Test data processing method, device, cloud, storage medium and system

Abstract

The embodiments of the present application provide a test data processing method, apparatus, cloud, storage medium and system. A calibration auxiliary system is set up including a cloud, a calibration auxiliary device, a remote device and a user device, and the cloud is respectively connected with the calibration auxiliary device, the remote device and the user device. The cloud obtains the working condition configuration data of the target test through the user device, and obtains the test data generated during the implementation of the target test through the remote device. The driver's driving behavior is scored according to the working condition configuration data and the test data. The scoring results are displayed through the calibration auxiliary device, which can remind the driver to adjust the improper driving behavior in time, improve the calibration efficiency, and thus reduce the labor cost.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of vehicle technology, and in particular to a test data processing method, device, cloud, storage medium and system. Background Art

[0002] Based on the control logic of the engine electronic control system, data is collected through calibration tests before the vehicle leaves the factory, and functional mode matching and data optimization are performed. This is not only the key to improving the performance of the entire vehicle, but also the key to ensuring that the operation of the entire vehicle meets industry regulations, corporate internal control standards and user needs.

[0003] The traditional electronic control system calibration process is usually that engineers formulate test tasks and send them to drivers, who then drive the vehicle to complete the test data collection according to the requirements of the test tasks. Since a change in a parameter in the electronic control system often causes a series of changes in the engine's operating status indicators, multiple tests may need to be repeated for the same operating condition. If the driver's improper operation causes the test to fail, more tests will need to be repeated, which is an extremely time-consuming and labor-intensive task.

[0004] Therefore, how to regulate drivers' driving behavior, improve calibration test efficiency and reduce labor costs has become a technical problem that needs to be urgently solved by existing technologies. Summary of the invention

[0005] The embodiments of the present application provide a test data processing method, device, cloud, storage medium and system, which can remind the driver to adjust improper driving behavior in time, improve calibration efficiency, and thus reduce labor costs.

[0006] In a first aspect, an embodiment of the present application provides a test data processing method, which is applied to a cloud in a calibration assistance system, wherein the calibration assistance system further includes a calibration assistance device, a remote device, and a user device, wherein the cloud is connected to the calibration assistance device, the remote device, and the user device, respectively, and the calibration assistance device and the remote device are both arranged on a vehicle, and the method includes:

[0007] Acquiring the operating condition configuration data of the target test through the user equipment;

[0008] Acquiring test data generated during the implementation of the target test through the remote device;

[0009] Scoring the driver's driving behavior according to the operating condition configuration data and the test data;

[0010] The scoring result is displayed by the calibration auxiliary device.

[0011] In a second aspect, an embodiment of the present application provides a test data processing device, which is integrated in a cloud in a calibration assistance system, wherein the calibration assistance system further includes a calibration assistance device, a remote device, and a user device, wherein the cloud is connected to the calibration assistance device, the remote device, and the user device, respectively, and the calibration assistance device and the remote device are both arranged on a vehicle, and the device includes:

[0012] An acquisition module, used to acquire the working condition configuration data of the target test through the user device; and acquire the test data generated during the implementation of the target test through the remote device;

[0013] The processing module is used to score the driver's driving behavior according to the working condition configuration data and the test data; and the scoring result is displayed through the calibration auxiliary device.

[0014] In a third aspect, an embodiment of the present application provides a cloud, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the test data processing method as described in the first aspect above is implemented.

[0015] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the test data processing method as described in the first aspect above.

[0016] In the fifth aspect, an embodiment of the present application provides a calibration assistance system, including a calibration assistance device, a remote device, a user device and a cloud as described in the third aspect above, wherein the cloud is connected to the calibration assistance device, the remote device and the user device respectively, and the calibration assistance device and the remote device are both arranged on the vehicle.

[0017] The test data processing method, device, cloud, storage medium and system provided in the embodiments of the present application, by setting up a calibration auxiliary system including a cloud, a calibration auxiliary device, a remote device and a user device, and setting up the cloud to be connected with the calibration auxiliary device, the remote device and the user device respectively, the cloud obtains the working condition configuration data of the target test through the user device, obtains the test data generated during the implementation of the target test through the remote device, scores the driver's driving behavior according to the working condition configuration data and the test data, and displays the scoring results through the calibration auxiliary device, which can remind the driver to adjust the improper driving behavior in time, improve the calibration efficiency, and thus reduce labor costs.

[0018] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A schematic diagram of the structure of a calibration assistance system provided in Example 1 of the present application;

[0021] Figure 2 A schematic diagram of a calibration test process provided in Example 1 of the present application;

[0022] Figure 3 An internal logic schematic diagram for generating a test report provided in Example 1 of the present application;

[0023] Figure 4 A flowchart of a test data processing method provided in Example 1 of the present application;

[0024] Figure 5 A schematic diagram of working condition partitioning provided in Example 2 of the present application;

[0025] Figure 6 A schematic diagram of operating parameters provided in Example 2 of the present application;

[0026] Figure 7 A schematic diagram of the structure of a test data processing device provided in Example 3 of the present application;

[0027] Figure 8 A schematic diagram of a cloud structure provided in Example 4 of the present application. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", target, etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] The main idea of ​​the technical solution of the present application: the technical problems existing in the prior art, the embodiment of the present application constructs a calibration assistance system, the system includes a calibration assistance device, a remote device, a user device and a cloud, the cloud is connected to the calibration assistance device, the remote device and the user device respectively, and a data processing method is provided based on the calibration assistance system, the cloud obtains the working condition configuration data set by the engineer through the user device, and obtains the test data generated during the implementation of the test through the remote device, so as to analyze the test data generated during the implementation of the test based on the working condition configuration data, score the driver's driving behavior according to the preset scoring rules, and display the scoring results through the calibration assistance device, so as to remind the driver to promptly discover the problems in driving, and make adjustments and optimizations, thereby improving the efficiency of subsequent tests, shortening the entire calibration test cycle, and achieving the purpose of saving labor costs.

[0031] Embodiment 1

[0032] For example, Figure 1 A schematic diagram of the structure of a calibration auxiliary system provided in Example 1 of the present application is shown in FIG. Figure 1 As shown, Figure 1 As shown, the calibration assistance system 100 provided in this embodiment includes: a cloud 110 , a user device 120 , a calibration assistance device 130 and a remote device 140 .

[0033] Among them, the cloud 110, which is the executor of the test data processing solution provided in the embodiment of the present application, is a server with functions such as calculation, data processing, and logic control, and is connected to the user device 120, the calibration auxiliary device 130 and the remote device 140 respectively.

[0034] The user device 120 corresponds to the terminal device on the engineer side, and can communicate remotely with the cloud 110. In this embodiment, the engineer can issue instructions and configure test parameters to the cloud 110 through the user device 120 as needed. The user device 120 can be a computer, a smart phone, a laptop, etc.

[0035] The calibration auxiliary device 130, corresponding to the driver's terminal device, is installed on the vehicle used for calibration and can communicate remotely with the cloud 110. In this embodiment, according to the needs, the driver can call the test task, check the calibration progress, receive the control command sent by the cloud 110 and perform the corresponding operation on the calibration auxiliary device 130. In a possible implementation, the calibration auxiliary device 130 is an intelligent terminal device with display function and voice broadcast function.

[0036] The remote device 140 is also arranged on the vehicle for calibration, and can communicate with the cloud 110 and the vehicle at the same time. In a possible implementation, on the one hand, the remote device 140 can realize the connection with the cloud 110 through the Internet of Things and the message queuing telemetry transport (MQTT) protocol to perform data transmission; on the other hand, the remote device 140 can realize the communication with the vehicle end 110 through the unified diagnostic services (UDS) protocol, the controller area network (CAN) protocol and the CAN database (DBC) file, and can collect, flash and calibrate the internal signals of the controller.

[0037] The calibration assistance system 100 provided in this embodiment has the following functions:

[0038] (1) Test route formulation

[0039] The engineer configures the test route (i.e., the driving route of the vehicle in this calibration test) through the configuration page provided by the user device 120, and the user device 120 uploads the test route to the cloud 110. Before the test starts, the calibration auxiliary device 130 sends a request to the cloud 110 (which can be triggered by the driver's operation) to retrieve the test route. After the calibration auxiliary device 130 obtains the test route from the cloud 110, it performs real-time navigation along the route to facilitate the driver to carry out the test.

[0040] (2) Test conditions formulation

[0041] The engineer configures the test conditions (such as the vehicle speed, accelerator pedal, brake pedal, driving time, mileage, etc. required for this test) through the configuration page provided by the user device 120, and the user device 120 uploads the test conditions to the cloud 110. Before the test starts, the calibration auxiliary device 130 sends a request to the cloud 110 (which can be triggered by the driver's operation) to retrieve the test conditions. After the calibration auxiliary device 130 obtains the test conditions from the cloud 110, it displays the test conditions on its display screen. During the test, the cloud 110 acquires the test data in real time through the remote device 140, analyzes the test data, determines the progress of the test completion and sends it to the calibration auxiliary device 130, and the calibration auxiliary device 130 displays the progress of the test completion in real time. After a test is completed, the driving score and driving behavior analysis report are generated based on the operating condition coverage, operating condition parameters, parameter weights, constraints and standards uploaded to the cloud 110 by the engineer through the user device 120 (see the description in Example 2 for the specific implementation process). At the same time, the driving score and driving behavior analysis report are mapped to the calibration auxiliary device 130 for the driver's reference, thereby improving driving behavior.

[0042] (3) Experimental data optimization

[0043] After the test is completed, the cloud 110 extracts characteristic factors of the calibration field based on the experience of calibration experts, and determines whether the reliability, smoothness, vibration and noise of the vehicle meet the preset test standards by comparing characteristic parameters. The preset test standards can be standards defined or required by customers, experts or the industry. If they meet the standards, a test report is generated based on the test data, and the test report and test data are sent to the engineer's mailbox by email; if they do not meet the standards, a comparison is made based on the database management system for characteristic elements such as the engine and transmission, and data is preset by means of mode, median, mean, fitting, etc., and the optimization direction is determined. The calibration data of a single associated calibration MAP and CRUVE is adjusted with a preset step size (such as 5%), and a test task is generated after adjustment, and the test is repeated; for multiple associated calibration MAPs and CRUVEs, the engineer is reminded to confirm the optimization data on the user device 120 by SMS and email, and a test task is generated after confirmation, and the test is repeated. For example, Figure 2 A schematic diagram of the flow of a calibration test provided in Example 1 of the present application.

[0044] (4) Automatic generation of test reports

[0045] After the test, the cloud 110 extracts characteristic factors of the calibration field based on the calibration expert experience, decomposes the characteristic factors, and combines data mining algorithms (through embedded functions, trigger conditions, feature extraction, mathematical calculations, logical programming, etc.) to realize a visual report that makes expert experience, standards, and customer complaints explicit. The cloud 110 generates a visual report and sends it to the user device 120, which shows whether the calibration test meets the industry standards through a traffic light mechanism. For example, Figure 3 An internal logic schematic diagram for generating a test report provided in Example 1 of the present application.

[0046] The calibration auxiliary system provided by the embodiment of the present application has the functions of test route formulation, test condition formulation, test data optimization, and automatic report generation, and can retrieve modular test schemes through the test scheme standard library, and map with calibration auxiliary equipment through the cloud. On the one hand, since the processes of test route formulation, test condition formulation, and test task issuance can be realized through the system, and there is no need for engineers to communicate face to face with drivers, it breaks the limitations of time and space, making communication smoother, more convenient and more efficient. At the same time, engineers also gain more time to process and analyze test data and formulate test schemes; on the other hand, the test progress, problems existing in the test process, and test results can be fed back to the driver in a timely manner, so that the driver can adjust the improper behavior in time and improve the success rate of the test; on the other hand, the calibration data can also be optimized according to the actual situation of the test, and the operability and rationality of the formulated test tasks can be improved, so as to ensure the smooth progress of the calibration test. Based on the above three aspects, the calibration auxiliary system provided by the embodiment of the present application is used for calibration test, which realizes intelligent calibration and greatly improves the calibration efficiency, thereby saving labor costs.

[0047] Embodiment 2

[0048] Figure 4 The flowchart of a test data processing method provided in the first embodiment of the present application is shown in FIG. 1. The method of the present embodiment can be executed by a test data processing device provided in the embodiment of the present application. The device can be implemented by software and / or hardware and can be integrated into Figure 1 As shown in the cloud. Figure 4 As shown, the test data processing method of this embodiment includes:

[0049] S201. Obtain working condition configuration data of a target test through a user device.

[0050] Among them, the target test, that is, the calibration test to be performed this time, can be determined by the engineer's selection operation on the user device. For example, when a specific calibration test is selected, the user device sends a message carrying the calibration test identifier to the cloud to determine the target test.

[0051] In this embodiment, after the engineer selects a calibration test, he can enter the configuration page of the calibration test to configure the test route and test conditions, etc. Accordingly, in this step, after the engineer completes the configuration operation of the target test, the cloud can obtain the relevant condition configuration data from the user device.

[0052] In one possible implementation, when the engineer clicks the "Confirm" or "Submit" button on the configuration page, the user terminal sends a configuration completion message to the cloud, and the cloud sends a working condition configuration data acquisition request carrying a target test identifier to the user device, so that the user device sends the corresponding working condition configuration data to the cloud.

[0053] S202. Acquire test data generated during the implementation of the target test through a remote device.

[0054] In this embodiment, during the implementation of the target test, the remote device collects test data of preset operating parameters in real time, and sends the collected test data to the cloud, where the preset operating parameters are one or more of vehicle speed, accelerator pedal opening, brake pedal opening, transmission gear, engine speed, etc.

[0055] In a possible implementation, the remote device sends the collected test data of the target test to the cloud at a preset period.

[0056] S203: Score the driver's driving behavior based on the working condition configuration data and the test data.

[0057] In this step, the test data obtained in S202 is analyzed according to the working condition configuration data obtained in S201, and the driver's driving behavior is scored according to the constraint conditions and preset scoring rules.

[0058] In a possible implementation, the test type is divided into a sweeping point type and a non-sweeping point type according to whether the test is a working condition that needs to cover part or all of the engine operation. Specifically, the test that needs to cover part or all of the engine operation is a sweeping point type test, and the test other than the sweeping point type is defined as a non-sweeping point type test. The following describes the specific implementation method of determining the driving behavior score in this step for the sweeping point type test and the non-sweeping point type test.

[0059] (1) Scanning point type

[0060] In a possible implementation manner, for the sweep point test, in this embodiment, all operating points are divided into multiple intervals according to the engine speed and the engine load. For example, Figure 5 A schematic diagram of working condition partitioning provided in Example 2 of the present application, such as Figure 5 As shown, assuming that the engine speed range of the target test is 0-7000r / min and the engine load range is 0-180%, the target test is divided into 7×9=63 operating ranges by taking 1000r / min as the engine speed step and 20% as the engine load step.

[0061] In a possible implementation, in a sweeping point test, engineers can configure the target operating range (such as Figure 5 The target operating interval in the dashed box in the middle), the time required to complete the test corresponding to the target operating interval (i.e., the target cycle), the allowable fluctuation range of the target cycle (i.e., the target cycle range), the size of the expected operating parameter in the target operating interval (i.e., the target value), and the number of times the expected operating parameter reaches the target value in the target operating interval (i.e., the target number). For ease of distinction, in this embodiment, the target cycle, target cycle range, and target value set in the sweeping point test are respectively called the first target cycle, the first target cycle range, and the first target value.

[0062] Since the sweeping point test is a test for a certain operating condition parameter, the test data obtained are all data of the operating condition parameter. In a possible implementation, after a sweeping point test is completed, the driving behavior of the driver can be scored through the following steps in this embodiment:

[0063] a. The actual period for completing the target test can be determined based on the test data collection time.

[0064] For the sake of distinction, the actual cycle in which the target test is completed is called the first actual cycle.

[0065] In a possible implementation, when the remote device sends the test data to the cloud, it can send the collection time of the test data to the cloud together, for example, using the collection time and the target test identifier as the data header and the test data as the data body to generate a data packet and send it to the cloud. Accordingly, in this step, the first actual period can be determined based on the difference between the time of the last data packet of the received target test and the time of the first data packet.

[0066] b. Compare the test data with the first target value in the operating condition configuration data to determine the actual number of times the operating condition parameter value reaches the first target value.

[0067] The actual number is the number of times the operating parameter value in the test data is greater than or equal to the first target value. Since a sweep test is usually a test for one operating parameter, the test data obtained is usually data for one operating parameter. In this step, the actual number is determined by comparing the values ​​of each operating parameter with the first target value.

[0068] c. Determine the driver's driving behavior score based on the first actual cycle, the actual number of times, the first target cycle, the first target cycle range and the target number of times.

[0069] A first evaluation parameter of the driver's driving behavior is determined based on the first actual cycle, the first target cycle, and the first target cycle range. A second evaluation parameter of the driver's driving behavior is determined based on the actual number of times and the target number of times. A driving behavior score of the driver is determined based on the first evaluation parameter and the second evaluation parameter.

[0070] Optionally, the first evaluation parameter = (|first actual cycle - first target cycle|) / first target cycle range, wherein the first target cycle range is the range within which the first actual cycle is allowed to exceed the first target cycle. For example, if the first target cycle is T, the fluctuation amount of the first actual cycle is allowed to be ±Δt, and the value of the first target cycle range is Δt. It is not difficult to see that the closer the first actual cycle is to the first target cycle, the smaller the value of the first evaluation parameter is.

[0071] Optionally, the second evaluation parameter = actual number of times / target number of times, and the closer the actual number of times is to the target number of times, the greater the value of the second evaluation parameter.

[0072] Optionally, the driving behavior score=(1-first evaluation parameter)×second evaluation parameter×100.

[0073] It is not difficult to see that the smaller the first evaluation parameter and the larger the second evaluation parameter, the higher the driving behavior score. The driving behavior score calculated in this way can not only reflect the time spent by the driver in implementing the target test, but also reflect the reaching of the working condition parameter value, thus comprehensively reflecting the driver's driving situation in the calibration test.

[0074] (2) Non-scanning type

[0075] In a possible implementation, in a non-sweeping point test, an engineer can configure the target value, fault tolerance amplitude, fault tolerance number, fault tolerance time, target severity, target severity range, target cycle, and target cycle range of at least two operating parameters through a user device. For ease of distinction, in this embodiment, the target cycle, target cycle range, and target value set in the non-sweeping point test are respectively referred to as the second target cycle, the second target cycle range, and the second target value.

[0076] Among them, the fault tolerance amplitude, fault tolerance times, and fault tolerance time refer to the amplitude, times, and duration of the operating condition parameter value being allowed to exceed the second target value. The severity is used to reflect the change of the operating condition parameter value at the next moment relative to the operating condition parameter value at the previous moment.

[0077] Since non-sweeping point experiments are usually conducted simultaneously on multiple operating parameters, when engineers configure parameters, they need to set different second target values, fault tolerance amplitudes, fault tolerance times, fault tolerance times, target severity levels, target severity ranges, second target cycles, and second target cycle ranges for different operating parameters. Accordingly, when scoring driving behavior, it is necessary to consider the situations of multiple operating parameters at the same time to comprehensively evaluate the driver's driving behavior. In one possible implementation, after a non-sweeping point test is completed, the driver's driving behavior can be scored in this embodiment through the following steps:

[0078] a. According to the collection time of the test data, the second actual period of at least two operating parameters during the implementation of the target test is determined respectively.

[0079] In this step, according to the implementation of the target test, it is necessary to obtain the actual cycle of each operating condition parameter respectively. It is understandable that the actual cycles of different operating condition parameters can be the same or different. b. According to the test data of each operating condition parameter and its second target value, determine the maximum amplitude, the number of times the amplitude is exceeded, the time of exceeding the amplitude, and the actual severity of at least two operating condition parameters.

[0080] In non-sweeping point tests, it is necessary to determine the maximum amplitude, number of times the amplitude is exceeded, time of exceeding the amplitude, and actual severity of different operating parameters based on the test data of different operating parameters and the second target value.

[0081] For example, Figure 6 A schematic diagram of operating parameters provided in Example 2 of the present application, such as Figure 6 As shown in the figure, the values ​​on the wavy lines are the actual operating parameter values ​​of the collected target operating parameters, such as K t1 Indicates the operating parameter value at time t1, K t2 It represents the operating parameter value at time t2 (the next moment after time t1), the horizontal straight line in the middle represents the target value, A represents the fault tolerance amplitude, T represents the actual cycle, t represents the time when the amplitude is exceeded, and n represents the number of times the amplitude is exceeded.

[0082] Among them, the maximum amplitude is the maximum value of the target operating condition parameter within a cycle, such as Figure 6 Amax in can be determined by screening the maximum value from the test data of the target operating parameters.

[0083] t can be determined by calculating the difference between the cut-off point time and the start point time of exceeding the fault tolerance amplitude A. Each time the actual operating condition parameter value exceeds the fault tolerance amplitude A, the number of times n exceeding the amplitude is counted once.

[0084] Assume that the severity is represented by α, Figure 6 For example, the formula M t2 =K t1 ×α+K t2 ×(1-α), calculate the actual severity of the target operating condition parameters at time t2, where M t2 represents the second target value at time t2, which can be determined from the operating condition configuration parameters, K t1 and K t2 It can be determined through test data. By analogy, the actual severity of the target operating parameters at each moment can be calculated.

[0085] It can be understood that the maximum amplitude, the number of times the amplitude is exceeded, the time when the amplitude is exceeded and the actual severity of other operating parameters can all be determined using the above method.

[0086] c. Determine the operating parameter scores of at least two operating parameters based on the second actual cycle, maximum amplitude, number of times the amplitude is exceeded, time of exceeding the amplitude, actual severity, fault tolerance amplitude, number of fault tolerances, fault tolerance time, target severity, target severity range, second target cycle and second target cycle range of each operating parameter.

[0087] Taking the target operating condition parameters as an example, after determining its second actual cycle, maximum amplitude, number of times the amplitude is exceeded, time of exceeding the amplitude, and actual severity, the driving behavior score corresponding to the target operating condition parameters, i.e., the operating condition parameter score, is determined by combining the fault tolerance amplitude, number of fault tolerances, fault tolerance time, target severity, target severity range, second target cycle, and second target cycle range configured by the engineer for the target operating condition parameters.

[0088] In one possible implementation, the maximum amplitude score, the number of times the amplitude is exceeded, the time score for exceeding the amplitude, the actual cycle score, and the severity score of the target operating condition parameter can be determined respectively, and then based on the actual scores of each scoring item and according to a preset algorithm, the operating condition parameter score of the target operating condition parameter can be calculated.

[0089] In a possible implementation, according to the maximum amplitude and the tolerance amplitude, the maximum amplitude score of the target operating condition parameter is determined by the following formula: maximum amplitude score = (1-maximum amplitude / tolerance amplitude) × 100. When the tolerance amplitude is 0 (i.e., it is not allowed to exceed the second target value), when the maximum amplitude is 0, the maximum amplitude score is 100 points, and when the operating condition parameter amplitude is not 0, the maximum amplitude score is 0 points. When the maximum amplitude is greater than or equal to the tolerance amplitude, the maximum amplitude score is 0 points.

[0090] In a possible implementation test, the number of times the amplitude is exceeded and the number of times the fault is tolerated are used to determine the number of times the amplitude is exceeded of the target operating condition parameter by the following formula: number of times the amplitude is exceeded = (1-number of times the amplitude is exceeded / number of times the fault is tolerated) × 100. When the number of times the amplitude is exceeded is greater than or equal to the number of times the fault is tolerated, the number of times the amplitude is exceeded is 0.

[0091] In a possible implementation test, the exceedance amplitude time score of the target operating condition parameter is determined according to the exceedance amplitude time and the tolerance time by the following formula: exceedance amplitude time score = (1-exceedance amplitude time / tolerance time) × 100. When the exceedance amplitude time is greater than or equal to the tolerance time, the exceedance time score is 0.

[0092] In a possible implementation, according to the second actual cycle, the second target cycle and the second target cycle range, the actual cycle score of the target operating condition parameter is determined by the following formula: actual cycle score = {1-|second actual cycle-second target cycle|) / second target cycle range}×100. The second target cycle range is determined in a similar manner to the first target cycle range, which will not be repeated here. When the absolute value of the difference between the second actual cycle and the second target cycle is greater than or equal to the second target cycle range, the actual cycle score is 0.

[0093] In a possible implementation, the severity score of the target operating condition parameter is determined according to the actual severity, the target severity and the target severity range by the following formula: Severity score = {1-|actual severity - target severity|) / target severity range}×100. The target severity range is the range in which the actual severity is allowed to exceed the target severity. For example, if the target severity is α, the fluctuation of the actual severity is allowed to be ±Δα, and the target severity range is Δα. When the absolute value of the difference between the actual severity and the target severity is greater than or equal to the target severity range, the actual cycle score is 0.

[0094] It should be noted that when calculating the severity score, the actual severity can be the average of the actual severity at each moment in the target operating condition parameter test cycle, or the maximum value of the actual severity at each moment in the test cycle. The specific setting can be made according to the actual situation and is not restricted here.

[0095] In a possible implementation, the working condition parameter score of the target working condition parameter is determined by the following formula according to the maximum amplitude score, the number of times the amplitude is exceeded, the time score of the amplitude is exceeded, the actual cycle score and the severity score: working condition parameter score = maximum amplitude score × first constraint item weight + number of times the amplitude is exceeded × second constraint item weight + time score of the amplitude is exceeded × third constraint item weight + actual cycle score × fourth constraint item weight + severity score × fifth constraint item weight, wherein the first constraint item weight, the second constraint item weight, the third constraint item weight, the fourth constraint item weight and the fifth constraint item weight are respectively the preset weights of the maximum amplitude score item, the number of times the amplitude is exceeded, the time score item of the amplitude is exceeded, the actual cycle score item and the severity score item, which can be set by the engineer when configuring the working condition parameters. If the score of one of the scoring items is 0, the working condition parameter score of the target working condition parameter is 0. For example, if the time score of the amplitude is exceeded is 0, the working condition parameter score is directly 0.

[0096] The working condition parameter scores of other working condition parameters can be calculated by referring to this method. It should be noted that if a working condition parameter is constrained by only one or several of the items, then only the score of this item or items needs to be calculated in this step, and only this item or items are considered when calculating the working condition parameter score, that is, the score items that do not participate in the score are removed from the working condition parameter score formula. Exemplarily, if a working condition parameter only constrains the driver's driving behavior through the maximum amplitude, period and severity, the working condition parameter score can be calculated by the following formula: working condition parameter score = maximum amplitude score × weight of the first constraint item + actual period score × weight of the fourth constraint item + severity score × weight of the fifth constraint item.

[0097] d. Determine the driver's driving behavior score based on the operating condition parameter scores and preset weights of at least two operating condition parameters.

[0098] When engineers configure the operating parameters for non-sweeping point tests, they can also set different weights for different operating parameters. After calculating the operating parameter scores of each operating parameter through step c, the driver's driving behavior score is determined by calculating the weighted sum of each operating parameter score and the preset weight.

[0099] For example, assuming that there are four operating parameters involved in a certain test, namely the first operating parameter, the second operating parameter, the third operating parameter and the fourth operating parameter, and the preset weights corresponding to each operating parameter are the first parameter item weight, the second parameter item weight, the third parameter item weight and the fourth parameter item weight, respectively, then the driver's driving behavior score during the test can be calculated by the following formula: driving behavior score = first operating parameter score × first parameter item weight + second operating parameter score × second parameter item weight + third operating parameter score × third parameter item weight + fourth operating parameter score × fourth parameter item weight, if the value of one operating parameter score is 0, then the driver's driving behavior score for this test is 0. By first determining the score of each operating parameter separately, and then determining the comprehensive score of all operating parameters as the driver's driving behavior score based on the preset weights, the driver's driving behavior is constrained from all aspects and dimensions of the calibration test, and a refined analysis of the driver's driving behavior is achieved.

[0100] In this embodiment, the driver's driving behavior score is determined by using different scoring methods based on different test types, so that the obtained driving behavior score can reflect the driver's actual driving level during the calibration test and meet application requirements in different scenarios.

[0101] S204: Display the scoring results through calibration auxiliary equipment.

[0102] After S203, the cloud sends the scoring result to the calibration auxiliary device so that the calibration auxiliary device displays it according to the preset display logic. In this embodiment, the scoring result can include not only the driving behavior score, but also the specific deduction items, so that the scoring result is presented to the driver at a glance, so that the driver can locate and adjust the problematic areas in time.

[0103] Optionally, in this embodiment, during the test, the vehicle status data can also be obtained in real time. After the experiment, the vehicle status data is sorted and counted according to a preset format to generate a driving behavior report, and the driving behavior report is used as part of the scoring results and displayed through the calibration auxiliary device. This is beneficial for the driver to combine the vehicle status data, more deeply locate and adjust the problems corresponding to the deduction items, and improve the efficiency of subsequent tests.

[0104] In this embodiment, a calibration assistance system is set up including a cloud, a calibration assistance device, a remote device and a user device, and the cloud is connected to the calibration assistance device, the remote device and the user device respectively. The cloud obtains the working condition configuration data of the target test through the user device, and obtains the test data generated during the implementation of the target test through the remote device. The driver's driving behavior is scored according to the working condition configuration data and the test data, and the scoring results are displayed through the calibration assistance device to remind the driver to promptly discover problems in driving, and make adjustments and optimizations, thereby improving the efficiency of subsequent tests, shortening the entire calibration test cycle, and achieving the purpose of saving labor costs.

[0105] Optionally, for sweeping point tests, during the test, the present embodiment can also perform real-time analysis on the collected test data based on the operating condition configuration data, such as determining the operating condition interval coverage, test cycle coverage and compliance status of the operating condition parameter values ​​of the completed test, and based on the operating condition interval coverage, test cycle coverage or compliance status of the operating condition parameter values, remind the driver of the operating condition progress through calibration auxiliary equipment.

[0106] Among them, the operating condition interval coverage refers to the ratio of the number of completed operating condition intervals to the number of target operating condition intervals, the test cycle coverage refers to the ratio of the duration of the test to the first target cycle, and the operating condition parameter value compliance refers to whether the operating condition parameter value reaches the first target value or the number of times the operating condition parameter value reaches the first target value.

[0107] Exemplarily, during the test, when it is detected that the actual test cycle reaches 30%, 50%, 80% or 100% and each time the operating parameter value reaches the first target value, the driver is reminded of the test progress through the calibration auxiliary equipment.

[0108] Exemplarily, during the test, when it is detected that the test cycle coverage reaches 100% and the actual number of times the operating condition parameter value reaches the first target value is the target number, the calibration auxiliary equipment is used to remind the driver that the test is completed.

[0109] Exemplarily, during the test, when it is detected that the first actual cycle of the test exceeds the first target cycle range, the driver is reminded of the test failure through the calibration auxiliary equipment.

[0110] In one possible implementation, during the test, for non-sweeping point tests, this embodiment can also perform real-time analysis on the collected test data based on the operating condition configuration data, such as determining by comparison whether the actual test value of the target operating condition parameter exceeds the corresponding target fault tolerance value. If so, the driver is reminded of the operating condition progress through calibration auxiliary equipment.

[0111] The actual test value is the operating parameter value of the target operating parameter in the test data. The target fault tolerance value is the specific value of the configuration data set by the engineer for the target operating parameter, including one or more of the second target value, fault tolerance amplitude, fault tolerance times, fault tolerance time, target severity, target severity range, second target cycle, and second target cycle range.

[0112] Exemplarily, during the test, when the detected and collected operating condition parameter value exceeds the fault-tolerant amplitude A, and the number of times the amplitude exceeds n exceeds the fault-tolerant number or the number of times the amplitude exceeds t exceeds the fault-tolerant time, the driver is reminded of the test failure through the calibration auxiliary equipment to remind the driver to re-test; when the detected and collected operating condition parameter value exceeds the fault-tolerant amplitude A, but the number of times the amplitude exceeds n does not exceed the fault-tolerant number and the number of times the amplitude exceeds t does not exceed the fault-tolerant time, the driver is reminded of standard operation through the calibration auxiliary equipment to avoid test failure; during the test, when the detected and collected operating condition parameter value does not exceed the fault-tolerant amplitude A, the driver is reminded of the test success through the calibration auxiliary equipment to remind the driver to conduct other tests intermittently.

[0113] Exemplarily, during the test, when it is detected that the second actual cycle exceeds the second target cycle range, the calibration auxiliary equipment will remind the driver of the test failure to remind the driver to redo the test; when it is detected that the second actual cycle does not exceed the second target cycle range, the calibration auxiliary equipment will remind the driver of the test success to remind the driver to conduct other tests intermittently.

[0114] Exemplarily, during the test, when it is detected that the actual severity exceeds the target severity range, the calibration auxiliary equipment will remind the driver of the test failure, so as to remind the driver to redo the test; when it is detected that the actual severity does not exceed the target severity range, the calibration auxiliary equipment will remind the driver of the test success, so as to remind the driver to conduct other tests intermittently.

[0115] In this embodiment, the voice broadcast function and / or display function of the calibrated auxiliary device can be used. The specific prompt method and the corresponding modes under different prompt methods (such as prompt sound, display position, etc.) can be set according to actual conditions and are not restricted here.

[0116] In this embodiment, during the test, the driver is reminded of the test progress according to the specific implementation of the test, so that the driver can grasp the progress of the test and the specific operations to be performed next in real time, which has a positive effect on standardizing the driver's driving behavior, improving calibration efficiency, and accelerating calibration progress.

[0117] Embodiment 3

[0118] Figure 7This is a schematic diagram of the structure of a test data processing device provided in Example 3 of the present application. The device can be implemented by software and / or hardware and can be integrated into Figure 1 As shown in the cloud. Figure 7 As shown, the test data processing device 700 in this embodiment includes:

[0119] An acquisition module 710 and a processing module 720 .

[0120] The acquisition module 710 is used to acquire the working condition configuration data of the target test through the user equipment; and acquire the test data generated during the implementation of the target test through the remote equipment;

[0121] The processing module 720 is used to score the driver's driving behavior according to the working condition configuration data and the test data; and display the scoring result through the calibration auxiliary equipment.

[0122] Optionally, if the test type of the target test is a scanning point type, the operating condition configuration data includes a first target cycle, a first target cycle range, a first target value and a target number of times, and the processing module 720 is specifically used to:

[0123] Determine the first actual cycle for completing the target test based on the test data collection time;

[0124] Compare the test data with the first target value to determine the actual number of times the operating condition parameter value reaches the first target value;

[0125] A driving behavior score of the driver is determined based on the first actual cycle, the actual number of times, the first target cycle, the first target cycle range, and the target number of times.

[0126] Optionally, the processing module 720 is specifically configured to:

[0127] Determining a first evaluation parameter of the driver's driving behavior according to the first actual cycle, the first target cycle, and the first target cycle range;

[0128] Determine a second evaluation parameter of the driver's driving behavior according to the actual number of times and the target number of times;

[0129] A driving behavior score of the driver is determined according to the first evaluation parameter and the second evaluation parameter.

[0130] Optionally, if the test type of the target test is non-sweeping type, the operating condition configuration data includes a second target value, a fault tolerance amplitude, a fault tolerance number, a fault tolerance time, a target severity, a target severity range, a second target cycle, and a second target cycle range of at least two operating condition parameters, and the processing module 720 is specifically used to:

[0131] Determine the second actual period of at least two operating condition parameters during the implementation of the target test according to the collection time of the test data;

[0132] Determine the maximum amplitude, the number of times the amplitude is exceeded, the time when the amplitude is exceeded, and the actual severity of at least two operating condition parameters according to the test data of each operating condition parameter and its second target value;

[0133] Determine the operating parameter scores of at least two operating parameters respectively according to the second actual cycle, the maximum amplitude, the number of times the amplitude is exceeded, the time of exceeding the amplitude, the actual severity, the fault tolerance amplitude, the number of times the fault tolerance is exceeded, the fault tolerance time, the target severity, the target severity range, the second target cycle and the second target cycle range of each operating parameter;

[0134] A driving behavior score of the driver is determined based on the operating condition parameter scores of at least two operating condition parameters and preset weights.

[0135] Optionally, the processing module 720 is specifically configured to:

[0136] According to the maximum amplitude and the tolerance amplitude, the maximum amplitude score of the target operating condition parameter is determined;

[0137] Determine the number of times the target operating condition parameter exceeds the amplitude according to the number of times the amplitude exceeds the amplitude and the number of times the error is tolerated;

[0138] Determine the time fraction of the target operating condition parameter exceeding the amplitude according to the exceeding amplitude time and the fault tolerance time;

[0139] Determining an actual cycle fraction of the target operating condition parameter according to the second actual cycle, the second target cycle, and the second target cycle range;

[0140] Determine the severity score of the target operating condition parameter according to the actual severity, the target severity and the target severity range;

[0141] The operating parameter score of the target operating parameter is determined based on the maximum amplitude score, the number of times the amplitude is exceeded, the time score for exceeding the amplitude, the actual cycle score and the severity score.

[0142] Optionally, the operating condition configuration data also includes a target operating condition interval, and the processing module 720 is further used to:

[0143] Based on the working condition configuration data, the test data is analyzed to determine the working condition interval coverage, test cycle coverage and working condition parameter value compliance of the completed test;

[0144] Based on the coverage of the operating range, the coverage of the test cycle or the compliance of the operating parameter values, the driver is reminded of the operating progress through calibration auxiliary equipment.

[0145] Optionally, the processing module 720 is further configured to:

[0146] Based on the working condition configuration data, the test data is analyzed to determine whether the actual test value of the target working condition parameter exceeds the corresponding target fault tolerance value;

[0147] If it exceeds the limit, the driver will be reminded of the working progress through calibration auxiliary equipment.

[0148] Optionally, the processing module 720 is further configured to:

[0149] The calibration data is optimized according to the test data and preset test standards.

[0150] The test data processing device provided in this embodiment can execute the test data processing method provided in the above method embodiment, and has the corresponding functional modules and beneficial effects of the execution method. The implementation principle and technical effects of this embodiment are similar to those of the above method embodiment, and will not be described one by one here.

[0151] Embodiment 4

[0152] Figure 8 A schematic diagram of a cloud structure provided in the fourth embodiment of the present application is shown in FIG. Figure 8 As shown, the cloud 110 includes a memory 111, a processor 112, and a computer program stored in the memory and executable on the processor; the number of the processor 112 in the cloud 110 may be one or more. Figure 8 A processor 112 is taken as an example; the processor 112 and the memory 111 in the cloud 110 may be connected via a bus or other means. Figure 8 The example of connecting through bus is taken in the following.

[0153] The memory 111 is a computer-readable storage medium that can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the acquisition module 710 and the processing module 720 in the embodiment of the present application. The processor 112 executes various functional applications and data processing in the cloud by running the software programs, instructions and modules stored in the memory 111, that is, realizing the above-mentioned test data processing method.

[0154] The memory 111 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 111 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 111 may further include a memory remotely arranged relative to the processor 112, and these remote memories may be connected to the cloud via a grid. Examples of the above-mentioned grid include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0155] Embodiment 5

[0156] Embodiment 5 of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a computer processor, the computer program is used to execute a test data processing method, the method comprising:

[0157] Obtaining the working condition configuration data of the target test through the user equipment;

[0158] Acquire test data generated during the implementation of the target test through remote equipment;

[0159] Score the driver's driving behavior based on the working condition configuration data and test data;

[0160] The scoring results are displayed through calibration auxiliary equipment.

[0161] Of course, the computer-readable storage medium provided in the embodiment of the present application, whose computer program is not limited to the method operations described above, can also execute related operations in the test data processing method provided in any embodiment of the present application.

[0162] Through the above description of the implementation method, the technicians in the relevant field can clearly understand that the present application can be implemented with the help of software and necessary general hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application can be essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or grid device, etc.) to execute the methods described in each embodiment of the present application.

[0163] It is worth noting that in the embodiment of the above-mentioned test data processing device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application.

[0164] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A test data processing method, characterized in that: The method is applied to a cloud in a calibration assistance system, wherein the calibration assistance system further includes a calibration assistance device, a remote device and a user device, wherein the cloud is connected to the calibration assistance device, the remote device and the user device respectively, and the calibration assistance device and the remote device are both arranged on a vehicle, and wherein the method includes: Acquiring the operating condition configuration data of the target test through the user equipment; Acquiring test data generated during the implementation of the target test through the remote device; Scoring the driver's driving behavior according to the operating condition configuration data and the test data; Displaying the scoring result by means of the calibration auxiliary device; Wherein, if the test type of the target test is a scanning point type, the operating condition configuration data includes a first target cycle, a first target cycle range, a first target value and a target number of times, and the driver's driving behavior is scored according to the operating condition configuration data and the test data, including: Determining a first actual cycle for completing the target test according to the collection time of the test data; Comparing the test data with the first target value to determine the actual number of times the operating condition parameter value reaches the first target value; determining a driving behavior score of the driver according to the first actual cycle, the actual number of times, the first target cycle, the first target cycle range, and the target number of times; Wherein, if the test type of the target test is non-sweeping point type, the operating condition configuration data includes a second target value, a fault tolerance amplitude, a fault tolerance number, a fault tolerance time, a target severity, a target severity range, a second target cycle, and a second target cycle range of at least two operating condition parameters, and the driver's driving behavior is scored according to the operating condition configuration data and the test data, including: Determining, according to the collection time of the test data, the second actual period of the at least two operating condition parameters during the implementation of the target test; Determining the maximum amplitude, the number of times the amplitude is exceeded, the time when the amplitude is exceeded, and the actual severity of the at least two operating parameters according to the test data of each operating parameter and its second target value; Determine the operating parameter scores of the at least two operating parameters according to the second actual cycle, the maximum amplitude, the number of times the amplitude is exceeded, the time of exceeding the amplitude, the actual severity, the fault tolerance amplitude, the number of times the fault tolerance is exceeded, the fault tolerance time, the target severity, the target severity range, the second target cycle and the second target cycle range of each operating parameter; The driving behavior score of the driver is determined according to the operating condition parameter scores and preset weights of the at least two operating condition parameters.

2. The method according to claim 1, characterized in that The determining the driver's driving behavior score according to the first actual cycle, the actual number of times, the first target cycle, the first target cycle range, and the target number of times includes: determining a first evaluation parameter of the driver's driving behavior according to the first actual cycle, the first target cycle and the first target cycle range; determining a second evaluation parameter of the driver's driving behavior according to the actual number of times and the target number of times; A driving behavior score of the driver is determined according to the first evaluation parameter and the second evaluation parameter.

3. The method according to claim 1, characterized in that According to the second actual cycle, maximum amplitude, number of times the amplitude is exceeded, time of exceeding the amplitude, actual severity, fault tolerance amplitude, number of times the fault tolerance is exceeded, fault tolerance time, target severity, target severity range, second target cycle and second target cycle range of the target operating condition parameter, the operating condition parameter score of the target operating condition parameter is determined, including: Determining a maximum amplitude score of the target operating condition parameter according to the maximum amplitude and the fault tolerance amplitude; Determining a score of the number of times the target operating condition parameter exceeds the amplitude according to the number of times the amplitude exceeds the amplitude and the number of times the fault is allowed to exceed; Determine an excess amplitude time fraction of the target operating condition parameter according to the excess amplitude time and the fault tolerance time; determining an actual cycle fraction of the target operating condition parameter according to the second actual cycle, the second target cycle and the second target cycle range; Determining a severity score of the target operating condition parameter according to the actual severity, the target severity, and the target severity range; The operating parameter score of the target operating parameter is determined according to the maximum amplitude score, the number of times the amplitude is exceeded score, the time score when the amplitude is exceeded score, the actual cycle score and the severity score.

4. The method according to claim 1, characterized in that: The operating condition configuration data also includes a target operating condition interval. Before scoring the driver's driving behavior based on the operating condition configuration data and the test data, the method further includes: Based on the working condition configuration data, the test data is analyzed to determine the working condition interval coverage, test cycle coverage and working condition parameter value compliance of the completed test; Based on the coverage of the operating condition interval, the coverage of the test cycle or the compliance of the operating condition parameter value, the driver is reminded of the operating condition progress through the calibration auxiliary equipment.

5. The method according to claim 1, characterized in that Before scoring the driver's driving behavior according to the operating condition configuration data and the test data, the method further includes: Based on the operating condition configuration data, the test data is analyzed to determine whether an actual test value of a target operating condition parameter exceeds a corresponding target fault tolerance value; If it exceeds, the driver will be reminded of the working progress through the calibration auxiliary equipment.

6. The method according to any one of claims 1 to 5, characterized in that: After the scoring result is displayed by the calibration auxiliary device, the method further includes: The calibration data is optimized according to the test data and the preset test standard.

7. A test data processing device, characterized in that: A cloud integrated in a calibration assistance system, wherein the calibration assistance system further includes a calibration assistance device, a remote device, and a user device, wherein the cloud is connected to the calibration assistance device, the remote device, and the user device, respectively, and the calibration assistance device and the remote device are both arranged on a vehicle, and wherein the device includes: An acquisition module, used to acquire the working condition configuration data of the target test through the user device; and acquire the test data generated during the implementation of the target test through the remote device; A processing module, used for scoring the driver's driving behavior according to the working condition configuration data and the test data; and displaying the scoring result through the calibration auxiliary device; Wherein, if the test type of the target test is a scanning point type, the operating condition configuration data includes a first target cycle, a first target cycle range, a first target value and a target number of times, and the processing module is specifically used to determine the first actual cycle of completing the target test according to the collection time of the test data; compare the test data with the first target value to determine the actual number of times the operating condition parameter value reaches the first target value; determine the driver's driving behavior score according to the first actual cycle, the actual number of times, the first target cycle, the first target cycle range and the target number of times; Among them, if the test type of the target test is a non-sweeping point type, the operating condition configuration data includes a second target value, a fault tolerance amplitude, a fault tolerance number, a fault tolerance time, a target severity, a target severity range, a second target cycle and a second target cycle range of at least two operating condition parameters, and the processing module is specifically used to determine the second actual cycle of the at least two operating condition parameters during the implementation of the target test according to the acquisition time of the test data; determine the maximum amplitude, the number of times the amplitude is exceeded, the time of exceeding the amplitude and the actual severity of the at least two operating condition parameters according to the test data of each operating condition parameter and its second target value; determine the operating condition parameter scores of the at least two operating condition parameters according to the second actual cycle, the maximum amplitude, the number of times the amplitude is exceeded, the time of exceeding the amplitude, the actual severity, the fault tolerance amplitude, the number of times the fault tolerance, the fault tolerance time, the target severity, the target severity range, the second target cycle and the second target cycle range of each operating condition parameter; determine the driving behavior score of the driver according to the operating condition parameter scores of the at least two operating condition parameters and preset weights.

8. A cloud comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the test data processing method as described in any one of claims 1-6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the test data processing method as described in any one of claims 1 to 6 is implemented.

10. A calibration assistance system, characterized in that: It includes a calibration auxiliary device, a remote device, a user device and a cloud as described in claim 8, wherein the cloud is connected to the calibration auxiliary device, the remote device and the user device respectively, and the calibration auxiliary device and the remote device are both arranged on the vehicle.

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