A method, device, medium and equipment for positioning a dummy based on seat conditions

Abstract

The present application provides a method, device, medium and equipment for positioning a dummy based on seat conditions. The target seat is divided into multiple reclining angles, and the key point coordinates of the man-machine dummy model, the crash dummy and the target driver at multiple reclining angles are measured. Taking the key point coordinates of the target driver as the standard, the applicability of the man-machine dummy model and the crash dummy is evaluated, and the target man-machine dummy model and the target crash dummy with better applicability are selected. During the experiment, the target key point coordinates of the target driver corresponding to the key point coordinates of the target man-machine dummy model are calculated and used as the key point coordinates of the target crash dummy, so as to obtain the positioning information of the target crash dummy under the large-angle seat condition.

Description

Technical Field

[0001] The present application relates to the technical field, and particularly to a method, device, medium and equipment for positioning a dummy based on seat conditions. Background Art

[0002] Compared with traditional upright seats, large-angle seats are more comfortable, but the impact on the safety of occupants has not been fully verified. In vehicle crash tests, human-machine dummy models (Human-Point Machine, abbreviated as HPM), crash dummies, etc. are usually used to simulate real drivers to evaluate the vehicle crash safety performance. The reliability of the data obtained by crash dummies in crash tests is directly related to whether the postures they are placed in can correctly simulate the standard postures of drivers in actual driving environments. Existing HPMs and crash dummies are all oriented towards verifying traditional upright seats, and their performance under large-angle seat conditions is unknown. Therefore, a method for positioning a human model under large-angle seat conditions is needed. Summary of the Invention

[0003] To solve the above technical problems, the present application is proposed. Embodiments of the present application provide a method, device, medium and equipment for positioning a dummy based on seat conditions.

[0004] According to one aspect of the present application, a method for positioning a dummy based on seat conditions is provided, including: establishing a seat coordinate system, and dividing a target seat into multiple reclining angles based on the seat coordinate system; measuring the first key point coordinates of a human-machine dummy model at the multiple reclining angles; measuring the second key point coordinates of a crash dummy at the multiple reclining angles; measuring the third key point coordinates of a target driver at the multiple reclining angles; taking the third key point coordinates of the target driver at the multiple reclining angles as a standard, and evaluating the applicability of the human-machine dummy model and the crash dummy based on the first key point coordinates of the human-machine dummy model at the multiple reclining angles and the second key point coordinates of the crash dummy at the multiple reclining angles; selecting the human-machine dummy model and the crash dummy whose applicability meets preset conditions as a target human-machine dummy model and a target crash dummy respectively; calculating the target key point coordinates of the target driver corresponding to the key point coordinates of the target human-machine dummy model based on the positioning conversion relationship between the target human-machine dummy model and the target driver, and taking the target key point coordinates as the key point coordinates of the target crash dummy.

[0005] In one embodiment, evaluating the applicability of the anthropomorphic dummy model and the crash dummy based on the third key point coordinates of the target driver at the multiple reclining angles, the first key point coordinates of the anthropomorphic dummy model at the multiple reclining angles, and the second key point coordinates of the crash dummy at the multiple reclining angles includes: based on the first key point coordinates of the anthropomorphic dummy model at the multiple reclining angles, fitting to obtain a first vector of the first key point coordinates of the anthropomorphic dummy model varying with the reclining angle; based on the second key point coordinates of the crash dummy at the multiple reclining angles, fitting to obtain a second vector of the second key point coordinates of the crash dummy varying with the reclining angle; based on the third key point coordinates of the target driver at the multiple reclining angles, fitting to obtain a third vector of the third key point coordinates of the target driver varying with the reclining angle; respectively calculating a first included angle between the first vector and the third vector, and a second included angle between the second vector and the third vector; and evaluating the applicability of the anthropomorphic dummy model and the crash dummy based on the first included angle and the second included angle.

[0006] In one embodiment, calculating the target key point coordinates of the target driver corresponding to the key point coordinates of the target anthropomorphic dummy model based on the positioning conversion relationship between the target anthropomorphic dummy model and the target driver, and using the target key point coordinates as the key point coordinates of the target crash dummy includes: during the experiment, measuring the key point coordinates of the target anthropomorphic dummy model; inputting the key point coordinates of the target anthropomorphic dummy model into the trained neural network model to obtain the target key point coordinates of the target driver, and using the target key point coordinates as the key point coordinates of the target crash dummy.

[0007] In one embodiment, dividing the target seat into multiple reclining angles based on the seat coordinate system includes: measuring the maximum tilt angle of the backrest of the target seat from the upright state to the maximum backward tilt state; calculating the number of reclining angles of the target seat and the magnitude of each reclining angle based on the set adjustment angle and the maximum tilt angle.

[0008] In one embodiment, measuring the first key point coordinates of the anthropomorphic dummy model at the multiple reclining angles includes: adjusting the target seat to the current reclining angle and installing the anthropomorphic dummy model on the target seat; measuring the left key point coordinates and the right key point coordinates of the anthropomorphic dummy model at the current reclining angle; if the first error between the left key point coordinates and the right key point coordinates of the anthropomorphic dummy model is less than the first preset value, calculating the first key point coordinates of the anthropomorphic dummy model at the current reclining angle based on the left key point coordinates and the right key point coordinates of the anthropomorphic dummy model.

[0009] In one embodiment, the measurement of the second key point coordinates of the measurement crash dummy at the multiple reclining angles includes: adjusting the target seat to the current reclining angle and mounting the crash dummy on the target seat; measuring the left key point coordinates and the right key point coordinates of the crash dummy at the current reclining angle; if the second error between the left key point coordinates and the right key point coordinates of the crash dummy is less than a second preset value, calculating the second key point coordinates of the crash dummy at the current reclining angle based on the left key point coordinates and the right key point coordinates of the crash dummy.

[0010] In one embodiment, the measurement of the third key point coordinates of the target driver at the multiple reclining angles includes: adjusting the target seat to the current reclining angle and adjusting the sitting posture of the target driver on the target seat; measuring the left key point coordinates and the right key point coordinates of the target driver at the current reclining angle; if the third error between the left key point coordinates and the right key point coordinates of the target driver is less than a third preset value, calculating the third key point coordinates of the target driver at the current reclining angle based on the left key point coordinates and the right key point coordinates of the target driver.

[0011] According to another aspect of the present application, there is provided a dummy positioning device based on seat conditions, including: a reclining angle division module for establishing a seat coordinate system and dividing a target seat into multiple reclining angles based on the seat coordinate system; a first key point measurement module for measuring the first key point coordinates of a human-machine dummy model at the multiple reclining angles; a second key point measurement module for measuring the second key point coordinates of a crash dummy at the multiple reclining angles; a third key point measurement module for measuring the third key point coordinates of a target driver at the multiple reclining angles; an applicability evaluation module for evaluating the applicability of the human-machine dummy model and the crash dummy based on the first key point coordinates of the human-machine dummy model at the multiple reclining angles and the second key point coordinates of the crash dummy at the multiple reclining angles with the third key point coordinates of the target driver at the multiple reclining angles as a standard; a target model selection module for selecting the human-machine dummy model and the crash dummy whose applicability meets preset conditions as a target human-machine dummy model and a target crash dummy respectively; and a crash dummy positioning module for calculating the target key point coordinates of the target driver corresponding to the key point coordinates of the target human-machine dummy model based on the positioning conversion relationship between the target human-machine dummy model and the target driver, and using the target key point coordinates as the key point coordinates of the target crash dummy.

[0012] According to another aspect of the present application, there is provided a computer-readable storage medium storing a computer program for executing any one of the above methods.

[0013] According to another aspect of the present application, there is provided an electronic device, including: a processor; a memory for storing executable instructions of the processor; the processor is configured to execute any one of the above methods.

[0014] A method, device, medium and equipment for positioning a dummy based on seat conditions provided by the present application establish a seat coordinate system, divide a target seat into multiple reclining angles based on the seat coordinate system; measure the coordinates of the first key points of a human-machine dummy model at multiple reclining angles; measure the coordinates of the second key points of a crash dummy at multiple reclining angles; measure the coordinates of the third key points of a target driver at multiple reclining angles; taking the coordinates of the third key points of the target driver at multiple reclining angles as a standard, based on the coordinates of the first key points of the human-machine dummy model at multiple reclining angles and the coordinates of the second key points of the crash dummy at multiple reclining angles, evaluate the applicability of the human-machine dummy model and the crash dummy; select the human-machine dummy model and the crash dummy whose applicability meets the preset conditions as the target human-machine dummy model and the target crash dummy respectively; based on the positioning conversion relationship between the target human-machine dummy model and the target driver, calculate the target key point coordinates of the target driver corresponding to the key point coordinates of the target human-machine dummy model, and use the target key point coordinates as the key point coordinates of the target crash dummy; by measuring the key point coordinates of the human-machine dummy model, the crash dummy and the target driver at multiple reclining angles of the seat, and evaluating the applicability of the human-machine dummy model and the crash dummy accordingly, to select a target human-machine dummy model and a target crash dummy with better applicability, during the experiment, convert the key point coordinates of the target human-machine dummy model into the target key point coordinates of the target driver, and use the target key point coordinates as the key point coordinates of the target crash dummy, so as to obtain the positioning information of the target crash dummy under large-angle seat conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other objects, features and advantages of the present application will become more obvious. The drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification, and are used to explain the present application together with the embodiments of the present application, and do not constitute a limitation to the present application. In the drawings, the same reference numerals generally represent the same components or steps.

[0016] Figure 1 It is a schematic flowchart of a method for positioning a dummy based on seat conditions provided by an exemplary embodiment of the present application.

[0017] Figure 2It is a schematic structural diagram of a seat coordinate system provided by an exemplary embodiment of the present application.

[0018] Figure 3 It is a schematic structural diagram of a change vector of a measurement object provided by an exemplary embodiment of the present application.

[0019] Figure 4 It is a schematic structural diagram of a conversion model for the H-point coordinate value of a target driver provided by an exemplary embodiment of the present application.

[0020] Figure 5 It is a schematic structural diagram of the back plate of an HPM provided by an exemplary embodiment of the present application.

[0021] Figure 6 It is a schematic structural diagram of a conversion model for converting an attitude part to a positioning part provided by an exemplary embodiment of the present application.

[0022] Figure 7 It is a schematic structural diagram of a conversion model for converting a positioning part to an attitude part provided by an exemplary embodiment of the present application.

[0023] Figure 8 It is a schematic structural diagram of a dummy positioning device based on seat conditions provided by an exemplary embodiment of the present application.

[0024] Figure 9 It is a structural diagram of an electronic device provided by an exemplary embodiment of the present application. Detailed implementation manners

[0025] Next, exemplary embodiments of the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein.

[0026] Figure 1 It is a schematic flowchart of a dummy positioning method based on seat conditions provided by an exemplary embodiment of the present application. As Figure 1 shown, the dummy positioning method based on seat conditions includes the following steps:

[0027] Step 110: Establish a seat coordinate system, and divide the target seat into multiple recline angles based on the seat coordinate system.

[0028] Specifically, fix the target seat on a flat ground, use a flexible three-coordinate device to measure the coordinate values of any two symmetric points on the surface of the seat cushion and the backrest surface of the target seat, compare whether the coordinate values in the plumb direction of the symmetric points are within the error range. If the error is exceeded, it is necessary to adjust the fixed plane of the target seat or the base of the target seat until the heights of the symmetric points on the surface of the seat cushion and the backrest surface of the target seat are the same in the plumb direction. Remove the outer enclosure of the rotating shaft of the target seat backrest to expose the rotating shaft of the target seat backrest. Punch multiple marking points on the metal structures on the left and right sides of the bottom of the target seat for the establishment of the seat coordinate system and the restoration of the coordinate system after the target seat is moved. When it is defined that the driver and passengers are sitting upright on the target seat, that is, when looking from the backrest of the target seat to the seat cushion of the target seat, the left side of the driver and passengers is recorded as the left side of the target seat, and the right side of the driver and passengers is recorded as the right side of the target seat. Use a flexible three-coordinate to locate the centers of the left and right rotating shafts of the backrest, and select the midpoint of the connection line of the centers as the origin of the seat coordinate system. Starting from the origin, with the horizontal direction from the backrest of the target seat pointing to the seat cushion of the target seat as the positive direction of the X-axis, on the connection line of the centers of the left and right rotating shafts, with the direction from the right side to the left side of the target seat as the positive direction of the Y-axis, perpendicular to the X-axis and the Y-axis, with the direction from the seat cushion to the headrest as the positive direction of the Z-axis. Use a flexible three-coordinate to record and construct the current seat coordinate system, and record the coordinates of the restoration marking points for the restoration of the coordinate system after the target seat is moved. As shown in Figure 2 Figure (a) in, select a fixed point on the backrest of the target seat as a marking point. The position of the headrest rod or a certain point on the backrest of the target seat can be selected. Select a flat area on the backrest as the backrest angle measurement area. According to the installation requirements of the HPMI device, install the HPM device on the target seat. During the installation process, adjust the backrest of the seat to make the torso angle of the HPM device meet the designed angle of the seat upright state. Use a flexible three-coordinate to measure the restoration marking points of the seat coordinate system to ensure that the installation of the HPM does not affect the accuracy of the seat coordinate system. Use a flexible three-coordinate to measure the left and right H points (key points) of the HPM. When the error between the left and right H points is within the allowable range, measure and record the coordinates of the backrest marking point, denoted as the "0-degree position". Calculate the average value of the left and right H points as the H point coordinate value of the HPM I device at the "0-degree position", denoted as the "I-0-H" point (as shown in Figure 2 Figure (b) in). Remove the HPM device. After waiting for a while, use an angle gauge to measure and record the angle value in the backrest angle measurement area, and zero the angle gauge at this position. Adjust the backrest to tilt backward until the reading of the angle gauge is β degrees (as shown in Figure 2 Figure (d) in), use a flexible three-coordinate to measure and record the coordinates of the backrest marking point, denoted as the "β-degree position". Continue to adjust the backrest to tilt backward until the reading of the angle gauge is 2β degrees, use a flexible three-coordinate to measure and record the coordinates of the backrest marking point, denoted as the "2β-degree position", and so on until the backrest is adjusted to the last position, the "α-degree position" (as shown in Figure 2As shown in Figure (c), a total of (α - 0) / β angular positions are obtained.

[0029] Step 120: Measure the coordinates of the first key point of the anthropomorphic dummy model at multiple reclining angles.

[0030] In this application, the anthropomorphic dummy model is installed on the target seat, and the coordinates of the first key point of the anthropomorphic dummy model are measured at multiple reclining angles.

[0031] Step 130: Measure the coordinates of the second key point of the crash dummy at multiple reclining angles.

[0032] In this application, the crash dummy is installed on the target seat, and the coordinates of the second key point of the crash dummy are measured at multiple reclining angles.

[0033] Step 140: Measure the coordinates of the third key point of the target driver at multiple reclining angles.

[0034] In this application, when the target driver is sitting on the target seat, the coordinates of the third key point of the target driver are measured at multiple reclining angles.

[0035] Step 150: Based on the coordinates of the third key point of the target driver at multiple reclining angles, evaluate the applicability of the anthropomorphic dummy model and the crash dummy based on the coordinates of the first key point of the anthropomorphic dummy model at multiple reclining angles and the coordinates of the second key point of the crash dummy at multiple reclining angles.

[0036] In this application, the applicability of the anthropomorphic dummy model and the crash dummy is evaluated based on the coordinates of the third key point of the target driver at multiple reclining angles. Specifically, based on the coordinates of the first key point of the anthropomorphic dummy model at multiple reclining angles, the coordinates of the second key point of the crash dummy at multiple reclining angles, and the coordinates of the third key point of the target driver at multiple reclining angles, the differences between the anthropomorphic dummy model, the crash dummy, and the target driver are calculated to evaluate the applicability of the anthropomorphic dummy model and the crash dummy.

[0037] Step 160: Select the anthropomorphic dummy model and the crash dummy with applicability meeting the preset conditions as the target anthropomorphic dummy model and the target crash dummy, respectively.

[0038] In this application, the anthropomorphic dummy model and the crash dummy with applicability meeting the preset conditions are selected as the target anthropomorphic dummy model and the target crash dummy, respectively, that is, the anthropomorphic dummy model and the crash dummy with the best applicability are selected as the target anthropomorphic dummy model and the target crash dummy, respectively.

[0039] Step 170: Based on the positioning conversion relationship between the target human-machine dummy model and the target driver, calculate the target key point coordinates of the target driver corresponding to the key point coordinates of the target human-machine dummy model, and use the target key point coordinates as the key point coordinates of the target crash dummy.

[0040] In this application, according to the positioning conversion relationship between the target human-machine dummy model and the target driver, calculate the target key point coordinates of the target driver corresponding to the key point coordinates of the target human-machine dummy model, and based on the target key point coordinates, obtain the key point coordinates of the target crash dummy.

[0041] A dummy positioning method based on seat conditions provided by this application includes: establishing a seat coordinate system, and dividing the target seat into multiple reclining angles based on the seat coordinate system; measuring the first key point coordinates of the human-machine dummy model at multiple reclining angles; measuring the second key point coordinates of the crash dummy at multiple reclining angles; measuring the third key point coordinates of the target driver at multiple reclining angles; using the third key point coordinates of the target driver at multiple reclining angles as a standard, and based on the first key point coordinates of the human-machine dummy model at multiple reclining angles and the second key point coordinates of the crash dummy at multiple reclining angles, evaluate the applicability of the human-machine dummy model and the crash dummy; select the human-machine dummy model and the crash dummy with applicability meeting the preset conditions as the target human-machine dummy model and the target crash dummy respectively; based on the positioning conversion relationship between the target human-machine dummy model and the target driver, calculate the target key point coordinates of the target driver corresponding to the key point coordinates of the target human-machine dummy model, and use the target key point coordinates as the key point coordinates of the target crash dummy; by measuring the key point coordinates of the human-machine dummy model, the crash dummy and the target driver at multiple reclining angles of the seat, and evaluating the applicability of the human-machine dummy model and the crash dummy with this, select the target human-machine dummy model and the target crash dummy with better applicability, during the experiment, convert the key point coordinates of the target human-machine dummy model into the target key point coordinates of the target driver, and use the target key point coordinates as the key point coordinates of the target crash dummy, so as to obtain the positioning information of the target crash dummy under the large-angle seat condition.

[0042] In one embodiment, the specific implementation of the above step 150 may be as follows: Based on the first key point coordinates of the human-machine dummy model at multiple reclining angles, a first vector of the change of the first key point coordinates of the human-machine dummy model with the reclining angle is fitted; based on the second key point coordinates of the crash dummy at multiple reclining angles, a second vector of the change of the second key point coordinates of the crash dummy with the reclining angle is fitted; based on the third key point coordinates of the target driver at multiple reclining angles, a third vector of the change of the third key point coordinates of the target driver with the reclining angle is fitted; the first included angle between the first vector and the third vector and the second included angle between the second vector and the third vector are calculated respectively; based on the first included angle and the second included angle, the applicability of the human-machine dummy model and the crash dummy is evaluated.

[0043] Specifically, when evaluating the applicability of the side position of the large-angle seat, among the data collected by the HPM device, the crash dummy and the target driver, the values of some data in the Y direction are not of comparative significance. For example, for the tragus marker point, shoulder peak marker point, greater trochanter marker point, left and right knee marker points, left and right ankle marker points, etc. used to examine the side position of the target driver, only the X and Z values need to be retained. At this time, for the H point collected by the HPM device, the head centroid point, shoulder marker point, knee marker point, ankle marker point, etc. collected by the crash dummy, only the X and Z values need to be retained. For the filtered data, taking the X and Z values of the target driver, the HPM device, and the crash dummy collected when the seat back position is at the "0" position as the reference values, the differences between the X and Z values of the above measurement objects at the positions of "β", "2β",..., "α" and the reference values are calculated.

[0044] When evaluating the applicability of the front position of the large-angle seat, among the data collected by the HPM device, the crash dummy and the target driver, the values of some data in the X direction are not of comparative significance. For example, for the tragus marker point, shoulder peak marker point, greater trochanter marker point, left and right knee marker points, left and right ankle marker points, etc. used to examine the front position of the target driver, only the Y and Z values need to be retained. At this time, for the head centroid point, shoulder marker point, knee marker point, ankle marker point, etc. collected by the crash dummy, only the Y and Z values need to be retained. Similarly, for the filtered data, corresponding processing is also performed, and the differences between the Y and Z values of the above measurement objects at the positions of "β", "2β",..., "α" and the reference values are calculated.

[0045] As Figure 3 shown in the left figure in Figure 3As shown in the right figure in the middle, in this application, the vectors of the above two at this position are drawn starting from the same point as the vector of the target driver at this position. The target driver vector is named , the HPM device vector is named , and the crash dummy vector is named . By calculating the value of the included angle to represent the positive and negative of the directions of the two vectors and their degree of change, the deviation degree of the HPM device and the dummy compared with the target driver is evaluated, and then their applicability is evaluated. The formula for calculating the included angle is as follows:

[0046]

[0047] including the included angle and of the vectors 1, and of the included angle 2, The larger the value of

[0048] , the greater the degree of deviation between the two vectors in a certain direction of the coordinate system, and the worse the applicability. In one embodiment, the specific implementation manner of the above step 170 may be: during the experiment, measure the key point coordinates of the target human-machine dummy model; input the key point coordinates of the target human-machine dummy model into the trained neural network model to obtain the target key point coordinates of the target driver, and use the target key point coordinates as the key point coordinates of the target crash dummy.

[0049] Specifically, in this application, by measuring the H point of the HPM device with high applicability, through the conversion relationship, the positioning position of the target driver is calculated, and this is used as the basis for dummy positioning. In this application, by constructing a neural network as shown in Figure 4 , the input is the H point coordinate value of the HPM, and the output is the H point coordinate value of the target driver. For the l th layer and the i th neuron in the network, there is the following expression form:

[0050] ;

[0051] where i = 1, 2,..., , j = 1, 2,..., , l = 2, 3,..., n , n is the number of layers of the neural network model, is the value of the l th layer and the i th neuron, denotes l the number of neurons in the th l layer, the i th neuron in the l th layer is connected to the th neuron in the th layer with a weight of l denotes the bias value of the i th neuron in the th layer, and the function l denotes the activation function of the i th neuron in the

[0052] In one embodiment, the specific implementation of the above step 110 may be: measuring the maximum tilt angle of the backrest of the target seat from the upright state to the maximum backward tilt state; calculating the number of backward tilt angles of the target seat and the magnitude of each backward tilt angle based on the set adjustment angle and the maximum tilt angle.

[0053] This application calculates the number of backward tilt angles of the target seat by measuring the maximum tilt angle of the backrest of the target seat from the upright state to the maximum backward tilt state and the angle of a single adjustment. It should be understood that the more the number of backward tilt angles of the target seat, the higher the measurement accuracy.

[0054] In one embodiment, the specific implementation of the above step 120 may be: adjusting the target seat to the current backward tilt angle and installing the anthropomorphic dummy model on the target seat; measuring the left key point coordinates and the right key point coordinates of the anthropomorphic dummy model at the current backward tilt angle; if the first error between the left key point coordinates and the right key point coordinates of the anthropomorphic dummy model is less than the first preset value, calculating the first key point coordinates of the anthropomorphic dummy model at the current backward tilt angle based on the left key point coordinates and the right key point coordinates of the anthropomorphic dummy model.

[0055] Specifically, adjust the seat backrest to the β-degree position, select a certain HPM device, and install the device on the target seat according to the installation requirements of the HPM. After adjusting the HPM device, use a flexible three-coordinate measuring instrument to measure the reduction marking points of the seat coordinate system to ensure that the installation of the HPM does not affect the accuracy of the seat coordinate system. Use a flexible three-coordinate measuring instrument to measure the left and right H points of the HPM. When the error between the left and right H points is within the allowable range, calculate the average value of the left and right H points as the H point coordinate value of the HPM device at the β-degree position. Adjust the seat backrest to the 2β-degree position and repeat the above measurement process to obtain the H point coordinate value of the HPM device at the 2β-degree position. Continue the above process until the H point coordinate value of the HPM device at the α-degree position is obtained. Replace other HPM devices and repeat the above operations to measure the key point H point coordinate values of all HPM devices at various backrest angle values.

[0056] During this process, for each angular measurement position, in addition to measuring the coordinate value of the H-point, the midpoints of the upper edge (denoted as "II-0-L1", "II-β-L1", "II-2β-L1",..., "II-α-L1") and the lower edge (denoted as "II-0-L2", "II-β-L2", "II-2β-L2",..., "II-α-L2") of the lumbar plate of the HPM device should also be measured, as Figure 5 shown.

[0057] In one embodiment, the specific implementation of the above step 130 may be: adjusting the target seat to the current reclining angle and installing the crash dummy on the target seat; measuring the left key point coordinates and the right key point coordinates of the crash dummy at the current reclining angle; if the second error between the left key point coordinates and the right key point coordinates of the crash dummy is less than the second preset value, then calculating the second key point coordinates of the crash dummy at the current reclining angle based on the left key point coordinates and the right key point coordinates of the crash dummy.

[0058] Specifically, adjust the seat back to the 0-degree position, install and adjust the position of the crash dummy according to the requirements of the test standard, use a flexible three-coordinate measuring device to measure the reduction marking points of the seat coordinate system to ensure that the installation of the crash dummy does not affect the accuracy of the seat coordinate system. Use the flexible three-coordinate measuring device to measure the left and right H-points of the dummy. When the error between the left and right H-points is within the allowable range, calculate the average value of the left and right H-points. If the average value of the H-point meets the requirements for the H-point position of this type of crash dummy in the test standard, then use the calculated average value as the coordinate value of the H-point of the crash dummy at the 0-degree position. Measure the following key points of the crash dummy for comparison with the target driver measurement test: the left and right centroid points of the head, the left and right marking points of the shoulders, the left and right knee marking points, the left and right ankle marking points, and the pelvic angle.

[0059] When the left and right error values of the above key points are within the allowable range, calculate the mean values on the left and right of the key points, which are: the centroid point of the head, the shoulder marking points, the knee marking points, and the ankle marking points. Adjust the backrest to the next measurement angle position, gently push the chest of the crash dummy until the chest and head of the crash dummy come into contact with the backrest and the headrest respectively, repeat the above measurement method and record the H-point, the left and right centroid points of the head, the left and right shoulder marking points, the left and right knee marking points, the left and right ankle marking points, and the pelvis angle of the crash dummy at this position. When the left and right error values of the above key points are within the allowable range, calculate the mean values on the left and right of the key points, which are: the centroid point of the head, the shoulder marking points, the knee marking points, and the ankle marking points. And so on, continue to repeat the above process until the backrest is adjusted to the α-degree position, and measure and record the key point measurement values at each angle position during the process. When the chest or head of the crash dummy cannot come into contact with the backrest or the headrest, if there is an adjustable device on the chest or neck of the crash dummy, the chest and head structures of the crash dummy can be adjusted according to the structural characteristics of the crash dummy to achieve the purpose of contacting the backrest and the headrest. If there is no such adjustable device, record the backrest angle value at this time and the non-contact state of the crash dummy.

[0060] Replace with other types of crash dummies, repeat the above process, and complete the measurement of the key point coordinates and the key part angle values of all types of crash dummies.

[0061] In an embodiment, the specific implementation manner of the above step 140 may be: adjust the target seat to the current reclining angle and adjust the sitting posture of the target driver on the target seat; measure the left key point coordinates and the right key point coordinates of the target driver at the current reclining angle; if the third error between the left key point coordinates and the right key point coordinates of the target driver is less than the third preset value, calculate the third key point coordinates of the target driver at the current reclining angle based on the left key point coordinates and the right key point coordinates of the target driver.

[0062] Specifically, paste marker points at the tragion, shoulder (acromion), knee, ankle, and greater trochanter of the pelvis on the target driver's body parts. Paste marker points at the T5 and L12 positions of the target driver's spine. Paste angle sensors at the anterior superior iliac spines on both sides of the pelvis. Adjust the seat back to the 0-degree position, guide the target driver to sit on the seat normally and keep the left and right sides of the body as symmetrical as possible. Use a flexible three-coordinate measuring device to restore the marker points of the seat coordinate system to ensure that the target driver's sitting does not affect the accuracy of the seat coordinate system. Use a flexible three-coordinate measuring device to measure the left and right marker points of the target driver. When the error between the left and right marker points is within the allowable range, calculate the average value of the left and right marker points. Measure the following key points of the target driver: the left and right tragion marker points, the left and right acromion marker points, the left and right knee marker points, the left and right ankle marker points, the marker points at the T12 and L5 positions of the spine. When the left and right error values of the above key points are within the allowable range, calculate the average values of the left and right key points, which are: the tragion marker point, the acromion marker point, the knee marker point, and the ankle marker point. Zero the angle sensor at this position, adjust the backrest to the next measurement angle position, and adjust the sitting posture of the target driver so that the chest and head touch the backrest and headrest respectively. Repeat the above process and record the H point, the left and right tragion marker points, the left and right acromion marker points, the left and right knee marker points, the left and right ankle marker points, the marker points at the T12 and L5 positions of the spine of the target driver at this position. When the left and right error values of the above key points are within the allowable range, calculate the average values of the left and right key points, which are: the tragion marker point, the acromion marker point, the knee marker point, and the ankle marker point, and record the value of the angle sensor at this time. And so on, continue to repeat the above process until the backrest is adjusted to the α-degree position, and measure and record the measured values of the key points and the values of the angle sensor at each angle position during the process.

[0063] Replace with other target drivers and repeat the above process to complete the measurement of the key points and the angle values of the key parts of all target drivers.

[0064] After this application obtains the target key point coordinates of the target driver corresponding to the key point coordinates of the target anthropomorphic dummy model through conversion, use these target key point coordinates as the H point coordinates of the crash dummy, and calculate the pose part coordinate values of the crash dummy based on these H point coordinates. Specifically, this application first trains a forward network, using the coordinate values of the center point of the eyeball, upper neck, lower neck, upper abdomen, lower abdomen, elbow, wrist, knee, ankle, heel, toe, and head centroid of the crash dummy (collectively referred to as pose parts) as inputs, and the coordinate values of the H point (collectively referred to as positioning parts) as outputs to construct a neural network, as Figure 6 shown. The obtained relational expressions are as follows:

[0065] ;

[0066] Among them, i= 1, 2, ..., , j = 1, 2, ..., , l = 2, 3, ..., n , n is the number of layers of the neural network model, is the value of the l -th neuron in the i -th layer with the pose part coordinate values as the input, represents l the number of neurons in the -th layer, l represents the i -th neuron in the l -th layer and the weight value linked to the -th neuron in the -th layer, l represents the bias value of the i -th neuron in the -th layer, and the function l represents the activation function of the i -th neuron in the

[0067] The above relational expressions are represented in the form of matrices and vectors as follows:

[0068] ;

[0069] When l is the N-th layer, the above formula is the kinematic equation one.

[0070] By performing an inverse operation on the kinematic equation one, the following formula can be obtained:

[0071] ;

[0072] where, is the diagonal matrix of the activation function, and the elements on its diagonal represent the activation functions of each layer, specifically as follows:

[0073] ;

[0074] ;

[0075] Since the weight matrix in the neural network is non-invertible, a generalized inverse operation needs to be performed on it to obtain:

[0076] ;

[0077] The standard regularized least squares method is adopted in the above formula, represents the Tikhonov regularization parameter, Denote the identity matrix corresponding to the regularization parameter. The regularization parameter should be determined according to the measurement noise level of the measurable output or the increased noise level in the calculated response. Since becomes a square matrix, the expressions of the weights and biases in the neural network after inverting the motion equations can be represented by the following formulas:

[0078] ;

[0079] ;

[0080] Combining the above formulas, it can be calculated that:

[0081] ;

[0082] where and represent the inverse operation of the first kinematic equation, that is, a neural network with the coordinate values of the positioning part as the input and the coordinate values of the posture part as the output, as shown in Figure 7 shown.

[0083] The above formula can be transformed into:

[0084] ;

[0085] Substituting the H-point of the crash dummy positioning, the coordinate values of other positioning points of the crash dummy can be output: the coordinate values of the center point of the eyeball, the upper neck, the lower neck, the upper abdomen, the lower abdomen, the elbow, the wrist, the knee, the ankle, the heel, the toe, and the centroid of the head (collectively referred to as the posture part) of the crash dummy.

[0086] Figure 8 is a schematic structural diagram of a dummy positioning device based on the seat condition provided by an exemplary embodiment of the present application. As shown in Figure 8As shown, the dummy positioning device 80 based on the seat condition includes: a recline angle division module 81 for establishing a seat coordinate system and dividing the target seat into multiple recline angles based on the seat coordinate system; a first key point measurement module 82 for measuring the coordinates of the first key points of the human-machine dummy model at multiple recline angles; a second key point measurement module 83 for measuring the coordinates of the second key points of the crash dummy at multiple recline angles; a third key point measurement module 84 for measuring the coordinates of the third key points of the target driver at multiple recline angles; an applicability evaluation module 85 for evaluating the applicability of the human-machine dummy model and the crash dummy based on the coordinates of the first key points of the human-machine dummy model at multiple recline angles and the coordinates of the second key points of the crash dummy at multiple recline angles, with the coordinates of the third key points of the target driver at multiple recline angles as the standard; a target model selection module 86 for selecting the human-machine dummy model and the crash dummy whose applicability meets the preset conditions as the target human-machine dummy model and the target crash dummy respectively; and a crash dummy positioning module 87 for calculating the target key point coordinates of the target driver corresponding to the key point coordinates of the target human-machine dummy model based on the positioning conversion relationship between the target human-machine dummy model and the target driver, and using the target key point coordinates as the key point coordinates of the target crash dummy.

[0087] A dummy positioning device based on seat conditions provided by the present application establishes a seat coordinate system through a reclining angle division module 81, and divides the target seat into multiple reclining angles based on the seat coordinate system; a first key point measurement module 82 measures the coordinates of the first key points of the human-machine dummy model at multiple reclining angles; a second key point measurement module 83 measures the coordinates of the second key points of the crash dummy at multiple reclining angles; a third key point measurement module 84 measures the coordinates of the third key points of the target driver at multiple reclining angles; an applicability evaluation module 85 evaluates the applicability of the human-machine dummy model and the crash dummy based on the coordinates of the third key points of the target driver at multiple reclining angles, the coordinates of the first key points of the human-machine dummy model at multiple reclining angles, and the coordinates of the second key points of the crash dummy at multiple reclining angles; a target model selection module 86 selects the human-machine dummy model and the crash dummy whose applicability meets the preset conditions as the target human-machine dummy model and the target crash dummy respectively; a crash dummy positioning module 87 calculates the target key point coordinates of the target driver corresponding to the key point coordinates of the target human-machine dummy model based on the positioning conversion relationship between the target human-machine dummy model and the target driver, and uses the target key point coordinates as the key point coordinates of the target crash dummy; by measuring the key point coordinates of the human-machine dummy model, the crash dummy, and the target driver at multiple reclining angles of the seat, and evaluating the applicability of the human-machine dummy model and the crash dummy based on this, to select the target human-machine dummy model and the target crash dummy with better applicability, during the experiment, the key point coordinates of the target human-machine dummy model are converted into the target key point coordinates of the target driver, and the target key point coordinates are used as the key point coordinates of the target crash dummy, so as to obtain the positioning information of the target crash dummy under the large-angle seat condition.

[0088] In one embodiment, the above applicability evaluation module 85 can be further configured as: based on the coordinates of the first key points of the human-machine dummy model at multiple reclining angles, fitting to obtain a first vector of the coordinates of the first key points of the human-machine dummy model changing with the reclining angle; based on the coordinates of the second key points of the crash dummy at multiple reclining angles, fitting to obtain a second vector of the coordinates of the second key points of the crash dummy changing with the reclining angle; based on the coordinates of the third key points of the target driver at multiple reclining angles, fitting to obtain a third vector of the coordinates of the third key points of the target driver changing with the reclining angle; respectively calculating a first included angle between the first vector and the third vector, and a second included angle between the second vector and the third vector; based on the first included angle and the second included angle, evaluating the applicability of the human-machine dummy model and the crash dummy.

[0089] In one embodiment, the above-mentioned crash dummy positioning module 87 may be further configured to: during the experiment, measure the key point coordinates of the target human-machine dummy model; input the key point coordinates of the target human-machine dummy model into the trained neural network model to obtain the target key point coordinates of the target driver, and use the target key point coordinates as the key point coordinates of the target crash dummy.

[0090] In one embodiment, the above-mentioned recline angle division module 81 may be further configured to: measure the maximum recline angle of the backrest of the target seat from the upright state to the maximum backward tilt state; calculate the number of recline angles of the target seat and the size of each recline angle based on the set adjustment angle and the maximum recline angle.

[0091] In one embodiment, the above-mentioned first key point measurement module 82 may be further configured to: adjust the target seat to the current recline angle and install the human-machine dummy model on the target seat; measure the left key point coordinates and the right key point coordinates of the human-machine dummy model at the current recline angle; if the first error between the left key point coordinates and the right key point coordinates of the human-machine dummy model is less than the first preset value, calculate the first key point coordinates of the human-machine dummy model at the current recline angle based on the left key point coordinates and the right key point coordinates of the human-machine dummy model.

[0092] In one embodiment, the above-mentioned second key point measurement module 83 may be further configured to: adjust the target seat to the current recline angle and install the crash dummy on the target seat; measure the left key point coordinates and the right key point coordinates of the crash dummy at the current recline angle; if the second error between the left key point coordinates and the right key point coordinates of the crash dummy is less than the second preset value, calculate the second key point coordinates of the crash dummy at the current recline angle based on the left key point coordinates and the right key point coordinates of the crash dummy.

[0093] In one embodiment, the above-mentioned third key point measurement module 84 may be further configured to: adjust the target seat to the current recline angle and adjust the sitting posture of the target driver on the target seat; measure the left key point coordinates and the right key point coordinates of the target driver at the current recline angle; if the third error between the left key point coordinates and the right key point coordinates of the target driver is less than the third preset value, calculate the third key point coordinates of the target driver at the current recline angle based on the left key point coordinates and the right key point coordinates of the target driver.

[0094] Next, refer to Figure 9 to describe the electronic device according to the embodiments of the present application. The electronic device may be any one or both of the first device and the second device, or a stand-alone device independent of them, and the stand-alone device may communicate with the first device and the second device to receive the input signals collected from them.

[0095] Figure 9 The block diagram of an electronic device according to an embodiment of the present application is illustrated.

[0096] As Figure 9 shown, the electronic device 10 includes one or more processors 11 and a memory 12.

[0097] The processor 11 may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.

[0098] The memory 12 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage media, and the processor 11 may run the program instructions to implement the methods of various embodiments of the present application described above and / or other desired functions. Various contents such as input signals, signal components, noise components, etc. may also be stored in the computer-readable storage media.

[0099] In one example, the electronic device 10 may further include: an input device 13 and an output device 14, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0100] When the electronic device is a stand-alone device, the input device 13 may be a communication network connector for receiving the collected input signals from the first device and the second device.

[0101] In addition, the input device 13 may further include, for example, a keyboard, a mouse, and so on.

[0102] The output device 14 may output various information to the outside, including the determined distance information, direction information, etc. The output device 14 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0103] Of course, for simplicity, Figure 9 only some of the components related to the present application in the electronic device 10 are shown, and components such as buses, input / output interfaces, etc. are omitted. In addition, according to specific application scenarios, the electronic device 10 may further include any other appropriate components.

[0104] In addition to the above methods and devices, embodiments of the present application may also be computer program products, which include computer program instructions that, when run on a processor, cause the processor to execute the steps in the methods according to various embodiments of the present application described in the "Exemplary Methods" section above of this specification.

[0105] The computer program product can be written in any combination of one or more programming languages for programming code to perform the operations of the embodiments of the present application. The programming languages include object-oriented programming languages such as Java, C++, etc., and also include conventional procedural programming languages such as the "C" language or similar programming languages. The programming code can be executed entirely on the user's computing device, partially on the user's device, executed as an independent software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0106] In addition, embodiments of the present application may also be computer-readable storage media, on which computer program instructions are stored, and the computer program instructions, when run on a processor, cause the processor to execute the steps in the methods according to various embodiments of the present application described in the "Exemplary Methods" section above of this specification.

[0107] The computer-readable storage media may adopt any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may, for example, include but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0108] The basic principles of the present application have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present application. In addition, the specific details disclosed above are only for the purposes of illustration and easy understanding, and not for limitation. The above details do not limit the present application to necessarily adopt the above specific details for implementation.

[0109] The block diagrams of the devices, apparatuses, equipment, and systems involved in the present application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "comprising," "including," "having," etc. are open-ended terms meaning "including but not limited to" and can be used interchangeably with each other. The word "or" and "and" used herein refer to the phrase "and / or" and can be used interchangeably with it, unless the context clearly indicates otherwise. The phrase "such as" used herein refers to the phrase "such as but not limited to" and can be used interchangeably with it.

[0110] It should also be noted that in the devices, equipment, and methods of the present application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present application.

[0111] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0112] The above description has been given for purposes of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions, and sub-combinations thereof.

Claims

1. A method for positioning a dummy based on seat conditions, characterized in that, Including: Establish a seat coordinate system, and divide the target seat into multiple reclining angles based on the seat coordinate system; Measure the coordinates of the first key points of the anthropomorphic dummy model at the multiple reclining angles; Measure the coordinates of the second key points of the crash dummy at the multiple reclining angles; Measure the coordinates of the third key points of the target driver at the multiple reclining angles; Taking the coordinates of the third key points of the target driver at the multiple reclining angles as a standard, based on the coordinates of the first key points of the anthropomorphic dummy model at the multiple reclining angles and the coordinates of the second key points of the crash dummy at the multiple reclining angles, evaluate the applicability of the anthropomorphic dummy model and the crash dummy; Select the anthropomorphic dummy model and the crash dummy whose applicability meets the preset conditions as the target anthropomorphic dummy model and the target crash dummy respectively; Based on the positioning conversion relationship between the target anthropomorphic dummy model and the target driver, calculate the target key point coordinates of the target driver corresponding to the key point coordinates of the target anthropomorphic dummy model, and use the target key point coordinates as the key point coordinates of the target crash dummy; The step of taking the coordinates of the third key points of the target driver at the multiple reclining angles as a standard, and evaluating the applicability of the anthropomorphic dummy model and the crash dummy based on the coordinates of the first key points of the anthropomorphic dummy model at the multiple reclining angles and the coordinates of the second key points of the crash dummy at the multiple reclining angles includes: Based on the coordinates of the first key points of the anthropomorphic dummy model at the multiple reclining angles, fit the first vector of the change of the coordinates of the first key points of the anthropomorphic dummy model with the change of the reclining angle; Based on the coordinates of the second key points of the crash dummy at the multiple reclining angles, fit the second vector of the change of the coordinates of the second key points of the crash dummy with the change of the reclining angle; Based on the coordinates of the third key points of the target driver at the multiple reclining angles, fit the third vector of the change of the coordinates of the third key points of the target driver with the change of the reclining angle; Calculate the first included angle between the first vector and the third vector, and the second included angle between the second vector and the third vector respectively; Based on the first included angle and the second included angle, evaluate the applicability of the anthropomorphic dummy model and the crash dummy.

2. The method for positioning a dummy based on seat conditions according to claim 1, wherein The step of calculating the target key point coordinates of the target driver corresponding to the key point coordinates of the target anthropomorphic dummy model based on the positioning conversion relationship between the target anthropomorphic dummy model and the target driver, and using the target key point coordinates as the key point coordinates of the target crash dummy includes: During the experiment, measure the key point coordinates of the target anthropomorphic dummy model; Input the key point coordinates of the target anthropomorphic dummy model into the trained neural network model to obtain the target key point coordinates of the target driver, and use the target key point coordinates as the key point coordinates of the target crash dummy.

3. The method for positioning a dummy based on the seat condition according to claim 1, wherein The step of dividing the target seat into multiple reclining angles based on the seat coordinate system includes: Measure the maximum tilt angle of the backrest of the target seat when it tilts backward from the upright state to the maximum state; Based on the set adjustment angle and the maximum tilt angle, calculate the number of backward tilt angles of the target seat and the magnitude of each backward tilt angle.

4. The method for positioning a dummy based on seat conditions according to claim 1, wherein The measurement of the first key point coordinates of the anthropomorphic dummy model at the multiple backward tilt angles includes: Adjust the target seat to the current backward tilt angle and install the anthropomorphic dummy model on the target seat; Measure the left key point coordinates and right key point coordinates of the anthropomorphic dummy model at the current backward tilt angle; If the first error between the left key point coordinates and the right key point coordinates of the anthropomorphic dummy model is less than the first preset value, calculate the first key point coordinates of the anthropomorphic dummy model at the current backward tilt angle based on the left key point coordinates and the right key point coordinates of the anthropomorphic dummy model.

5. The method for positioning a dummy based on seat conditions according to claim 1, wherein The measurement of the second key point coordinates of the crash dummy at the multiple backward tilt angles includes: Adjust the target seat to the current backward tilt angle and install the crash dummy on the target seat; Measure the left key point coordinates and right key point coordinates of the crash dummy at the current backward tilt angle; If the second error between the left key point coordinates and the right key point coordinates of the crash dummy is less than the second preset value, calculate the second key point coordinates of the crash dummy at the current backward tilt angle based on the left key point coordinates and the right key point coordinates of the crash dummy.

6. The method for positioning a dummy based on the seat working condition according to claim 1, characterized in that, The measurement of the third key point coordinates of the target driver at the multiple backward tilt angles includes: Adjust the target seat to the current backward tilt angle and adjust the sitting posture of the target driver on the target seat; Measure the left key point coordinates and right key point coordinates of the target driver at the current backward tilt angle; If the third error between the left key point coordinates and the right key point coordinates of the target driver is less than the third preset value, calculate the third key point coordinates of the target driver at the current backward tilt angle based on the left key point coordinates and the right key point coordinates of the target driver.

7. A dummy positioning device based on seat conditions, characterized in that, Includes: A backward tilt angle division module for establishing a seat coordinate system and dividing the target seat into multiple backward tilt angles based on the seat coordinate system; A first key point measurement module for measuring the first key point coordinates of the anthropomorphic dummy model at the multiple backward tilt angles; A second key point measurement module for measuring the second key point coordinates of the crash dummy at the multiple backward tilt angles; A third key point measurement module for measuring the third key point coordinates of the target driver at the multiple backward tilt angles; An applicable performance evaluation module for evaluating the applicable performance of the anthropomorphic dummy model and the crash dummy based on the first key point coordinates of the anthropomorphic dummy model at the multiple backward tilt angles and the second key point coordinates of the crash dummy at the multiple backward tilt angles with the third key point coordinates of the target driver at the multiple backward tilt angles as the standard; A target model selection module for selecting the anthropomorphic dummy model and the crash dummy whose applicable performance meets the preset conditions as the target anthropomorphic dummy model and the target crash dummy respectively; A collision dummy positioning module, configured to calculate the target key point coordinates of the target driver corresponding to the key point coordinates of the target human-machine dummy model based on the positioning conversion relationship between the target human-machine dummy model and the target driver, and use the target key point coordinates as the key point coordinates of the target collision dummy; The applicability evaluation module is further configured to: Based on the first key point coordinates of the human-machine dummy model at the multiple reclining angles, fit a first vector of the first key point coordinates of the human-machine dummy model changing with the reclining angle; Based on the second key point coordinates of the collision dummy at the multiple reclining angles, fit a second vector of the second key point coordinates of the collision dummy changing with the reclining angle; Based on the third key point coordinates of the target driver at the multiple reclining angles, fit a third vector of the third key point coordinates of the target driver changing with the reclining angle; Calculate a first included angle between the first vector and the third vector, and a second included angle between the second vector and the third vector respectively; Based on the first included angle and the second included angle, evaluate the applicability of the human-machine dummy model and the collision dummy.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1-6 above.

9. An electronic device, characterized in that, Comprising: A processor; A memory for storing executable instructions of the processor; The processor is used to execute the method according to any one of claims 1-6 above.

Images