Vehicle damage automatic processing analysis method and system based on multi-dimensional data

Abstract

The invention discloses a multi-dimensional data-based vehicle damage automatic processing analysis method and system, and belongs to the technical field of vehicle damage assessment, and the method comprises the steps: a user side recognizes an acquisition target; when the collection target is a vehicle owner vehicle, the vehicle-mounted terminal carries out data collection to obtain vehicle damage information, and the vehicle damage information is analyzed through a preset second evaluation model to obtain a second vehicle damage evaluation result; when the collection target is a non-owner vehicle, performing data supplementary collection according to user requirements to obtain user collection data, and analyzing the user collection data through a preset first evaluation model to obtain a first vehicle damage evaluation result; whether the first vehicle damage assessment result or the second vehicle damage assessment result meets a preset sending standard is assessed, vehicle damage feedback information is generated according to the second vehicle damage assessment result or the second vehicle damage assessment result meeting the sending standard, the vehicle damage feedback information is analyzed through a standard assessment model, and a standard vehicle damage assessment result is obtained.

Description

Technical Field

[0001] This invention belongs to the field of vehicle damage assessment technology, specifically a method and system for automated processing and analysis of vehicle damage based on multidimensional data. Background Technology

[0002] In traditional vehicle damage assessment scenarios, car owners often face multiple dilemmas after an accident, and existing technical solutions fail to fully meet their needs for independent assessment. This forms the core background for the present invention. Traditional assessment processes heavily rely on human damage assessors, whose experience differences lead to highly subjective assessment results. For example, different assessors may judge the depth of the same scratch by more than 0.5 millimeters, leading to disagreements on repair plans. Simultaneously, car owners are in a passive position during the assessment process, unable to view damage data in real time or understand the assessment logic, and can only accept the conclusions given by the assessor. This information asymmetry easily leads to disputes. Statistics show that approximately 15% of car insurance claims disputes stem from car owners questioning the damage assessment results.

[0003] The demand for self-assessment by car owners is becoming increasingly urgent with the widespread adoption of smart terminals and sensor technologies. Modern vehicles are widely equipped with high-precision cameras, onboard AI chips, and various types of sensors. The development of mobile phone imaging technology and edge computing allows ordinary users to upload accident photos or videos via apps and quickly identify damage types (such as scratches, dents, and cracks) using pre-trained models. Based on this, in order to address car owners' need for self-assessment of vehicle damage, this invention provides an automated vehicle damage processing and analysis method and system based on multi-dimensional data. Summary of the Invention

[0004] To address the problems of the above solutions, this invention provides an automated vehicle damage processing and analysis method and system based on multidimensional data.

[0005] The objective of this invention can be achieved through the following technical solutions: A vehicle damage automated processing and analysis system based on multidimensional data, including in-vehicle terminal, user terminal and cloud; The cloud platform includes a vehicle evaluation module; The vehicle assessment module is used to analyze the received vehicle damage feedback information, obtain the corresponding standard vehicle damage assessment results, and send the standard vehicle damage assessment results to the corresponding user terminal.

[0006] Furthermore, the received vehicle damage feedback information is analyzed, including: A corresponding standard evaluation model is preset, and the standard evaluation model is simplified to obtain a corresponding first evaluation model and a second evaluation model. The first evaluation model and the second evaluation model are respectively arranged in the user analysis module and the vehicle analysis module. By analyzing vehicle damage feedback information using a standard assessment model, corresponding standard vehicle damage assessment results are obtained.

[0007] The user terminal includes an autonomous control module, a supplementary data collection module, and a user analysis module; The autonomous control module is used by users to control data collection and identify the collection target when they have a need for vehicle damage assessment. When the target of the data collection is the vehicle owner's vehicle, a data collection command is generated and sent to the vehicle-mounted data collection module. When the target of the data collection is a non-owner vehicle, no corresponding operation will be performed; The supplementary data collection module is used to collect supplementary data according to user needs and obtain corresponding supplementary data. When the target of the data collection is the vehicle owner's vehicle, the supplementary vehicle data will be sent to the vehicle-mounted data collection module. When the target of the data collection is a non-owner vehicle, the supplementary data collection will be marked as user-collected data and sent to the user analysis module.

[0008] The user analysis module analyzes the received user-collected data through a preset first evaluation model to obtain the corresponding first vehicle damage evaluation result, displays the first vehicle damage evaluation result to the user, evaluates whether the first vehicle damage evaluation result meets the preset sending standard, generates corresponding vehicle damage feedback information based on the first vehicle damage evaluation result that meets the sending standard, and sends the vehicle damage feedback information to the cloud.

[0009] Furthermore, the vehicle damage feedback information includes the initial vehicle damage assessment results and the corresponding user-collected data.

[0010] The vehicle-mounted terminal includes a data acquisition module and a vehicle-mounted analysis module; The acquisition module is used to collect vehicle damage information when it receives an acquisition command, and send the vehicle damage information to the vehicle analysis module.

[0011] Furthermore, information on vehicle damage is collected, including: Identify the target data acquisition command; When the target of the data collection is a vehicle owner's vehicle, obtain the initial vehicle information of the target; When the target of the data collection is a non-owner vehicle, no corresponding operation will be performed; It receives supplementary data from the supplementary data collection module in the user terminal in real time, and integrates the supplementary data with the initial vehicle information to form vehicle damage information.

[0012] The vehicle analysis module is used to analyze the received vehicle damage information through a preset second evaluation model, obtain the corresponding second vehicle damage evaluation result, display the second vehicle damage evaluation result to the user, evaluate whether the second vehicle damage evaluation result meets the preset sending standard, generate corresponding vehicle damage feedback information based on the second vehicle damage evaluation result that meets the sending standard, and send the vehicle damage feedback information to the cloud.

[0013] Furthermore, the vehicle damage feedback information includes the second vehicle damage assessment results and the corresponding vehicle damage information.

[0014] Further, assess whether the first or second vehicle damage assessment result meets the preset sending criteria, including: The accuracy rate of the first or second assessment model for assessing vehicle damage of various types of vehicles is statistically analyzed in real time, and a corresponding list of assessment accuracy is generated based on the obtained accuracy rate. Mark the first or second vehicle damage assessment result as sent assessment material; identify the vehicle type and vehicle damage type corresponding to the sent assessment material; match the corresponding accuracy rate from the assessment accuracy list according to the vehicle type and vehicle damage type; and integrate the vehicle type, vehicle damage type and accuracy rate into vehicle damage material data. The vehicle damage data is analyzed using a pre-set delivery evaluation model to obtain the corresponding delivery evaluation results.

[0015] Furthermore, the vehicle damage data is analyzed using a pre-defined delivery evaluation model, including: The expression for sending the evaluation model is: ; In the formula: (s, BZ) are the input data, s is the vehicle damage material data, BZ is the sending standard, s→BZ means that the corresponding vehicle damage material data meets the sending standard; the output data is the sending evaluation value FA(s, BZ), and the sending evaluation value is 1 or 0; The input data is fed into the transmission evaluation model for analysis to obtain the corresponding transmission evaluation value of the input data. When the sending evaluation value is 1, the sending evaluation result is that the sending criteria are met; When the sending evaluation value is 0, the sending evaluation result is that the sending standard is not met.

[0016] Furthermore, the standard vehicle damage assessment results, the first vehicle damage assessment results, and the second vehicle damage assessment results are all displayed in three preset scenarios: user-responsible repair, case reference, and other party-responsible repair.

[0017] An automated vehicle damage processing and analysis method based on multidimensional data, the method includes: A corresponding standard evaluation model is preset in the cloud, and the standard evaluation model is simplified to obtain a first evaluation model and a second evaluation model. The first evaluation model and the second evaluation model are then deployed in the user terminal and the vehicle terminal, respectively. When a user needs a vehicle damage assessment, the user terminal identifies the data collection target. When the target of the data collection is the vehicle owner's vehicle, a data collection command is generated and sent to the vehicle terminal. The vehicle terminal collects data to obtain vehicle damage information. It analyzes the received vehicle damage information through a preset second assessment model to obtain the corresponding second vehicle damage assessment result. It also assesses whether the second vehicle damage assessment result meets the preset sending standard. Based on the second vehicle damage assessment result that meets the sending standard, it generates the corresponding vehicle damage feedback information and sends the vehicle damage feedback information to the cloud. When the target of the data collection is a non-owner vehicle, data supplementation is carried out according to user needs to obtain user-collected data. The received user-collected data is analyzed through a preset first evaluation model to obtain the corresponding first vehicle damage evaluation result. The first vehicle damage evaluation result is displayed to the user, and it is evaluated whether the first vehicle damage evaluation result meets the preset sending standard. Based on the first vehicle damage evaluation result that meets the sending standard, the corresponding vehicle damage feedback information is generated and sent to the cloud. By analyzing vehicle damage feedback information using a standard assessment model, corresponding standard vehicle damage assessment results are obtained.

[0018] Compared with the prior art, the beneficial effects of the present invention are: This invention overcomes the limitations of traditional vehicle damage assessment, which heavily relies on human assessors. In traditional methods, differences in experience among assessors lead to highly subjective assessment results and disagreements on repair plans. This invention, however, utilizes a multi-dimensional data-based automated vehicle damage processing and analysis method and system. By integrating data collected from high-precision cameras, onboard AI chips, and various sensors in modern vehicles, as well as accident photos or videos uploaded via a mobile app, it employs a pre-trained model for rapid and accurate analysis. This avoids the subjectivity of manual assessments, significantly improving the objectivity and accuracy of the results and providing a reliable basis for subsequent repair plan development. Furthermore, this invention fully considers the urgent need for self-assessment by vehicle owners. Leveraging the widespread use of smart terminals and sensor technology, it allows vehicle owners to actively participate in the vehicle damage assessment process. Owners can upload accident information via a mobile app, obtain real-time multi-dimensional data on vehicle damage, and clearly understand the assessment logic through the system's visual interface and detailed explanations. This enhances the owner's autonomy and participation in the assessment process, effectively reducing disputes caused by information asymmetry. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a block diagram illustrating the principle of the present invention. Detailed Implementation

[0021] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0022] like Figure 1 As shown, the automated vehicle damage processing and analysis system based on multidimensional data includes an on-board terminal, a user terminal, and a cloud terminal. The cloud platform includes a vehicle evaluation module; The vehicle assessment module is used to analyze the received vehicle damage feedback information, obtain the corresponding standard vehicle damage assessment results, and send the standard vehicle damage assessment results to the corresponding user terminal.

[0023] In one embodiment, the received vehicle damage feedback information is analyzed to assess the damage using existing intelligent vehicle damage assessment methods, such as establishing an intelligent assessment model based on deep learning algorithms, or establishing a large model for analysis, i.e., using existing cloud platform resources and assessment methods. The assessment model based on the cloud application is then simplified, for example, by using knowledge distillation, pruning, or quantification to obtain assessment models applicable to both the user end and the vehicle end. To differentiate them, the assessment model corresponding to the vehicle assessment module is labeled as the standard assessment model; the assessment models corresponding to the user end and the vehicle end are labeled as the first assessment model and the second assessment model, respectively; the first assessment model and the second assessment model are then deployed in the user analysis module and the vehicle analysis module, respectively.

[0024] In one embodiment, the standard evaluation model can be classified according to different vehicle types and vehicle damage types, such as by using clustering algorithms, and a corresponding standard evaluation model can be set for each classification to improve the evaluation accuracy.

[0025] In one embodiment, the standard vehicle damage assessment result is divided into three scenarios: user-responsible repair, case law reference, and other party-responsible repair. User-responsible repair refers to the user choosing a repair shop for repair. Case law reference refers to similar repair cases that have reference value, generally choosing legal cases such as similar repair judgments as references. Other party-responsible repair refers to other relevant parties choosing a repair shop for repair. Different scenarios will lead to different vehicle damage assessment losses due to differences in repair, and there will also be differences due to different responsible parties. Therefore, a differentiated analysis is conducted based on the actual situation, and the user chooses the responsible party to generate the assessment result under the corresponding background.

[0026] The standard vehicle damage assessment result, the first vehicle damage assessment result, and the second vehicle damage assessment result are all displayed in three preset scenarios: user is responsible for repairs, case reference, and the other party is responsible for repairs.

[0027] The user terminal is for user use. Users can be vehicle owners or related personnel. It typically runs on the user's mobile phone and can be an app, mini-program, etc.; it includes an autonomous control module, a supplementary data collection module, and a user analysis module. The autonomous control module is used by the user to collect data when there is a vehicle damage assessment, and to identify the data collection target. The data collection target is the vehicle that needs to be assessed for vehicle damage, which can be the owner's vehicle or other vehicles. When the target of the data collection is the vehicle owner's vehicle, a data collection command is generated and sent to the vehicle-mounted data collection module. No action will be taken when the target of the data collection is a vehicle that is not owned by the vehicle owner.

[0028] For example, when a user needs to independently assess vehicle damage, they can click on "Vehicle Damage Assessment" on the preset interface, and can select to assess the owner's vehicle or other vehicles, and then generate collection instructions.

[0029] The supplementary data collection module is used to collect supplementary data and obtain corresponding supplementary data. When the collection target is a vehicle owner's vehicle, the vehicle supplementary data is sent to the collection module on the vehicle side; when the collection target is a non-vehicle owner's vehicle, the supplementary data is marked as user-collected data and sent to the user analysis module.

[0030] That is, the supplementary data collection module collects data according to the user's needs.

[0031] In one embodiment, supplementary data collection includes: When the target of data collection is a non-owner vehicle, the system cannot automatically collect the initial vehicle data of other vehicles. The user needs to negotiate with other vehicle owners to collect the data. If other vehicle owners allow the collection of supplementary data (initial vehicle data) from their vehicles, such as OBD (On-Board Diagnostics) and collision sensors, the data will be collected using the existing method and uploaded through the supplementary data collection module. Alternatively, it can be directly uploaded to the cloud. This data collection is typically done by repair shops, etc. If the user can directly operate the data collection, it can be uploaded directly. If other vehicle owners do not allow data collection, the initial vehicle information will be empty. Regardless of whether the vehicle belongs to the owner, users can obtain images and other relevant data about the damaged parts of the vehicle through mobile phones and other devices. Users can collect relevant data as needed and mark it as supplementary data. If a self-addition function is displayed to the user, the user can add the relevant supplementary vehicle data according to the self-addition function. The system will then prompt for photos, videos and other relevant data that can be added. If it is not possible to collect photos of the vehicle damage, the user can collect them through mobile phones and other devices.

[0032] The user analysis module analyzes the received user-collected data through a preset first evaluation model to obtain the corresponding first vehicle damage evaluation result, displays the first vehicle damage evaluation result to the user, evaluates whether the first vehicle damage evaluation result meets the preset sending standard, generates corresponding vehicle damage feedback information based on the first vehicle damage evaluation result that meets the sending standard, and sends the vehicle damage feedback information to the cloud.

[0033] The vehicle damage feedback information includes the initial vehicle damage assessment results and the corresponding user-collected data.

[0034] The vehicle-mounted terminal is installed in the vehicle and includes a data acquisition module, a vehicle-mounted analysis module, and The acquisition module is used to collect vehicle damage information when it receives an acquisition command, send the vehicle damage information to the on-board analysis module, and send the vehicle damage information to the cloud.

[0035] The data collection module interfaces with various systems, devices, and sensors on the vehicle that are related to vehicle damage assessment to collect relevant vehicle information. If the data is collected from the cloud after authorization from the vehicle manufacturer, the user needs to apply for authorization.

[0036] In one embodiment, collecting vehicle damage information includes: Identify the target data acquisition command; When the target of data collection is a vehicle owner's vehicle, the corresponding initial vehicle information is collected in real time, that is, vehicle information that can be read and collected directly through the vehicle's system, equipment, etc., and marked as initial vehicle information; When the target of the data collection is a non-owner vehicle, no corresponding operation is performed. That is, the subsequent evaluation can be carried out through the user terminal or the cloud, without the need for evaluation on the vehicle terminal. The vehicle terminal does not need to collect the initial vehicle data of other vehicles. It receives supplementary data from the supplementary data collection module in the user terminal in real time, and integrates the supplementary data with the initial vehicle information to form vehicle damage information.

[0037] The vehicle analysis module is used to analyze the received vehicle damage information through a preset second evaluation model, obtain the corresponding second vehicle damage evaluation result, display the second vehicle damage evaluation result to the user (which can be displayed on the vehicle display screen), evaluate whether the second vehicle damage evaluation result meets the preset sending standard, generate the corresponding vehicle damage feedback information based on the second vehicle damage evaluation result that meets the sending standard, and send the vehicle damage feedback information to the cloud.

[0038] The vehicle damage feedback information includes the second vehicle damage assessment results and the corresponding vehicle damage information.

[0039] In one embodiment, the sending standard is set according to user needs. For example, if the user does not allow sending, sending is allowed in all situations. An accuracy requirement can also be preset, that is, whether to send is determined based on the historical accuracy of this type of damage assessment. According to the above definition, the first vehicle damage assessment result or the second vehicle damage assessment result is evaluated according to the sending standard using existing technology to see if the sending standard is met.

[0040] In one embodiment, evaluating whether the first vehicle damage assessment result or the second vehicle damage assessment result meets a preset sending standard includes: The accuracy rate of the first or second assessment model for assessing vehicle damage of various types of vehicles is statistically analyzed in real time, and the relevant historical assessment data is used for statistical analysis; based on the obtained accuracy rate, a corresponding assessment accuracy list is generated, which includes at least the accuracy rate of different vehicles under different damage types. Mark the first or second vehicle damage assessment result as sent assessment material; identify the vehicle type and vehicle damage type corresponding to the sent assessment material; match the corresponding accuracy rate from the assessment accuracy list according to the vehicle type and vehicle damage type; and integrate the vehicle type, vehicle damage type and accuracy rate into vehicle damage material data. The vehicle damage data is analyzed using a pre-set delivery evaluation model to obtain the corresponding delivery evaluation results.

[0041] In one embodiment, the evaluation model is built based on existing technologies, such as machine learning or deep learning algorithms.

[0042] In one embodiment, the expression for sending the evaluation model is: ; In the formula: (s, BZ) are the input data, s is the vehicle damage material data, BZ is the sending standard, s→BZ means that the corresponding vehicle damage material data meets the sending standard; the output data is the sending evaluation value FA(s, BZ), and the sending evaluation value is 1 or 0; the corresponding training set is labeled with the corresponding historical data for training; The specific criteria depend on the sending standards. If the sending standards only limit the accuracy rate, then the corresponding accuracy rates can be directly compared. If the user also limits the vehicle type, vehicle damage type, etc., then the vehicle type and vehicle damage type need to be matched and compared.

[0043] The input data is analyzed using a pre-defined sending evaluation model, including: The input data is fed into the transmission evaluation model for analysis to obtain the corresponding transmission evaluation value of the input data. When the sending evaluation value is 1, the sending evaluation result is that the sending criteria are met; When the sending evaluation value is 0, the sending evaluation result is that the sending standard is not met.

[0044] An automated vehicle damage processing and analysis method based on multidimensional data, the method includes: A corresponding standard evaluation model is preset in the cloud, and the standard evaluation model is simplified to obtain a first evaluation model and a second evaluation model. The first evaluation model and the second evaluation model are then deployed in the user terminal and the vehicle terminal, respectively. When a user needs a vehicle damage assessment, the user terminal identifies the data collection target. When the target of the data collection is the vehicle owner's vehicle, a data collection command is generated and sent to the vehicle terminal. The vehicle terminal collects data to obtain vehicle damage information. It analyzes the received vehicle damage information through a preset second assessment model to obtain the corresponding second vehicle damage assessment result. It also assesses whether the second vehicle damage assessment result meets the preset sending standard. Based on the second vehicle damage assessment result that meets the sending standard, it generates the corresponding vehicle damage feedback information and sends the vehicle damage feedback information to the cloud. When the target of the data collection is a non-owner vehicle, data supplementation is carried out according to user needs to obtain user-collected data. The received user-collected data is analyzed through a preset first evaluation model to obtain the corresponding first vehicle damage evaluation result. The first vehicle damage evaluation result is displayed to the user, and it is evaluated whether the first vehicle damage evaluation result meets the preset sending standard. Based on the first vehicle damage evaluation result that meets the sending standard, the corresponding vehicle damage feedback information is generated and sent to the cloud. By analyzing vehicle damage feedback information using a standard assessment model, corresponding standard vehicle damage assessment results are obtained.

[0045] The above formulas are all numerical calculations after removing dimensions. The formulas are obtained by software simulation based on a large amount of data and are closest to the real situation. The preset parameters and preset thresholds in the formulas are set by those skilled in the art according to the actual situation or obtained by simulation based on a large amount of data.

[0046] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A vehicle damage automated processing and analysis system based on multidimensional data, characterized in that, This includes the vehicle terminal, the user terminal, and the cloud; The cloud platform includes a vehicle evaluation module; the user terminal includes an autonomous control module, a supplementary data collection module, and a user analysis module; the vehicle-mounted terminal includes a data collection module and a vehicle-mounted analysis module. The vehicle assessment module is used to analyze the received vehicle damage feedback information, obtain the corresponding standard vehicle damage assessment results, and send the standard vehicle damage assessment results to the corresponding user terminal. The autonomous control module is used by the user to control the collection when there is a need for vehicle damage assessment and to identify the collection target; when the collection target is the owner's vehicle, it generates a collection command and sends the collection command to the vehicle-mounted collection module. When the target of the data collection is a non-owner vehicle, no corresponding operation will be performed; The supplementary data collection module is used to collect supplementary data according to user needs and obtain corresponding supplementary data; when the collection target is the vehicle owner's vehicle, the supplementary vehicle data is sent to the collection module on the vehicle side. When the target of the data collection is a non-owner vehicle, the supplementary data collection will be marked as user-collected data and sent to the user analysis module. The user analysis module analyzes the received user-collected data through a preset first evaluation model to obtain the corresponding first vehicle damage evaluation result, and displays the first vehicle damage evaluation result to the user. The acquisition module is used to acquire vehicle damage information when it receives an acquisition command, and send the vehicle damage information to the vehicle analysis module; The vehicle analysis module is used to analyze the received vehicle damage information through a preset second evaluation model, obtain the corresponding second vehicle damage evaluation result, and display the second vehicle damage evaluation result to the user. The system assesses whether the first or second vehicle damage assessment result meets the preset sending criteria. Based on the second vehicle damage assessment result that meets the sending criteria, it generates vehicle damage feedback information and sends the vehicle damage feedback information to the cloud.

2. The automated vehicle damage processing and analysis system based on multidimensional data according to claim 1, characterized in that, The received vehicle damage feedback information is analyzed, including: A corresponding standard evaluation model is preset, and the standard evaluation model is simplified to obtain a corresponding first evaluation model and a second evaluation model. The first evaluation model and the second evaluation model are respectively arranged in the user analysis module and the vehicle analysis module. By analyzing vehicle damage feedback information using a standard assessment model, corresponding standard vehicle damage assessment results are obtained.

3. The automated vehicle damage processing and analysis system based on multidimensional data according to claim 1, characterized in that, The vehicle damage feedback information includes the initial vehicle damage assessment results and the corresponding user-collected data.

4. The automated vehicle damage processing and analysis system based on multidimensional data according to claim 1, characterized in that, Collect vehicle damage information, including: Identify the target data acquisition command; When the target of the data collection is a vehicle owner's vehicle, obtain the initial vehicle information of the target; When the target of the data collection is a non-owner vehicle, no corresponding operation will be performed; It receives supplementary data from the supplementary data collection module in the user terminal in real time, and integrates the supplementary data with the initial vehicle information to form vehicle damage information.

5. The automated vehicle damage processing and analysis system based on multidimensional data according to claim 1, characterized in that, The vehicle damage feedback information includes the second vehicle damage assessment results and the corresponding vehicle damage information.

6. The automated vehicle damage processing and analysis system based on multidimensional data according to claim 1, characterized in that, Evaluate whether the first or second vehicle damage assessment result meets the preset sending criteria, including: The accuracy rate of the first or second assessment model for assessing vehicle damage of various types of vehicles is statistically analyzed in real time, and a corresponding list of assessment accuracy is generated based on the obtained accuracy rate. Mark the first or second vehicle damage assessment result as sent assessment material; identify the vehicle type and vehicle damage type corresponding to the sent assessment material; match the corresponding accuracy rate from the assessment accuracy list according to the vehicle type and vehicle damage type; and integrate the vehicle type, vehicle damage type and accuracy rate into vehicle damage material data. The vehicle damage data is analyzed using a pre-set delivery evaluation model to obtain the corresponding delivery evaluation results.

7. The automated vehicle damage processing and analysis system based on multidimensional data according to claim 6, characterized in that, The vehicle damage data is analyzed using a pre-defined delivery evaluation model, including: The expression for sending the evaluation model is: ； In the formula: (s, BZ) are the input data, s is the vehicle damage material data, BZ is the sending standard, s→BZ means that the corresponding vehicle damage material data meets the sending standard; the output data is the sending evaluation value FA(s, BZ), and the sending evaluation value is 1 or 0; The input data is fed into the transmission evaluation model for analysis to obtain the corresponding transmission evaluation value of the input data. When the sending evaluation value is 1, the sending evaluation result is that the sending criteria are met; When the sending evaluation value is 0, the sending evaluation result is that the sending standard is not met.

8. The automated vehicle damage processing and analysis system based on multidimensional data according to claim 1, characterized in that, The standard vehicle damage assessment results, the first vehicle damage assessment results, and the second vehicle damage assessment results are all displayed in three preset scenarios: user-responsible repair, case reference, and other party-responsible repair.

9. An automated vehicle damage processing and analysis method based on multidimensional data, characterized in that, The method, applied to the automated vehicle damage processing and analysis system based on multidimensional data as described in any one of claims 1 to 8, comprises: A corresponding standard evaluation model is preset in the cloud, and the standard evaluation model is simplified to obtain a first evaluation model and a second evaluation model. The first evaluation model and the second evaluation model are then deployed in the user terminal and the vehicle terminal, respectively. When a user needs a vehicle damage assessment, the user terminal identifies the data collection target. When the target of the data collection is the vehicle owner's vehicle, a data collection command is generated and sent to the vehicle terminal. The vehicle terminal collects data to obtain vehicle damage information. It analyzes the received vehicle damage information through a preset second assessment model to obtain the corresponding second vehicle damage assessment result. It also assesses whether the second vehicle damage assessment result meets the preset sending standard. Based on the second vehicle damage assessment result that meets the sending standard, it generates the corresponding vehicle damage feedback information and sends the vehicle damage feedback information to the cloud. When the target of the data collection is a non-owner vehicle, data supplementation is carried out according to user needs to obtain user-collected data. The received user-collected data is analyzed through a preset first evaluation model to obtain the corresponding first vehicle damage evaluation result. The first vehicle damage evaluation result is displayed to the user, and it is evaluated whether the first vehicle damage evaluation result meets the preset sending standard. Based on the first vehicle damage evaluation result that meets the sending standard, the corresponding vehicle damage feedback information is generated and sent to the cloud. By analyzing vehicle damage feedback information using a standard assessment model, corresponding standard vehicle damage assessment results are obtained.

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