Intelligent traffic signal lamp control method and system, electronic equipment and medium

Abstract

The invention discloses a control method and system of an intelligent traffic signal lamp, electronic equipment and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring a monitoring video of a target intersection; based on the monitoring video, determining traffic flow information and people flow information in a plurality of traffic directions in the target intersection; for each passing direction, based on the traffic flow information, calculating the traffic flow demand saturation and the vehicle passing demand proportion, and based on the pedestrian flow information, calculating the pedestrian crossing demand saturation of the passing direction; generating a traffic flow signal lamp distribution strategy of the target intersection in combination with the vehicle passing demand proportion of each passing direction, and generating a pedestrian flow signal lamp distribution strategy of the target intersection in combination with the traffic flow demand saturation and pedestrian crossing demand saturation of each passing direction; and according to the traffic flow signal lamp distribution strategy and the people flow signal lamp distribution strategy, controlling a plurality of traffic signal lamps in the target intersection. By implementing the technical scheme provided by the invention, the effect of improving the control efficiency of the traffic signal lamp is achieved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and specifically to a control method, system, electronic device and storage medium for a smart traffic light. Background Art

[0002] With the rapid development of urbanization, traffic congestion has become a major problem faced by many large cities. As a key facility for regulating traffic flow, the optimized management of traffic lights is of great significance to alleviating urban traffic pressure and improving road use efficiency.

[0003] At present, the existing traffic light control method mainly sets a fixed signal light change strategy based on historical traffic flow data to control the traffic light. However, in actual applications, due to the complex and changeable traffic environment, it is often difficult to adapt to different traffic conditions by only setting a fixed signal light change strategy, resulting in traffic congestion problems, thus resulting in low control efficiency of traffic lights. Summary of the invention

[0004] The present application provides a control method, system, electronic device and medium for a smart traffic light, which has the effect of improving the control efficiency of the traffic light.

[0005] In a first aspect, the present application provides a method for controlling a smart traffic signal light, comprising: Obtain surveillance video of the target intersection; Based on the monitoring video, determine the vehicle flow information and pedestrian flow information in multiple traffic directions at the target intersection; For each of the traffic directions, based on the traffic information, the traffic demand saturation and vehicle traffic demand ratio of the traffic direction are calculated, and based on the pedestrian flow information, the pedestrian crossing demand saturation of the traffic direction is calculated; Combined with the vehicle traffic demand ratio of each of the traffic directions, a traffic signal light allocation strategy for the target intersection is generated; combined with the traffic demand saturation and pedestrian crossing demand saturation of each of the traffic directions, a pedestrian signal light allocation strategy for the target intersection is generated; According to the vehicle flow signal light allocation strategy and the pedestrian flow signal light allocation strategy, multiple traffic lights in the target intersection are controlled.

[0006] In a second aspect of the present application, a control system for a smart traffic signal light is provided, the system comprising: An information acquisition module is used to acquire a surveillance video of a target intersection; based on the surveillance video, determine the vehicle flow information and pedestrian flow information of multiple traffic directions in the target intersection; An information processing module, for calculating, for each of the traffic directions, the vehicle flow demand saturation and vehicle traffic demand ratio of the traffic direction based on the traffic flow information, and calculating the pedestrian crossing demand saturation of the traffic direction based on the pedestrian flow information; A strategy generation module, for generating a traffic light allocation strategy for the target intersection based on the vehicle traffic demand ratio of each of the traffic directions, and for generating a pedestrian traffic light allocation strategy for the target intersection based on the traffic demand saturation and pedestrian crossing demand saturation of each of the traffic directions; The signal light control module is used to control multiple traffic lights in the target intersection according to the vehicle flow signal light allocation strategy and the pedestrian flow signal light allocation strategy.

[0007] In a third aspect of the present application, an electronic device is provided, comprising a memory, a processor, and a program stored in the memory and executable on the processor, wherein the program can implement a method for controlling a smart traffic light when loaded and executed by the processor.

[0008] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements a method for controlling a smart traffic light.

[0009] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: By adopting the above technical solution, the surveillance video of the target intersection is obtained, and the traffic information and pedestrian flow information of each traffic direction are extracted from the surveillance video. The system realizes the accurate quantification of the traffic demand at the intersection by calculating key indicators such as the traffic demand saturation, the proportion of vehicle traffic demand and the saturation of pedestrian crossing demand. This multi-dimensional demand assessment method can comprehensively reflect the traffic pressure distribution at the intersection and provide a basis for the subsequent signal timing optimization. At the same time, by introducing the demand saturation index, the system can accurately identify the traffic pressure in each direction and avoid unreasonable timing problems. In the process of generating signal light allocation strategy, the system considers the demand characteristics of vehicle flow and pedestrian flow respectively. The traffic light allocation strategy ensures that each direction obtains the travel time that matches its actual demand by combining the proportion of vehicle traffic demand. The pedestrian light allocation strategy realizes the dynamic balance of the demand for vehicle and pedestrian flow by comprehensively considering the differences in the saturation of vehicle demand and the saturation of pedestrian crossing demand, avoiding the limitation of focusing on the single demand of vehicle or pedestrian flow in traditional signal control. In the process of traffic light control, the system coordinates and controls multiple traffic lights in the intersection based on the generated dual strategy. This signal control method based on real-time demand can respond to changes in traffic demand in a timely manner, dynamically adjust the timing strategy of traffic lights, avoid traffic congestion problems caused by fixed timing schemes, and improve the control efficiency of traffic lights. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 It is a flow chart of a method for controlling a smart traffic signal light provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of a control system of a smart traffic light provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0011] Description of reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0012] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0013] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0014] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0015] The present application embodiment provides a method for controlling a smart traffic signal light. In one embodiment, please refer to Figure 1 , Figure 1 This is a flow chart of a method for controlling a smart traffic light provided in an embodiment of the present application. The method can be implemented by a computer program, which can be integrated into an application or run as an independent tool application. The method can also be implemented by a single-chip microcomputer or run in a control system of a smart traffic light based on a von Neumann system. Specifically, the method can include the following steps: Step 101: Obtain surveillance video of a target intersection; and determine vehicle flow information and pedestrian flow information in multiple travel directions at the target intersection based on the surveillance video.

[0016] The target intersection refers to a specific road intersection that needs to be controlled by intelligent traffic lights. The target intersection can be a crossroad, T-junction or other form of road intersection in the urban road network, which is characterized by having multiple vehicle lanes and pedestrian crossings, and traffic lights are needed to coordinate and manage vehicle and pedestrian flows in different directions.

[0017] Traffic flow information refers to the quantitative data of the vehicle operation status in each direction of traffic at the target intersection. Traffic flow information includes two basic parameters: the number of vehicles and the vehicle speed. The number of vehicles reflects the total number of vehicles waiting to pass through the intersection in a specific direction of traffic, and the vehicle speed reflects the actual movement status of vehicles in that direction.

[0018] Pedestrian flow information refers to the quantitative data of pedestrian activity status in each direction of traffic at the target intersection. Pedestrian flow information includes two basic parameters: the number of pedestrians and the speed of pedestrian movement. The number of pedestrians reflects the total number of pedestrians waiting to cross the street in a specific direction of traffic, and the speed of pedestrian movement reflects the actual movement status of pedestrians in that direction.

[0019] Specifically, surveillance cameras are set up in all directions of the target intersection to continuously collect surveillance videos of the target intersection. The installation position and angle of the surveillance camera should ensure that all traffic directions of the target intersection can be fully covered, so as to ensure the integrity and accuracy of the collected data. After obtaining the surveillance video, the video data needs to be processed to extract effective information. First, the surveillance video is preprocessed, including but not limited to image denoising, illumination compensation, distortion correction and other operations, to obtain a clear and standardized target image. Subsequently, the target image is analyzed using a target detection algorithm, which can be a target detection model based on deep learning, such as YOLO, Faster R-CNN, etc., to achieve accurate recognition and positioning of vehicle targets and pedestrian targets in the image. After obtaining vehicle targets and pedestrian targets through target detection, the system further analyzes the motion characteristics of these targets. For each traffic direction, the system calculates the number of vehicles and vehicle driving speed in that direction, and counts the number of pedestrians and pedestrian moving speed. Specifically, the speed information is calculated by tracking the position change of the target in adjacent frames, and the quantity information is obtained by target counting. Finally, the number of vehicles and vehicle speeds in each direction of travel are used as the vehicle flow information in that direction, and the number of pedestrians and pedestrian moving speeds are used as the pedestrian flow information in that direction. This video analysis-based method can obtain traffic condition information at the intersection in real time and accurately.

[0020] Based on the above embodiment, as an optional embodiment, in step 101: based on the monitoring video, determining the vehicle flow information and pedestrian flow information of multiple traffic directions in the target intersection, this step may also include the following steps: Step 201: pre-process the surveillance video to obtain a target image; perform target detection on the target image to obtain a vehicle target and a pedestrian target.

[0021] The target image refers to the preprocessed surveillance video frame image. The target image is a standardized image obtained by performing preprocessing operations such as frame extraction, denoising, illumination compensation and distortion correction on the original surveillance video. The image has a clear target outline, uniform illumination distribution, low noise level and corrected geometry.

[0022] Vehicle targets refer to motor vehicle entities identified in target images by deep learning target detection algorithms. Vehicle targets contain attribute information such as the position coordinates of the vehicle in the image, the size of the bounding box, the vehicle type, and the detection confidence. The position coordinates represent the spatial position of the vehicle on the image plane, the size of the bounding box reflects the actual space occupied by the vehicle, the vehicle type distinguishes different types of motor vehicles, and the detection confidence indicates the credibility of the target detection result.

[0023] Pedestrian targets refer to pedestrian entities identified in target images through deep learning target detection algorithms. Pedestrian targets contain attribute information such as the position coordinates of pedestrians in the image, bounding box size, pedestrian posture, and detection confidence. The position coordinates represent the spatial position of pedestrians on the image plane, the bounding box size reflects the actual space occupied by pedestrians, the pedestrian posture represents the standing or moving state of pedestrians, and the detection confidence indicates the credibility of the target detection results.

[0024] Specifically, in order to ensure the accuracy of subsequent target detection, the acquired surveillance video needs to be preprocessed first. Since the surveillance video may be affected by environmental factors such as uneven lighting, noise interference, lens distortion, etc., these factors will reduce the effect of target detection. The preprocessing process first extracts frames from the surveillance video and converts continuous video data into a discrete image frame sequence. Then, Gaussian filtering or median filtering algorithm is applied to each frame of the image for denoising to eliminate random noise introduced by the device or environment. Then, illumination compensation is performed by the histogram equalization method to adjust the brightness and contrast of the image so that the image can maintain good visual effects under different lighting conditions. Finally, distortion correction is performed to compensate for the image deformation caused by the camera installation angle or lens characteristics, ensuring that the geometric shape of the target in the image is consistent with the actual. After these preprocessing steps, a clear and standardized target image is obtained. When performing target detection on the preprocessed target image, the system uses computer vision technology to identify and locate vehicle targets and pedestrian targets in the image. The target detection process includes two main steps: feature extraction and target recognition. In the feature extraction stage, the system analyzes visual features such as edges, textures, and colors in the image to construct a feature description of the target. In the target recognition stage, the system determines the category of the target based on the extracted feature information, and calculates the location coordinates and bounding box size of the target. In addition, the system calculates the confidence of the detection results, and filters out possible false detection results by setting a reasonable confidence threshold to improve the accuracy of detection. After this processing, the system can obtain accurate vehicle target and pedestrian target information. Each detected target contains attribute information such as location coordinates, bounding box size, target category, and detection confidence. This information provides a reliable data basis for the subsequent extraction of vehicle flow information and pedestrian flow information.

[0025] Step 202: Based on the vehicle target, determine the number of vehicles and the vehicle speed in each direction of travel, and based on the pedestrian target, determine the number of pedestrians and the pedestrian moving speed in each direction of travel; use the number of vehicles and the vehicle speed in each direction of travel as the vehicle flow information of each direction of travel, and use the number of pedestrians and the pedestrian moving speed in each direction of travel as the pedestrian flow information of each direction of travel.

[0026] Specifically, in order to accurately evaluate the actual traffic demand of each direction of the target intersection, it is necessary to extract vehicle flow information and pedestrian flow information based on the detected vehicle targets and pedestrian targets. This information directly reflects the traffic pressure in each direction of the intersection and is the key data basis for realizing intelligent traffic signal control. First, the system analyzes the vehicle targets in each direction. By counting the number of vehicle target bounding boxes in each direction, the number of vehicles in that direction is obtained. At the same time, the real-time driving speed of the vehicle is obtained by calculating the ratio of the change in the position coordinates of the same vehicle target in adjacent frames to the time interval between frames. Specifically, the system tracks each vehicle target in a continuous sequence of target images, records the change in its position coordinates over time, and calculates the instantaneous speed of the vehicle. This method can accurately reflect the actual motion state of the vehicle and avoids the installation and maintenance costs of traditional speed detection equipment. Then, the system uses a similar method to process pedestrian targets. By counting the number of pedestrian target bounding boxes in the crosswalk area of ​​each direction of travel, the number of pedestrians in that direction is obtained. At the same time, by analyzing the ratio of the change in the position coordinates of the pedestrian target in adjacent frames to the time interval between frames, the moving speed of the pedestrian is calculated. When the moving speed of pedestrian targets is lower than the preset speed threshold, the system determines them as pedestrians waiting to cross the street. The number of these pedestrians directly reflects the intensity of the demand for crossing the street in that direction. The system organizes the number of vehicles and vehicle speeds obtained from each direction of traffic into the traffic information of that direction, and organizes the number of pedestrians and pedestrian moving speeds into the pedestrian information of that direction. This information organization method establishes a standardized data structure, which is convenient for the system to conduct subsequent traffic demand analysis and signal timing optimization. Traffic flow information reflects the traffic demand and operating status of motor vehicles, and pedestrian flow information reflects the crossing demand and waiting status of pedestrians. The two together constitute a complete description of the traffic conditions at the intersection. The traffic flow information and pedestrian flow information obtained in this way are real-time and accurate. The system can capture changes in traffic conditions at intersections in a timely manner and provide reliable data support for subsequent signal control decisions.

[0027] Step 102: For each travel direction, based on the vehicle flow information, the vehicle flow demand saturation and vehicle travel demand ratio of the travel direction are calculated, and based on the pedestrian flow information, the pedestrian crossing demand saturation of the travel direction is calculated.

[0028] The traffic demand saturation refers to the ratio of the length of the vehicle queue in a specific direction of travel to the preset road length in that direction. The length of the vehicle queue is the actual occupied length calculated based on the number of vehicles in that direction and the vehicle speed, and the preset road length is the standard road section length set according to the actual situation at the intersection. This indicator changes dynamically with the number of vehicles and the vehicle driving status, and can reflect the degree of congestion in the direction of travel in real time.

[0029] The vehicle traffic demand ratio refers to the ratio of the length of the vehicle queue in a specific traffic direction to the sum of the lengths of the vehicle queues in all directions at the target intersection. The system first calculates the length of the vehicle queues in each traffic direction at the target intersection, and then divides the length of the vehicle queue in a specific direction by the sum of the lengths of the vehicle queues in all directions to obtain the relative intensity of the traffic demand in that direction at the entire intersection. The calculation of the vehicle queue length comprehensively considers the impact of the number of vehicles and the vehicle speed, and more accurately reflects the actual traffic demand.

[0030] Pedestrian crossing demand saturation refers to the ratio of the actual number of pedestrians waiting to cross the street in a specific direction of travel to the preset benchmark number of pedestrians in that direction. The actual number of pedestrians waiting to cross the street refers to the target number of pedestrians whose moving speed in the crosswalk area is lower than the preset speed threshold. The benchmark number of pedestrians is a standard reference value determined based on factors such as the width of the crosswalk, safe spacing and traffic capacity, reflecting the reasonable capacity of the crosswalk under normal traffic conditions.

[0031] Specifically, the system calculates the length of the vehicle queue based on the number of vehicles in that direction and the vehicle speed, and calculates the ratio of the calculated vehicle queue length to the preset road length in that direction to obtain the traffic demand saturation. When the traffic demand saturation is close to or exceeds 1, it indicates that the vehicle traffic pressure in that direction is relatively large and the traffic time needs to be allocated first. In addition, the calculation of the vehicle queue length also takes into account the influence of the vehicle speed. When the vehicle is at a low speed or stopped, the system will appropriately increase its weight in the queue length calculation. Then calculate the proportion of vehicle traffic demand in each direction. Specifically, the system divides the length of the vehicle queue in a specific direction by the sum of the lengths of the vehicle queues in all directions of the target intersection to obtain the proportion of vehicle traffic demand in that direction. This indicator reflects the relative intensity of traffic demand in each direction and helps the system to reasonably allocate traffic resources among multiple directions. The direction with a larger proportion of vehicle traffic demand should obtain more green light time in the signal timing plan. At the same time, the system calculates the saturation of pedestrian crossing demand based on the pedestrian flow information in each direction. Specifically, the system calculates the ratio of the number of pedestrians in that direction to the preset benchmark number of pedestrians to obtain the saturation of pedestrian crossing demand. Among them, the benchmark number of pedestrians is a reference value determined according to the width and traffic capacity of the crosswalk. When the saturation of pedestrian crossing demand is high, it indicates that there is a large pressure on pedestrians to cross the street in this direction, and the system needs to appropriately extend the green light time of the crosswalk. By calculating these three evaluation indicators, a comprehensive traffic demand evaluation system is established. The traffic demand saturation reflects the traffic pressure of vehicles in a single direction, the proportion of vehicle traffic demand reflects the relative relationship between traffic demands in each direction, and the pedestrian crossing demand saturation represents the urgency of pedestrian crossing. These indicators work together to take into account both the traffic demand of motor vehicles and the demand of pedestrians crossing the street, and can support the system to make more reasonable signal timing decisions.

[0032] Based on the above embodiment, as an optional embodiment, in step 102: based on the traffic information, the traffic demand saturation and vehicle traffic demand ratio of the traffic direction are calculated. This step may also include the following steps: Step 301: Based on the number of vehicles and the vehicle speed in the traffic flow information, the length of the vehicle queue in the travel direction is calculated.

[0033] Among them, the number of vehicles refers to the count value of motor vehicle targets identified in a specific direction of travel, and the vehicle speed refers to the instantaneous speed of these motor vehicle targets when they move on the road. The system collects vehicle movement information in real time through the vehicle detection device, numbers and measures the speed of each identified vehicle target, and thus obtains the number of vehicles and vehicle speed data in the traffic information. The number of vehicles can be understood as the total number of vehicle targets existing in the detection area at the same time, which is a discrete integer value. For example, when 15 vehicles are detected in a certain direction of travel, the number of vehicles in that direction is 15. The vehicle speed can be understood as the displacement change rate of the vehicle target in unit time, usually expressed in meters / second or kilometers / hour. For example, the speed of a vehicle target is 5 meters / second, indicating that the vehicle is moving slowly; when the speed is close to 0, it indicates that the vehicle is in an approximately stationary state.

[0034] The length of the vehicle queue refers to the actual distance from the vehicle stop line to the rear end of the last waiting vehicle. Based on the judgment result of the waiting state of the vehicle, the system converts the number of waiting vehicles with the preset single vehicle length and vehicle spacing to obtain the distance value that reflects the actual queuing space demand of the vehicles. Among them, the waiting state refers to the state where the vehicle speed is lower than the preset speed threshold.

[0035] Specifically, in order to accurately evaluate the actual traffic demand in each direction of the target intersection, the system needs to calculate the length of the vehicle queue through traffic information. As a quantitative indicator of a spatial dimension, the length of the vehicle queue directly reflects the actual spatial distribution of vehicles waiting to pass and is a key parameter for evaluating traffic conditions. The system first obtains the traffic information of a specific direction through a vehicle detection device and determines the position of the vehicle stop line in that direction as the measurement reference point. In the process of obtaining traffic information, the system identifies and numbers each vehicle target in the detection area and measures its instantaneous driving speed. The system sets a speed threshold V0 (for example, 2 meters per second). When the vehicle speed is lower than V0, the vehicle is judged to be in a waiting state. This judgment method based on speed threshold takes into account the possible slight movement of vehicles in actual traffic conditions, which can accurately identify waiting vehicles and avoid misjudging vehicles traveling at normal low speeds as waiting. Next, the system traverses the vehicle targets in the direction of travel, counts the number of vehicles with speeds lower than the threshold V0, and obtains the number of waiting vehicles N. This statistical process is dynamic, and the system will continuously monitor changes in vehicle status and update the number of waiting vehicles in real time. Then, the system converts the number of waiting vehicles into the length of the vehicle queue based on the preset single-vehicle length L (e.g. 5 meters) and the vehicle spacing D (e.g. 2 meters). The conversion formula is: Vehicle queue length = N×(L+D). Among them, the single-vehicle length L is a reference value set according to the standard vehicle model, and the vehicle spacing D takes into account the safe distance that needs to be maintained between adjacent vehicles. Through this queue length calculation method based on waiting state judgment, the system can accurately reflect the actual queue situation in each direction of traffic, providing a data basis for the subsequent calculation of traffic demand saturation and vehicle traffic demand ratio.

[0036] Step 302: The ratio of the length of the vehicle queue to the preset road length is determined as the traffic demand saturation of the travel direction.

[0037] Specifically, according to the actual road conditions of the target intersection, a preset road length L0 is set for each direction of travel. The preset road length is a standard reference value determined based on the physical characteristics of the road (such as the distance from the upstream intersection, road channelization design, etc.) and the traffic capacity requirements, and represents the reasonable queue space under normal traffic conditions in the direction. Then, the system obtains the vehicle queue length L1 calculated in step 301, and performs a ratio operation on it with the preset road length L0 to obtain the traffic demand saturation S. The calculation formula is: S = L1 / L0. This calculation method standardizes the vehicle queue length into a dimensionless ratio indicator, and its value range is usually between 0 and 1. When the traffic demand saturation is equal to 0, it means that there are no vehicles waiting to pass in this direction; when the value is close to 1, it means that the vehicle queue length is close to the preset road length, and there is a large traffic pressure in this direction; when the value exceeds 1, it means that the vehicle queue length has exceeded the preset space range, and there is serious congestion in this direction. The system dynamically monitors the congestion status of each direction of travel by calculating and updating the traffic demand saturation in real time. Through this standardized evaluation method, the system realizes the unified quantification of traffic status in different directions. The traffic demand saturation directly reflects the traffic pressure in each direction and provides a basis for signal timing optimization.

[0038] Step 303: Calculate the ratio of the length of the vehicle queue in the passing direction to the total length of the vehicle queues in all passing directions in the target intersection, and obtain the vehicle traffic demand ratio in the passing direction.

[0039] Specifically, in order to reasonably allocate traffic resources at the intersection, the system needs to calculate the proportion of vehicle traffic demand in each direction. This indicator is calculated by the ratio of the length of the vehicle queue in a specific direction to the total queue length at the intersection, reflecting the relative importance of the direction in the traffic demand of the entire intersection. The system first obtains the vehicle queue length data of all traffic directions at the target intersection. Taking the four entrances as an example, the system obtains the vehicle queue lengths in the straight direction and left turn direction of the east entrance, the straight direction and left turn direction of the south entrance, the straight direction and left turn direction of the west entrance, and the straight direction and left turn direction of the north entrance. Then, the system adds up the queue lengths of these directions to obtain the sum of the vehicle queue lengths in all directions of the intersection. Then, for each specific traffic direction, the system divides the vehicle queue length in that direction by the total queue length to obtain the proportion of vehicle traffic demand in that direction. This calculation method converts the absolute queue lengths of each direction into relative proportion values, and the sum of the proportions of all directions equals one. For example, when the vehicle traffic demand in the straight direction of the east entrance accounts for 30%, it means that the queue length in this direction accounts for 30% of the total queue length at the intersection, reflecting the relatively high traffic demand in this direction. The system dynamically grasps the distribution of traffic demand at the intersection by calculating and updating the demand ratio of each direction in real time. Through this evaluation method based on relative proportion, the system realizes a balanced analysis of traffic demand in each direction at the intersection. As a reference indicator, the vehicle traffic demand ratio reflects the weight of each direction in the overall traffic demand, providing a basis for the refined control of signal timing.

[0040] Based on the above embodiment, as an optional embodiment, in step 102: calculating the pedestrian crossing demand saturation in the passing direction based on the pedestrian flow information, this step may also include the following steps: Step 304: Obtain a baseline number of pedestrians at the crosswalk corresponding to the direction of travel within a preset time interval; based on the pedestrian movement speed and the number of pedestrians in the crowd information, filter out the number of pedestrian targets in a waiting state in the direction of travel, and obtain the number of waiting pedestrians. The pedestrian targets in a waiting state are pedestrians whose movement speed is less than a speed threshold.

[0041] The benchmark number of pedestrians refers to the historical average number of pedestrians at a specific crosswalk within a preset time interval, which is a standard reference value obtained through long-term statistics. The system continuously monitors the pedestrian flow at the crosswalk and accumulates data to calculate the benchmark number of pedestrians that can reflect normal traffic demand.

[0042] The number of waiting pedestrians refers to the real-time statistical number of pedestrian targets whose moving speed is lower than the preset speed threshold in a specific crosswalk area. Specifically, the system obtains the moving speed data of pedestrian targets through the pedestrian flow detection device, determines pedestrians whose speed is lower than the threshold as waiting, and counts these pedestrians in the waiting state.

[0043] Specifically, in order to comprehensively evaluate the traffic demand at the intersection, the system needs to consider not only the traffic conditions of motor vehicles, but also the traffic demand of pedestrians. By comparing the benchmark number of pedestrians and the actual number of waiting pedestrians, the system can accurately grasp the changing characteristics of pedestrian crossing demand and provide a more comprehensive decision-making basis for subsequent signal control optimization. The system first obtains the benchmark number of pedestrians corresponding to the crosswalk in the preset time interval. This benchmark number of pedestrians is a reference value obtained based on historical data statistics, reflecting the pedestrian traffic demand of the crosswalk under normal circumstances. The preset time interval usually selects a duration that matches the signal cycle, such as selecting a complete signal cycle as the statistical interval. The setting of the benchmark number of pedestrians takes into account the characteristics of pedestrian flow in different time periods and can reflect the pedestrian traffic rules during peak and off-peak hours in the morning and evening. Next, the system collects pedestrian flow information in real time through the pedestrian flow detection device to obtain pedestrian movement speed and pedestrian quantity data. The system sets a pedestrian speed threshold, for example, setting the speed threshold to 0.5 meters per second. When it is detected that the pedestrian's movement speed is lower than this threshold, it is determined that the pedestrian is in a waiting state. This judgment method takes into account the fact that pedestrians may move slightly or wander while waiting to cross the street in actual situations. By setting a reasonable speed threshold, it can accurately identify real waiting pedestrians. The system traverses all pedestrian targets in the detection area, counts the number of pedestrians whose moving speed is lower than the threshold, and obtains the number of waiting pedestrians. This statistical process is dynamically updated, and the data is adjusted in real time as the pedestrian group changes. The number of waiting pedestrians directly reflects the current real-time traffic demand of the crosswalk.

[0044] Step 305: The ratio of the number of waiting pedestrians to the benchmark number of pedestrians is determined as the pedestrian crossing demand saturation in the passing direction.

[0045] Specifically, in order to accurately assess the pressure of pedestrian crossing, the system needs to calculate the saturation of pedestrian crossing demand through the relationship between the number of waiting pedestrians and the benchmark number of pedestrians. This saturation index reflects the current service pressure level of the crosswalk by comparing the actual waiting demand with the normal traffic capacity, providing an important basis for the optimization of pedestrian signal timing. First, the number of waiting pedestrians and the preset benchmark number of pedestrians are obtained. For a crosswalk in a specific direction of traffic, the system divides the current number of waiting pedestrians obtained by the statistics by the benchmark number of pedestrians corresponding to the period to obtain the saturation of pedestrian crossing demand in that direction. This calculation method converts the absolute number of waiting pedestrians into a ratio indicator relative to the normal traffic scale, making the traffic pressure of different crosswalks in different periods comparable. As a standardized indicator, the saturation of pedestrian crossing demand not only reflects the relative level of current traffic pressure, but also provides a clear basis for judgment for the optimization of signal control strategies.

[0046] Step 103: Based on the vehicle traffic demand ratio in each direction of travel, a traffic signal light allocation strategy for the target intersection is generated, and based on the traffic demand saturation and pedestrian crossing demand saturation in each direction of travel, a pedestrian signal light allocation strategy for the target intersection is generated.

[0047] The traffic signal allocation strategy refers to the motor vehicle signal time configuration plan formulated for each entrance of the target intersection based on the proportion of vehicle traffic demand in each direction of travel. The strategy includes the specific settings of the timing parameters such as the length of the green light time, phase switching sequence, and cycle length for each direction of travel.

[0048] The pedestrian signal allocation strategy refers to the pedestrian signal time allocation plan for each crosswalk at the target intersection based on the saturation of vehicle demand and pedestrian crossing demand in each direction. The strategy comprehensively evaluates the demand conditions of vehicle and pedestrian flow, and determines the timing parameters such as the length of green light time for each crosswalk, the arrangement of pedestrian traffic phases, and the coordination relationship with motor vehicle signals.

[0049] Specifically, in order to achieve the reasonable allocation of traffic resources at the intersection, the system needs to generate allocation strategies for vehicle traffic lights and pedestrian traffic lights based on the actual demand of each traffic direction. This hierarchical signal timing scheme can take into account the traffic demand of both motor vehicles and pedestrians and improve the overall service level of the intersection. The system first generates a traffic traffic light allocation strategy based on the proportion of vehicle traffic demand. By analyzing the proportion of each traffic direction in the overall traffic demand, the system determines the green light time allocation ratio for each direction. For directions with a higher demand ratio, the system increases its green light time accordingly; for directions with a lower demand ratio, the green light time is appropriately reduced. At the same time, the system also needs to ensure the minimum green light time requirements for each direction to ensure the basic traffic service level. For example, when the traffic demand ratio of the straight direction of the east entrance is 30%, the system will increase the green light time ratio of this direction to the corresponding level on the basis of ensuring the minimum green light time. When generating the pedestrian traffic light allocation strategy, the system comprehensively considers the two indicators of vehicle demand saturation and pedestrian crossing demand saturation. When the pedestrian crossing demand saturation in a certain direction is high, the system will appropriately extend the pedestrian green light time in that direction; but at the same time, the vehicle flow demand saturation in that direction should also be considered to avoid excessively long queues of motor vehicles due to excessive extension of pedestrian green light time. The system balances these two demands by setting a saturation threshold. When the pedestrian crossing demand saturation exceeds the threshold, pedestrian passage is given priority; when the vehicle flow demand saturation is too high, it is necessary to appropriately compress the pedestrian passage time on the basis of ensuring the minimum green light time for pedestrians to improve the traffic efficiency of motor vehicles. This signal timing scheme based on multi-dimensional demand indicators has strong adaptability. The system dynamically responds to changes in traffic demand by adjusting signal timing parameters in real time. When the motor vehicle flow is large during peak hours in the morning and evening, the system will optimize the vehicle flow signal timing according to the proportion of vehicle traffic demand; when the pedestrian flow is concentrated around the commercial area, the system will adjust the pedestrian flow signal timing according to the saturation of pedestrian crossing demand. This refined control strategy effectively alleviates traffic congestion and improves the traffic efficiency of intersections.

[0050] Based on the above embodiment, as an optional embodiment, in step 103: combining the vehicle traffic demand ratio of each traffic direction to generate a traffic signal light allocation strategy for the target intersection, this step may also include the following steps: Step 401: Obtain a preset traffic light cycle duration; allocate the traffic light cycle duration according to the vehicle traffic demand ratio of each traffic direction, and obtain the target green light duration of the lane corresponding to each traffic direction.

[0051] Among them, the preset signal light cycle duration refers to the length of time required for a complete signal timing cycle at the intersection, including the sum of the green light time, yellow light time and all-red time of each phase. This duration is a benchmark parameter determined based on factors such as the physical characteristics of the intersection, traffic flow characteristics and service level requirements, and is usually set in seconds. In an embodiment of the present application, the preset signal light cycle duration can be understood as the basic time unit for intersection signal control. For example, for a typical four-way intersection, the preset signal light cycle duration may be 120 seconds, which means that the signal display at the intersection completes a complete cycle every 120 seconds. Within this cycle, the system needs to reasonably arrange the time allocation for each traffic phase, including the necessary transition interval time (yellow light time and all-red time) and the effective green light time in each direction.

[0052] The target green light duration for lanes in each direction of traffic refers to the effective green light display time allocated to lanes in each direction within the preset signal light cycle according to the proportion of vehicle traffic demand in each direction. Specifically, this duration is the time that each direction can obtain based on the actual demand ratio after deducting the necessary yellow light time and full red time from the total cycle.

[0053] Specifically, the preset signal light cycle duration is obtained. This cycle duration is a basic parameter determined comprehensively based on factors such as the size of the intersection and traffic flow characteristics. For example, for a typical four-way intersection, the signal cycle can be set to 120 seconds. After determining the total cycle duration, the system needs to reserve yellow light time and full red time. These safety intervals are used to ensure the safety of phase conversion. Assuming that each phase conversion requires 3 seconds of yellow light time and 2 seconds of full red time, the system deducts these times from the total cycle to obtain the effective green light time that can be allocated. Then, the system allocates the remaining effective green light time according to the previously counted proportion of vehicle traffic demand in each direction of travel. For example, when the demand for straight travel in the east-west direction accounts for 40%, the demand for straight travel in the north-south direction accounts for 30%, and the demand for left turn accounts for 30%, the system will allocate green light time according to this proportional relationship. Specifically, if the effective green light time that can be allocated is 100 seconds, the east-west direction straight travel will obtain 40 seconds of green light time, the north-south direction straight travel will obtain 30 seconds, and the left turn direction will obtain 30 seconds. When allocating time, the system also needs to consider the minimum green light time requirements for each direction. Even if the demand ratio of a certain direction is very low, its green light time cannot be lower than the preset minimum value to ensure the basic level of traffic service. At the same time, the system will consider some special needs according to the specific conditions of the intersection. For example, if a certain direction is connected to an important traffic artery, its minimum green light time standard can be appropriately increased. This green light time allocation scheme based on demand ratio has strong adaptability. When the traffic demand in each direction changes, the system can dynamically adjust the allocation ratio of green light time to ensure that resource allocation matches actual demand. For example, during the morning rush hour, if the demand ratio of the main road direction increases significantly, the system will increase the green light time of that direction accordingly to improve traffic efficiency. Through this precise time allocation scheme, the system achieves efficient use of traffic resources. Each traffic direction obtains a green light time that matches its demand, which not only avoids congestion and backlog in the high-demand direction, but also reduces the waste of resources in the low-demand direction.

[0054] Step 402: Generate a traffic signal light allocation strategy for a target intersection based on the target green light duration of the lanes corresponding to each direction of travel.

[0055] Specifically, the basic signal phase structure is determined according to the target green light duration in each direction. For traffic directions with cross-conflicts, the system arranges them in different signal phases. For example, when the east-west straight direction obtains a target green light duration of 40 seconds, the north-south straight direction obtains 30 seconds, and the left turn direction obtains 30 seconds, the system will organize these times into several phases according to the principles of safety and efficiency. In each phase, the system arranges non-conflicting traffic to pass at the same time to improve the traffic efficiency of the intersection. Next, the system needs to determine the switching order between the phases. This sequence arrangement needs to consider the continuity and coordination of the turning traffic. For example, after the straight phase ends, the associated left turn phase can be arranged, which can reduce the repeated parking of vehicles. At the same time, the system also inserts the necessary yellow light time and full red time during the phase switching process to ensure the safety of phase conversion. For the common four-phase scheme, it can be cycled in the order of "east-west straight-east-west left turn-north-south straight-north-south left turn". When generating a specific execution plan, the system also needs to consider the handling of some special cases. For example, when there is a backlog of vehicles in a certain direction, the system can appropriately extend the green light time in that direction in the next cycle, but the extended time cannot affect the minimum green light time guarantee in other directions. At the same time, the system must reserve a certain amount of flexible time to deal with emergencies or temporary adjustment needs. This signal light allocation strategy based on the target green light duration is highly practical and adaptable. Through reasonable phase settings and timing arrangements, the system achieves orderly organization of traffic flow at intersections. Traffic in each direction can obtain travel time that matches its needs, and at the same time, through the optimized connection between phases, the parking waiting time of vehicles is reduced.

[0056] Based on the above embodiment, as an optional embodiment, in step 103: combining the traffic demand saturation of each traffic direction and the pedestrian crossing demand saturation to generate a pedestrian traffic light allocation strategy for the target intersection, this step may also include the following steps: Step 403: For each direction of travel, calculate the saturation difference between the traffic demand saturation and the pedestrian crossing demand saturation; when the traffic demand saturation of the direction of travel is greater than or equal to the pedestrian crossing demand saturation, reduce the green light duration of the pedestrian crossing corresponding to the direction of travel by the benchmark duration corresponding to the saturation difference; when the traffic demand saturation of the direction of travel is less than the pedestrian crossing demand saturation, increase or decrease the green light duration of the pedestrian crossing corresponding to the direction of travel by the benchmark duration corresponding to the saturation difference, and obtain the target green light duration of the pedestrian crossing corresponding to the direction of travel.

[0057] Among them, the reference duration refers to the standard unit used to convert the difference between the saturation of vehicle demand and the saturation of pedestrian crossing demand into a specific adjustment time. This duration reflects the correspondence between the saturation difference and the actual signal timing adjustment, and is usually expressed as the number of seconds corresponding to each unit saturation difference. In an embodiment of the present application, the reference duration can be understood as a conversion coefficient, which is used to quantify the degree of influence of the difference in pedestrian and vehicle demand on the signal time. For example, when the reference duration is set to 20 seconds / unit saturation, if the saturation difference in a certain direction is 0.1, the corresponding time adjustment is 2 seconds. This linear correspondence enables the system to perform a corresponding proportion of time adjustment according to different degrees of demand differences, and the specific value of the reference duration can be set according to the actual situation of the intersection.

[0058] Specifically, first calculate the difference between the saturation of vehicle demand and the saturation of pedestrian crossing demand in each direction of traffic. For example, if the saturation of vehicle demand in a certain direction is 1.2 and the saturation of pedestrian crossing demand is 0.8, then the saturation difference is 0.4. This difference reflects the imbalance between the demand for pedestrians and vehicles in this direction, and provides a basis for subsequent time adjustments. At the same time, the system also needs to set a benchmark duration to convert the saturation difference into a specific time adjustment amount. For example, every saturation difference of 0.1 can be corresponded to a benchmark adjustment duration of 2 seconds.

[0059] When the system finds that the traffic demand saturation in a certain direction of traffic is greater than or equal to the pedestrian crossing demand saturation, it means that the traffic pressure in this direction is relatively large, and the green light time of the crosswalk needs to be appropriately reduced. The specific reduction time is equal to the saturation difference multiplied by the reference time. For example, when the saturation difference is 0.4, the corresponding time adjustment is 8 seconds, and the system will subtract these 8 seconds from the original green light time of the crosswalk. However, when making the reduction adjustment, the system needs to ensure that the adjusted green light time is not lower than the preset minimum value to ensure the basic traffic needs of pedestrians.

[0060] When the saturation of traffic demand in a certain direction is less than the saturation of pedestrian crossing demand, it indicates that the pedestrian demand in that direction is relatively high, and the system needs to appropriately increase the green light time of the crosswalk. The increased duration is also determined by the product of the saturation difference and the benchmark duration. For example, if the saturation of traffic demand in a certain direction is 0.7, the saturation of pedestrian crossing demand is 1.1, and the saturation difference is 0.4, the system will increase the green light time of the crosswalk by 8 seconds on the original basis. When adding adjustments, the system also needs to consider the maximum green light time limit to avoid excessive extension that has a significant impact on traffic flow.

[0061] Through this dynamic time adjustment mechanism, the system achieves a refined balance between pedestrian and vehicle traffic demands. When traffic pressure is high, the pedestrian crossing time is appropriately reduced to improve vehicle traffic efficiency; when pedestrian crossing demand is high, the green light time is increased to provide more adequate crossing guarantees.

[0062] Step 404: Generate a pedestrian traffic signal light allocation strategy for the target intersection based on the target green light duration of the pedestrian crossing corresponding to each traffic direction.

[0063] The target green light duration for pedestrian crossings in each direction of traffic refers to the actual effective green light display time allocated to pedestrian crossings in each direction after adjustment based on the difference between the traffic demand saturation and the pedestrian crossing demand saturation. This duration is the final permitted time obtained by dynamically adjusting the original pedestrian crossing green light time based on the calculation of the saturation difference and the benchmark duration.

[0064] Specifically, the basic pedestrian signal timing structure is designed according to the target green light duration of pedestrian crossings in each direction. For pedestrian crossings at four-way intersections, the system usually divides them into two groups, east-west and north-south, and the pedestrian crossings in each group are released synchronously. For example, when the target green light duration of the east-west pedestrian crossing is 30 seconds and that of the north-south pedestrian crossing is 25 seconds, the system will organize these times according to the principles of pedestrian crossing safety and efficiency. During the timing process, the system needs to ensure the coordination of pedestrian signals and motor vehicle signals to avoid conflicts. Next, the system needs to determine the switching sequence of pedestrian signals. This timing arrangement needs to take into account the continuity and waiting experience of pedestrian crossing. For example, before the start of the straight phase of the motor vehicle, a certain amount of advance release time can be given to pedestrians in the corresponding direction in advance, which can reduce the conflict between pedestrians and turning vehicles. At the same time, the system also needs to set sufficient clearing time during the pedestrian signal switching process to ensure that pedestrians can complete the crossing safely. For wider intersections, the system may need to set a longer clearing time. When generating a specific implementation plan, the system also needs to consider some special situation handling mechanisms. For example, when a large number of pedestrians are detected waiting, the system can appropriately extend the pedestrian green light time in that direction in the next cycle, but it must ensure that it does not excessively affect the passage of motor vehicles. At the same time, the system must also reserve response time for pedestrian button triggering, so that it can respond in time when pedestrians request to cross the street.

[0065] Step 104: Control multiple traffic lights in the target intersection according to the vehicle flow signal light allocation strategy and the pedestrian flow signal light allocation strategy.

[0066] Specifically, in order to convert the generated traffic signal allocation strategy and pedestrian signal allocation strategy into actual signal control effects, the system needs to perform coordinated control on multiple traffic lights in the target intersection. This control needs to ensure the precise coordination of traffic signals and pedestrian signals to ensure the safety and efficiency of traffic organization at the intersection. First, a unified control timing framework is established to synchronize the traffic signal allocation strategy and the pedestrian signal allocation strategy. For example, when the east-west lane obtains a target green light duration of 40 seconds and the corresponding pedestrian crossing obtains a target green light duration of 30 seconds, the system will reasonably arrange these times in the same cycle. In specific execution, the system usually gives pedestrians a certain amount of advance release time before releasing motor vehicles, which can improve the safety of pedestrians crossing the street. At the same time, the system also needs to insert necessary transition time in each signal switching process, including yellow light time, full red time and other safety intervals. In the execution control process, the system needs to ensure that the switching of each signal light group strictly follows the preset timing arrangement. For four-way intersections, the system usually divides the traffic lights into motor vehicle signal light groups and pedestrian signal light groups, and the signal lights in each light group are switched synchronously. For example, when the system executes the east-west straight phase, it will simultaneously control the east-west motor vehicle signal lights to display green lights, while the north-south motor vehicle and pedestrian signal lights will display red lights, ensuring the orderly organization of traffic flow.

[0067] The system also needs to establish a real-time monitoring and emergency response mechanism. By collecting real-time data on vehicle and pedestrian traffic at the intersection, the system can determine the effectiveness of the current control scheme. When an emergency occurs, such as a pedestrian button being triggered or a serious backlog of vehicles, the system can make appropriate adjustments to the signal timing for the next cycle while ensuring safety. This dynamic response mechanism enables the system to better adapt to changes in traffic demand.

[0068] This coordinated control based on dual strategies is highly practical. Through precise time control and phase switching, the system achieves orderly organization of pedestrian and vehicle flows. Vehicles and pedestrians in all directions can obtain passage opportunities that match their needs. At the same time, through reasonable time arrangement, traffic conflicts are reduced and the traffic efficiency of the target intersection is improved.

[0069] Based on the above embodiment, as an optional embodiment, in step 104: controlling multiple traffic lights in the target intersection according to the vehicle flow signal light allocation strategy and the pedestrian flow signal light allocation strategy, this step may also include the following steps: Step 501: Determine the first traffic light for the lane corresponding to each travel direction and the second traffic light for the crosswalk corresponding to each travel direction; for each travel direction, adjust the current green light duration of the first traffic light to the target green light duration of the lane corresponding to the travel direction in the traffic signal light allocation strategy.

[0070] The first traffic light refers to the traffic light installed on the lanes corresponding to each direction of traffic at the target intersection, which is used to control the passage of motor vehicles. It is a traffic control device installed at the entrance of the lane, which indicates whether motor vehicles can pass through the red, yellow and green lights. Each direction of traffic may contain one or more first traffic lights, depending on the number of lanes and turning requirements in that direction.

[0071] The second traffic signal is a traffic signal installed at both ends of the crosswalk corresponding to each direction of traffic at the target intersection to control pedestrians crossing the street. It is a traffic control device installed at the entrance of the crosswalk and indicates whether pedestrians can pass through the crosswalk through red and green lights. Each crosswalk usually has a second traffic signal at both ends to ensure that pedestrians can clearly see the signal indication from either end.

[0072] Specifically, the signal lights are first identified and classified. For each direction of travel, the system will identify the traffic light of the corresponding lane as the first traffic light, and the traffic light of the corresponding pedestrian crossing as the second traffic light. For example, in the eastbound direction of travel, the signal light that controls the passage of motor vehicles is the first traffic light, and the signal light that controls pedestrians crossing the street is the second traffic light. This clear classification of signal lights enables the system to accurately perform subsequent duration adjustment operations. After completing the signal light identification, the system needs to read the target green light duration of each direction of travel in the traffic signal light allocation strategy, and apply these durations to the corresponding first traffic lights respectively. For example, when the target green light duration of the eastbound direction of travel is 45 seconds, the system will adjust the green light display time of the first traffic light of the eastbound lane from the current value to 45 seconds. When performing the adjustment, the system needs to ensure the smoothness of the duration change to avoid sudden changes from causing impact on the traffic flow. In order to achieve a smooth transition, the system usually performs the duration adjustment at the beginning of the next complete signal cycle. This can avoid interrupting the green light display in the current cycle and ensure the continuity of vehicle traffic. At the same time, the system also needs to consider the safety interval during the adjustment process, including ensuring sufficient yellow light time and full red time to ensure the safety of phase switching. This signal adjustment method based on the target green light duration has strong operability. By accurately identifying and classifying traffic lights, the system can accurately execute duration adjustment instructions. Traffic in all directions can obtain the passage time that matches their needs, and through a smooth adjustment process, the stable operation of traffic flow is guaranteed.

[0073] Step 502: Adjust the current green light duration of the second signal light to the target green light duration of the pedestrian crossing corresponding to the direction of travel in the pedestrian signal light allocation strategy.

[0074] Specifically, the target green light duration of the pedestrian crossing corresponding to each direction of traffic specified in the pedestrian traffic light allocation strategy is first read, and these durations are applied to the corresponding second traffic lights. For example, when the target green light duration of the eastbound pedestrian crossing is 30 seconds, the system will synchronously adjust the green light display time of the second traffic lights at both ends of the pedestrian crossing in that direction from the current value to 30 seconds. When making adjustments, the system needs to consider the continuity and safety of pedestrian crossings to ensure that the duration adjustment will not affect pedestrians crossing the street. In the specific implementation process, the system usually implements the duration adjustment at the beginning of the next complete signal cycle. This can avoid interrupting pedestrian crossings in the current cycle and ensure the continuity of pedestrian traffic. At the same time, the system also needs to ensure that the adjusted green light duration meets the minimum safe crossing time requirements. For example, for a wider pedestrian crossing, even if the calculated target green light duration is shorter, the system will ensure that it is not less than the minimum time required for pedestrians to cross the street safely. In order to coordinate with motor vehicle signals, the system will consider the timing relationship with the first traffic light in the relevant direction when adjusting the duration of the second traffic light. For example, when a pedestrian crossing in a certain direction gets a green light, the first traffic light in the conflicting turning lane should show a red light to avoid conflicts between pedestrians and vehicles. This coordination mechanism ensures the safety of pedestrians crossing the street, and achieves orderly passage of pedestrian crossings through precise duration control and synchronous adjustment.

[0075] Reference Figure 2 , is a control system for a smart traffic light provided in an embodiment of the present application, the system comprises: an information acquisition module, an information processing module, a strategy generation module, and a traffic light control module, wherein: An information acquisition module is used to acquire surveillance video of a target intersection; based on the surveillance video, determine the traffic flow information and pedestrian flow information of multiple traffic directions in the target intersection; An information processing module is used to calculate the vehicle flow demand saturation and vehicle traffic demand ratio of each traffic direction based on the traffic flow information, and calculate the pedestrian crossing demand saturation of the traffic direction based on the pedestrian flow information; The strategy generation module is used to generate a traffic light allocation strategy for the target intersection based on the vehicle traffic demand ratio in each direction of travel, and to generate a pedestrian traffic light allocation strategy for the target intersection based on the vehicle traffic demand saturation and pedestrian crossing demand saturation in each direction of travel; The signal light control module is used to control multiple traffic lights in the target intersection according to the vehicle flow signal light allocation strategy and the pedestrian flow signal light allocation strategy.

[0076] On the basis of the above-mentioned embodiment, the information acquisition module is also used to pre-process the monitoring video to obtain the target image; perform target detection on the target image to obtain the vehicle target and the pedestrian target; determine the number of vehicles and the vehicle driving speed in each direction of travel based on the vehicle target, and determine the number of pedestrians and the pedestrian moving speed in each direction of travel based on the pedestrian target; use the number of vehicles and the vehicle driving speed in each direction of travel as the vehicle flow information in each direction of travel, and use the number of pedestrians and the pedestrian moving speed in each direction of travel as the pedestrian flow information in each direction of travel.

[0077] On the basis of the above embodiment, the information processing module is also used to calculate the length of the vehicle queue in the direction of travel based on the number of vehicles and the vehicle driving speed in the traffic information; determine the ratio of the vehicle queue length to the preset road length as the traffic demand saturation in the direction of travel; calculate the ratio of the vehicle queue length in the direction of travel to the total length of the vehicle queues in all directions of travel in the target intersection, and obtain the vehicle traffic demand ratio in the direction of travel.

[0078] On the basis of the above embodiment, the information processing module is also used to obtain the benchmark number of pedestrians at the crosswalk corresponding to the travel direction within a preset time interval; based on the pedestrian movement speed and the number of pedestrians in the crowd information, the number of pedestrian targets in a waiting state in the travel direction is screened out to obtain the number of waiting pedestrians, and the pedestrian targets in a waiting state are pedestrians whose movement speed is less than a speed threshold; the ratio of the number of waiting pedestrians to the benchmark number of pedestrians is determined as the pedestrian crossing demand saturation in the travel direction.

[0079] Based on the above embodiment, the strategy generation module is also used to obtain the preset signal light cycle duration; allocate the signal light cycle duration according to the proportion of vehicle traffic demand in each direction of travel, and obtain the target green light duration of the lanes corresponding to each direction of travel; based on the target green light duration of the lanes corresponding to each direction of travel, generate the traffic signal light allocation strategy for the target intersection.

[0080] On the basis of the above embodiment, the strategy generation module is also used to calculate the saturation difference between the traffic demand saturation and the pedestrian crossing demand saturation for each direction of travel; when the traffic demand saturation of the direction of travel is greater than or equal to the pedestrian crossing demand saturation, the green light duration of the pedestrian crossing corresponding to the direction of travel is reduced by the benchmark duration corresponding to the saturation difference; when the traffic demand saturation of the direction of travel is less than the pedestrian crossing demand saturation, the green light duration of the pedestrian crossing corresponding to the direction of travel is increased or decreased by the benchmark duration corresponding to the saturation difference to obtain the target green light duration of the pedestrian crossing corresponding to the direction of travel; based on the target green light duration of the pedestrian crossing corresponding to each direction of travel, a pedestrian signal light allocation strategy for the target intersection is generated.

[0081] Based on the above embodiment, the traffic light control module is also used to determine the first traffic light for the lane corresponding to each direction of travel and the second traffic light for the crosswalk corresponding to each direction of travel; for each direction of travel, the current green light duration of the first traffic light is adjusted to the target green light duration of the lane corresponding to the direction of travel in the traffic signal light allocation strategy; the current green light duration of the second traffic light is adjusted to the target green light duration of the crosswalk corresponding to the direction of travel in the pedestrian signal light allocation strategy.

[0082] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0083] The present application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0084] The communication bus 302 is used to realize the connection and communication between these components.

[0085] The user interface 303 may include a display interface and a camera interface. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0086] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0087] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface diagrams and applications, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0088] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 , the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a method for controlling a smart traffic light.

[0089] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call the application program of a control method of a smart traffic light stored in the memory 305. When executed by one or more processors 301, the electronic device 300 executes one or more methods in the above-mentioned embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0090] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0092] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0093] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0094] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0095] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0096] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not recorded in the present disclosure. The description and examples are to be regarded as exemplary only.

Claims

1. A method for controlling a smart traffic signal light, characterized in that: include: Obtain surveillance video of the target intersection; Based on the monitoring video, determine the vehicle flow information and pedestrian flow information in multiple traffic directions at the target intersection; For each of the traffic directions, based on the traffic information, the traffic demand saturation and vehicle traffic demand ratio of the traffic direction are calculated, and based on the pedestrian flow information, the pedestrian crossing demand saturation of the traffic direction is calculated; Combined with the vehicle traffic demand ratio of each of the traffic directions, a traffic signal light allocation strategy for the target intersection is generated; combined with the traffic demand saturation and pedestrian crossing demand saturation of each of the traffic directions, a pedestrian signal light allocation strategy for the target intersection is generated; According to the vehicle flow signal light allocation strategy and the pedestrian flow signal light allocation strategy, multiple traffic lights in the target intersection are controlled.

2. The control method of the intelligent traffic signal light according to claim 1, characterized in that: The determining, based on the surveillance video, vehicle flow information and pedestrian flow information in multiple traffic directions at the target intersection includes: Preprocessing the surveillance video to obtain a target image; Performing target detection on the target image to obtain vehicle targets and pedestrian targets; Based on the vehicle target, determine the number of vehicles and the vehicle travel speed in each of the travel directions, and based on the pedestrian target, determine the number of pedestrians and the pedestrian movement speed in each of the travel directions; The number of vehicles and the vehicle travel speed in each of the travel directions are used as the vehicle flow information in each of the travel directions, and the number of pedestrians and the pedestrian moving speed in each of the travel directions are used as the pedestrian flow information in each of the travel directions.

3. The control method of the intelligent traffic signal light according to claim 1, characterized in that: The calculating, based on the traffic information, the traffic demand saturation and vehicle traffic demand proportion of the traffic direction includes: Calculating the length of the vehicle queue in the travel direction based on the number of vehicles and the vehicle travel speed in the traffic flow information; The ratio of the vehicle queue length to the preset road length is determined as the traffic demand saturation of the travel direction; The ratio of the length of the vehicle queue in the travel direction to the total length of the vehicle queues in all travel directions in the target intersection is calculated to obtain the vehicle traffic demand ratio in the travel direction.

4. The control method of the intelligent traffic signal light according to claim 1, characterized in that: The calculating the pedestrian crossing demand saturation in the traffic direction based on the pedestrian flow information includes: Obtaining a baseline number of pedestrians passing through the crosswalk corresponding to the passing direction within a preset time interval; Based on the pedestrian moving speed and the number of pedestrians in the pedestrian flow information, the number of pedestrian targets in a waiting state in the passing direction is screened out to obtain the number of waiting pedestrians, wherein the pedestrian targets in a waiting state are pedestrians whose pedestrian moving speed is less than a speed threshold; The ratio of the number of waiting pedestrians to the benchmark number of pedestrians is determined as the pedestrian crossing demand saturation in the traffic direction.

5. The control method of the intelligent traffic signal light according to claim 1, characterized in that: The generating of the traffic signal light allocation strategy of the target intersection in combination with the vehicle traffic demand ratio of each traffic direction includes: Get the preset signal light cycle duration; Allocate the signal light cycle duration according to the vehicle traffic demand ratio of each traffic direction to obtain the target green light duration of the lane corresponding to each traffic direction; Based on the target green light duration of the lane corresponding to each of the travel directions, a traffic signal light allocation strategy for the target intersection is generated.

6. The control method of the intelligent traffic signal light according to claim 1, characterized in that: The generating of the pedestrian traffic light allocation strategy at the target intersection by combining the vehicle flow demand saturation and pedestrian crossing demand saturation of each of the traffic directions includes: For each of the traffic directions, calculating the saturation difference between the traffic demand saturation and the pedestrian crossing demand saturation; When the traffic demand saturation of the passage direction is greater than or equal to the pedestrian crossing demand saturation, the green light duration of the pedestrian crossing corresponding to the passage direction is reduced by the reference duration corresponding to the saturation difference; when the traffic demand saturation of the passage direction is less than the pedestrian crossing demand saturation, the green light duration of the pedestrian crossing corresponding to the passage direction is increased or decreased by the reference duration corresponding to the saturation difference to obtain the target green light duration of the pedestrian crossing corresponding to the passage direction; Based on the target green light duration of the pedestrian crossing corresponding to each of the traffic directions, a pedestrian traffic signal light allocation strategy for the target intersection is generated.

7. The control method of the intelligent traffic signal light according to claim 1, characterized in that: The controlling of the plurality of traffic lights in the target intersection according to the vehicle flow signal light allocation strategy and the pedestrian flow signal light allocation strategy includes: Determine a first traffic light for a lane corresponding to each of the passing directions and a second traffic light for a crosswalk corresponding to each of the passing directions; For each of the passing directions, adjusting the current green light duration of the first signal light to the target green light duration of the lane corresponding to the passing direction in the traffic signal light allocation strategy; The current green light duration of the second signal light is adjusted to the target green light duration of the pedestrian crossing corresponding to the direction of travel in the pedestrian signal light allocation strategy.

8. A control method system for a smart traffic signal light, characterized in that: The system comprises: An information acquisition module is used to acquire a surveillance video of a target intersection; based on the surveillance video, determine the vehicle flow information and pedestrian flow information of multiple traffic directions in the target intersection; An information processing module, for calculating, for each of the traffic directions, the vehicle flow demand saturation and vehicle traffic demand ratio of the traffic direction based on the traffic flow information, and calculating the pedestrian crossing demand saturation of the traffic direction based on the pedestrian flow information; A strategy generation module, for generating a traffic light allocation strategy for the target intersection based on the vehicle traffic demand ratio of each of the traffic directions, and for generating a pedestrian traffic light allocation strategy for the target intersection based on the traffic demand saturation and pedestrian crossing demand saturation of each of the traffic directions; The signal light control module is used to control multiple traffic lights in the target intersection according to the vehicle flow signal light allocation strategy and the pedestrian flow signal light allocation strategy.

9. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the control method of the smart traffic light as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the control method of the smart traffic light as described in any one of claims 1-7 is executed.

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