A traffic signal lamp control method and system based on edge computing

Abstract

The embodiment of the application relates to the technical field of traffic management, and discloses a traffic signal lamp control method and system based on edge calculation, wherein the traffic signal lamp control method detects and judges the traffic abnormal state of a target area of a branch road according to an edge processor; when detecting that the traffic flow of the branch road has a large dynamic change (such as an abnormal vehicle failure condition), adaptive control is performed on each traffic signal lamp at a crossroad according to real-time traffic flow data of straight vehicles on a main road, straight vehicle traffic on the main road is preferentially guaranteed, and the phenomenon of resource idling and waste at the target cross section is avoided, so that the technical scheme of the application can adapt to complex and changeable traffic environments, and the road traffic capacity and traffic efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of traffic management technology, specifically to a traffic signal control method and system based on edge computing. Background Technology

[0002] With the acceleration of urbanization, road traffic volume is increasing daily, and traffic congestion is becoming increasingly serious. Traditional traffic light control methods often use fixed time allocation patterns, which cannot be flexibly adjusted according to real-time traffic conditions, resulting in low utilization efficiency of road resources. Especially at some intersections, the traffic volume on main roads and branch roads varies greatly. Fixed signal duration settings can easily lead to traffic congestion on some road sections while other road sections are idle. For example, when there are emergencies such as vehicle breakdowns on a road, traditional signal light systems cannot make timely and flexible adjustments, further exacerbating traffic congestion.

[0003] Against this backdrop, the development of edge computing technology has provided a new solution for traffic signal control. Edge computing brings computation and data storage closer to the data source or user, reducing data transmission latency and enabling real-time processing of traffic data. This allows traffic signal control systems to dynamically adjust based on the actual traffic conditions at intersections. For example, at intersections with main roads and branch roads, the traffic demand on branch roads varies significantly at different times. In some cases, such as when vehicles with specific traffic conditions appear in the target area, more refined signal control strategies are needed to optimize traffic flow to better adapt to complex and changing traffic environments, thereby improving road capacity and traffic efficiency. Summary of the Invention

[0004] The main objective of this invention is to provide a traffic signal control method and system based on edge computing, which aims to solve the technical problem of low traffic efficiency under certain circumstances in the prior art.

[0005] To achieve the above objectives, in a first aspect, this application provides a traffic signal control method based on edge computing, applied to a traffic signal control system, wherein the traffic signal control system includes an edge processor located at a target intersection, and the method includes:

[0006] Obtain the traffic status of vehicles within a target area, wherein the target area is located on a branch road of a target intersection;

[0007] If there are target vehicles in the target area that meet the preset traffic conditions, the traffic indication status of the first traffic light is obtained. The first traffic light is used to indicate the traffic flow turning on the branch road.

[0008] If the first traffic light is in a green light state, control the first traffic light to remain in a green light state until all vehicles in front of the target vehicle have completed their turning and proceeding.

[0009] The third traffic light is controlled to maintain the lane change and queue-jumping indication state until the waiting area in front of the target vehicle is full. The third traffic light is located on one side of the target area and is used to indicate lane change and queue-jumping.

[0010] Based on real-time traffic flow data of vehicles traveling straight on the main road, the first, second, and third traffic lights are used to provide traffic indication control. The second traffic light is used to provide traffic indication for vehicles traveling straight on the main road, and the green light duration of the second traffic light is greater than that of the first traffic light.

[0011] In one possible implementation, the traffic signal control system further includes a lidar located in the target area, wherein acquiring the traffic status of vehicles within the target area includes:

[0012] The speed of vehicles passing through the target area is obtained by the lidar;

[0013] When a target vehicle meeting a preset traffic condition exists within the target area, obtaining the traffic indication status of the first traffic light includes:

[0014] If a vehicle in the target area has a speed less than or equal to a preset speed for a preset duration, it is determined that there is a target vehicle in the target area that meets the preset traffic conditions.

[0015] The edge processor obtains the traffic signal light's passage indication status.

[0016] In one possible implementation, if the first traffic light is in a green light state, controlling the first traffic light to remain in a green light state until all vehicles in front of the target vehicle have completed their turns to proceed includes:

[0017] If the first traffic light is in a green light state, control the first traffic light to remain in a green light state, and switch the green light state to a red light state after all vehicles in front of the target vehicle have completed their turning and passing.

[0018] In one possible implementation, controlling the third traffic light to maintain the lane-changing / queue-jumping indication state until the waiting area in front of the target vehicle is full includes:

[0019] The third traffic light is controlled to maintain the lane change and queue-jumping indication state, and after the waiting area in front of the target vehicle is full, the lane change and queue-jumping indication state is switched to the lane change and queue-jumping prohibition indication state.

[0020] In one possible implementation, the traffic signal control system further includes a traffic flow monitoring device installed on the main road. The step of controlling the first, second, and third traffic signals based on real-time traffic flow data of through traffic on the main road includes:

[0021] The traffic flow monitoring data of the traffic flow monitoring device is obtained through the edge processor;

[0022] Based on the traffic flow monitoring data, a target traffic control strategy is determined for the first traffic light, the second traffic light, and the third traffic light.

[0023] According to the target traffic control strategy, the first traffic light, the second traffic light, and the third traffic light are controlled to indicate traffic flow.

[0024] In one possible implementation, determining the target traffic control strategy for the first traffic light, the second traffic light, and the third traffic light based on the traffic flow monitoring data includes:

[0025] Based on the traffic flow monitoring data, a first sub-traffic control strategy is determined for the first traffic light and the second traffic light;

[0026] A second sub-traffic control strategy is determined for the first and third traffic lights based on the first sub-traffic control strategy.

[0027] In one possible implementation, determining the first sub-traffic control strategy for the first traffic light and the second traffic light based on the traffic flow monitoring data includes:

[0028] The green light duration percentages of the first and second traffic lights are determined based on the traffic flow monitoring data, wherein the green light duration percentage of the second traffic light is positively correlated with the traffic flow monitoring data, and / or the green light duration percentage of the first traffic light is negatively correlated with the traffic flow monitoring data.

[0029] In one possible implementation, determining the second sub-traffic control strategy for the first traffic light and the third traffic light based on the first sub-traffic control strategy includes:

[0030] The traffic control strategy for the third traffic light is determined based on the traffic indication status of the first traffic light. Specifically, when the traffic indication status of the first traffic light switches to a green light, the third traffic light is controlled to switch to a lane-changing and queue-jumping indication status. After a preset time following the switch of the traffic indication status of the first traffic light to a red light prohibiting traffic, the third traffic light is controlled to switch to a lane-changing and queue-jumping prohibiting indication status.

[0031] In one possible implementation, the traffic signal control system further includes a geomagnetic sensor array, and the method further includes:

[0032] The geomagnetic sensor array is used to detect vehicle occupancy in the waiting area.

[0033] When all the geomagnetic sensor arrays in the waiting area trigger the sensing signal, it is determined that the waiting area has been filled.

[0034] Secondly, this application also provides a traffic signal light control system, including:

[0035] A lidar is installed in a target area on a branch road, the target area being a region within a preset range from the waiting stop line, and is used to monitor the traffic status of vehicles within the target area;

[0036] Traffic flow monitoring devices are installed on main roads to monitor traffic flow.

[0037] A geomagnetic sensor array is installed in the waiting area of ​​a branch road, the waiting area being the area between the target area and the waiting stop line, for detecting vehicles occupying the waiting area;

[0038] The first traffic light is used to indicate the passage of turning traffic on the branch road;

[0039] The second traffic light is used to indicate the passage of straight-through traffic on the main road;

[0040] The third traffic light is located on one side of the target area and is used to indicate lane changing and queue cutting.

[0041] Memory, the memory being used to store program code; and

[0042] A processor, the processor being configured to invoke the program code to execute the method as described in the first aspect.

[0043] Unlike existing technologies, this application provides a traffic light control method based on edge computing. First, it acquires the traffic status of vehicles within a target area. If a target vehicle meets a preset traffic status within the target area, it acquires the traffic indication status of a first traffic light. If the first traffic light's traffic indication status is green, it controls the first traffic light to maintain the green light until all vehicles in front of the target vehicle have completed their turns. Then, it controls a third traffic light to maintain the lane-changing / queue-jumping indication status until the waiting area in front of the target vehicle is full. Next, it determines a target traffic control strategy for the first, second, and third traffic lights based on real-time traffic flow data of vehicles traveling straight on the main road. Finally, it controls the traffic flow of the first, second, and third traffic lights according to this target traffic control strategy. In other words, when a significant dynamic change (abnormal situation) in the traffic flow of a branch road is detected, the traffic lights at the intersection are adaptively controlled based on the real-time traffic flow data of vehicles traveling straight on the main road, thereby adapting to the complex and ever-changing traffic environment and improving the road's capacity and traffic efficiency. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram of the layout of a traffic signal control system in some embodiments of this application;

[0046] Figure 2 This is a schematic diagram showing the layout of the geomagnetic sensor array in some embodiments of this application;

[0047] Figure 3 This is a flowchart illustrating a traffic light control method based on edge computing in some embodiments of this application;

[0048] Figure 4 This is a flowchart illustrating a traffic light control method based on edge computing in some other embodiments of this application;

[0049] Figure 5 This is a schematic diagram of the module structure of a traffic signal control system in some embodiments of this application.

[0050] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0052] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0053] Furthermore, the use of terms such as "first" and "second" in this invention is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the term "and / or" throughout the text includes three solutions; taking A and / or B as an example, it includes technical solution A, technical solution B, and a technical solution that simultaneously satisfies A and B. Furthermore, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of a person skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0054] With the acceleration of urbanization, road traffic volume is increasing daily, and traffic congestion is becoming increasingly serious. Traditional traffic light control methods often use fixed time allocation patterns, which cannot be flexibly adjusted according to real-time traffic conditions, resulting in low utilization efficiency of road resources. Especially at some intersections, the traffic volume on main roads and branch roads varies greatly. Fixed signal duration settings can easily lead to traffic congestion on some road sections while other road sections are idle. For example, when there are emergencies such as vehicle breakdowns on a road, traditional signal light systems cannot make timely and flexible adjustments, further exacerbating traffic congestion.

[0055] Against this backdrop, the development of edge computing technology has provided a new solution for traffic signal control. Edge computing brings computation and data storage closer to the data source or user, reducing data transmission latency and enabling real-time processing of traffic data. This allows traffic signal control systems to dynamically adjust based on the actual traffic conditions at intersections. For example, at intersections with main roads and branch roads, the traffic demand on branch roads varies significantly at different times. In some cases, such as when vehicles with specific traffic conditions appear in the target area, more refined signal control strategies are needed to optimize traffic flow to better adapt to complex and changing traffic environments, thereby improving road capacity and traffic efficiency.

[0056] It is particularly important to note that if a vehicle breaks down near the waiting area (pedestrian crossing) at an intersection, and vehicles cannot be guided through in an orderly manner, it can easily cause traffic congestion at the intersection.

[0057] like Figure 1-2 As shown in the embodiment of this application, the traffic signal control system is deployed at a target intersection, which can be a crossroads or a T-junction. The target intersection includes a main road D100 and a branch road D200. The branch road D200 includes a target area P100 and a waiting area P200 located in front of the target area P100. The target area P100 is an area within a preset range (e.g., 50-100 meters) from the waiting stop line L100, and the waiting area P200 is the area between the target area P100 and the waiting stop line L100. The traffic signal control system of this application includes:

[0058] The lidar 100 is installed in the target area P100 of the branch road D200 to monitor the traffic status of vehicles in the target area P100, such as the direction of traffic, speed or acceleration of vehicles.

[0059] Traffic flow monitoring device 200 is installed on the main road D100 to monitor the traffic flow on the main road D100. The traffic flow monitoring device 200 can be a camera, magnetic sensor or lidar, etc.

[0060] A geomagnetic sensor array 300 is installed in the waiting area P200 of the branch road D200 to detect vehicles occupying spaces in the waiting area P200.

[0061] The first traffic light 400 is used to indicate the passage of turning traffic on the branch road D200;

[0062] The second traffic signal light 500 is used to indicate the passage of straight-through traffic on the main road D100.

[0063] The third traffic light 600, located on one side of the target area P100, is used to indicate lane-changing and queuing procedures. For example, when a vehicle in the target area P100 breaks down and stops, it instructs vehicles behind it to change lanes and cut in line; and...

[0064] An edge processor 700 is installed in the target intersection area and is connected via wires to a lidar 100, a traffic flow monitor 200, a geomagnetic sensor array 300, a first traffic light 400, a second traffic light 500, and a third traffic light 600. It is used to acquire and analyze the monitoring data of each sensor and to control the first traffic light 400, the second traffic light 500, and the third traffic light 600 to provide traffic indication based on the analysis results.

[0065] Thus, the traffic signal control system of this application fully utilizes edge computing technology, that is, distributes computing and data processing capabilities to edge processor devices close to the data source, to achieve real-time and accurate monitoring and intelligent and flexible control of traffic conditions at target intersections, effectively improving traffic efficiency, emergency response capabilities and system reliability, and providing an efficient, intelligent and reliable solution for modern urban traffic management.

[0066] like Figures 1-4 As shown, the following explanation uses a traffic signal control system as an example to illustrate the execution of this edge computing-based traffic signal control method. It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order. Please refer to the appendix. Figure 3 The method includes the following steps S100-S500:

[0067] Step S100: Obtain the traffic status of vehicles within the target area;

[0068] There are several ways to obtain the traffic status of vehicles within a target area. For example, it can be obtained through camera equipment, geomagnetic sensors, or, in other embodiments, lidar. The traffic status of vehicles can include vehicle speed, direction of travel, and acceleration.

[0069] In one embodiment, step S100, acquiring the traffic status of vehicles within the target area, includes: acquiring the traffic speed of vehicles within the target area using a lidar; specifically, the lidar 100 scans the target area P100 at a preset frequency, and determines the presence, speed, direction, and other traffic status of vehicles by identifying the reflected laser signals. The edge processor 700 processes the collected data and extracts vehicle traffic status information, such as vehicle speed. That is, the vehicle speed is acquired using the Time-of-Flight (TOF) principle.

[0070] Step S200: If there is a target vehicle in the target area that meets the preset passage conditions, obtain the passage indication status of the first traffic light;

[0071] In this embodiment, the edge processor 700 determines whether there is a target vehicle in the target area P100 that meets a preset traffic condition (such as speed below a certain threshold, breakdown, etc.) based on the data provided by the lidar 100. If such a target vehicle exists, the edge processor 700 further obtains the current traffic indication status (red light, green light, or yellow light) of the first traffic light 400.

[0072] In one embodiment, the step of obtaining the traffic indication status of the first traffic light when there is a target vehicle in the target area that meets the preset traffic conditions includes: determining that there is a target vehicle in the target area that meets the preset traffic conditions when there is a vehicle in the target area whose speed is less than or equal to a preset speed for a preset duration; and obtaining the traffic indication status of the first traffic light through the edge processor.

[0073] Specifically, the lidar 100 continuously scans within the target area P100 and calculates the vehicle speed by measuring the round-trip time of the laser pulse. The edge processor 700 receives the data from the lidar 100 and calculates the speed of each vehicle within the target area in real time. The edge processor 700 compares the calculated speed with a preset speed (e.g., below a certain threshold, such as 5 km / h or lower). Simultaneously, the edge processor 700 also determines whether the speed being lower than or equal to the preset speed has lasted for a preset duration (e.g., 5 seconds, 10 seconds, etc.) to avoid misidentifying a vehicle as a target due to a brief deceleration or stop. If a vehicle within the target area has a speed less than or equal to the preset speed for a preset duration, the edge processor 700 determines that a target vehicle meeting the preset traffic conditions exists within the target area, indicating that the target vehicle is a disabled parked vehicle. Once the existence of the target vehicle is confirmed, the edge processor 700 sends a query command to the first traffic light 400, requesting the current traffic indication status (red, green, or yellow light). After receiving the query command, the first traffic light 400 returns the current traffic indication status to the edge processor 700.

[0074] Step S300: If the first traffic light is in a green light state, control the first traffic light to remain in a green light state until all vehicles in front of the target vehicle have completed their turns and proceeded.

[0075] In this embodiment, after confirming that the first traffic light 400 is green, the edge processor 700 sends a command to the first traffic light 400 to maintain the green light via a communication interface. Simultaneously, the edge processor 700 uses data from the lidar 100 and / or the geomagnetic sensor array 300 to monitor the traffic conditions ahead of the target vehicle until all vehicles have completed their turns and proceeded.

[0076] In one embodiment, step S300: if the first traffic light is in a green light state, control the first traffic light to maintain the green light state until all vehicles in front of the target vehicle have completed their turns to proceed, including:

[0077] If the first traffic light is in a green light state, control the first traffic light to remain in a green light state, and switch the green light state to a red light state after all vehicles in front of the target vehicle have completed their turning and passing.

[0078] For example, if the system detects a disabled vehicle within the target area, it immediately executes the control strategy for the first traffic light. By maintaining its green light status, sufficient time and passage conditions are provided for vehicles ahead of the disabled vehicle, allowing them to quickly leave their current position and preventing the formation of a congestion point in the area. Once all these vehicles have completed their turn, the traffic light is quickly turned red, effectively preventing disorderly overtaking and cutting in line by vehicles behind the disabled vehicle. This avoids traffic congestion caused by vehicles vying for space on side roads, while also creating reasonable space and order for the orderly passage of subsequent vehicles.

[0079] Step S400: Control the third traffic light to maintain the lane change and queue cutting indication state until the waiting area in front of the target vehicle is full;

[0080] Once all vehicles ahead of the target vehicle have successfully moved out of their current positions, and given that a certain amount of usable space has been freed up in the waiting area, the system will precisely control the third traffic light to enter lane-changing / queue-jumping mode. This creates a reasonable path for vehicles behind the target vehicle, allowing them to skillfully avoid the disabled vehicle and enter the waiting area in an orderly manner, preparing to turn and proceed. This process will continue until the waiting area in front of the target vehicle is completely filled by subsequent vehicles, making full use of limited road resources and improving overall traffic efficiency.

[0081] Once the waiting area in front of the target vehicle is full, the system will respond quickly, switching the third traffic light from a lane-changing / cutting-in indicating permission to change lanes / cut in to a no-lane-changing / cutting-in indicating permission to change lanes / cut in. This timely and precise control effectively regulates traffic flow, preventing traffic chaos caused by excessive cutting in line or disorderly lane changes. It ensures that vehicles behind the disabled vehicle can safely and efficiently enter the waiting area and patiently wait for their turn, thus maintaining a stable and smooth traffic flow even in complex traffic conditions.

[0082] In one embodiment, the traffic light control method further includes a step of detecting whether the waiting area is full:

[0083] Step S600: Detect vehicle occupancy in the waiting area using a geomagnetic sensor array;

[0084] Step S700: When all the geomagnetic sensor arrays in the waiting area trigger the sensing signal, it is determined that the waiting area has been filled.

[0085] Specifically, such as Figure 2 As shown, a geomagnetic sensor array is deployed within a traffic waiting area, with each sensor capable of detecting changes in the magnetic field above or near it. When a vehicle enters the waiting area and stops above a sensor, that sensor detects the change in the magnetic field and triggers a sensing signal. When every sensor in the geomagnetic sensor array within the waiting area has triggered a sensing signal, it is determined that the waiting area is full.

[0086] Step S500: Based on the real-time traffic flow data of straight-through vehicles on the main road, conduct traffic indication control on the first traffic light, the second traffic light and the third traffic light, wherein the green light duration of the second traffic light is greater than the green light duration of the first traffic light.

[0087] When there are vehicles waiting to pass on both the branch roads and the main roads, this embodiment of the application first determines the target traffic control strategy for the first traffic light, the second traffic light and the third traffic light based on the real-time traffic flow data of the straight-through vehicles on the main roads, and then performs traffic indication control on the first traffic light, the second traffic light and the third traffic light according to the target traffic control strategy.

[0088] For example, traffic flow monitoring data from a traffic flow monitoring device is acquired via an edge processor; and a target traffic control strategy for the first, second, and third traffic lights is determined based on the traffic flow monitoring data.

[0089] Specifically, the traffic flow monitoring device 200 (such as a camera, magnetic sensor, or lidar) collects real-time traffic flow data of straight-through vehicles on the main road D100. The edge processor 700 analyzes the collected traffic flow data and, in conjunction with a preset traffic control algorithm or model, determines the optimal traffic control strategy (i.e., the target traffic control strategy). This may include adjusting parameters such as the green light duration, red light duration, and yellow light duration of the first traffic light 400, the second traffic light 500, and the third traffic light 600.

[0090] In one embodiment, determining a target traffic control strategy for the first traffic light, the second traffic light, and the third traffic light based on traffic flow monitoring data includes:

[0091] Based on the traffic flow monitoring data, a first sub-traffic control strategy is determined for the first traffic light and the second traffic light;

[0092] A second sub-traffic control strategy is determined for the first and third traffic lights based on the first sub-traffic control strategy.

[0093] Specifically, the green light duration ratios of the first and second traffic lights (i.e., the first sub-traffic control strategy) can first be determined based on traffic flow monitoring data. The green light duration ratio of the second traffic light is positively correlated with the traffic flow monitoring data, and / or the green light duration ratio of the first traffic light is negatively correlated with the traffic flow monitoring data. That is, if traffic flow monitoring data indicates a large amount of straight-through traffic on the main road, the green light duration ratio of the second traffic light is increased, and the green light duration ratio of the first traffic light is decreased. In this way, when faced with sudden drops in traffic efficiency on branch roads due to unexpected situations such as disabled vehicles, the allocation of road resources can be optimized, maximizing the efficient passage of main roads, effectively avoiding resource idleness and waste at target intersections, and significantly improving the overall operational efficiency of the traffic network. After determining the first sub-traffic control strategy, this embodiment of the application determines the traffic control strategy for the third traffic light (i.e., the second sub-traffic control strategy) based on the traffic indication status of the first traffic light.

[0094] For example, when the first traffic light switches to a green light to go, the third traffic light switches to a lane-changing / queue-jumping indicator, allowing vehicles in the branch road waiting area to leave their current positions and simultaneously instructing following vehicles to enter the waiting area in an orderly manner to wait for turning. When the first traffic light switches to a red light to prohibit going, the system does not immediately disable the lane-changing / queue-jumping indicator function of the third traffic light after a preset delay. Instead, it switches it to a no-lane-changing / queue-jumping indicator state after a preset delay. This fully considers the vehicle's inertia and reaction time in actual traffic scenarios, providing sufficient and reasonable time windows for following vehicles to safely and orderly enter the waiting area to wait for turning within the short time after the red light turns on. This not only effectively avoids problems such as sudden braking and chaotic queue-jumping caused by abrupt traffic light switching, but also further ensures the continuity and stability of traffic flow on branch roads, allowing the entire traffic flow to maintain an efficient and orderly operation even in complex and changing conditions.

[0095] After obtaining the target traffic control strategy for the first, second, and third traffic lights, the edge processor 700 sends corresponding traffic indication control commands to the first traffic light 400, second traffic light 500, and third traffic light 600 via the communication interface according to the determined target traffic control strategy. The entire traffic indication strategy ensures that the green light duration of the second traffic light 500 is greater than that of the first traffic light 400, so as to prioritize the passage of straight-through vehicles on the main road D100 in the event of vehicle malfunctions on branch roads.

[0096] Based on this, this application provides a traffic light control method based on edge computing. First, it acquires the traffic status of vehicles within a target area. If a target vehicle meets a preset traffic status within the target area, it acquires the traffic indication status of a first traffic light. If the first traffic light's traffic indication status is green, it controls the first traffic light to maintain the green light until all vehicles in front of the target vehicle have completed their turns. Then, it controls a third traffic light to maintain the lane-changing / queue-jumping indication status until the waiting area in front of the target vehicle is full. Next, it determines a target traffic control strategy for the first, second, and third traffic lights based on real-time traffic flow data of vehicles traveling straight on the main road. Finally, it controls the traffic flow of the first, second, and third traffic lights according to this target traffic control strategy. In other words, when a significant dynamic change in traffic flow is detected on a branch road (such as a vehicle malfunction), the traffic lights at the intersection are adaptively controlled based on real-time traffic flow data of through traffic on the main road. Priority is given to ensuring the passage of through traffic on the main road, thereby avoiding resource idleness and waste at the target intersection. The technical solution of this application can adapt to complex and ever-changing traffic environments and improve road capacity and traffic efficiency.

[0097] like Figure 5 As shown, the traffic signal control system provided in this application embodiment further includes a memory 800, wherein the memory 800 is used to store computer-readable instructions, and the edge processor 700 is used to call the computer-readable instructions to execute the traffic signal control method based on edge computing as described above.

[0098] The edge processor 700 provides computing and control capabilities to control the traffic signal control system to perform corresponding tasks. For example, it controls the traffic signal control system to perform the edge computing-based traffic signal control method in any of the above method embodiments. The method includes: acquiring the traffic status of vehicles in the target area; acquiring the traffic indication status of the first traffic light when there is a target vehicle in the target area that meets the preset traffic status; controlling the first traffic light to maintain the green light traffic indication status when the traffic indication status of the first traffic light is green until all vehicles in front of the target vehicle have completed turning and passing; controlling the third traffic light to maintain the lane-changing and queue-jumping traffic indication status until the waiting area in front of the target vehicle is full; determining a target traffic control strategy for the first traffic light, the second traffic light, and the third traffic light based on real-time traffic flow data of straight-ahead vehicles on the main road; and controlling the traffic of the first traffic light, the second traffic light, and the third traffic light according to the target traffic control strategy, wherein the green light duration of the second traffic light is greater than the green light duration of the first traffic light.

[0099] The edge processor 700 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The aforementioned PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0100] The memory 800, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the edge computing-based traffic light control method in the embodiments of this application. The edge processor 700 can implement the edge computing-based traffic light control method in any of the above method embodiments by running the non-transitory software programs, instructions, and modules stored in the memory 800.

[0101] Specifically, memory 800 may include volatile memory (VM), such as random access memory (RAM); memory 800 may also include non-volatile memory (NVM), such as read-only memory (ROM), flash memory, hard disk drive (HDD), solid-state drive (SSD), or other non-transitory solid-state storage devices; memory 800 may also include combinations of the above types of memory.

[0102] In summary, the traffic signal control system of this application adopts the technical solution of any of the above-mentioned edge computing-based traffic signal control method embodiments. Therefore, it has at least the beneficial effects brought about by the technical solutions of the above embodiments, which will not be elaborated here.

[0103] This application also provides a computer-readable storage medium, such as a memory including program code, which can be executed by a processor to complete the traffic light control method based on edge computing described in the above embodiments. For example, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CDROM), magnetic tape, floppy disk, and optical data storage device, etc.

[0104] This application also provides a computer program product comprising one or more lines of program code stored in a computer-readable storage medium. The processor of the traffic signal control system reads the program code from the computer-readable storage medium and executes the program code to complete the steps of the edge computing-based traffic signal control method provided in the above embodiments.

[0105] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware, or by a program or program code related to hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0106] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0107] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software and a general-purpose hardware platform, or of course, using hardware. Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0108] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformations made using the contents of the present invention's specification and drawings under the inventive concept of the present invention, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A traffic signal control method based on edge computing, characterized in that, An application is made to a traffic signal control system, the traffic signal control system including an edge processor located at a target intersection and a first traffic signal, a second traffic signal, and a third traffic signal located at the target intersection. The target intersection includes a main road and branch roads. The branch roads include a target area and a waiting area located in front of the target area. The target area is an area within a preset range from a stop line, and the waiting area is the area between the target area and the stop line. The first traffic signal is used to indicate the passage of turning traffic on the branch road, the second traffic signal is used to indicate the passage of straight-going traffic on the main road, and the third traffic signal is located on one side of the target area to indicate lane-changing and queue-jumping passage. The method includes: Obtain the traffic status of vehicles within the target area; If there is a target vehicle in the target area that meets the preset passage conditions, the passage indication status of the first traffic light is obtained; If the first traffic light is in a green light state, control the first traffic light to remain in a green light state until all vehicles in front of the target vehicle have completed their turning and proceeding. The third traffic light is controlled to maintain the lane-changing and queue-jumping indication state until the waiting area in front of the target vehicle is full; The target traffic control strategy for the first, second, and third traffic lights is determined based on the real-time traffic flow data of vehicles traveling straight on the main road. According to the target traffic control strategy, the first traffic light, the second traffic light, and the third traffic light are controlled to indicate traffic flow, wherein the green light duration of the second traffic light is greater than the green light duration of the first traffic light. If the first traffic light is in a green light state, controlling the first traffic light to remain in a green light state until all vehicles in front of the target vehicle have completed their turns to proceed includes: If the first traffic light is in a green light state, control the first traffic light to remain in a green light state, and switch the green light state to a red light state after all vehicles in front of the target vehicle have completed their turns and passed. The control of the third traffic light to maintain the lane-changing and queuing indication state until the waiting area in front of the target vehicle is full includes: The third traffic light is controlled to maintain the lane change and queue-jumping indication state, and after the waiting area in front of the target vehicle is full, the lane change and queue-jumping indication state is switched to the lane change and queue-jumping prohibition indication state.

2. The traffic signal control method based on edge computing as described in claim 1, characterized in that, The traffic signal control system includes a lidar system installed in the target area. The step of acquiring the traffic status of vehicles within the target area includes: The speed of vehicles passing through the target area is obtained by the lidar; When a target vehicle meeting a preset traffic condition exists within the target area, obtaining the traffic indication status of the first traffic light includes: If a vehicle in the target area has a speed less than or equal to a preset speed for a preset duration, it is determined that there is a target vehicle in the target area that meets the preset traffic conditions. The edge processor obtains the traffic signal light's passage indication status.

3. The traffic signal control method based on edge computing as described in claim 1, characterized in that, The traffic signal control system includes a traffic flow monitoring device installed on the main road. The step of determining the target traffic control strategy for the first, second, and third traffic signals based on real-time traffic flow data of through traffic on the main road includes: The traffic flow monitoring data of the traffic flow monitoring device is obtained through the edge processor; Based on the traffic flow monitoring data, a target traffic control strategy is determined for the first traffic light, the second traffic light, and the third traffic light.

4. The traffic signal control method based on edge computing as described in claim 3, characterized in that, The step of determining the target traffic control strategy for the first traffic light, the second traffic light, and the third traffic light based on the traffic flow monitoring data includes: Based on the traffic flow monitoring data, a first sub-traffic control strategy is determined for the first traffic light and the second traffic light; A second sub-traffic control strategy is determined for the first and third traffic lights based on the first sub-traffic control strategy.

5. The traffic signal control method based on edge computing as described in claim 4, characterized in that, The step of determining the first sub-traffic control strategy for the first traffic light and the second traffic light based on the traffic flow monitoring data includes: The green light duration percentages of the first and second traffic lights are determined based on the traffic flow monitoring data, wherein the green light duration percentage of the second traffic light is positively correlated with the traffic flow monitoring data, and / or the green light duration percentage of the first traffic light is negatively correlated with the traffic flow monitoring data.

6. The traffic signal control method based on edge computing as described in claim 4, characterized in that, The step of determining the second sub-traffic control strategy for the first traffic light and the third traffic light based on the first sub-traffic control strategy includes: The traffic control strategy for the third traffic light is determined based on the traffic indication status of the first traffic light. Specifically, when the traffic indication status of the first traffic light switches to a green light, the third traffic light is controlled to switch to a lane-changing and queue-jumping indication status. After a preset time following the switch of the traffic indication status of the first traffic light to a red light prohibiting traffic, the third traffic light is controlled to switch to a lane-changing and queue-jumping prohibiting indication status.

7. The traffic signal control method based on edge computing as described in claim 1, characterized in that, The traffic signal control system further includes a geomagnetic sensor array, and the method further includes: The geomagnetic sensor array is used to detect vehicle occupancy in the waiting area. When all the geomagnetic sensor arrays in the waiting area trigger the sensing signal, it is determined that the waiting area has been filled.

8. A traffic signal control system, characterized in that, include: A lidar is installed in a target area on a branch road, the target area being a region within a preset range from the waiting stop line, and is used to monitor the traffic status of vehicles within the target area; Traffic flow monitoring devices are installed on main roads to monitor traffic flow. A geomagnetic sensor array is installed in the waiting area of ​​a branch road, the waiting area being the area between the target area and the waiting stop line, for detecting vehicles occupying the waiting area; The first traffic light is used to indicate the passage of turning traffic on the branch road; The second traffic light is used to indicate the passage of straight-through traffic on the main road; The third traffic light is located on one side of the target area and is used to indicate lane changing and queue cutting. The memory is used to store program code; and A processor, the processor being configured to invoke the program code to perform the method as described in any one of claims 1 to 7.

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