Description:FIELD OF THE INVENTION

[0001] The present invention is a patent of addition for Indian Patent Application number IN 202311023941. The present invention generally relates to traffic management and more particularly relates to a system and method of managing the traffic signal based on a trigger.

BACKGROUND

[0002] Traffic lights are a ubiquitous feature on roads, crossings, and lanes, playing a crucial role in managing traffic conditions and ensuring a smooth flow of vehicles. These systems traditionally operate on predefined rules or are preprogrammed to generate signals based on countdown timers. While this method generally works well, it comes with its set of disadvantages, especially during peak traffic hours when congestion becomes a significant concern. The current conventional method of operating and managing traffic lights is full of challenges and thus requires the need for innovative, real-time solutions to address the following issues discussed in forthcoming paragraphs.
[0003] In one limitation, the traffic lights are generally preprogrammed. Though effective under normal circumstances, the preprogrammed traffic lights may prove inadequate during peak traffic hours. The fixed signal generation pattern of the preprogrammed traffic lights may not be suitable for dynamically changing traffic conditions, leading to congestion on specific lanes or roads. This lack of adaptability poses a challenge in efficiently managing the flow of vehicles, especially when traffic keeps increasing on a particular route.
[0004] In attempts to mitigate the shortcomings of preprogrammed traffic lights, traffic cops are often deployed to manage congestion manually. While their presence may help regulate traffic flow, it fails to provide a real-time solution to dynamically changing scenarios. Additionally, manual intervention may not be sufficient to handle the complexity of traffic patterns during peak hours, leading to suboptimal traffic management.
[0005] To address these challenges, there is a growing demand for innovative solutions that offer real-time management of traffic at intersections. Real-time traffic management systems would allow traffic lights to dynamically adjust signal timings based on the current traffic conditions. This adaptive approach could prevent congestion by optimizing the flow of vehicles in response to the actual volume on specific lanes or roads.
[0006] Another aspect that existing traffic management techniques fail to adequately address is the monitoring of traffic offenders at traffic lights. Traditional systems lack the capability to efficiently identify and penalize those violating traffic rules at intersections. Introducing real-time monitoring technologies could significantly enhance the ability to identify and penalize traffic offenders, contributing to safer road conditions.
[0007] As our cities continue to grow and traffic congestion becomes a pervasive issue, the need for real-time traffic management solutions at traffic lights becomes increasingly apparent. Adaptable systems that may respond to changing traffic conditions in real time will not only enhance the efficiency of traffic flow but also contribute to improved road safety. It is imperative for urban planners and traffic management authorities to embrace innovative technologies to create smarter, safer, and more efficient transportation systems for our ever-evolving cities.
[0008] To address these challenges, there exists a need to find a technical solution for the above-mentioned technical problems.
SUMMARY

[0009] This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention. This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
[0010] According to one embodiment of the present disclosure, a method for traffic management is disclosed. The method includes receiving by a server, a current signal state from a traffic signal and a respective device state input associated with one or more vehicles from one or more roadside receivers, wherein the current signal state indicates a status corresponding to at least one of, one or more light indicators and a timer indicator at a timestamp, and the respective device state input indicates a parameter associated with detection of each vehicle among the one or more vehicles. The method further includes determining, by the server, one or more of, a traffic density based on the respective device state input, a position information of the at least one vehicle among the one or more vehicles based on the respective device state input, and a historical data for predicting a change in the current signal state. The method further includes generating, by the server, a trigger based on one of, the traffic density, the position information, and the historical data, wherein the trigger indicates one of a notification or an instruction to the traffic signal for changing the current signal state.
[0011] According to one embodiment of the present disclosure, a system for traffic management is disclosed. The system includes a memory and at least one processor residing in a server. The at least one processor is configured to receive a current signal state from a traffic signal and a respective device state input associated with one or more vehicles from one or more roadside receivers. The current signal state indicates a status corresponding to at least one of, one or more light indicators and a timer indicator at a timestamp, and the respective device state input indicates a parameter associated with detection of each vehicle among the one or more vehicles. The at least one processor is further configured to determine one or more of, a traffic density based on the respective device state input, a position information of the at least one vehicle among the one or more vehicles based on the respective device state input, and a historical data for predicting a change in the current signal state. The at least one processor is further configured to generate a trigger based on one of, the traffic density, the position information, and the historical data, wherein the trigger indicates one of a notification or an instruction to the traffic signal for changing the current signal state
[0012] To further clarify the advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which are illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail in the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0013] These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:
[0014] Figure 1 illustrates a schematic block diagram depicting an environment for the implementation of a system for traffic management at a traffic signal, according to an embodiment of the present invention;
[0015] Figure 2 illustrates another schematic detailed block diagram of modules/software components of the system, according to an embodiment of the present invention;
[0016] Figure 3 illustrates a use-case scenario for the implementation of the system, according to an embodiment of the present invention; and
[0017] Figure 4 illustrates a flow chart of a method for traffic management at the traffic signal, according to an embodiment of the present invention.
[0018] Further, skilled artisans will appreciate that elements in the drawings are illustrated for simplicity and may not have necessarily been drawn to scale. For example, the flow charts illustrate the method in terms of the most prominent steps involved to help to improve understanding of aspects of the present invention. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

DETAILED DESCRIPTION

[0019] For the purpose of promoting an understanding of the principles of the invention, reference will now be made to the various embodiments and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the invention as illustrated therein being contemplated as would normally occur to one skilled in the art to which the invention relates.
[0020] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are explanatory of the invention and are not intended to be restrictive thereof.
[0021] Reference throughout this specification to “an aspect,” “another aspect” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrase “in an embodiment”, “in another embodiment” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.
[0022] The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by “comprises... a” does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.
[0023] Figure 1 illustrates a schematic block diagram depicting an environment for the implementation of a system 100 for traffic management at traffic signals 110a-110d, according to an embodiment of the present invention. For the sake of brevity, the system 100 for traffic management is hereinafter interchangeably referred to as the system 100.
[0024] In an embodiment, referring to Figure 1, the system 100 may be implemented between a server 102, a plurality of roadside receivers (RRs) 104a- 104d (hereinafter interchangeably referred to as the roadside receivers), a device 106 installed and in communication with at least one vehicle 108 (hereinafter interchangeably referred to as the vehicle 108), wherein the vehicle 108 may be moving or travelling on a road 103 with a plurality of lanes. The RRs 104a-104d may be installed at each of the traffic signals 110a-110d across the lanes, consequently detecting the device 106 installed in the vehicle 108. It may be apparent to an ordinary person skill in art that the plurality of roadside receivers (RRs) may be installed through out a stretch of the road 103. For the sake of brevity and purpose of the invention, only the RRs (104a-104d) at the traffic signals 110a-110d are depicted.
[0025] In an embodiment, referring to Figure 1, the system 100 may include the vehicle 108 travelling on the road 103, with the device 106 installed in the vehicle 108. In some embodiments, the RRs 104a-104d installed in the vicinity of the road 103, particularly at each of the traffic signals 110a-110d, may detect and communicate with the device 106. Further, the RRs 104a-104d may transmit detected information to the server 102 for further processing.
[0026] In an embodiment, the RRs 104a-104d may be installed alongside the traffic signals 110a-110d. The RRs 104a-104d may be adapted to detect the device 106 installed in the vehicle 108, while the vehicle 108 travels within a predefined range of the RRs 104a-104d. In an example, a first roadside receiver 104a may be adapted to detect the device 106 installed in the vehicle 108 within the predefined range. It may be apparent to an ordinary person skilled in the art to install more than one roadside receiver alongside each of the traffic signals 110a-110d thus detecting the device 106 installed in each of the vehicles that may approach within the predefined range of the respective roadside receiver.
[0027] Thus, the installation of the RRs 104a-104d alongside each of the traffic signals 110a-110d, may be able to detect the device 106 installed in the vehicle 108, while the vehicle 108 travels through the respective traffic signals 110a-110d. For instance, the vehicle 108 while travelling on the road 103 approaches the predefined range of the first roadside receiver 104a, installed at the traffic signal 110a thus, resulting in the first roadside receiver 104a detecting the device 106 installed in the vehicle 108. Consequently, the server 102 in communication with the first roadside receiver 104a may receive a communication from the first roadside receiver 104a indicative of detection of the device 106 installed in the vehicle 108. Thus, the server 102 in real-time may be aware of a location of the vehicle 108 travelling on the road 103. Similarly, each of the RRs 104b, 104c, and 104d installed at corresponding traffic signals 110b, 110c, and 110d respectively may detect any device installed in the vehicle whenever the vehicle approaches the predefined range of respective RRs 104b, 104c, and 104d. It may be apparent to an ordinary person skilled in the art that at any instance, as illustrated in Fig. 1, each of the RRs 104a-104d at each of the traffic signals 110a-110d may detect multiple devices consequently detecting the presence of multiple vehicles travelling across the road 103.
[0028] In an embodiment, the RRs 104a-104d may use wireless transmission to establish communication with the device 106 installed in the vehicle 108, such as, but not limited to, radio frequency identification (RFID) or Near Field Communication (NFC). In an example, the first roadside receiver 104a may be adapted to detect an identification signal via the wireless transmission from the device 106 installed in the vehicle 108, as the vehicle 108 passes or travels within the predefined range of the first roadside receiver 104b. In some embodiments, the RRs 104a-104d may be adapted to determine a device state input based on the detected identification signal. In an example, the device state input may indicate parameters associated with the device 106 installed in the vehicle 108 such as, but not limited to, an identification tag, a timestamp, and any other metadata associated with the device 106 installed in the vehicle 108. Thus, as the vehicle 108 travels on the road 103 and approaches the RRs 104a-104d, each of the RRs 104a-104d may be adapted to detect the identification signal from the device 106 installed in the vehicle 108 within the predefined range to determine the device state input. Further, the RRs 104a-104d may be adapted to transmit the determined device state input to the server 102. The RRs 104a-104d may be in communication with the server 102 or the traffic signals 110a-110d via a wireless communication network. In an example, the wireless communication network may include wired networks, wireless networks, Ethernet AVB networks, or combinations thereof. The wireless network as appeared throughout the present disclosure may be a zig-bee network, a cellular telephone network such as 4G, 5G, an 802.11, 802.16, 802.20, 802.1Q, Wi-Fi, or a WiMax network. Further, the network may be a public network, such as the Internet, a private network, such as an intranet, or combinations thereof, and may utilize a variety of networking protocols now available or later developed including, but not limited to TCP/IP based networking protocols.
[0029] In an embodiment, the device 106 may be installed in the vehicle 108. The device 106 may indicate any logical circuitry implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Further, the device 106 may be adapted to transmit wireless signals including but not limited to, Radio Frequency Identification (RFID), Bluetooth, and Ultra-Wide Band (UWB) such that the RRs 104a-104d may be able to detect the device 106 installed in the vehicle 108 based on the transmitted wireless signals. Among other capabilities, the device 106 is adapted to fetch and execute computer-readable instructions and data stored in its memory. The device 106 may receive operating power via the vehicle 108 in which it is installed. Thus, the device 106 may provide the identification signal to the RRs 104a-104d related to the vehicle 104 in which it is installed. In the example, the identification tag may indicate a unique serial number associated with the device 106 installed in the vehicle 108.
[0030] In an example, the vehicle 108 initiates travelling on the road 103 and approaches the traffic signal 110a. In the example, the traffic signal 110a may display a current signal state associated with the traffic signal 110a. The current signal state may indicate a status comprising of one or more light indicators and a timer indicator at an instant timestamp ‘t’. Similarly, each of the other traffic signals 110b, 110c, and 110d may also display the current signal state. For instance, the current signal state with the light indicators may correspond to a visual instruction indicating a stop light, a passage light, or a caution light, signalling a halt, or a persistent movement to the vehicle 108 using different colours such that traffic flow may be managed on the road 103. For another instance, the current signal state includes the timer indicator that displays the amount of time remaining for a particular light indicator before the traffic signal changes. As illustrated in Fig.1, in the example, the traffic signals 110a and 110d may display the stop light thus the vehicle 108 is expected to stop or halt at the traffic signal 110a and 110d. Similarly, in another instance, the traffic signals 110b and 110b may display the passage light thus signalling the vehicles to continue proceeding on the road 103.
[0031] In an embodiment, the traffic signals 110a-110d may be in wireless communication with each of the corresponding RRs 104a-104d or the server 102, thus sending the current signal state associated with each of the traffic signals 110a-110d to the respective RRs 104a-104d or directly to the server 102. Consequently, the respective RRs 104a-104d may send the current signal state to the server 102. In an alternative embodiment, the traffic signals 110a-110d may be in wireless communication with the server 102 thus sending the current signal state associated with each of the traffic signals 110a-110d to the server 102.
[0032] Further, the server 102 may receive the device state input indicating the parameter associated with the detection of each vehicle on the road 103 and in the predefined range of the respective RRs 104a-104d. Further, the server 102 may also receive the current signal state associated with each of the traffic signals 110a-110d either via the respective RRs 104a-104d or directly via the respective traffic signals 110a-110d. Further, the server 102 may store a relational database associating the RRs 104a-104d with the traffic signals 110a-110d. For instance, the server 102 may store a positional information including geo-coordinates of the RRs 104a-104d and the traffic signals 110a-110d such that each of the RRs 104a-104d may be correlated to the corresponding traffic signals 110a-110d. For instance, when the vehicle 108 approaches the predefined range of the RR 104a, the server 102 may be configured to correlate the current signal state of the traffic signal 110a and the device state input associated with the device 106 installed in the vehicle 108. Furthermore, the server 102 may be configured to determine traffic density, a position information of each of the vehicles 108 on the road 103 and correlate with the current signal state of the traffic signals 110a-110d to efficiently manage the traffic on the road 103.
[0033] In one example, as illustrated in Fig. 1, the server 102 may be configured to determine that the traffic density i.e., the number of vehicles at the traffic signals 110b and 110c is more than the traffic density at the traffic signals 110a and 110d. Consequently, the server 102 may generate a trigger indicative of an instruction to the traffic signals 110b and 110c for changing the current signal state, such that the current signal state may display the passage light for continuous movement of the vehicles across the traffic signals 110b and 110c. Similarly, the server 102 may generate the trigger indicative of the instruction to the traffic signals 110a, and 110d for changing the current signal state, such that the current signal state may display the stop light for halting the movement of the vehicles across the traffic signals 110a and 110d. Therefore, the device state input sent by the RRs 104a-104d and the current signal state enables the server 102 to better manage the traffic at the traffic signals 110a-110d.
[0034] In another example, the server 102 may be configured to store historical data for predicting a change in the current signal state. In the example, the server 102 may be configured to determine the traffic density of each lane of the road 103 and obtain the current signal state corresponding to each of the lanes at a predefined interval ‘i’. In the example, the lane on the road 103 may refer to a defined area marked for the movement of a single line of vehicles on the road 103. The server 102 may be configured to accumulate the historical data based on the traffic density corresponding to the lane on the road 103 and consequently, predict a traffic density pattern in a real-time corresponding to the lane at the timestamp ‘t’, based on the accumulated historical data.
[0035] Further, in the example, the server 102 may be configured to categorize the traffic density of each of the lanes at another timestamp ‘t+1’, based on the traffic density pattern. The categorization may include a high traffic density, a medium traffic density, or a low traffic density and thereafter, the server 102 may be configured to generate the trigger indicating the instruction for changing the current signal state corresponding to each of the lanes at the timestamp ‘t+1’ based on the categorization.
[0036] In the example, as illustrated in Fig. 1, the server 102 may be configured to thus, predict the traffic density pattern in real-time at the traffic signals 110b and 110c. Consequently, the server 102 may be configured to generate the trigger indicating the instruction for change in the current signal state of the traffic signals 110b and 110c to display the passage light because of the high traffic density. Similarly, the server 102 may be configured to thus, predict the traffic density pattern in the real-time at the traffic signals 110a and 110d. Consequently, the server 102 may be configured to generate the trigger indicating the instruction for change in the current signal state of the traffic signals 110a and 110d to display the stop light because of the low traffic density. Therefore, the device state input sent by the RRs 104a-104d, historical data of the road 103, and the current signal state enables the server 102 to better manage the traffic at the traffic signals 110a-110d.
[0037] Figure 2 illustrates another schematic detailed block diagram of modules/software components of the system 100, according to an embodiment of the present invention. In an example, the system 100 may reside in the server 102.
[0038] In an embodiment, the server 102 may be a cloud IoT Core server which may be in communication with the RRs 104a-104d. In an example, the server 102 is adapted to generate the trigger for managing the traffic at the traffic signal 110a-110d using the device state input received from the RRs 104a-104d and the current signal state of the corresponding traffic signals 110a-110d. Further, the server 102 is adapted to identify which of the RRs 104a-104d may be transmitting the device state input as each of the RRs 104a-104d may be identified based on the unique identification number. The server 102 may be adapted to store in its memory the geo-location associated with the RRs 104a-104d and the corresponding traffic signals 110a-110d. The geo-location thus indicates the position information of the RRs 104a-104d. In an example, the position information may indicate a placement coordinate such as the geographical location of the RRs 104a-104d on the corresponding traffic signals 110a-110d. Thus, the server 102 is adapted to determine the traffic density, traffic offenders, and vehicle position at each of the traffic signals 110a-110d, based on the device state input being sent by the RRs 104a-104d respectively and the associated geo-location.
[0039] Further, the server 102 may be adapted to receive and store a respective profile for the device 106 installed in the vehicle 108, via an application (not shown). Thus, the server 102 may store information related to the device 106 such as, but not limited to, an identification tag associated with the device 106, a type of vehicle 108 in which the device 106 is installed, vehicle registration details, pollution certificate details, owner details, and any other user details. The server 102 may store information related to the device 106 as preconfigured information corresponding to the device 106. For example, upon manufacturing the device 106, the server 102 may receive and store information related to the device 106.
[0040] In an embodiment, the server 102 may include the modules/engines/units implemented with an AI module that may include a plurality of neural network layers. Examples of neural networks include, but are not limited to, convolutional neural network (CNN), deep neural network (DNN), recurrent neural network (RNN), and Restricted Boltzmann Machine (RBM). The learning technique is a method for training a predetermined target device (for example, a robot, or the server) using a plurality of learning data to cause, allow, or control the target device to make a determination or prediction. Examples of learning techniques include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning. At least one of a plurality of CNN, DNN, RNN, RMB models and the like may be implemented to thereby achieve execution of the present subject matter’s mechanism through an AI model. A function associated with AI may be performed through the non-volatile memory, the volatile memory, and the processor. The processor may include one or a plurality of processors. At this time, one or a plurality of processors may be a general-purpose processor, such as a central processing unit (CPU), an application processor (AP), or the like, a graphics-only processing unit such as a graphics processing unit (GPU), a visual processing unit (VPU), and/or an AI-dedicated processor such as a neural processing unit (NPU). One or a plurality of processors control the processing of the input data in accordance with a predefined operating rule or artificial intelligence (AI) model stored in the non-volatile memory and the volatile memory. The predefined operating rule or artificial intelligence model is provided through training or learning. In one example, the server 102 with the AI module may be adapted to predict the traffic density pattern in real-time on the road 103 and corresponding to each of the traffic signals 110a-110d.
[0041] In an embodiment, referring to Figures 1 and 2, the server 102 may include, but is not limited to, at least one processor 202 (referred to as the processor 202), memory 204, modules 206, and data 208. The modules 206 and the memory 204 may be coupled to the processor 202.
[0042] The processor 202 can be a single processing unit or several units, all of which could include multiple computing units. The 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 devices that manipulate signals based on operational instructions. Among other capabilities, the processor 202 is adapted to fetch and execute computer-readable instructions and data stored in the memory 204. At this time, one or a plurality of processors may be a general purpose processor, such as a central processing unit (CPU), an application processor (AP), or the like, a graphics-only processing unit such as a graphics processing unit (GPU), a visual processing unit (VPU), and/or an AI-dedicated processor such as a neural processing unit (NPU). One or a plurality of processors control the processing of the input data in accordance with a predefined operating rule or artificial intelligence (AI) model stored in the non-volatile memory and the volatile memory. The predefined operating rule or artificial intelligence model is provided through training or learning. A detailed explanation of each of the server 102 as shown in figures 1 and 2 will be explained in detail in the forthcoming paragraphs. Further, the working of the system 100 will be explained with respect to figures 1 and 2. The reference numerals are kept the same in the disclosure wherever applicable for ease of explanation.
[0043] The memory 204 may include any non-transitory 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 geo-location or the position information associated with the RRs 104a-104d, historical data of traffic at each of the traffic signals 110a-110d may be stored in the memory 204.
[0044] The modules 206, amongst other things, include routines, programs, objects, components, data structures, etc., which perform particular tasks or implement data types. The modules 206 may also be implemented as, signal processor(s), state machine(s), logic circuitries, and/or any other device or component that manipulates signals based on operational instructions.
[0045] Further, the modules 206 can be implemented in hardware, instructions executed by a processing unit, or by a combination thereof. The processing unit can comprise a computer, a processor, a state machine, a logic array, or any other suitable devices capable of processing instructions. The processing unit can be a general-purpose processor which executes instructions to cause the general-purpose processor to perform the required tasks or, the processing unit can be dedicated to performing the required functions. In another embodiment of the present disclosure, the processor 202 via the modules 206 is configured to execute machine-readable instructions (software) which perform the working of the system 100 within the scope of the present invention as described in forthcoming paragraphs.
[0046] In an embodiment, the processor 202 may be configured to receive the current signal state from the traffic signals 110a-110d and the respective device state input associated with the vehicle 108 via the RRs 104a-104d. Further, the processor may be configured to determine the traffic density based on the respective device state input. Further, the processor 202 may be configured to determine the position information of the vehicle 108 based on the respective device state input. Further, the processor 202 may be configured to determine the historical data for predicting the change in the current signal state. Furthermore, the processor 202 may be configured to generate the trigger based on the traffic density, the position information, and the historical data. In an example, the trigger may indicate the notification or the instruction to the traffic signals 110a-110d for changing the current signal state.
[0047] In an embodiment, the processor 202 may be configured to generate the trigger based on the traffic density. In an example, the processor 202 may be configured to determine the traffic density corresponding to the lane on the road 103. The processor 202 may be configured to obtain the current signal state corresponding to the traffic signals 110a-110d at each lane of the road 103 at the predefined interval. Consequently, the processor 202 may be configured to generate the trigger indicating the instruction to change the current signal state of the traffic signals 110a-110d corresponding to the lane having the traffic density above a predefined threshold range.
[0048] In another embodiment, the processor 202 may be configured to transmit the notification to third party systems 220. In a non-limiting example, the third party systems 220 may be referred to as independent servers or devices in communication with the server 102 and adapted to receive the notification. For instance, law enforcement authorities, an application installed in a user device of the vehicle 108a and 108d, and alike.
[0049] An alternative embodiment of the present invention as performed by the processor 202 is now explained with the help of Figure 3 hereinafter.
[0050] Figure 3 illustrates a use-case for implementation of the system 100, according to an embodiment of the present invention.
[0051] In an embodiment, the processor 202 may be configured to generate the trigger based on the position information. In an example, the processor 202 may be configured to receive the respective device state input corresponding to the vehicle 108a from the first roadside receiver 104a among the RRs 104a-104d at the first timestamp. As illustrated in Fig. 3, in the example, the vehicle 108a may be in a first lane ‘A’ of the road 103. The processor 202 may be configured to obtain the current signal state corresponding to the traffic light 110a in the first lane ‘A’ at the first timestamp. For instance, the current signal state corresponding to the traffic light 110a may display the passage light allowing the vehicle 108a to pass the intersecting road. Simultaneously, the processor 202 may be configured to receive the respective device state input of another vehicle 108c approaching the intersecting road via a second lane ‘C’, from a second roadside receiver 104c among the one or more roadside receivers 104a-104d. For instance, the current signal state corresponding to the traffic light 110c may display the stop light, thus indicating that the vehicle 108c must halt before the intersecting road. Furthermore, the processor 202 may be configured to determine that the vehicle 108c approaching the intersecting road via the second lane ‘C’ is not in accordance with the current signal state of the traffic signal 110c. In the example, the processor 202 may be configured to generate the notification when the vehicle 108c approaching the intersecting road via the second lane 103b is not in accordance with the current signal state of the traffic signal 110c. In an example, the processor 202 may be configured to send the notification to the third party systems 220 such as law enforcement authorities, an application installed in a user device of the vehicle 108a and 108d.
[0052] In the example, thus, the server 102 may be able to send the notification to the vehicle 108c for incorrect driving on the road 103. Additionally, the server 102 may be able to send the notification to the vehicle 108a for halting thus avoiding a possible crash with the vehicle 108c at the intersecting road. Therefore, the server 102 may be enabled to manage the traffic at the traffic signals 110a-110d efficiently without the need for human intervention or preprogrammed logic in the traffic signals 110a-110d.
[0053] Figure 4 illustrates a process flow of a method 400 for traffic management, according to an embodiment of the present invention. The method 400 may be a computer-implemented method executed, for example, by the server 102 and the modules 206. For the sake of brevity, the constructional and operational features of the system 100 that are already explained in the description of Figure 1, Figure 2, and Figure 3 are not explained in detail in the description of Figure 4.
[0054] At step 402, the method 400 may include receiving, by the server 102, the current signal state from the traffic signals 110a-110d and the respective device state input associated with the vehicle 108 from the RRs 104a-104d. The current signal state indicates the status corresponding to the light indicators and the timer indicator and the respective device state input indicates the parameter associated with the detection of each vehicle.
[0055] At step 404, the method 400 may include determining, by the server 102, the traffic density based on the respective device state input, the position information of the vehicle 108 based on the respective device state input, and the historical data for predicting the change in the current signal state.
[0056] At step 406, the method 400 may include generating, by the server 102, the trigger based on the traffic density, the position information, and the historical data. In an example, the trigger may indicate the notification or the instruction to the traffic signals 110a-110d for changing the current signal state.
[0057] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.
[0058] The drawings and the forgoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein. , Claims:1. A method (400) for traffic management, the method (400) comprising:
receiving, by a server, a current signal state from a traffic signal and a respective device state input associated with one or more vehicles from one or more roadside receivers, wherein the current signal state indicates a status corresponding to at least one of, one or more light indicators and a timer indicator at a timestamp, and the respective device state input indicates a parameter associated with the detection of each vehicle among the one or more vehicles;
determining, by the server, one or more of,
a traffic density based on the respective device state input,
a position information of the at least one vehicle among the one or more vehicles based on the respective device state input, and
a historical data for predicting a change in the current signal state; and
generating, by the server, a trigger based on one of, the traffic density, the position information, and the historical data,
wherein the trigger indicates one of a notification or an instruction to the traffic signal to change the current signal state.

2. The method (400) as claimed in claim 1, wherein the generation of the trigger based on the traffic density, comprises:
determining the traffic density corresponding to each lane among a plurality of lanes of intersecting roads at a predefined interval; obtaining the current signal state corresponding to the each lane at the predefined interval; and
generating the trigger indicating the instruction for changing the current signal state of the traffic signal corresponding to a lane having the traffic density above a predefined threshold range.

3. The method (400) as claimed in claim 1, wherein the generation of the trigger based on the position information, comprises:
receiving the respective device state input of the at least one vehicle from a first roadside receiver among the one or more roadside receivers at a first timestamp, wherein the at least one vehicle is in a first lane among a plurality of lanes of intersecting roads;
obtaining, by the server, the current signal state corresponding to the first lane at the first timestamp;
receiving, by the server, the respective device state input of the at least one vehicle approaching a second lane among the plurality of lanes of the intersecting roads at a second timestamp from a second roadside receiver among the one or more roadside receivers;
determining, by the server, if the at least one vehicle approaching the second lane is in accordance with the current signal state of the traffic signal at the second timestamp based on the received respective device state inputs of the at least one vehicle at the first timestamp and the second timestamp; and
generating the trigger indicating the notification when the at least one vehicle approaching the second lane is not in accordance with the current signal state of the traffic signal at the second timestamp.

4. The method (400) as claimed in claim 3, further comprising:
sending the notification to one or more of, a third party, an application, and the at least one vehicle.

5. The method (400) as claimed in claim 1, wherein the generation of the trigger is based on the historical data, comprises:
determining the traffic density of each lane among a plurality of lanes of intersecting roads and obtaining the current signal state corresponding to each of the lane at a predefined interval;
accumulating the historical data based on the traffic density corresponding to each of the lane;
predicting a traffic density pattern at a real-time corresponding to the plurality of lanes at the timestamp, based on the accumulated historical data;
categorizing the traffic density of each of the lane at the timestamp, based on the traffic density pattern, in one of a high traffic density, a medium traffic density, or a low traffic density; and
generating the trigger indicating the instruction for changing the current signal state corresponding to each of the lane at the timestamp based on the categorization.

6. The method (400) as claimed in claim 5, wherein the traffic density pattern further includes a rate of change in the traffic density in each lane among the plurality of lanes in the timestamp.

7. The method (400) as claimed in any of the preceding claims, wherein the one or more indicators of the traffic signal are indicative of one of a stop light, a passage light, or a caution light.

8. The method (400) as claimed in any of the preceding claims, wherein the timer indicator includes a digital display adapted to display a remaining time until a change in the current signal state of the one or more indicators of the traffic signal.

9. A system (100) for traffic management, the system (100) comprising:
a memory (204); and
at least one processor (202) communicably coupled to the memory (204), the at least one processor (202) is configured to:
receive a current signal state from a traffic signal and a respective device state input associated with one or more vehicles from one or more roadside receivers (104a-104d),
wherein the current signal state indicates a status corresponding to at least one of, one or more light indicators and a timer indicator at a timestamp, and the respective device state input indicates a parameter associated with detection of each vehicle among the one or more vehicles;
determine one or more of,
a traffic density based on the respective device state input,
a position information of at least one vehicle among the one or more vehicles based on the respective device state input, and
a historical data for predicting a change in the current signal state; and
generate a trigger based on one of the traffic density, the position information, and the historical data,
wherein the trigger indicates one of a notification or an instruction such that the traffic signal receives the change in the current signal state.

10. The system (100) as claimed in claim 9, wherein to generate the trigger based on the traffic density, the at least one processor (202) is configured to:
determine the traffic density corresponding to each lane among a plurality of lanes of intersecting roads at a predefined interval;
obtain the current signal state corresponding to the each lane at the predefined interval; and
generate the trigger indicating the instruction for changing the current signal state of a traffic signal corresponding to a lane having the traffic density above a predefined threshold range.

11. The system (100) as claimed in claim 9, wherein to generate the trigger based on the position information, the at least one processor (202) is configured to:
receive, the respective device state input of the at least one vehicle from a first roadside receiver among the one or more roadside receivers at a first timestamp, wherein the at least one vehicle is in a first lane among a plurality of lanes of intersecting roads;
obtain, the current signal state corresponding to the first lane at the first timestamp;
receive, the respective device state input of the at least one vehicle approaching a second lane among the plurality of lanes of the intersecting roads at a second timestamp, from a second roadside receiver among the one or more roadside receivers;
determine if the at least one vehicle approaching towards the second lane is in accordance with the current signal state of the traffic signal at the second timestamp based on the received respective device state inputs of the at least one vehicle at the first timestamp and the second timestamp; and
generate, the trigger indicating the notification when the at least one vehicle approaching the second lane is not in accordance with the current signal state of the traffic signal at the second timestamp.

12. The system (100) as claimed in claim 11, wherein the at least one processor (202) is configured to:
send the notification to one or more of, a third party, an application, and the at least one vehicle.

13. The system (100) as claimed in claim 9, wherein to generate the trigger based on the historical data, the at least one processor (202) is configured to:
determine the traffic density of each lane among a plurality of lanes of intersecting roads and obtain the current signal state corresponding to the each lane at a predefined interval;
accumulate the historical data based on the traffic density of the each lane;
predict a traffic density pattern at a real-time corresponding to the plurality of lanes at the timestamp, based on the accumulated historical data;
categorize the traffic density of the each lane at the timestamp, based on the traffic density pattern, in one of a high traffic density, a medium traffic density, or a low traffic density; and
generate the trigger indicating the instruction for changing the current signal state corresponding to the each lane at the timestamp based on the categorization.

14. The system (100) as claimed in claim 13, wherein the traffic density pattern further includes a rate of change in the traffic density in each lane among the plurality of lanes in the timestamp.

15. The system (100) as claimed in any of the preceding claims, wherein the one or more indicators of the traffic signal are indicative of one of a stop light, a passage light, or a caution light.

16. The system (100) as claimed in any of the preceding claims, wherein the timer indicator includes a digital display adapted to display a remaining time until a change in the current signal state of the one or more indicators of the traffic signal.

17. The system (100) as claimed in any of the preceding claims, wherein the at least one processor is communicatively connected to the traffic signal and the one or more roadside receivers.