Target screening method and system, vehicle and equipment

Abstract

The invention discloses a target screening method and system, a vehicle and equipment. The target screening method comprises the steps that continuous multiple frames of historical data are acquired, and the multiple frames of historical data comprise multiple frames of steering wheel angle information and multiple frames of yaw rate information; according to the multi-frame steering wheel angle information and the multi-frame yaw rate information, whether the vehicle runs on a target road or not is judged, and the target road at least comprises a lane-line-free road or a lane-line-poor-quality road, a curve or a continuous curve; if yes, predicting a driving track of the vehicle according to the current speed and acceleration of the vehicle and the multi-frame historical data; and performing target screening according to the driving track. By the adoption of the method and device, when it can be accurately judged that the vehicle is located on the target road such as a complex curve, a continuous turning road and a lane-line-free road, the vehicle data are effectively utilized, and the more accurate driving track of the vehicle is predicted.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a target screening method, system, vehicle and equipment. Background Art

[0002] Use lane lines for target screening. The lane line information is used to predict the vehicle's running trajectory. Generally, the lane line is a curve with the same curvature as the lane line. Target screening is performed by judging whether the target is within the range of the curve. Alternatively, the vehicle's trajectory is predicted based on the vehicle's yaw rate (i.e., yaw_rate). The vehicle's trajectory curve is predicted using the vehicle's yaw_rate information. Target screening is performed by judging whether the target is within the range of the curve. Alternatively, the vehicle's running trajectory is predicted using information such as the steering wheel angle and wheel speed. Target screening is performed by judging whether the target is within the range of the curve.

[0003] The following technical problems exist: when using lane lines, targets may be mis-selected due to unclear lane lines, no lane lines, or misdetection or missed detection of lane lines, resulting in false alarms or misbraking of the vehicle; when using yaw_rate, the yaw_rate sensor accuracy, road bumps, vehicle shaking and other factors may cause insufficient accuracy, leading to misselection, false alarms, misbraking and other problems; information such as steering wheel angle and wheel speed may also be insufficiently accurate due to the sensor accuracy, road bumps, vehicle shaking and other factors, resulting in target selection errors and misbraking of the vehicle. Summary of the invention

[0004] Based on this, it is necessary to provide a target screening method, system, vehicle and equipment for the above technical problems, which can accurately determine when the ego vehicle is on a target road such as a complex curve, continuous turn, no lane line and other complex roads, and effectively use the ego vehicle data to predict a more accurate ego vehicle driving trajectory. Through more effective analysis and calculation of the ego vehicle and target vehicle data, the ego vehicle trajectory and the possibility of collision with the target vehicle can be more accurately calculated under complex road conditions, providing good target input for various auxiliary driving functions.

[0005] In a first aspect, a target screening method is provided, comprising:

[0006] Acquire multiple frames of continuous historical data, wherein the multiple frames of historical data include multiple frames of steering wheel angle information and multiple frames of yaw rate information;

[0007] Determining whether the vehicle is traveling on a target road according to the multi-frame steering wheel angle information and the multi-frame yaw rate information, wherein the target road at least includes a road without lane lines / a road with poor lane line quality, a curve, or continuous curves;

[0008] If yes, predicting the driving trajectory of the vehicle according to the current vehicle speed, acceleration and the multiple frames of historical data;

[0009] Target screening is performed according to the driving trajectory.

[0010] In some examples, judging whether the vehicle is traveling on a target road based on the multiple frames of steering wheel angle information and the multiple frames of yaw rate information includes:

[0011] Obtaining a steering wheel speed, a rotation state, and a steering wheel continuous change state according to the multiple frames of steering wheel angle information;

[0012] Whether the vehicle is traveling on a target road is determined according to the steering wheel speed, the rotation state, the steering wheel continuous change state and the multi-frame yaw rate information.

[0013] In some examples, judging whether the vehicle is traveling on a target road based on the steering wheel speed, the rotation state, the steering wheel continuous change state, and the multi-frame yaw rate information includes:

[0014] Determining the rotation direction or change trend of the steering wheel according to the steering wheel speed, the rotation state, and the continuous change state of the steering wheel;

[0015] Determining a final yaw rate according to the multiple frames of yaw rate information;

[0016] Determining whether the final yaw rate is in the same direction or has the same change trend as the steering wheel rotation;

[0017] If yes, it is determined that the vehicle is traveling on the target road.

[0018] In some examples, predicting the driving trajectory of the vehicle based on the current speed and acceleration of the vehicle and the multiple frames of historical data includes:

[0019] According to the current speed and acceleration of the vehicle and the multiple frames of historical data, a trajectory is fitted using a method to obtain the driving trajectory of the vehicle.

[0020] In some examples, the target screening according to the driving trajectory includes:

[0021] Get the target location;

[0022] According to the driving trajectory, calculating the time when the longitudinal distance between the vehicle and the target is 0;

[0023] When the time meets the requirement, the lateral position difference between the vehicle and the target after the longitudinal distance is the same at the time is calculated;

[0024] The target is obtained according to the difference.

[0025] In some examples, obtaining the target according to the difference includes:

[0026] If there are multiple targets, the candidate target with the shortest time is selected from the multiple candidate targets as the target.

[0027] In a second aspect, a target screening system is provided, comprising:

[0028] An acquisition module, used for acquiring multiple frames of continuous historical data, wherein the multiple frames of historical data include multiple frames of steering wheel angle information and multiple frames of yaw rate information;

[0029] A judgment module, configured to judge whether the vehicle is traveling on a target road according to the multi-frame steering wheel angle information and the multi-frame yaw rate information, wherein the target road at least includes a road without lane lines / a road with poor lane line quality, a curve, or a continuous curve;

[0030] A prediction module, used for predicting the driving trajectory of the vehicle according to the current speed and acceleration of the vehicle and the multiple frames of historical data when the vehicle is driving on the target road;

[0031] A screening module is used to screen targets according to the driving trajectory.

[0032] In a third aspect, a vehicle is provided, comprising: a target screening system according to the second aspect.

[0033] In a fourth aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the target screening method of the first aspect and any possible implementation method of the first aspect are implemented.

[0034] In a fifth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the steps of the target screening method of the above-mentioned first aspect and any possible implementation method of the first aspect are implemented.

[0035] In a sixth aspect, a computer program product is provided, on which a computer program is stored, and when the program is executed by a processor, the steps of the target screening method of the above-mentioned first aspect and any possible implementation method of the first aspect are implemented.

[0036] By using the embodiments of the present application, continuous multi-frame historical data is obtained, and based on the multi-frame steering wheel angle information and multi-frame yaw rate information, it is determined whether the vehicle is traveling on the target road. When on the target road, the vehicle's driving trajectory is predicted based on the vehicle's current speed, acceleration and multi-frame historical data, and finally the target is screened based on the driving trajectory. In this way, it is possible to accurately determine when the vehicle is on the target road, such as a complex road with complex curves, continuous turns, or no lane lines, and effectively utilize the vehicle data to predict a more accurate vehicle driving trajectory. Through more effective analysis and calculation of the vehicle and target vehicle data, the vehicle trajectory and the possibility of collision with the target vehicle can be more accurately calculated under complex road conditions, providing good target input for various auxiliary driving functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0038] Figure 1 A flow chart of a target screening method provided in an embodiment of the present application;

[0039] Figure 2 A structural block diagram of a target screening system provided in an embodiment of the present application;

[0040] Figure 3 A structural block diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] The present application is further described in detail below in conjunction with the embodiments and drawings. It is to be understood that the specific embodiments described herein are only used to explain the relevant application, rather than to limit the application. It is also necessary to explain that, for ease of description, only the parts related to the application are shown in the drawings.

[0042] It should be noted that, in the absence of conflict, the embodiments of the present application, that is, the features of the embodiments, can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0043] The target screening method, system, vehicle and equipment according to the embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0044] Figure 1 : is a flow chart of a target screening method according to one embodiment of the present application. Figure 1 As shown, the target screening method according to the embodiment of the present application includes the following steps:

[0045] S101: Acquire multiple frames of continuous historical data, wherein the multiple frames of historical data include multiple frames of steering wheel angle information and multiple frames of yaw rate information.

[0046] That is, record multiple frames of historical data. Specifically, record the steering wheel angle information of n frames of history:

[0047] S={S 1 , S 2 …S n}.

[0048] Record the yaw_rate information (yaw rate information) of the historical n frames:

[0049] Y={Y 1 , Y 2 …Y n}.

[0050] S102: judging whether the vehicle is traveling on a target road based on the multi-frame steering wheel angle information and the multi-frame yaw rate information, wherein the target road at least includes a road without lane lines / a road with poor lane line quality, a curve, or a continuous curve.

[0051] In one embodiment of the present application, judging whether the vehicle is traveling on a target road based on the multiple frames of steering wheel angle information and the multiple frames of yaw rate information includes: obtaining a steering wheel speed, a rotation state, and a steering wheel continuous change state based on the multiple frames of steering wheel angle information; judging whether the vehicle is traveling on the target road based on the steering wheel speed, the rotation state, the steering wheel continuous change state, and the multiple frames of yaw rate information.

[0052] Further, judging whether the vehicle is traveling on the target road according to the steering wheel speed, the rotation state, the steering wheel continuously changing state and the multi-frame yaw rate information includes: determining the rotation direction or the changing trend of the steering wheel according to the steering wheel speed, the rotation state and the steering wheel continuously changing state; determining the final yaw rate according to the multi-frame yaw rate information; judging whether the final yaw rate is in the same direction or the same changing trend as the steering wheel rotation; if so, judging that the vehicle is traveling on the target road.

[0053] Specifically, the steering wheel speed calculation is to confirm the current rotation state:

[0054] Steering wheel rotation speed calculation, due to factors such as sensor accuracy and jitter, adding historical frame data for comprehensive calculation can obtain a more accurate and smooth speed, w is the weight:

[0055]

[0056] If the rotation speed is greater than the limit value, that is, the steering wheel is turning quickly, it is considered that the vehicle may be on a curve or a complex road.

[0057] Judgment of the continuous change state of the steering wheel:

[0058] The speed direction is consistent, and the change direction between consecutive frames is consistent, and the change range is greater than the limit:

[0059] Vsteering*Vsteering last >0

[0060] △d1=Si-S i-1 △d1*△d1 last >0 △d1>△limit

[0061] The speed direction is consistent, the changes in consecutive frames are inconsistent, but the historical changes are consistent:

[0062] △d1*△dl last <0 △d5=Si-S i-5 >△limit5

[0063] △d10=Si-S i-10 >△limit10 △d20=Si-S i-20 >△limit20

[0064] When the above two conditions are met, the counter is incremented by 1. When the limit is met, it is considered that the vehicle is currently in a complex curve state based on the steering wheel state:

[0065] count+1 count>C limit .

[0066] Processing of yaw_rate data (yaw rate information):

[0067] Due to the jitter of yaw_rate, adding historical frames for comprehensive calculation can avoid the impact of jitter:

[0068]

[0069] If yaw_rate and the steering wheel are in the same direction or have the same changing trend, it is determined that the road is currently in a complex curve state:

[0070] (Y i *S i >0)||(Vyaw_rate*Vsteering>0).

[0071] S103: If the vehicle is traveling on the target road, predicting the vehicle's driving trajectory according to the vehicle's current speed, acceleration and the multiple frames of historical data.

[0072] In one embodiment of the present application, the driving trajectory of the vehicle is predicted based on the current speed, acceleration and the multiple frames of historical data of the vehicle, including: according to the current speed, acceleration and the multiple frames of historical data of the vehicle, using the trajectory you and method, the driving trajectory of the vehicle is fitted.

[0073] Specifically, in complex road environments, the vehicle speed, acceleration, and yaw_rate are all changing rapidly. That is, on complex roads, increasing the acceleration and yaw_rate change rate to increase the accuracy of the predicted trajectory can yield more accurate results:

[0074]

[0075] Using trajectory fitting method, a more accurate trajectory can be obtained:

[0076] Compute point set:

[0077] P={(x t ,y t ),(x t +△t,y t +△t)...(x t+5 ,y t+5 )}

[0078] Polynomial fitting, generally a cubic polynomial can be used:

[0079]

[0080] Error between polynomial and true value:

[0081]

[0082] Least squares solution, the sum of squares of point set errors is E(w):

[0083]

[0084] By taking the partial derivative of E(w) and solving the corresponding matrix, the polynomial parameters can be obtained, thereby obtaining the predicted trajectory curve (i.e., driving trajectory).

[0085] S104: Target screening is performed according to the driving trajectory.

[0086] In a specific example, target screening is performed according to the driving trajectory, including: obtaining the target position; calculating the time when the longitudinal distance between the vehicle and the target is 0 according to the driving trajectory; when the time meets the requirements, calculating the lateral position difference between the vehicle and the target after the longitudinal distance is the same at the time; and obtaining the target according to the difference.

[0087] Further, obtaining the target according to the difference includes: if there are multiple targets, selecting the candidate target with the shortest time from the multiple candidate targets as the target.

[0088] Specifically, the target position is: (x obj ,y obj ).

[0089] According to the predicted trajectory, calculate the time when the longitudinal distance between the vehicle and the target is 0. t should be between 0 and the limit value, otherwise the target can be discarded without risk:

[0090]

[0091] For the target that meets the previous step, calculate the horizontal position difference at time t, that is, after the longitudinal distance is the same:

[0092] By car:

[0093] Target car:

[0094] Right now:

[0095] When the lateral position difference between the ego vehicle and the target vehicle is less than the specified Y value, it is considered that the ego vehicle may collide with the target vehicle. When multiple target vehicles may collide, the target with the smallest t is selected, that is, the target that makes contact the fastest.

[0096] According to the target screening method of the embodiment of the present application, continuous multi-frame historical data is obtained, and based on the multi-frame steering wheel angle information and the multi-frame yaw rate information, it is determined whether the vehicle is traveling on the target road. When it is on the target road, the vehicle's driving trajectory is predicted based on the vehicle's current speed, acceleration and multi-frame historical data, and finally the target is screened based on the driving trajectory. In this way, it is possible to accurately determine that the vehicle is on the target road, such as a complex road with complex curves, continuous turns, or no lane lines, and effectively utilize the vehicle data to predict a more accurate vehicle driving trajectory. Through more effective analysis and calculation of the vehicle and target vehicle data, the vehicle trajectory and the possibility of collision with the target vehicle can be more accurately calculated under complex road conditions, providing good target input for various auxiliary driving functions.

[0097] Figure 2 is a structural block diagram of a target screening system according to an embodiment of the present application. Figure 2 As shown, the target screening system according to the embodiment of the present application includes: an acquisition module 210, a judgment module 220, a prediction module 230 and a screening module 240, wherein:

[0098] An acquisition module 210 is used to acquire multiple frames of continuous historical data, wherein the multiple frames of historical data include multiple frames of steering wheel angle information and multiple frames of yaw rate information;

[0099] A judgment module 220, configured to judge whether the vehicle is traveling on a target road according to the multi-frame steering wheel angle information and the multi-frame yaw rate information, wherein the target road at least includes a road without lane lines / a road with poor lane line quality, a curve, or a continuous curve;

[0100] A prediction module 230, used for predicting the driving trajectory of the vehicle according to the current speed and acceleration of the vehicle and the multiple frames of historical data when the vehicle is driving on the target road;

[0101] The screening module 240 is used to screen targets according to the driving trajectory.

[0102] According to the target screening system of the embodiment of the present application, continuous multi-frame historical data is obtained, and based on the multi-frame steering wheel angle information and multi-frame yaw rate information, it is determined whether the vehicle is traveling on the target road. When it is on the target road, the vehicle's driving trajectory is predicted based on the vehicle's current speed, acceleration and multi-frame historical data, and finally the target is screened based on the driving trajectory. In this way, it is possible to accurately determine that the vehicle is on the target road, such as a complex road with complex curves, continuous turns, or no lane lines, and effectively utilize the vehicle data to predict a more accurate vehicle driving trajectory. Through more effective analysis and calculation of the vehicle and target vehicle data, the vehicle trajectory and the possibility of collision with the target vehicle can be more accurately calculated under complex road conditions, providing good target input for various auxiliary driving functions.

[0103] For the specific definition of the target screening system, please refer to the definition of the target screening method above, which will not be repeated here. The various modules of the above-mentioned target screening system can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned various modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0104] In one embodiment, a vehicle is provided, comprising: a target screening system according to the above embodiment, the vehicle obtains continuous multi-frame historical data, and determines whether the vehicle is traveling on a target road based on multi-frame steering wheel angle information and multi-frame yaw rate information. When on the target road, the vehicle's driving trajectory is predicted based on the vehicle's current speed, acceleration and multi-frame historical data, and finally the target is screened based on the driving trajectory. Thus, it is possible to accurately determine that the vehicle is on a target road such as a complex road with complex curves, continuous turns, or a road without lane lines, and effectively utilize the vehicle data to predict a more accurate vehicle driving trajectory. Through more effective analysis and calculation of the vehicle and target vehicle data, the vehicle trajectory and the possibility of collision with the target vehicle can be more accurately calculated under complex road conditions, providing good target input for various auxiliary driving functions.

[0105] In one embodiment, a computer device is provided. Figure 3 This is a block diagram of the computer device provided in the embodiment of the present application, refer to Figure 3 The computer device includes a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the aforementioned target screening method embodiment when executing the computer program. For example, the following steps are performed: obtaining multiple frames of continuous historical data, wherein the multiple frames of historical data include multiple frames of steering wheel angle information and multiple frames of yaw rate information;

[0106] Determining whether the vehicle is traveling on a target road according to the multi-frame steering wheel angle information and the multi-frame yaw rate information, wherein the target road at least includes a road without lane lines / a road with poor lane line quality, a curve, or continuous curves;

[0107] If yes, predicting the driving trajectory of the vehicle according to the current vehicle speed, acceleration and the multiple frames of historical data;

[0108] Target screening is performed according to the driving trajectory.

[0109] The embodiment of the present application further provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and the processor implements the aforementioned target screening method embodiment when executing the computer program. For example, the following steps are performed: obtaining multiple frames of continuous historical data, wherein the multiple frames of historical data include multiple frames of steering wheel angle information and multiple frames of yaw rate information;

[0110] Determining whether the vehicle is traveling on a target road according to the multi-frame steering wheel angle information and the multi-frame yaw rate information, wherein the target road at least includes a road without lane lines / a road with poor lane line quality, a curve, or continuous curves;

[0111] If yes, predicting the driving trajectory of the vehicle according to the current vehicle speed, acceleration and the multiple frames of historical data;

[0112] Target screening is performed according to the driving trajectory.

[0113] The present application embodiment provides a computer program product, which includes instructions. When the instructions are executed, the method described in the embodiment of the present application is executed. For example, it can be executed Figure 1 The various steps of the target screening method shown, for example, are performed: acquiring multiple frames of continuous historical data, wherein the multiple frames of historical data include multiple frames of steering wheel angle information and multiple frames of yaw rate information;

[0114] Determining whether the vehicle is traveling on a target road according to the multi-frame steering wheel angle information and the multi-frame yaw rate information, wherein the target road at least includes a road without lane lines / a road with poor lane line quality, a curve, or continuous curves;

[0115] If yes, predicting the driving trajectory of the vehicle according to the current vehicle speed, acceleration and the multiple frames of historical data;

[0116] Target screening is performed according to the driving trajectory.

[0117] Those of ordinary skill in the art can understand that all or part of the processes in the methods for implementing the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0118] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0119] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A target screening method, characterized in that: include: Acquire multiple frames of continuous historical data, wherein the multiple frames of historical data include multiple frames of steering wheel angle information and multiple frames of yaw rate information; Determining whether the vehicle is traveling on a target road according to the multi-frame steering wheel angle information and the multi-frame yaw rate information, wherein the target road at least includes a road without lane lines / a road with poor lane line quality, a curve, or continuous curves; If yes, predicting the driving trajectory of the vehicle according to the current vehicle speed, acceleration and the multiple frames of historical data; Target screening is performed according to the driving trajectory.

2. The target screening method according to claim 1, characterized in that The determining whether the vehicle is traveling on the target road according to the multiple frames of steering wheel angle information and the multiple frames of yaw rate information includes: Obtaining a steering wheel speed, a rotation state, and a steering wheel continuous change state according to the multiple frames of steering wheel angle information; Whether the vehicle is traveling on a target road is determined according to the steering wheel speed, the rotation state, the steering wheel continuous change state and the multi-frame yaw rate information.

3. The target screening method according to claim 2, characterized in that: The determining whether the vehicle is traveling on the target road according to the steering wheel speed, the rotation state, the steering wheel continuous change state and the multi-frame yaw rate information includes: Determining the rotation direction or change trend of the steering wheel according to the steering wheel speed, the rotation state, and the continuous change state of the steering wheel; Determining a final yaw rate according to the multiple frames of yaw rate information; Determining whether the final yaw rate is in the same direction or has the same change trend as the steering wheel rotation; If yes, it is determined that the vehicle is traveling on the target road.

4. The target screening method according to claim 1, characterized in that The predicting of the driving trajectory of the vehicle according to the current vehicle speed, acceleration and the multiple frames of historical data includes: According to the current speed and acceleration of the vehicle and the multiple frames of historical data, a trajectory is fitted using a method to obtain the driving trajectory of the vehicle.

5. The target screening method according to any one of claims 1 to 4, characterized in that: The target screening according to the driving trajectory includes: Get the target location; According to the driving trajectory, calculating the time when the longitudinal distance between the vehicle and the target is 0; When the time meets the requirement, the lateral position difference between the vehicle and the target after the longitudinal distance is the same at the time is calculated; The target is obtained according to the difference.

6. The target screening method according to claim 5, characterized in that: Obtaining the target according to the difference includes: If there are multiple targets, the candidate target with the shortest time is selected from the multiple candidate targets as the target.

7. A target screening system, characterized in that: include: An acquisition module, used for acquiring multiple frames of continuous historical data, wherein the multiple frames of historical data include multiple frames of steering wheel angle information and multiple frames of yaw rate information; A judgment module, configured to judge whether the vehicle is traveling on a target road according to the multi-frame steering wheel angle information and the multi-frame yaw rate information, wherein the target road at least includes a road without lane lines / a road with poor lane line quality, a curve, or a continuous curve; A prediction module, used for predicting the driving trajectory of the vehicle according to the current speed and acceleration of the vehicle and the multiple frames of historical data when the vehicle is driving on the target road; A screening module is used to screen targets according to the driving trajectory.

8. A vehicle, characterized in that: include: The target screening system according to claim 7.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the target screening method according to any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium, comprising a memory and a computer program stored in the memory and executable on a processor, characterized in that: When the program is executed by a processor, the target screening method according to any one of claims 1 to 6 is implemented.

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