Automobile collision performance evaluation system based on virtual reality

Abstract

The invention discloses an automobile collision performance evaluation system based on virtual reality, and relates to the field of data processing, the system comprises an evaluation center, the evaluation center is in communication connection with a model acquisition module, a virtual test module, a virtual evaluation module and a result display module; the model acquisition module is used for acquiring an automobile test model of a target automobile; the virtual test module is used for carrying out a virtual automobile collision test based on the obtained automobile test model and carrying out data acquisition on a corresponding collision test process to obtain corresponding automobile collision data and human body injury data; the virtual evaluation module is used for evaluating the automobile collision performance according to the obtained automobile collision data and human body injury data to obtain a corresponding evaluation result; the result display module is used for taking corresponding performance optimization measures according to the obtained evaluation result and displaying a corresponding collision test process; according to the invention, efficient and accurate evaluation of the collision performance of the automobile is realized.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a virtual reality-based vehicle collision performance evaluation system. Background Art

[0002] Studying the passive safety of vehicles is of great significance for ensuring people's travel safety; compared with the prior art: traditional vehicle collision performance evaluations mostly use actual collision tests, and the actual collision test process is costly, has a long test cycle, and poses a safety threat to test personnel. Moreover, the number of elements in traditional vehicle finite element models is huge, and when there are many design schemes or structural improvements, it is often necessary to repeatedly modify the design and verification of the finite element model, which requires a large amount of computing time; these are the problems we need to solve, and for this reason, we provide a virtual reality-based vehicle collision performance evaluation system. Summary of the Invention

[0003] The purpose of the present invention is to provide a virtual reality-based vehicle collision performance evaluation system.

[0004] The purpose of the present invention can be achieved through the following technical solutions: a virtual reality-based vehicle collision performance evaluation system, including an evaluation center, which is communicatively connected to a model acquisition module, a virtual test module, a virtual evaluation module, and a result display module; The model acquisition module is used to acquire the vehicle test model of the target vehicle; The virtual test module is used to perform virtual vehicle collision tests based on the obtained vehicle test model, collect data on the corresponding collision test process, and obtain corresponding vehicle collision data and human injury data; The virtual evaluation module is used to evaluate the vehicle collision performance based on the obtained vehicle collision data and human injury data, and obtain corresponding evaluation results; The result display module is used to take corresponding performance optimization measures based on the obtained evaluation results and display the corresponding collision test process.

[0005] Further, the process of the model acquisition module acquiring the vehicle test model of the target vehicle includes: Acquire the initial vehicle model of the target vehicle, and at the same time acquire the optimization criteria, and select the corresponding optimization method according to the obtained optimization criteria to optimize the corresponding initial vehicle model; If the corresponding initial vehicle model does not meet the optimization criteria, use the first optimization method to optimize the corresponding initial vehicle model; If the corresponding initial vehicle model meets the optimization criteria, use the second optimization method to optimize the corresponding initial vehicle model; After the optimization is completed, the optimized initial vehicle model is output to obtain the corresponding vehicle test model.

[0006] Furthermore, the process of optimizing the corresponding initial vehicle model using the second optimization method includes Dividing the obtained initial vehicle model into regions according to the influence degree of regional deformation on the overall collision response of the vehicle to obtain the corresponding key regions and non-key regions; Performing a simplification operation on the corresponding non-key regions, and dynamically adjusting the mesh density of the corresponding key regions based on the adaptive mesh refinement technology; After the optimization is completed, the corresponding simplified model is obtained. Perform the corresponding analysis process based on the obtained simplified model and the initial vehicle model, and obtain the corresponding key output parameters. Calculate the difference between the key output parameters obtained from the corresponding simplified model and the initial vehicle model to obtain the corresponding deviation value; Set an error threshold, compare the obtained deviation value with the error threshold, and judge whether the corresponding simplified model meets the requirements according to the comparison result. If it meets the requirements, the optimization is completed.

[0007] Furthermore, the process of the virtual test module performing virtual vehicle collision tests based on the obtained vehicle test model includes: Set up a virtual building unit and select a collision scenario. The virtual building unit builds the corresponding three-dimensional driving environment and digital passengers according to the collision scenario; Deploy the corresponding vehicle test model and digital passengers into the built three-dimensional driving environment according to the collision scenario, and at the same time perform collision marking in the corresponding three-dimensional driving environment to obtain the corresponding target vehicle and collision object; Set the initial conditions and boundary conditions for the corresponding target vehicle and collision object according to the collision scenario; After the conditions are set, perform virtual vehicle collision tests based on the built three-dimensional driving environment, and collect data on the corresponding collision test process.

[0008] Furthermore, the process of collecting the corresponding collision test process data to obtain the corresponding vehicle collision data and human injury data includes: Set a collision period, obtain the corresponding collision test area according to the selected collision scenario, divide the obtained collision test area to obtain several collision areas; Furthermore, collect data on the collision areas of the corresponding target vehicle within the corresponding collision period to obtain the corresponding vehicle collision data; Meanwhile, data acquisition nodes are set at partial body parts of the corresponding digital passengers, and the data acquisition nodes are used to acquire data on the changes of the body parts of the corresponding digital passengers, so as to obtain corresponding human body injury data.

[0009] Further, the process of the virtual evaluation module evaluating the vehicle collision performance based on the obtained vehicle collision data and human body injury data includes: The virtual evaluation module includes a vehicle injury evaluation unit and a passenger injury evaluation unit; The vehicle injury evaluation unit is used to evaluate the target vehicle based on the obtained vehicle collision data to obtain corresponding vehicle injury coefficients; The passenger injury evaluation unit is used to evaluate the corresponding digital passengers based on the obtained human body injury data to obtain corresponding human body injury coefficients; Furthermore, based on the obtained human body injury coefficients and vehicle injury coefficients, corresponding performance evaluation coefficients are obtained, an evaluation threshold range is set, and the corresponding performance evaluation coefficients are compared with the corresponding evaluation threshold range to obtain corresponding evaluation results.

[0010] Further, the process of the vehicle injury evaluation unit evaluating the target vehicle based on the obtained vehicle collision data to obtain corresponding vehicle injury coefficients includes: Read the collected collision data, and divide the corresponding collision areas based on it to obtain corresponding high-force and high-deformation areas, and use the corresponding collision areas as collision points; Furthermore, obtain the corresponding maximum collision force, maximum acceleration, deformation parameters, and collision recovery coefficient based on the obtained collision data; Build a corresponding injury evaluation model based on big data technology, input relevant data such as the corresponding maximum collision force, maximum acceleration, deformation parameters, and collision gray coefficient into the built injury evaluation model, obtain the injury score corresponding to the collision point, and mark it as the injury coefficient.

[0011] Further, the process of the passenger injury evaluation unit evaluating the corresponding digital passengers based on the obtained human body injury data to obtain corresponding human body injury coefficients includes: Read the obtained human body injury coefficients, and obtain the peak force on the abdomen and pelvis, chest deformation index, and head performance index of the corresponding digital passengers based on them, and perform weighted summation on the obtained peak force on the abdomen and pelvis, chest deformation index, and head performance index to obtain corresponding human body injury coefficients.

[0012] Further, the process of the result display module taking corresponding performance optimization measures based on the obtained evaluation results and displaying the corresponding collision test process includes: Read the obtained evaluation results, generate corresponding collision test reports based on the evaluation results, and generate corresponding performance optimization suggestions based on the corresponding evaluation results; Meanwhile, the result display module can also display the corresponding virtual car collision test process to the user in an interactive manner such as a helmet display or VR projection based on immersive virtual reality technology.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. By obtaining the test model of the target car and conducting collision tests in a virtual environment, the present invention avoids the high cost, high risk, and long cycle of actual collision tests, greatly shortens the evaluation cycle, and at the same time ensures the accuracy of the evaluation results; 2. By optimizing the obtained initial car model, it helps to reduce the redundant parts in the car model, improve the quality and accuracy of the model, and more accurately reflect the performance of the car in actual collisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is the schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] As Figure 1 shown, a virtual reality-based car collision performance evaluation system includes an evaluation center, and the evaluation center is communicatively connected to a model acquisition module, a virtual test module, a virtual evaluation module, and a result display module; The model acquisition module is used to acquire the car test model of the target car; It should be further noted that in the specific implementation process, the process of the model acquisition module acquiring the car test model of the target car includes: Acquire the initial car model of the target car, where the initial car model is a detailed car finite element model constructed by staff at the construction node of the target car; Acquire the optimization criteria, and select the corresponding optimization method to optimize the corresponding initial car model according to the obtained optimization criteria; where the optimization criteria include but are not limited to the number of loading and constraint conditions, the requirements of the solver and computing resources, and the degrees of freedom of the model; If the corresponding initial car model does not meet the optimization criteria, the first optimization method is used to optimize the corresponding initial car model, where the first optimization method includes but is not limited to structural optimization, topology optimization, and size optimization; it should be further noted that the first optimization method is mostly a conventional optimization means, and the present invention will not elaborate too much; If the corresponding initial car model meets the optimization criteria, the second optimization method is used to optimize the corresponding initial car model; After the optimization is completed, the initial vehicle model after optimization is output to obtain the corresponding vehicle test model; It should be further noted that, in the specific implementation process, the process of optimizing the corresponding initial vehicle model according to the second optimization method includes: The obtained initial vehicle model is divided into regions according to the influence degree of regional deformation on the overall collision response of the vehicle to obtain the corresponding key regions and non-key regions, and then the corresponding non-key regions are simplified. The simplification operation refers to merging adjacent similar material property units in the corresponding initial vehicle model or replacing low-order units with high-order units to reduce the number of units while maintaining or improving the simulation accuracy; Based on the adaptive mesh refinement technology, the mesh density of the corresponding key regions is dynamically adjusted. For example, the local mesh density of the impact region and the high stress gradient region is increased to improve the solution accuracy; After the processing is completed, the corresponding simplified model is obtained. The corresponding analysis process is performed based on the obtained simplified model and the initial vehicle model, and the corresponding key output parameters are obtained. The difference between the key output parameters obtained from the corresponding simplified model and the initial vehicle model is calculated to obtain the corresponding deviation value; An error threshold is set, and the obtained deviation value is compared with the error threshold. If the corresponding deviation value meets the error threshold, the corresponding simplified model is output to obtain the corresponding vehicle test model; if the corresponding deviation value does not meet the error threshold, the corresponding simplified model is continuously iteratively optimized until it meets the requirements.

[0016] The virtual test module is used to perform virtual vehicle collision tests based on the obtained vehicle test model, and collect data during the corresponding collision tests to obtain the corresponding vehicle collision data and human injury data; It should be further noted that, in the specific implementation process, the process of the virtual test module performing virtual vehicle collision tests based on the obtained vehicle test model includes: Virtual building units are set. The virtual building units are used to collect data on the driving environment of the vehicle and build the corresponding three-dimensional driving environment according to the collection results. The three-dimensional driving environment includes traffic roads, traffic signs, surrounding buildings, environmental weather, and other relevant vehicle parameters; it is also used to virtually build the target vehicle passengers to obtain the corresponding digital passengers. Among them, the digital passengers include ordinary passengers and vehicle drivers, and the management personnel can also modify the relevant human body data such as the age and gender of the corresponding digital passengers according to the requirements; Further, a collision scenario is selected, and the virtual construction unit constructs a corresponding three-dimensional driving environment and digital passengers according to the collision scenario, where the collision scenario includes but is not limited to frontal collision, side collision, and rear-end collision; Furthermore, the corresponding vehicle test model and digital passengers are deployed into the constructed three-dimensional driving environment according to the collision scenario; and the corresponding vehicle test model is marked as the target vehicle. At the same time, other vehicles or surrounding buildings that the target vehicle needs to collide with are selected in the corresponding three-dimensional driving environment and marked as collision objects; Initial conditions and boundary conditions are set for the corresponding target vehicle and collision objects according to the collision scenario; where the initial conditions refer to the vehicle state at the start of the collision test, and the vehicle state includes but is not limited to vehicle speed, vehicle acceleration, and vehicle mass distribution. For example, for frontal collision simulation, the vehicle may be set to move straight at a certain speed, while for side collision, lateral movement of the vehicle needs to be considered, etc.; the boundary conditions define the physical limitations of the model, such as the interaction between the target vehicle and the collision object, applying friction conditions (frictionless contact), fixed walls and ground, etc. boundary conditions to the target vehicle; After the conditions are set, a virtual vehicle collision test is carried out based on the constructed three-dimensional driving environment, and data is collected during the corresponding collision test process; It should be further noted that in the specific implementation process, the process of collecting data during the corresponding collision test process to obtain the corresponding vehicle collision data and human injury data includes: Set the collision period (T1, T2); where T1 is the moment when the initial collision occurs between the target vehicle and the collision object, and T2 is the moment when the final collision ends between the target vehicle and the collision object; Obtain the corresponding collision test area according to the selected collision scenario, divide the obtained collision test area, and obtain several collision areas; Furthermore, data is collected for the collision area of the corresponding target vehicle within the corresponding collision period to obtain the corresponding vehicle collision data; At the same time, data collection nodes are set at some body parts of the corresponding digital passengers, and the data change conditions of the body parts of the corresponding digital passengers are collected through the data collection nodes to obtain the corresponding human injury data, where the human injury data includes the force condition, linear acceleration data, angular acceleration, and position change of the data collection nodes.

[0017] The virtual evaluation module is used to evaluate the vehicle collision performance based on the obtained vehicle collision data and human injury data; It should be further noted that in the specific implementation process, the process of the virtual evaluation module evaluating the vehicle collision performance based on the obtained vehicle collision data and human body injury data includes: The virtual evaluation module includes a vehicle damage evaluation unit and a passenger damage evaluation unit; The vehicle damage evaluation unit is used to evaluate the target vehicle based on the obtained vehicle collision data and obtain the corresponding vehicle damage coefficient; The passenger damage evaluation unit is used to evaluate the corresponding digital passenger based on the obtained human body injury data and obtain the corresponding human body injury coefficient; Furthermore, based on the obtained human body injury coefficient and vehicle damage coefficient, the corresponding performance evaluation coefficient is obtained, and the obtained performance evaluation coefficient is denoted as PXN; Among them, ; Set the evaluation threshold range, compare the corresponding performance evaluation coefficient with the corresponding evaluation threshold range, and obtain the corresponding evaluation result; the evaluation results include primary collision risk, secondary collision risk, tertiary collision risk, and collision safety; It should be further noted that in the specific implementation process, the process of the vehicle damage evaluation unit evaluating the target vehicle based on the obtained vehicle collision data and obtaining the corresponding vehicle damage coefficient includes: Taking a certain collision area as an example, read the vehicle collision data corresponding to the corresponding collision area, and obtain the corresponding force parameters and deformation parameters. Among them, the force parameters refer to the forces received within the corresponding collision area, which are jointly determined by the forces perpendicular and parallel to the collision area direction, and the deformation parameters refer to the degree of deformation of the corresponding collision area due to the force parameters; and the force parameters and deformation parameters are in direct proportion; Set the parameter thresholds, where the parameter thresholds include force thresholds and deformation thresholds, compare the corresponding force parameters and deformation parameters with the corresponding parameter thresholds, and determine the corresponding collision points based on the comparison results; If both the force parameters and deformation parameters are higher than the corresponding parameter thresholds, indicating that the corresponding collision area is a high-force and high-deformation area, then mark the corresponding collision area as a collision point; If at most one of the force parameters and deformation parameters is higher than the corresponding parameter threshold, indicating that the corresponding collision area is a non-collision point, then no other operations are performed; Use the same method to traverse all collision areas and obtain all collision points; Number the obtained collision points, denoted as i, i = 1, 2,..., n, where n > 0 and n is an integer; Read the vehicle collision data corresponding to the corresponding collision i, construct a corresponding two-dimensional rectangular coordinate system with time as the horizontal axis and the corresponding vehicle collision data as the vertical axis, and obtain the corresponding vehicle collision data change curve; Obtain the corresponding speed change curve and acceleration change curve based on the obtained collision change curve, and at the same time obtain the maximum acceleration of the target vehicle during the corresponding collision period; Furthermore, obtain the collision force of the corresponding target vehicle during the collision period based on it, and record the obtained collision force as F, ; where Ft represents the collision force at the collision point i at time t, k and xbt respectively represent the stiffness coefficient of the collision point i and the deformation parameter at time t; obtain the change condition of the corresponding collision force during the collision period based on it, and then obtain the peak value of the collision force of the corresponding collision point i during the collision period, and record it as the maximum collision force, Vt represents the vehicle speed of the target vehicle at time t, where t ∈ (T1, T2); At the same time, obtain the collision restitution coefficient of the target vehicle, and the corresponding mathematical formula is as follows, In the formula, V1, V2, V 11 , V 22 respectively represent the speeds of the target vehicle and the collision object before and after the collision test. Among them, the collision gray coefficient is used for the reduction degree of the relative speed of the two vehicles after the collision, and is used to estimate the "soft" or "hard" degree of the collision; Build a corresponding damage assessment model based on big data technology, input relevant data such as the corresponding maximum collision force, maximum acceleration, deformation parameter, and collision gray coefficient into the constructed damage assessment model, obtain the damage score corresponding to the collision point i, and mark it as the damage coefficient Di Classify the damage degree of the corresponding collision point i according to the obtained damage coefficient, and assign the corresponding weight λi; It should be further noted that in the specific implementation process, the process of the passenger damage assessment unit evaluating the corresponding digital passenger based on the obtained human body damage data includes: Read the collected human body damage data, and obtain the peak forces on the abdomen and pelvis of the corresponding digital passenger based on the obtained human body damage data, and record them as FN and GN respectively; Obtain the position change of the data acquisition node set on the chest of the corresponding digital passenger, mark the initial position of the corresponding data acquisition node as (x1, y1, z1), and the deformation position corresponding to the corresponding data acquisition node at time t0, and record it as (xt0, yt0, zt0); Furthermore, obtain the deformation amount of the corresponding digital passenger based on the obtained initial position and deformation position, and mark the obtained deformation amount as D (m); Furthermore, corresponding chest deformation indexes of digital passengers are obtained based on this, and the corresponding mathematical calculation formula is as follows: In the formula, Dt+1 (m), Dt-1 (m), Dt+2 (m), and Dt-2 (m) respectively represent the deformation amounts D (m) at times t+1, t-1, t+2, and t-2; ∆T represents the time interval during acquisition; among them, t0, t+1, t-1, t+2, and t-2 all belong to (T1, T2); Meanwhile, the corresponding head performance indexes of digital passengers are calculated by the same method and denoted as HPC, where In the formula, a1 and a2 respectively represent the linear acceleration and angular acceleration of the digital passenger's head; Based on the obtained peak forces at the abdomen and pelvis, chest deformation indexes, and head performance indexes, weighted summation is performed to obtain the corresponding human injury coefficient, denoted as SS.

[0018] The result display module is used to take corresponding performance optimization measures according to the obtained evaluation results and display the corresponding collision test process; It should be further noted that in the specific implementation process, the process in which the result display module is used to take corresponding performance optimization measures according to the obtained evaluation results and display the corresponding collision test process includes: Read the obtained evaluation results, generate a corresponding collision test report based on the evaluation results, and at the same time generate corresponding performance optimization suggestions based on the corresponding evaluation results. For example, for a first-level collision risk, it can be recommended to increase the vehicle support structure, and at the same time use materials with a large yield stress and a small elastic modulus at a position close to the root of the longitudinal beam of the target vehicle, so as to make the material rebound more easily before reaching yield in the later stage of the collision, thereby increasing the rebound speed of the support structure of the target vehicle; Meanwhile, the result display module can also display the corresponding virtual vehicle collision test process to the user in an interactive manner such as a helmet display or VR projection based on immersive virtual reality technology.

[0019] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A virtual reality-based vehicle crash performance evaluation system, characterized in that, It includes an evaluation center, which is communicatively connected to a model acquisition module, a virtual test module, a virtual evaluation module, and a result display module; The model acquisition module is used to acquire the vehicle test model of the target vehicle; The virtual test module is used to perform a virtual vehicle collision test based on the acquired vehicle test model, collect data during the corresponding collision test process, and obtain the corresponding vehicle collision data and human injury data; The virtual evaluation module is used to evaluate the vehicle collision performance based on the acquired vehicle collision data and human injury data, and obtain the corresponding evaluation results; The result display module is used to take corresponding performance optimization measures based on the acquired evaluation results and display the corresponding collision test process.

2. The automotive collision performance evaluation system based on virtual reality according to claim 1, wherein, The process by which the model acquisition module acquires the vehicle test model of the target vehicle includes: Acquire the initial vehicle model of the target vehicle, and at the same time acquire the optimization criteria. Select the corresponding optimization method according to the acquired optimization criteria to optimize the corresponding initial vehicle model; If the corresponding initial vehicle model does not meet the optimization criteria, use the first optimization method to optimize the corresponding initial vehicle model; If the corresponding initial vehicle model meets the optimization criteria, use the second optimization method to optimize the corresponding initial vehicle model; After the optimization is completed, output the optimized initial vehicle model to obtain the corresponding vehicle test model.

3. The automotive crash performance evaluation system based on virtual reality according to claim 2, wherein, The process of using the second optimization method to optimize the corresponding initial vehicle model includes Divide the obtained initial vehicle model into regions according to the influence degree of regional deformation on the overall collision response of the vehicle, and obtain the corresponding key regions and non-key regions; Perform a simplification operation on the corresponding non-key regions, and at the same time dynamically adjust the mesh density of the corresponding key regions based on the adaptive mesh refinement technology; After the optimization is completed, obtain the corresponding simplified model. Perform the corresponding analysis process based on the obtained simplified model and the initial vehicle model, and obtain the corresponding key output parameters. Calculate the difference between the key output parameters obtained from the corresponding simplified model and the initial vehicle model to obtain the corresponding deviation value; Set an error threshold, compare the obtained deviation value with the error threshold, and judge whether the corresponding simplified model meets the requirements according to the comparison result. If it meets the requirements, the optimization is completed.

4. The automotive crash performance evaluation system based on virtual reality according to claim 2, characterized in that, The process by which the virtual test module performs a virtual vehicle collision test based on the acquired vehicle test model includes: Set up a virtual building unit and select a collision scenario. The virtual building unit builds the corresponding three-dimensional driving environment and digital passengers according to the collision scenario; Deploy the corresponding vehicle test model and digital passengers into the built three-dimensional driving environment according to the collision scenario, and at the same time perform collision marking in the corresponding three-dimensional driving environment to obtain the corresponding target vehicle and collision object; Set the initial conditions and boundary conditions for the corresponding target vehicle and collision object according to the collision scenario; After the conditions are set, perform a virtual vehicle collision test based on the built three-dimensional driving environment and collect data during the corresponding collision test process.

5. The automotive crash performance evaluation system based on virtual reality according to claim 4, characterized in that, The process of collecting data for the corresponding collision test and obtaining the corresponding vehicle collision data and human injury data includes: Set the collision period, obtain the corresponding collision test area according to the selected collision scenario, divide the obtained collision test area, and obtain several collision areas; Furthermore, collect data for the collision area of the corresponding target vehicle within the corresponding collision period to obtain the corresponding vehicle collision data; At the same time, set data collection nodes at some body parts of the corresponding digital passenger, and collect data on the data changes of the body parts of the corresponding digital passenger through the data collection nodes to obtain the corresponding human injury data.

6. The vehicle collision performance evaluation system based on virtual reality according to claim 5, characterized in that, The process of the virtual evaluation module evaluating the vehicle collision performance based on the obtained vehicle collision data and human injury data includes: The virtual evaluation module includes a vehicle damage evaluation unit and a passenger damage evaluation unit; The vehicle damage evaluation unit is used to evaluate the target vehicle based on the obtained vehicle collision data to obtain the corresponding vehicle damage coefficient; The passenger damage evaluation unit is used to evaluate the corresponding digital passenger based on the obtained human injury data to obtain the corresponding human injury coefficient; Furthermore, based on the obtained human injury coefficient and vehicle damage coefficient, obtain the corresponding performance evaluation coefficient, set the evaluation threshold range, compare the corresponding performance evaluation coefficient with the corresponding evaluation threshold range, and obtain the corresponding evaluation result.

7. The vehicle collision performance evaluation system based on virtual reality according to claim 6, characterized in that, The process of the vehicle damage evaluation unit evaluating the target vehicle based on the obtained vehicle collision data to obtain the corresponding vehicle damage coefficient includes: Read the collected collision data, and divide the corresponding collision area according to it to obtain the corresponding high-force and high-deformation areas, and use the corresponding collision area as the collision point; Furthermore, obtain the corresponding maximum collision force, maximum acceleration, deformation parameter, and collision recovery coefficient based on the obtained collision data; Build a corresponding damage evaluation model based on big data technology, input the corresponding maximum collision force, maximum acceleration, deformation parameter, and collision gray coefficient into the built damage evaluation model, obtain the damage score corresponding to the collision point, and mark it as the damage coefficient.

8. The vehicle collision performance evaluation system based on virtual reality according to claim 6, wherein The process of the passenger damage evaluation unit evaluating the corresponding digital passenger based on the obtained human injury data to obtain the corresponding human injury coefficient includes: Read the obtained human injury coefficient, and obtain the peak force, chest deformation index, and head performance index at the abdomen and pelvis of the corresponding digital passenger according to it, and perform weighted summation on the obtained peak force, chest deformation index, and head performance index at the abdomen and pelvis to obtain the corresponding human injury coefficient.

9. The automotive crash performance evaluation system based on virtual reality according to claim 6, wherein The process of the result display module taking corresponding performance optimization measures based on the obtained evaluation result and displaying the corresponding collision test process includes: Read the obtained evaluation result, generate a corresponding collision test report according to the evaluation result, and generate corresponding performance optimization suggestions according to the corresponding evaluation result; Meanwhile, based on immersive virtual reality technology, the corresponding virtual car crash test process is presented to users through a helmet display or VR projection and other interaction methods.

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