahead of the vehicle and moving in the direction of the vehicle from the first set of other vehicles, wherein the second set of other vehicles is identified based on a comparison of the GPS location of the vehicle and the GPS location of each of the first set of other vehicles;
identifying, by the processor, target data from the data based on the second set of other vehicles, wherein the target data is associated with the second set of other vehicles; and
computing, by the processor, a length of traffic congestion in front of the vehicle based on the target data and a total time required to travel the traffic congestion based on the length of traffic congestion and an average speed of traffic congestion.

2. The method of claim 1, further comprising transmitting, by the processor, a message using the Dedicated Short Range Communication (DSRC) module based on the determining, wherein the message comprises at least one of a GPS location of the vehicle, type of message and current speed.

3. The method of claim 1, further comprising transmitting, by the processor, congestion data using the Dedicated Short Range Communication (DSRC) module installed in the vehicle, wherein the congestion data comprises one or more of a message type, a GPS location of the other vehicle, the length of traffic congestion in front of the vehicle, a time elapsed in the traffic congestion, and a cause of traffic congestion.
4. The method of claim 1, further comprising
computing, by the processor, an angle between the second set of other vehicles and the vehicle based on the comparison of the GPS location of the vehicle and the GPS location of each of the first set of other vehicles;
determining, by the processor, a third set of other vehicles from the second set of other vehicles based on a comparison of the angel with a predefined threshold angel;
filtering, by the processor, the target data based on the third set of other vehicles; and
computing, by the processor, at a length of traffic congestion in front of the vehicle based on the filtered target data.

5. The method of claim 1, further comprising
computing, by the processor, the average speed of the traffic congestion based on a length of traffic congestion covered by a vehicle exiting the traffic congestion and a total time required by the vehicle exiting the traffic congestion to travel the length of traffic congestion; and
transmitting, by the processor, the average speed of the traffic congestion using the Dedicated Short Range Communication (DSRC) module.

6. The method of claim 1, further comprising
receiving, by the processor, a cause of the traffic congestion from at least one of the second set of other vehicles;
displaying, by the processor, the total time required, the length of traffic congestion, and the cause to a driver of the vehicle.

7. The method of claim 1, wherein the Dedicated Short Range Communication (DSRC) module is configured to transmit and receive at a predefined time interval, and at a predefined transmission power.

8. A system for determining a length of traffic congestion in front of a vehicle, the system comprising:
a memory; and
a processor coupled to the memory, wherein the processor is configured to:
receiving data from a first set other vehicles, wherein the data is received over a vehicle to vehicle communication network by a Dedicated Short Range Communication (DSRC) module installed in a vehicle, wherein the data comprises one or more of a message type, a GPS location of the other vehicle, a traffic length ahead of the other vehicle, a time elapsed in the traffic congestion, and a cause of traffic congestion;
determining if the vehicle is within the traffic congestion based on comparison of an average speed of the vehicle with a predetermined threshold for a predetermined time duration;
identifying a second set of other vehicles, ahead of the vehicle and moving in the direction of the vehicle from the first set of other vehicles, wherein the second set of other vehicles is identified based on a comparison of the GPS location of the vehicle and the GPS location of each of the first set of other vehicles;
identifying target data from the data based on the second set of other vehicles, wherein the target data is associated with the second set of other vehicles; and
computing a length of traffic congestion in front of the vehicle based on the target data and a total time required to travel the traffic congestion based on the length of traffic congestion and an average speed of traffic congestion.

9. The system of claim 8, further comprising transmitting a message using the Dedicated Short Range Communication (DSRC) module based on the determining, wherein the message comprises at least one of a GPS location of the vehicle, type of message and current speed.

10. The system of claim 8, transmitting congestion data using the Dedicated Short Range Communication (DSRC) module installed in the vehicle, wherein the congestion data comprises one or more of a message type, a GPS location of the other vehicle, the length of traffic congestion in front of the vehicle, a time elapsed in the traffic congestion, and a cause of traffic congestion.

11. The system of claim 8, further comprising
computing an angle between the second set of other vehicles and the vehicle based on the comparison of the GPS location of the vehicle and the GPS location of each of the first set of other vehicles;
determining a third set of other vehicles from the second set of other vehicles based on a comparison of the angel with a predefined threshold angel;
filtering the target data based on the third set of other vehicles; and
computing at a length of traffic congestion in front of the vehicle based on the filtered target data.

12. The system of claim 8, further comprising
computing an average speed of the traffic congestion based on the length of traffic congestion and a total time required to travel the length of traffic congestion; and
transmitting the average speed of the traffic congestion using the Dedicated Short Range Communication (DSRC) module installed in the vehicle.

13. The system of claim 8, further comprising
receiving an average speed of the traffic congestion, and a cause of the traffic congestion from at least one of the second set of other vehicles;
computing the total time required to travel the traffic congestion based on the average speed of the traffic congestion and the length of the traffic congestion; and
displaying the total time required, the length of traffic congestion, and the cause to a driver of the vehicle.

14. The system of claim 8, wherein the Dedicated Short Range Communication (DSRC) module is configured to transmit and receive at a predefined time interval, and at a predefined transmission power.