A data processing method, apparatus, system, electronic device and storage medium

Abstract

A data processing method, device, system, electronic device and storage medium disclosed by an embodiment of the present application include obtaining a first pose data set of a vehicle, a second pose data set of a target object, and a third pose data set of the vehicle relative to the target object, and determining perception error information of an in-vehicle camera device according to the first pose data set, the second pose data set, and the third pose data set. The sampling times of the first pose data set, the second pose data set, and the third pose data set are the same. The first pose data set and the second pose data set are collected based on a positioning device on the vehicle, and the third pose data set is collected based on the in-vehicle camera device. Based on the embodiment of the present application, the pose data set of the target object detected by the in-vehicle camera device can be verified, and data can be obtained through the satellite positioning system, so as to improve the accuracy of the collected data and the correctness of the verification.

Description

Technical Field

[0001] The present invention relates to the field of data processing of vehicle-mounted camera devices, and in particular to a data processing method, device, system, electronic device and storage medium. Background Art

[0002] Driverless is the mainstream of the current development of automotive technology. As the core technology of driverless, the vehicle lateral control system collects the left and right lane lines through vehicle-mounted camera devices, and calculates the distance between the vehicle and the left and right lane lines in real time to automatically control the vehicle steering, ensuring that the vehicle travels within its own lane, which can greatly reduce traffic accidents caused by the vehicle deviating from the lane. The traditional verification of the lane lines collected by vehicle-mounted camera devices mostly relies on manual verification, which not only has low verification efficiency, is time-consuming and laborious, but also has low verification accuracy and fails to achieve the expected effect.

[0003] In the existing verification methods, one method starts from the perspective of image processing, and collects the road surface image when the vehicle deviates from the lane through a camera temporarily installed on the front fender of the vehicle to obtain the distance between the vehicle and the left and right lane lines. This method uses an external camera to verify the lane line data collected by the vehicle's own camera, and the comparability of the obtained data is poor, and the true value of the lane lines collected by the vehicle's own camera cannot be effectively verified.

[0004] Another method is to perform coordinate transformation on the lane line information at the position of the vehicle itself in the high-precision map to obtain the position of the lane line point sequence in the vehicle coordinate system in the high-precision map, and then compare the position of the lane line point sequence in the vehicle coordinate system with the lane lines collected by the vehicle's own camera. This method is limited by the fact that the accuracy of the high-precision map cannot meet the requirements, the update is not timely, the regional differences are large, and the accuracy is difficult to guarantee. Summary of the Invention

[0005] The embodiments of the present application provide a data processing method, device, system, electronic device and storage medium, which can verify the motion data set of the target object detected by the vehicle-mounted camera device. Moreover, by performing differential correction on the first pose data set and the second pose data set, the detection accuracy of the positioning device on the vehicle can be further improved, and further the accuracy of the motion data set of the target object detected by the subsequent vehicle-mounted camera device can be improved. In addition, by obtaining the first pose data set of the vehicle and the second pose data set of the target object through the satellite positioning system, the accuracy of the collected first pose data set and second pose data set can be improved, which can make the data more comparable than the data collected by the peripheral camera, and can improve the correctness of the verification. Using this data processing method can improve the perception data processing method of the vehicle-mounted camera device to improve the detection accuracy of the vehicle-mounted camera device, and further improve the safety of the driving assistance system.

[0006] An embodiment of the present application provides a data processing method, which is used to process data collected by an in-vehicle camera device. The data processing method includes:

[0007] Obtain a first pose data set of the vehicle, a second pose data set of the target object, and a third pose data set of the vehicle relative to the target object;

[0008] Determine the perception error information of the in-vehicle camera device according to the first pose data set, the second pose data set, and the third pose data set;

[0009] Among them, the sampling times of the first pose data set, the second pose data set, and the third pose data set are the same. The first pose data set and the second pose data set are based on data collected by a positioning device on the vehicle, and the third pose data set is based on data collected by the in-vehicle camera device.

[0010] Further, before determining the perception error information of the in-vehicle camera device according to the first pose data set, the second pose data set, and the third pose data set, the method further includes:

[0011] Determine the positioning error data set of the positioning device;

[0012] Determining the perception error information of the in-vehicle camera device according to the first pose data set, the second pose data set, and the third pose data set includes:

[0013] Determine the perception error information of the in-vehicle camera device according to the positioning error data set, the first pose data set, the second pose data set, and the third pose data set.

[0014] Further, determining the positioning error data set of the positioning device includes:

[0015] Obtain the calibration position data set of the reference object;

[0016] Obtain the predicted position data set of the reference object based on the satellite positioning system;

[0017] Determine the positioning error data set of the positioning device according to the calibration position data set and the predicted position data set.

[0018] Further, determining the perception error information of the in-vehicle camera device according to the positioning error data set, the first pose data set, the second pose data set, and the third pose data set includes:

[0019] Determine a fourth pose data set of the vehicle relative to the target object according to the first pose data set and the second pose data set; the third pose data in the third pose data set corresponds one-to-one with the fourth pose data in the fourth pose data set;

[0020] Determine the perception error information of the vehicle-mounted camera device according to the third pose data set and the fourth pose data set.

[0021] Further, determine the fourth pose data set of the vehicle relative to the target object according to the first pose data set and the second pose data set, including:

[0022] Determine the first corrected pose data set of the vehicle according to the positioning error data set and the first pose data set;

[0023] Determine the second corrected pose data set of the target object according to the positioning error data set and the second pose data set;

[0024] Based on the relative information measuring instrument on the vehicle, determine the fourth pose data set of the vehicle relative to the target object according to the first corrected pose data set and the second corrected pose data set.

[0025] Further, based on the relative information measuring instrument on the vehicle, determine the fourth pose data set of the vehicle relative to the target object according to the first corrected pose data set and the second corrected pose data set, including:

[0026] Determine the local map corresponding to the target object based on the relative information measuring instrument and the second corrected pose data set;

[0027] Determine the position data of the vehicle on the local map based on the relative information measuring instrument and the first corrected pose data set;

[0028] Determine the fourth pose data set of the vehicle relative to the target object based on the local map.

[0029] Further, determine the perception error information of the vehicle-mounted camera device according to the third pose data set and the fourth pose data set, including:

[0030] Determine the error data set according to the corresponding third pose data and fourth pose data one by one;

[0031] Determine the perception error information of the vehicle-mounted camera device according to the error data set and the reference error threshold corresponding to each error data in the error data set.

[0032] Correspondingly, an embodiment of the present application provides a data processing device, which is used to process the data collected by the vehicle-mounted camera device. The data processing device includes:

[0033] An acquisition module, configured to acquire the first pose data set of the vehicle, the second pose data set of the target object, and the third pose data set of the vehicle relative to the target object;

[0034] A first determination module, configured to determine the perception error information of the vehicle-mounted camera device according to the first pose data set, the second pose data set, and the third pose data set;

[0035] Among them, the sampling times of the first pose dataset, the second pose dataset, and the third pose dataset are the same. The first pose dataset and the second pose dataset are data collected based on a positioning device on the vehicle, and the third pose dataset is data collected based on an in-vehicle camera device.

[0036] Furthermore, the above device further includes:

[0037] A second determination module, configured to determine a positioning error dataset of the positioning device before determining the perception error information of the in-vehicle camera device according to the first pose dataset, the second pose dataset, and the third pose dataset.

[0038] A first determination module, configured to determine the perception error information of the in-vehicle camera device according to the positioning error dataset, the first pose dataset, the second pose dataset, and the third pose dataset.

[0039] Furthermore, the second determination module includes

[0040] A first acquisition sub-module, configured to acquire a calibration position dataset of a reference object;

[0041] A second acquisition sub-module, configured to acquire a predicted position dataset of the reference object based on a satellite positioning system;

[0042] A first determination sub-module, configured to determine the positioning error dataset of the positioning device according to the calibration position dataset and the predicted position dataset.

[0043] Furthermore, the first determination module includes:

[0044] A second determination sub-module, configured to determine a fourth pose dataset of the vehicle relative to a target object according to the first pose dataset and the second pose dataset; the third pose data in the third pose dataset corresponds one-to-one with the fourth pose data in the fourth pose dataset;

[0045] A third determination sub-module, configured to determine the perception error information of the in-vehicle camera device according to the third pose dataset and the fourth pose dataset.

[0046] Furthermore, the second determination sub-module includes:

[0047] A first determination unit, configured to determine a first corrected pose dataset of the vehicle according to the positioning error dataset and the first pose dataset;

[0048] A second determination unit, configured to determine a second corrected pose dataset of the target object according to the positioning error dataset and the second pose dataset;

[0049] A third determination unit, configured to determine a fourth pose dataset of the vehicle relative to a target object based on a relative information measuring instrument on the vehicle, according to a first corrected pose dataset and a second corrected pose dataset.

[0050] Further, the third determination unit includes:

[0051] A first determination subunit, configured to determine a local map corresponding to the target object based on the relative information measuring instrument and the second corrected pose dataset;

[0052] A second determination subunit, configured to determine position data of the vehicle on the local map based on the relative information measuring instrument and the first corrected pose dataset;

[0053] Determine a fourth pose dataset of the vehicle relative to the target object based on the local map.

[0054] Further, the third determination sub-module includes:

[0055] A fourth determination unit, configured to determine an error dataset according to the corresponding third pose data and fourth pose data in a one-to-one correspondence;

[0056] A fifth determination unit, configured to determine the perception error information of the vehicle-mounted camera device according to the error dataset and the reference error threshold corresponding to each error data in the error dataset.

[0057] Correspondingly, an embodiment of the present application provides a perception error determination system for a vehicle-mounted camera device, including:

[0058] A positioning device, which is arranged on the vehicle and is configured to obtain a first pose dataset of the vehicle and a second pose dataset of the target object;

[0059] A vehicle-mounted camera device, which is arranged on the vehicle and is configured to obtain a third pose dataset of the vehicle relative to the target object;

[0060] A relative information measuring instrument, which is arranged on the vehicle and is configured to determine a fourth pose dataset of the vehicle relative to the target object according to the first pose dataset and the second pose dataset;

[0061] A processor, which is configured to load and execute to implement the above data processing method.

[0062] Correspondingly, an embodiment of the present application further provides an electronic device, which includes a processor and a memory, and at least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, at least one program, the code set or the instruction set is loaded and executed by the processor to implement the above data processing method.

[0063] Accordingly, an embodiment of the present application further provides a computer-readable storage medium, in which at least one instruction, at least one program, a code set or an instruction set is stored, and the at least one instruction, at least one program, the code set or the instruction set is loaded and executed by a processor to implement the above data processing method.

[0064] The embodiment of the present application has the following beneficial effects:

[0065] A data processing method, device, system, electronic device and storage medium disclosed in the embodiment of the present application include obtaining a first pose data set of a vehicle, a second pose data set of a target object, and a third pose data set of the vehicle relative to the target object, and determining perception error information of an in-vehicle camera device according to the first pose data set, the second pose data set and the third pose data set. Among them, the sampling times of the first pose data set, the second pose data set and the third pose data set are the same. The first pose data set and the second pose data set are data collected based on a positioning device on the vehicle, and the third pose data set is data collected based on the in-vehicle camera device. Based on the embodiment of the present application, the motion data set of the target object detected by the in-vehicle camera device can be verified. Moreover, by performing differential correction on the first pose data set and the second pose data set, the detection accuracy of the positioning device on the vehicle can be further improved, and further the accuracy of the motion data set of the target object detected by the subsequent in-vehicle camera device can be improved. In addition, by obtaining the first pose data set of the vehicle and the second pose data set of the target object through a satellite positioning system, the accuracy of the collected first pose data set and second pose data set can be improved, the data can be made more comparable with the data collected by the peripheral camera, and the correctness of the verification can be improved. Using this data processing method can improve the perception data processing method of the in-vehicle camera device to improve the detection accuracy of the in-vehicle camera device, and further improve the safety of the driving assistance system. Description of the Drawings

[0066] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0067] Figure 1 It is a schematic diagram of an application environment provided by an embodiment of the present application;

[0068] Figure 2 It is a flowchart of a data processing method provided by an embodiment of the present application;

[0069] Figure 3It is a schematic structural diagram of a satellite positioning system provided by an embodiment of the present application;

[0070] Figure 4 It is a schematic flowchart of another data processing method provided by an embodiment of the present application;

[0071] Figure 5 It is a schematic structural diagram of a data processing device provided by an embodiment of the present application. Detailed implementation manners

[0072] To make the objectives, technical solutions and advantages of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only one embodiment of the present application, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0073] As used herein, the term "embodiment" refers to specific features, structures or characteristics that may be included in at least one implementation manner of the present application. In the description of the embodiments of the present application, it should be understood that the orientation or positional relationship indicated by terms such as "upper", "top", "bottom", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device / system or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be construed as a limitation of the present application. Terms such as "first", "second", "third" and "fourth" are only used for descriptive purposes, and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, features defined with "first", "second", "third" and "fourth" etc. may explicitly or implicitly include one or more of such features. Moreover, terms such as "first", "second", "third" and "fourth" etc. are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include", "have" and "be" and any variations thereof are intended to cover non-exclusive inclusion.

[0074] Please refer to Figure 1 , which shows a schematic diagram of an application environment provided by an embodiment of the present application, including a vehicle 101 and lane lines 103. A satellite positioning system 1011, an in-vehicle camera device 1013 and an in-vehicle processor 1015 are installed on the vehicle. The satellite positioning system 1011 on the vehicle 101 may include a positioning instrument and a relative information measuring instrument.

[0075] Among them, the positioning device can be used to obtain the first pose data set of the vehicle and the second pose data set of the lane line. The first pose data set includes, but is not limited to, the position data of the vehicle in the vehicle coordinate system, and the second pose data set includes, but is not limited to, the position data of the lane line in the vehicle coordinate system. The on-vehicle camera device can obtain the third pose data set of the vehicle relative to the lane line, and the third pose data set includes, but is not limited to, the lateral distance and the included angle of the vehicle relative to the lane line. The relative information measuring instrument can be used to determine the fourth pose data set of the vehicle relative to the lane line according to the first pose data set and the second pose data set, and the fourth data set to be compared includes, but is not limited to, the lateral distance and the included angle of the vehicle relative to the lane line. The processor can determine the error information of the on-vehicle camera device according to the third pose data set and the fourth pose data set. The processor can be used to load and execute to implement the above data processing method.

[0076] In the embodiment of the present application, the motion data set of the target object detected by the on-vehicle camera device is verified. Moreover, by obtaining the first pose data set of the vehicle and the second pose data set of the target object through the satellite positioning system, the accuracy of the collected first pose data set and second pose data set can be improved, the comparability of the data can be made stronger compared with the data collected by the peripheral camera, and the correctness of the verification can be improved. Adopting this data processing method can improve the perception data processing method of the on-vehicle camera device to improve the detection accuracy of the on-vehicle camera device, and further improve the safety of the driving assistance system.

[0077] Embodiment 1

[0078] The following introduces a specific embodiment of a data processing method of the present application. Figure 2 It is a schematic flowchart of a data processing method provided by an embodiment of the present application. This specification provides the method operation steps as shown in the embodiment or flowchart, but based on routine or non-creative labor, there may be more or fewer operation steps. The step sequence listed in the embodiment is only one of many execution sequences and does not represent the only execution sequence. In actual execution, it can be executed in the order shown in the embodiment or the drawing or executed in parallel (for example, in an environment of parallel processors or multi-threaded processing).

[0079] In the embodiment of the present application, the data processing method can be used to process the data collected by the on-vehicle camera device, that is, to verify the pose data of the target object detected by the on-vehicle camera device. Among them, the on-vehicle camera device can be an on-vehicle camera or a driving recorder.

[0080] Specifically, as Figure 2 shown, the method may include:

[0081] S201: Obtain the first pose dataset of the vehicle, the second pose dataset of the target object, and the third pose dataset of the vehicle relative to the target object.

[0082] In the embodiments of the present application, a satellite positioning system, an in-vehicle camera device, and a processor may be provided on the vehicle. The satellite positioning system may include a positioning device and a relative information measuring instrument. The positioning device and the relative information measuring instrument may be arranged inside the vehicle, and the in-vehicle camera device may be arranged at the position corresponding to the license plate lamp of the license plate holder. The above-mentioned position setting is only an exemplary setting method listed in the embodiments of the present application and does not represent the only setting method.

[0083] In the embodiments of the present application, the target object may include objects without motion attributes such as lane lines, road railings, flower beds, etc.

[0084] In the embodiments of the present application, the positioning device may be a positioning instrument RT, and the relative information measuring instrument may be an RT range. Figure 3 It is a schematic structural diagram of the satellite positioning system provided by the embodiments of the present application. By obtaining the first pose dataset of the vehicle and the second pose dataset of the target object through the satellite positioning system, the accuracy of the collected first pose dataset and second pose dataset can be improved, and the data can be made more comparable than the data collected by the camera device installed on the front fender of the vehicle.

[0085] In an alternative embodiment, during the process of controlling the vehicle to perform dotting positioning along the target object, that is, during the process of the vehicle performing dotting positioning along the lane line, the first pose dataset of the vehicle may be obtained based on the positioning instrument and transmitted to the relative information measuring instrument on the vehicle. Among them, the first pose dataset may include, but is not limited to, data such as images of the vehicle at each sampling moment. While obtaining the first pose dataset of the vehicle, the second pose dataset of the target object may be obtained based on the positioning instrument and transmitted to the relative information measuring instrument on the vehicle. Among them, the second pose dataset may include, but is not limited to, data such as images of the target object at each sampling moment. By obtaining the first pose dataset of the vehicle and the second pose dataset of the target object during the process of the vehicle performing dotting positioning along the target object, the accuracy of the pose dataset of the target object detected by the in-vehicle camera device in multiple scenarios can be verified.

[0086] In the embodiments of the present application, after obtaining the first pose dataset and the second pose dataset at each sampling moment, the first pose dataset and the second pose dataset may be mapped to the vehicle coordinate system to obtain information such as the horizontal and vertical coordinate data of the vehicle at each sampling moment, and the horizontal and vertical coordinate data of the target object at each sampling moment. By mapping the first pose dataset and the second pose dataset to the same coordinate system and unifying the reference, the accuracy of the pose dataset of the target object detected by the in-vehicle camera device can be improved.

[0087] In the embodiments of the present application, the in-vehicle camera device may obtain the third pose data set of the target object, and the third pose data set includes, but is not limited to, information such as the lateral distance and included angle between the vehicle and the target object at each sampling moment. The lateral distance and included angle may be data in the vehicle coordinate system or data in the coordinate system of the in-vehicle camera device.

[0088] In an alternative embodiment, the in-vehicle camera device may obtain information such as the image data of the target object at each sampling moment, and then, through the perception data processing method corresponding to the in-vehicle camera device, output information such as the lateral distance and included angle of the target object in the coordinate system of the in-vehicle camera device. Then, through the conversion rule between the in-vehicle camera device and the vehicle coordinate system, a third pose data set including the lateral distance and included angle of the target object in the vehicle coordinate system can be obtained. Then, it can be transmitted to the CAN on the vehicle in the form of a message. By obtaining the lateral distance and included angle between the vehicle and the target object in the vehicle coordinate system based on the in-vehicle camera device, the resources of the processor can be saved.

[0089] In the embodiments of the present application, the first pose data set, the second pose data set, and the third pose data set may be stored in the data storage unit of the processor. The data storage unit may perform processing such as removing burr points, flash points, and adding positioning points on the first pose data set, the second pose data set, and the third pose data set.

[0090] S203: Determine the perception error information of the in-vehicle camera device according to the first pose data set, the second pose data set, and the third pose data set; wherein, the sampling times of the first pose data set, the second pose data set, and the third pose data set are the same, the first pose data set and the second pose data set are data collected based on the positioning device on the vehicle, and the third pose data set is data collected based on the in-vehicle camera device.

[0091] In the embodiments of the present application, the processor may determine the fourth pose data set of the target object according to the first pose data set and the second pose data set, and determine the perception error information of the in-vehicle camera device according to the third pose data set and the fourth pose data set.

[0092] In an alternative embodiment, after the relative information measuring instrument obtains the first pose data set and the second pose data set, it can determine the local map corresponding to the target object according to the second pose data set, that is, generate the local map of the lane line, and then determine the position data of the vehicle on the local map corresponding to the target object according to the first pose data set, that is, map the vehicle and the lane line to the same local map, and the coordinate system corresponding to this map can be the vehicle coordinate system. Then, based on the local map, information such as the lateral distance and included angle of the vehicle relative to the target object can be determined, and then transmitted to the CAN on the vehicle in the form of a message.

[0093] In the embodiments of the present application, the processor can use the message acquisition tool canalyzer to obtain the third pose data set of the vehicle relative to the target object acquired by the on-vehicle camera device and the fourth pose data set of the vehicle relative to the target object output by the relative information measuring instrument at the same sampling moment. Among them, the third pose data in the third pose data set and the fourth pose data in the fourth pose data set are in one-to-one correspondence. For example, the lateral distance of the vehicle relative to the target object collected by the on-vehicle camera device corresponds to the lateral distance of the vehicle relative to the target object output by the relative information measuring instrument, and the included angle of the vehicle relative to the target object collected by the on-vehicle camera device corresponds to the included angle of the vehicle relative to the target object output by the relative information measuring instrument. Then, the perception error information of the on-vehicle camera device can be determined according to the third pose data set and the fourth pose data set.

[0094] In an alternative embodiment, a reference error threshold set can be preset in advance, and the reference error threshold set can include a lateral distance error threshold X 0 , an included angle error threshold θ 0 . The processor can determine the error data set according to the one-to-one corresponding third pose data and fourth pose data. The error data set can be the error data set corresponding to each sampling moment. Then, the perception error information of the on-vehicle camera device can be determined according to the error data and the reference error threshold corresponding to each error data in the error data set. Optionally, the lateral distance X 1 of the vehicle relative to the target object collected by the on-vehicle camera device and the lateral distance X 2 of the vehicle relative to the target object output by the relative information measuring instrument can be used to determine the lateral distance error ΔX = X 1 - X 2 . The included angle θ 1 of the vehicle relative to the target object collected by the on-vehicle camera device and the included angle θ 2 of the vehicle relative to the target object output by the relative information measuring instrument can be used to determine the included angle error Δθ = θ 1 - θ 2 , and the lateral distance error ΔX and the lateral distance error threshold X 0Compare the included angle error Δθ with the included angle error threshold θ 0 Compare. If the lateral distance error ΔX is less than the lateral distance error threshold X 0 , and the included angle error Δθ is less than the included angle error threshold θ 0 , it can be determined that the perception error information of the vehicle-mounted camera device is "better accuracy" or "the vehicle-mounted camera device has qualified accuracy". If the lateral distance error ΔX is less than the lateral distance error threshold X 0 , and the included angle error Δθ is greater than or equal to the included angle error threshold θ 0 , or, the lateral distance error ΔX is greater than or equal to the lateral distance error threshold X 0 , and the included angle error Δθ is less than the included angle error threshold θ 0 , or, the lateral distance error ΔX is greater than or equal to the lateral distance error threshold X 0 , and the included angle error Δθ is greater than or equal to the included angle error threshold θ 0 , it can be determined that the perception error information of the vehicle-mounted camera device is "poor accuracy" or "the vehicle-mounted camera device has unqualified accuracy".

[0095] Adopt the data processing method provided by the embodiment of the present application to verify the motion data set of the target object detected by the vehicle-mounted camera device. Moreover, by obtaining the first pose data set of the vehicle and the second pose data set of the target object through the satellite positioning system, the accuracy of the collected first pose data set and second pose data set can be improved, the comparability of the data can be made stronger compared with the data collected by the peripheral camera, and the correctness of the verification can be improved. Using this data processing method can improve the perception data processing method of the vehicle-mounted camera device to improve the detection accuracy of the vehicle-mounted camera device, and further improve the safety of the driving assistance system.

[0096] Embodiment 2

[0097] The following introduces a specific embodiment of a data processing method of the present application Figure 4 It is a flowchart of another data processing method provided by the embodiment of the present application. This specification provides the method operation steps as shown in the embodiment or flowchart, but based on routine or non-creative labor, more or fewer operation steps may be included. The step order listed in the embodiment is only one of many execution orders and does not represent the only execution order. In actual execution, it can be executed in the order shown in the embodiment or the drawing or executed in parallel (for example, in an environment of parallel processors or multi-threaded processing).

[0098] In the embodiment of the present application, the data processing method can be used to process the data collected by the vehicle-mounted camera device, that is, to verify the pose data of the target object detected by the vehicle-mounted camera device. Among them, the vehicle-mounted camera device can be a vehicle-mounted camera or a driving recorder.

[0099] Specifically, as Figure 4 shown, the method may include:

[0100] S401: Determine the positioning error data set of the positioning device.

[0101] In the embodiments of the present application, a satellite positioning system, an in-vehicle camera device, and a processor may be provided on a vehicle. The satellite positioning system may include a positioning device and a relative information measuring instrument. The positioning device and the relative information measuring instrument may be provided inside the vehicle, and the in-vehicle camera device may be provided at a position corresponding to the license plate lamp of the license plate holder. The above position setting is only an exemplary setting method listed in the embodiments of the present application and does not represent the only setting method.

[0102] In the embodiments of the present application, the target object may include objects without motion attributes such as lane lines, road railings, flower beds, etc.

[0103] In the embodiments of the present application, the positioning device may be a positioning instrument RT, and the relative information measuring instrument may be an RTrange. By obtaining the first pose data set of the vehicle and the second pose data set of the target object through the satellite positioning system, the accuracy of the collected first pose data set and second pose data set can be improved, and the data can be made more comparable than the data collected by the camera device installed on the front fender of the vehicle.

[0104] In the embodiments of the present application, since there are certain errors in satellite positioning, it is necessary to correct the first pose data set and the second pose data set obtained by the positioning device. The processor may obtain the calibration position data set of the reference object and obtain the predicted position data set of the reference object based on the satellite positioning system, and then may determine the positioning error data set of the positioning device according to the calibration position data set and the predicted position data set.

[0105] In a specific embodiment, the reference object may be a device capable of providing a feedback-calibrated position data set. For example, the reference object may be a base station. Therefore, the first pose data set and the second pose data set can be corrected based on the calibrated position and the pseudorange of the base station. After the base station is initialized, its absolute position in the spatial coordinate system can be output. Then, by comparing the absolute position of the base station with the satellite position of the base station detected by the satellite positioning system, the positioning error of the satellite positioning system can be calculated and transmitted to the locator. That is, while the positioning device obtains the first pose data set and the second pose data set, it also obtains the positioning error data. By transmitting the positioning error data set to the positioning device on the vehicle, differential correction can be performed on the first pose data set and the second pose data set. Compared with the data processing method in Embodiment 1, the detection accuracy of the positioning device on the vehicle can be further improved, and thus the accuracy of the motion data set of the target object detected by the subsequent vehicle-mounted camera device can be further improved.

[0106] S403: Obtain the first pose data set of the vehicle, the second pose data set of the target object, and the third pose data set of the vehicle relative to the target object.

[0107] In the embodiment of the present application, during the process of controlling the vehicle to perform dot positioning along the target object, that is, during the process of the vehicle performing dot positioning along the lane line, the first pose data set of the vehicle can be obtained based on the locator and transmitted to the relative information measuring instrument on the vehicle. The first pose data set may include, but is not limited to, data such as images of the vehicle at each sampling moment. While obtaining the first pose data set of the vehicle, the second pose data set of the target object can be obtained based on the locator and transmitted to the relative information measuring instrument on the vehicle. The second pose data set may include, but is not limited to, data such as images of the target object at each sampling moment. By obtaining the first pose data set of the vehicle and the second pose data set of the target object during the process of the vehicle performing dot positioning along the target object, the accuracy of the pose data set of the target object detected by the vehicle-mounted camera device in multiple scenarios can be verified.

[0108] In the embodiment of the present application, after obtaining the first pose data set and the second pose data set at each sampling moment, both the first pose data set and the second pose data set can be mapped to the vehicle coordinate system to obtain information such as the horizontal and vertical coordinate data of the vehicle at each sampling moment, and the horizontal and vertical coordinate data of the target object at each sampling moment. By mapping the first pose data set and the second pose data set to the same coordinate system to unify the reference, the accuracy of the pose data set of the target object detected by the vehicle-mounted camera device can be improved.

[0109] In the embodiments of the present application, the vehicle-mounted camera device can obtain the third pose data set of the target object, and the third pose data set includes, but is not limited to, information such as the lateral distance and included angle of the vehicle relative to the target object at each sampling moment. The lateral distance and included angle can be data in the vehicle coordinate system or data in the vehicle-mounted camera device coordinate system.

[0110] In an alternative embodiment, the vehicle-mounted camera device can obtain information such as the image data of the target object at each sampling moment, and then, through the perception data processing method corresponding to the vehicle-mounted camera device, output information such as the lateral distance and included angle of the target object in the vehicle-mounted camera device coordinate system. Then, through the conversion rule between the vehicle-mounted camera device and the vehicle coordinate system, a third pose data set including the lateral distance and included angle of the target object in the vehicle coordinate system can be obtained. Then it can be transmitted to the CAN on the vehicle in the form of a message. By obtaining the lateral distance and included angle of the vehicle relative to the target object in the vehicle coordinate system based on the vehicle-mounted camera device, the resources of the processor can be saved.

[0111] In the embodiments of the present application, the first pose data set, the second pose data set, and the third pose data set can be stored in the data storage unit of the processor. The data storage unit can perform processing such as removing burr points, flash points, and adding positioning points on the first pose data set, the second pose data set, and the third pose data set.

[0112] S405: Determine the perception error information of the vehicle-mounted camera device according to the positioning error data set, the first pose data set, the second pose data set, and the third pose data set; wherein, the sampling times of the first pose data set, the second pose data set, and the third pose data set are the same, the first pose data set and the second pose data set are data collected based on the positioning device on the vehicle, and the third pose data set is data collected based on the vehicle-mounted camera device.

[0113] In the embodiments of the present application, the processor can determine the third pose data set of the vehicle relative to the target object according to the positioning error data set, the first pose data set, and the second pose data set, and determine the perception error information of the vehicle-mounted camera device according to the third pose data set and the fourth pose data set.

[0114] In an alternative embodiment, after the relative information measuring instrument obtains the first pose data set, the second pose data set, and the positioning error data set, it can perform correction processing on the horizontal and vertical positions in the first pose data set and the horizontal and vertical positions in the second pose data set, output the lateral distance and angle of the vehicle relative to the target object, and obtain the fourth pose data set. Optionally, the processor can determine the first corrected pose data set of the vehicle according to the positioning error data set and the first pose data set, and determine the second corrected pose data set of the target object according to the positioning error data set and the second pose data set. Then, according to the first corrected pose data set and the second corrected pose data set, determine the fourth pose data set of the vehicle relative to the target object. Furthermore, it can be transmitted to the CAN on the vehicle in the form of a message.

[0115] In an alternative embodiment, after the relative information measuring instrument obtains the first corrected pose data set and the second corrected pose data set, it can determine the local map corresponding to the target object according to the second corrected pose data set, that is, generate the local map of the lane line. Furthermore, it can determine the position data of the vehicle on the local map corresponding to the target object according to the first corrected pose data set, that is, map the vehicle and the lane line to the same local map. The coordinate system corresponding to this map can be the vehicle coordinate system. After that, based on the local map, information such as the lateral distance and angle of the vehicle relative to the target object can be determined, and further, it can be transmitted to the CAN on the vehicle in the form of a message.

[0116] In the embodiments of the present application, the processor can use the message acquisition tool canalyzer to obtain the third pose data set of the vehicle relative to the target object obtained by the on-vehicle camera device and the fourth pose data set of the vehicle relative to the target object output by the relative information measuring instrument at the same sampling moment. Among them, the third pose data in the third pose data set and the fourth pose data in the fourth pose data set are in one-to-one correspondence. For example, the lateral distance of the vehicle relative to the target object collected by the on-vehicle camera device corresponds to the lateral distance of the vehicle relative to the target object output by the relative information measuring instrument, and the angle of the vehicle relative to the target object collected by the on-vehicle camera device corresponds to the angle of the vehicle relative to the target object output by the relative information measuring instrument. Then, the perception error information of the on-vehicle camera device can be determined according to the third pose data set and the fourth pose data set.

[0117] In an alternative embodiment, a reference error threshold set can be preset in advance. The reference error threshold set can include the lateral distance error threshold X 0 , the angle error threshold θ 0。The processor can determine an error data set based on the one-to-one corresponding third pose data and fourth pose data. This error data set can be the error data set corresponding to each sampling moment. Furthermore, the perception error information of the vehicle-mounted camera device can be determined based on the error data and the reference error threshold corresponding to each error data in the error data set. Optionally, the lateral distance X of the vehicle relative to the target object collected by the vehicle-mounted camera device 1 and the lateral distance X of the vehicle relative to the target object output by the relative information measuring instrument 2 are used to determine the lateral distance error ΔX = X 1 - X 2 . Based on the angle θ of the vehicle relative to the target object collected by the vehicle-mounted camera device 1 and the angle θ of the vehicle relative to the target object output by the relative information measuring instrument 2 , the angle error Δθ = θ 1 - θ 2 is determined. Then, the lateral distance error ΔX is compared with the lateral distance error threshold X 0 , and the angle error Δθ is compared with the angle error threshold θ 0 . If the lateral distance error ΔX is less than the lateral distance error threshold X 0 , and the angle error Δθ is less than the angle error threshold θ 0 , it can be determined that the perception error information of the vehicle-mounted camera device is "better accuracy" or "the vehicle-mounted camera device has qualified accuracy". If the lateral distance error ΔX is less than the lateral distance error threshold X 0 , and the angle error Δθ is greater than or equal to the angle error threshold θ 0 , or, the lateral distance error ΔX is greater than or equal to the lateral distance error threshold X 0 , and the angle error Δθ is less than the angle error threshold θ 0 , or, the lateral distance error ΔX is greater than or equal to the lateral distance error threshold X 0 , and the angle error Δθ is greater than or equal to the angle error threshold θ 0 , it can be determined that the perception error information of the vehicle-mounted camera device is "poor accuracy" or "the vehicle-mounted camera device has unqualified accuracy".

[0118] By using the data processing method provided in the embodiments of the present application, the motion data set of the target object detected by the vehicle-mounted camera device can be verified. Moreover, by performing differential correction on the first pose data set and the second pose data set, the detection accuracy of the positioning device on the vehicle can be further improved, and thus the accuracy of the motion data set of the target object detected by the subsequent vehicle-mounted camera device can be further improved. In addition, by obtaining the first pose data set of the vehicle and the second pose data set of the target object through the satellite positioning system, the accuracy of the collected first pose data set and second pose data set can be improved, making the data more comparable than the data collected by the peripheral camera and improving the correctness of the verification. By using this data processing method, the perception data processing method of the vehicle-mounted camera device can be improved to improve the detection accuracy of the vehicle-mounted camera device, and thus the safety of the driving assistance system can be improved.

[0119] An embodiment of the present application further provides a data processing device Figure 5 is a schematic structural diagram of a data processing device provided in an embodiment of the present application. This data processing device can be used to process the data collected by the vehicle-mounted camera device, that is, to verify the pose data of the target object detected by the vehicle-mounted camera device.

[0120] As Figure 5 shown, the device may include:

[0121] An acquisition module 501 is configured to acquire a first pose data set of the vehicle, a second pose data set of the target object, and a third pose data set of the vehicle relative to the target object;

[0122] A first determination module 503 is configured to determine the perception error information of the vehicle-mounted camera device according to the first pose data set, the second pose data set, and the third pose data set;

[0123] Wherein, the sampling times of the first pose data set, the second pose data set, and the third pose data set are the same. The first pose data set and the second pose data set are based on the data collected by the positioning device on the vehicle, and the third pose data set is based on the data collected by the vehicle-mounted camera device.

[0124] In an embodiment of the present application, the above device may further include:

[0125] A second determination module, configured to determine the positioning error data set of the positioning device before determining the perception error information of the vehicle-mounted camera device according to the first pose data set, the second pose data set, and the third pose data set.

[0126] The first determination module 503 is configured to determine the perception error information of the vehicle-mounted camera device according to the positioning error data set, the first pose data set, the second pose data set, and the third pose data set.

[0127] In the embodiments of the present application, the second determination module may include

[0128] a first acquisition sub-module, configured to acquire a calibration position data set of a reference object;

[0129] a second acquisition sub-module, configured to acquire a predicted position data set of the reference object based on a satellite positioning system;

[0130] a first determination sub-module, configured to determine a positioning error data set of a positioning device according to the calibration position data set and the predicted position data set.

[0131] In the embodiments of the present application, the first determination module may include:

[0132] a second determination sub-module, configured to determine a fourth pose data set of the vehicle relative to a target object according to a first pose data set and a second pose data set; the third pose data in the third pose data set corresponds to the fourth pose data in the fourth pose data set one by one;

[0133] a third determination sub-module, configured to determine perception error information of an in-vehicle camera device according to the third pose data set and the fourth pose data set.

[0134] In the embodiments of the present application, the second determination sub-module may include:

[0135] a first determination unit, configured to determine a first corrected pose data set of the vehicle according to the positioning error data set and the first pose data set;

[0136] a second determination unit, configured to determine a second corrected pose data set of the target object according to the positioning error data set and the second pose data set;

[0137] a third determination unit, configured to determine a fourth pose data set of the vehicle relative to the target object according to the first corrected pose data set and the second corrected pose data set based on a relative information measuring instrument on the vehicle.

[0138] In the embodiments of the present application, the third determination unit may include:

[0139] a first determination subunit, configured to determine a local map corresponding to the target object based on the relative information measuring instrument and the second corrected pose data set;

[0140] a second determination subunit, configured to determine position data of the vehicle on the local map based on the relative information measuring instrument and the first corrected pose data set;

[0141] Determine a fourth pose data set of the vehicle relative to the target object based on the local map.

[0142] In the embodiments of the present application, the third determination sub-module may include:

[0143] A fourth determination unit, configured to determine an error data set according to the one-to-one corresponding third pose data and fourth pose data;

[0144] A fifth determination unit, configured to determine the perception error information of the vehicle-mounted camera device according to the reference error threshold corresponding to each error data in the error data set in the error data set.

[0145] The device and method embodiments in this application are based on the same application concept.

[0146] By using the data processing device provided in the embodiments of this application, the motion data set of the target object detected by the vehicle-mounted camera device can be verified. Moreover, by performing differential correction on the first pose data set and the second pose data set, the detection accuracy of the positioning device on the vehicle can be further improved, and then the accuracy of the motion data set of the target object detected by the subsequent vehicle-mounted camera device can be further improved. In addition, by obtaining the first pose data set of the vehicle and the second pose data set of the target object through the satellite positioning system, the accuracy of the collected first pose data set and second pose data set can be improved, which can make the data more comparable than the data collected by the peripheral camera, and can improve the correctness of the verification. By using this data processing method, the perception data processing method of the vehicle-mounted camera device can be improved to improve the detection accuracy of the vehicle-mounted camera device, and then the safety of the driving assistance system can be improved.

[0147] The embodiments of this application provide a perception error determination system for a vehicle-mounted camera device, including:

[0148] A positioning device, which is arranged on the vehicle and is configured to obtain the first pose data set of the vehicle and the second pose data set of the target object;

[0149] A vehicle-mounted camera device, which is arranged on the vehicle and is configured to obtain the third pose data set of the target object;

[0150] A relative information measuring instrument, which is arranged on the vehicle and is configured to determine the fourth pose data set of the target object according to the first pose data set and the second pose data set;

[0151] A processor is used to load and execute to implement the above data processing method. By using the perception error determination system of the vehicle-mounted camera device provided in the embodiments of the present application, the motion data set of the target object detected by the vehicle-mounted camera device can be verified. Moreover, by performing differential correction on the first pose data set and the second pose data set, the detection accuracy of the positioning device on the vehicle can be further improved, and then the accuracy of the motion data set of the target object detected by the subsequent vehicle-mounted camera device can be further improved. In addition, by obtaining the first pose data set of the vehicle and the second pose data set of the target object through the satellite positioning system, the accuracy of the collected first pose data set and the second pose data set can be improved, the data can be made more comparable than the data collected by the peripheral camera, and the correctness of the verification can be improved. By using this data processing method, the perception data processing method of the vehicle-mounted camera device can be improved to improve the detection accuracy of the vehicle-mounted camera device, and then the safety of the driving assistance system can be improved.

[0152] An electronic device provided in the embodiments of the present application can be set in a server to store at least one instruction, at least one program, a code set or an instruction set related to a data processing method for implementing the method embodiments. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the memory to implement the above data processing method.

[0153] A storage medium provided in the embodiments of the present application can be set in a server to store at least one instruction, at least one program, a code set or an instruction set related to a data processing method for implementing the method embodiments. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the above data processing method.

[0154] Optionally, in this embodiment, the above storage medium can be located in at least one of multiple network servers in a computer network. Optionally, in this embodiment, the above storage medium may include, but is not limited to, various media that can store program codes such as USB flash drives, read-only memories (ROMs), mobile hard disks, magnetic disks, or optical discs.

[0155] As can be seen from the embodiments of the data processing method, apparatus, system, electronic device, or storage medium provided by the present application above, the method in the present application includes obtaining a first pose data set of a vehicle, a second pose data set of a target object, and a third pose data set of the vehicle relative to the target object, and determining the perception error information of an in-vehicle camera device according to the first pose data set, the second pose data set, and the third pose data set. Among them, the sampling times of the first pose data set, the second pose data set, and the third pose data set are the same. The first pose data set and the second pose data set are data collected based on a positioning device on the vehicle, and the third pose data set is data collected based on the in-vehicle camera device. Based on the embodiments of the present application, the motion data set of the target object detected by the in-vehicle camera device can be verified. Moreover, by performing differential correction on the first pose data set and the second pose data set, the detection accuracy of the positioning device on the vehicle can be further improved, and further, the accuracy of the motion data set of the target object detected by the subsequent in-vehicle camera device can be improved. In addition, by obtaining the first pose data set of the vehicle and the second pose data set of the target object through a satellite positioning system, the accuracy of the collected first pose data set and second pose data set can be improved, which can make the data more comparable than the data collected by the peripheral cameras and improve the correctness of the verification. By adopting this data processing method, the perception data processing method of the in-vehicle camera device can be improved to improve the detection accuracy of the in-vehicle camera device, and further, the safety of the driving assistance system can be improved.

[0156] In the present invention, unless otherwise clearly defined and limited, terms such as "connected" and "coupled" shall be construed in a broad sense. For example, it may be a fixed connection, a detachable connection, or integrated; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the connection inside two components or the interaction relationship between two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0157] It should be noted that: the above order of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. Moreover, the above description of specific embodiments is provided, and other embodiments are also within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be executed in the order of different embodiments and can achieve the expected results. In addition, the processes depicted in the drawings do not necessarily require a specific order or connection order to achieve the desired results. In certain embodiments, multi-task parallel processing is also possible or may be advantageous.

[0158] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for the embodiments of the device, since it is based on a method similar to the method embodiment, the description is relatively simple, and for the relevant parts, reference can be made to the partial description of the method embodiment.

[0159] The above is the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements are also regarded as the protection scope of the present invention.

Claims

1. A data processing method, characterized in that, the data processing method is used to process data collected by an in-vehicle camera device, and the data processing method includes: determining a positioning error data set of a positioning device; obtaining a first pose data set of the vehicle, a second pose data set of a target object, and a third pose data set of the vehicle relative to the target object; the first pose data set includes position data of the vehicle in a vehicle coordinate system; the second pose data set includes position data of a lane line in the vehicle coordinate system; the third pose data set includes a lateral distance and an angle of the vehicle relative to the lane line; based on the positioning error data set, performing correction processing on the lateral and longitudinal positions in the first pose data set and the lateral and longitudinal positions in the second pose data set to obtain a lateral distance and an angle of the vehicle relative to the target object, and determining a fourth pose data set of the vehicle relative to the target object; determining sensing error information of the in-vehicle camera device according to the third pose data set and the fourth pose data set; wherein, the sampling times of the first pose data set, the second pose data set, and the third pose data set are the same, the first pose data set and the second pose data set are based on data collected by the positioning device on the vehicle, and the third pose data set is based on data collected by the in-vehicle camera device.

2. The method according to claim 1, characterized in that, before determining the fourth pose data set of the vehicle relative to the target object according to the positioning error data set, the first pose data set, and the second pose data set, the method further includes: determining the sensing error information of the in-vehicle camera device according to the positioning error data set, the first pose data set, the second pose data set, and the third pose data set.

3. The method according to claim 2, characterized in that, determining the positioning error data set of the positioning device includes: obtaining a calibration position data set of a reference object; acquiring a predicted position data set of the reference object based on a satellite positioning system; determining the positioning error data set of the positioning device according to the calibration position data set and the predicted position data set.

4. The method according to claim 3, characterized in that, determining the fourth pose data set of the vehicle relative to the target object according to the first pose data set and the second pose data set includes: determining a first corrected pose data set of the vehicle according to the positioning error data set and the first pose data set; determining a second corrected pose data set of the target object according to the positioning error data set and the second pose data set; based on a relative information measuring instrument on the vehicle, determining the fourth pose data set of the vehicle relative to the target object according to the first corrected pose data set and the second corrected pose data set.

5. The method according to claim 4, characterized in that, Based on the relative information measuring instrument on the vehicle, determining a fourth pose dataset of the vehicle relative to the target object according to the first calibrated pose dataset and the second calibrated pose dataset includes: Determining a local map corresponding to the target object based on the relative information measuring instrument and the second calibrated pose dataset; Determining position data of the vehicle on the local map based on the relative information measuring instrument and the first calibrated pose dataset; Determining the fourth pose dataset of the vehicle relative to the target object based on the local map.

6. The method according to claim 1, wherein, determining the perception error information of the vehicle-mounted camera device according to the third pose dataset and the fourth pose dataset includes: Determining an error dataset according to the one-to-one corresponding third pose data and the fourth pose data; Determining the perception error information of the vehicle-mounted camera device according to the error data and the reference error threshold corresponding to each error data in the error dataset.

7. A data processing device, wherein, the data processing device is used to process data collected by a vehicle-mounted camera device, and the data processing device includes: An acquisition module, configured to determine a positioning error dataset of a positioning device; Obtaining a first pose dataset of the vehicle, a second pose dataset of a target object, and a third pose dataset of the vehicle relative to the target object; the first pose dataset includes position data of the vehicle in a vehicle coordinate system; the second pose dataset includes position data of a lane line in the vehicle coordinate system; the third pose dataset includes a lateral distance and an angle of the vehicle relative to the lane line; A first determination module, configured to perform correction processing on the horizontal and vertical positions in the first pose dataset and the horizontal and vertical positions in the second pose dataset based on the positioning error dataset, obtain a lateral distance and an angle of the vehicle relative to the target object, and determine a fourth pose dataset of the vehicle relative to the target object; Determining the perception error information of the vehicle-mounted camera device according to the third pose dataset and the fourth pose dataset; wherein, the sampling times of the first pose dataset, the second pose dataset, and the third pose dataset are the same, the first pose dataset and the second pose dataset are based on data collected by the positioning device on the vehicle, and the third pose dataset is based on data collected by the vehicle-mounted camera device.

8. A perception error determination system for a vehicle-mounted camera device, wherein, it includes: A positioning device, which is arranged on the vehicle and is used to obtain a first pose dataset of the vehicle and a second pose dataset of the target object; A vehicle-mounted camera device, which is arranged on the vehicle and is used to obtain a third pose dataset of the vehicle relative to the target object; A relative information measuring device, which is arranged on the vehicle and is used to determine a fourth pose data set of the vehicle relative to the target object according to the first pose data set and the second pose data set; A processor, which is used to load and execute to implement the data processing method described in any one of claims 1-6.

9. An electronic device, characterized in that, the electronic device includes a processor and a memory, and at least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the data processing method described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that, at least one instruction, at least one program, a code set or an instruction set is stored in the storage medium, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement the data processing method described in any one of claims 1-6.

Images