Data recharging method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a data recharge method and device, electronic equipment and a storage medium, relates to the field of intelligent driving, and can improve the test quality of a recharge test. The method comprises the following steps: acquiring pre-recorded sensor fusion information in a real vehicle test, wherein the sensor fusion information comprises fusion statistical information and at least one sensor data packet; wherein each sensor data packet comprises a data packet information header and measurement data, and the data packet information header comprises a receiving moment when the measurement data is received by the processor; the fusion statistical information comprises at least one statistical frame, and each statistical frame comprises a scheduling execution moment of one fusion operation and a data packet information header in the sensor data packet to be fused corresponding to the fusion operation; generating recharge data based on the sensor fusion information; and providing the recharge data to a to-be-tested object, so that the to-be-tested object is tested by using the recharge data. The method is suitable for vehicle testing.

Description

Technical Field

[0001] This invention relates to the field of intelligent driving, and more particularly to a data reinjection method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the rapid development of intelligent driving technology, the iteration speed of intelligent driving software and vehicle models equipped with such software is accelerating, and the update cycle of controllers, sensors, and corresponding software is also speeding up. To improve development efficiency and reduce manpower and equipment costs during testing, in the field of intelligent driving, various sensor data can be recorded during actual vehicle testing. This recorded sensor data can then be used to simulate real-world vehicle conditions and execute preset algorithms on the sensor data, thereby achieving data feedback testing and verification.

[0003] In related technologies, intelligent driving control can generally be performed based on data collected from multiple sensors. For example, preset algorithms need to be executed on data from vision sensors, front radar sensors, and corner radars to enable intelligent driving control. However, due to differences in the processing frequency of each sensor and the time consumption of the transmission link, there are timing differences between the retest and the actual vehicle test. This can lead to inconsistencies in the test results, affecting the test quality. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a data backfeeding method, recording method, apparatus, system, electronic device and storage medium, which can effectively reduce or eliminate the difference between backfeeding test and actual test, and effectively improve the test quality of backfeeding test.

[0005] In a first aspect, embodiments of the present invention provide a data refeeding method, comprising: acquiring sensor fusion information pre-recorded during actual vehicle testing, the sensor fusion information including fusion statistics and at least one sensor data packet; wherein each sensor data packet includes a data packet header and measurement data, the data packet header including the reception time when the measurement data is received by a processor; the fusion statistics include at least one statistical frame, each statistical frame including the scheduling execution time of a fusion operation and the data packet header in the sensor data packet to be fused corresponding to the fusion operation; generating refeeding data based on the sensor fusion information; and providing the refeeding data to a test object so that the test object can use the refeeding data for testing.

[0006] In one embodiment, the data packet header further includes the measurement occurrence time of the measurement data; generating feedback data based on the sensor fusion information includes: according to the fusion statistics, sequentially searching in each of the sensor data packets to be fused for the measurement data required for each fusion operation and the measurement occurrence time of the measurement data; sequentially generating the feedback data required for each feedback operation according to the found measurement data and the measurement occurrence time; providing the feedback data to the test object so that the test object can use the feedback data for testing includes: sequentially providing the sequentially generated feedback data to the test object so that the test object can use the feedback data for testing.

[0007] In one embodiment, the step of sequentially searching for the measurement data required for each fusion operation and the measurement occurrence time of the measurement data in each of the sensor data packets to be fused according to the fusion statistics information includes: for each fusion operation, determining the statistical frame corresponding to the current fusion operation according to the fusion statistics information to obtain a target statistical frame; determining whether the reception time contained in the header of each data packet in the target statistical frame is less than the scheduling execution time in the target statistical frame; if the reception time is less than the scheduling execution time, using the header of the data packet in the target statistical frame as a query index, searching for the measurement data corresponding to the query index and the measurement occurrence time of the measurement data in each of the sensor data packets.

[0008] In one embodiment, the step of using the data packet header in the target statistical frame as a query index to search for the measurement data and the measurement occurrence time of the measurement data in each of the sensor data packets includes: using the data packet header in the target statistical frame as a query index to search for sensor data packets in each of the sensor data packets whose data packet header matches the query index, thereby obtaining a target data packet; and determining the measurement data and the measurement occurrence time in the target data packet as the measurement data and the measurement occurrence time of the measurement data corresponding to the query index.

[0009] In one embodiment, the statistical frame further includes a frame count; the step of generating feedback data based on the sensor fusion information includes: determining, according to the fusion statistical information, whether the difference between the frame count corresponding to the current fusion operation and the frame count corresponding to the previous fusion operation is greater than 1; if the difference is greater than 1, determining that there are lost statistical frames in the fusion statistical information; determining the estimated scheduling time of each lost statistical frame according to the count difference and the scheduling period of the fusion operation; for each estimated scheduling time, searching for a supplementary data packet corresponding to the current estimated scheduling time in each of the sensor data packets that have not been fed back; and generating supplementary feedback data based on the supplementary data packet.

[0010] In one implementation, the number of lost statistical frames is at least one; each lost statistical frame corresponds to an estimated scheduling time, wherein the supplementary data packet corresponding to the smallest estimated scheduling time is a first sensor data packet, the reception time in the first sensor data packet is greater than the scheduling execution time of the previous fusion operation and less than the smallest estimated scheduling time, and the reception time in the first sensor data packet is not recorded in the statistical frame corresponding to the current fusion operation; among the estimated scheduling times, the supplementary data packet corresponding to each estimated scheduling time other than the smallest estimated scheduling time is a second sensor data packet, the reception time in the second sensor data packet is greater than the previous estimated scheduling time and less than the current estimated scheduling time, and the reception time in the second sensor data packet is not recorded in the statistical frame corresponding to the current fusion operation.

[0011] In one embodiment, after acquiring the sensor fusion information pre-recorded during the actual vehicle test, the method further includes: determining whether there is a situation where the sensor data packets are lost based on the fusion statistics and the data reporting cycle of each sensor known in advance; and in response to the situation where the sensor data packets are lost, locating the sensor that has lost packets based on the fusion statistics.

[0012] In one embodiment, the measurement data in the at least one sensor data packet comes from at least one sensor, and the data reporting times of each sensor are the same or different, and the data reporting periods of each sensor are the same or different.

[0013] Secondly, embodiments of the present invention also provide a data recording method, comprising: in a real vehicle test, receiving measurement data sent by each sensor and recording the reception time of the measurement data; generating a corresponding sensor data packet according to each measurement data and its corresponding reception time, the sensor data packet including a data packet header and the measurement data, the data packet header including the reception time; performing a fusion operation on each sensor data packet generated within the preset time interval at a preset time interval, and generating a corresponding statistical frame, the statistical frame including the scheduling execution time of the fusion operation and the data packet header of each sensor data packet generated within the preset time interval; the statistical frames corresponding to each fusion operation forming fusion statistical information; and recording sensor fusion information according to each sensor data packet and the fusion statistical information.

[0014] In one embodiment, receiving measurement data sent by each sensor and recording the reception time of the measurement data during the actual vehicle test includes: receiving raw data packets sent by each sensor and recording the reception time of the raw data packets during the actual vehicle test, wherein the raw data packets include the measurement data and the measurement occurrence time of the measurement data; generating a corresponding sensor data packet based on each measurement data and its corresponding reception time includes: generating a corresponding sensor data packet based on each raw data packet and its corresponding reception time.

[0015] In one embodiment, recording sensor fusion information based on each of the sensor data packets and the fusion statistics includes: sending each of the sensor data packets and the fusion statistics to a recording data industrial control computer, so as to record the sensor fusion information through the recording data industrial control computer.

[0016] In one implementation, the statistical frame further includes a frame count; the frame count is incremented by 1 each time the fusion operation is performed.

[0017] In one embodiment, the number of sensors is at least one, and the data reporting times of each sensor may be the same or different, and the data reporting periods of each sensor may be the same or different.

[0018] Thirdly, embodiments of the present invention also provide a data refeeding device, comprising: an acquisition unit, configured to acquire sensor fusion information pre-recorded during actual vehicle testing, the sensor fusion information including fusion statistical information and at least one sensor data packet; wherein each sensor data packet includes a data packet header and measurement data, the data packet header including the reception time when the measurement data is received by the processor; the fusion statistical information includes at least one statistical frame, each statistical frame including the scheduling execution time of a fusion operation and the data packet header in the sensor data packet to be fused corresponding to the fusion operation; a first generation unit, configured to generate refeeding data based on the sensor fusion information; and a providing unit, configured to provide the refeeding data to a test object, so that the test object can use the refeeding data for testing.

[0019] In one embodiment, the data packet header further includes the measurement occurrence time of the measurement data; the first generation unit includes: a first search module, configured to search sequentially in each of the sensor data packets to be fused for the measurement data required for each fusion operation and the measurement occurrence time of the measurement data according to the fusion statistics; a first generation module, configured to generate sequentially the refeed data required for each refeed operation according to the found measurement data and the measurement occurrence time; the providing unit is specifically configured to provide the sequentially generated refeed data to the test object, so that the test object can use the refeed data for testing sequentially.

[0020] In one embodiment, the first search module includes: a first determining submodule, configured to determine, for each fusion operation, the statistical frame corresponding to the current fusion operation based on the fusion statistics information, and obtain a target statistical frame; a second determining submodule, configured to determine whether the receiving time contained in the header of each data packet in the target statistical frame is less than the scheduling execution time in the target statistical frame; and a search submodule, configured to, when the receiving time is less than the scheduling execution time, use the header of the data packet in the target statistical frame as a query index to search for the measurement data corresponding to the query index and the measurement occurrence time of the measurement data in each of the sensor data packets.

[0021] In one implementation, the search submodule is specifically used to: use the data packet header in the target statistical frame as a query index to search for sensor data packets in each of the sensor data packets whose data packet header matches the query index, and obtain the target data packet; and determine the measurement data and the measurement occurrence time in the target data packet as the measurement data and the measurement occurrence time of the measurement data corresponding to the query index.

[0022] In one embodiment, the statistical frame further includes a frame count; the first generation unit includes: a first determining module, configured to determine whether the count difference between the frame count corresponding to the current fusion operation and the frame count corresponding to the previous fusion operation is greater than 1 based on the fusion statistical information; a second determining module, configured to determine that there are lost statistical frames in the fusion statistical information if the count difference is greater than 1; a third determining module, configured to determine the estimated scheduling time of each lost statistical frame based on the count difference and the scheduling period of the fusion operation; a second searching module, configured to search for a supplementary data packet corresponding to the current estimated scheduling time in each of the sensor data packets that have not been fed back for each estimated scheduling time; and a second generation module, configured to generate supplementary feedback data based on the supplementary data packet.

[0023] In one implementation, the number of lost statistical frames is at least one; each lost statistical frame corresponds to an estimated scheduling time, wherein the supplementary data packet corresponding to the smallest estimated scheduling time is a first sensor data packet, the reception time in the first sensor data packet is greater than the scheduling execution time of the previous fusion operation and less than the smallest estimated scheduling time, and the reception time in the first sensor data packet is not recorded in the statistical frame corresponding to the current fusion operation; among the estimated scheduling times, the supplementary data packet corresponding to each estimated scheduling time other than the smallest estimated scheduling time is a second sensor data packet, the reception time in the second sensor data packet is greater than the previous estimated scheduling time and less than the current estimated scheduling time, and the reception time in the second sensor data packet is not recorded in the statistical frame corresponding to the current fusion operation.

[0024] In one embodiment, the data refeeding device further includes: a determining unit, configured to determine whether there is a situation where the sensor data packets are lost, based on the fusion statistics and the data reporting cycle of each sensor known in advance, after acquiring the sensor fusion information pre-recorded in the actual vehicle test; and a locating unit, configured to locate the sensor that has lost packets based on the fusion statistics in response to the situation where the sensor data packets are lost.

[0025] In one embodiment, the measurement data in the at least one sensor data packet comes from at least one sensor, and the data reporting times of each sensor are the same or different, and the data reporting periods of each sensor are the same or different.

[0026] Fourthly, embodiments of the present invention also provide a data recording apparatus, comprising: a receiving unit, configured to receive measurement data sent by each sensor and record the reception time of the measurement data during a real vehicle test; a second generating unit, configured to generate a corresponding sensor data packet based on each measurement data and its corresponding reception time, the sensor data packet including a data packet header and the measurement data, the data packet header including the reception time; a third generating unit, configured to perform a fusion operation on each sensor data packet generated within a preset time interval at each preset time interval, and generate a corresponding statistical frame, the statistical frame including the scheduling execution time of the fusion operation and the data packet header of each sensor data packet generated within the preset time interval; the statistical frames corresponding to each fusion operation form fusion statistical information; and a recording unit, configured to record sensor fusion information based on each sensor data packet and the fusion statistical information.

[0027] In one embodiment, the receiving unit is specifically used to receive raw data packets sent by each sensor and record the receiving time of the raw data packets during actual vehicle testing. The raw data packets include the measurement data and the measurement occurrence time of the measurement data. The second generating unit is specifically used to generate a corresponding sensor data packet based on each raw data packet and its corresponding receiving time.

[0028] In one embodiment, the recording unit is specifically used to send each of the sensor data packets and the fusion statistical information to the recording data industrial control computer, so as to record the sensor fusion information through the recording data industrial control computer.

[0029] In one implementation, the statistical frame further includes a frame count; the frame count is incremented by 1 each time the fusion operation is performed.

[0030] In one embodiment, the number of sensors is at least one, and the data reporting times of each sensor may be the same or different, and the data reporting periods of each sensor may be the same or different.

[0031] Fifthly, embodiments of the present invention also provide a data reinjection system, including a data recording device and a data reinjection device, wherein the data recording device is communicatively connected to the data reinjection device; wherein the data recording device is used to implement any data recording method provided in the embodiments of the present invention, and the data reinjection device is used to implement any data reinjection method provided in the embodiments of the present invention.

[0032] In a sixth aspect, embodiments of the present invention also provide an electronic device, including: a processor and a memory, wherein the processor is electrically connected to the memory; the memory is used to store executable program code; the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement any data backfeeding method or any data recording method provided by embodiments of the present invention.

[0033] In a seventh aspect, embodiments of the present invention also provide a computer-readable storage medium storing one or more programs, which can be executed by one or more processors to implement any data reflow method or any data recording method provided in embodiments of the present invention.

[0034] The embodiments of the present invention provide a data re-feedback method, recording method, apparatus, system, electronic device and storage medium, which can acquire sensor fusion information pre-recorded in real vehicle testing, generate re-feedback data based on the sensor fusion information, and provide the re-feedback data to the test object so that the test object can use the re-feedback data for testing. Since the sensor fusion information includes fusion statistics and at least one sensor data packet, and each statistical frame of the fusion statistics includes the scheduling execution time of a fusion operation and the data packet header of the sensor data packet to be fused corresponding to the fusion operation, it is possible to determine which sensor data packets are the sensor data packets to be fused for this fusion operation based on the scheduling execution time in each statistical frame and the reception time in the data packet header of each statistical frame. On the other hand, it is possible to find the sensor data packets to be fused for this fusion operation from each sensor data packet based on the data packet header in the statistical frame and the data packet header in each sensor data packet, and use the found sensor data packets to generate backfeed data for backfeed testing. In this way, it is possible to more accurately reproduce the sensor data packets to be fused for each fusion operation under the actual vehicle test conditions, and use these sensor data packets to generate backfeed data for each test. Therefore, it is possible to effectively reduce or eliminate the difference between backfeed testing and actual testing, and effectively improve the test quality of backfeed testing. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 A flowchart of a data reinjection method provided in an embodiment of the present invention;

[0037] Figure 2 This is a schematic diagram of a sensor data packet structure in an embodiment of the present invention;

[0038] Figure 3 This is a schematic diagram of a structure that integrates statistical information in an embodiment of the present invention;

[0039] Figure 4 This is a schematic diagram of a structure of a statistical frame that integrates statistical information in an embodiment of the present invention;

[0040] Figure 5 This is a schematic diagram of another structure for integrating statistical information in an embodiment of the present invention;

[0041] Figure 6 A detailed flowchart of a data reinjection method provided for embodiments of the present invention;

[0042] Figure 7 This is a schematic diagram of a sensor data packet structure for a visual sensor in an embodiment of the present invention;

[0043] Figure 8 This is a schematic diagram of a sensor data packet structure of a front radar sensor in an embodiment of the present invention;

[0044] Figure 9 This is a schematic diagram of a sensor data packet structure for an angle radar sensor in an embodiment of the present invention;

[0045] Figure 10 This is a schematic diagram of a specific structure for integrating statistical information in an embodiment of the present invention;

[0046] Figure 11 This is a schematic diagram illustrating the timing relationship between the data reception time of each sensor and the scheduling execution time of each fusion operation in an embodiment of the present invention.

[0047] Figure 12 This is a schematic diagram illustrating the effect of supplementing the missing statistical frames in the fused statistical information in an embodiment of the present invention;

[0048] Figure 13 This is a schematic diagram illustrating the diagnosis and localization of sensor data packet loss based on fused statistical information in an embodiment of the present invention;

[0049] Figure 14 A flowchart of a data recording method provided in an embodiment of the present invention;

[0050] Figure 15 This is a schematic diagram of the sensor data packet generation process in an embodiment of the present invention;

[0051] Figure 16 Another flowchart of a data recording method provided for an embodiment of the present invention;

[0052] Figure 17 A schematic diagram of a data reinjection device provided for an embodiment of the present invention;

[0053] Figure 18 A schematic diagram of a data recording apparatus provided in an embodiment of the present invention;

[0054] Figure 19 A schematic diagram of a data reinjection system provided for an embodiment of the present invention;

[0055] Figure 20 A schematic diagram of an electronic device provided as an embodiment of the present invention. Detailed Implementation

[0056] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0057] It should be understood that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0058] In a first aspect, embodiments of the present invention provide a data reinjection method that can effectively reduce or eliminate the difference between reinjection testing and actual testing, thereby effectively improving the testing quality of reinjection testing.

[0059] like Figure 1 As shown, the data reinjection method provided in the embodiments of the present invention may include:

[0060] S11, acquire sensor fusion information pre-recorded during the actual vehicle test, the sensor fusion information including fusion statistics and at least one sensor data packet;

[0061] Each of the sensor data packets includes a data packet header and measurement data. The data packet header includes the reception time corresponding to when the measurement data is received by the processor. The fusion statistics include at least one statistics frame. Each statistics frame includes the scheduling execution time of a fusion operation and the data packet header in the sensor data packet to be fused corresponding to the fusion operation.

[0062] In this embodiment of the invention, the sensor fusion information is recorded under actual vehicle testing conditions. In this step, pre-recorded sensor fusion information can be acquired to generate recharge data based on the sensor fusion information for recharge testing.

[0063] In embodiments of the present invention, sensor fusion information may include fusion statistics and sensor data packets. In one embodiment, the sensor data packet includes sensor measurement data and the reception time when the measurement data is received by the processor, wherein the reception time may be included in the data packet header, and the measurement data may be included in the data packet body. It should be noted that the sensor fusion information is recorded under actual vehicle testing conditions; therefore, the processor here is also a processor under actual vehicle testing conditions.

[0064] Fusion statistics are a set of statistical information for the sensor data packets targeted in each fusion operation. They can record the sensor data packets corresponding to each fusion operation, and this correspondence can be reflected by the scheduling execution time of the fusion operation and the reception time in the data packet header of each sensor data packet.

[0065] S12, Generate reinjection data based on the sensor fusion information;

[0066] After obtaining the sensor fusion information, in this step, the backfeed data can be generated based on the fusion statistics and data packets of each sensor in the sensor fusion information.

[0067] S13, the reinjection data is provided to the object under test so that the object under test can use the reinjection data for testing.

[0068] In this step, the reflowed data can be provided to the object under test (AUT) for reflow testing. The AUT can be hardware, such as a processor or controller, or software, such as autonomous driving software; embodiments of this invention do not limit this.

[0069] The data refeeding method provided by the embodiments of the present invention can acquire sensor fusion information pre-recorded in real vehicle testing, generate refeeding data based on the sensor fusion information, and provide the refeeding data to the test object so that the test object can use the refeeding data for testing. Since the sensor fusion information includes fusion statistics and at least one sensor data packet, and each statistical frame of the fusion statistics includes the scheduling execution time of a fusion operation and the data packet header of the sensor data packet to be fused corresponding to the fusion operation, it is possible to determine which sensor data packets are the sensor data packets to be fused for this fusion operation based on the scheduling execution time in each statistical frame and the reception time in the data packet header of each statistical frame. On the other hand, it is possible to find the sensor data packets to be fused for this fusion operation from each sensor data packet based on the data packet header in the statistical frame and the data packet header in each sensor data packet, and use the found sensor data packets to generate backfeed data for backfeed testing. In this way, it is possible to more accurately reproduce the sensor data packets to be fused for each fusion operation under the actual vehicle test conditions, and use these sensor data packets to generate backfeed data for each test. Therefore, it is possible to effectively reduce or eliminate the difference between backfeed testing and actual testing, and effectively improve the test quality of backfeed testing.

[0070] In embodiments of the present invention, sensor fusion information may include sensor data packets and fusion statistics, which will be described in detail below.

[0071] First, the sensor data packets are introduced. In embodiments of the present invention, the sensor data packets may include measurement data. The measurement data in each sensor data packet may come from one or more sensors. The data reporting times of each sensor may be the same or different, and the data reporting periods of each sensor may be the same or different. For example, in one example, the measurement data in sensor data packets P1 and P2 comes from sensor A1, and the measurement data in sensor data packet P3 comes from sensor A2. The data reporting period of sensor A1 is once every 20 milliseconds, and the data reporting period of sensor A2 is once every 50 milliseconds.

[0072] Furthermore, in one embodiment of the present invention, the data packet header may include not only the time of receiving the measurement data, but also the time of measurement occurrence. The measurement data and the measurement occurrence time can be sent together by the sensor to the processor in the actual vehicle test.

[0073] The structure of a sensor data packet can be as follows: Figure 2 As shown. See also Figure 2In one implementation, the sensor data packet includes sensor measurement data, the time when the measurement data was measured, and the time when the measurement data was received by the processor. The receiving time and the measurement time can be included in the data packet header, and the measurement data can be included in the data packet body. For example, in one instance, speed sensor SEN1 measures a vehicle speed of v1 at time t1, and the processor receives this measurement data at time t2. It is understood that t2 is greater than t1. The data packet header can include the measurement time t1 and the receiving time t2, and the data packet body can include the vehicle speed v1.

[0074] The following section introduces fused statistical information. One type of fused statistical information can be as follows: Figure 3 As shown. Among them. This represents the received data time corresponding to the p-th packet of data transmitted from the m-th sensor during the n-th fusion calculation. m ranges from 1 to M, where M is the number of sensors configured in the current system; n ranges from 1 to N, where N is the number of fusion calculations performed for each group of recorded data; and p ranges from 0 to P, where p=0 indicates that no data from the current sensor was transmitted during this fusion calculation. Figure 3 For simplification, only the data of the p-th packet is used. In actual recording, if P>0, the data packets can be arranged sequentially from 1 to P.

[0075] For example, for Figure 3 Each line in the text can be further expanded as follows: Figure 4 As shown. Among them, This represents the receiving time of the p-th packet of data received by the m-th sensor in this fusion calculation. Similarly, the time of measurement occurrence is indicated, where The value depends on the frequency at which the sensor transmits data. In one implementation, Figure 4 The values ​​in can be in a tiled format, for example, they can be:

[0076] .

[0077] Specifically, in one embodiment of the present invention, step S12, generating feedback data based on the sensor fusion information, may include: according to the fusion statistics, sequentially searching in each of the sensor data packets to be fused for the measurement data required for each fusion operation and the measurement occurrence time of the measurement data; and sequentially generating the feedback data required for each feedback operation based on the found measurement data and the measurement occurrence time. Based on this, step S13, providing the feedback data to the test object so that the test object can use the feedback data for testing, may include: sequentially providing the sequentially generated feedback data to the test object so that the test object can sequentially use the feedback data for testing.

[0078] Understandably, in real-vehicle testing, data collected from various sensors is fused at intervals to enable continuous intelligent driving control of the vehicle. Correspondingly, the backfeed test simulates real-vehicle testing conditions to improve accuracy. Therefore, in one embodiment of this invention, fusion operations can be performed multiple times at intervals, where the measurement data required for each fusion operation is the measurement data received by the processor between the previous fusion operation and the current one. After each fusion operation finds the required measurement data, backfeed data can be generated based on the found measurement data and the time of measurement, and a backfeed test can be performed.

[0079] In one implementation, the process of sequentially searching for the measurement data required for each fusion operation and the measurement occurrence time of the measurement data in each of the sensor data packets to be fused, based on the fusion statistics, may specifically include: for each fusion operation, determining the statistical frame corresponding to the current fusion operation based on the fusion statistics to obtain a target statistical frame; determining whether the reception time contained in the header of each data packet in the target statistical frame is less than the scheduling execution time in the target statistical frame; and if the reception time is less than the scheduling execution time, using the header of the data packet in the target statistical frame as a query index, searching for the measurement data corresponding to the query index and the measurement occurrence time of the measurement data in each of the sensor data packets.

[0080] In this embodiment, the fusion statistics information may include multiple statistical frames, which can be arranged sequentially according to the scheduling execution time of the fusion operation to form a statistical information table. In one implementation, each statistical frame can be used as a target statistical frame according to the arrangement order of the statistical frames in the statistical information table, and the measurement data required for each fusion operation and the time of measurement occurrence can be found based on each target statistical frame. For example, see again Figure 3 The first fusion operation can use the row where the scheduling execution time ft1 is located as the target statistical frame, and find the required measurement data and the measurement occurrence time based on the row of statistical frames where the scheduling execution time ft1 is located. The second fusion operation can use the row where the scheduling execution time ft2 is located as the target statistical frame, and find the required measurement data and the measurement occurrence time based on the row of statistical frames where the scheduling execution time ft2 is located, and so on.

[0081] In practice, after determining the target statistical frame, it can be first determined whether the reception time contained in the header of each data packet in the target statistical frame is less than the scheduling execution time in the target statistical frame. If the reception time is less than the scheduling execution time, it indicates that the information recorded in the target statistical frame is correct, and the next step can be performed. Using the header of the data packet in the target statistical frame as a query index, the measurement data corresponding to the query index and the measurement occurrence time of the measurement data are searched in each sensor data packet. If any reception time is greater than or equal to the scheduling execution time, that is, the reception time of the measurement data is later than the scheduling execution time of the fusion operation, which is impossible, it indicates that the information recorded in the target statistical frame is incorrect, and the fusion operation can be skipped.

[0082] In one embodiment of the present invention, using the data packet header in the target statistical frame as a query index to search for the measurement data and the measurement occurrence time of the measurement data corresponding to the query index in each of the sensor data packets may specifically include: using the data packet header in the target statistical frame as a query index to search for sensor data packets in each of the sensor data packets whose data packet header matches the query index, thereby obtaining a target data packet; and determining the measurement data and the measurement occurrence time in the target data packet as the measurement data and the measurement occurrence time of the measurement data corresponding to the query index.

[0083] For example, such as Figure 3 As shown, in one example, the nth fusion operation uses the line containing ftn as the target statistical frame, which records the reception time of the measurement data from sensor 1. The measurement occurred at the time of That is, the header of the data packet is ( , Then, using the header of this data packet as the query index, the header of the data packet is searched in each sensor data packet as follows: , From the sensor data packet, a target data packet is obtained. If the measurement data stored in the target data packet is data1, and the measurement occurred at time [time missing], then [data packet type missing]. Then data1, This refers to the measurement data corresponding to the query index and the time when the measurement occurred. Furthermore, the target statistics frame also records the time when the measurement data from sensor 2 was received. The measurement occurred at the time of That is, the header of the data packet is ( , Then, using the header of this data packet as the query index, the header of the data packet is searched in each sensor data packet as follows: , From the sensor data packet, another target data packet is obtained. The measurement data stored in this target data packet is data2, and the measurement occurred at time [time missing]. Similarly, the target data packets from all sensors targeted by the nth fusion operation can be queried, and the measurement data and their measurement times within these target data packets can be obtained. Then, based on the measurement data found in the nth fusion operation and the measurement times of each measurement data, the refeed data required for the nth refeed operation is generated. Here, n can be 1, 2, ..., N.

[0084] The foregoing embodiments detail how to locate the measurement data required for each fusion operation and the measurement time of such measurement data based on fusion statistics, but the embodiments of the present invention are not limited thereto. In other embodiments of the present invention, even if there are some missing statistical frames in the fusion statistics, the measurement data required for these missing statistical frames and the measurement time of such measurement data can still be located, thereby improving the robustness of data backfeedback.

[0085] Specifically, such as Figure 5 As shown, in one embodiment of the present invention, the statistical frames in the fusion statistics information may further include a frame count fn, where the frame count represents the number of each statistical frame. After each fusion operation generates a statistical frame, the corresponding frame count is incremented by 1. Based on this, step S12, generating feedback data based on the sensor fusion information, may include: determining, according to the fusion statistics information, whether the difference between the frame count corresponding to the current fusion operation and the frame count corresponding to the previous fusion operation is greater than 1; if the difference is greater than 1, determining that there are lost statistical frames in the fusion statistics information; determining the estimated scheduling time of each lost statistical frame according to the difference and the scheduling period of the fusion operation; for each estimated scheduling time, searching for a supplementary data packet corresponding to the current estimated scheduling time in each of the sensor data packets that have not been fed back; and generating supplementary feedback data based on the supplementary data packet.

[0086] In this embodiment, since the frame count is incremented by 1 for each generated statistical frame, if there are no missing statistical frames in the fused statistical information, the frame count of each statistical frame will increment by 1 sequentially from beginning to end. Conversely, if the fused statistical information stores missing statistical frames, there will be an interruption in the frame counts of each statistical frame, resulting in a difference greater than 1 between the counts of two adjacent frames. For example, if the frame counts of five adjacent statistical frames are 1, 2, 4, 5, and 6, the difference between frame count 2 and frame count 4 is 4-2=2, which is greater than 1. This indicates that there are missing statistical frames in the fused statistical information; that is, the statistical frame with a frame count of 3 was not written into the fused statistical information during the sensor fusion information recording.

[0087] Furthermore, based on the scheduling execution time of the previous fusion operation in the fusion statistics, several fusion operation scheduling cycles can be added to obtain the estimated scheduling time of each lost statistical frame. For example, in one case, the statistical frame corresponding to the current fusion operation is frame B, and the statistical frame corresponding to the previous fusion operation is frame A. If This indicates that packet loss occurred in the recorded fused frame information, and the number of lost packets is equal to... In embodiments of the present invention, the process performing the fusion operation can be scheduled to execute at a fixed frequency; that is, the scheduling period of the fusion operation is determined. The scheduling execution time sequence ft sequence of each fusion operation recorded in the fusion statistics information increases with a fixed scheduling period. If this scheduling period is... Then the estimated scheduling time of the fusion operation corresponding to the i-th statistical frame lost between frame A and frame B can be... ,in .

[0088] In the embodiments of the present invention, theoretically the specific number of frames lost between two statistical frames is unlimited. However, due to the complex environment in real vehicle testing, the scheduling cycle of each fusion operation may not be completely uniform. In order to make the error controllable, in one embodiment of the present invention, the number of consecutive packet losses can be limited as needed. For example, in one example, the maximum number of consecutive packet losses allowed is 2.

[0089] After calculating each estimated scheduling time, for each estimated scheduling time, the supplementary data packet corresponding to the current estimated scheduling time can be found in the data packets of each sensor that have not been fed back, so as to generate supplementary feedback data based on the supplementary data packet.

[0090] Specifically, in one implementation, the number of lost statistical frames is at least one; each lost statistical frame corresponds to an estimated scheduling time, and the supplementary data packet corresponding to the smallest estimated scheduling time is a first sensor data packet. The receiving time in the first sensor data packet is greater than the scheduling execution time of the previous fusion operation and less than the smallest estimated scheduling time, and the receiving time in the first sensor data packet is not recorded in the statistical frame corresponding to the current fusion operation. Among the estimated scheduling times, the supplementary data packet corresponding to each estimated scheduling time other than the smallest estimated scheduling time is a second sensor data packet. The receiving time in the second sensor data packet is greater than the previous estimated scheduling time and less than the current estimated scheduling time, and the receiving time in the second sensor data packet is not recorded in the statistical frame corresponding to the current fusion operation.

[0091] For example, in one embodiment of the present invention, the statistical frame corresponding to the current fusion operation is statistical frame 6, and the statistical frame corresponding to the previous fusion operation is statistical frame 3. Between statistical frame 3 and statistical frame 6, two statistical frames, statistical frame 4 and statistical frame 5, are lost. The estimated scheduling time corresponding to statistical frame 4 is the smallest among the two lost statistical frames. Therefore, the first sensor data packet can be found in the sensor data packets that have not yet been fed back into the data packet. The first sensor data packet is used as the supplementary data packet corresponding to statistical frame 4. The first sensor data packet satisfies the following conditions: the reception time of the first sensor data packet is greater than the scheduling execution time recorded in statistical frame 3 and less than the estimated scheduling time of statistical frame 4, and the reception time of the first sensor data packet is not recorded in statistical frame 6.

[0092] Correspondingly, the second sensor data packet can also be found in the sensor data packets that have not yet been fed back, and the second sensor data packet is used as the supplementary data packet corresponding to the statistical frame 5. The second sensor data packet satisfies the following conditions: the reception time of the second sensor data packet is greater than the estimated scheduling time corresponding to the statistical frame 4 and less than the estimated scheduling time corresponding to the statistical frame 5, and the reception time in the second sensor data packet is not recorded in the statistical frame 6.

[0093] After finding the supplementary data packets corresponding to statistical frame 4 and statistical frame 5, we can use the supplementary data packets of statistical frame 4 to generate a backfeed data and perform a backfeed test. Then we can use the supplementary data packets of statistical frame 5 to generate a backfeed data and perform a backfeed test.

[0094] Furthermore, in addition to investigating and supplementing missing statistical frames in the fused statistical information, in some embodiments of the present invention, the loss of sensor data packets can also be investigated.

[0095] Specifically, in one embodiment, after obtaining the sensor fusion information pre-recorded during the actual vehicle test in step S11, the data backfeeding method provided by the embodiments of the present invention may further include: determining whether there is a situation where the sensor data packets are lost based on the fusion statistics and the data reporting cycle of each sensor known in advance; and locating the sensor that has lost packets based on the fusion statistics in response to the situation where the sensor data packets are lost.

[0096] For example, you can view the data recorded in each statistical frame in the fused statistics. If you find that the data packet header corresponding to sensor B is not recorded in a statistical frame, but the data reporting cycle of sensor B determines that the data packet header corresponding to sensor B should be recorded in that statistical frame, then you can determine that sensor B has a data packet loss situation.

[0097] The data reinjection method provided by the embodiments of the present invention will be described in detail below through specific examples.

[0098] like Figure 6 As shown, the data reinjection method provided in the embodiments of the present invention may include:

[0099] S201, acquire sensor fusion information pre-recorded during real vehicle testing;

[0100] The sensor fusion information may include fusion statistics and at least one sensor data packet;

[0101] S202, Is this the first time data backfeeding has been performed? If yes, proceed to step S203; otherwise, proceed to step S204.

[0102] S203, obtain the execution scheduling time ft1 in the first statistical frame of the fused statistical information;

[0103] S204, obtain the execution scheduling time ftn in the nth statistical frame of the fused statistical information;

[0104] S205, Determine whether the statistical frame has been lost. If yes, proceed to step S206; otherwise, proceed to step S211.

[0105] In this step, based on the fusion statistics, it can be determined whether the difference between the frame count corresponding to the current fusion operation and the frame count corresponding to the previous fusion operation is greater than 1; if yes, packet loss is determined; if no, no packet loss is determined.

[0106] S206, Calculate the number of lost packets;

[0107] The number of lost packets equals the count difference minus 1.

[0108] S207. Is the number of lost packets within the preset range? If yes, proceed to step S208; otherwise, proceed to step S210.

[0109] S208, calculate the estimated scheduling time fti corresponding to the lost statistical frames;

[0110] S209, based on the estimated scheduling time fti, search for sensor data packets whose received time rt is less than the estimated scheduling time fti in the unfollowed sensor data packets, and obtain the measurement data and measurement occurrence time from them; proceed to step S212;

[0111] S210, data invalid, end reflow;

[0112] S211, Based on the information in the statistical frame, search for the measurement data and measurement time required for this fusion operation in the sensor data packet;

[0113] S212, Generate reinjection data based on the found measurement data and the time when the measurement occurred;

[0114] S213, provide the recharge data to the tested object to complete this recharge;

[0115] S214. Has the traversal of the integrated statistical information ended? If yes, proceed to step S215; otherwise, proceed to step S202.

[0116] S215, End.

[0117] The data reinjection method provided by the embodiments of the present invention will be described in detail below with reference to specific sensor data of the vehicle.

[0118] In one embodiment of the present invention, the process in which the fusion operation takes place is periodically scheduled at a frequency of 20Hz, that is, the fusion operation is scheduled to be executed once every 50 milliseconds. Sensor data packets come from the forward-looking (Vis-Vision) sensor, the front radar (Rdr-FrontRadar), and the corner radar (CnrRdr-CornerRadar), respectively. Specifically, the forward-looking sensor transmits data at a frequency of 20Hz, that is, one frame of data is transmitted every 50 milliseconds; the front radar and corner radar sensors each transmit data at a frequency of 10Hz, that is, one frame of data is transmitted every 100 milliseconds. The structure of the multiple sensor data packets from the forward-looking sensor can be as follows: Figure 7 As shown, the structure of multiple sensor data packets of the front radar sensor can be as follows: Figure 8 As shown, the structure of each sensor data packet of the angle radar sensor can be as follows: Figure 9 As shown in the figure. Here, rt represents the receiving time, mt represents the measurement occurrence time, and data represents the specific data information from the sensor. All times in the figure are in milliseconds.

[0119] By recording the data packet headers, the scheduling execution time of the fusion operation, and the frame counts of the statistical frames from the aforementioned sensor data packets, a structure like this can be formed. Figure 10 The fusion statistics are shown below. Here, ft represents the scheduled execution time of the fusion operation.

[0120] It should be noted that in the fusion statistics, when the scheduling execution time is 500, the data packet header corresponding to the corner radar sensor is 0, indicating that no data reported by the corner radar sensor was received before this fusion operation. Figure 10 The situation is similar for other data packets with a header of 0, and will not be repeated here.

[0121] For example, a temporal relationship between the time when each sensor reports data and the scheduling execution time of each fusion operation can be as follows: Figure 11 As shown. By Figure 11 It can be seen that before the scheduling execution time ft1 of the first fusion operation, the first sensor data packet Vis1 from the vision sensor and the first sensor data packet Rdr1 from the front radar sensor were acquired. Therefore, the sensor data packets corresponding to the first fusion operation are Vis1 and Rdr1. Before the scheduling execution time ft2 of the second fusion operation, the second sensor data packet Vis2 from the vision sensor and the first sensor data packet CnRdr1 from the corner radar sensor were acquired. Therefore, the sensor data packets corresponding to the second fusion operation are Vis2 and CnRdr1, and so on.

[0122] In one implementation, such as Figure 12 As shown, if the second statistical frame (fn=2) in the fused statistical information is lost, the estimated scheduling time corresponding to the lost statistical frame can be determined as 550 according to the method described above. Then, based on the estimated scheduling time, the corresponding measurement data and measurement occurrence time can be found in each sensor data packet to generate the refeed data.

[0123] In one implementation, such as Figure 13 As shown, in the fusion statistics, the Vis2 header of the vision sensor is missing (0), indicating that there is packet loss during actual vehicle testing, and the processor did not receive the data from the sensor.

[0124] Secondly, embodiments of the present invention also provide a data recording method, which facilitates reducing or eliminating the difference between the reinjection test and the actual test, and effectively improves the test quality of the reinjection test.

[0125] like Figure 14 As shown, the data recording method provided in the embodiments of the present invention may include:

[0126] S31, In the actual vehicle test, receive the measurement data sent by each sensor and record the time of receiving the measurement data;

[0127] S32, generate a corresponding sensor data packet based on each measurement data and its corresponding reception time. The sensor data packet includes a data packet header and the measurement data. The data packet header includes the reception time.

[0128] S33, at each preset time interval, a fusion operation is performed on each of the sensor data packets generated within the preset time interval, and a corresponding statistical frame is generated. The statistical frame includes the scheduling execution time of the fusion operation and the data packet header of each of the sensor data packets generated within the preset time interval; the statistical frames corresponding to each fusion operation form fusion statistical information.

[0129] S34, Record sensor fusion information based on the sensor data packets and the fusion statistics.

[0130] The data recording method provided by the embodiments of the present invention can receive measurement data sent by various sensors and record the reception time of the measurement data in actual vehicle testing. A corresponding sensor data packet is generated based on each measurement data and its corresponding reception time. A fusion operation is performed on each sensor data packet generated within a preset time interval, and a corresponding statistical frame is generated. The statistical frame includes the scheduling execution time of the fusion operation and the data packet header of each sensor data packet generated within the preset time interval. The statistical frames corresponding to each fusion operation form fusion statistical information. Sensor fusion information is recorded based on each sensor data packet and the fusion statistical information. This approach facilitates, on the one hand, determining which sensor data packets correspond to the current fusion operation and require fusion based on the scheduling execution time in each statistical frame and the reception time in the header of each data packet within each statistical frame during data refeeding. On the other hand, it allows for the identification of the sensor data packets corresponding to the current fusion operation from among the various sensor data packets during data refeeding, based on the headers of the data packets in the statistical frames and the headers of each sensor data packet. The identified sensor data packets are then used to generate refeeding data for refeeding testing. This enables a more accurate replication of the sensor data packets required for each fusion operation under actual vehicle testing conditions, and the generation of refeeding data from these sensor data packets. Therefore, it effectively reduces or eliminates the discrepancy between refeeding testing and actual testing, significantly improving the quality of refeeding testing.

[0131] Specifically, in one embodiment of the present invention, step S31, receiving measurement data sent by each sensor and recording the reception time of the measurement data during the actual vehicle test, may include: receiving raw data packets sent by each sensor and recording the reception time of the raw data packets during the actual vehicle test, wherein the raw data packets include the measurement data and the measurement occurrence time of the measurement data. Based on this, step S32, generating a corresponding sensor data packet based on each measurement data and its corresponding reception time, may include: generating a corresponding sensor data packet based on each raw data packet and its corresponding reception time. For example, in one embodiment, a schematic diagram of sensor data packet generation may be as follows: Figure 15 As shown.

[0132] Furthermore, in the above embodiments, the data packet header can be used to generate sensor data packets, but the embodiments of the present invention are not limited thereto. In other embodiments of the present invention, in addition to being used to assemble sensor data packets, the data packet header can also be used to generate statistical frames and further generate fused statistical information.

[0133] Specifically, in embodiments of the present invention, the number of sensors can be at least one, and the data reporting times of each sensor can be the same or different, as can the data reporting periods of each sensor. In one embodiment, the system is configured with M sensors. During each fusion operation, the headers of all M sensor data packets can be recorded, along with the scheduling execution time ft (fusion timestamp) of this fusion operation. The reception time rt recorded in the header of each sensor's data packet is always less than the scheduling execution time ft of this fusion operation. Since the frequency of receiving sensor data typically depends on the frequency of sensor data reporting, and the reporting frequencies of different sensors are usually different, the sensor data packets received during each fusion operation may include one or more packets, or zero packets, meaning no current sensor data has been received.

[0134] In embodiments of the present invention, the data packet header and the scheduling execution time of a fusion operation can be referred to as a statistical frame, the information recorded within it as follows: Figure 4 As shown, This represents the reception time of the p-th packet of data received by the m-th sensor in this fusion operation. Similarly, the time of measurement occurrence is indicated, where The value depends on the frequency at which the sensor sends data.

[0135] Furthermore, in some embodiments of the present invention, the statistical frame may include not only the data packet header and the scheduling execution time of the fusion operation, but also a frame count, which increases by 1 each time a fusion operation is performed.

[0136] After obtaining the data packets and fusion statistics of each sensor, sensor fusion information can be recorded in step S33 based on the data packets and fusion statistics. Specifically, in one embodiment, the data packets and fusion statistics of each sensor can be sent to a recording data industrial control computer to record the sensor fusion information.

[0137] The data recording method provided by the embodiments of the present invention will be described in detail below through a specific example.

[0138] like Figure 16 As shown, the data recording method provided in the embodiments of the present invention may include:

[0139] S41, In the actual vehicle test, the raw data packets sent by each sensor are received and the time of receipt of the raw data packets is recorded. The raw data packets include measurement data and the time when the measurement data is measured.

[0140] S42, generate a corresponding sensor data packet based on each raw data packet and its corresponding receiving time, and send the sensor data packet to the recording data industrial control computer to record the sensor data packet through the recording data industrial control computer;

[0141] S43. At each preset time interval, a fusion operation is performed on each sensor data packet generated within the preset time interval, and a corresponding statistical frame is generated. The statistical frame includes the scheduling execution time of the fusion operation, the data packet header of each sensor data packet generated within the preset time interval, and the frame count. The statistical frame is sent to the recording data industrial control computer so that each statistical frame can be recorded by the recording data industrial control computer to form fusion statistical information.

[0142] Thirdly, embodiments of the present invention provide a data reinjection device that can effectively reduce or eliminate the difference between reinjection tests and actual tests, thereby effectively improving the test quality of reinjection tests.

[0143] like Figure 17 As shown, the data reinjection device provided in the embodiments of the present invention may include:

[0144] The acquisition unit 51 is used to acquire sensor fusion information pre-recorded during actual vehicle testing. The sensor fusion information includes fusion statistics and at least one sensor data packet. Each sensor data packet includes a data packet header and measurement data. The data packet header includes the reception time when the measurement data is received by the processor. The fusion statistics include at least one statistical frame. Each statistical frame includes the scheduling execution time of a fusion operation and the data packet header in the sensor data packet to be fused corresponding to the fusion operation.

[0145] The first generation unit 52 is used to generate recharge data based on the sensor fusion information;

[0146] The providing unit 53 is used to provide the recharge data to the object under test so that the object under test can use the recharge data for testing.

[0147] The data recharge device provided in the embodiments of the present invention can acquire sensor fusion information pre-recorded during actual vehicle testing, generate recharge data based on the sensor fusion information, and provide the recharge data to the test object so that the test object can use the recharge data for testing. Since the sensor fusion information includes fusion statistics and at least one sensor data packet, and each statistical frame of the fusion statistics includes the scheduling execution time of a fusion operation and the data packet header of the sensor data packet to be fused corresponding to the fusion operation, it is possible to determine which sensor data packets are the sensor data packets to be fused for this fusion operation based on the scheduling execution time in each statistical frame and the reception time in the data packet header of each statistical frame. On the other hand, it is possible to find the sensor data packets to be fused for this fusion operation from each sensor data packet based on the data packet header in the statistical frame and the data packet header in each sensor data packet, and use the found sensor data packets to generate backfeed data for backfeed testing. In this way, it is possible to more accurately reproduce the sensor data packets to be fused for each fusion operation under the actual vehicle test conditions, and use these sensor data packets to generate backfeed data for each test. Therefore, it is possible to effectively reduce or eliminate the difference between backfeed testing and actual testing, and effectively improve the test quality of backfeed testing.

[0148] In one embodiment, the data packet header further includes the measurement occurrence time of the measurement data; the first generation unit 52 may include:

[0149] The first search module is used to search, according to the fusion statistics, the measurement data required for each fusion operation and the measurement time of the measurement data in each of the sensor data packets to be fused.

[0150] The first generation module is used to generate the reinjection data required for each reinjection operation sequentially based on the found measurement data and the time when the measurement occurred.

[0151] The providing unit 53 is specifically used to provide the successively generated backflow data to the object under test, so that the object under test can use the backflow data for testing.

[0152] In one implementation, the first search module may include:

[0153] The first determining submodule is used to determine the statistical frame corresponding to the current fusion operation based on the fusion statistics information for each fusion operation, and obtain the target statistical frame.

[0154] The second determining submodule is used to determine whether the receiving time contained in the header of each data packet in the target statistical frame is less than the scheduling execution time in the target statistical frame;

[0155] The lookup submodule is used to, when the receiving time is less than the scheduling execution time, use the data packet header in the target statistical frame as the query index to find the measurement data corresponding to the query index and the measurement occurrence time of the measurement data in each of the sensor data packets.

[0156] In one implementation, the lookup submodule is specifically used for:

[0157] Using the data packet header in the target statistical frame as a query index, the target data packet is obtained by searching for the sensor data packet whose header matches the query index in each of the sensor data packets;

[0158] The measurement data and the measurement occurrence time in the target data packet are determined as the measurement data and the measurement occurrence time of the measurement data corresponding to the query index.

[0159] In one implementation, the statistical frame further includes a frame count;

[0160] The first generation unit 52 may include:

[0161] The first determining module is used to determine, based on the fusion statistics, whether the difference between the frame count corresponding to the current fusion operation and the frame count corresponding to the previous fusion operation is greater than 1.

[0162] The second determining module is used to determine, when the count difference is greater than 1, that there are missing statistical frames in the fused statistical information;

[0163] The third determining module is used to determine the estimated scheduling time of each of the lost statistical frames based on the count difference and the scheduling period of the fusion operation.

[0164] The second search module is used to search for the supplementary data packet corresponding to the current estimated scheduling time in each of the sensor data packets that have not been fed back for each estimated scheduling time.

[0165] The second generation module is used to generate supplementary backfeed data based on the supplementary data packet.

[0166] In one implementation, the number of lost statistical frames is at least one; each lost statistical frame corresponds to an estimated scheduling time, wherein the supplementary data packet corresponding to the smallest estimated scheduling time is a first sensor data packet, the reception time in the first sensor data packet is greater than the scheduling execution time of the previous fusion operation and less than the smallest estimated scheduling time, and the reception time in the first sensor data packet is not recorded in the statistical frame corresponding to the current fusion operation; among the estimated scheduling times, the supplementary data packet corresponding to each estimated scheduling time other than the smallest estimated scheduling time is a second sensor data packet, the reception time in the second sensor data packet is greater than the previous estimated scheduling time and less than the current estimated scheduling time, and the reception time in the second sensor data packet is not recorded in the statistical frame corresponding to the current fusion operation.

[0167] In one embodiment, the data reinjection device further includes:

[0168] The determining unit is used to determine whether there is a situation of sensor data packet loss after acquiring the sensor fusion information pre-recorded in the actual vehicle test, based on the fusion statistics and the data reporting cycle of each sensor known in advance;

[0169] A positioning unit is used to locate the sensor that has experienced packet loss based on the fused statistical information in response to the situation where the sensor data packets are lost.

[0170] In one embodiment, the measurement data in the at least one sensor data packet comes from at least one sensor, and the data reporting times of each sensor are the same or different, and the data reporting periods of each sensor are the same or different.

[0171] Fourthly, embodiments of the present invention also provide a data recording device, which facilitates reducing or eliminating the difference between the reinjection test and the actual test, and effectively improves the test quality of the reinjection test.

[0172] like Figure 18As shown, the data recording apparatus provided in the embodiments of the present invention may include:

[0173] The receiving unit 61 is used to receive measurement data sent by each sensor and record the time of receiving the measurement data during actual vehicle testing.

[0174] The second generation unit 62 is used to generate a corresponding sensor data packet based on each measurement data and its corresponding reception time. The sensor data packet includes a data packet header and the measurement data. The data packet header includes the reception time.

[0175] The third generation unit 63 is used to perform a fusion operation on each of the sensor data packets generated within the preset time interval at a preset time interval, and generate a corresponding statistical frame. The statistical frame includes the scheduling execution time of the fusion operation and the data packet header of each of the sensor data packets generated within the preset time interval; the statistical frames corresponding to each fusion operation form fusion statistical information.

[0176] The recording unit 64 is used to record sensor fusion information based on the sensor data packets and the fusion statistics.

[0177] The data recording device provided in the embodiments of the present invention can receive measurement data sent by various sensors and record the reception time of the measurement data during actual vehicle testing. It generates a corresponding sensor data packet based on each measurement data and its corresponding reception time. At preset time intervals, it performs a fusion operation on each sensor data packet generated within the preset time interval and generates a corresponding statistical frame. The statistical frame includes the scheduling execution time of the fusion operation and the data packet header of each sensor data packet generated within the preset time interval. The statistical frames corresponding to each fusion operation form fusion statistical information. Sensor fusion information is recorded based on each sensor data packet and the fusion statistical information. This approach facilitates, on the one hand, determining which sensor data packets correspond to the current fusion operation and require fusion based on the scheduling execution time in each statistical frame and the reception time in the header of each data packet within each statistical frame during data refeeding. On the other hand, it allows for the identification of the sensor data packets corresponding to the current fusion operation from among the various sensor data packets during data refeeding, based on the headers of the data packets in the statistical frames and the headers of each sensor data packet. The identified sensor data packets are then used to generate refeeding data for refeeding testing. This enables a more accurate replication of the sensor data packets required for each fusion operation under actual vehicle testing conditions, and the generation of refeeding data from these sensor data packets. Therefore, it effectively reduces or eliminates the discrepancy between refeeding testing and actual testing, significantly improving the quality of refeeding testing.

[0178] In one embodiment, the receiving unit 61 is specifically used to receive raw data packets sent by each sensor and record the receiving time of the raw data packets during actual vehicle testing. The raw data packets include the measurement data and the measurement time of the measurement data.

[0179] In one embodiment, the second generation unit 62 is specifically used to generate a corresponding sensor data packet based on each of the original data packets and its corresponding receiving time.

[0180] In one embodiment, the recording unit 64 is specifically used to send each of the sensor data packets and the fusion statistical information to the recording data industrial control computer, so as to record the sensor fusion information through the recording data industrial control computer.

[0181] In one implementation, the statistical frame further includes a frame count; the frame count is incremented by 1 each time the fusion operation is performed.

[0182] In one embodiment, the number of sensors is at least one, and the data reporting times of each sensor may be the same or different, and the data reporting periods of each sensor may be the same or different.

[0183] Fifthly, embodiments of the present invention provide a data reinjection system that can effectively reduce or eliminate the difference between reinjection testing and actual testing, thereby effectively improving the testing quality of reinjection testing.

[0184] like Figure 19 As shown, embodiments of the present invention also provide a data recovery system, including a data recording device 6 and a data recovery device 5, wherein the data recording device 6 and the data recovery device 5 are communicatively connected; wherein the data recording device is used to implement any of the data recording methods provided in the foregoing embodiments, and the data recovery device is used to implement any of the data recovery methods provided in the foregoing embodiments. Therefore, the corresponding technical effects can also be achieved, as has been described in detail above, and will not be repeated here.

[0185] Sixthly, embodiments of the present invention also provide an electronic device that can effectively reduce or eliminate the difference between the reflow test and the actual test, thereby effectively improving the test quality of the reflow test.

[0186] like Figure 20 As shown, the electronic device provided in the embodiments of the present invention may include: a processor 71 and a memory 72, wherein the processor 71 and the memory 72 are electrically connected; the memory 72 is used to store executable program code; the processor 71 runs a program corresponding to the executable program code by reading the executable program code stored in the memory 72, so as to implement any of the data backfilling method or data recording method provided in the foregoing embodiments.

[0187] The specific execution process of the above steps by the processor 71, as well as the steps further executed by the processor 71 by running executable program code, can be found in the description of the foregoing embodiments, and will not be repeated here.

[0188] In a seventh aspect, embodiments of the present invention also provide a computer-readable storage medium storing one or more programs, which can be executed by one or more processors to implement any of the data backfeeding methods or data recording methods provided in the foregoing embodiments, thus achieving the corresponding technical effects. This has been described in detail above and will not be repeated here.

[0189] It should be noted that, in this document, relational terms such as "first" and "second" are used only 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 one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0190] The various embodiments in this specification are described in a related manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0191] In particular, the device embodiment is basically similar to the method embodiment, so the description is relatively simple. For relevant details, please refer to the description of the method embodiment.

[0192] For ease of description, the above apparatus is described by dividing it into various functional units / modules. Of course, in implementing this invention, the functions of each unit / module can be implemented in one or more software and / or hardware.

[0193] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0194] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A data reinjection method, characterized in that, include: The sensor fusion information is obtained from pre-recorded sensor fusion information during real vehicle testing. The sensor fusion information includes fusion statistics and at least one sensor data packet. Each sensor data packet includes a data packet header and measurement data. The data packet header includes the reception time when the measurement data is received by the processor. The fusion statistics include at least one statistical frame. Each statistical frame includes the scheduling execution time of a fusion operation and the data packet header in the sensor data packet to be fused corresponding to the fusion operation. Reinjection data is generated based on the sensor fusion information; The recharge data is provided to the object under test so that the object under test can use the recharge data for testing.

2. The data reinjection method according to claim 1, characterized in that, The data packet header also includes the measurement time of the measurement data; the generation of feedback data based on the sensor fusion information includes: Based on the fusion statistics, the measurement data required for each fusion operation and the measurement time of the measurement data are searched sequentially in each of the sensor data packets to be fused. Based on the measured data found and the time when the measurement occurred, the reinjection data required for each reinjection operation is generated sequentially. Providing the reflowed data to the test object so that the test object can use the reflowed data for testing includes: The successively generated backflow data is provided to the object under test so that the object under test can use the backflow data for testing.

3. The data reinjection method according to claim 2, characterized in that, The step of sequentially searching for the measurement data required for each fusion operation and the measurement occurrence time of the measurement data in each of the sensor data packets to be fused based on the fusion statistics includes: For each fusion operation, the statistical frame corresponding to the current fusion operation is determined based on the fusion statistics information, and the target statistical frame is obtained; Determine whether the reception time contained in the header of each data packet in the target statistical frame is less than the scheduling execution time in the target statistical frame; If the receiving time is less than the scheduling execution time, the data packet header in the target statistical frame is used as the query index to search for the measurement data corresponding to the query index and the measurement occurrence time of the measurement data in each of the sensor data packets.

4. The data reinjection method according to claim 3, characterized in that, The step of using the header information of the data packet in the target statistical frame as a query index to find the measurement data corresponding to the query index and the measurement time of the measurement data in each of the sensor data packets includes: Using the data packet header in the target statistical frame as a query index, the target data packet is obtained by searching for the sensor data packet whose header matches the query index in each of the sensor data packets; The measurement data and the measurement occurrence time in the target data packet are determined as the measurement data and the measurement occurrence time of the measurement data corresponding to the query index.

5. The data reinjection method according to claim 1, characterized in that, The statistical frames also include frame counts; The generation of reinjection data based on the sensor fusion information includes: Based on the fusion statistics, determine whether the difference between the frame count corresponding to the current fusion operation and the frame count corresponding to the previous fusion operation is greater than 1; If the count difference is greater than 1, it is determined that there are missing statistical frames in the fused statistics. Based on the count difference and the scheduling period of the fusion operation, the estimated scheduling time of each lost statistical frame is determined; For each estimated scheduling time, search for the supplementary data packet corresponding to the current estimated scheduling time in each of the sensor data packets that have not been fed back; Supplementary backfeed data is generated based on the supplementary data packet.

6. The data reinjection method according to claim 5, characterized in that, The number of lost statistical frames is at least one; each lost statistical frame corresponds to an estimated scheduling time, wherein the supplementary data packet corresponding to the smallest estimated scheduling time is a first sensor data packet, the reception time in the first sensor data packet is greater than the scheduling execution time of the previous fusion operation and less than the smallest estimated scheduling time, and the reception time in the first sensor data packet is not recorded in the statistical frame corresponding to the current fusion operation; among the estimated scheduling times, the supplementary data packet corresponding to each estimated scheduling time other than the smallest estimated scheduling time is a second sensor data packet, the reception time in the second sensor data packet is greater than the previous estimated scheduling time and less than the current estimated scheduling time, and the reception time in the second sensor data packet is not recorded in the statistical frame corresponding to the current fusion operation.

7. The data reinjection method according to claim 1, characterized in that, After acquiring the sensor fusion information pre-recorded during the actual vehicle test, the method further includes: Based on the fused statistical information and the pre-known data reporting cycle of each sensor, determine whether there is a situation where the sensor data packets are lost; In response to the occurrence of sensor data packet loss, the sensor experiencing packet loss is located based on the fused statistical information.

8. The data reinjection method according to claim 1, characterized in that, The measurement data in the at least one sensor data packet comes from at least one sensor, and the data reporting time of each sensor may be the same or different, and the data reporting period of each sensor may be the same or different.

9. A data reinjection device, characterized in that, include: The acquisition unit is used to acquire sensor fusion information pre-recorded during real vehicle testing. The sensor fusion information includes fusion statistics and at least one sensor data packet. Each sensor data packet includes a data packet header and measurement data. The data packet header includes the reception time when the measurement data is received by the processor. The fusion statistics include at least one statistical frame. Each statistical frame includes the scheduling execution time of a fusion operation and the data packet header in the sensor data packet to be fused corresponding to the fusion operation. The first generation unit is used to generate reinjection data based on the sensor fusion information; A providing unit is configured to provide the recharged data to the object under test so that the object under test can use the recharged data for testing.

10. An electronic device, characterized in that, include: A processor and a memory, wherein the processor and the memory are electrically connected; The memory is used to store executable program code; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the data backfilling method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs, which can be executed by one or more processors to implement the data backfeeding method according to any one of claims 1 to 8.

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