Method for determining coordinates of parking space, vehicle and computer storage medium

Abstract

The invention discloses a method for determining the coordinates of a parking stall, a vehicle and a computer storage medium, and the method comprises the steps: obtaining a plurality of frames of historical parking stall collection images in a parking stage; and performing error optimization on the current parking space coordinate corresponding to the current frame of parking space acquisition image according to the plurality of frames of historical parking space acquisition images so as to determine the reference target parking space coordinate when the vehicle is parked at the next moment. By adopting the method, the parking space coordinate error can be optimized, and the parking effect is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicles, and in particular to a method for determining parking space coordinates, a vehicle and a computer storage medium. Background Art

[0002] In the related art, automatic parking generally processes the initial parking space by directly obtaining sensor information, completely relying on the perception accuracy to park, and directly using the original data of the parking space for subsequent parking or updating the parking space through simple low-pass filtering. However, this method will cause a certain degree of deviation in the positioning of the parking space coordinates during parking due to the problem of detection accuracy. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, one object of the present invention is to provide a method for determining the coordinates of a parking space, which can optimize the parking space coordinate error and improve the parking effect.

[0004] A second object of the present invention is to provide a vehicle.

[0005] A third object of the present invention is to provide a computer storage medium.

[0006] A fourth object of the present invention is to provide a computer program product.

[0007] In order to solve the above problems, an embodiment of the first aspect of the present invention proposes a method for determining parking space coordinates, including: in the parking stage, obtaining multiple frames of historical parking space acquisition images; optimizing the error of the current parking space coordinates corresponding to the current frame parking space acquisition image according to the multiple frames of historical parking space acquisition images, so as to determine the target parking space coordinates for reference when the vehicle parks at the next moment.

[0008] According to the method for determining parking space coordinates of an embodiment of the present invention, during the parking stage, the error generated when the current parking space coordinates are generated is considered, thereby affecting the positioning of the parking space. By introducing multiple frames of historical parking space acquisition images, the error generated by the current parking space coordinates is optimized, so that the error is minimized in a local range, thereby improving the parking space positioning accuracy and improving the parking effect.

[0009] In some embodiments, error optimization is performed on the current parking space coordinates corresponding to the current parking space acquisition image according to multiple frames of historical parking space acquisition images, including: error optimization is performed on the current parking space coordinates corresponding to the current parking space acquisition image according to multiple frames of historical parking space acquisition images using a nonlinear optimization method.

[0010] In some embodiments, a nonlinear optimization method is used based on multiple frames of historical parking space acquisition images to perform error optimization on the current parking space coordinates corresponding to the current frame parking space acquisition image to determine the target parking space coordinates for reference when the vehicle parks at the next moment, including: constructing a Gauss-Newton equation about coordinate residuals based on multiple frames of historical parking space acquisition images; substituting the current parking space coordinates into the Gauss-Newton equation to determine the target parking space coordinates corresponding to the minimum residual value.

[0011] In some embodiments, substituting the current parking space coordinates into the Gauss-Newton equation includes: determining a weight value of the current parking space coordinates in the time dimension of the overall historical parking space acquisition image; and substituting the product value of the current parking space coordinates and the weight value into the Gauss-Newton equation.

[0012] In some embodiments, the method further includes: determining the initial coordinates of the handshake parking space before entering the parking phase; establishing a Kalman filter equation; and performing error optimization on the initial coordinates according to the Kalman filter equation to obtain updated initial coordinates.

[0013] In some embodiments, the initial coordinates are error optimized according to the Kalman filter equation, including: substituting the initial coordinates and the target parking space coordinates into the Kalman filter equation to perform error optimization on the initial coordinates, wherein the initial coordinates are used as predicted values ​​and the target parking space coordinates are used as observed values.

[0014] In some embodiments, the initial coordinates and the target parking space coordinates are substituted into the Kalman filter equation to perform error optimization on the initial coordinates, including: determining the coordinate difference between the initial coordinates and the target parking space coordinates; determining the weight value corresponding to the initial coordinates and the weight value corresponding to the target parking space coordinates according to the coordinate difference; substituting the initial coordinates, the weight value corresponding to the initial coordinates, the target parking space coordinates and the weight value corresponding to the target parking space coordinates into the Kalman filter equation to perform error optimization on the initial coordinates.

[0015] In some embodiments, the method also includes: under the condition that there is no handshake parking space in the current frame parking space acquisition image, a nonlinear optimization method is used to optimize the parking space coordinates corresponding to the previous frame parking space acquisition image according to multiple frames of continuous historical parking space acquisition images to determine the target parking space coordinates.

[0016] A second aspect of the present invention provides a vehicle, comprising: a collection device, the collection device is used to collect parking space collection images; a controller, the controller is connected to the collection device, and the controller is used to execute the method for determining the parking space coordinates described in the above embodiment.

[0017] According to the vehicle of the embodiment of the present invention, the parking space coordinate error can be optimized and the parking effect can be improved by executing the above method for determining the parking space coordinates through the controller.

[0018] In some embodiments, it also includes: a display device, which is connected to the controller and is used to display images based on the parking space captured image and the target parking space coordinates.

[0019] A third aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method for determining the coordinates of a parking space as described in the above embodiment.

[0020] A fourth aspect of the present invention provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the method for determining the coordinates of a parking space described in the above embodiment.

[0021] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which: Figure 1 is a flow chart of a method for determining parking space coordinates according to one embodiment of the present invention; Figure 2 is a structural block diagram of a vehicle according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] Embodiments of the present invention are described in detail below. The embodiments described with reference to the accompanying drawings are exemplary. Embodiments of the present invention are described in detail below.

[0024] The first embodiment of the present invention provides a method for determining the coordinates of a parking space. The method can optimize the parking space coordinate error and improve the parking effect.

[0025] Reference below Figure 1 The method for determining the parking space coordinates according to an embodiment of the present invention is described as follows: Figure 1 As shown, the method at least includes step S1-step S2.

[0026] Step S1, during the parking phase, multiple frames of historical parking space acquisition images are acquired.

[0027] Step S2, using a nonlinear optimization method based on multiple frames of historical parking space acquisition images to perform error optimization on the current parking space coordinates corresponding to the current frame of parking space acquisition images, so as to determine the target parking space coordinates for reference when the vehicle parks at the next moment.

[0028] Specifically, after the vehicle starts the automatic parking function, it will first enter the vehicle-searching stage, that is, the stage of looking for a parking space, and generate the initial coordinates of the parking space after determining a reliable parking space, that is, the parking space where the vehicle is expected to park is the handshake parking space, and then control the vehicle to enter the parking stage based on the initial coordinates. During the parking stage, the vehicle will continue to collect images of the handshake parking space and park based on the parking space coordinates identified in each frame of the image. During this process, the detection accuracy of the ultrasonic radar will change significantly when the vehicle leaves the target parking space or parks in the target parking space. In this case, updating the parking space will cause a large change in the parking space, thereby affecting the vehicle during the parking stage. The mapping results in deviations in the positioning of parking space coordinates when parking. Therefore, in order to avoid the problem that the error caused by the generation of the current parking space coordinates corresponding to the current frame parking space acquisition image due to the ultrasonic radar detection accuracy affects the parking positioning, the present application no longer directly uses the current parking space coordinates for parking, but introduces multiple frames of historical parking space acquisition images to optimize the error generated by the current parking space coordinates, so that this error is minimized in the local range, thereby avoiding the problem of error accumulation of the entire parking space due to the introduction of local errors into the overall global, thereby improving the parking space positioning accuracy, improving the parking space update of the vehicle during the parking stage to be more accurate and robust, and improving the parking effect.

[0029] In some embodiments, a nonlinear optimization method can be used to optimize the error of the current parking space coordinates corresponding to the current parking space acquisition image based on multiple frames of historical parking space acquisition images. That is, the error between the historical parking space acquisition images and the current parking space in time sequence is introduced, and the error is continuously optimized by nonlinear optimization means to minimize the error in a local range, thereby obtaining better target parking space coordinates.

[0030] Among them, nonlinear optimization methods can include least squares method, Gauss-Newton, gradient descent algorithm, Levenberg-Marquardt algorithm, etc., without limitation.

[0031] Exemplarily, there is no limit on the number of frames of historical parking space acquisition images. For example, if a vehicle has collected ten frames of historical parking space acquisition images, the eleventh frame of parking space acquisition images is the current frame of parking space acquisition images, and the coordinates of the eleventh frame of parking space acquisition images are identified to obtain the coordinates of the current parking space, and then the error between the historical parking space acquisition images and the current frame of parking space acquisition images in the time series is introduced, and the error is continuously optimized by nonlinear optimization means to minimize the error in the local range, thereby obtaining the optimized target parking space coordinates, and then the vehicle can use the target parking space coordinates as a reference for parking at the next moment. Therefore, by constructing the error association in the time series by nonlinear optimization means, the historical data accuracy can be better utilized to stabilize the error in the overall parking process, making the target parking space more accurate, and facilitating the parking of the vehicle.

[0032] According to the method for determining parking space coordinates of an embodiment of the present invention, during the parking stage, the error generated when the current parking space coordinates are generated is considered, thereby affecting the positioning of the parking space. By introducing multiple frames of historical parking space acquisition images and adopting a nonlinear optimization method, the error generated by the current parking space coordinates is optimized, so that the error is minimized in a local range, thereby improving the parking space positioning accuracy and improving the parking effect.

[0033] In some embodiments, a nonlinear optimization method is used to perform error optimization on the current parking space coordinates corresponding to the current parking space acquisition image based on multiple frames of historical parking space acquisition images to determine the target parking space coordinates for reference when the vehicle parks at the next moment, including: constructing a Gauss-Newton equation about the coordinate residual based on the multiple frames of historical parking space acquisition images; substituting the current parking space coordinates into the Gauss-Newton equation to determine the target parking space coordinates corresponding to the minimum residual value.

[0034] Specifically, it is usually assumed that multiple measurement results are independent and identically distributed, that is, a certain measurement does not affect the results of other measurements. On the other hand, assuming that the designed model can well describe the real physical event, then the error of any measurement should be a random error, which can be considered to satisfy the following Gaussian distribution: Formula (1) The probability of the symmetry axis of the Gaussian distribution is the highest. The symmetry axis of is at the origin, and the desired optimization direction is towards the origin. Based on this, minimizing the residual is equivalent to maximizing the joint probability of all measurements. Since the measurements are independent and identically distributed, we can directly convert the probability of each measurement into Multiplying them together gives formula (2).

[0035] Formula (2) Substitute into formula (1) The definition of can be obtained: Formula (3) Since m and σ are both constants, the sum of squares of the residuals is the best objective function both in theory and in practice. Therefore, the objective function is rewritten as follows: Formula (4) Among them, rj is the jth residual, is the residual function. Under this definition, the first-order and second-order derivatives of the objective function can be expressed by the Jacobian matrix and Hessian matrix of the residual as follows (5):

[0036] Where J(x) is the Jacobian matrix of the residual, 2r(x) is the Hessian matrix of the residual.

[0037] Each iteration of the Gauss-Newton method requires solving a linear equation: Formula (6) Substituting formula (4) and formula (5) into the linear equation, the second term in formula (5) is a very small amount, and after discarding it, we can get: Formula (7) Then the linear equation is solved using the QR decomposition method or the SVD decomposition method to obtain the result.

[0038] Based on the above principle, after entering the parking stage, the initial Gauss-Newton equation is iteratively updated based on multiple frames of historical parking space acquisition images until the iteration is stopped after the convergence condition is met. The Gauss-Newton equation is constructed, and then the current parking space coordinates are substituted into the Gauss-Newton equation for iterative extremes until the target parking space coordinates corresponding to the minimum residual value are obtained after convergence.

[0039] In some embodiments, substituting the current parking space coordinates into the Gauss-Newton equation includes: determining a weight value of the current parking space coordinates under the overall historical parking space acquisition image; and substituting the product value of the current parking space coordinates and the weight value into the Gauss-Newton equation.

[0040] Specifically, in order to further improve the accuracy of coordinate positioning, time is used as the weight when optimizing the coordinate error, and the nonlinear optimization method is used to use the translation and rotation as the residual to optimize the parking space coordinates. That is, the earlier the parking space acquisition image is collected, the lower the weight is, and the later the parking space acquisition image is collected, the higher the weight is. By determining the weight value of the current parking space coordinate under the overall historical parking space acquisition image, and substituting the product of the current parking space coordinate and the weight value into the Gauss-Newton equation to calculate the target parking space coordinate, the stability and robustness of the parking space coordinate update are further increased.

[0041] In some embodiments, determining the weight value of the current parking space coordinates under the overall historical parking space collection image includes: constructing a Gaussian model about the time dimension based on multiple frames of continuous historical parking space collection images; and determining the weight value of the current parking space coordinates under the overall historical parking space collection image based on the Gaussian model.

[0042] That is to say, the present application constructs a Gaussian model through historical parking space acquisition images acquired through multiple frames in a row, and then uses the Gaussian model to give the weight of the current parking space coordinates corresponding to the current frame parking space acquisition image in the overall multi-frame parking space coordinates, and then uses a nonlinear optimization method to calculate the optimized target parking space coordinates. This can better utilize the accuracy of historical data to stabilize the error in the overall parking process, making the target parking space more accurate and facilitating the parking of the vehicle.

[0043] In some embodiments, the method of the present application further includes: determining the initial coordinates of the handshake parking space before entering the parking phase; establishing a Kalman filter equation; and performing error optimization on the initial coordinates according to the Kalman filter equation to obtain updated initial coordinates.

[0044] Specifically, since the perception detection model in the parking space search stage is different from the model in the parking stage, there will be a certain degree of deviation in the positioning of the parking space. If the parking space is updated directly without considering this part of the deviation, the parking space coordinates in the parking stage will be inconsistent with the initial coordinates of the handshake parking space, which will affect the selection of the target parking space in the parking stage. Therefore, in the parking stage, Kalman filtering is used to optimize the error of the initial coordinates to obtain the final initial coordinates, thereby improving the accuracy and stability of the initial input parking space, namely the handshake parking space.

[0045] In some embodiments, the initial coordinates are optimized for error according to the Kalman filter equation, including: substituting the initial coordinates and the target parking space coordinates into the Kalman filter equation to optimize the initial coordinates for error, wherein the initial coordinates are used as predicted values ​​and the target parking space coordinates are used as observed values.

[0046] Specifically, the initial coordinates are used as predicted values, and the target parking space coordinates in the parking phase are used as observed values ​​and substituted into the Kalman filter equation:

[0047] Among them, x t is the state quantity, that is, the coordinates of the four vertices of the parking space, which can be expressed as {x0, y0, x1, y1, x2, y2, x3, y3}; F is the unit matrix, B is the unit matrix, and u is the error amount.

[0048] The observation equation is Z(k)=HX(k)+V(k) in, , , , .

[0049] Based on the above Kalman filter equation, the error optimization of the initial coordinates by Kalman filter can be realized, thereby improving the accuracy and stability of the initial input parking space, i.e., the handshake parking space.

[0050] In some embodiments, the initial coordinates and the target parking space coordinates are substituted into the Kalman filter equation to optimize the error of the initial coordinates, including: determining the coordinate difference between the initial coordinates and the target parking space coordinates; determining the weight value corresponding to the initial coordinates and the weight value corresponding to the target parking space coordinates according to the coordinate difference; substituting the initial coordinates, the weight value corresponding to the initial coordinates, the target parking space coordinates and the weight value corresponding to the target parking space coordinates into the Kalman filter equation to optimize the error of the initial coordinates.

[0051] That is to say, the distribution of noise weights is determined according to the difference between the coordinates of the parking space in the parking stage, i.e., the target parking space, and the initial coordinates in the mapping stage. The noise of the target parking space coordinates obtained at the beginning of the parking stage is relatively large, and as the number of gaps increases, the noise of the initial coordinates gradually increases. Based on this principle, when the Kalman filter is used to update the initial coordinates, as the parking stage continues, the weight values ​​corresponding to the initial coordinates and the weight values ​​corresponding to the target parking space coordinates are determined based on the coordinate difference, and then the initial coordinates, the weight values ​​corresponding to the initial coordinates, the target parking space coordinates, and the weight values ​​corresponding to the target parking space coordinates are substituted into the Kalman filter equation to optimize the error of the initial coordinates, thereby further improving the accuracy and stability of the initial input parking space, i.e., the handshake parking space.

[0052] In some embodiments, the method of the present application also includes: under the condition that there is no handshake parking space in the current frame parking space acquisition image, a nonlinear optimization method is used to optimize the parking space coordinates corresponding to the previous frame parking space acquisition image based on multiple frames of continuous historical parking space acquisition images to determine the target parking space coordinates.

[0053] Specifically, due to the limitations of perception, the handshake parking space may not be observed all the time, so it is necessary to save the parking spaces around the handshake parking space in time series. That is, if the handshake parking space does not exist in the parking space acquisition image of the current frame, the parking space coordinates of the parking space in the previous frame are directly used for subsequent calculations. If the handshake parking space exists, the parking space coordinates are updated before calculation.

[0054] In addition, after determining the target parking space coordinates for reference when the vehicle parks at the next moment, the method also includes: determining the initial coordinates of the handshake parking space before entering the parking stage; determining the coordinate difference between the initial coordinates and the target parking space coordinates; determining that the coordinate difference is not within the allowable error range, it means that there is a deviation in the parking space, and the vehicle is parked in the wrong handshake parking space position, so the target parking space coordinates are ignored, that is, the vehicle does not park according to the target parking space coordinates, and will exit this parking control, and re-identify the parking space to park again.

[0055] A second aspect of the present invention provides a vehicle, such as Figure 2 As shown, the vehicle 10 includes a collection device 1 and a memory 2 .

[0056] The acquisition device 1 is used to acquire parking space images; the controller 2 is connected to the acquisition device 1, and the controller 2 is used to execute the method for determining the parking space coordinates of the above embodiment.

[0057] It should be noted that the specific implementation method of the vehicle 10 in the embodiment of the present invention is similar to the specific implementation method of the method for determining the parking space coordinates in any of the above embodiments of the present invention. Please refer to the description of the method for determining the parking space coordinates. In order to reduce redundancy, it will not be repeated here.

[0058] According to the vehicle of the embodiment of the present invention, the parking space coordinate error can be optimized and the parking effect can be improved by executing the above method for determining the parking space coordinates through the controller.

[0059] In some embodiments, the vehicle 10 further includes a display device, which is connected to the controller 2, and is used to display an image based on the parking space acquisition image and the target parking space coordinates. A third aspect of the present invention provides a computer storage medium having a computer program stored thereon, which implements the method for determining the parking space coordinates of the above embodiment when the computer program is executed by a processor.

[0060] A fourth aspect of the present invention provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the method for determining the coordinates of a parking space in the above embodiment.

[0061] In the description of this specification, any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code including one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0062] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0063] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0064] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0065] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0066] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

[0067] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example.

[0068] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A method for determining the coordinates of a parking space, characterized in that: include: During the parking phase, multiple frames of historical parking space acquisition images are obtained; The error of the current parking space coordinates corresponding to the current parking space acquisition image is optimized according to multiple frames of historical parking space acquisition images to determine the target parking space coordinates for reference when the vehicle parks at the next moment.

2. The method for determining parking space coordinates according to claim 1, characterized in that: The error optimization of the current parking space coordinates corresponding to the current parking space acquisition image is performed based on multiple frames of historical parking space acquisition images, including: According to multiple frames of historical parking space acquisition images, a nonlinear optimization method is used to optimize the error of the current parking space coordinates corresponding to the current frame parking space acquisition image.

3. The method for determining parking space coordinates according to claim 2, characterized in that: According to the multi-frame historical parking space acquisition images, a nonlinear optimization method is used to optimize the error of the current parking space coordinates corresponding to the current frame parking space acquisition image, so as to determine the target parking space coordinates for reference when the vehicle parks at the next moment, including: Construct the Gauss-Newton equation about coordinate residuals based on multiple frames of historical parking space acquisition images; Substitute the current parking space coordinates into the Gauss-Newton equation to determine the target parking space coordinates corresponding to the minimum residual value.

4. The method for determining the coordinates of a parking space according to any one of claims 1 to 3, characterized in that: The method further comprises: Determine the initial coordinates of the handshake parking space before entering the parking phase; Establish the Kalman filter equation; The initial coordinates are error optimized according to the Kalman filter equation to obtain updated initial coordinates.

5. The method for determining parking space coordinates according to claim 4, characterized in that: The error optimization of the initial coordinates is performed according to the Kalman filter equation, including: Substitute the initial coordinates and the target parking space coordinates into the Kalman filter equation to perform error optimization on the initial coordinates, wherein the initial coordinates are used as predicted values ​​and the target parking space coordinates are used as observed values.

6. The method for determining parking space coordinates according to claim 5, characterized in that: Substituting the initial coordinates and the target parking space coordinates into the Kalman filter equation to perform error optimization on the initial coordinates, including: Determine the coordinate difference between the initial coordinates and the target parking space coordinates; Determine the weight value corresponding to the initial coordinates and the weight value corresponding to the target parking space coordinates according to the coordinate difference; The initial coordinates, the weight values ​​corresponding to the initial coordinates, the target parking space coordinates and the weight values ​​corresponding to the target parking space coordinates are substituted into the Kalman filter equation to perform error optimization on the initial coordinates.

7. The method for determining parking space coordinates according to claim 4, characterized in that: The method further comprises: Under the condition that there is no handshake parking space in the current frame parking space acquisition image, a nonlinear optimization method is used to optimize the parking space coordinates corresponding to the previous frame parking space acquisition image according to multiple frames of continuous historical parking space acquisition images to determine the target parking space coordinates.

8. A vehicle, characterized in that: include: A collection device, the collection device is used to collect parking space collection images; A controller, wherein the controller is connected to the acquisition device, and the controller is used to execute the method for determining the parking space coordinates according to any one of claims 1 to 7.

9. The vehicle according to claim 8, characterized in that Also includes: A display device is connected to the controller, and is used for displaying images according to the parking space acquisition image and the target parking space coordinates.

10. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining the coordinates of a parking space according to any one of claims 1 to 7 is implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for determining the coordinates of a parking space as described in any one of claims 1 to 7 are implemented.

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