Artificial intelligence sidewalk traffic light system based on Internet of Things technology
Through the Internet of Things-based artificial intelligence sidewalk traffic light system, traffic flow is monitored in real time and traffic light signals are dynamically adjusted, which solves the problem of insufficient flexibility of traditional traffic light systems and improves traffic efficiency and safety.
Patent Information
- Application Number
- CN202510352956.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-25
- Publication Date
- 2025-07-11
AI Technical Summary
Traditional traffic light systems cannot flexibly adjust according to real-time changes in traffic flow, resulting in low traffic efficiency, serious traffic congestion, and low intelligence level, affecting driving experience and safety.
The artificial intelligence sidewalk traffic light system based on the Internet of Things technology is adopted, and high-definition cameras and sensors are used to monitor traffic flow in real time. Combined with deep learning and image recognition technology, the traffic light signal is dynamically adjusted, and the automatic lifting guardrail is used to prevent accidentally running red lights.
It improves road traffic efficiency, reduces waiting time for pedestrians and vehicles, improves traffic safety and user experience, and adapts to changes in different traffic conditions.
Smart Images
Figure CN120299270A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of intelligent traffic signal control, and in particular to an artificial intelligence pedestrian traffic light system based on Internet of Things technology. Background Art
[0002] As an important part of urban traffic management, the traffic light system plays a crucial role in ensuring smooth traffic, improving road traffic capacity, and optimizing the urban traffic structure. In the traditional traffic light system, signal control mainly relies on traffic lights with fixed durations. Based on a preset time sequence, the traffic flow is indicated by the changes of three colors: red, yellow, and green. However, due to the limitation of fixed durations, the traditional traffic light system cannot be flexibly adjusted according to the real-time changes in traffic flow, resulting in low traffic efficiency and serious traffic congestion. In cities or regions with dense population and large traffic flow, the traditional traffic light system cannot fully meet the traffic flow requirements. Even if improvements are made by increasing the number of traffic lights or extending the green light time, the traffic congestion problem may not be fundamentally solved. In addition, too many traffic lights may also affect the driving experience and comfort of drivers. In some individual cities, traffic police still control the traffic at intersections on-site, which seriously wastes human resources.
[0003] Regarding problems such as unreasonable signal configuration and insufficient coordination between traffic lights, there is currently no established and efficient solution at home and abroad. Regarding the phenomenon that the red light time is set extremely long and pedestrians are prone to running red lights after a long wait, existing basic systems have problems such as low intelligence level.
[0004] In summary, in order to solve the problems of pedestrian and vehicle congestion and unreasonable signal configuration, effectively improve traffic efficiency, ensure traffic safety, and enhance the user experience, the current traffic light system urgently needs innovation. In view of this problem, the present invention has invented an artificial intelligence pedestrian traffic light system based on Internet of Things technology with adaptive capabilities. Summary of the Invention
[0005] In view of this, the purpose of the present invention is to provide an artificial intelligence pedestrian traffic light system based on Internet of Things technology, which can improve road traffic efficiency, adapt to different traffic conditions, and play an important role in promoting and applying this advanced form of artificial intelligence pedestrian traffic light system.
[0006] To achieve the above purpose, the present invention adopts the following technical solutions: An artificial intelligence pedestrian traffic light system based on Internet of Things technology, comprising: A number statistics camera, installed at the top of the traffic light pole; A sensor system, installed at the traffic lights on the vehicle lane at the intersection; An automatic lifting guardrail, installed on both sides of the zebra crossing; The intelligent analysis server is installed inside the traffic light pole. The intelligent signal control system is installed inside the traffic light pole.
[0007] In a preferred embodiment, the people counting camera is equipped with a high-definition binocular camera, which obtains depth information by simulating human eye vision to calculate image differences, and based on the object detection algorithm of deep learning, learns the feature patterns in the image, detects and classifies pedestrians in the image, distinguishes the situation of multiple people passing through at the same time, and filters non-pedestrian targets.
[0008] In a preferred embodiment, the camera records videos in real time and transmits them to the chip. Combining the algorithm, it tracks the trajectories of the identified pedestrians and records the time and route information when they enter and leave a specific area; in a static scene, by establishing a background model, it differentiates the current frame from the background model to detect moving targets, thereby extracting pedestrian information, eliminating background interference, and achieving better people counting results; the camera has built-in edge computing capabilities to perform preliminary processing and analysis on the collected data locally.
[0009] In a preferred embodiment, the sensor system is built with infrared sensors, ultrasonic sensors, and microwave radar sensors; the infrared sensors, ultrasonic sensors, and microwave radar sensors coordinate with each other and sensitively detect vehicle quantity, speed, position, and traffic condition information; the real-time collected data is connected to the background management system through wired network technology and wireless network technology, and the wired network technology realizes stable and high-speed data transmission; through cloud storage technology, the statistical data and video materials are stored in the cloud, and administrators can access and view historical data to achieve long-term preservation and backup of data and expand the storage capacity as needed.
[0010] In a preferred embodiment, the automatic lifting guardrail is specifically an automatic lifting guardrail driven by a new energy motor. The automatic lifting guardrail uses photovoltaic conversion technology to store and output electrical energy. After starting the motor, it converts the rotational motion into linear motion through gearbox and lead screw mechanical components to drive the guardrail to rise or fall; the automatic lifting guardrail is intelligently integrated with the sidewalk traffic light system. The guardrail rises two seconds before the red light changes, and a prompt of "Pay attention to the red light" sounds. When the green light is on, it quickly descends to allow pedestrians to pass, preventing pedestrians from accidentally running a red light, and there is a blue reflective film on the guardrail.
[0011] In a preferred embodiment, the intelligent analysis server uses image recognition technology to intelligently analyze the images transmitted by the people counting camera and count the number of people in the images; it is divided into the following three situations: ① When the number of people reaches the preset value, the intelligent analysis server sends a signal to the intelligent signal control system; ② When there are people, but the number of people does not reach the preset value, taking 10 people as a stage, the intelligent analysis server sends a specific signal to the intelligent signal control system; ③ When there are no people, the intelligent analysis server does not send a signal.
[0012] In a preferred embodiment, an intelligent signal control system is installed inside the traffic light pole. It receives the signals sent by the intelligent analysis server and dynamically adjusts the traffic light signal timing according to the number of pedestrians. When the signal control machine receives the signal, the red and green traffic lights on the vehicle lane turn red, and the pedestrian light turns green. Conversely, when the signal control machine does not receive the signal, the red and green traffic lights on the vehicle lane turn green, and the pedestrian light turns red. When the number of pedestrians in a certain direction increases, the system can appropriately increase the green light time in that direction to reduce the waiting time of pedestrians. By using the green wave coordination control technology, the signals of adjacent intersections are coordinated, and the green light start time difference is set so that pedestrians can continuously encounter green lights when walking at a specified speed.
[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention analyzes the traffic flow data in real time, realizes the artificial intelligence automatic adjustment of the traffic light timing according to the pedestrian flow and vehicle conditions, reduces the waiting time of pedestrians and vehicles, improves the road traffic efficiency, adapts to different traffic conditions, and plays an important role in promoting the popularization and application of this advanced form of the artificial intelligence sidewalk traffic light system. BRIEF DESCRIPTION OF THE DRAWINGS
[0014] Figure 1 is a schematic structural diagram of the road surface application of the artificial intelligence sidewalk traffic light system based on the Internet of Things technology in the embodiment of the present invention; Figure 2 is a schematic structural diagram of the sidewalk traffic light system in the present invention.
[0015] Figure 3 is a schematic structural diagram of the vehicle lane traffic light system in the present invention.
[0016] Figure 4 is a block diagram of the system for adjusting the traffic light signal timing in the present invention.
[0017] Figure 5 is a schematic structural diagram of the automatic lifting guardrail in the present invention.
[0018] Reference Numerals: 1 - sidewalk traffic light system; 2 - automatic lifting guardrail; 3 - waiting area; 4 - zebra crossing; 5 - vehicle lane traffic light system; 6 - number statistics camera; 7 - color signal light; 8 - intelligent signal control system; 9 - intelligent analysis server; 10 - sensor system; 11 - motor control system; 12 - solar panel; 13 - blue reflective film. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0019] The following further describes the present invention with reference to the drawings and embodiments.
[0020] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.
[0021] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application; as used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should also be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.
[0022] The present invention provides an artificial intelligence pedestrian traffic light system based on Internet of Things technology, referring to Figure 1-5 , for realizing real-time traffic data collection, dynamically adjusting traffic light signal timing, and preventing running red lights by mistake. The artificial intelligence pedestrian traffic light system includes: A people counting camera is installed at the top of the traffic light pole and is equipped with a high-definition binocular camera. It obtains depth information by simulating human eye vision to calculate image differences. Based on the object detection algorithm of deep learning, such as convolutional neural network (CNN), it learns the feature patterns in the image, detects and classifies pedestrians in the image, distinguishes the situation of multiple people passing through at the same time, filters non-pedestrian targets, and more accurately judges the width, position and other features of pedestrians, avoiding double counting or missing counting, and having obvious advantages in complex environments. At the same time, the camera records videos in real time, and the huge image database is quickly transmitted to the chip. Combining algorithms such as optical flow method and Kalman filter, it tracks the trajectories of the identified pedestrians and records information such as the time and route when they enter and leave a specific area. In a static scene, by establishing a background model, the current frame is differentiated from the background model to detect moving targets, so as to extract pedestrian information, eliminate background interference, and achieve better people counting effect. The camera has built-in edge computing capabilities. First, it preliminarily processes and analyzes the collected data locally, thereby reducing the computing pressure on the cloud server, reducing network latency, and improving the response speed.
[0023] The sensor system is installed at the traffic lights on the road surface of the intersection. This system incorporates three types of sensors, namely infrared sensors, ultrasonic sensors, and microwave radar sensors. They coordinate with each other and sensitively detect traffic flow information, such as the number of vehicles, speed, position, and traffic conditions. The data collected in real time is connected to the back-end management system through wired network technology and wireless network technology. The wired network technology enables stable and high-speed data transmission, while the wireless network technology makes the deployment of cameras more flexible, allowing them to be used in places where it is not convenient to lay network cables, meeting the data transmission requirements in different scenarios. This system also utilizes cloud storage technology to store statistical data and video materials in the cloud, facilitating administrators to access and view historical data anytime and anywhere, achieving long-term data preservation and backup, and the storage capacity can be expanded as needed.
[0024] The automatic lifting guardrail is installed on both sides of the zebra crossing. This new energy motor-driven automatic lifting guardrail uses photovoltaic conversion technology to store and output electrical energy. After starting the motor, the rotational motion is converted into linear motion through mechanical components such as gearboxes and lead screws, driving the guardrail to rise or fall. It has a fast response speed, low noise, and low maintenance costs. The automatic lifting guardrail is intelligently integrated with the sidewalk traffic light system. Two seconds before the red light changes, the guardrail slowly rises and a prompt of "Attention: Red Light" sounds. When the green light is on, it quickly descends to allow pedestrians to pass, preventing pedestrians from accidentally running a red light. Additionally, blue reflective films are pasted on the guardrail to reduce accidents at night.
[0025] The intelligent analysis server is installed inside the traffic light pole. It uses image recognition technology to intelligently analyze the images transmitted by the number-of-people statistical camera and count the number of people in the images. There are the following three situations: ① When the number of people reaches a specific value (such as 30 people), the intelligent analysis server sends a signal to the intelligent signal control system; ② When there are people but the number has not reached the specific value, in stages of 10 people, the intelligent analysis server sends a specific signal to the intelligent signal control system; ③ When there are no people, the intelligent analysis server does not send a signal.
[0026] The intelligent signal control system is installed inside the traffic light pole. It receives the signals sent by the intelligent analysis server and dynamically adjusts the traffic light signal timing according to the number of pedestrians. This system not only has the functions of an adaptive traffic light system but also can be linked with other intelligent transportation system components. When the signal controller receives a signal, the traffic lights on the road surface turn red and the pedestrian lights turn green; conversely, when the signal controller does not receive a signal, the traffic lights on the road surface turn green and the pedestrian lights turn red. When the number of pedestrians in a certain direction increases, the system can appropriately increase the green light time in that direction to reduce the waiting time of pedestrians. At the same time, using the green wave coordination control technology, the signals of adjacent intersections are coordinated, and the green light start-up time difference is reasonably set so that pedestrians can continuously encounter green lights when walking at a certain speed.
[0027] The sensor system described in the present invention adopts advanced algorithms and technologies, such as data cleaning, data mining, etc. When performing data cleaning, duplicate data, missing values, and outliers are removed to enhance the performance of the model; when performing data mining, time series analysis methods, such as ARIMA models, LSTM neural networks, etc., are used to model the data and predict future trends, improving the availability and accuracy of the data. At the same time, through data integration, data from different sources can be fused to form complete traffic information.
[0028] The intelligent signal control system described in the present invention is based on Internet of Things technology and data processing technology, which is different from the signal conversion robot of the vision servo technology route. The latter's technical solution is essentially constructed through deterministic programming, while the intelligent signal control system can have the ability of adaptive upgrade through the introduction of artificial supervision signals during continuous operations. In addition, the intelligent signal control system can accurately predict the change trend of traffic flow according to artificial intelligence algorithms after installation, effectively improving traffic efficiency, reducing congestion and emissions.
Claims
1. An artificial intelligence pedestrian traffic light system based on Internet of Things technology, characterized in that Including: A people counting camera, installed at the top of the traffic light pole; A sensor system, installed at the traffic lights on the road lanes of the intersection; An automatic lifting guardrail, installed on both sides of the zebra crossing; An intelligent analysis server, installed inside the traffic light pole; An intelligent signal control system, installed inside the traffic light pole.
2. The artificial intelligence sidewalk traffic light system based on the Internet of Things technology according to claim 1, wherein The people counting camera is equipped with a high-definition binocular camera, which obtains depth information by simulating the visual calculation of the human eye for image differences, and also based on the object detection algorithm of deep learning, learns the feature patterns in the image, detects and classifies pedestrians in the image, distinguishes the situation of multiple people passing through at the same time, and filters non-pedestrian targets.
3. An artificial intelligence sidewalk traffic light system based on Internet of Things technology according to claim 2, characterized in that, The camera records videos in real time and transmits them to the chip. Combining with the algorithm, it tracks the trajectories of the identified pedestrians and records the time and route information when they enter and leave a specific area; In a static scene, by establishing a background model, the current frame is differenced from the background model to detect moving targets, thereby extracting pedestrian information, excluding background interference, and achieving better people counting effect; The camera has built-in edge computing capabilities to perform preliminary processing and analysis on the collected data locally.
4. The artificial intelligence sidewalk traffic light system based on Internet of Things technology according to claim 1, characterized in that, The sensor system is built with an infrared sensor, an ultrasonic sensor, and a microwave radar sensor; the infrared sensor, the ultrasonic sensor, and the microwave radar sensor coordinate with each other and sensitively detect vehicle quantity, speed, position, and traffic condition information; the data collected in real time is connected to the background management system through wired network technology and wireless network technology, and the wired network technology realizes stable and high-speed data transmission; through cloud storage technology, the statistical data and video materials are stored in the cloud, and the administrator can access and view the historical data to achieve long-term preservation and backup of the data and expand the storage capacity as needed.
5. An artificial intelligence sidewalk traffic light system based on Internet of Things technology according to claim 1, characterized in that, The automatic lifting guardrail is specifically an automatic lifting guardrail driven by a new energy motor. The automatic lifting guardrail uses photoelectric conversion technology to store and output electrical energy. After starting the motor, the rotational motion is converted into linear motion through gearbox and lead screw mechanical components to drive the guardrail to rise or fall; the automatic lifting guardrail is intelligently integrated with the sidewalk traffic light system. The guardrail rises two seconds before the red light changes, and a prompt of "Pay attention to the red light" sounds. When the green light is on, it quickly descends to allow pedestrians to pass, preventing pedestrians from accidentally running a red light, and there is a blue reflective film on the guardrail.
6. An artificial intelligence sidewalk traffic light system based on Internet of Things technology according to claim 1, characterized in that, The intelligent analysis server uses image recognition technology to intelligently analyze the pictures transmitted by the people counting camera and count the number of people in the pictures; it is divided into the following three situations: ① When the number of people reaches the preset value, the intelligent analysis server sends a signal to the intelligent signal control system; ② When there are people, but the number of people does not reach the preset value, taking 10 people as a stage, the intelligent analysis server sends a specific signal to the intelligent signal control system; ③ When there are no people, the intelligent analysis server does not send a signal.
7. An artificial intelligence sidewalk traffic light system based on Internet of Things technology according to claim 1, characterized in that, An intelligent signal control system is installed inside the traffic light pole. It receives the signals sent by the intelligent analysis server and dynamically adjusts the signal timing of the traffic lights according to the number of pedestrians. When the signal controller receives the signal, the red and green traffic lights on the vehicle lane turn red, and the pedestrian lights turn green. Conversely, when the signal controller does not receive the signal, the red and green traffic lights on the vehicle lane turn green, and the pedestrian lights turn red. When the number of pedestrians in a certain direction increases, the system can appropriately increase the green light time in that direction to reduce the waiting time of pedestrians. Using the green wave coordination control technology, the signals of adjacent intersections are coordinated, and the green light start-up time difference is set so that pedestrians can continuously encounter green lights when walking at a specified speed.