WO2021189970A1

WO2021189970A1 - Intelligent control method and system for traffic light, and storage medium and computing device

Info

Publication number: WO2021189970A1
Application number: PCT/CN2020/136057
Authority: WO
Inventors: 曾昱为; 王健宗; 黄章成
Original assignee: 平安科技（深圳）有限公司
Priority date: 2020-10-28
Filing date: 2020-12-14
Publication date: 2021-09-30
Also published as: CN112309146A

Abstract

An intelligent control method and system for a traffic light, and a storage medium and a computing device, which relate to the field of artificial intelligence. The method comprises: acquiring an operation parameter of a traffic light (S102); according to the operation parameter of the traffic light, determining whether the traffic light meets a starting condition for a preset dual-track working mode (S104); and if the traffic light meets the starting condition for the preset dual-track working mode, controlling the traffic light to operate in the preset dual-track working mode (S106). In the method, both visual intelligent recognition technology and a traditional static time distribution mechanism are taken into consideration, and the prompt color of a traffic light is controlled by means of a dual-track working control policy, such that the configuration efficiency of resources for the whole highway system can be improved, and the usage experience of pedestrians and vehicles for a highway can also be improved.

Description

Intelligent control method and system, storage medium and computing equipment of traffic signal lamp

This application claims the priority of the Chinese patent application filed with the Chinese Patent Office on October 28, 2020, the application number is 202011171429.9, and the invention title is "Intelligent Control Method and System of Traffic Signal Lights, Storage Media, and Computing Equipment", and its entire contents Incorporated in this application by reference.

Technical field

This application relates to the field of intelligent control technology, in particular to an intelligent control method and system for traffic signal lights, storage media, and computing equipment.

Background technique

Traffic signal lights are signal lights that direct traffic operation, and are generally composed of red, green, and yellow lights. A red light means no traffic, a green light means permission to pass, and a yellow light means a warning.

The existing traffic signal light system is a work equipment that is planned based on a static time interval scheduling algorithm, which switches the color of the signal light according to a preset time period. The inventor found that the biggest disadvantage of such a planning algorithm is that it cannot dynamically adapt to changes and changes in the flow of people and vehicles. At some traffic signal intersections, there are often situations where there are clearly no pedestrians, but vehicles still have to wait for the red light for the previous section, or there are clearly no vehicles but pedestrians have to wait.

At the same time, with the development of cities and regions, the flow of people and vehicles will also dynamically change. The original static system cannot adapt to this feature, and its preset algorithms will slowly become obsolete.

technical problem

In view of the above-mentioned problems, this application is proposed to provide an intelligent control method and system, storage medium, and computing device for traffic lights that overcome the above-mentioned problems or at least partially solve the above-mentioned problems.

Technical solutions

According to one aspect of the present application, there is provided an intelligent control method for traffic signal lights, including:

Obtain the operating parameters of traffic lights;

Judging whether the traffic signal has a preset starting condition for the dual-track operating mode according to the operating parameters of the traffic signal;

If the traffic signal lamp has the preset starting condition of the dual-track operating mode, controlling the traffic signal lamp to operate in the preset dual-track operating mode;

Wherein, in the dual-track working mode, the color control mechanism of the traffic signal light switches between a preset static time allocation mechanism and a visual dynamic control mechanism according to the image information of the predetermined range of the traffic signal light.

According to another aspect of the present application, there is also provided an intelligent control system for traffic lights, including:

The acquisition module is suitable for acquiring the operating parameters of the traffic signal light;

The judging module is suitable for judging whether the traffic signal has a preset starting condition of the dual-track working mode according to the operating parameters of the traffic signal;

The first control module is adapted to set the operating mode of the traffic signal light to the dual-track operating mode when the traffic signal light has a preset starting condition for the dual-track operating mode;

According to another aspect of the present application, a computer-readable storage medium is also provided, the computer-readable storage medium is used to store program code, and the program code is used to execute an intelligent control method of a traffic signal light;

Wherein, the intelligent control method of the traffic signal light includes:

Obtain the operating parameters of traffic lights;

Wherein, in the dual-track operating mode, the color control mechanism of the traffic signal light switches between a preset static time allocation mechanism and a visual dynamic control mechanism according to the image information of the traffic road controlled by the traffic signal light.

According to another aspect of the present application, there is also provided a computing device, including a processor and a memory:

The memory is used to store program code and transmit the program code to the processor;

The processor is configured to execute an intelligent control method for traffic signal lights according to instructions in the program code;

Wherein, the intelligent control method of the traffic signal light includes:

Obtain the operating parameters of traffic lights;

Beneficial effect

This application provides an intelligent control method, system, storage medium, and computing device for traffic signal lights. In the method provided in this application, after judging that the traffic signal light has the preset dual-track operating mode on condition according to the operating parameters of the traffic signal light, The traffic signal lamp can be controlled to operate in a preset dual-track working mode. The dual-track working mode provided in this application uses visual intelligent recognition technology to efficiently identify pedestrians and vehicles for dynamic control of traffic lights, while taking into account the traditional static time allocation mechanism, and using a dual-track work control strategy to control the color of traffic lights , Can improve the resource allocation efficiency of the entire highway system to a certain extent, and also improve the road use experience of pedestrians and vehicles.

Description of the drawings

Fig. 1 shows a schematic flow chart of an intelligent control method for traffic signal lights according to an embodiment of the present application;

Fig. 2 shows a schematic diagram of a traffic signal light control scene according to an embodiment of the present application;

Fig. 3 shows a schematic diagram of a traffic signal light control scene according to another embodiment of the present application;

Fig. 4 shows a schematic flow chart of a method for intelligent control of a traffic signal light according to another embodiment of the present application;

Fig. 5 shows a schematic structural diagram of an intelligent control device for a traffic signal light according to an embodiment of the present application;

Fig. 6 shows a schematic structural diagram of an intelligent control device for a traffic signal light according to another embodiment of the present application.

The best mode of the present invention

Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although the drawings show exemplary embodiments of the present disclosure, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

FIG. 1 shows a schematic flow chart of a method for intelligent control of traffic lights according to an embodiment of the present application. Referring to FIG. 1, it can be seen that the method for intelligent control of traffic lights provided by an embodiment of the present application may at least include the following steps S102 to S106.

S102: Acquire operating parameters of the traffic signal light.

In the embodiment of the present application, before intelligently controlling the traffic signal light, it is necessary to obtain the operating parameters of the traffic signal light. The image recognition parameters of the processing equipment in the signal lamp, etc. The specific process of obtaining the operating parameters of the traffic signal light will be described in detail below.

1. Get the network connection parameters of traffic lights

In this embodiment, the traffic signal lamp can communicate with the cloud central server for data transmission. When the network connection parameters of the traffic signal lamp are obtained, the network communication debugging can be carried out with the cloud central server to ensure that the traffic signal lamp and the cloud central server Maintain a good communication connection between them to provide a network communication basis for the subsequent intelligent control of traffic lights.

Optionally, a wireless communication module may be provided in the traffic signal light, and the network connection parameters of the traffic signal light may be acquired based on the wireless communication module.

2. Obtain the working parameters of the hardware equipment of traffic lights

Since the traffic signal lamp can emit red, green, and yellow prompts, there will be a light-emitting device inside. Therefore, when obtaining the working parameters of the hardware device of the traffic signal light, the working parameters of the light-emitting device can be obtained, that is, whether the light-emitting device is normal Luminous working parameters.

In addition, the hardware device in this embodiment may also include an image collection device for collecting image information within a preset range of the traffic signal light, for example, collecting image information of a traffic road under the jurisdiction of the traffic signal light to which the image collection device belongs. Therefore, when acquiring the operating parameters of the hardware device of the traffic signal light, it is also necessary to acquire the operating parameters of the image acquisition device to determine whether it can normally acquire image information. Among them, the image acquisition device may be a camera device, a camera device, and other related devices that can realize image acquisition.

In practical applications, because other equipment components may be set in the traffic signal light, in addition to the operating parameters of the above-mentioned light emitting device and image acquisition device, the operating parameters of other hardware devices of the traffic signal light can also be acquired. Go into details.

3. Obtain the image recognition parameters of the processing equipment in the traffic signal light

The image recognition parameters of the processing device may include the recognition accuracy of the object in the image information. Specifically, the processing device may use a preset target detection algorithm to perform object recognition on the image information collected by the image acquisition device to identify the object. The various objects included. In this embodiment, test pictures can be pre-stored in the processing device, communicate with the cloud central server by simulating a normal work process, and then the image recognition parameters of the processing device can be obtained according to the recognition result and related reaction actions. The processing device may be a processor, a processing chip, or other components that can execute an image detection algorithm. The processing device may be integrated in a traffic signal light or an independent device connected to the traffic signal.

Based on the method provided in the embodiment of the present application, by acquiring the operating parameters of the traffic signal light, it is possible to effectively provide an accurate judgment basis for judging whether the traffic signal light is operating normally. In practical applications, the operating parameters of the traffic signal light can be acquired periodically during the initial work phase or the work relay phase of the traffic signal light. The above embodiments respectively introduced the network connection parameters of the traffic signal lamp, the operating parameters of the hardware device of the traffic signal lamp, and the image recognition parameters of the processing device in the traffic signal lamp. In practical applications, when the operating parameters of the traffic signal lamp can be obtained, the operating parameters of the traffic signal lamp can be obtained. One or more. Preferably, when acquiring the operating parameters of the traffic signal light, the network connection parameters, the operating parameters of the hardware devices, and the image recognition parameters of the processing devices mentioned in the above-mentioned embodiment are also acquired. Moreover, in addition to obtaining the network connection parameters, hardware device parameters, and the algorithm accuracy of the processing device described in the foregoing embodiments, it is also possible to obtain other operating parameters of the traffic signal lamp, which this application does not do. limited.

S104: Judging whether the traffic signal has a preset starting condition of the dual-track operating mode according to the operating parameters of the traffic signal.

The operating parameters of the traffic signal lamp have been obtained in the above step S102, and further, it can be determined whether the traffic signal lamp has the preset starting condition of the dual-track operating mode according to the operating parameters of the traffic signal lamp.

As mentioned in step S102 above, when acquiring the operating parameters of the traffic signal light, the network connection parameters of the traffic signal light, the operating parameters of the hardware device of the traffic signal light, and the image recognition parameters of the processing equipment in the traffic signal light can be acquired respectively.

Further, when judging whether the traffic signal lamp has the preset opening condition of the dual-track working mode, the judgment can be made according to the obtained one or more operating parameters. Preferably, each type of operating parameter can be used as a basis for judging whether the traffic signal light has the preset opening condition of the dual-track operating mode. For example, when judging whether the traffic signal light has the preset dual-track operating mode on condition, it is necessary to judge whether the network is connected normally according to the network connection parameters of the traffic signal light; judging whether the hardware device is working normally according to the working parameters of the hardware device of the traffic signal light; According to the image recognition parameters of the processing device in the traffic signal light, it is judged whether the processing device has a certain degree of recognition accuracy when executing the target detection algorithm, and the above three judgment steps need to be executed. If the results of the above three judgment steps are all yes, it can be judged that the traffic signal has the preset dual-track operating mode opening conditions; if the result of the above three judgment steps is no, it is judged that any device in the traffic signal is not In a normal working state, it can be judged that the traffic signal light does not have the preset opening conditions for the dual-track working mode.

S106: If the traffic signal lamp has the preset starting condition of the dual-track operating mode, control the traffic signal lamp to operate in the preset dual-track operating mode. In the dual-track working mode, the color control mechanism of the traffic signal light switches between the preset static time allocation mechanism and the visual dynamic control mechanism according to the image information of the preset range of the traffic signal light.

In the embodiment of the present application, the dual-track working mode is a dual-track mechanism based on the parallel of the traditional static time allocation mechanism and the visual dynamic control mechanism based on the target detection AI vision technology. The original intention of the static time allocation mechanism is to maintain the maximum circulation of road conditions while ensuring the fair use of pedestrians and vehicles.

When pedestrians and vehicles have demands on the highway at the same time, a traditional static time allocation mechanism is needed to ensure fairness. In general, the static time allocation mechanism pre-stores the flashing time, flashing frequency, and switching sequence of the red, yellow, and green lights. When the color control mechanism of the traffic signal light is the preset static time allocation mechanism, the red light, yellow light, and green light can be prompted according to the preset switching sequence, flashing time, and flashing frequency.

When the color control mechanism of traffic lights is a visual dynamic control mechanism, the color of traffic signals and other prompts can be intelligently adjusted according to the dynamic image of the traffic road, and the current environment can be intelligently perceived and processed, especially for vehicles and pedestrians. AI recognition ability to realize intelligent switching of traffic lights.

In an optional embodiment of the present application, controlling the traffic signal lamp to operate in a preset dual-track working mode in step S106 may include:

S106-1: Collect image information of multiple angles in a preset range of the traffic signal light. When collecting image information, you can collect multiple angles of the traffic signal preset range and the image information within a set distance from the traffic signal. The image information can include multiple single-frame image frames acquired at intervals, or it can be Continuous image frames within a certain period of time are not limited in this application.

S106-2: Identify the number of pedestrians and the number of vehicles in the image information.

When recognizing the number of pedestrians and vehicles summarized by image information, target detection algorithms can be used, such as the R-CNN series algorithm in the Two-stage method, the SSD (Single Shot MultiBox Detector) algorithm in the One-stage method, and the Yolo (You Only Look Once) algorithm and so on. The specific identification process can be as follows:

Step S1: Recognize multiple recognition objects corresponding to different object categories in the image information through the target detection algorithm, and obtain the confidence level of each recognition object. Among them, the object category includes at least one of animals, pedestrians, and vehicles.

In practical applications, the target detection algorithm can identify all object categories such as vehicles, animals, pedestrians and other objects in the image information, and will simultaneously output the confidence of each identified object, that is, the accuracy of the judgment.

Step S2, selecting a plurality of first objects with a confidence level greater than a preset threshold from the plurality of recognition objects according to the confidence level of each recognition object.

Since each recognition object has its own confidence level, at this time, the recognition object with a confidence level greater than the preset threshold may be used as the first object. Optionally, the preset threshold may be 0.1 to 0.2, preferably 0.2. When the confidence is less than or equal to the preset threshold, the corresponding recognition object will be considered as a misjudgment, that is, ignored. In actual applications, the preset threshold can also be set to other values according to different requirements, which is not limited in this application.

Step S3: Recognize and filter out the repeated objects among the multiple first objects to obtain the target object.

When target detection is based on image information, the same recognition object may be detected multiple times. In this case, repeated detection can be used to filter out the repeated objects in the first object. Specifically, NMS (Non-Maximum Suppression , Non-maximum suppression) algorithm detects duplicate objects in the first object. Optionally, when filtering out duplicate objects, the threshold can be set to 0.45. If you want to ensure the optimal result, you can also do a grid search based on the test set to find the most accurate optimal value.

Step S4: Count the number of pedestrians and the number of vehicles in the target object.

After de-duplication and screening of the identified objects, the number of pedestrians and the number of vehicles in the image information can be counted.

In the embodiments of this application, the Yolo-v4 algorithm is preferentially used to identify the number of pedestrians and the number of vehicles in the image information. Yolo-v4 is the best model currently made in the field of target detection between high performance and high detection frame rate. It can guarantee an ultra-high detection speed of 65 frames per second FPS with such a fairly high AP average accuracy of 43.5%. For the real-time detection of signal lights, in addition to requiring more accurate detection accuracy, a sufficiently precise detection frame number FPS is also an important indicator. The use of Yolo-v4 algorithm can ensure the real-time visual detection of the system to the greatest extent and adapt to the vehicle speed to the greatest extent. A time difference with the signal switch of the semaphore improves the experience and safety of the application.

In practical applications, the above step S106-2 identifies the number of pedestrians and the number of vehicles in the image information, which can be executed in the processing device on the side of the traffic signal, or the image information can be uploaded to the cloud central server via 5G through the traffic signal, and received The cloud center server performs target detection and returns the detection results including the number of pedestrians and the number of vehicles. Specifically, it can be set independently according to the traffic volume and traffic volume of the traffic road where the traffic signal light is located. When the traffic volume is large, because the cloud central server has a large data processing capacity, the target detection algorithm can be executed through the cloud central server to efficiently determine the number of pedestrians and the number of vehicles. When the traffic flow of traffic lights is small, the target detection algorithm can be executed locally by the traffic lights to quickly determine the number of pedestrians and vehicles.

S106-3, according to the number of pedestrians and the number of vehicles, according to a preset static time allocation mechanism or a visual dynamic control mechanism to control the color of the traffic signal light.

Specifically, it can be judged according to the number of pedestrians and vehicles whether there are pedestrians and vehicles at the same time; if so, switch the prompt colors of traffic lights in sequence according to the preset static time allocation mechanism; if not, control according to the visual dynamic control mechanism The color of traffic lights.

In the embodiments of the present application, the visual dynamic control mechanism is a control mechanism based on pedestrian monopoly or vehicle monopoly respectively. The traffic signal light mentioned in this embodiment may include a pedestrian crossing signal light. Optionally, when the traffic road has only pedestrians, the warning color of the traffic signal light on the pedestrian side is controlled to be green; or, when the traffic road has only vehicles, the traffic signal light is controlled The color of the tip on the pedestrian side is red.

In practical applications, traffic signal lights may also include motor vehicle signal lights and non-motor vehicle signal lights. At this time, the traffic signal light can also communicate with other signal lights on the same road direction or on the intersecting traffic road to realize the linkage control of the traffic signal light.

For example, as shown in Figure 2, suppose the crosswalk signal light is A. When the traffic road has only pedestrians, A is a green light; when the traffic road has only vehicles, A is a red light.

As shown in Figure 3, assuming that the pedestrian crossing signal light is B, the motor vehicle signal light is C and D, assuming that there are only vehicles and no pedestrians around C and D, at this time, C and D perform traffic lights based on the traffic of the vehicles identified by each Switch, B is a red light; assuming that there are only pedestrians and no vehicles around C and D, then C and D enter the red light, and B is the green light. The foregoing embodiment only schematically introduces the traffic signal light control method. In practical applications, it is also possible to predict pedestrian flow, vehicle flow, etc., to achieve intelligent control of the traffic signal light.

The method provided in the embodiments of this application can perform intelligent control of traffic lights according to the number of vehicles and pedestrians around the traffic lights, so that the traffic lights can effectively adapt to changes in the flow of people and vehicles, and perform intelligent control when there are only pedestrians or only vehicles. , It can save traffic time while meeting traffic demands, and effectively realize the intelligent control of traffic lights.

In an optional embodiment of the present application, continuing to refer to FIG. 1, it can be seen that after the above step S102 determines whether the traffic signal has the preset conditions of the dual-track operating mode according to the network and device status, the method further includes:

In step S108, if the traffic signal light does not have the preset opening condition of the dual-track working mode, the prompt color of the traffic signal light is sequentially switched according to the preset static time allocation mechanism.

In an optional embodiment of the present application, the operating parameters of the traffic signal light can also be directionally updated through an air download dynamic update mechanism. Over the air (OTA) online upgrade mechanism is a technology for downloading upgrade packages on remote servers through wireless networks to upgrade systems or applications. Through the OTA download technology, you can download various business menus provided by the network to your mobile phone using OTA mechanism according to your personal preferences with simple operations, and you can also customize specific services according to your own wishes.

In the embodiment of this application, the traffic signal light side can deploy an over-the-air (OTA) online upgrade mechanism, so that the operator can directionally (designate a certain device or certain devices) in the cloud to easily complete various system configuration parameters Updates, or related software upgrades.

Optionally, the operating parameters such as the duration of each prompt color of the signal lamp, the flashing frequency, and the prompt color switching sequence can be mainly updated or modified online through the OTA online update mechanism. In addition, the above embodiments mentioned that the traffic signal lights are provided with processing equipment to execute the target detection algorithm to obtain the number of pedestrians and the number of vehicles. Therefore, the target detection algorithm can also be dynamically upgraded through the OTA online upgrade mechanism to continuously improve the accuracy and granularity of object recognition. In this way, the work effect is continuously improved, and the response strategy to the recognition results can also be dynamically adjusted through OTA upgrade; for example, how the lights change when there are vehicles and pedestrians at the same time; how far away pedestrians or vehicles need to trigger corresponding changes, and so on.

Based on the method provided in the embodiments of this application, by setting the OTA online upgrade mechanism on the traffic signal side, the relevant traffic and transportation departments can lead the development of the update and upgrade of the traffic signal operating parameters according to the actual road conditions and urban development plan; Suppliers related to detection algorithms can provide new models based on technical upgrades, and the relevant departments will decide whether to implement upgrades based on actual measurement results and local conditions. Based on the method provided by the embodiments of the present application, the directional configuration of traffic signal lights can be quickly changed and upgraded in the cloud, which greatly improves the operability and flexible response capability of the entire signal light system.

Fig. 4 shows a method for intelligent control of a traffic signal light according to another embodiment of the present application. Referring to Fig. 3, it can be seen that the method provided by the embodiment of the present application may include:

Step S402, start the traffic lights; control the traffic lights to switch the prompt colors of the traffic lights in sequence according to the static time allocation mechanism; when the traffic lights are in start-up operation, first use the static time allocation mechanism as a control strategy to control the prompt colors of the traffic lights to ensure traffic Road traffic safety.

Step S404, acquiring the operating parameters of the traffic signal light;

Step S406, judging whether the traffic signal has the preset dual-track operating mode turn-on conditions according to the operating parameters; if yes, execute step S408; if not, execute step S420;

Step S408, controlling the traffic signal lamp to operate in a preset dual-track working mode;

Step S410, collecting image information within a preset range of the traffic signal light;

Step S412: Send the above-mentioned image information to the cloud central server for target detection. Specifically, the Yolo-V4 target detection algorithm can be used to first identify each object in the image information, and then screen out objects with low confidence and duplicate objects. The target object counts the number of pedestrians and vehicles in the image information;

Step S414, receiving the number of pedestrians and the number of vehicles returned by the cloud center server;

Step S416, it is judged whether there are specific pedestrians and vehicles at the same time; if yes, go to step 420; if not, go to step S418;

Step S418: Control the traffic signal to operate in the pedestrian exclusive mode or the vehicle exclusive mode; among them, the pedestrian exclusive mode means that the traffic signal on the pedestrian side is a green light, and the traffic signal on the vehicle side is a red light; the vehicle exclusive mode refers to The traffic light on the side is green, and the traffic light on the pedestrian side is red

In step S420, the prompt colors of the traffic signal lights are sequentially switched according to the preset static time allocation mechanism.

The method provided in the embodiments of this application adopts advanced Yolo-V4 visual intelligent recognition technology to efficiently recognize pedestrians and vehicles for dynamic control of traffic lights, while taking into account the traditional static time allocation mechanism, and using a dual-track control strategy control The prompt color of the traffic signal light will ensure safety, fairness, stability, efficiency and integration. Among them, AI technology is used to empower traditional traffic lights, thereby improving the rationality of the allocation of highway resources, which can improve the allocation efficiency of the entire highway system to a certain extent, and also improve the road use experience of pedestrians and vehicles.

Based on the same inventive concept, the embodiment of the present application also provides a traffic signal light intelligent control system. Referring to FIG. 5, it can be seen that the traffic signal light intelligent control system provided by the embodiment of the present application may include:

The obtaining module 510 is adapted to obtain the operating parameters of the traffic signal light;

The judging module 520 is suitable for judging whether the traffic signal has the preset starting condition of the dual-track working mode according to the operating parameters of the traffic signal;

The first control module 530 is adapted to control the traffic signal lamp to operate in the preset dual-track operating mode when the traffic signal lamp has the preset dual-track operating mode on condition; wherein, in the dual-track operating mode, the color control mechanism of the traffic signal light is based on The image information of the preset range of traffic lights is switched between the preset static time allocation mechanism and the visual dynamic control mechanism.

In an optional embodiment of the present application, the obtaining module 510 may also be adapted to:

Obtain the network connection parameters of traffic lights; and/or

Obtain the operating parameters of the hardware equipment of the traffic signal; and/or

Obtain the image recognition parameters of the processing equipment in the traffic signal light;

Among them, the hardware device includes at least one of an image acquisition device and a light-emitting device.

In an optional embodiment of the present application, the first control module 530 may be further adapted to:

Collect image information of multiple angles in the preset range of traffic signal lights;

Identify the number of pedestrians and vehicles in the image information;

According to the number of pedestrians and the number of vehicles, the color of the traffic signal light is controlled according to the preset static time allocation mechanism or the visual dynamic control mechanism.

Identify multiple recognition objects corresponding to different object categories in the image information through a target detection algorithm, and obtain the confidence level of each recognition object; wherein the object category includes at least one of animals, pedestrians, and vehicles;

Selecting a plurality of first objects with a confidence level greater than a preset threshold from the plurality of recognition objects according to the confidence level of each recognition object;

Identify and filter out duplicate objects among multiple first objects to obtain target objects;

Count the number of pedestrians and vehicles in the target object.

According to the number of pedestrians and vehicles, judge whether the traffic road has both pedestrians and vehicles;

If yes, switch the prompt colors of traffic lights in sequence according to the preset static time allocation mechanism;

If not, control the color of the traffic signal light according to the visual dynamic control mechanism; among them, when the traffic road has only pedestrians, control the traffic signal light to be green on the pedestrian side; or, when the traffic road has only vehicles, control the traffic signal light The color of the tip on the pedestrian side is red.

In an optional embodiment of the present application, as shown in FIG. 6, the foregoing system may further include a second control module 540:

The second control module 540 is adapted to sequentially switch the prompt colors of the traffic signal lights according to the preset static time allocation mechanism if the traffic signal lights do not have the preset opening conditions of the dual-track working mode.

In an optional embodiment of the present application, as shown in FIG. 5, the foregoing system may further include an update module 550;

The update module 550 is adapted to update the operating parameters of the traffic signal light directionally through an air download dynamic update mechanism.

In a possible embodiment of the present application, a computer-readable storage medium is also provided. The computer-readable storage medium may be non-volatile or volatile. The computer-readable storage medium is used to store program codes. The program code is used to execute the intelligent control method of the traffic signal light of any of the above embodiments.

In a possible embodiment of the present application, a computing device is also provided, including a processor and a memory:

The memory is used to store the program code and transmit the program code to the processor;

The processor is configured to execute the intelligent control method for traffic signal lights of any one of the above embodiments according to the instructions in the program code.

Those skilled in the art can clearly understand that for the specific working processes of the systems, devices, modules and units described above, reference may be made to the corresponding processes in the foregoing method embodiments. For the sake of brevity, it will not be repeated here.

In addition, the functional units in the various embodiments of the present application may be physically independent of each other, or two or more functional units may be integrated together, or all functional units may be integrated in one processing unit. The above-mentioned integrated functional unit may be implemented in the form of hardware, or may be implemented in the form of software or firmware.

A person of ordinary skill in the art can understand that if the integrated functional unit is implemented in the form of software and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solution of the present application is essentially or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions to make a computer A computing device (for example, a personal computer, a server, or a network device, etc.) executes all or part of the steps of the methods described in the embodiments of the present application when running the instructions. The aforementioned storage media include: U disk, mobile hard disk, read only memory (ROM), random access memory (RAM), magnetic disks or optical disks and other media that can store program codes.

Alternatively, all or part of the steps of the foregoing method embodiments may be implemented by program instructions related to hardware (computing devices such as personal computers, servers, or network devices), and the program instructions may be stored in a computer readable storage. In the medium, when the program instructions are executed by the processor of the computing device, the computing device executes all or part of the steps of the methods described in the embodiments of the present application.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the application, not to limit it; although the application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: Within the spirit and principle of this application, it is still possible to modify the technical solutions described in the foregoing embodiments, or to make equivalent replacements to some or all of the technical features; and these modifications or replacements do not depart from the corresponding technical solutions The scope of protection of this application.

Claims

An intelligent control method for traffic signal lights, which includes:

Obtain the operating parameters of traffic lights;

Judging whether the traffic signal has a preset starting condition for the dual-track operating mode according to the operating parameters of the traffic signal;

If the traffic signal lamp has the preset starting condition of the dual-track operating mode, controlling the traffic signal lamp to operate in the preset dual-track operating mode;

Wherein, in the dual-track operating mode, the color control mechanism of the traffic signal light switches between a preset static time allocation mechanism and a visual dynamic control mechanism according to the image information of the traffic road controlled by the traffic signal light.
The method according to claim 1, wherein said obtaining the operating parameters of the traffic signal light comprises:

Obtain the network connection parameters of the traffic signal light; and/or

Obtain the operating parameters of the hardware device of the traffic signal light; and/or

Acquiring image recognition parameters of the processing equipment in the traffic signal light;

Wherein, the hardware device includes at least one of an image acquisition device and a light emitting device.
The method according to claim 1, wherein said controlling said traffic signal lamp to operate in a preset dual-track operating mode comprises:

Collecting image information of multiple angles of the traffic road controlled by the traffic signal light;

Identifying the number of pedestrians and the number of vehicles in the image information;

The prompt color of the traffic signal light is controlled according to the number of pedestrians and the number of vehicles according to a preset static time allocation mechanism or a visual dynamic control mechanism.
The method according to claim 3, wherein said identifying the number of pedestrians and the number of vehicles in the image information comprises:

Recognizing multiple recognition objects corresponding to different object categories in the image information through a target detection algorithm, and obtaining the confidence of each recognition object; wherein the object category includes at least one of an animal, a pedestrian, and a vehicle;

Selecting a plurality of first objects with a confidence level greater than a preset threshold from the plurality of recognition objects according to the confidence level of each recognition object;

Identifying and filtering out duplicate objects among the plurality of first objects to obtain a target object;

Count the number of pedestrians and vehicles in the target object.
The method according to claim 3, wherein the controlling the color of the traffic signal light according to the preset static time allocation mechanism or the visual dynamic control mechanism according to the number of pedestrians and the number of vehicles comprises:

Judging whether the traffic road has pedestrians and vehicles at the same time according to the number of pedestrians and the number of vehicles;

If yes, switch the prompt colors of the traffic signal lights sequentially according to the preset static time allocation mechanism;

If not, control the prompt color of the traffic signal light according to the visual dynamic control mechanism; wherein, when the traffic road has only pedestrians, control the prompt color of the traffic signal light on the pedestrian side to be green; or, on the traffic road When there is only a vehicle, the warning color of the traffic signal light on the pedestrian side is red.
The method according to any one of claims 1 to 5, wherein after the judging whether the traffic signal has the preset condition of the dual-track working mode according to the network and device status, the method further comprises:

If the traffic signal light does not meet the preset opening conditions of the dual-track operating mode, the prompt color of the traffic signal light is sequentially switched according to the preset static time allocation mechanism.
The method according to any one of claims 1-5, wherein the method further comprises:

The operating parameters of the traffic signal lights are directionally updated through an air download dynamic update mechanism.
An intelligent control system for traffic lights, which includes:

The acquisition module is suitable for acquiring the operating parameters of the traffic signal light;

The judging module is suitable for judging whether the traffic signal has a preset starting condition of the dual-track working mode according to the operating parameters of the traffic signal;

The first control module is adapted to set the operating mode of the traffic signal light to the dual-track operating mode when the traffic signal light has a preset starting condition for the dual-track operating mode;

Wherein, in the dual-track working mode, the color control mechanism of the traffic signal light switches between a preset static time allocation mechanism and a visual dynamic control mechanism according to the image information of the predetermined range of the traffic signal light.
A computer-readable storage medium, wherein the computer-readable storage medium is used to store program code, and the program code is used to execute an intelligent control method of a traffic signal light;

Wherein, the intelligent control method of the traffic signal light includes:

Obtain the operating parameters of traffic lights;

Judging whether the traffic signal has a preset starting condition for the dual-track operating mode according to the operating parameters of the traffic signal;

If the traffic signal lamp has the preset starting condition of the dual-track operating mode, controlling the traffic signal lamp to operate in the preset dual-track operating mode;

Wherein, in the dual-track operating mode, the color control mechanism of the traffic signal light switches between a preset static time allocation mechanism and a visual dynamic control mechanism according to the image information of the traffic road controlled by the traffic signal light.
The computer-readable storage medium according to claim 9, wherein said obtaining the operating parameters of the traffic signal light comprises:

Obtain the network connection parameters of the traffic signal light; and/or

Obtain the operating parameters of the hardware device of the traffic signal light; and/or

Acquiring image recognition parameters of the processing equipment in the traffic signal light;

Wherein, the hardware device includes at least one of an image acquisition device and a light emitting device.
The computer-readable storage medium according to claim 9, wherein said controlling said traffic signal lamp to operate in a preset dual-track working mode comprises:

Collecting image information of multiple angles of the traffic road controlled by the traffic signal light;

Identifying the number of pedestrians and the number of vehicles in the image information;

The prompt color of the traffic signal light is controlled according to the number of pedestrians and the number of vehicles according to a preset static time allocation mechanism or a visual dynamic control mechanism.
The computer-readable storage medium according to claim 11, wherein said identifying the number of pedestrians and the number of vehicles in the image information comprises:

Recognizing multiple recognition objects corresponding to different object categories in the image information through a target detection algorithm, and obtaining the confidence of each recognition object; wherein the object category includes at least one of an animal, a pedestrian, and a vehicle;

Selecting a plurality of first objects with a confidence level greater than a preset threshold from the plurality of recognition objects according to the confidence level of each recognition object;

Identifying and filtering out duplicate objects among the plurality of first objects to obtain a target object;

Count the number of pedestrians and vehicles in the target object.
11. The computer-readable storage medium according to claim 11, wherein the controlling the color of the traffic signal light according to the number of pedestrians and the number of vehicles according to a preset static time allocation mechanism or a visual dynamic control mechanism comprises:

Judging whether the traffic road has pedestrians and vehicles at the same time according to the number of pedestrians and the number of vehicles;

If yes, switch the prompt colors of the traffic signal lights sequentially according to the preset static time allocation mechanism;

If not, control the prompt color of the traffic signal light according to the visual dynamic control mechanism; wherein, when the traffic road has only pedestrians, control the prompt color of the traffic signal light on the pedestrian side to be green; or, on the traffic road When there is only a vehicle, the warning color of the traffic signal light on the pedestrian side is red.
The computer-readable storage medium according to any one of claims 9-13, wherein after the judging whether the traffic signal lamp has the preset condition of the dual-track operating mode according to the network and device status, the method further comprises:

If the traffic signal light does not meet the preset opening conditions of the dual-track operating mode, the prompt color of the traffic signal light is sequentially switched according to the preset static time allocation mechanism.
The computer-readable storage medium according to any one of claims 9-13, wherein the method further comprises:

The operating parameters of the traffic signal lights are directionally updated through an air download dynamic update mechanism.
A computing device, which includes a processor and a memory:

The memory is used to store program code and transmit the program code to the processor;

The processor is configured to execute an intelligent control method for traffic signal lights according to instructions in the program code;

Wherein, the intelligent control method of the traffic signal light includes:

Obtain the operating parameters of traffic lights;

Judging whether the traffic signal has a preset starting condition for the dual-track operating mode according to the operating parameters of the traffic signal;

If the traffic signal lamp has the preset starting condition of the dual-track operating mode, controlling the traffic signal lamp to operate in the preset dual-track operating mode;

Wherein, in the dual-track operating mode, the color control mechanism of the traffic signal light switches between a preset static time allocation mechanism and a visual dynamic control mechanism according to the image information of the traffic road controlled by the traffic signal light.
The computing device according to claim 16, wherein said obtaining the operating parameters of the traffic signal light comprises:

Obtain the network connection parameters of the traffic signal light; and/or

Obtain the operating parameters of the hardware device of the traffic signal light; and/or

Acquiring image recognition parameters of the processing equipment in the traffic signal light;

Wherein, the hardware device includes at least one of an image acquisition device and a light emitting device.
The computing device according to claim 16, wherein said controlling said traffic signal lamp to operate in a preset dual-track working mode comprises:

Collecting image information of multiple angles of the traffic road controlled by the traffic signal light;

Identifying the number of pedestrians and the number of vehicles in the image information;

The prompt color of the traffic signal light is controlled according to the number of pedestrians and the number of vehicles according to a preset static time allocation mechanism or a visual dynamic control mechanism.
The computing device according to claim 16, wherein said identifying the number of pedestrians and the number of vehicles in the image information comprises:

Recognizing multiple recognition objects corresponding to different object categories in the image information through a target detection algorithm, and obtaining the confidence of each recognition object; wherein the object category includes at least one of an animal, a pedestrian, and a vehicle;

Selecting a plurality of first objects with a confidence level greater than a preset threshold from the plurality of recognition objects according to the confidence level of each recognition object;

Identifying and filtering out duplicate objects among the plurality of first objects to obtain a target object;

Count the number of pedestrians and vehicles in the target object.
The computing device according to claim 16, wherein the controlling the color of the traffic signal light according to the number of pedestrians and the number of vehicles according to a preset static time allocation mechanism or a visual dynamic control mechanism comprises:

Judging whether the traffic road has pedestrians and vehicles at the same time according to the number of pedestrians and the number of vehicles;

If yes, switch the prompt colors of the traffic signal lights sequentially according to the preset static time allocation mechanism;

If not, control the prompt color of the traffic signal light according to the visual dynamic control mechanism; wherein, when the traffic road has only pedestrians, control the prompt color of the traffic signal light on the pedestrian side to be green; or, on the traffic road When there is only a vehicle, the warning color of the traffic signal light on the pedestrian side is red.