Brake control method and device, intelligent driving vehicle and storage medium

Abstract

The invention provides a brake control method and device, an intelligent driving vehicle and a storage medium, and relates to the technical field of computers. The braking control method comprises the steps that point cloud data, collected by a laser radar, at the current moment and point cloud data, collected by the laser radar, at the previous moment are processed through a motion sensing model, so that position information, motion information and category information of each target point in a target point set are obtained; according to the position information, the motion information and the category information of each target point, clustering the target point set to identify a target object; and according to the current motion information of the intelligent driving vehicle, the position information and the motion information of the target object, the braking distance of the intelligent driving vehicle for currently executing the braking operation and the orientation of the target object relative to the intelligent driving vehicle, performing braking control on the intelligent driving vehicle.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a braking control method and device, an intelligent driving vehicle, and a storage medium. Background Art

[0002] The active safety system is an important safety assurance module in the intelligent driving system. It ensures vehicle safety by judging the real-time driving conditions of the vehicle and performing emergency braking when there is a risk of collision between the vehicle and a target object.

[0003] Existing active safety technologies are usually developed based on millimeter-wave radar, which can directly measure the speed of the target based on the Doppler effect, thereby realizing the perception of the target's motion state. Summary of the invention

[0004] The inventors have noticed that existing millimeter-wave radars have three disadvantages: 1) The point cloud collected by millimeter-wave radars is sparse, and the response to small targets is relatively weak, such as children, cats and dogs. 2) The vertical resolution of millimeter-wave radars is very low, and the reflection points are located on the BEV (Bird's Eye View) 2D plane, so it is difficult to distinguish between static obstacles (such as cars parked on the roadside) and non-obstructive background objects (such as the road surface). Therefore, millimeter-wave radars have difficulty in handling static obstacles and can only effectively perceive dynamic obstacles. 3) The speed perception principle of millimeter-wave radars is based on the Doppler effect, and can only achieve effective speed perception in the radial direction (the direction of the line connecting the radar and the target object), but lacks effective perception in the lateral direction. Therefore, millimeter-wave radars cannot measure the true motion state of objects, and thus cannot achieve precise braking control of intelligent driving vehicles.

[0005] Accordingly, the present disclosure provides a braking control method, which obtains the position information, motion information and category information of each target point by utilizing the point cloud data collected by the laser radar at the current moment and the previous moment, identifies the target object by clustering the target points, and then performs braking control on the intelligent driving vehicle according to the current motion information of the intelligent driving vehicle and the braking distance of the current braking operation, the position information and motion information of the target object, and the orientation of the target object relative to the intelligent driving vehicle, thereby ensuring the driving safety of the intelligent driving vehicle through precise braking control.

[0006] According to a first aspect of an embodiment of the present disclosure, a braking control method is provided, which is executed by a braking control device in an intelligent driving vehicle, comprising: using a motion perception model to process point cloud data at a current moment and point cloud data at a previous moment collected by a laser radar to obtain position information, motion information and category information of each target point in a target point set; clustering the target point set according to the position information, motion information and category information of each target point to identify a target object; and performing braking control on the intelligent driving vehicle according to the current motion information of the intelligent driving vehicle, the position information and motion information of the target object, the braking distance of the intelligent driving vehicle currently performing a braking operation, and the orientation of the target object relative to the intelligent driving vehicle.

[0007] In some embodiments, the braking control of the intelligent driving vehicle includes: judging whether the intelligent driving vehicle has a risk of collision with the target object within the braking distance based on the current motion information of the intelligent driving vehicle and the position information and motion information of the target object; judging whether the target object is located in front of the intelligent driving vehicle based on the position information of the target object when the intelligent driving vehicle has a risk of collision with the target object within the braking distance; and controlling the intelligent driving vehicle to perform a braking operation when the target object is located in front of the intelligent driving vehicle.

[0008] In some embodiments, the performing braking control on the intelligent driving vehicle includes: when the target object is located behind or to the side of the intelligent driving vehicle, not performing braking on the intelligent driving vehicle.

[0009] In some embodiments, when the target object is located in front of the intelligent driving vehicle, controlling the intelligent driving vehicle to perform a braking operation includes: when the target object is located in front of the intelligent driving vehicle, judging whether the movement direction of the target object is the same as the movement direction of the intelligent driving vehicle based on the current movement information of the intelligent driving vehicle and the movement information of the target object; and when the movement direction of the target object is the same as the movement direction of the intelligent driving vehicle, controlling the intelligent driving vehicle to perform a braking operation.

[0010] In some embodiments, when the target object is located in front of the intelligent driving vehicle, controlling the intelligent driving vehicle to perform a braking operation includes: when the movement direction of the target object is opposite to the movement direction of the intelligent driving vehicle, not braking the intelligent driving vehicle.

[0011] In some embodiments, when the movement direction of the target object is the same as the movement direction of the intelligent driving vehicle, controlling the intelligent driving vehicle to perform a braking operation includes: when the movement direction of the target object is the same as the movement direction of the intelligent driving vehicle, obtaining the position information and motion information of the target object at N moments before the current moment, where N is a natural number greater than 0; if the change in the relative position of the intelligent driving vehicle and the target object between the current moment and the previous N moments is not within a predetermined range, controlling the intelligent driving vehicle to perform a braking operation.

[0012] In some embodiments, when the movement direction of the target object is the same as the movement direction of the intelligent driving vehicle, controlling the intelligent driving vehicle to perform a braking operation includes: if the change in the relative position of the intelligent driving vehicle and the target object between the current moment and the previous N moments is within a predetermined range, then the intelligent driving vehicle is not braked.

[0013] In some embodiments, after the target object is identified, it is determined whether the target object is included in the target point set obtained at the M moments before the current moment, where M is a natural number greater than 0; if the target object is included in the target point set obtained at the M moments before the current moment, braking control is performed on the intelligent driving vehicle.

[0014] In some embodiments, when the target object is not included in the target point set obtained at the first M moments, emergency braking is not performed on the intelligent driving vehicle.

[0015] In some embodiments, the motion information of each target point includes speed information, acceleration information and angular velocity information of each target point.

[0016] In some embodiments, background points in the original point cloud data collected by the laser radar at the current moment are deleted to obtain a point cloud to be processed; and voxelization is performed on the point cloud to be processed to obtain the point cloud data at the current moment.

[0017] In some embodiments, clustering the target point set includes: cleaning the target point set to delete abnormal target points in the target point set; in the cleaned target point set, clustering target points with the same position information, the same motion information and the same category information to identify the target object.

[0018] According to a second aspect of an embodiment of the present disclosure, a braking control device is provided, comprising: a memory; a processor, coupled to the memory, the processor being configured to execute a braking control method as described in any of the above embodiments based on instructions stored in the memory.

[0019] According to a third aspect of an embodiment of the present disclosure, an intelligent driving vehicle is provided, comprising: a braking control device as described in any of the above embodiments; and a laser radar configured to collect raw point cloud data around the intelligent driving vehicle and send the raw point cloud data to the braking control device.

[0020] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the method involved in any of the above embodiments is implemented.

[0021] According to a fifth aspect of an embodiment of the present disclosure, there is provided a computer program product, comprising computer instructions, wherein the computer instructions, when executed by a processor, implement the method involved in any of the above embodiments.

[0022] Other features and advantages of the present disclosure will become apparent from the following detailed description of exemplary embodiments of the present disclosure with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0024] Figure 1 The figure is a flow chart of a braking control method according to an embodiment of the present disclosure.

[0025] Figure 2 This is a schematic diagram of brake control according to an embodiment of the present disclosure.

[0026] Figure 3 The figure is a schematic structural diagram of a brake control device according to an embodiment of the present disclosure.

[0027] Figure 4 A schematic diagram of the structure of an intelligent driving vehicle according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present disclosure and its application or use. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0029] Unless specifically stated otherwise, the relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present disclosure.

[0030] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0031] Technologies, methods, and apparatus known to ordinary technicians in the relevant field may not be discussed in detail, but where appropriate, such technologies, methods, and apparatus should be considered part of the authorization specification.

[0032] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0033] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0034] Figure 1 The flowchart of the braking control method of one embodiment of the present disclosure is shown in FIG. 1. In some embodiments, the following braking control method is executed by a braking control device in an intelligent driving vehicle, including steps 11-13.

[0035] In step 11, the point cloud data at the current moment and the point cloud data at the previous moment collected by the laser radar are processed using a motion perception model to obtain the position information, motion information and category information of each target point in the target point set.

[0036] Compared with millimeter-wave radar, the point cloud of lidar is dense and includes richer semantic and geometric information.

[0037] In some embodiments, the motion information of each target point includes speed information, acceleration information, and angular velocity information of each target point.

[0038] It should be noted here that the motion perception model uses the point cloud data at the current moment and the point cloud data at the previous moment to mine spatiotemporal semantic information, thereby outputting rich information about the target point. For example, the output of the motion perception model includes the position information (x, y), velocity information (vx, vy), acceleration information (ax, ay), angular velocity information (w) and category information (objType) of the target point, thereby being able to fully describe the target in the scene.

[0039] In some embodiments, background points in the original point cloud data collected by the laser radar at the current moment are deleted to obtain the point cloud to be processed. Next, the point cloud to be processed is voxelized to obtain the point cloud data at the current moment.

[0040] It should be noted here that background points in the original point cloud data (for example, point cloud data related to the ground) will interfere with the braking control and even cause a large number of emergency braking false triggers. Therefore, by deleting the background points in the original point cloud data, the occurrence of emergency braking false triggers can be effectively avoided.

[0041] In some embodiments, background points in the original point cloud data are deleted by a clustering algorithm, for example, the clustering algorithm includes a DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm.

[0042] In step 12, the target point set is clustered according to the position information, motion information and category information of each target point to identify the target object.

[0043] It should be noted that multiple target points on the same object have consistent information. For example, target points on the same car should have the same speed, acceleration and category information, and the position deviations between the target points on the same car should also be within a predetermined range.

[0044] In some embodiments, the target point set is cleaned to delete abnormal target points in the target point set. Next, in the cleaned target point set, target points with the same position information, the same motion information and the same category information are clustered to identify the target object.

[0045] For example, the clustering algorithm includes the DBSCAN algorithm.

[0046] It should be noted here that by cleaning the target set so as to delete outliers, the occurrence of erroneous triggering of emergency braking can be effectively reduced.

[0047] For example, using the above processing, the following information can be obtained: a car is located in front of the intelligent driving vehicle , the speed is , the acceleration is , the angular velocity is 15 degrees counterclockwise per second.

[0048] In some embodiments, after the target object is identified, it is determined whether the target object is included in the target point set obtained at the previous M moments before the current moment, where M is a natural number greater than 0. If the target object is included in the target point set obtained at the previous M moments, the following step 13 is performed. If the target object is not included in the target point set obtained at the previous M moments, emergency braking is not performed on the intelligent driving vehicle.

[0049] It should be noted here that if the target object is recognized at the current moment, but not recognized at the M moments before the current moment, it means that the target object is recognized for the first time, which may be an erroneous result caused by interference from background points. Therefore, in this case, there is no need to perform emergency braking on the intelligent driving vehicle.

[0050] If the target object is identified at the current moment and the target object is also identified at the M moments before the current moment, it indicates that the target object does exist. In this case, the following step 13 is performed to perform the operation of braking control on the intelligent driving vehicle.

[0051] It should also be noted that if the value of parameter M is too large, the processing time of the brake control device may be too long. Since the vehicle is usually traveling at a high speed, a vehicle collision may occur before the brake control device completes the judgment process. To avoid this, the value of M is not greater than 3. For example, M is 1.

[0052] In step 13, the intelligent driving vehicle is braked according to the current motion information of the intelligent driving vehicle, the position information and motion information of the target object, the braking distance of the intelligent driving vehicle currently performing the braking operation, and the orientation of the target object relative to the intelligent driving vehicle.

[0053] For example, the current motion information of the intelligent driving vehicle includes information such as the speed and acceleration of the intelligent driving vehicle, and also includes the driving trajectory of the intelligent driving vehicle in the future.

[0054] In some embodiments, the steps of performing braking control on an intelligent driving vehicle include the following.

[0055] 1) Based on the current motion information of the intelligent driving vehicle and the position and motion information of the target object, determine whether there is a risk of collision between the intelligent driving vehicle and the target object within the braking distance.

[0056] 2) When there is a risk of collision between the intelligent driving vehicle and a target object within the braking distance, determine whether the target object is located in front of the intelligent driving vehicle based on the position information of the target object.

[0057] 3) When the target object is located in front of the intelligent driving vehicle, the intelligent driving vehicle is controlled to perform a braking operation.

[0058] In some embodiments, when the target object is located behind or to the side of the smart driving vehicle, the smart driving vehicle is not braked.

[0059] It should be noted that, when there is a risk of collision between the target object and the intelligent driving vehicle, and the target object is behind or to the side of the intelligent driving vehicle, the possible collision is a passive collision for the intelligent driving vehicle. In this case, if the intelligent driving vehicle performs braking or other operations, it may not be conducive to the avoidance operation of the target object, and a rear-end collision is more likely to occur. Therefore, in this case, the brake control device does not brake the intelligent driving vehicle.

[0060] In some embodiments, when the target object is located in front of the intelligent driving vehicle, it is determined whether the moving direction of the target object is the same as the moving direction of the intelligent driving vehicle based on the current moving information of the intelligent driving vehicle and the moving information of the target object. When the moving direction of the target object is the same as the moving direction of the intelligent driving vehicle, the intelligent driving vehicle is controlled to perform a braking operation.

[0061] That is to say, there is a risk of collision between the target object and the intelligent driving vehicle, the target object is located in front of the intelligent driving vehicle, and the moving direction of the target object is the same as the moving direction of the intelligent driving vehicle. In this case, the intelligent driving vehicle may rear-end the target object in front. Therefore, in this case, the braking control device controls the intelligent driving vehicle to perform a braking operation to avoid rear-ending the target object in front.

[0062] In some embodiments, when the moving direction of the target object is opposite to the moving direction of the smart driving vehicle, the smart driving vehicle is not braked.

[0063] That is to say, there is a risk of collision between the target object and the smart driving vehicle, the target object is located in front of the smart driving vehicle, and the movement direction of the target object is opposite to the movement direction of the smart driving vehicle. In this case, the target object is moving in the opposite direction relative to the smart driving vehicle. Usually in this case, the target object in the reverse driving state will take corresponding avoidance measures. If the smart driving vehicle performs emergency braking at this time, it may cause the vehicle behind the smart driving vehicle to rear-end the smart driving vehicle. Therefore, in this case, the brake control device does not brake the smart driving vehicle.

[0064] In some embodiments, when the moving direction of the target object is the same as the moving direction of the intelligent driving vehicle, the position information and movement information of the target object at the N moments before the current moment are obtained, where N is a natural number greater than 0. If the change in the relative position of the intelligent driving vehicle and the target object between the current moment and the N moments before the current moment is not within a predetermined range, the intelligent driving vehicle is controlled to perform a braking operation.

[0065] That is to say, if the change in the relative position of the intelligent driving vehicle and the target object between the current moment and the previous N moments is not within a predetermined range, it indicates that the intelligent driving vehicle and the target object are not in a state of accompanying driving. In this case, the braking control device controls the intelligent driving vehicle to perform a braking operation.

[0066] In some embodiments, if the change in the relative position of the intelligent driving vehicle and the target object between the current moment and the previous N moments is within a predetermined range, the intelligent driving vehicle is not braked.

[0067] That is to say, if the change in the relative position of the intelligent driving vehicle and the target object between the current moment and the previous N moments is within a predetermined range, it indicates that the intelligent driving vehicle and the target object are in a state of accompanying driving. In this case, the braking control device does not brake the intelligent driving vehicle.

[0068] It should be noted here that if the intelligent driving vehicle and the target object are in a accompanying driving state, it means that although the distance between the intelligent driving vehicle and the target object is close, the probability of a collision is very small. Therefore, in this case, the braking control device does not brake the intelligent driving vehicle.

[0069] For example, at the current moment and the previous N moments, if the intelligent driving vehicle and the target object have the same driving direction, the position of the target object relative to the intelligent driving vehicle has not changed, and the change in the distance between the target object and the intelligent driving vehicle is within a predetermined range, then it is determined that the intelligent driving vehicle and the target object are in an accompanying driving state.

[0070] It should also be noted that if the value of parameter N is too large, the processing time of the brake control device may be too long. Since the vehicle is usually traveling at a high speed, a vehicle collision may occur before the brake control device completes the judgment process. To avoid this, the value of N is not greater than 3. For example, N is 1.

[0071] Figure 2 This is a schematic diagram of brake control according to an embodiment of the present disclosure.

[0072] like Figure 2 As shown, the original point cloud data collected by the laser radar at the current time T is preprocessed to obtain the point cloud data at the time T.

[0073] For example, the background points in the original point cloud data are deleted to obtain the point cloud to be processed. The point cloud to be processed is voxelized to obtain the point cloud data at time T.

[0074] The point cloud data at the current time T and the point cloud data at the time T-1 are input into the motion sensing network so that the motion sensing network outputs the position information, speed information, acceleration information, angle information and category information of each target point in the target point set.

[0075] Next, the target point set is clustered according to the position information, motion information and category information of each target point to identify the target object.

[0076] Then, the braking control device performs braking control on the intelligent driving vehicle according to the current motion information of the intelligent driving vehicle, the position information and motion information of the target object, the braking distance of the intelligent driving vehicle currently performing the braking operation, and the orientation of the target object relative to the intelligent driving vehicle.

[0077] Figure 3 The figure is a schematic structural diagram of a brake control device according to an embodiment of the present disclosure.

[0078] like Figure 3 As shown, the brake control device 30 is in the form of a general-purpose computing device. The brake control device 30 includes a memory 31, a processor 32, and a bus 33 connecting different system components.

[0079] The memory 31 may include, for example, a system memory, a non-volatile storage medium, etc. The system memory may store, for example, an operating system, an application program, a boot loader, and other programs. The system memory may include a volatile storage medium, such as a random access memory (RAM) and / or a cache memory. The non-volatile storage medium may store, for example, instructions of a corresponding embodiment of at least one braking control method being executed. The non-volatile storage medium includes, but is not limited to, a disk memory, an optical memory, a flash memory, etc.

[0080] The processor 32 may be implemented by a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistors, and other discrete hardware components. Accordingly, each module such as an acquisition module, a calculation module, and an adjustment module may be implemented by a central processing unit (CPU) running instructions in a memory that execute corresponding steps, or may be implemented by a dedicated circuit that executes corresponding steps.

[0081] For example, the processor 32 is configured to execute instructions stored in the memory to implement the following Figure 1The method of any one of the embodiments.

[0082] The bus 33 may use any of a variety of bus structures, including, but not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, and a Peripheral Component Interconnect (PCI) bus.

[0083] The interfaces 34, 35, 36 of the brake control device 30 and the memory 31 and the processor 32 can be connected via a bus 33. The input / output interface 34 provides a connection interface for input / output devices such as a display, a mouse, and a keyboard. The network interface 35 provides a connection interface for various networked devices. The storage interface 36 provides a connection interface for external storage devices such as a floppy disk, a USB flash drive, and an SD card.

[0084] Here, various aspects of the present disclosure are described with reference to flowcharts and / or block diagrams of methods, devices, and computer program products according to embodiments of the present disclosure. It should be understood that each frame of the flowchart and / or block diagram and the combination of frames can be implemented by computer-readable program instructions.

[0085] These computer-readable program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable device to produce a machine, so that the processor executes the instructions to produce means for implementing the functions specified in one or more blocks in the flowchart and / or block diagram.

[0086] These computer-readable program instructions may also be stored in a computer-readable memory, which cause the computer to work in a specific manner to produce an article of manufacture, including instructions for implementing the functions specified in one or more blocks in the flowchart and / or block diagram.

[0087] The present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects.

[0088] The present disclosure also provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the following is implemented: Figure 1 The method of any one of the embodiments.

[0089] The present disclosure also provides a computer program product, including computer instructions, wherein when the computer instructions are executed by a processor, the following is achieved: Figure 1 The method of any one of the embodiments.

[0090] Figure 4 FIG. 1 is a schematic diagram of the structure of an intelligent driving vehicle according to an embodiment of the present disclosure. Figure 4 As shown, the intelligent driving vehicle includes a brake control device 41 and a laser radar 42. The brake control device 41 includes Figure 2A brake control device according to any one of the embodiments.

[0091] The laser radar 42 is configured to collect raw point cloud data around the intelligent driving vehicle and send the raw point cloud data to the brake control device 41.

[0092] The present invention obtains the position information, motion information and category information of each target point by utilizing the point cloud data collected by the laser radar at the current moment and the previous moment, identifies the target object by clustering the target points, and then performs braking control on the intelligent driving vehicle according to the current motion information of the intelligent driving vehicle and the braking distance of the current braking operation, the position information and motion information of the target object, and the orientation of the target object relative to the intelligent driving vehicle, thereby ensuring the driving safety of the intelligent driving vehicle through precise braking control.

[0093] In some embodiments, the functional modules described above can be implemented as a general-purpose processor, a programmable logic controller (PLC), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components or any appropriate combination thereof for performing the functions described in the present disclosure.

[0094] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0095] The description of the present disclosure is given for the purpose of illustration and description, and is not intended to be exhaustive or to limit the present disclosure to the disclosed form. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present disclosure, and to enable those of ordinary skill in the art to understand the present disclosure and thereby design various embodiments with various modifications suitable for specific uses.

Claims

1. A braking control method, performed by a braking control device in an intelligent driving vehicle, comprising: The motion perception model is used to process the point cloud data at the current moment and the point cloud data at the previous moment collected by the laser radar to obtain the position information, motion information and category information of each target point in the target point set; Clustering the target point set according to the position information, motion information and category information of each target point to identify the target object; The intelligent driving vehicle is braked according to the current motion information of the intelligent driving vehicle, the position information and motion information of the target object, the braking distance of the intelligent driving vehicle currently performing the braking operation, and the orientation of the target object relative to the intelligent driving vehicle.

2. The braking control method according to claim 1, wherein: The braking control of the intelligent driving vehicle includes: Determining whether there is a risk of collision between the intelligent driving vehicle and the target object within the braking distance according to the current motion information of the intelligent driving vehicle and the position information and motion information of the target object; When there is a risk of collision between the intelligent driving vehicle and the target object within the braking distance, judging whether the target object is located in front of the intelligent driving vehicle according to the position information of the target object; When the target object is located in front of the intelligent driving vehicle, the intelligent driving vehicle is controlled to perform a braking operation.

3. The braking control method according to claim 2, wherein: The braking control of the intelligent driving vehicle includes: In the case where the target object is located behind or on the side of the intelligent driving vehicle, the intelligent driving vehicle is not braked.

4. The braking control method according to claim 2, wherein: When the target object is located in front of the intelligent driving vehicle, controlling the intelligent driving vehicle to perform a braking operation includes: When the target object is located in front of the intelligent driving vehicle, judging whether the movement direction of the target object is the same as the movement direction of the intelligent driving vehicle according to the current movement information of the intelligent driving vehicle and the movement information of the target object; When the moving direction of the target object is the same as the moving direction of the intelligent driving vehicle, the intelligent driving vehicle is controlled to perform a braking operation.

5. The braking control method according to claim 4, wherein: When the target object is located in front of the intelligent driving vehicle, controlling the intelligent driving vehicle to perform a braking operation includes: When the moving direction of the target object is opposite to the moving direction of the intelligent driving vehicle, the intelligent driving vehicle is not braked.

6. The braking control method according to claim 4, wherein: When the moving direction of the target object is the same as the moving direction of the intelligent driving vehicle, controlling the intelligent driving vehicle to perform a braking operation includes: When the moving direction of the target object is the same as the moving direction of the intelligent driving vehicle, obtaining the position information and movement information of the target object at N moments before the current moment, where N is a natural number greater than 0; If the change in the relative position of the intelligent driving vehicle and the target object between the current moment and the previous N moments is not within a predetermined range, the intelligent driving vehicle is controlled to perform a braking operation.

7. The braking control method according to claim 6, wherein: When the moving direction of the target object is the same as the moving direction of the intelligent driving vehicle, controlling the intelligent driving vehicle to perform a braking operation includes: If the change in the relative position between the intelligent driving vehicle and the target object between the current moment and the previous N moments is within a predetermined range, the intelligent driving vehicle is not braked.

8. The brake control method according to claim 1, further comprising: After the target object is identified, it is determined whether the target object is included in the target point set obtained at M moments before the current moment, where M is a natural number greater than 0; In a case where the target point set obtained at the first M moments includes the target object, braking control is performed on the intelligent driving vehicle.

9. The brake control method according to claim 8, further comprising: When the target object is not included in the target point set obtained at the first M moments, emergency braking is not performed on the intelligent driving vehicle.

10. The brake control method according to claim 1, wherein: The motion information of each target point includes speed information, acceleration information and angular velocity information of each target point.

11. The braking control method according to any one of claims 1 to 10, further comprising: Deleting background points in the original point cloud data collected by the laser radar at the current moment to obtain a point cloud to be processed; The point cloud to be processed is voxelized to obtain the point cloud data at the current moment.

12. The braking control method according to any one of claims 1 to 10, wherein: The clustering of the target point set comprises: Cleaning the target point set to delete abnormal target points in the target point set; In the cleaned target point set, target points with the same position information, the same motion information and the same category information are clustered to identify the target object.

13. A brake control device, comprising: Memory; A processor is coupled to the memory, and the processor is configured to execute the brake control method according to any one of claims 1 to 12 based on instructions stored in the memory.

14. An intelligent driving vehicle, comprising: The brake control device according to claim 13; The laser radar is configured to collect raw point cloud data around the intelligent driving vehicle and send the raw point cloud data to the braking control device.

15. A computer-readable storage medium, wherein: The computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the braking control method according to any one of claims 1 to 12 is implemented. 16 . A computer program product, comprising computer instructions, wherein when the computer instructions are executed by a processor, the brake control method according to claim 1 is implemented.

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