Vehicle positioning method, device, equipment and storage medium

Abstract

The present invention relates to a vehicle positioning method, device, equipment and storage medium, including obtaining multiple angular velocity information collected by an inertial measurement unit within a preset time period; determining multiple angle reference information based on multiple images collected by a vehicle-mounted camera within a preset time period; determining lane line angle prediction information corresponding to each of the multiple angular velocity information according to the multiple angle reference information; determining angular velocity compensation information according to the multiple angular velocity information and the lane line angle prediction information corresponding to each of the multiple angular velocity information; compensating the angular velocity information collected at the current moment using the angular velocity compensation information; and determining the vehicle position according to the compensated target angular velocity information. The present invention can determine the lane line angle prediction information using the images collected by the camera, and compensate the angular velocity collected by the inertial sensor at the current moment in combination with the angular velocity information collected by the inertial sensor, thereby improving the accuracy of vehicle positioning.

Description

Technical Field

[0001] The present invention relates to the field of safe driving assistance technology, and in particular to a vehicle positioning method, device, equipment and storage medium. Background Art

[0002] Vehicle positioning has become a critical technology in autonomous driving. The positioning accuracy of the vehicle determines the accuracy of vehicle perception, planning and control. At present, the main methods of vehicle positioning are based on Global Navigation Satellite System (GNSS) positioning or Inertial Measurement Unit (IMU) positioning. However, in scenarios with building obstructions and tunnels, GNSS will have problems with reduced accuracy or even signal loss. In this case, inertial navigation needs to be achieved through IMU. However, the navigation error in the inertial navigation process of IMU will continue to accumulate over time. As the navigation time increases, the positioning accuracy of the vehicle decreases, and it may even cause the problem of being unable to track the vehicle's position. Summary of the invention

[0003] The technical problem to be solved by the present invention is the problem of poor vehicle positioning accuracy caused by IMU navigation errors in the prior art.

[0004] In order to solve the above technical problems, the present invention discloses a vehicle positioning method, which comprises:

[0005] Acquire multiple angular velocity information collected by the inertial measurement unit within a preset time period, where the end time of the preset time period is the current time;

[0006] Determining multiple angle reference information based on multiple images captured by the vehicle-mounted camera within the preset time period;

[0007] Determine lane line angle prediction information corresponding to each of the plurality of angular velocity information according to the plurality of angle reference information;

[0008] Determining angular velocity compensation information according to the plurality of angular velocity information and lane line angle prediction information corresponding to each of the plurality of angular velocity information;

[0009] Using the angular velocity compensation information to compensate the angular velocity information collected at the current moment, to obtain the target angular velocity information at the current moment;

[0010] The vehicle position is determined according to the target angular velocity information.

[0011] Further, each angular velocity information of the multiple angular velocity information corresponds to a first collection time, each angle reference information of the multiple angle reference information corresponds to a second collection time, and determining the lane line angle prediction information corresponding to each of the multiple angular velocity information according to the multiple angle reference information includes:

[0012] Acquire a first collection time corresponding to each of the plurality of angular velocity information and a second collection time corresponding to each of the plurality of angle reference information;

[0013] Determine two adjacent second collection moments corresponding to each of the plurality of first collection moments,

[0014] Lane line angle prediction information corresponding to each of the multiple angular velocity information is determined according to two adjacent second collection moments corresponding to each of the multiple first collection moments and angle reference information corresponding to each of the two adjacent second collection moments.

[0015] Further, the determining the angular velocity compensation information according to the plurality of angular velocity information and the lane line angle prediction information corresponding to each of the plurality of angular velocity information comprises:

[0016] Obtaining the start time and end time of multiple first collection moments;

[0017] Determine lane line angle prediction information corresponding to the start time and the end time respectively;

[0018] Determining an angle prediction change amount according to lane line angle prediction information corresponding to the start time and the end time respectively;

[0019] Determine the time interval between two adjacent first collection moments;

[0020] Determining an angular velocity cumulative deviation value according to the multiple angular velocity information and the time interval;

[0021] An angular velocity compensation value is determined according to the angle prediction change and the angular velocity cumulative deviation value.

[0022] Furthermore, the determining of the plurality of angle reference information based on the plurality of images captured by the vehicle-mounted camera within the preset time period includes:

[0023] Acquire images respectively captured by the vehicle-mounted camera at a plurality of the second capturing moments;

[0024] Determine transformation regions corresponding to each of the plurality of images, each transformation region having a first viewing angle;

[0025] Performing a perspective transformation on each of the multiple transformation areas to obtain a target area with a second perspective corresponding to each of the multiple transformation areas;

[0026] A plurality of angle reference information is determined according to the plurality of second viewing angles, and each second viewing angle corresponds to a piece of angle reference information.

[0027] Furthermore, performing perspective transformation on each of the multiple transformation areas to obtain target areas corresponding to each of the multiple transformation areas includes:

[0028] An inverse perspective transformation is performed on each of the multiple transformation areas to obtain target areas corresponding to each of the multiple transformation areas.

[0029] According to another aspect of the present application, the present application also discloses a vehicle positioning device, the device comprising:

[0030] An angular velocity information acquisition module, used to acquire a plurality of angular velocity information collected by the inertial measurement unit within a preset time period, wherein the end time of the preset time period is the current time;

[0031] An angle reference information determination module, used to determine a plurality of angle reference information based on a plurality of images captured by the vehicle-mounted camera within the preset time period;

[0032] A lane line angle prediction information determination module, used to determine the lane line angle prediction information corresponding to each of the plurality of angular velocity information according to the plurality of angle reference information;

[0033] An angular velocity compensation information determination module, configured to determine angular velocity compensation information according to the plurality of angular velocity information and lane line angle prediction information corresponding to each of the plurality of angular velocity information;

[0034] a target angular velocity information determination module, configured to compensate the angular velocity information collected at the current moment by using the angular velocity compensation information to obtain the target angular velocity information at the current moment;

[0035] The vehicle position determination module is used to determine the vehicle position according to the target angular velocity information.

[0036] According to another aspect of the present application, the present application also discloses an electronic device, including:

[0037] processor;

[0038] a memory for storing instructions executable by the processor;

[0039] The processor is configured to execute the instructions to implement the vehicle positioning method as described in the above claims.

[0040] According to another aspect of the present application, a computer-readable storage medium is also disclosed. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can execute the vehicle positioning method as described in the above claims.

[0041] The present invention obtains multiple angular velocity information collected by an inertial measurement unit within a preset time period, the end time of the preset time period being the current time; determines multiple angle reference information based on multiple images collected by a vehicle-mounted camera within the preset time period; determines lane line angle prediction information corresponding to each of the multiple angular velocity information according to the multiple angle reference information; determines angular velocity compensation information according to the multiple angular velocity information and lane line angle prediction information corresponding to each of the multiple angular velocity information; uses the angular velocity compensation information to compensate the angular velocity information collected at the current time to obtain the target angular velocity information at the current time; and determines the vehicle position according to the target angular velocity information. The present invention can use images collected by a camera to determine lane line angle prediction information, and in combination with the angular velocity information collected by the inertial sensor, compensates for the angular velocity collected by the inertial sensor at the current time, thereby improving the accuracy of vehicle positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0043] Figure 1 It is a schematic diagram of an implementation environment of a vehicle positioning method provided in an embodiment of the present application;

[0044] Figure 2 is a flow chart of a vehicle positioning method provided by an embodiment of the present application;

[0045] Figure 3 is a flow chart of determining lane line angle prediction information provided by an embodiment of the present application;

[0046] Figure 4 is a flow chart of determining angular velocity compensation information provided by an embodiment of the present application;

[0047] Figure 5 is a flow chart of another vehicle positioning method provided by an embodiment of the present application;

[0048] Figure 6 is a structural block diagram of a vehicle positioning device provided in an embodiment of the present application;

[0049] Figure 7is a block diagram of a device provided in an embodiment of the present application;

[0050] Figure 8 It is a schematic diagram of the changing area before and after the perspective transformation, where a is the transformation area and b is the target area. DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0052] The "one embodiment" or "embodiment" referred to herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. In the description of the present invention, it should be understood that the terms "first", "second", "third" and "fourth" in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed.

[0053] elements, or optionally further include other steps or units inherent to these processes, methods, products or devices.

[0054] See also Figure 1 , Figure 1 It is a schematic diagram of an implementation environment of a vehicle positioning method provided in an embodiment of the present application. The application environment may include a vehicle 01, a vehicle-mounted camera 02 arranged on the vehicle 01, an inertial measurement unit 03 arranged on the vehicle 01, and a controller 04.

[0055] In an optional embodiment, the on-board camera 02 on the vehicle 01 can be used to obtain road information around the vehicle 01, wherein the road information may include lane line information, vehicles, pedestrians and other object information. In this application, the on-board camera is mainly used to obtain lane line information.

[0056] In an optional embodiment, the inertial measurement unit 03 can provide the controller in the vehicle with the real-time motion information of the vehicle. The real-time motion information may include the angular velocity information of the longitudinal and lateral swing of the vehicle, as well as the longitudinal, lateral and vertical acceleration information. In the embodiment of the present application, the inertial measurement unit 03 mainly provides the angular velocity information for the controller of the vehicle. And it is transmitted to the data bus through a standard interface. The obtained signal is used for complex adjustment algorithms to enhance the comfort and safety applications of passenger cars and commercial vehicles (e.g., ESC / ESP, ADAS, AD) and motorcycles (optimized curve ABS), industrial vehicles and agricultural vehicles.

[0057] In an optional embodiment, the controller 04 may be disposed on the vehicle body, and is used to communicate with the vehicle-mounted camera 02 through a standard interface or a controller area network CAN bus (Controller Area Network), obtain the image captured by the vehicle-mounted camera 02, and process the image, such as extracting lane line information on the image, determining the lane line angle, etc. Further, the controller may also communicate with the inertial measurement unit 03 through a standard interface or a controller area network CAN bus, to achieve data transmission between the two.

[0058] The following introduces a vehicle positioning method provided by this application. Figure 2 : is a flow chart of a vehicle positioning method provided by an embodiment of the present application, the method comprising:

[0059] S100: Acquire multiple angular velocity information collected by an inertial measurement unit within a preset time period.

[0060] Specifically, the preset time period can be pre-set, and the specific preset time period length can be 10s

[0061] Or 20s or 30s, which can be set according to actual needs and are not specifically limited here. The end time of the preset time period can be the current time.

[0062] S102: Determine multiple angle reference information based on multiple images captured by the vehicle-mounted camera within a preset time period.

[0063] Specifically, the image captured by the vehicle-mounted camera refers to the road image, and the angle reference information refers to the angle reference information corresponding to the lane line in the road image captured by the vehicle-mounted camera. The lane line in the image can be determined first, and then the angle reference information corresponding to the lane line can be determined based on the slope of the lane line. Specifically, each image can extract a lane line, so that each image can correspond to the angle reference information of a lane line.

[0064] In one feasible solution, lane line extraction can be performed based on Hough Transform. Specifically, the road image captured by the camera can be grayscale enhanced first, and then edge extraction can be performed. After straight line fitting through Hough Transform, lane line extraction can be achieved. Exemplarily, edge extraction can be achieved based on the Canny edge detection algorithm.

[0065] S104. Determine lane line angle prediction information corresponding to each of the plurality of angular velocity information according to the plurality of angle reference information.

[0066] It is understandable that, since the time when the vehicle-mounted camera collects images is inconsistent with the time when the inertial measurement unit collects angular velocity information, time alignment is required. Specifically, the angle reference information determined based on the image collected by the vehicle-mounted camera can be aligned to the inertial measurement unit, that is, based on the time when the inertial measurement unit collects the angular velocity information, the angle reference information corresponding to the angular velocity information at that time is determined.

[0067] Specifically, Figure 3 A flow chart of a method for determining lane line angle prediction information corresponding to each of a plurality of angular velocity information according to a plurality of angle reference information is shown. Figure 3 As shown, the method specifically includes:

[0068] S200: Acquire first collection moments corresponding to each of the plurality of angular velocity information and second collection moments corresponding to each of the plurality of angle reference information.

[0069] Specifically, when the inertial measurement unit collects angular velocity information, the preset time period can be divided into a plurality of first collection moments, and the inertial measurement unit can collect angular velocity information corresponding to each first collection moment, and then the correspondence between the first collection moment and the angular velocity information can be determined. After obtaining a plurality of angular velocity information, the first collection moment corresponding to each of the plurality of angular velocity information can be determined based on the correspondence between the angular velocity information and the first collection moment.

[0070] Similarly, when the vehicle-mounted camera collects images, the preset time period can also be divided into multiple second collection moments, and the vehicle-mounted camera can collect images at each second collection moment, and then determine the correspondence between the second collection moment and the angle reference information determined based on the image. After determining multiple angle reference information, the second collection moments corresponding to the multiple angle reference information can be determined based on the correspondence between the angle reference information and the second collection moment.

[0071] S202: Determine two adjacent second collection moments corresponding to each of the plurality of first collection moments.

[0072] Specifically, determining two adjacent second collection moments corresponding to each of the plurality of first collection moments specifically refers to determining the second collection moments adjacent to each first collection moment before and after each first collection moment.

[0073] S204: Determine lane line angle prediction information corresponding to each of the plurality of angular velocity information according to two adjacent second collection moments corresponding to each of the plurality of first collection moments and angle reference information corresponding to each of the two adjacent second collection moments.

[0074] Specifically, through the above steps, the angle reference information determined based on the image captured by the camera is used as a calculation basis to calculate the angle reference information of the first acquisition moment corresponding to the angular velocity information, which is used as the lane line angle prediction information. This can make the navigation data determined based on the camera and the navigation data of the inertial measurement unit in the same dimension, thereby laying a dimensional foundation for the subsequent compensation of the navigation data of the inertial measurement unit.

[0075] S106. Determine angular velocity compensation information according to the plurality of angular velocity information and the lane line angle prediction information corresponding to each of the plurality of angular velocity information.

[0076] For details, see Figure 4 As shown, Figure 4 A flow chart showing a method for determining angular velocity compensation information is shown, the method comprising:

[0077] S300: Obtain the start time and end time of multiple first collection times.

[0078] It is understandable that since the error of the inertial measurement unit will accumulate over time, the angular velocity information at the current moment collected by the inertial measurement unit is the accumulation of the errors before the current moment within the preset time period. At this time, when determining the compensated angular velocity information at the current moment, only the start and end times of multiple first collection moments within the preset time period can be obtained.

[0079] A start time and an end time are determined from the plurality of first collection time points.

[0080] S302: Determine lane line angle prediction information corresponding to the start time and the end time respectively.

[0081] Specifically, the lane line angle prediction information corresponding to the start time and the lane line angle prediction information corresponding to the end time are determined from the lane line angle prediction information corresponding to each of the multiple angular velocity information determined above.

[0082] S304: Determine the angle prediction change amount according to the lane line angle prediction information corresponding to the start time and the end time respectively.

[0083] Specifically, the angle prediction change refers to the difference between the lane line angle measurement information corresponding to the starting time and the lane line angle measurement information corresponding to the ending time.

[0084] S306: Determine the time interval between two adjacent first collection moments.

[0085] S308: Determine an angular velocity cumulative deviation value according to the multiple angular velocity information and time intervals.

[0086] S310: Determine an angular velocity compensation value according to the angle prediction change and the angular velocity cumulative deviation value.

[0087] Specifically, in combination with the following loss function L, steps S304 to S310 are comprehensively introduced:

[0088]

[0089] in, Predict the change in angle;

[0090] i is the number corresponding to the first acquisition moment, and the value of i is i=1, 2, 3...n;

[0091] is the angular velocity information corresponding to the i-th first acquisition moment;

[0092] is the time interval;

[0093] is the angular velocity compensation value required to be solved;

[0094] is the accumulated deviation value of angular velocity.

[0095] Specifically, solve The process is specifically the process of solving the minimum value of the loss function L. When the loss function L is at its minimum value, the corresponding S108: Use the angular velocity compensation information to compensate the angular velocity information collected at the current moment to obtain the target angular velocity information at the current moment.

[0096] Specifically, the angular velocity compensation information and the currently collected angular velocity information may be summed to obtain a sum result, and the sum result may be used as the target angular velocity information.

[0097] S110. Determine the vehicle position according to the target angular velocity information.

[0098] The present invention obtains multiple angular velocity information collected by an inertial measurement unit within a preset time period, and the end time of the preset time period is the current time; based on multiple images collected by a vehicle-mounted camera within the preset time period, multiple angle reference information is determined; according to the multiple angle reference information, lane line angle prediction information corresponding to each of the multiple angular velocity information is determined; according to the multiple angular velocity information and the lane line angle prediction information corresponding to each of the multiple angular velocity information, angular velocity compensation information is determined; the angular velocity information collected at the current moment is compensated by the angular velocity compensation information to obtain the target angular velocity information at the current moment; and the vehicle position is determined according to the target angular velocity information. The present invention can use the images collected by the camera to determine the lane line angle prediction information, and in combination with the angular velocity information collected by the inertial sensor, the angular velocity collected by the inertial sensor at the current moment is compensated to improve the vehicle positioning accuracy.

[0099] Furthermore, Figure 5 is another flow chart of the vehicle positioning method provided by the present application, such as Figure 5 As shown, the method includes:

[0100] S100: Acquire multiple angular velocity information collected by an inertial measurement unit within a preset time period, where the end time of the preset time period is the current time.

[0101] S102: Determine multiple angle reference information based on multiple images captured by the vehicle-mounted camera within a preset time period.

[0102] Specifically, step S102 determines multiple angle reference information based on multiple images collected by the vehicle-mounted camera within a preset time period, which can be implemented based on the following steps:

[0103] S400: Acquire images respectively captured by the vehicle-mounted camera at multiple second capturing moments.

[0104] S402: Determine transformation regions corresponding to each of the multiple images, each transformation region having a first viewing angle.

[0105] Specifically, the transformation area may refer to an area involving the ground. The first viewing angle may be a shooting angle of an image taken by a vehicle-mounted camera. For example, a transformation area having a first viewing angle may be Figure 8 As shown in view a in .

[0106] S404: Perform a perspective transformation on each of the multiple transformation areas to obtain a target area with a second perspective corresponding to each of the multiple transformation areas.

[0107] Specifically, each of the multiple transformation areas can be subjected to inverse perspective transformation to obtain a target area with a second viewing angle corresponding to each of the multiple transformation areas. The second viewing angle is based on a top-down viewing angle obtained after the perspective transformation. An exemplary target area with a second viewing angle after the transformation is as follows: Figure 8 As shown in view b.

[0108] S406: Determine a plurality of angle reference information according to the plurality of second viewing angles, where each second viewing angle corresponds to a piece of angle reference information.

[0109] Specifically, the transformation area is roughly a triangle before the perspective transformation, and in the top view formed after the transformation, it is a rectangular image, and the linear and parallel characteristics can be retained. Then, the angle reference information α of the lane line can be determined based on the angle between the lane line in the target area determined after the perspective transformation and the horizontal direction. Exemplarily, the angle reference information α is the inverse tangent value of the slope of the lane line.

[0110] S104. Determine lane line angle prediction information corresponding to each of the plurality of angular velocity information according to the plurality of angle reference information.

[0111] S106. Determine angular velocity compensation information according to the plurality of angular velocity information and the lane line angle prediction information corresponding to each of the plurality of angular velocity information.

[0112] S108. Compensate the angular velocity information collected at the current moment using the angular velocity compensation information to obtain the target angular velocity information at the current moment.

[0113] S110. Determine the vehicle position according to the target angular velocity information.

[0114] Specifically, the specific introduction of steps S100-S110 can refer to the above introduction, which will not be repeated here.

[0115] like Figure 6 As shown, the present application also discloses a vehicle positioning device, the device comprising:

[0116] An angular velocity information acquisition module is used to acquire a plurality of angular velocity information collected by the inertial measurement unit within a preset time period, where the end time of the preset time period is the current time;

[0117] An angle reference information determination module, used to determine a plurality of angle reference information based on a plurality of images captured by the vehicle-mounted camera within a preset time period;

[0118] A lane line angle prediction information determination module, used to determine lane line angle prediction information corresponding to each of the multiple angular velocity information based on the multiple angle reference information;

[0119] An angular velocity compensation information determination module, used to determine angular velocity compensation information according to a plurality of angular velocity information and lane line angle prediction information corresponding to each of the plurality of angular velocity information;

[0120] A target angular velocity information determination module is used to compensate the angular velocity information collected at the current moment by using the angular velocity compensation information to obtain the target angular velocity information at the current moment;

[0121] The vehicle position determination module is used to determine the vehicle position according to the target angular velocity information.

[0122] Furthermore, the lane line angle prediction information determination module includes:

[0123] The first acquisition unit is used to acquire first acquisition moments corresponding to each of the multiple angular velocity information and second acquisition moments corresponding to each of the multiple angle reference information.

[0124] The adjacent time determination unit is used to determine two adjacent second collection time instants corresponding to each of the plurality of first collection time instants.

[0125] The first determination unit is used to determine lane line angle prediction information corresponding to each of the multiple angular velocity information according to two adjacent second acquisition moments corresponding to each of the multiple first acquisition moments and angle reference information corresponding to each of the two adjacent second acquisition moments.

[0126] Furthermore, the angular velocity compensation information determination module includes:

[0127] The second acquisition unit is used to acquire the start time and the end time of multiple first collection moments.

[0128] The second determination unit is used to determine the lane line angle prediction information corresponding to the start time and the end time respectively.

[0129] The angle prediction change determination unit is used to determine the angle prediction change according to the lane line angle prediction information corresponding to the start time and the end time respectively.

[0130] The time interval determining unit is used to determine the time interval between two adjacent first collection moments.

[0131] The cumulative deviation value determining unit is used to determine the angular velocity cumulative deviation value according to a plurality of angular velocity information and time intervals.

[0132] The angular velocity compensation value determining unit is used to determine the angular velocity compensation value according to the angle prediction variation and the angular velocity cumulative deviation value.

[0133] Furthermore, the angle reference information determination module includes:

[0134] The third acquisition unit is used to acquire images respectively acquired by the vehicle-mounted camera at a plurality of second acquisition moments.

[0135] The transformation region determining unit is used to determine transformation regions corresponding to each of the multiple images, each transformation region having a first viewing angle.

[0136] The target region determining unit is used to perform a perspective transformation on each of the multiple transformation regions to obtain a target region with a second perspective corresponding to each of the multiple transformation regions.

[0137] The angle reference information determining unit is used to determine a plurality of angle reference information according to a plurality of second viewing angles, wherein each second viewing angle corresponds to a piece of angle reference information.

[0138] The implementation scheme of each module in a vehicle positioning device in this embodiment refers to the processing steps of the above method, which will not be repeated here.

[0139] Furthermore, the present application also discloses an electronic device, comprising:

[0140] processor;

[0141] a memory for storing processor-executable instructions;

[0142] The processor is configured to execute instructions to implement the vehicle positioning method as claimed in the above claims.

[0143] For example, Figure 7 is a block diagram of an electronic device for vehicle positioning according to an exemplary embodiment. The electronic device may be a server, and its internal structure diagram may be as shown in FIG. Figure 7 As shown. The electronic device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the electronic device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a vehicle positioning method is implemented.

[0144] Those skilled in the art will understand that Figure 7 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present disclosure, and does not constitute a limitation on the electronic device to which the scheme of the present disclosure is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0145] Furthermore, the present application also discloses a computer-readable storage medium. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can execute the vehicle positioning method as claimed above.

[0146] The computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0147] In an exemplary embodiment, a computer program product containing instructions is also provided. When the computer program product is run on a computer, the computer is caused to execute the vehicle positioning method in the embodiment of the present disclosure.

[0148] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0149] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0150] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

[0151] It is worth noting that in the above-mentioned device and terminal embodiments, the modules and units included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the modules and units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0152] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the terminal embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of modules or units, which can be electrical, mechanical or other forms.

[0153] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle positioning method, characterized in that: The method comprises: Acquire multiple angular velocity information collected by the inertial measurement unit within a preset time period, where the end time of the preset time period is the current time; Determining multiple angle reference information based on multiple images captured by the vehicle-mounted camera within the preset time period; Determine lane line angle prediction information corresponding to each of the plurality of angular velocity information according to the plurality of angle reference information; Determining angular velocity compensation information according to the multiple angular velocity information and the lane line angle prediction information corresponding to each of the multiple angular velocity information, including: obtaining the start time and the end time of multiple first acquisition moments; determining the lane line angle prediction information corresponding to the start time and the end time respectively; determining the angle prediction change amount according to the lane line angle prediction information corresponding to the start time and the end time respectively; determining the time interval between two adjacent first acquisition moments; determining the angular velocity cumulative deviation value according to the multiple angular velocity information and the time interval; determining the angular velocity compensation value according to the angle prediction change amount and the angular velocity cumulative deviation value; Using the angular velocity compensation information to compensate the angular velocity information collected at the current moment, to obtain the target angular velocity information at the current moment; The vehicle position is determined according to the target angular velocity information.

2. The vehicle positioning method according to claim 1, characterized in that: The using the angular velocity compensation information to compensate the angular velocity information collected at the current moment to obtain the target angular velocity information at the current moment includes: Performing a summation process on the angular velocity compensation information and the angular velocity information collected at the current moment to obtain a summation result; The summation result is determined as the target angular velocity information at the current moment.

3. The vehicle positioning method according to claim 1, characterized in that: Each angular velocity information of the plurality of angular velocity information corresponds to a first acquisition time, each angular reference information of the plurality of angle reference information corresponds to a second acquisition time, and determining lane line angle prediction information corresponding to each of the plurality of angular velocity information according to the plurality of angle reference information includes: Acquire a first collection time corresponding to each of the plurality of angular velocity information and a second collection time corresponding to each of the plurality of angle reference information; Determine two adjacent second collection moments corresponding to each of the plurality of first collection moments, Lane line angle prediction information corresponding to each of the multiple angular velocity information is determined according to two adjacent second collection moments corresponding to each of the multiple first collection moments and angle reference information corresponding to each of the two adjacent second collection moments.

4. The vehicle positioning method according to claim 1, characterized in that: The determining of the plurality of angle reference information based on the plurality of images captured by the vehicle-mounted camera within the preset time period includes: Acquire images respectively captured by the vehicle-mounted camera at multiple second capturing moments; Determine transformation regions corresponding to each of the plurality of images, each transformation region having a first viewing angle; Performing a perspective transformation on each of the multiple transformation areas to obtain a target area with a second perspective corresponding to each of the multiple transformation areas; A plurality of angle reference information is determined according to the plurality of second viewing angles, and each second viewing angle corresponds to a piece of angle reference information.

5. The vehicle positioning method according to claim 4, characterized in that: The performing perspective transformation on each of the multiple transformation areas to obtain target areas corresponding to each of the multiple transformation areas comprises: An inverse perspective transformation is performed on each of the multiple transformation areas to obtain target areas corresponding to each of the multiple transformation areas.

6. A vehicle positioning device, characterized in that: The device comprises: An angular velocity information acquisition module, used to acquire a plurality of angular velocity information collected by the inertial measurement unit within a preset time period, wherein the end time of the preset time period is the current time; An angle reference information determination module, used to determine a plurality of angle reference information based on a plurality of images captured by the vehicle-mounted camera within the preset time period; A lane line angle prediction information determination module, used to determine the lane line angle prediction information corresponding to each of the plurality of angular velocity information according to the plurality of angle reference information; An angular velocity compensation information determination module is used to determine the angular velocity compensation information according to the multiple angular velocity information and the lane line angle prediction information corresponding to each of the multiple angular velocity information, including: obtaining the starting time and the ending time of multiple first acquisition moments; determining the lane line angle prediction information corresponding to the starting time and the ending time respectively; determining the angle prediction change amount according to the lane line angle prediction information corresponding to the starting time and the ending time respectively; determining the time interval between two adjacent first acquisition moments; determining the angular velocity cumulative deviation value according to the multiple angular velocity information and the time interval; determining the angular velocity compensation value according to the angle prediction change amount and the angular velocity cumulative deviation value; a target angular velocity information determination module, configured to compensate the angular velocity information collected at the current moment by using the angular velocity compensation information to obtain the target angular velocity information at the current moment; The vehicle position determination module is used to determine the vehicle position according to the target angular velocity information.

7. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the vehicle positioning method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the vehicle positioning method according to any one of claims 1 to 5.

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