Method and device for processing data information in vehicle and electronic equipment

Abstract

The invention discloses a method and device for processing data information in a vehicle and electronic equipment, and relates to the technical field of intelligent driving, and the method comprises the steps: obtaining the current motion parameters of a target object, determining the direction angle of the target object relative to a target vehicle based on the current motion direction and the operation parameters of the target vehicle, and obtaining the direction angle of the target object; and determining a target cluster from a preset cluster set based on the cluster parameter and the direction angle of each preset cluster in the preset cluster set stored in the target vehicle, and updating the cluster parameter of the target cluster in the target vehicle according to the current motion parameter. The technical problem that cluster parameters cannot be accurately updated due to the fact that the target cluster associated with the target object cannot be accurately determined in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent driving technology, and in particular to a method and device for processing data information in a vehicle, and an electronic device. Background Art

[0002] In the field of intelligent automobile driving, millimeter-wave radar can be used to detect and track target objects in the surrounding environment. Millimeter-wave radar can collect point cloud data reflected by the target object (i.e., the signal points reflected by the target object). Then, clustering and association methods can be used to accurately identify and track the target. That is, these point cloud data can be clustered into clusters according to spatial position and motion characteristics, and then the correlation between the target and the cluster can be further compared to associate the target and update the motion parameters of the target.

[0003] In related technologies, the association algorithm generally adopts the nearest neighbor (NN) strategy, that is, first calculating the feature difference between the target and the cluster, such as the distance and speed, and then comparing the feature difference with a preset fixed threshold to determine which cluster the target is closest to, and then performing association.

[0004] However, in actual applications, since the target may have various movement postures during the activity, such as going straight, crossing, and crossing diagonally, the setting of the threshold becomes very complex and sensitive. The wrong threshold may lead to the situation that the target is not associated with a cluster or is associated with the wrong cluster, which in turn reduces the recognition accuracy of the target's operating parameters and reduces the reliability and safety of intelligent driving.

[0005] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0006] The embodiments of the present invention provide a method and device for processing data information in a vehicle, and an electronic device, so as to at least solve the technical problem in the related art that a target cluster associated with a target object cannot be accurately determined, resulting in an inability to accurately update cluster parameters.

[0007] According to one aspect of an embodiment of the present invention, a method for processing data information in a vehicle is provided, comprising: obtaining current motion parameters of a target object, wherein the current motion parameters include at least: a current motion direction, and the target object refers to an object that moves within a preset range of a driving target vehicle; determining a direction angle of the target object relative to the target vehicle based on the current motion direction and the operating parameters of the target vehicle; determining a target cluster from the preset cluster set stored in the target vehicle based on cluster parameters of each preset cluster in the preset cluster set and the direction angle, wherein each preset cluster is used to indicate an object, and the cluster parameters are used to record the motion parameters of each object; and updating the cluster parameters of the target cluster in the target vehicle according to the current motion parameters.

[0008] Furthermore, before obtaining the current motion parameters of the target object, it also includes: constructing a vehicle coordinate system with the target vehicle as the center, the motion direction of the target vehicle as the first direction, and the left direction or the right direction of the target vehicle as the second direction; based on the vehicle coordinate system, using a radar sensor deployed in the target vehicle to collect point cloud data of the target object, wherein the point cloud data includes: position data, speed data; based on the point cloud data, determining the current position and current speed of the target object, and based on the position data and the speed data, determining the current motion direction of the target object.

[0009] Furthermore, the current motion parameters also include: a current speed, the current speed includes: a first direction speed and a second direction speed, the operating parameters include at least: a yaw angular rate, and based on the current motion direction and the operating parameters of the target vehicle, the step of determining the direction angle of the target object relative to the target vehicle includes: calculating a first rotational direction speed and a second rotational direction speed based on the first direction speed, the second direction speed and the yaw angular rate; calculating the direction angle of the target object relative to the target vehicle based on the first rotational direction speed and the second rotational direction speed.

[0010] Furthermore, before determining the target cluster from the preset cluster set based on the cluster parameters of each preset cluster in the preset cluster set stored in the target vehicle and the direction angle, it also includes: determining the associated area based on the current motion direction; and screening the preset clusters located in the associated area from all clusters stored in the target vehicle based on the position parameters included in the cluster parameters to obtain the preset cluster set.

[0011] Furthermore, based on the cluster parameters of each preset cluster in the preset cluster set stored in the target vehicle and the direction angle, the step of determining the target cluster from the preset cluster set includes: traversing the preset cluster set to calculate the angle between the line connecting the current cluster and the target object; based on the line angle and the direction angle, calculating the parameter difference between the cluster parameters of the current cluster and the current motion parameters, wherein the parameter difference includes: a first direction difference, a second direction difference, and a speed difference; when the first direction difference is less than a first preset position threshold, the second direction difference is less than a second preset position threshold, and the speed difference is less than a preset speed threshold, adding the current cluster to the initial cluster set; based on the parameter difference, calculating the preset distance of each cluster in the initial cluster set; and determining the cluster indicated by the minimum preset distance as the target cluster.

[0012] Furthermore, the current motion parameters also include: a current position, and a step of calculating an angle between a line connecting the current cluster and the target object, comprising: calculating a first absolute difference between a first cluster direction position included in the cluster parameters of the current cluster and a first direction position in the current position; calculating a second absolute difference between a second cluster direction position included in the cluster parameters of the current cluster and a second direction position in the current position; and calculating the angle between the line based on the first absolute difference and the second absolute difference.

[0013] Furthermore, the step of calculating the parameter difference between the cluster parameters of the current cluster and the current motion parameters based on the line angle and the direction angle includes: calculating the deflection angle of the current cluster based on the line angle and the direction angle; calculating the distance value between the current cluster and the target object based on the first absolute difference and the second absolute difference; calculating the first direction difference and the second direction difference based on the distance value and the deflection angle; determining the current radial velocity based on the current velocity included in the current motion parameters, and calculating the velocity difference based on the cluster velocity included in the cluster parameters and the current radial velocity; and characterizing the first direction difference, the second direction difference and the velocity difference as the parameter difference.

[0014] According to another aspect of an embodiment of the present invention, a device for processing data information in a vehicle is also provided, comprising: an acquisition unit, used to acquire current motion parameters of a target object, wherein the current motion parameters include at least: a current motion direction, and the target object refers to an object that moves within a preset range of a driving target vehicle; a first determination unit, used to determine the direction angle of the target object relative to the target vehicle based on the current motion direction and the operating parameters of the target vehicle; a second determination unit, used to determine a target cluster from a preset cluster set stored in the target vehicle based on the cluster parameters of each preset cluster in the preset cluster set and the direction angle, wherein each preset cluster is used to indicate an object, and the cluster parameters are used to record the motion parameters of each object; an updating unit, used to update the cluster parameters of the target cluster in the target vehicle according to the current motion parameters.

[0015] Furthermore, the processing device also includes: a first construction module, which is used to construct a vehicle coordinate system with the target vehicle as the center, the movement direction of the target vehicle as the first direction, and the left direction or the right direction of the target vehicle as the second direction before obtaining the current motion parameters of the target object; a first acquisition module, which is used to acquire point cloud data of the target object based on the vehicle coordinate system using a radar sensor deployed in the target vehicle, wherein the point cloud data includes: position data and speed data; a first determination module, which is used to determine the current position and current speed of the target object based on the point cloud data, and determine the current motion direction of the target object based on the position data and the speed data.

[0016] Furthermore, the current motion parameters also include: a current speed, the current speed includes: a first direction speed and a second direction speed, the operating parameters include at least: a yaw angular rate, and the first determination unit includes: a first calculation module, used to calculate a first rotational direction speed and a second rotational direction speed based on the first direction speed, the second direction speed and the yaw angular rate; a second calculation module, used to calculate the direction angle of the target object relative to the target vehicle based on the first rotational direction speed and the second rotational direction speed.

[0017] Furthermore, the processing device also includes: a second determination module, used to determine the associated area based on the current movement direction before determining the target cluster from the preset cluster set based on the cluster parameters of each preset cluster in the preset cluster set stored in the target vehicle and the direction angle; a first screening module, used to screen the preset cluster located in the associated area from all clusters stored in the target vehicle based on the position parameters contained in the cluster parameters to obtain the preset cluster set.

[0018] Furthermore, the second determination unit includes: a third calculation module, used to traverse the preset cluster set and calculate the angle between the line connecting the current cluster and the target object; a fourth calculation module, used to calculate the parameter difference between the cluster parameters of the current cluster and the current motion parameters based on the line angle and the direction angle, wherein the parameter difference includes: a first direction difference, a second direction difference, and a speed difference; a first adding module, used to add the current cluster to the initial cluster set when the first direction difference is less than a first preset position threshold, the second direction difference is less than a second preset position threshold, and the speed difference is less than a preset speed threshold; a fifth calculation module, used to calculate the preset distance of each cluster in the initial cluster set based on the parameter difference; and a third determination module, used to determine the cluster indicated by the minimum preset distance as the target cluster.

[0019] Furthermore, the current motion parameters also include: a current position, and the third calculation module includes: a first calculation submodule, used to calculate a first absolute difference between a first cluster direction position included in the cluster parameters of the current cluster and a first direction position in the current position; a second calculation submodule, used to calculate a second absolute difference between a second cluster direction position included in the cluster parameters of the current cluster and a second direction position in the current position; and a third calculation submodule, used to calculate the line angle based on the first absolute difference and the second absolute difference.

[0020] Further, the fourth calculation module includes: a fourth calculation submodule, used to calculate the deflection angle of the current cluster based on the connecting line angle and the direction angle; a fifth calculation submodule, used to calculate the distance value between the current cluster and the target object based on the first absolute difference and the second absolute difference; a sixth calculation submodule, used to calculate the first direction difference and the second direction difference based on the distance value and the deflection angle; a first determination submodule, used to determine the current radial velocity based on the current velocity included in the current motion parameter, and calculate the velocity difference based on the cluster velocity included in the cluster parameter and the current radial velocity; a first characterization submodule, used to characterize the first direction difference, the second direction difference and the velocity difference as the parameter difference.

[0021] According to another aspect of an embodiment of the present invention, a computer program product is also provided, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for processing data information in a vehicle described in any one of the above is implemented.

[0022] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the above-mentioned methods for processing data information in a vehicle.

[0023] In the present invention, by acquiring the current motion parameters of the target object, the direction angle of the target object relative to the target vehicle is determined based on the current motion direction and the operating parameters of the target vehicle, the target cluster is determined from the preset cluster set based on the cluster parameters and direction angle of each preset cluster in the preset cluster set stored in the target vehicle, and the cluster parameters of the target cluster in the target vehicle are updated according to the current motion parameters, thereby solving the technical problem in the related art that the target cluster associated with the target object cannot be accurately determined, resulting in the inability to accurately update the cluster parameters.

[0024] In the present invention, when the target object is moving, by obtaining the current movement direction of the target object relative to the ground and combining it with the operating parameters of the target vehicle in driving, the movement posture of the target object relative to the target vehicle (i.e., the direction angle of the target object relative to the target vehicle) can be calculated, and then the target cluster associated with the target object is retrieved according to the movement posture, so that the cluster parameters of the target object can be accurately updated, and accurate tracking of the target object is achieved, avoiding the problem of dynamic adjustment of the threshold, and thus achieving the technical effect of associating the target object to the correct cluster to improve the accuracy of target recognition. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0026] Figure 1 is a flow chart of an optional method for processing data information in a vehicle according to an embodiment of the present invention;

[0027] Figure 2 is a schematic diagram of an optional vehicle coordinate system according to an embodiment of the present invention;

[0028] Figure 3 is an optional schematic diagram of the target object in different motion postures;

[0029] Figure 4 is a schematic diagram of an optional method of converting a motion posture of a target object into a motion posture relative to a target vehicle according to an embodiment of the present invention;

[0030] Figure 5It is a schematic diagram of an optional method of using a nearest neighbor algorithm to associate clusters with target objects in the related art;

[0031] Figure 6 is a schematic diagram of an optional cluster association according to the motion posture of the target object relative to the vehicle according to an embodiment of the present invention;

[0032] Figure 7 is a schematic diagram of an optional process of associating clusters of target objects according to postures according to an embodiment of the present invention;

[0033] Figure 8 is a schematic diagram of an optional device for processing data information in a vehicle according to an embodiment of the present invention;

[0034] Fig. 9 The present invention is a hardware structure block diagram of an electronic device (or mobile device) for a method for processing data information in a vehicle according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0036] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0037] It should be noted that the relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) collected and involved in the present invention are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data are in compliance with the relevant laws, regulations and standards of the relevant regions, necessary confidentiality measures are taken, and public order and good customs are not violated, and corresponding operation entrances are provided for users to choose to authorize or refuse. For example, an interface is set between the system and the relevant users or organizations. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0038] The present invention proposes a method for associating millimeter-wave radar targets according to the posture of a vehicle, which can fully consider the actual motion conditions of target objects (such as vehicles, pedestrians, road facilities, etc.) detected by the millimeter-wave radar, and correctly associate the target objects with corresponding clusters through the motion posture of the target objects relative to the vehicle (i.e., the target vehicle in driving) through operation steps such as direction angle rotation, thereby improving the accuracy of target motion parameter recognition.

[0039] The present invention is described in detail below in conjunction with various embodiments.

[0040] Embodiment 1

[0041] According to an embodiment of the present invention, an embodiment of a method for processing data information in a vehicle is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0042] Figure 1 is a flow chart of an optional method for processing data information in a vehicle according to an embodiment of the present invention, such as Figure 1 As shown, the method comprises the following steps:

[0043] Step S101, obtaining current motion parameters of the target object, wherein the current motion parameters at least include: current motion direction, and the target object refers to an object moving within a preset range of the target vehicle being driven.

[0044] In step S101, a millimeter-wave radar deployed in a target vehicle (also referred to as the vehicle) in motion can be used to transmit information to objects (i.e., target objects, also referred to as target objects, such as other vehicles, pedestrians, and road facilities) that are active within a preset range of the vehicle (i.e., a range centered on the vehicle and extending outward a certain distance (e.g., 5 meters)), and receive signals transmitted back by the target objects. By processing the signals, the current motion parameters of the target objects can be obtained. In this way, the dynamic changes of the target objects can be monitored in real time to achieve real-time identification and tracking of the target objects.

[0045] In this embodiment, the current motion parameters of the target object may include: the current motion direction (the motion direction is the motion direction relative to the earth (ground)), and may also include: current speed, current position and other information. For example, the motion parameters corresponding to the target object 1 (obj1) can be expressed as: obj1 (x1, y1, Vx1, Vy1, head1), where x1 and y1 are used to indicate the position, Vx1 and Vy1 are used to indicate the speed, and head1 is used to indicate the motion direction of the target object relative to the earth.

[0046] Step S102: determining the direction angle of the target object relative to the target vehicle based on the current moving direction and the operating parameters of the target vehicle.

[0047] In step S102, the target object's current moving direction head1 and the target vehicle's operating parameters (including yaw rate yawrate) can be combined to obtain the target's moving posture relative to the vehicle (i.e., the target's direction angle headAngle relative to the vehicle). In this way, the target vehicle's moving posture relative to the ground can be converted into a moving posture relative to the vehicle, which facilitates the subsequent correct association of the corresponding clusters.

[0048] In this embodiment, the yaw rate yawrate of the vehicle may be determined by the rotation angle of the steering wheel.

[0049] Step S103, determining a target cluster from the preset cluster set based on the cluster parameters and direction angles of each preset cluster in the preset cluster set stored in the target vehicle, wherein each preset cluster is used to indicate an object, and the cluster parameters are used to record motion parameters of each object.

[0050] In this embodiment, the point cloud data (including data such as speed and position) collected by the radar sensor in the target vehicle during the driving process can be clustered to obtain multiple clusters, and these clusters are stored in the target vehicle. Each cluster indicates an object (such as a vehicle, a pedestrian, etc.), and then the cluster parameters corresponding to the cluster (including motion parameters such as position parameters and speed parameters) are determined by statistically analyzing the point cloud data belonging to the same cluster, so as to record the running parameters of the corresponding object with the cluster parameters. For example, based on all the point cloud data, the sum of the speeds is counted, and then the average speed is calculated based on the sum of the speeds, and the average speed is the speed parameter in the cluster parameters (i.e., the cluster speed).

[0051] In step S103, the target cluster can be determined from the preset cluster set based on the cluster parameters (including: first cluster direction position Cx1, second cluster direction position Cy1, cluster speed Cv1) and direction angle of each preset cluster in the preset cluster set stored in the target vehicle (i.e., a cluster set composed of preset clusters pre-screened from all clusters).

[0052] In this embodiment, the cluster parameters can be expressed as Cl u1 (Cx1, Cy1, Cv1), where Cx1 and Cy1 represent the motion coordinates in the first direction x and the second direction y, and Cv1 represents the radial velocity of the cluster relative to the radar (i.e., the radar on the target vehicle) (i.e., the projection of the velocity components in the x and y directions on the relative radar line).

[0053] Step S104, updating the cluster parameters of the target cluster in the target vehicle according to the current motion parameters.

[0054] In step S104, cluster parameters of the target cluster in the target vehicle may be updated according to the current motion parameters of the target object, so as to achieve accurate recognition and tracking of the target object.

[0055] In this embodiment, the motion coordinates and speed of the target object can be recalculated according to the current motion parameters and the operating parameters contained in the multiple point cloud data in the cluster parameters to obtain the latest cluster parameters, thereby achieving the purpose of accurately identifying and tracking the target object.

[0056] In summary, the current motion parameters of the target object can be obtained, and the direction angle of the target object relative to the target vehicle can be determined based on the current motion direction and the operating parameters of the target vehicle. The target cluster is determined from the preset cluster set based on the cluster parameters and direction angle of each preset cluster in the preset cluster set stored in the target vehicle, and the cluster parameters of the target cluster in the target vehicle are updated according to the current motion parameters, thereby solving the technical problem in the related technology that the target cluster associated with the target object cannot be accurately determined, resulting in the inability to accurately update the cluster parameters, and achieving the technical effect of associating the target object to the correct cluster to improve the accuracy of target recognition.

[0057] In order to accurately determine the motion parameters of the target object, in the method for processing data information in a vehicle provided in Example 1 of the present application, before obtaining the current motion parameters of the target object, it also includes: constructing a vehicle coordinate system with the target vehicle as the center, the motion direction of the target vehicle as the first direction, and the left direction or the right direction of the target vehicle as the second direction; based on the vehicle coordinate system, using a radar sensor deployed in the target vehicle to collect point cloud data of the target object, wherein the point cloud data includes: position data, speed data; based on the point cloud data, determining the current position and current speed of the target object, and based on the position data and the speed data, determining the current motion direction of the target object.

[0058] In an embodiment of the present invention, the vehicle body coordinate system (i.e., the vehicle coordinate system) can be used as the millimeter wave radar detection target motion coordinate system, that is, with the vehicle as the center, the front of the vehicle as the first direction +x, and the left or right direction of the vehicle as the second direction +y. When the target object is tracked normally, the radar sensor deployed in the target vehicle can be used to collect the point cloud data of the target object (including: the position data and speed data of the target object), wherein the position data includes: the motion coordinates (i.e., the current position) determined based on the vehicle coordinate system, and the speed data includes: the current speed determined based on the vehicle coordinate system, and the current motion direction of the target object can be determined based on the position data and the speed data.

[0059] Exemplarily, the moving direction of the target object can be determined by calculating a vector between consecutive position points. The direction of the vector can be obtained by calculating the azimuth between two points.

[0060] In another exemplary embodiment, the motion parameters of the target object can be expressed as: Obj1 (Ox1, Oy1, Ov1), where Ox1 and Oy1 represent the motion coordinates in the first direction x and the second direction y, and Ov1 represents the radial velocity. Moreover, after tracking the target object, the velocity components in the x direction (i.e., the first direction) and the y direction (i.e., the second direction) can be calculated, so the motion parameters of the target object can be expressed as: obj1 (x1, y1, Vx1, Vy1, head1).

[0061] Figure 2 is a schematic diagram of an optional vehicle coordinate system according to an embodiment of the present invention, such as Figure 2As shown, a vehicle coordinate system is established with the center point o of the vehicle body ABCD as the center, the front of the vehicle body as the +x direction, and the left side of the vehicle body as the +y direction, so as to determine the motion parameter coordinates and speed information of the tracked target object on the basis of the vehicle coordinate system, namely Obj1 (Ox1, Oy1, Ov1), and the clusters formed by the point cloud data detected during the tracking process, namely Cl u1 (Cx1, Cy1, Cv1).

[0062] In an optional embodiment, the current motion parameter also includes: current speed, the current speed includes: first direction speed and second direction speed, and the operating parameter includes at least: yaw rate. In order to improve the accuracy of calculating the direction angle of the target object relative to the target vehicle, in the method for processing data information in the vehicle provided in the first embodiment of the present application, the first rotation direction speed and the second rotation direction speed are calculated based on the first direction speed, the second direction speed and the yaw rate; the direction angle of the target object relative to the target vehicle is calculated based on the first rotation direction speed and the second rotation direction speed.

[0063] In an embodiment of the present invention, the current motion parameters of the target object also include: the current speed Ov1, which is the radial speed of the target object relative to the radar line. The speed components in the x and y directions, i.e., the first direction speed Vx1 and the second direction speed Vy1, can be calculated based on the radial speed.

[0064] In the embodiment of the present invention, the attitude of the target relative to the vehicle (i.e., the direction angle of the target object relative to the target vehicle) can be obtained according to the current moving direction head1 of the target object and the vehicle speed speed and the yaw rate yawrate of the vehicle (the vehicle speed speed and the yaw rate yawrate are included in the operating parameters of the vehicle and can be obtained according to the sensors on the vehicle). Specifically, the speed corresponding to the rotation of the target (i.e., the first direction speed Vx1 and the second direction speed Vy1) can be obtained according to yawrate to obtain the first rotation direction speed Vx1 ′ And the second rotation direction speed Vy1 ′ , the calculation formula is as follows:

[0065] Vx1 ′ =Vx1*cos(yawrate)-Vy1*sin(yawrate);

[0066] V Y ′ =Vx1*sin(yawrate)+Vy1*cos(yawrate);

[0067] Then, calculate the direction angle headAngle of the target object relative to the vehicle. The calculation formula is as follows:

[0068] headAngle = atan2(Vy1 ′ , Vx1′);

[0069] For example, in the related art, the motion parameter difference between the target object and each cluster is directly calculated based on the collected motion parameters of the target object, such as:

[0070] Δx = |Ox1 - Cx1| < Xthr;

[0071] Δy = |Oy1 - Cy1| < Ythr;

[0072] Δv = |Ov1 - Cv1| < Vthr;

[0073] Where Ox1 is the position of the target object in the x - direction, Oy1 is the position of the target object in the y - direction, Ov1 is the radial velocity of the target object, Cx1 is the position of the cluster in the x - direction, Cy1 is the position of the cluster in the y - direction, Cv1 is the radial velocity of the cluster, Xthr, Ythr, and Vthr are the set thresholds respectively, and Δx, Δy, and Δv are the motion parameter differences between the target object and the cluster respectively.

[0074] Therefore, in the related art, in order to associate the target object to the correct cluster, appropriate thresholds need to be set. If Xthr, Ythr, and Vthr are set unreasonably, it is easy to出现 the situation of failure to associate or incorrect association. For example, the target of a car is rectangular, with the characteristics of a long side and a short side. According to the running situation of the car, generally, the longitudinal long - side threshold Xthr is set to 0.5 - 1 car length, that is, 2 - 4m, and the transverse short - side threshold Ythr is set to 0.5 - 1 car width, that is, 1 - 2m. Therefore, when Xthr > Ythr, it is more suitable for the straight - running situation of the car target. When the car target crosses, the long side and the short side are reversed. If the Xthr > Ythr threshold is still used to search for the cluster, it is very easy to出现 the situation that when the car crosses, it fails to associate with the cluster in the horizontal front (Δy > Ythr), or is associated with the wrong longitudinal cluster (Δx < Xthr). When the car target runs obliquely, the problem of failure to associate or incorrect association will also occur, and the Xthr, Ythr, and Vthr thresholds need to be dynamically adjusted according to the motion posture of the target object. However, in actual operation, multiple frames are required to obtain the motion postures such as straight - running, crossing, and oblique - running of the target object, and then dynamically adjusting the thresholds according to the motion posture has a lag.

[0075] Figure 3 is a schematic diagram of an optional target object in different motion postures, such as Figure 3As shown, based on the vehicle coordinate system with the center point o of the vehicle body ABCD as the center, the front of the vehicle body as the +x direction, and the left side of the vehicle body as the +y direction, the motion parameter coordinates of the target object with different motion postures (such as straight, crossing, and oblique crossing) are determined (such as: the motion parameter coordinates when straight is Obj1 (x1, y1); the motion parameter coordinates when crossing is Obj2 (x2, y2); the motion parameter coordinates when crossing obliquely are Obj3 (x3, y3)). When associating corresponding clusters of target objects with different motion postures (for example, Obj1 (x1, y1) needs to be associated with cluster Cl u1; Obj2 (x2, y2) needs to be associated with cluster Cl u2; Obj3 (x3, y3) needs to be associated with cluster Cl u3), if a fixed threshold is always used, it is easy to have the problem of not being associated or being associated with the wrong cluster. If the threshold is dynamically adjusted according to the motion posture, it has hysteresis and cannot identify and track the target object in real time.

[0076] Based on this, in an embodiment of the present invention, by converting the movement posture of the target object relative to the ground (straight, crossing, diagonally, etc.) into the movement posture relative to the target vehicle, it is possible to avoid the need to dynamically adjust the threshold according to the movement posture due to the change of the movement posture of the target object, otherwise it is easy to fail to associate with the cluster or associate with the wrong cluster.

[0077] Figure 4 is a schematic diagram of an optional method of converting a motion posture of a target object into a motion posture relative to a target vehicle according to an embodiment of the present invention, such as Figure 4 As shown, based on the vehicle coordinate system with the center point o of the vehicle body ABCD as the center, the front of the vehicle body as the +x direction, and the left side of the vehicle body as the +y direction, the head1 in the determined target object's running parameters (such as Obj1(x1, y1, head1)) is the target object's moving direction relative to the ground. Since the position and speed parameters of the target object relative to the vehicle are constantly changing when the target object moves, but the moving direction heading relative to the ground changes slowly, therefore, by converting the heading ing of each frame into the moving posture relative to the vehicle (i.e., converting head1 into the posture head1' relative to the vehicle), the target object can be more accurately associated with the correct cluster, for example, the correct cluster can be selected from clusters Clu1, Clu2, Clu3, Clu4, Clu5, and Clu6.

[0078] In order to improve the efficiency of determining the target cluster, all clusters can be screened in advance. In the method for processing data information in a vehicle provided in Example 1 of the present application, before determining the target cluster from the preset cluster set based on the cluster parameters and direction angles of each preset cluster in the preset cluster set stored in the target vehicle, it also includes: determining the associated area based on the current motion direction; and screening the preset clusters located in the associated area from all clusters stored in the target vehicle based on the position parameters included in the cluster parameters to obtain the preset cluster set.

[0079] In the embodiment of the present invention, the associated area of ​​the target object can be determined in the current moving direction of the target object (for example, the range constructed with the direction indicated by the current moving direction as the center line and a certain distance from the target object (which can be set according to actual conditions) is the associated area, for example, Figure 4 The region indicated by the solid line frame including clusters Cl u1 and Cl u2 as shown in the figure is used to preliminarily screen the clusters in the associated region as candidate clusters to be associated with the target object (i.e., preset clusters, for example, Figure 4 The clusters C1 u1, C1 u2) shown in the figure are specifically: according to the position parameters included in the cluster parameters, the preset clusters located in the associated area can be screened from all the clusters stored in the target vehicle to obtain a preset cluster set, so that the correct cluster associated with the target object can be screened more efficiently.

[0080] In order to improve the accuracy of determining the target cluster, in the method for processing data information in a vehicle provided in Example 1 of the present application, a preset cluster set is traversed to calculate the angle between the line connecting the current cluster and the target object; based on the line angle and the direction angle, a parameter difference between the cluster parameters of the current cluster and the current motion parameters is calculated, wherein the parameter difference includes: a first direction difference, a second direction difference, and a speed difference; when the first direction difference is less than a first preset position threshold, the second direction difference is less than a second preset position threshold, and the speed difference is less than a preset speed threshold, the current cluster is added to the initial cluster set; based on the parameter difference, a preset distance of each cluster in the initial cluster set is calculated; and the cluster indicated by the minimum preset distance is determined as the target cluster.

[0081] In the embodiment of the present invention, each cluster in the preset cluster set can be traversed, and the angle OCAngle between the selected current cluster and the target object is calculated. Then, according to the angle OCAngle and the direction angle headAngle, the vehicle coordinate system is rotated to the direction of the target object relative to the vehicle, and then the running parameter difference between the cluster and the target object in the coordinate system is calculated (i.e., the parameter difference, including: the first direction difference Δx′, the second direction difference Δy′, and the speed difference Δv).

[0082] In an embodiment of the present invention, if the first direction difference is less than the first preset position threshold Xthr, the second direction difference is less than the second preset position threshold Ythr, and the speed difference is less than the preset speed threshold Vthr, that is, Δx′<Xthr, Δy′<Ythr, Δv<Vthr, then the current cluster can be added to the initial cluster set. If the number of clusters in the initial cluster set is greater than 1, then according to the selected preset distance function (such as the Euclidean distance function or the Mahalanobis distance function), based on these parameter differences, the preset distance of each cluster in the initial cluster set can be calculated. After that, the cluster indicated by the minimum preset distance can be determined as the target cluster. In this way, regardless of the current motion posture of the target object, the correct cluster that the target object needs to be associated with can be accurately and quickly determined according to the currently set thresholds (i.e., the first preset position threshold Xthr, the second preset position threshold Ythr, and the preset speed threshold Vthr).

[0083] In an embodiment of the present invention, if there are more than one cluster that meets the threshold conditions, distance function formulas such as the Euclidean distance function and the Mahalanobis distance function can be used to screen out the cluster with the closest preset distance such as the Euclidean distance or the Mahalanobis distance as the final target cluster. For example, to screen out the cluster with the closest Euclidean distance, that is, to find the cluster corresponding to the minimum value of the Euclidean distance Di stR. The Euclidean distance calculation formula is as follows:

[0084]

[0085] It is also possible to screen out the cluster with the closest Mahalanobis distance, that is, to find the cluster corresponding to the minimum value of the Mahalanobis distance D i stM. The Mahalanobis distance calculation formula is as follows:

[0086] Among them, α, β, and γ are pre-set weight coefficients, which can be adjusted according to the actual situation.

[0087] In an optional embodiment, the current motion parameters further include: the current position. To improve the accuracy of calculating the included angle between the line connecting the current cluster and the target object, in the method for processing vehicle data information provided in Embodiment 1 of the present application, calculate the first absolute difference between the first cluster direction position included in the cluster parameters of the current cluster and the first direction position in the current position; calculate the second absolute difference between the second cluster direction position included in the cluster parameters of the current cluster and the second direction position in the current position; based on the first absolute difference and the second absolute difference, calculate the included angle of the line connection.

[0088] In the embodiment of the present invention, the current motion parameters of the target object also include: current positions Ox1 and Oy1. The first absolute difference Δx between the first directional position Ox1 in the current position and the first cluster directional position Cx1 included in the cluster parameters of the current cluster can be calculated, and the first absolute difference Δy between the second directional position Oy1 in the current position and the second cluster directional position Cy1 included in the cluster parameters of the current cluster can be calculated, that is, the first absolute difference Δx and the second directional position Oy1 can be calculated using the following formulas: Δx = |Ox1-Cx1|, Δy = |Oy1-Cy1|.

[0089] Then, the angle OCAngle between the cluster and the target object is calculated according to the following formula:

[0090] OCAngle = atan2(Δy, Δx);

[0091] In order to improve the accuracy of calculating the parameter difference between the cluster parameters of the current cluster and the current motion parameters, in the method for processing data information in a vehicle provided in Example 1 of the present application, the deflection angle of the current cluster is calculated based on the connecting line angle and the direction angle; the distance value between the current cluster and the target object is calculated based on the first absolute difference and the second absolute difference; the first direction difference and the second direction difference are calculated based on the distance value and the deflection angle; the current radial speed is determined based on the current speed included in the current motion parameters, and the speed difference is calculated based on the cluster speed included in the cluster parameters and the current radial speed; the first direction difference, the second direction difference and the speed difference are characterized as parameter differences.

[0092] In the embodiment of the present invention, the deflection angle deltaAngle of the current cluster in the rotated coordinate system can be calculated by the following formula: deltaAngle=OCAngle-headAngle. Then, according to the first absolute difference Δx 2 and the second absolute difference Δy 2 , calculate the distance value DistR between the current cluster and the target object, that is, After that, the first direction difference Δx′ on the long side and the second direction difference Δy′ on the short side between the current cluster and the target object are calculated as follows:

[0093] Δx ′ =DistR*cos(deltaAngle);

[0094] Δy ′ =DistR*sin(deltaAngle);

[0095] In this embodiment, since the radar detection point cloud can only detect the radial velocity, the cluster only has the radial velocity. Therefore, it is necessary to first calculate the current radial velocity according to the current velocity included in the current motion parameters of the target object (that is, re-project the velocity components in the x and y directions onto the line connecting the target object and the radar to obtain the radial velocity). Then, according to the cluster velocity included in the cluster parameters and the current radial velocity, calculate the velocity difference Δv. These first direction difference, second direction difference, and velocity difference are the parameter differences between the target object and the current cluster.

[0096] Figure 5 FIG. is a schematic diagram of an optional method for associating a cluster with a target object using the nearest neighbor algorithm in the related art. Figure 6 FIG. is a schematic diagram of an optional method for associating a cluster according to the motion attitude of the target object relative to the vehicle according to an embodiment of the present invention. Figure 5 and Figure 6 Intuitively compares the effects of ordinary association using the nearest neighbor algorithm and the attitude association method in this embodiment. That is, in Figure 5 , targets 24, 10, 5, and 3 are successfully associated with the cluster, but for target 15 due to diagonal crossing, the ordinary association method using the nearest neighbor algorithm cannot correctly associate with the right cross point cluster, resulting in the target about to lose tracking. While in Figure 6 , targets 24, 20, 0, and 2 are successfully associated with the cluster, and target 28 (the same target as target 15 in Figure 5 ) can be normally tracked after using the attitude association method, demonstrating the accuracy of the attitude association method in this embodiment when dealing with complex moving targets.

[0097] Figure 7 FIG. is a schematic diagram of an optional process for a target object to associate a cluster according to the attitude according to an embodiment of the present invention. As shown in Figure 7 , first obtain the motion parameters of target Obj, and obtain the association thresholds Xthr, Ythr, and Vthr. Then, calculate the motion attitude of the target. Next, by traversing the clusters, obtain the cluster parameters, and calculate the differences Δx, Δy, and Δv between the motion parameters of the target and the cluster parameters. If Δx < Xthr && Δy < Ythr && Δv < Vthr, then calculate the distance value between the target and the cluster, and determine whether this distance value is less than the previously obtained minimum distance value. If this distance value is less than the minimum distance value, then update this distance value to the minimum distance value, and record the cluster information. Determine whether it is the last cluster. If not, continue to traverse the clusters. If so, associate the cluster indicated by the minimum distance value with the target. After successful association, determine whether it is the last target. If so, directly end. Otherwise, continue to traverse the targets and perform cluster association for the next target.

[0098] In Figure 7In [the above], if Δx < Xthr && Δy < Ythr && Δv < Vthr is not satisfied, it indicates that the current cluster is not the cluster that the target needs to be associated with, and continue to traverse the clusters; if the distance value is not less than the minimum distance value, it indicates that the current cluster is not the cluster that the target needs to be associated with, and continue to traverse the clusters.

[0099] In the embodiments of the present invention, by converting the motion posture of the target object relative to the ground into the motion posture relative to the vehicle, and through operation steps such as direction angle rotation, the target object can be correctly associated with the corresponding cluster, thereby improving the accuracy of target motion parameter recognition, achieving the purpose of real-time tracking of the target, and ensuring the safety of intelligent driving.

[0100] The following is a detailed description in combination with another embodiment.

[0101] Embodiment 2

[0102] A processing device for data information in a vehicle provided in this embodiment includes a plurality of implementation units, and each implementation unit corresponds to each implementation step in the first embodiment above.

[0103] Figure 8 is a schematic diagram of an optional processing device for data information in a vehicle according to an embodiment of the present invention, as Figure 8 shown, the processing device may include: an acquisition unit 80, a first determination unit 81, a second determination unit 82, and an update unit 83.

[0104] Among them, the acquisition unit 80 is used to acquire the current motion parameters of the target object, where the current motion parameters at least include: the current motion direction, and the target object refers to an object that moves within the preset range of the target vehicle during driving;

[0105] The first determination unit 81 is used to determine the direction angle of the target object relative to the target vehicle based on the current motion direction and the running parameters of the target vehicle;

[0106] The second determination unit 82 is used to determine the target cluster from the preset cluster set based on the cluster parameters and direction angle of each preset cluster in the preset cluster set stored in the target vehicle, where each preset cluster is used to indicate an object, and the cluster parameters are used to record the motion parameters of each object;

[0107] The update unit 83 is used to update the cluster parameters of the target cluster in the target vehicle according to the current motion parameters.

[0108] The above-mentioned processing device can obtain the current motion parameters of the target object through the acquisition unit 80, determine the direction angle of the target object relative to the target vehicle based on the current motion direction and the operating parameters of the target vehicle through the first determination unit 81, determine the target cluster from the preset cluster set based on the cluster parameters and direction angle of each preset cluster in the preset cluster set stored in the target vehicle through the second determination unit 82, and update the cluster parameters of the target cluster in the target vehicle according to the current motion parameters through the updating unit 83, thereby solving the technical problem in the related art that the target cluster associated with the target object cannot be accurately determined, resulting in the inability to accurately update the cluster parameters, and achieving the technical effect of associating the target object to the correct cluster to improve the accuracy of target recognition.

[0109] Optionally, the processing device also includes: a first construction module, used to construct a vehicle coordinate system with the target vehicle as the center, the movement direction of the target vehicle as the first direction, and the left direction or the right direction of the target vehicle as the second direction before acquiring the current motion parameters of the target object; a first acquisition module, used to collect point cloud data of the target object based on the vehicle coordinate system using a radar sensor deployed in the target vehicle, wherein the point cloud data includes: position data, speed data; a first determination module, used to determine the current position and current speed of the target object based on the point cloud data, and determine the current motion direction of the target object based on the position data and the speed data.

[0110] Optionally, the current motion parameters also include: current speed, the current speed includes: first direction speed and second direction speed, the operating parameters include at least: yaw angular rate, and the first determination unit includes: a first calculation module, used to calculate the first rotation direction speed and the second rotation direction speed based on the first direction speed, the second direction speed and the yaw angular rate; a second calculation module, used to calculate the direction angle of the target object relative to the target vehicle based on the first rotation direction speed and the second rotation direction speed.

[0111] Optionally, the processing device also includes: a second determination module, used to determine the associated area based on the current movement direction before determining the target cluster from the preset cluster set based on the cluster parameters and direction angles of each preset cluster in the preset cluster set stored in the target vehicle; a first screening module, used to screen the preset clusters located in the associated area from all the clusters stored in the target vehicle based on the position parameters contained in the cluster parameters to obtain the preset cluster set.

[0112] Optionally, the second determination unit includes: a third calculation module, which is used to traverse the preset cluster set and calculate the angle between the line connecting the current cluster and the target object; a fourth calculation module, which is used to calculate the parameter difference between the cluster parameters of the current cluster and the current motion parameters based on the line angle and the direction angle, wherein the parameter difference includes: a first direction difference, a second direction difference, and a speed difference; a first adding module, which is used to add the current cluster to the initial cluster set when the first direction difference is less than a first preset position threshold, the second direction difference is less than a second preset position threshold, and the speed difference is less than a preset speed threshold; a fifth calculation module, which is used to calculate the preset distance of each cluster in the initial cluster set based on the parameter difference; and a third determination module, which is used to determine the cluster indicated by the minimum preset distance as the target cluster.

[0113] Optionally, the current motion parameters also include: the current position, and the third calculation module includes: a first calculation submodule, used to calculate the first absolute difference between the first cluster direction position included in the cluster parameters of the current cluster and the first direction position in the current position; a second calculation submodule, used to calculate the second absolute difference between the second cluster direction position included in the cluster parameters of the current cluster and the second direction position in the current position; and a third calculation submodule, used to calculate the connecting line angle based on the first absolute difference and the second absolute difference.

[0114] Optionally, the fourth calculation module includes: a fourth calculation submodule, used to calculate the deflection angle of the current cluster based on the connecting line angle and the direction angle; a fifth calculation submodule, used to calculate the distance value between the current cluster and the target object based on the first absolute difference and the second absolute difference; a sixth calculation submodule, used to calculate the first direction difference and the second direction difference based on the distance value and the deflection angle; a first determination submodule, used to determine the current radial velocity based on the current velocity included in the current motion parameters, and calculate the velocity difference based on the cluster velocity included in the cluster parameters and the current radial velocity; a first characterization submodule, used to characterize the first direction difference, the second direction difference and the velocity difference as parameter differences.

[0115] The above-mentioned processing device may also include a processor and a memory. The above-mentioned acquisition unit 80, first determination unit 81, second determination unit 82, update unit 83, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

[0116] The processor includes a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be set, and the cluster parameters of the target cluster in the target vehicle are updated according to the current motion parameters by adjusting the kernel parameters.

[0117] The above-mentioned memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (fl ash RAM), and the memory includes at least one storage chip.

[0118] According to another aspect of an embodiment of the present invention, a computer program product is also provided, including a non-volatile computer-readable storage medium, the non-volatile computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, implementing any of the above-mentioned methods for processing data information in a vehicle.

[0119] When the computer program product is executed on a data processing device, it is suitable for executing an initialization program having the following method steps: obtaining current motion parameters of the target object, determining the direction angle of the target object relative to the target vehicle based on the current motion direction and the operating parameters of the target vehicle, determining the target cluster from the preset cluster set based on the cluster parameters and direction angle of each preset cluster in the preset cluster set stored in the target vehicle, and updating the cluster parameters of the target cluster in the target vehicle according to the current motion parameters.

[0120] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement the above-mentioned method for processing data information in a vehicle.

[0121] Fig. 9 1 is a hardware structure block diagram of an electronic device (or mobile device) for a method for processing data information in a vehicle according to an embodiment of the present invention. Fig. 9 As shown, the electronic device may include one or more processors (e.g., Fig. 9 The processor 902a, processor 902b, ..., processor 902n, etc., which may include but are not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 904 for storing data. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a keyboard, a power supply and / or a camera. It can be understood by those skilled in the art that Fig. 9 The structure shown is only for illustration and does not limit the structure of the above electronic device. Fig. 9 More or fewer components as shown, or with Fig. 9 Different configurations are shown.

[0122] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0123] The embodiments or examples of the present disclosure are not exhaustive, but are only illustrative of some embodiments or examples, and are not intended to be specific limitations on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment or example can be implemented as an independent example, and the steps can be combined arbitrarily. For example, the scheme after removing some steps in a certain embodiment or example can also be implemented as an independent example, and the order of the steps in a certain embodiment or example can be arbitrarily exchanged. In addition, the optional methods or optional examples in a certain embodiment or example can be combined arbitrarily; in addition, the various embodiments or examples can be combined arbitrarily, for example, some or all steps of different embodiments or examples can be combined arbitrarily, and a certain embodiment or example can be combined arbitrarily with the optional methods or optional examples of other embodiments or examples.

[0124] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0125] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0126] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0127] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0128] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0129] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for processing data information in a vehicle, characterized in that: include: Acquiring current motion parameters of the target object, wherein the current motion parameters at least include: a current motion direction, and the target object refers to an object moving within a preset range of the driving target vehicle; Determining a direction angle of the target object relative to the target vehicle based on the current motion direction and the operating parameters of the target vehicle; Determine a target cluster from the preset cluster set based on the cluster parameters of each preset cluster in the preset cluster set stored in the target vehicle and the direction angle, wherein each preset cluster is used to indicate an object, and the cluster parameters are used to record motion parameters of each object; The cluster parameters of the target cluster in the target vehicle are updated according to the current motion parameters.

2. The processing method according to claim 1, characterized in that: Before obtaining the current motion parameters of the target object, it also includes: Constructing a vehicle coordinate system with the target vehicle as the center, the moving direction of the target vehicle as the first direction, and the left direction or the right direction of the target vehicle as the second direction; Based on the vehicle coordinate system, a radar sensor deployed in the target vehicle is used to collect point cloud data of the target object, wherein the point cloud data includes: position data and speed data; Based on the point cloud data, a current position and a current speed of the target object are determined, and based on the position data and the speed data, the current movement direction of the target object is determined.

3. The processing method according to claim 1, characterized in that: The current motion parameters also include: a current speed, the current speed includes: a first direction speed and a second direction speed, the operating parameters include at least: a yaw rate, and based on the current motion direction and the operating parameters of the target vehicle, the step of determining the direction angle of the target object relative to the target vehicle includes: Calculating a first rotational direction speed and a second rotational direction speed based on the first direction speed, the second direction speed and the yaw rate; The direction angle of the target object relative to the target vehicle is calculated based on the first rotation direction speed and the second rotation direction speed.

4. The processing method according to claim 1, characterized in that: Before determining a target cluster from the preset cluster set based on the cluster parameters of each preset cluster in the preset cluster set stored in the target vehicle and the direction angle, the method further includes: Determining an associated area based on the current motion direction; Based on the location parameters included in the cluster parameters, the preset cluster located in the associated area is screened from all clusters stored in the target vehicle to obtain the preset cluster set.

5. The processing method according to claim 1, characterized in that: The step of determining a target cluster from the preset cluster set based on the cluster parameters of each preset cluster in the preset cluster set stored in the target vehicle and the direction angle comprises: Traversing the preset cluster set, and calculating the angle between the current cluster and the target object; Based on the line angle and the direction angle, calculating a parameter difference between the cluster parameter of the current cluster and the current motion parameter, wherein the parameter difference includes: a first direction difference, a second direction difference, and a speed difference; When the first direction difference is less than a first preset position threshold, the second direction difference is less than a second preset position threshold, and the speed difference is less than a preset speed threshold, adding the current cluster to the initial cluster set; Based on the parameter difference, calculating a preset distance of each cluster in the initial cluster set; The cluster indicated by the minimum preset distance is determined as the target cluster.

6. The processing method according to claim 5, characterized in that: The current motion parameters also include: the current position, and the step of calculating the angle between the current cluster and the target object includes: Calculating a first absolute difference between a first cluster direction position included in the cluster parameters of the current cluster and a first direction position in the current position; Calculating a second absolute difference between a second cluster direction position included in the cluster parameters of the current cluster and a second direction position in the current position; The connecting line angle is calculated based on the first absolute difference and the second absolute difference.

7. The processing method according to claim 6, characterized in that: The step of calculating the parameter difference between the cluster parameter of the current cluster and the current motion parameter based on the connection angle and the direction angle comprises: Calculating the deflection angle of the current cluster based on the line angle and the direction angle; Calculating a distance value between the current cluster and the target object based on the first absolute difference and the second absolute difference; Calculating the first direction difference and the second direction difference based on the distance value and the deflection angle; Determine a current radial velocity based on a current velocity included in the current motion parameter, and calculate the velocity difference based on a cluster velocity included in the cluster parameter and the current radial velocity; The first direction difference, the second direction difference, and the speed difference are characterized as the parameter differences.

8. A data information processing device in a vehicle, characterized in that: include: An acquisition unit, configured to acquire current motion parameters of a target object, wherein the current motion parameters at least include: a current motion direction, and the target object refers to an object moving within a preset range of a driving target vehicle; A first determining unit, configured to determine a direction angle of the target object relative to the target vehicle based on the current moving direction and an operating parameter of the target vehicle; a second determining unit, configured to determine a target cluster from the preset cluster set based on cluster parameters of each preset cluster in the preset cluster set stored in the target vehicle and the direction angle, wherein each preset cluster is used to indicate an object, and the cluster parameters are used to record motion parameters of each object; An updating unit is used to update the cluster parameters of the target cluster in the target vehicle according to the current motion parameters.

9. The device according to claim 8, characterized in that The current motion parameters also include: current speed, the current speed includes: first direction speed and second direction speed, the operation parameters at least include: yaw rate, the first determination unit includes: A first calculation module, configured to calculate a first rotation direction speed and a second rotation direction speed based on the first direction speed, the second direction speed and the yaw angular rate; The second calculation module is used to calculate the direction angle of the target object relative to the target vehicle based on the first rotation direction speed and the second rotation direction speed.

10. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for processing data information in a vehicle as described in any one of claims 1 to 7.

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