A method, apparatus, device, and storage medium for determining synchronization time deviation.

Abstract

This application discloses a method, apparatus, device, and storage medium for determining synchronization time deviation. The method includes: acquiring data from the on-board system and the true system of a test vehicle at each time point within a preset time period; determining, for multiple preset time offsets, first detection data obtained by interpolating the on-board system data after offsetting by each time offset, or second detection data obtained by interpolating the true system data after offsetting by each time offset; calculating a first set of correlation coefficients between the true system data and the first detection data obtained after offsetting by each time offset, or calculating a second set of correlation coefficients between the on-board system data and the second detection data obtained after offsetting by each time offset; and determining the time offset corresponding to the largest correlation coefficient in the first or second set of correlation coefficients as the synchronization time deviation. The method provided by this application can improve the accuracy of the determined synchronization time deviation.

Description

Technical Field

[0001] This application belongs to the field of sensor evaluation technology, and in particular relates to a method, apparatus, device and storage medium for determining synchronization time deviation. Background Technology

[0002] The process of testing automotive sensors includes multiple stages such as sensor detection, computation and processing, sending the detection results to the bus, and storing the data records received from the bus. For different testing systems, the time consumed in these transmission, processing, and storage stages varies greatly. This results in a significant time deviation between the data measured by the on-board system installed on the same test vehicle and the data measured by the true system. This time deviation will adversely affect the accuracy of subsequent evaluations.

[0003] Currently, time deviations are estimated by technicians based on experience, but the estimated time deviations are usually not very accurate. Summary of the Invention

[0004] This application provides a method, apparatus, device, and storage medium for determining synchronization time deviation, which can improve the accuracy of time deviation.

[0005] In a first aspect, embodiments of this application provide a method for determining synchronization time deviation, the method comprising:

[0006] Acquire data from the onboard system and the true value system of the test vehicle at each time point within a preset time period for measuring the target object;

[0007] For each of the preset multiple time offsets, determine the data of the vehicle system after offsetting each time offset, or determine the data of the true system after offsetting each time offset;

[0008] The first detection data is obtained by interpolating the data of the vehicle system after offsetting each time offset, based on the time point of the data of the true system; or the second detection data is obtained by interpolating the data of the true system after offsetting each time offset, based on the time point of the data of the vehicle system.

[0009] The first set of correlation coefficients for the first detection data obtained by interpolating the data of the true system with each time offset, or the second set of correlation coefficients for the second detection data obtained by interpolating the data of the vehicle system with each time offset;

[0010] The time offset corresponding to the largest correlation coefficient in the first or second set of correlation coefficients is determined as the synchronization time deviation between the data of the on-board system of the test vehicle and the data of the true system.

[0011] In one possible implementation, the first set of correlation coefficients is calculated between the data of the truth system and the first set of detection data obtained by offsetting each time offset and interpolating, including:

[0012] Based on the data from the truth system, determine the first trend of change in the data of the truth system;

[0013] Based on the first detection data obtained by offsetting each time offset and interpolating, determine the second trend of change of the first detection data obtained by offsetting each time offset and interpolating.

[0014] Calculate the correlation coefficient between the first trend of change and each second trend of change to obtain the first set of correlation coefficients.

[0015] In one possible implementation, a second set of correlation coefficients is calculated between the data from the on-board system and the second detection data obtained by interpolation at each time offset, including:

[0016] Based on the data from the vehicle system, determine the third trend of change in the vehicle system data;

[0017] Based on the second detection data obtained by offsetting each time offset and interpolating, determine the fourth trend of change of the second detection data obtained by offsetting each time offset and interpolating.

[0018] Calculate the correlation coefficient between the third trend and each fourth trend to obtain the second set of correlation coefficients.

[0019] In one possible implementation, the time offset corresponding to the largest correlation coefficient in the first or second set of correlation coefficients is determined as the synchronization time deviation between the data of the test vehicle's onboard system and the data of the ground truth system, including:

[0020] The first target correspondence between multiple time offsets and the first set of correlation coefficients is obtained by fitting a preset function to fit the correspondence between multiple time offsets and the first set of correlation coefficients; or the second target correspondence between multiple time offsets and the second set of correlation coefficients is obtained by fitting a preset function to fit the correspondence between multiple time offsets and the second set of correlation coefficients.

[0021] The time offset with the largest correlation coefficient in either the first or second target correspondence is determined as the synchronization time deviation between the data of the on-board system of the test vehicle and the data of the true system.

[0022] In one possible implementation, before determining the data of the on-board system offset by each of a preset plurality of time offsets, or determining the data of the truth system offset by each time offset, the method further includes:

[0023] Obtain the first measurement cycle of the vehicle system;

[0024] The first unit time is calculated based on the first test cycle and the preset time granularity;

[0025] Calculate the product of the first unit time and the preset unit time share to obtain multiple time offsets;

[0026] or,

[0027] Obtain the second measurement cycle of the true value system;

[0028] The second unit time is calculated based on the second measurement cycle and the preset time granularity;

[0029] Calculate the product of the second unit time and the preset unit time share to obtain multiple time offsets.

[0030] In one possible implementation, data from the onboard system and the ground truth system, measured by the test vehicle at each time point within a preset time period, are acquired, including:

[0031] Data measured by the on-board system and the ground truth system within the same time period are extracted from the data measured by the on-board system and the ground truth system of the test vehicle, respectively.

[0032] In one possible implementation, the first detection data is obtained by interpolating the data of the vehicle system after offsetting each time point, using the time point of the data from the truth system as a reference, including:

[0033] When the time point of the data of the vehicle system after each time offset is not exactly the same as the time point of the data of the true system, the time point of the data of the true system is used as the reference, and interpolation is performed in the data of the vehicle system after each time offset to obtain the first detection data with the same time point as the data of the true system.

[0034] Alternatively, using the time point of the data from the vehicle-mounted system as a reference, interpolation is performed on the true data from the system after offsetting by each time offset to obtain the second detection data, including:

[0035] When the time point of the data in the true system after each time offset is not exactly the same as the time point of the data in the vehicle system, the time point of the data in the vehicle system is used as the reference, and interpolation is performed in the data in the true system after each time offset to obtain the second detection data with the same time point as the data in the vehicle system.

[0036] Secondly, embodiments of this application provide an apparatus for determining synchronization time deviation, the apparatus comprising:

[0037] The acquisition module is used to acquire the data of the on-board system and the true value system of the test vehicle measuring the target object at each time point within a preset time period;

[0038] The determination module is used to determine the data of the on-board system after offsetting each time offset, or to determine the data of the true system after offsetting each time offset;

[0039] The interpolation module is used to interpolate the data of the vehicle system after offsetting each time offset, based on the time point of the data of the truth system, to obtain the first detection data, or to interpolate the data of the truth system after offsetting each time offset, based on the time point of the data of the vehicle system, to obtain the second detection data.

[0040] The calculation module is used to calculate the first set of correlation coefficients of the data of the true value system and the first detection data obtained by interpolation after offsetting each time offset, or to calculate the second set of correlation coefficients of the data of the vehicle system and the second detection data obtained by interpolation after offsetting each time offset;

[0041] The determination module is also used to determine the time offset corresponding to the largest correlation coefficient in the first or second set of correlation coefficients as the synchronization time deviation between the data of the on-board system of the test vehicle and the data of the true system.

[0042] In one possible implementation, the computation module is specifically used for:

[0043] Based on the data from the truth system, determine the first trend of change in the data of the truth system;

[0044] Based on the first detection data obtained by offsetting each time offset and interpolating, determine the second trend of change of the first detection data obtained by offsetting each time offset and interpolating.

[0045] Calculate the correlation coefficient between the first trend of change and each second trend of change to obtain the first set of correlation coefficients.

[0046] In one possible implementation, the computation module is specifically used for:

[0047] Based on the data from the vehicle system, determine the third trend of change in the vehicle system data;

[0048] Based on the second detection data obtained by offsetting each time offset and interpolating, determine the fourth trend of change of the second detection data obtained by offsetting each time offset and interpolating.

[0049] Calculate the correlation coefficient between the third trend and each fourth trend to obtain the second set of correlation coefficients.

[0050] In one possible implementation, a module is defined, specifically for:

[0051] The first target correspondence between multiple time offsets and the first set of correlation coefficients is obtained by fitting a preset function to fit the correspondence between multiple time offsets and the first set of correlation coefficients; or the second target correspondence between multiple time offsets and the second set of correlation coefficients is obtained by fitting a preset function to fit the correspondence between multiple time offsets and the second set of correlation coefficients.

[0052] The time offset with the largest correlation coefficient in either the first or second target correspondence is determined as the synchronization time deviation between the data of the on-board system of the test vehicle and the data of the true system.

[0053] In one possible implementation, the acquisition module is also used to acquire the first measurement cycle of the vehicle system;

[0054] The calculation module is also used to calculate the first unit time based on the first test cycle and the preset time granularity; it is also used to calculate the product of the first unit time and the preset unit time share to obtain multiple time offsets;

[0055] or,

[0056] The acquisition module is also used to acquire the second measurement period of the truth system;

[0057] The calculation module is also used to calculate the second unit time based on the second measurement cycle and the preset time granularity; it is also used to calculate the product of the second unit time and the preset unit time share to obtain multiple time offsets.

[0058] Thirdly, embodiments of this application provide an electronic device, the device including: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the method as described in the first aspect or any possible implementation of the first aspect.

[0059] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions that, when executed by a processor, implement the method as described in the first aspect or any possible implementation thereof.

[0060] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform a method as described in the first aspect or any possible implementation thereof.

[0061] This application provides a method, apparatus, device, and storage medium for determining synchronization time deviation. Multiple time offsets are preset, and the correlation coefficient between the data from the onboard system and the data from the true system measured by the test vehicle on the target test object is determined at each time offset. The time offset corresponding to the largest correlation coefficient is taken as the synchronization time deviation between the onboard system data and the true system data. Since the correlation coefficient between the onboard system data and the true system data is the largest under the synchronization time deviation, the synchronization time deviation is an accurate time deviation, thereby improving the accuracy of the determined synchronization time deviation. Attached Figure Description

[0062] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0063] Figure 1 This is a schematic flowchart of a method for determining synchronization time deviation provided in an embodiment of this application;

[0064] Figure 2 This is a schematic diagram illustrating the correspondence between multiple time offsets and a second set of correlation coefficients after a first set of correlation coefficients, provided in an embodiment of this application.

[0065] Figure 3 This is a schematic diagram of a preset function fitting a first target correspondence or a second target correspondence, provided in an embodiment of this application.

[0066] Figure 4 This is a schematic diagram of a device structure for determining synchronization time deviation provided in an embodiment of this application;

[0067] Figure 5 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0068] The features and exemplary embodiments of various aspects of this application will now be described in detail. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only configured to explain this application and are not configured to limit this application. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples of this application.

[0069] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0070] The process of testing automotive sensors involves multiple stages, including sensor detection, computational processing, transmitting the detection results to the bus, and storing the data received from the bus. Different testing systems consume significantly different amounts of time in these transmission, processing, and storage stages. This results in a noticeable time discrepancy between the data measured by the onboard system installed on the same test vehicle and the data measured by the true system. This time discrepancy negatively impacts the accuracy of subsequent evaluations. Currently, technicians estimate the time discrepancy based on experience, but these estimates are typically inaccurate.

[0071] This application provides a method, apparatus, device, and storage medium for determining synchronization time deviation. Multiple time offsets are preset, and the correlation coefficient between the data from the vehicle's onboard system and the data from the true system is determined at each time offset. The time offset corresponding to the largest correlation coefficient is taken as the synchronization time deviation between the data from the vehicle's onboard system and the data from the true system. Since the correlation coefficient between the data from the vehicle's onboard system and the data from the true system is the largest at the synchronization time deviation, the synchronization time deviation is an accurate time deviation, thus improving the accuracy of the time deviation.

[0072] The method provided in this application is executed by a terminal with data acquisition and data processing functions, such as a calculator, server, or other device.

[0073] To facilitate understanding of the proposed solution, the following explanations of the terms used in this application will be provided.

[0074] The correlation coefficient is a statistical indicator used to reflect the degree of correlation between variables. It is calculated using the product-moment method, which is based on the deviations of two variables from their respective means. The correlation between the two variables is reflected by multiplying these two deviations.

[0075] The following will combine Figure 1 This application provides a detailed description of a method for determining synchronization time deviation.

[0076] like Figure 1 As shown, the method may include the following steps:

[0077] S110, acquire the data of the on-board system and the true value system of the test vehicle measuring the target object at each time point within a preset time period.

[0078] The test vehicle is equipped with both an onboard system and a truth system. The target measurement object refers to the object of the test data of the test vehicle. The data of the onboard system refers to the data measured by the onboard system, and the data of the truth system refers to the data measured by the truth system. The preset time period includes multiple continuous measurement cycles of the onboard system or the truth system. The time point within the preset time period refers to the moment when the onboard system and the truth system acquire data within multiple continuous measurement cycles.

[0079] Data on the target object measured by the on-board system and the ground truth system within the same time period are extracted from the data measured by the on-board system and the ground truth system, respectively.

[0080] In one example, the target test object could be a three-dimensional object, a lane line, or a traffic sign.

[0081] S120, for each of the preset multiple time offsets, determines the data of the vehicle system after offsetting each time offset.

[0082] The system offsets each time point within a preset time period by a time offset, resulting in the offset time point. The data of the in-vehicle system at the offset time point and the data at the time point before the offset are used as the data of the in-vehicle system after each time offset. For each of the multiple time offsets, the data of the in-vehicle system is time-offset separately, resulting in the data of the in-vehicle system after each time offset. This data of the in-vehicle system after each time offset is used as the data of the in-vehicle system after each time offset.

[0083] Several time offsets are preset by technicians according to their needs.

[0084] In one example, the data of the vehicle system at each time point within a preset time period includes the data measured at the time point of each measurement data of the vehicle system between time T1 and time T2. One of the multiple time offsets is T3. The sum of the time point t of each measurement data between time T1 and time T2 and T3 is calculated. The data of the vehicle system at time point t is taken as the data of the vehicle system at time point t+T3, and the data of the vehicle system after offset T3 is obtained.

[0085] S130: Using the time point of the data in the true value system as a reference, interpolate the data in the vehicle system after offsetting each time offset to obtain the first detection data.

[0086] The time point of the data in the vehicle system after each time offset may not be exactly the same as the time point of the data in the true system. Using the time point of the data in the true system as the reference, interpolation is performed on the data in the vehicle system after each time offset to obtain the first detection data with the same time point as the data in the true system.

[0087] In one example, the data in the truth system includes time points t1, and the data in the vehicle system after offsetting by a time offset T3 includes time points t1-Δt1 and t1+Δt2. The data in the vehicle system at time point t1-Δt1 is X, and the data in the vehicle system at time point t1+Δt2 is Y. Therefore, the data interpolated from the vehicle system data after offset T3, with time point t1 as the point of difference, is... The first detection data after offsetting T3 and interpolation includes data Z at time point t1.

[0088] S140, calculate the first set of correlation coefficients of the first detection data obtained by interpolating the data of the true system with each time offset.

[0089] The first set of correlation coefficients for the first detection data is obtained by calculating the data of the true system and the offset at each time offset, and then interpolating them.

[0090] The first set of correlation coefficients includes the correlation coefficients between the data from the true system and the first detection data obtained by offsetting each time offset and interpolating.

[0091] S150, determine the time offset corresponding to the largest correlation coefficient in the first set of correlation coefficients, which is the synchronization time deviation between the data of the on-board system of the test vehicle and the data of the true system.

[0092] The correlation coefficient between the data of the truth system and the first detection data obtained after offsetting by a time offset is the correlation coefficient corresponding to that time offset. The values ​​of multiple correlation coefficients in the first group of correlation coefficients are compared to obtain the maximum correlation coefficient in the first group of correlation coefficients. The time offset corresponding to the maximum correlation coefficient is determined as the synchronization time deviation.

[0093] Alternatively, the following steps can be included after S110:

[0094] S160, for each of the preset multiple time offsets, determine the true value system data after offsetting each time offset.

[0095] Offset each time point within a preset time period by a time offset to obtain the offset time point. Compare the data of the truth system at the offset time point with the data of the time point before the offset to determine the data of the truth system after each time offset. For each of the multiple time offsets, time offset the data of the truth system separately to obtain the data of the truth system after each time offset. Use the data of the truth system after each time offset as the data of the truth system after each time offset.

[0096] Several time offsets are preset by technicians according to their needs.

[0097] In one example, the data of the truth system at each time point within a preset time period includes the data measured at the time point of each measurement data in the truth system between time T4 and time T5. One of the multiple time offsets is T6. The sum of the time point t and T6 for each measurement data between time T4 and time T5 is calculated. The data of the truth system at time point t is used as the data of the truth system at time point t+T6 to obtain the data of the truth system after offset T6.

[0098] S170, using the time point of the data from the vehicle system as a reference, interpolates the data from the true system after offsetting each time offset to obtain the second detection data.

[0099] The time point of the data in the true system after each time offset may not be exactly the same as the time point of the data in the vehicle system. Using the time point of the data in the vehicle system as a reference, interpolation is performed on the data in the true system after each time offset to obtain the second detection data with the same time point as the data in the vehicle system.

[0100] In one example, the data from the vehicle system includes time points t2, and the data from the truth system after offsetting by a time offset T6 includes time points t2-Δt3 and t2+Δt4. The data from the truth system at time point t2-Δt3 is M, and the data from the truth system at time point t2+Δt4 is N. Therefore, the data interpolated from the truth system data after offset T6, with time point t2, is: The second detection data after offsetting T6 and interpolation includes data P at time point t2.

[0101] S180, calculate the second set of correlation coefficients for the second detection data obtained by interpolating the data of the vehicle system with each time offset.

[0102] The second set of correlation coefficients for the second detection data is obtained by calculating the data of the vehicle system and the offset at each time offset, and then interpolating them.

[0103] The second set of correlation coefficients includes the correlation coefficients between the data from the vehicle system and the second detection data obtained by interpolating each time offset.

[0104] S190, determine the time offset corresponding to the largest correlation coefficient in the second set of correlation coefficients as the synchronization time deviation.

[0105] The correlation coefficient between the data from the vehicle system and the second detection data obtained by offsetting by a time offset and interpolating is the correlation coefficient corresponding to that time offset. The values ​​of multiple correlation coefficients in the second set of correlation coefficients are compared to obtain the maximum correlation coefficient in the second set of correlation coefficients. The time offset corresponding to the maximum correlation coefficient is determined as the synchronization time deviation.

[0106] The method provided in this application pre-sets multiple time offsets. For each time offset, the data of the vehicle system at each time point within a preset time period is time-offset and interpolated to obtain first detection data after offsetting and interpolating by each time offset. The correlation coefficient between the first detection data obtained after offsetting by each time offset and the data of the true system is determined, and the time offset corresponding to the largest correlation coefficient is taken as the synchronization time deviation between the data of the vehicle system and the data of the true system. Alternatively, for each time offset, the data of the true system at each time point within a preset time period is time-offset and interpolated to obtain second detection data after offsetting and interpolating by each time offset. The correlation coefficient between the second detection data obtained after offsetting by each time offset and the data of the vehicle system is determined, and the time offset corresponding to the largest correlation coefficient is taken as the synchronization time deviation between the data of the vehicle system and the data of the true system. Since the correlation coefficient between the data of the vehicle system and the data of the true system is the largest under the synchronization time deviation, the synchronization time deviation is an accurate time deviation, thereby improving the accuracy of the determined time deviation.

[0107] In some embodiments, S140, calculating the first set of correlation coefficients between the data of the true system and the first set of detection data obtained by offsetting each time offset and interpolating, may include the following steps:

[0108] First, based on the data from the truth system, determine the first trend of change in the data of the truth system.

[0109] Calculate the difference between the true system data at a given time point and the true system data at the previous time point, and determine the trend of the true system data at that time point based on the difference. For the true system data at each time point within a preset time period, determine the trend of the true system data at each time point to obtain the first trend of the true system data.

[0110] In one example, when the difference is greater than 0, the trend is increasing; when the difference is less than 0, the trend is decreasing; and when the difference is equal to 0, the trend is stable.

[0111] Then, based on the first detection data obtained after offsetting each time offset, the second trend of change of the first detection data obtained after offsetting each time offset is determined.

[0112] The first detection data obtained after offsetting by each time offset includes the detection data obtained after offsetting by each time offset. For each detection data obtained after offsetting by each time offset, the difference between the detection data at a time point and the detection data at the previous time point is calculated. The trend of change of the detection data at that time point is determined based on the difference. For the detection data at each time point, the trend of change of the detection data at each time point is determined respectively, and the second trend of change of the first detection data obtained after offsetting by each time offset is obtained.

[0113] In one example, when the difference is greater than 0, the trend is increasing; when the difference is less than 0, the trend is decreasing; and when the difference is equal to 0, the trend is stable.

[0114] Finally, the correlation coefficients between the first trend and each second trend are calculated to obtain the first set of correlation coefficients.

[0115] For each second trend, the correlation coefficient between the trend at each time point in the first trend and the trend at each time point in the second trend is calculated to obtain the correlation coefficient between the first trend and each second trend. The correlation coefficient between the first trend and each second trend is used as the first set of correlation coefficients.

[0116] The method provided in this application provides the correlation coefficient between the changing trend of the data in the true value system and the changing trend of the first detection data obtained after offsetting each time offset, which provides a basis for determining the time offset corresponding to the maximum correlation coefficient. Based on the correlation coefficient, the accuracy of the time deviation can be improved.

[0117] In some embodiments, S150: Determining the time offset corresponding to the largest correlation coefficient in the first set of correlation coefficients as the synchronization time deviation between the data of the on-board system of the test vehicle and the data of the true system may include the following steps:

[0118] First, a preset function is used to fit the correspondence between multiple time offsets and the first set of correlation coefficients to obtain the first target correspondence between multiple time offsets and the first set of correlation coefficients.

[0119] In actual measurement processes, there are not only time discrepancies between the data detected by the on-board system and the data detected by the true value system, but also numerical errors caused by differences in the measurement systems. For example, ... Figure 2 As shown, the horizontal axis represents the time offset, and the vertical axis represents the correlation coefficient in the first group of correlation coefficients. The curve drawn based on the correspondence between the correlation coefficient in the first group of correlation coefficients and the time offset is not smooth enough and has spikes.

[0120] To more accurately determine the synchronization time deviation, a preset function is used to fit the correspondence between multiple time offsets and the first set of correlation coefficients, thereby obtaining the first target correspondence between multiple time offsets and the first set of correlation coefficients.

[0121] In one example, the preset function is a quadratic function y = ax. 2 When fitting the correlation between multiple time offsets and the first set of correlation coefficients, the values ​​of coefficients a, b, and c in the quadratic function are determined to obtain a smoother quadratic function curve, such as... Figure 3 As shown, the horizontal axis represents the time offset, and the vertical axis represents the correlation coefficient in the first set of correlation coefficients after fitting. The correspondence after fitting with a preset function is the first target correspondence between multiple time offsets and the first set of correlation coefficients.

[0122] Then, the time offset with the largest correlation coefficient in the first target correspondence is determined as the synchronization time deviation between the data of the on-board system of the test vehicle and the data of the true system.

[0123] Compare the values ​​of multiple correlation coefficients in the first target correspondence, and take the time offset with the largest correlation coefficient as the synchronization time deviation between the data of the test vehicle's on-board system and the data of the true system.

[0124] In one example, the first target correspondence is represented by the curve of a quadratic function, such as... Figure 3 As shown, the horizontal axis of the quadratic function represents the time offset, and the vertical axis represents the correlation coefficient in the first set of correlation coefficients after fitting. The horizontal axis value corresponding to the vertex of the quadratic function curve is -25, so the synchronization time deviation is -25.

[0125] The method provided in this application uses a preset function to fit the correspondence between multiple time offsets and a first set of correlation coefficients, eliminating the interference of numerical errors caused by differences in measurement systems and improving the accuracy of synchronization time deviation.

[0126] In some embodiments, before S120: determining the data of the vehicle system after offsetting each of the preset multiple time offsets, the following steps may also be included:

[0127] First, obtain the first measurement cycle of the vehicle system.

[0128] Extract the first measurement cycle of the vehicle system from the data recorded by the vehicle system.

[0129] Then, the first unit time is calculated based on the first test cycle and the preset time granularity.

[0130] Calculate the quotient of the first measurement cycle and the preset time granularity to obtain the first unit time.

[0131] In one example, the preset time granularity is 10, and the first measurement period is 'a', then the first unit time is...

[0132] Finally, the product of the first unit time and the preset unit time share is calculated to obtain multiple time offsets.

[0133] The preset unit time share includes multiple values. The product of the first unit time and each value in the preset unit time share is calculated to obtain multiple time offsets.

[0134] In one example, the first unit of time is The preset unit time share includes every integer in the range [-100, 100], for a total of 201 integers. Therefore, calculate the sum of each integer in the range [-100, 100] and... The product of these two values ​​yields 201 time offsets.

[0135] The method provided in this application provides multiple time offsets, which provide a data basis for determining the synchronization time deviation among these multiple time offsets.

[0136] In some embodiments, S180, calculating the second set of correlation coefficients between the data from the vehicle system and the second detection data obtained by interpolation after offsetting each time offset may include the following steps:

[0137] First, based on the data from the vehicle system, determine the third trend of change in the vehicle system data.

[0138] Calculate the difference between the vehicle system data at a given time point and the data at the previous time point, and determine the trend of the vehicle system data at that time point based on the difference. For the vehicle system data at each time point within a preset time period, determine the trend of the vehicle system data at each time point to obtain the third trend of the vehicle system data.

[0139] In one example, when the difference is greater than 0, the trend is increasing; when the difference is less than 0, the trend is decreasing; and when the difference is equal to 0, the trend is stable.

[0140] Then, based on the second detection data obtained by offsetting each time offset and interpolating, the fourth trend of change of the second detection data obtained by offsetting each time offset and interpolating is determined.

[0141] The second detection data obtained after offsetting and interpolating each time offset includes the detection data obtained after offsetting and interpolating each time offset. For each detection data obtained after offsetting and interpolating each time offset, the difference between the detection data at a time point and the detection data at the previous time point is calculated. The change trend of the detection data at that time point is determined based on the difference. For the detection data at each time point, the change trend of the detection data at each time point is determined respectively, and the fourth change trend of the second detection data obtained after offsetting each time offset is obtained.

[0142] In one example, when the difference is greater than 0, the trend is increasing; when the difference is less than 0, the trend is decreasing; and when the difference is equal to 0, the trend is stable.

[0143] Finally, the correlation coefficients between the third trend and each of the fourth trends are calculated to obtain the second set of correlation coefficients.

[0144] For each third trend, the correlation coefficient between the trend at each time point in the third trend and the trend at each time point in the fourth trend is calculated to obtain the correlation coefficient between the third trend and each fourth trend. The correlation coefficient between the third trend and each fourth trend is used as the second set of correlation coefficients.

[0145] The method provided in this application provides the correlation coefficient between the changing trend of the data of the vehicle system and the changing trend of the second detection data obtained after offsetting each time offset, which provides a basis for determining the time offset corresponding to the maximum correlation coefficient. Based on the correlation coefficient, the accuracy of the time deviation can be improved.

[0146] In some embodiments, S190: Determining the time offset corresponding to the largest correlation coefficient in the second set of correlation coefficients as the time deviation between the data of the test vehicle's on-board system and the data of the true system may include the following steps:

[0147] First, a preset function is used to fit the correspondence between multiple time offsets and the second set of correlation coefficients to obtain the second target correspondence between multiple time offsets and the second set of correlation coefficients.

[0148] In actual measurement processes, there are not only time discrepancies between the data detected by the on-board system and the data detected by the true value system, but also numerical errors caused by differences in the measurement systems. For example, ... Figure 2As shown, the horizontal axis represents the time offset, and the vertical axis represents the correlation coefficient in the second set of correlation coefficients. The curve plotted based on the correspondence between the correlation coefficient in the second set of correlation coefficients and the time offset is not smooth enough and has spikes.

[0149] To more accurately determine the synchronization time deviation, a preset function is used to fit the correspondence between multiple time offsets and the second set of correlation coefficients, thereby obtaining the second target correspondence between multiple time offsets and the second set of correlation coefficients.

[0150] In one example, the preset function is a quadratic function y = ax. 2 When fitting the correlation between multiple time offsets and the second set of correlation coefficients using +bx+c, the values ​​of coefficients a, b, and c in the quadratic function are determined to obtain a smoother quadratic function curve, such as... Figure 3 As shown, the horizontal axis represents the time offset, and the vertical axis represents the correlation coefficient in the second set of correlation coefficients after fitting. The correspondence after fitting with a preset function is the second target correspondence between multiple time offsets and the second set of correlation coefficients.

[0151] Then, the time offset with the largest correlation coefficient in the second target correspondence is determined as the synchronization time deviation between the data of the on-board system of the test vehicle and the data of the true system.

[0152] Compare the values ​​of multiple correlation coefficients in the second target correspondence, and take the time offset with the largest correlation coefficient as the synchronization time deviation between the data of the test vehicle's on-board system and the data of the true system.

[0153] In one example, the second objective correspondence is represented by a curve of a quadratic function, such as... Figure 3 As shown, the horizontal axis of the quadratic function represents the time offset, and the vertical axis represents the correlation coefficient in the second set of correlation coefficients after fitting. The horizontal axis value corresponding to the vertex of the quadratic function curve is -25, so the synchronization time deviation is -25.

[0154] The method provided in this application uses a preset function to fit the correspondence between multiple time offsets and a second set of correlation coefficients, eliminating the interference of numerical errors caused by differences in measurement systems and improving the accuracy of synchronization time deviation.

[0155] In some embodiments, before S150: determining the data of the truth system after offsetting each of the preset plurality of time offsets, the following steps may also be included:

[0156] First, obtain the second measurement cycle of the true value system.

[0157] Extract the second measurement period of the truth system from the data recorded by the truth system.

[0158] Then, the second unit time is calculated based on the second measurement cycle and the preset time granularity.

[0159] The second unit time is obtained by calculating the quotient of the second measurement cycle and the preset time granularity.

[0160] In one example, the preset time granularity is 10, and the second measurement period is Q, then the second unit time is

[0161] Finally, the product of the second unit time and the preset unit time share is calculated to obtain multiple time offsets.

[0162] The preset unit time share includes multiple values. The product of the second unit time and each value in the preset unit time share is calculated to obtain multiple time offsets.

[0163] In one example, the second unit of time is The preset unit time share includes every integer in the range [-100, 100], for a total of 201 integers. Therefore, calculate the sum of each integer in the range [-100, 100] and... The product of these two values ​​yields 201 time offsets.

[0164] The method provided in this application provides multiple time offsets, which provide a data basis for determining the synchronization time deviation among these multiple time offsets.

[0165] This application also provides an apparatus for determining synchronization time deviation, such as... Figure 4 As shown, the device 400 may include an acquisition module 410, a determination module 420, an interpolation module 430, and a calculation module 440.

[0166] The acquisition module 410 is used to acquire the data of the on-board system and the true value system of the test vehicle measuring the target measurement object at each time point within a preset time period.

[0167] The determination module 420 is used to determine the data of the vehicle system after offsetting each time offset, or to determine the data of the true system after offsetting each time offset.

[0168] The interpolation module 430 is used to interpolate the data of the vehicle system after offsetting each time offset, based on the time point of the data of the true system, to obtain the first detection data, or to interpolate the data of the true system after offsetting each time offset, based on the time point of the data of the vehicle system, to obtain the second detection data.

[0169] The calculation module 440 is used to calculate the first set of correlation coefficients of the data of the true value system and the first detection data obtained by interpolation after offsetting each time offset, or to calculate the second set of correlation coefficients of the data of the vehicle system and the second detection data obtained by interpolation after offsetting each time offset.

[0170] The determination module 420 is also used to determine the time offset corresponding to the largest correlation coefficient in the first set of correlation coefficients or the second set of correlation coefficients as the synchronization time deviation between the data of the on-board system of the test vehicle and the data of the true system.

[0171] The device for determining synchronization time deviation provided in this application embodiment presets multiple time offsets, determines the correlation coefficient between the data of the vehicle system and the data of the true system at each time offset, and takes the time offset corresponding to the maximum correlation coefficient as the synchronization time deviation between the data of the vehicle system and the data of the true system of the test vehicle. Since the correlation coefficient between the data of the vehicle system and the data of the true system is the largest under the synchronization time deviation, the synchronization time deviation is an accurate time deviation, thereby improving the accuracy of the time deviation.

[0172] In some embodiments, the calculation module 440 may be specifically used for:

[0173] Based on the data from the truth system, determine the first trend of change in the data of the truth system;

[0174] Based on the first detection data obtained by offsetting each time offset and interpolating, determine the second trend of change of the first detection data obtained by offsetting each time offset and interpolating.

[0175] Calculate the correlation coefficient between the first trend of change and each second trend of change to obtain the first set of correlation coefficients.

[0176] The apparatus for determining synchronization time deviation provided in this application embodiment obtains the change trend of the true system data and the correlation coefficient of the change trend of the first detection data obtained after offsetting each time offset and interpolating. This provides a basis for determining the time offset corresponding to the maximum correlation coefficient, and the accuracy of the time deviation can be improved based on the correlation coefficient.

[0177] In some embodiments, the calculation module 440 may be specifically used for:

[0178] Based on the data from the vehicle system, determine the third trend of change in the vehicle system data;

[0179] Based on the second detection data obtained by offsetting each time offset and interpolating, determine the fourth trend of change of the second detection data obtained by offsetting each time offset and interpolating.

[0180] Calculate the correlation coefficient between the third trend and each fourth trend to obtain the second set of correlation coefficients.

[0181] The device for determining synchronization time deviation provided in this application embodiment obtains the change trend of the data of the vehicle system and the correlation coefficient of the change trend of the second detection data obtained after offsetting each time offset, providing a basis for determining the time offset corresponding to the maximum correlation coefficient. Based on the correlation coefficient, the accuracy of the time deviation can be improved.

[0182] In some embodiments, the determining module 420 may be specifically used for:

[0183] The first target correspondence between multiple time offsets and the first set of correlation coefficients is obtained by fitting a preset function to fit the correspondence between multiple time offsets and the first set of correlation coefficients; or the second target correspondence between multiple time offsets and the second set of correlation coefficients is obtained by fitting a preset function to fit the correspondence between multiple time offsets and the second set of correlation coefficients.

[0184] The time offset with the largest correlation coefficient in either the first or second target correspondence is determined as the synchronization time deviation.

[0185] The device for determining synchronization time deviation provided in this application embodiment uses a preset function to fit the correspondence between multiple time offsets and a first set of correlation coefficients, or uses a preset function to fit the correspondence between multiple time offsets and a second set of correlation coefficients, thereby eliminating the interference of numerical errors caused by differences in measurement systems and improving the accuracy of synchronization time deviation.

[0186] In some embodiments, the acquisition module 410 is further configured to acquire the first measurement cycle of the vehicle system;

[0187] The calculation module 440 is also used to calculate the first unit time based on the first test cycle and the preset time granularity; it is also used to calculate the product of the first unit time and the preset unit time share to obtain multiple time offsets;

[0188] or,

[0189] The acquisition module 410 is also used to acquire the second measurement period of the truth system;

[0190] The calculation module 440 is also used to calculate the second unit time based on the second measurement cycle and the preset time granularity; it is also used to calculate the product of the second unit time and the preset unit time share to obtain multiple time offsets.

[0191] The apparatus for determining synchronization time deviation provided in this application provides a data basis for determining the synchronization time deviation among these multiple time offsets by obtaining multiple time offsets.

[0192] The device for determining synchronization time deviation provided in this application embodiment performs... Figure 1 The steps in the method shown, and the technical effect of improving the accuracy of time deviation, will not be elaborated further here for the sake of brevity.

[0193] Figure 5 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application is shown.

[0194] An electronic device may include a processor 501 and a memory 502 storing computer program instructions.

[0195] Specifically, the processor 501 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0196] Memory 502 may include mass storage for data or instructions. For example, and not limitingly, memory 502 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 502 may include removable or non-removable (or fixed) media. Where appropriate, memory 502 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 502 is non-volatile solid-state memory.

[0197] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to one aspect of this disclosure.

[0198] The processor 501 reads and executes computer program instructions stored in the memory 502 to implement any of the methods for determining synchronization time deviation in the above embodiments.

[0199] In one example, the electronic device may also include a communication interface 503 and a bus 510. Wherein, as... Figure 5As shown, the processor 501, memory 502, and communication interface 503 are connected through bus 510 and complete communication with each other.

[0200] The communication interface 503 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0201] Bus 510 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 510 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0202] The electronic device can perform the method for determining synchronization time deviation in the embodiments of this application, thereby achieving the combination Figure 1 The method described is for determining synchronization time deviation.

[0203] Furthermore, in conjunction with the methods for determining synchronization time deviation in the above embodiments, this application embodiment can provide a computer-readable storage medium for implementation. This computer-readable storage medium stores computer program instructions; when executed by a processor, these computer program instructions implement any of the methods for determining synchronization time deviation in the above embodiments.

[0204] Based on the methods for determining synchronization time deviation in the above embodiments, embodiments of this application can provide a computer program product for implementation. When the instructions in the computer program product are executed by the processor of an electronic device, they implement any of the methods for determining synchronization time deviation in the above embodiments.

[0205] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0206] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0207] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0208] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method of determining a synchronization time offset, the method comprising: The method comprises: obtaining original measurement data of a vehicle-mounted system and original measurement data of a true value system of a target measurement object measured by a test vehicle at each time point in a preset time period; for each time offset in a plurality of preset time offsets, offsetting the time points of the original measurement data of the vehicle-mounted system by the time offset to obtain data of the vehicle-mounted system after offsetting each time offset, or offsetting the time points of the original measurement data of the true value system by the time offset to obtain data of the true value system after offsetting each time offset; based on the time points of the original measurement data of the true value system as a reference, interpolating in the data of the vehicle-mounted system after offsetting each time offset to align the interpolated time points with the data time points of the true value system to obtain first detection data, or based on the time points of the original measurement data of the vehicle-mounted system as a reference, interpolating in the data of the true value system after offsetting each time offset to align the interpolated time points with the data time points of the vehicle-mounted system to obtain second detection data; calculating a first set of correlation coefficients of the original measurement data of the true value system and the first detection data obtained after offsetting each time offset and interpolating, or calculating a second set of correlation coefficients of the original measurement data of the vehicle-mounted system and the second detection data obtained after offsetting each time offset and interpolating; determining a time offset corresponding to a maximum correlation coefficient in the first set of correlation coefficients or the second set of correlation coefficients as a synchronization time deviation between the original measurement data of the vehicle-mounted system and the original measurement data of the true value system of the test vehicle; the calculation of the first set of correlation coefficients of the original measurement data of the true value system and the first detection data obtained after offsetting each time offset and interpolating comprises: determining a first change trend of the original measurement data of the true value system according to the original measurement data of the true value system; determining a second change trend of the first detection data obtained after offsetting each time offset and interpolating according to the first detection data obtained after offsetting each time offset and interpolating; calculating a correlation coefficient of the first change trend and each second change trend to obtain the first set of correlation coefficients; the calculation of the second set of correlation coefficients of the original measurement data of the vehicle-mounted system and the second detection data obtained after offsetting each time offset and interpolating comprises: determining a third change trend of the original measurement data of the vehicle-mounted system according to the original measurement data of the vehicle-mounted system; determining a fourth change trend of the second detection data obtained after offsetting each time offset and interpolating according to the second detection data obtained after offsetting each time offset and interpolating; calculating a correlation coefficient of the third change trend and each fourth change trend to obtain the second set of correlation coefficients.

2. The method of claim 1, wherein, the determination of the time offset corresponding to the maximum correlation coefficient in the first set of correlation coefficients or the second set of correlation coefficients as the synchronization time deviation between the original measurement data of the vehicle-mounted system and the original measurement data of the true value system of the test vehicle comprises: fitting the preset function to the correspondence between the plurality of time offsets and the first set of correlation coefficients to obtain a first target correspondence between the plurality of time offsets and the first set of correlation coefficients, or fitting the preset function to the correspondence between the plurality of time offsets and the second set of correlation coefficients to obtain a second target correspondence between the plurality of time offsets and the second set of correlation coefficients; determining a time offset with the largest correlation coefficient in the first target correspondence or the second target correspondence as the synchronization time offset between the original measurement data of the vehicle-mounted system of the test vehicle and the original measurement data of the true value system.

3. The method according to any of claims 1-2, characterized in that, Before the time point of the original measurement data of the vehicle-mounted system is offset by each time offset in the plurality of preset time offsets to obtain the data of the vehicle-mounted system after being offset by each time offset, or the time point of the original measurement data of the true value system is offset by each time offset to obtain the data of the true value system after being offset by each time offset, the method further comprises: obtaining a first measurement period of the vehicle-mounted system; calculating a first unit time according to the first measurement period and a preset time granularity; calculating a product of the first unit time and a preset unit time share number to obtain the plurality of time offsets; or obtaining a second measurement period of the true value system; calculating a second unit time according to the second measurement period and the preset time granularity; calculating a product of the second unit time and the preset unit time share number to obtain the plurality of time offsets.

4. The method of claim 1, wherein, The obtaining of the original measurement data of the vehicle-mounted system and the original measurement data of the true value system measured by the test vehicle on the target measurement object at each time point in a preset time period comprises: extracting data measured by the vehicle-mounted system and the true value system on the target measurement object in a plurality of continuous measurement periods of the vehicle-mounted system and the true value system in the same time period from data measured by the vehicle-mounted system and data measured by the true value system of the test vehicle, respectively.

5. The method of claim 1, wherein, The interpolation in the data of the vehicle-mounted system after being offset by each time offset with the time point of the original measurement data of the true value system as a reference to align the time point after interpolation with the time point of the data of the true value system to obtain first detection data comprises: when the time point of the data of the vehicle-mounted system after being offset by each time offset is not completely the same as the time point of the original measurement data of the true value system, interpolating in the data of the vehicle-mounted system after being offset by each time offset with the time point of the original measurement data of the true value system as a reference to obtain the first detection data which is the same as the time point of the data of the true value system; or the interpolation in the data of the true value system after being offset by each time offset with the time point of the original measurement data of the vehicle-mounted system as a reference to obtain second detection data comprises: When the time points of the true value system data after being offset by each time offset are not completely same as the time points of the original measurement data of the vehicle-mounted system, interpolation is performed in the true value system data after being offset by each time offset based on the time points of the original measurement data of the vehicle-mounted system, so that the second detection data with the same time points as the data of the vehicle-mounted system is obtained.

6. An apparatus for determining a synchronization time offset, the apparatus comprising: The device comprises: an acquisition module configured to acquire original measurement data of a vehicle-mounted system and original measurement data of a true value system measured by a test vehicle on a target measurement object at each time point in a preset time period; a determination module configured to offset the time points of the original measurement data of the vehicle-mounted system by each of a plurality of preset time offsets to obtain vehicle-mounted system data after being offset by each time offset, or offset the time points of the original measurement data of the true value system by each of the plurality of preset time offsets to obtain true value system data after being offset by each time offset; an interpolation module configured to perform interpolation in the vehicle-mounted system data after being offset by each time offset based on the time points of the original measurement data of the true value system, so that the time points after interpolation are aligned with the time points of the true value system data to obtain first detection data, or perform interpolation in the true value system data after being offset by each time offset based on the time points of the original measurement data of the vehicle-mounted system, so that the time points after interpolation are aligned with the time points of the vehicle-mounted system data to obtain second detection data; a calculation module configured to calculate a first group of correlation coefficients of the original measurement data of the true value system and the first detection data obtained after being offset by each time offset and performing interpolation, or calculate a second group of correlation coefficients of the original measurement data of the vehicle-mounted system and the second detection data obtained after being offset by each time offset and performing interpolation; The determination module is further configured to determine a time offset corresponding to a maximum correlation coefficient in the first group of correlation coefficients or the second group of correlation coefficients as a synchronization time deviation between the original measurement data of the vehicle-mounted system of the test vehicle and the original measurement data of the true value system. The calculation module is specifically configured to: determine a first variation trend of the original measurement data of the true value system according to the original measurement data of the true value system; determine a second variation trend of the first detection data obtained after being offset by each time offset and performing interpolation according to the first detection data obtained after being offset by each time offset and performing interpolation; calculate a correlation coefficient of the first variation trend and each second variation trend to obtain the first group of correlation coefficients; determine a third variation trend of the original measurement data of the vehicle-mounted system according to the original measurement data of the vehicle-mounted system; determine a fourth variation trend of the second detection data obtained after being offset by each time offset and performing interpolation according to the second detection data obtained after being offset by each time offset and performing interpolation; calculate a correlation coefficient of the third variation trend and each fourth variation trend to obtain the second group of correlation coefficients.

7. An electronic device, comprising: The device comprises a processor and a memory storing computer program instructions; the processor implements the method for determining the synchronization time offset according to any one of claims 1-5 when executing the computer program instructions.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer program instructions; the computer program instructions are executed by the processor to implement the method for determining the synchronization time offset according to any one of claims 1-5.

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