Description:BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to a traffic control system and particularly to an Artificial Intelligence (AI)-based traffic control system for real-time traffic management.
Description of Related Art
[002] Urban traffic congestion has appeared as a significant global challenge, driven by rapid urbanization and population growth. As cities expand, the increasing number of vehicles on roads has led to a surge in traffic-related issues, including prolonged delays, excessive fuel consumption, and elevated pollution levels. These problems not only result in economic losses but also hurt the quality of life and contribute to environmental degradation. Addressing these challenges needs the development of more efficient and adaptive traffic management systems.
[003] Traditional traffic management systems rely on pre-programmed signal cycles or time-based controls. These systems work on fixed schedules that are unable to account for dynamic and real-time changes in traffic conditions. Consequently, they often do not respond effectively to unpredictable traffic patterns, such as those caused by accidents, construction activities, emergencies, or peak-hour congestion. The rigidity of these systems leads to inefficient traffic flow, worsening congestion and its associated problems.
[004] Existing methods of traffic management, while incorporating advancements like sensor-based detection and traffic cameras, remain limited in their scope and scalability. These systems are typically localized, focusing on specific intersections or corridors without the ability for city-wide integration. Moreover, the processing of traffic data is often delayed or insufficient, resulting in suboptimal decision-making and delayed responses to real-time traffic anomalies.
[005] There is thus a need for an improved and advanced Artificial Intelligence (AI)-based traffic control system for real-time traffic management that can administer the aforementioned limitations in a more efficient manner.
SUMMARY
[006] Embodiments in accordance with the present invention provide an Artificial Intelligence (AI)-based traffic control system for real-time traffic management. The system comprising: traffic monitoring units, installed on a road network such the traffic monitoring units are radially connected to at least one traffic lights, adapted to be in communication with vehicles travelling on the road network via a location tracking unit. The traffic monitoring units are adapted to collect a location of the vehicles, and detect anomalies on the road network. The system further comprising: a cloud-based storage unit adapted to receive and store the collected location and the detected anomalies, from the traffic monitoring units. The system further comprising: a processing unit communicatively connected to the cloud-based storage unit. The processing unit is configured to: receive the collected location and the detected anomalies from the cloud-based storage unit; analyze a traffic pattern based on the collected location and the detected anomalies using an Artificial Intelligence (AI) algorithm; control the traffic lights based on the analyzed traffic pattern; and generate insights based on the analyzed traffic pattern.
[007] Embodiments in accordance with the present invention further provide a method for controlling traffic using an Artificial Intelligence (AI)-based traffic control system. The method comprising steps of: collecting a location of vehicles; detecting anomalies on a road network; receiving the collected location and the detected anomalies; analyzing a traffic pattern based on the collected location and the detected anomalies using an artificial intelligence (AI) algorithm; controlling traffic lights based on the analyzed traffic pattern; and generating insights based on the analyzed traffic pattern.
[008] Embodiments of the present invention may provide a number of advantages depending on their particular configuration. First, embodiments of the present application may provide an Artificial Intelligence (AI)-based traffic control system for real-time traffic management.
[009] Next, embodiments of the present application may provide a traffic control system that dynamically adjusts traffic signals and reroutes vehicles based on real-time data, significantly reducing congestion and wait times.
[0010] Next, embodiments of the present application may provide a traffic control system that optimizes signal timings, ensuring smoother traffic flow and minimizing unnecessary stops.
[0011] Next, embodiments of the present application may provide a traffic control system that enables city-wide traffic management by integrating data from multiple clusters and sources, accommodating the needs of expanding urban areas.
[0012] Next, embodiments of the present application may provide a traffic control system that is trained on historical traffic patterns predict potential congestion and anomalies, allowing preventive measures to be taken before delays occur.
[0013] Next, embodiments of the present application may provide a traffic control system that incorporates data from weather conditions, public transportation schedules, and Global Positioning System (GPS) systems, offering a comprehensive view of traffic scenarios.
[0014] Next, embodiments of the present application may provide a traffic control system that receive real-time updates, route recommendations, and alerts about road conditions, improving navigation and reducing travel time.
[0015] Next, embodiments of the present application may provide a traffic control system that reduces idle times and fuel consumption, contributing to lower emissions and a cleaner environment.
[0016] Next, embodiments of the present application may provide a traffic control system that detects anomalies such as accidents or hazards and responds promptly, reducing the risk of incidents and ensuring safer roads.
[0017] Next, embodiments of the present application may provide a traffic control system that eliminates the need for significant on-site infrastructure, reducing maintenance costs and enabling flexible upgrades.
[0018] Next, embodiments of the present application may provide a traffic control system that supports seamless integration with existing vehicular communication technologies, making it easier for drivers to adapt without requiring additional hardware.
[0019] Next, embodiments of the present application may provide a traffic control system that is scalable based on increasing population and traffic density.
[0020] These and other advantages will be apparent from the present application of the embodiments described herein.
[0021] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
[0023] FIG. 1 illustrates an Artificial Intelligence (AI)-based traffic control system for real-time traffic management, according to an embodiment of the present invention;
[0024] FIG. 2 illustrates a block diagram of a processing unit of the Artificial Intelligence (AI)-based traffic control system for real-time traffic management, according to an embodiment of the present invention; and
[0025] FIG. 3 depicts a flowchart of a method for controlling traffic using an Artificial Intelligence (AI)-based traffic control system, according to an embodiment of the present invention.
[0026] The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including but not limited to. To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures. Optional portions of the figures may be illustrated using dashed or dotted lines, unless the context of usage indicates otherwise.
DETAILED DESCRIPTION
[0027] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the scope of the invention as defined in the claims.
[0028] In any embodiment described herein, the open-ended terms "comprising", "comprises”, and the like (which are synonymous with "including", "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of", “consists essentially of", and the like or the respective closed phrases "consisting of", "consists of”, the like.
[0029] As used herein, the singular forms “a”, “an”, and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.
[0030] FIG. 1 illustrates an Artificial Intelligence (AI)-based traffic control system 100 (hereinafter referred to as the system 100) for real-time traffic management, according to an embodiment of the present invention. In an embodiment of the present invention, the system 100 may be adapted to detect a traffic population, a traffic density, a traffic distribution, and so forth of vehicles 102a-102n (hereinafter referred individually to as the vehicle 102, and plurally to as the vehicles 102) on a road network. Further, the system 100 may be adapted to navigate the traffic in an optimal manner to prevention traffic congestion and traffic jam of the vehicles 102 on the road network. The system 100 may be adapted to provide recommendations to a driver of the vehicle, that may further aid in mitigation of traffic congestion and the traffic jam. Mitigation of the traffic congestion and the traffic jam may in-turn reduce a total travel time for every of the vehicle.
[0031] In an embodiment of the present invention, the system 100 may navigate the vehicle on the road network by an activation and/or deactivation of traffic lights 104a-104m (hereinafter referred individually to as the traffic light 104, and plurally to as the traffic lights 104). The vehicles 102 navigated by the system 100 may be, but not limited to, two-wheeler vehicles, three-wheeler vehicles, four-wheeler vehicles, trucks, semi-trucks, vans, trailers, buses, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the vehicles 102 that may be navigated by the system 100, including known, related art, and/or later developed technologies.
[0032] In an embodiment of the present invention, the system 100 may activate the traffic light to illuminate a red indicator indicating a stoppage to the vehicles 102. In another embodiment of the present invention, the system 100 may activate the traffic light to illuminate a green indicator indicating a passage to the vehicles 102.
[0033] The system 100 may be installed in locations such as, but not limited to, a city, a town, a village, an internal premise of establishments, and so forth. Embodiments of the present invention are intended to include or otherwise cover any location for installation of the system 100, including known, related art, and/or later developed technologies.
[0034] The system 100 may further comprise traffic monitoring units 106a-106m (hereinafter referred individually to as the traffic monitoring unit 106, and plurally to as the traffic monitoring units 106), a location tracking unit 108, a cloud-based storage unit 110, a processing unit 112, and a vehicle communication unit 114.
[0035] In an embodiment of the present invention, the traffic monitoring units 106 may be installed on the road network. The traffic monitoring units 106 may be radially connected to the traffic lights 104. The radial connectivity of the traffic monitoring units 106 with the traffic lights 104 may ensure that every of the traffic lights 104 may be connected to the traffic monitoring units 106. The radial connectivity may construct circular clusters of the traffic monitoring units 106 with the traffic lights 104. In a preferred embodiment of the present invention, the circular clusters may be a diameter of 500 meters. Embodiments of the present invention are intended to include or otherwise cover any diameter of the circular clusters.
[0036] The traffic monitoring units 106 may be adapted to be in communication with vehicles 102 travelling on the road network. The communication between the traffic monitoring units 106 and the vehicles 102 may be established through the location tracking unit 108. In an embodiment of the present invention, the traffic monitoring units 106 may be adapted to adapted to collect a location of the vehicles 102 using the location tracking unit 108.
[0037] The traffic monitoring units 106 may be adapted to detect anomalies on the road network. The anomalies detected on the road network may be, but not limited to, accidents, breakdowns, road hazards, weather forecasts, public transportation schedules, and so forth. Embodiments of the present invention are intended to include or otherwise cover any anomalies that may be detected on the road network, including known, related art, and/or later developed technologies.
[0038] In an embodiment of the present invention, the location tracking unit 108 may be adapted to interpolate the location of the vehicles 102 on the road network. The location tracking unit 108 may be adapted to interpolate a real-time location of the vehicles 102 on the road network. In an exemplary embodiment of the present invention, the interpolated location may be represented in x° North, y° East coordinated format. In another exemplary embodiment of the present invention, the interpolated location may be in x° North y minute and z second, a° East b minute and c second coordinated format. In yet another exemplary embodiment of the present invention, the interpolated location may be in any format. The location tracking unit 108 may be of any type such as, but not limited to, a Global Navigation Satellite System (GLONASS), a Real-Time Locating Systems (RTLS), and so forth. In a preferred embodiment of the present invention, the location tracking unit 108 may be a Global Positioning System (GPS). Embodiments of the present invention are intended to include or otherwise cover any type of the location tracking unit 108, including known, related art, and/or later developed technologies.
[0039] In an embodiment of the present invention, the cloud-based storage unit 110 may be adapted to receive and store the collected location and the detected anomalies. In an embodiment of the present invention, the cloud-based storage unit 110 may be a non-transitory storage medium (not shown). In an embodiment of the present invention, non-limiting examples of the non-transitory storage medium may be, but not limited to, a Read Only Memory (ROM), a Random-Access Memory (RAM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a hard drive, a removable media drive for handling memory cards, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the non-transitory storage medium, including known, related art, and/or later developed technologies.
[0040] The cloud-based storage unit 110 may be for example, but not limited to, a distributed storage unit, a personal storage unit, an end-user storage unit, a commercial storage unit, a Structured Query Language (SQL) storage unit, a non-SQL storage unit, an operational storage unit, a relational storage unit, an object-oriented storage unit, a graph storage unit, and so forth. In a preferred embodiment of the present invention, the cloud-based storage unit 110 may be a cloud storage unit. Embodiments of the present invention are intended to include or otherwise cover any type of the cloud-based storage unit 110 including known, related art, and/or later developed technologies.
[0041] Further, the cloud-based storage unit 110 may be established in a cloud server (not shown), in an embodiment of the present invention. In an embodiment of the present invention, the cloud server may be remotely located. In an exemplary embodiment of the present invention, the cloud server may be a public cloud server. In another exemplary embodiment of the present invention, the cloud server may be a private cloud server. In yet another embodiment of the present invention, the cloud server may be a dedicated cloud server. The cloud server may be, but not limited to, a Microsoft Azure cloud server, an Amazon Web Services (AWS) cloud server, a Google Compute Engine (GCE) cloud server, an Amazon Elastic Compute Cloud (EC2) cloud server, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the cloud server including known, related art, and/or later developed technologies.
[0042] In an embodiment of the present invention, the processing unit 112 may be communicatively connected to the cloud-based storage unit 110. The processing unit 112 may be configured to execute computer-executable instructions to generate an output relating to the system 100. The processing unit 112 may be, but not limited to, a Programmable Logic Control (PLC) unit, a microprocessor, a development board, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the processing unit 112 including known, related art, and/or later developed technologies. In an embodiment of the present invention, the processing unit 112 may be explained in conjunction with FIG. 2.
[0043] In an embodiment of the present invention, the vehicle communication unit 114 may be a physical-interactive hardware that may be installed in the vehicles 102. Further, the vehicle communication unit 114 may be adapted to be operated by the driver of the vehicles 102. The vehicle communication unit 114 may be adapted to receive insights. The insights received on the vehicle communication unit 114 may enable the driver to drive the vehicle in such a fashion to mitigate the traffic congestion and the traffic jam. The insights may be, but not limited to, real-time route recommendations, alerts about congestion, information about road conditions, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the insights that may be delivered on the vehicle communication unit 114, including known, related art, and/or later developed technologies.
[0044] In an embodiment of the present invention, the vehicle communication unit 114 may be an inbuilt infotainment system (not shown) or an instrument cluster (not shown) of the vehicle. In another embodiment of the present invention, the vehicle communication unit 114 may be a user device (not shown) that may be portably used by the driver. The user device may be, but not limited to, a mobile phone, a smart phone, an audible Personal Assistance (PA) system, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the vehicle communication unit 114, including known, related art, and/or later developed technologies.
[0045] FIG. 2 illustrates a block diagram of the processing unit 112 of the system 100, according to an embodiment of the present invention. The processing unit 112 may comprise the computer-executable instructions in form of programming modules such as a data receiving module 200, a data analysis module 202, a data control module 204, a data generation module 206, and a data transmission module 208.
[0046] In an embodiment of the present invention, the data receiving module 200 may be configured to receive the collected location and the detected anomalies from the cloud-based storage unit 110. The data receiving module 200 may be configured to transmit the collected location and the detected anomalies to the data analysis module 202.
[0047] The data analysis module 202 may be activated upon receipt of the collected location and the detected anomalies from the data receiving module 200. In an embodiment of the present invention, the data analysis module 202 may be configured to analyze a traffic pattern based on the collected location and the detected anomalies. The data analysis module 202 may be configured to analyze the traffic pattern using an Artificial Intelligence (AI) algorithm. The Artificial Intelligence (AI) algorithm may be trained on machine learning models. The machine learning models may comprise historical traffic data. The training of the Artificial Intelligence (AI) algorithm on the historical traffic data may enable a prediction of future traffic conditions and optimize the traffic lights 104.
[0048] Upon analysis of the traffic pattern and prediction of the future traffic conditions, the data analysis module 202 may be configured to transmit an optimization signal to the data control module 204.
[0049] The data control module 204 may be activated upon receipt of the optimization signal from the data analysis module 202. In an embodiment of the present invention, the data control module 204 may be configured to control the traffic lights 104 based on the analyzed traffic pattern.
[0050] In an exemplary scenario, if a lane ‘A’ on the road network may be observing a surge in a number of the vehicles 102, and a lane ‘B’ on the road network may be observing a minimization in the number for the vehicles 102. In scenarios as such, the data control module 204 may be configured to control the traffic lights 104 corresponding to the lane ‘A’ in such a fashion that the vehicles 102 in the lane ‘A’ may pass. The data control module 204 may be configured to activate the traffic light corresponding to the lane ‘A’ to illuminate the green indicator indicating the passage to the vehicles 102 in the lane ‘A’. Further, the data control module 204 may be configured to extend a timing of the green indicator of the traffic light corresponding to the lane ‘A’ and reduce the timing of the green indicator of the traffic light corresponding to the lane ‘B’.
[0051] Upon controlling of the traffic lights 104, the data control module 204 may be configured to transmit a generative signal to the data generation module 206.
[0052] The data generation module 206 may be activated upon receipt of the generative signal from the data control module 204. In an embodiment of the present invention, the data generation module 206 may be configured to generate the insights based on the analyzed traffic pattern. Further, the data generation module 206 be configured to transmit an activation signal to the data transmission module 208.
[0053] The data transmission module 208 may be activated upon receipt of the activation signal from the data generation module 206. In an embodiment of the present invention, the data transmission module 208 may be configured to transmit the generated insights to the vehicle communication unit 114. The insights received on the vehicle communication unit 114 may be in a pre-defined form, in an embodiment of the present invention. According to embodiments of the present invention, the pre-defined form of the insights received on the vehicle communication unit 114 may be, but not limited to a pop-up notification, a flash notification, a ringer notification, a silent notification, a push notification, a hidden notification, an electronic mail notification, a Short Message Service (SMS) notification, an always on-screen notification, and so forth. Embodiments of the present invention are intended to include or otherwise cover any pre-defined form of the insights that may be received on the vehicle communication unit 114, including known, related art, and/or later developed technologies.
[0054] FIG. 3 depicts a flowchart of a method 300 for controlling the traffic using the system 100, according to an embodiment of the present invention.
[0055] At step 302, the system 100 may collect the location of the vehicles 102 from the traffic monitoring units 106.
[0056] At step 304, the system 100 may detect anomalies on the road network from the traffic monitoring units 106.
[0057] At step 306, the system 100 may receive the collected location and the detected anomalies.
[0058] At step 308, the system 100 may analyze the traffic pattern based on the collected location and the detected anomalies using the artificial intelligence (AI) algorithm.
[0059] At step 310, the system 100 may control the traffic lights 104 based on the analyzed traffic pattern.
[0060] At step 312, the system 100 may generate insights based on the analyzed traffic pattern.
[0061] At step 314, the system 100 may transmit the generated insights to the vehicle communication unit 114.
[0062] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
[0063] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined in the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements within substantial differences from the literal languages of the claims. , Claims:CLAIMS
I/We Claim:
1. An Artificial Intelligence (AI)-based traffic control system (100) for real-time traffic management, the system (100) comprising:
traffic monitoring units (106a-106m), installed on a road network such the traffic monitoring units (106a-106m) are radially connected to at least one traffic lights (104a-104m), adapted to be in communication with vehicles (102a-102n) travelling on the road network via a location tracking unit (108), wherein the traffic monitoring units (106a-106m) are adapted to collect a location of the vehicles (102a-102n), and detect anomalies on the road network;
a cloud-based storage unit (110) adapted to receive and store the collected location and the detected anomalies, from the traffic monitoring units (106a-106m); and
a processing unit (112) communicatively connected to the cloud-based storage unit (110), characterized in that the processing unit (112) is configured to:
receive the collected location and the detected anomalies from the cloud-based storage unit (110);
analyze a traffic pattern based on the collected location and the detected anomalies using an Artificial Intelligence (AI) algorithm;
control the traffic lights (104a-104m) based on the analyzed traffic pattern; and
generate insights based on the analyzed traffic pattern.
2. The system (100) as claimed in claim 1, wherein the processing unit (112) is configured to transmit the generated insights to a vehicle communication unit (114).
3. The system (100) as claimed in claim 1, wherein the insights are selected from real-time route recommendations, alerts about congestion, information about road conditions, or a combination thereof.
4. The system (100) as claimed in claim 1, wherein the anomalies are selected from accidents, breakdowns, road hazards, weather forecasts, public transportation schedules, or a combination thereof.
5. The system (100) as claimed in claim 1, wherein the Artificial Intelligence (AI) algorithm is trained on machine learning models comprising historical traffic data to predict future traffic conditions and optimize the traffic lights (104a-104m).
6. The system (100) as claimed in claim 1, wherein the location tracking unit (108) is a Global Positioning System (GPS).
7. A method (300) for controlling traffic using an Artificial Intelligence (AI)-based traffic control system (100), the method (300) is characterized by steps of:
collecting a location of vehicles (102a-102n);
detecting anomalies on a road network;
receiving the collected location and the detected anomalies;
analyzing a traffic pattern based on the collected location and the detected anomalies using an artificial intelligence (AI) algorithm;
controlling traffic lights (104a-104m) based on the analyzed traffic pattern; and
generating insights based on the analyzed traffic pattern.
8. The method (300) as claimed in claim 7, comprising a step of transmitting the generated insights to a vehicle communication unit (114).
9. The method (300) as claimed in claim 7, wherein the insights are selected from real-time route recommendations, alerts about congestion, information about road conditions, or a combination thereof.
10. The method (300) as claimed in claim 7, wherein the anomalies are selected from accidents, breakdowns, road hazards, weather forecasts, public transportation schedules, or a combination thereof.
Date: December 23, 2024
Place: Noida

Nainsi Rastogi
Patent Agent (IN/PA-2372)
Agent for the Applicant