Parking space rendering method, electronic equipment, storage medium, program product and vehicle

Abstract

The invention relates to a parking space rendering method, electronic equipment, a storage medium, a program product and a vehicle, and the method comprises the steps: carrying out the clustering of to-be-rendered parking spaces according to at least two clustering conditions when the number of the to-be-rendered parking spaces is at least two during the rendering of the parking spaces, and obtaining at least one parking space large group, and the parking spaces in the clustered parking space large group are rendered. According to the embodiment of the invention, the to-be-rendered parking spaces are clustered for multiple times, and the rendered display of the parking spaces is realized by using the clustered parking spaces in large groups, so that the parking space rendering efficiency can be improved, the parking space rendering error is reduced, the parking space rendering precision is improved, and the self-service parking accuracy and reliability of the vehicle can be improved.

Description

Technical Field

[0001] This application relates to the field of intelligent driving technology, and in particular to a parking space rendering method, electronic device, storage medium, program product, and vehicle. Background Technology

[0002] During automatic parking, it is necessary to render perceived objects such as vehicles, pedestrians, lane lines, and parking spaces on the vehicle's infotainment interface. Traditional parking space rendering suffers from discrepancies between the perceived parking space and the actual space, resulting in low rendering accuracy and poor rendering quality. Therefore, a parking space rendering method with minimal error and high accuracy is urgently needed. Summary of the Invention

[0003] This application provides a parking space rendering method, storage medium, program product, controller, and vehicle method, which improves the rendering accuracy of parking spaces and reduces rendering errors, thereby at least partially solving the above-mentioned technical problems.

[0004] To achieve the above objective, according to a first aspect of this application, a parking space rendering method is provided, comprising: when there are at least two parking spaces to be rendered, clustering the parking spaces to be rendered according to at least two clustering conditions to obtain at least one large group of parking spaces; and rendering the parking spaces within the large group of parking spaces.

[0005] Optionally, when there are at least two parking spaces in the same parking space group, at least two types of state characteristics of the parking spaces in the same parking space group are consistent, and the state characteristics correspond to the clustering conditions.

[0006] Optionally, when the parking space group includes at least two, at least one state characteristic of the parking spaces in different parking space groups is different.

[0007] Optionally, the method further includes: adjusting the parking lines of the parking space to be rendered according to the parking space type of the parking space to be rendered.

[0008] Optionally, the parking space type includes at least one of the following: perpendicular parking space, horizontal parking space, and angled parking space.

[0009] Optionally, the clustering conditions include one of the following: parking space orientation, parking space type, parking space dividing line spacing, parking space entrance line spacing, and parking space entrance line slope; the parking space state characteristics include one of the following: parking space orientation, parking space type, parking space dividing line spacing, parking space entrance line spacing, and parking space entrance line slope.

[0010] Optionally, the method further includes: performing at least one clustering operation on the parking spaces to be rendered based on at least one of the clustering conditions, namely, the parking space orientation, the parking space type, the parking space dividing line spacing, and the parking space entrance line spacing, to obtain at least one parking space group.

[0011] Optionally, the step of clustering the parking spaces to be rendered according to at least two clustering conditions includes: obtaining at least one first parking space group based on the parking space orientation; wherein the parking spaces in a first parking space group have the same orientation; and obtaining at least one second parking space group based on the parking space type within a first parking space group; wherein adjacent parking spaces in a second parking space group have the same parking space type.

[0012] Optionally, the method further includes: within a second parking space group, obtaining at least one third parking space group based on the parking space dividing line spacing; wherein, within a third parking space group, the parking space dividing line spacing between adjacent parking spaces is less than or equal to a first spacing threshold.

[0013] Optionally, the method further includes: within one of the third parking space groups, obtaining at least one parking space group based on the parking space entrance line spacing; wherein, within one of the parking space groups, the parking space entrance line spacing between adjacent parking spaces is less than or equal to a second spacing threshold.

[0014] Optionally, the method further includes: adjusting the parking line layout of parking spaces within the same parking space group to make the parking line layout of parking spaces within the same parking space group consistent.

[0015] Optionally, adjusting the parking line layout of parking spaces within the same parking space group includes: adjusting the parking line layout of parking spaces within the same parking space group based on the weighted parking line layout of the parking space group.

[0016] Optionally, the parking space layout includes at least one of the following: parking space orientation layout, parking space dividing line length, and parking space entrance line length.

[0017] Optionally, the weighted parking space line layout of the parking space group is determined by weighting the parking space line layouts of parking spaces within the same parking space group.

[0018] Optionally, the method further includes: determining a first weight of the parking space based on the distance between the vehicle and the parking space within the same parking space group; and determining a weighted parking space line layout of the parking space group based on the first weight of the parking space.

[0019] Optionally, determining the first weight of the parking space based on the distance between the vehicle and the parking space within the same parking space group includes: determining a first extreme value and a second extreme value among the distances between the vehicle and all parking spaces in the parking space group; and determining the first weight of the parking space based on the first extreme value, the second extreme value, and the actual distance between the vehicle and the current parking space.

[0020] Optionally, the method further includes: clustering parking spaces within at least one parking space group based on the slope of the parking space entrance line of the parking space to be rendered, to obtain at least one large parking space group; wherein, within one large parking space group, the slope of the parking space entrance line of all parking spaces is within the same range.

[0021] Optionally, the entrance line data of parking spaces within the same parking space group can be adjusted to ensure that the slope of the entrance lines of parking spaces within the same parking space group is consistent.

[0022] Optionally, adjusting the entrance line data of parking spaces within the same parking space group includes: weighting the slope of the entrance line of the parking spaces within the same parking space group to obtain the inter-group entrance line slope of the parking space group; and adjusting the entrance line slope of the parking spaces within the same parking space group based on the inter-group entrance line slope of the parking space group.

[0023] Optionally, the method further includes: determining a second weight of the parking space based on the distance between the vehicle and the parking space within the same parking space group; and determining the slope of the inter-group entrance line of the parking space group based on the second weight of the parking space.

[0024] Optionally, when the parking space group includes at least two, the method further includes: adjusting the entrance line data of the parking spaces within each parking space group to ensure that the parking space groups satisfy the constraint relationship.

[0025] Optionally, adjusting the entrance line data of parking spaces within each parking space group to ensure that the parking space groups satisfy the constraint relationship includes adjusting the entrance line slope of parking spaces within each parking space group to ensure that the entrance line slope of parking spaces within each parking space group satisfies the constraint relationship between the parking space groups.

[0026] Optionally, the constraint relationship between the parking space groups includes: the angle between the entrance line of a parking space in any parking space group and the entrance line of a parking space in other parking space groups is greater than a preset angle threshold.

[0027] Optionally, the constraint relationship between the parking space groups includes: the entrance line of a parking space in any one parking space group is perpendicular to the entrance lines of parking spaces in other parking space groups.

[0028] Optionally, the method further includes rendering the parking space if there is only one parking space to be rendered.

[0029] According to a second aspect of this application, an electronic device is provided, comprising: a memory having a computer program stored thereon; and a processor for executing the computer program in the memory to implement the steps of the parking space rendering method provided in the first aspect.

[0030] According to a third aspect of this application, a computer-readable storage medium is provided that stores a computer program or instructions thereon, which, when executed by a processor, implement the steps of the parking space rendering method provided in the first aspect.

[0031] According to a fourth aspect of this application, a computer program product is also provided, including a computer program or instructions that, when executed by a processor, implement the steps of the parking space rendering method provided in the first aspect.

[0032] According to a fifth aspect of this application, a vehicle is also provided, including the electronic equipment described in the second aspect.

[0033] In summary, this embodiment renders parking spaces using the above-described technical solution. When there are at least two parking spaces to be rendered, clustering is performed on the parking spaces according to at least two clustering conditions to obtain at least one large group of parking spaces. The parking spaces within each clustered large group are then rendered. This embodiment clusters the parking spaces to be rendered before rendering them, grouping them into at least one large group corresponding to the clustering conditions, and then uses these clustered large groups to display the parking spaces. Since the parking spaces within each large group are obtained based on the same clustering conditions, they share the same characteristics. This embodiment clusters the parking spaces before rendering, improving the consistency of the rendered parking spaces, reducing rendering errors, and increasing the accuracy and efficiency of parking space rendering. Furthermore, by rendering high-precision and high-reliability parking spaces, the accuracy and reliability of self-parking can also be improved.

[0034] Other features and advantages of this application will be described in detail in the following detailed description section. Attached Figure Description

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

[0036] To gain a more complete understanding of this application and its beneficial effects, the following description will be provided in conjunction with the accompanying drawings, wherein the same reference numerals in the following description denote the same parts.

[0037] Figure 1 This is a flowchart illustrating the steps of a parking space rendering method provided in an exemplary embodiment of this application;

[0038] Figure 2 This is a schematic diagram of a parking space line provided in an exemplary embodiment of this application;

[0039] Figure 3 This is a schematic diagram of a parking space to be rendered provided in an exemplary embodiment of this application;

[0040] Figure 4 This is a flowchart of another parking space rendering method provided in an exemplary embodiment of this application;

[0041] Figure 5 This is a schematic diagram of parking space clustering provided in an exemplary embodiment of this application;

[0042] Figure 6 This is a schematic diagram of another parking space clustering provided in an exemplary embodiment of this application;

[0043] Figure 7 This is a schematic diagram of another parking space clustering provided in an exemplary embodiment of this application;

[0044] Figure 8 This is a schematic diagram of another parking space clustering provided in an exemplary embodiment of this application;

[0045] Figure 9 This is a schematic diagram of another parking space clustering provided in an exemplary embodiment of this application;

[0046] Figure 10 This is a schematic diagram of an optimized parking space group provided in an exemplary embodiment of this application;

[0047] Figure 11 This is a schematic diagram of the vehicle architecture provided in an exemplary embodiment of this application. Detailed Implementation

[0048] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the protection scope of this application.

[0049] During automatic parking, the perceived objects of the autonomous driving system, such as vehicles, pedestrians, lane lines, and parking spaces, need to be rendered on the vehicle's infotainment interface. However, the data perceived by the autonomous driving system often differs from the actual data. In parking space rendering, errors in the perceived parking space data lead to rendering errors, affecting rendering accuracy and resulting in poor rendering quality.

[0050] This application provides a parking space rendering method. Please refer to [link / reference]. Figure 1 The flowchart shown illustrates the steps of the parking space rendering method. The parking space rendering method provided in this embodiment includes step S100. Wherein:

[0051] Step S100: If there are at least two parking spaces to be rendered, cluster the parking spaces to be rendered according to at least two clustering conditions to obtain at least one large group of parking spaces.

[0052] Step S200: Render the parking spaces within the parking space group.

[0053] Parking space rendering refers to the process of converting parking space information in a parking area into a visual image or graphic, which is then displayed on the vehicle's infotainment system. Before rendering, parking space data can be acquired through sensors on the vehicle, or external sensors can be used to transmit the collected data to the vehicle's processor. The parking area refers to the target parking area corresponding to the vehicle within a parking lot.

[0054] The parking spaces to be rendered refer to the parking spaces set up in the parking area. For different parking areas, the number, orientation, size, and layout of the parking spaces to be rendered can be different. In this embodiment of the application, when there are at least two types of parking spaces to be rendered, the parking spaces to be rendered are clustered according to at least two clustering conditions. The related parking spaces that meet the same clustering conditions are grouped into one class to obtain at least one large group of parking spaces, and then the parking spaces within the large group of parking spaces are rendered.

[0055] Since parking spaces within a large group are clustered using the same conditions, the parking spaces within each group share the same characteristics. This embodiment of the application clusters the parking spaces to be rendered before rendering, which improves the consistency of the rendered parking spaces, reduces rendering errors, and increases the accuracy and efficiency of parking space rendering. Furthermore, by rendering high-precision and high-reliability parking spaces, the accuracy and reliability of self-parking can also be improved.

[0056] In some embodiments, when a parking space group includes at least two parking spaces, at least two types of state characteristics of the parking spaces in the same parking space group are consistent, and the state characteristics correspond to the clustering conditions.

[0057] Clustering parking spaces to be rendered based on clustering conditions can be achieved by traversing each parking space in the parking area according to the state features corresponding to the clustering conditions, and grouping the parking spaces with the same state features into one group. After clustering, the clustering results include a class of identical state features. After clustering the parking spaces to be rendered using at least two clustering conditions, the parking spaces in the resulting large group include at least two classes of identical state features.

[0058] This application embodiment performs a clustering operation on the parking spaces to be rendered using clustering conditions, ensuring that the parking spaces within the same large group after clustering include at least two identical state features. When rendering the clustered parking space groups, since each large group includes at least two identical state features, the consistency of the rendering of parking spaces within the large group can be guaranteed, rendering errors can be reduced, and the rendering accuracy and reliability of parking spaces can be improved.

[0059] In some embodiments, when a parking space group comprises at least two, at least one state characteristic of the parking spaces within different parking space groups is different.

[0060] This application embodiment clusters the parking spaces to be rendered according to clustering conditions, grouping parking spaces with the same state characteristics into one category. If at least two large groups of parking spaces are obtained after clustering, it means that during the final clustering of the parking spaces to be rendered according to the clustering conditions, multiple parking spaces with different state characteristics corresponding to the clustering conditions exist, ultimately resulting in at least two large groups of parking spaces.

[0061] In some embodiments, clustering conditions include one of the following: parking space orientation, parking space type, spacing between parking space dividing lines, spacing between parking space entrance lines, and slope of parking space entrance lines.

[0062] In some embodiments, the parking space rendering method further includes: adjusting the parking space lines of the parking space to be rendered according to the parking space type of the parking space to be rendered.

[0063] Parking lines indicate the boundaries of parking spaces. The layout of parking lines can determine the orientation, size, and type of a parking space. For example, for perpendicular parking spaces, the entrance line and the dividing line are perpendicular to each other. For angled parking spaces, the entrance line and the perpendicular line within the same parking area are at the same angle.

[0064] Figure 2 The diagram shown is a schematic representation of a parking space line according to an embodiment of this application. Please refer to [link / reference]. Figure 2 Parking space lines can include the parking space entrance line, the parking space dividing line, and the parking space bottom edge line. The parking space entrance line is represented as... Figure 2Line 'a' in the diagram represents the boundary of the parking space closest to the vehicle. Normally, vehicles enter the parking space from the entrance line, but depending on the parking area, vehicles can choose different entry methods and are not necessarily required to enter from the entrance line. Parking space dividing lines are represented as follows: Figure 2 Lines b and c in the diagram are parking space dividing lines used to distinguish different parking spaces. Figure 2 As shown, for the parking space corresponding to the entrance line 'a', the parking space dividing lines 'b' and 'c' are the boundaries of that parking space. The area outside the dividing lines belongs to other parking spaces. The bottom edge line of the parking space is represented as... Figure 2 Line 'd' in the diagram represents the bottom line of the parking space, parallel to the entrance line. The bottom edge line of the parking space is the same as the dividing line, used to distinguish different parking spaces. Figure 2 In the diagram, A, B, C, and D represent the corner points of the parking space, that is, the intersection of the boundary lines of the parking space.

[0065] This application embodiment renders based on the perceived parking space data. Due to different sensing methods, the perceived parking spaces may be distorted or missing. Therefore, before rendering the parking spaces, the parking lines of the parking spaces to be rendered are adjusted according to the type of parking space to be rendered, in order to standardize the parking spaces to be rendered, reduce rendering errors, and improve rendering accuracy.

[0066] In some embodiments, the parking space type includes at least one of the following: perpendicular parking space, horizontal parking space, and angled parking space.

[0067] Parking space type refers to the layout of the parking space. Common parking space types include perpendicular parking spaces, horizontal parking spaces, and angled parking spaces.

[0068] A perpendicular parking space is a parking space where the parking direction is perpendicular to the lane. When a vehicle is parked in a perpendicular parking space, its front or rear is directly facing the lane. Perpendicular parking spaces make it easy to determine the parking direction, but because the vehicle is parked perpendicular to the lane, a certain width needs to be left for vehicles to turn into. They are suitable for parking areas with high parking efficiency requirements but relatively spacious areas.

[0069] A level parking space is one where the parking direction is parallel to the lane, and when a vehicle is parked in a level parking space, its body is aligned with the direction of the lane. Level parking spaces have high space utilization, but are more difficult to enter, making them suitable for parking areas with limited space but high parking demand.

[0070] An angled parking space is one where the parking direction is at a certain angle to the lane, usually between 30 and 60 degrees. When a vehicle is parked in an angled space, the body of the vehicle is tilted relative to the lane. Angled parking spaces are easier to enter than horizontal parking spaces and have higher space utilization than perpendicular parking spaces, making them suitable for parking areas where both parking convenience and space utilization are important.

[0071] It's understandable that perpendicular parking spaces are perpendicular to the lane, and horizontal parking spaces are horizontal to the lane, appearing as rectangles in the parking space rendering. Angled parking spaces form an angle with the lane, appearing as parallelograms in the parking space rendering. Before clustering the parking spaces to be rendered according to the S100 step above, the parking lines of the parking spaces to be rendered can be adjusted according to the parking space type to correct the parking lines perceived by the sensor and improve rendering accuracy.

[0072] For example, when adjusting the parking lines of a vertical parking space, first fix the two corner points of the parking space entrance line, determine the direction of the parking space dividing line according to the parking space type, calculate the length of the parking space dividing line, and then determine the coordinates of the other two corner points of the vertical parking space. When the parking space to be rendered is a horizontal or angled parking space, the method for adjusting the parking lines is roughly the same, the difference being that the length of the parking space dividing line for a horizontal parking space is different from that for a vertical parking space, and the direction of the parking space dividing line for an angled parking space is different from that for a vertical parking space.

[0073] In some embodiments, clustering conditions include one of the following: parking space orientation, parking space type, spacing between parking space dividing lines, spacing between parking space entrance lines, and slope of parking space entrance lines; the state characteristics of parking spaces include one of the following: parking space orientation, parking space type, spacing between parking space dividing lines, spacing between parking space entrance lines, and slope of parking space entrance lines.

[0074] The embodiments of this application cluster the parking spaces to be rendered based on at least two clustering conditions, which means that the parking spaces to be rendered are clustered at least twice based on different clustering conditions.

[0075] The parking space orientation indicates the direction the parking space faces. The orientation is perpendicular to the entrance line and points from the inside of the space to the outside. Please continue reading. Figure 2 The parking spaces shown include north-facing and south-facing spaces. Parking space types correspond to different vehicle entry methods, including perpendicular, horizontal, and angled spaces. Different types of parking spaces have different angles and length ratios between the parking space entrance line and the parking space dividing line. The spacing between parking space dividing lines represents the distance between adjacent parking space dividing lines, indicating the distance between parking spaces. The spacing between parking space entrance lines represents the distance between adjacent parking space entrance lines, indicating the staggered state between parking spaces. The slope of the parking space entrance line represents the angle of the parking space entrance line. Due to the parking space layout rules in parking areas, the parking space entrance lines are mostly parallel or perpendicular. This embodiment can also cluster the parking spaces to be rendered based on the slope of the parking space entrance lines to merge areas with the same characteristics, thereby improving the accuracy and reliability of parking space rendering.

[0076] In this embodiment of the application, when clustering based on clustering conditions, the state features corresponding to the clustering conditions are not single fixed values, but fall within a preset range. Taking parking space orientation as a clustering condition as an example, if two parking spaces have roughly the same orientation, or if the orientations of two parking spaces are both within the preset range, then the two parking spaces can be clustered into one class.

[0077] State features are parking space characteristics that correspond to clustering conditions. As described in the previous embodiments, parking spaces within the same large group have the same state features. State features, which correspond to clustering conditions, may also include: parking space orientation, parking space type, spacing between parking space dividing lines, spacing between parking space entrance lines, and slope of parking space entrance lines.

[0078] In some embodiments, the parking space rendering method further includes: performing at least one clustering of the parking spaces to be rendered based on at least one clustering condition among parking space orientation, parking space type, parking space dividing line spacing, and parking space entrance line spacing, to obtain at least one parking space group.

[0079] This application embodiment clusters the parking spaces to be rendered based on at least two clustering conditions. Each clustering corresponds to different clustering conditions, which can be understood as performing at least two clustering operations. Therefore, the clustering process of this application embodiment can be divided into a final clustering operation and several clustering operations before the final clustering operation. A parking space group can represent the clustering results before the final clustering of the parking spaces to be rendered. After obtaining the parking space groups, the final clustering operation is performed based on the clustering conditions and the parking space groups.

[0080] This application embodiment can perform clustering operations on the parking spaces to be rendered based on any one of the clustering conditions, such as parking space orientation, parking space type, parking space dividing line spacing, or parking space entrance line spacing, so as to divide the parking spaces to be rendered into multiple parking space groups.

[0081] For example, the parking spaces to be rendered can be clustered according to any one of the following clustering conditions: parking space orientation, parking space type, spacing between parking space dividing lines, or spacing between parking space entrance lines, to obtain at least one cluster group. Alternatively, the parking spaces to be rendered can be clustered according to any two different clustering conditions: parking space orientation, parking space type, spacing between parking space dividing lines, or spacing between parking space entrance lines, to obtain at least one cluster group. Alternatively, the parking spaces to be rendered can be clustered according to any three different clustering conditions: parking space orientation, parking space type, spacing between parking space dividing lines, or spacing between parking space entrance lines, to obtain at least one cluster group. Alternatively, the parking spaces to be rendered can be clustered according to each of the four clustering conditions: parking space orientation, parking space type, spacing between parking space dividing lines, or spacing between parking space entrance lines, to obtain at least one cluster group.

[0082] It is understood that the embodiments of this application do not restrict the order of setting clustering conditions when forming cluster groups. In practical applications, the order of setting clustering conditions can be determined according to different needs.

[0083] In some embodiments, the parking spaces to be rendered are clustered according to at least two clustering conditions, including: obtaining at least one first parking space group based on the orientation of the parking spaces; wherein the parking spaces in a first parking space group have the same orientation; and obtaining at least one second parking space group based on the parking space type within a first parking space group; wherein adjacent parking spaces in a second parking space group have the same parking space type.

[0084] The parking space orientation indicates the relative position of the parking space to be rendered and the vehicle. The same parking space may have different orientations depending on the vehicle's position. For example, for a vehicle waiting to park, the parking space orientation is perpendicular to the parking space entrance line and points from inside the parking space to the outside. Please refer to [link / reference]. Figure 3 , Figure 3 The image shown is a schematic diagram of a parking space to be rendered according to an embodiment of this application. Figure 3 As shown, parking space orientation includes parking spaces located to the right of the parking space and facing the left side of the vehicle, and parking spaces located to the left of the parking space and facing the right side of the vehicle. When clustering the parking spaces to be rendered based on at least two clustering conditions, the parking spaces to be rendered can be clustered first based on the parking space orientation to obtain at least one first parking space group; then, within each first parking space group, the parking spaces within each first parking space group are clustered based on the parking space type to obtain at least one second parking space group.

[0085] Please continue reading. Figure 3 After clustering the parking spaces to be rendered based on their orientation, the parking spaces are divided into two first parking space groups: those located to the right of the vehicle and those located to the left. Each first parking space group is then clustered based on its parking space type, which includes perpendicular, horizontal, and angled parking spaces. The parking spaces in each first parking space group are traversed in a specific order. When two adjacent parking spaces have different types, a new parking space group is generated, ultimately resulting in at least one second parking space group after clustering. Within each second parking space group, two adjacent parking spaces have the same parking space type.

[0086] In some embodiments, the parking space rendering method further includes: within a second parking space group, obtaining at least one third parking space group based on the spacing between parking space dividing lines; wherein, within a third parking space group, the spacing between parking space dividing lines of adjacent parking spaces is less than or equal to a first spacing threshold.

[0087] Parking space dividing lines are the boundary lines between adjacent parking spaces, and the spacing between these dividing lines can be used to represent the distance between adjacent parking spaces. If at least one second parking space group is obtained by clustering based on parking space orientation and type, the parking spaces within the second parking space group can be further clustered based on the spacing between the dividing lines to obtain at least one third parking space group. Here, the spacing between the dividing lines represents the distance between the lines of two adjacent parking spaces.

[0088] For example, the parking spaces in the second parking space group are traversed in a certain order. When the distance between the parking space dividing lines of two adjacent parking spaces is greater than the first distance threshold, a new parking space group is generated. Finally, at least one third parking space group after clustering is obtained. In each third parking space group, the distance between the parking space dividing lines of two adjacent parking spaces is less than or equal to the first distance threshold.

[0089] In some embodiments, the parking space rendering method further includes: within a third parking space group, obtaining at least one parking space group based on the parking space entrance line spacing; wherein, within a parking space group, the parking space entrance line spacing between adjacent parking spaces is less than or equal to a second spacing threshold.

[0090] The parking space entrance line is the boundary line for vehicles to enter the parking space, and the spacing between the parking space entrance lines can be used to represent the misalignment status of adjacent parking spaces. If at least one third parking space group is obtained by clustering based on parking space orientation, parking space type, and parking space dividing line spacing, the parking spaces within the third parking space group can be further clustered based on the misalignment status to obtain at least one parking space subgroup.

[0091] For example, the parking spaces in the third parking space group are traversed in a certain order. When the distance between the entrance lines of two adjacent parking spaces is greater than the second distance threshold, a new parking space group is generated. Finally, at least one group of parking spaces after clustering is obtained. In each parking space group, the distance between the entrance lines of two adjacent parking spaces is less than or equal to the second distance threshold.

[0092] In some embodiments, the parking space rendering method further includes: adjusting the parking space line layout of parking spaces within the same parking space group to make the parking space line layout of parking spaces within the same parking space group consistent.

[0093] Parking space layout includes the length of the parking spaces and the angles between them. Based on the parking space layout, the orientation and type of each parking space can be determined. When the parking spaces to be rendered are clustered into at least one group, the parking space layout within each group is adjusted to ensure consistency. In other words, after clustering into at least one group, this embodiment adjusts the parking spaces within each group to ensure they present the same layout, guaranteeing consistency within the group. Adjusting each parking space within a group to have the same layout improves the reliability and accuracy of parking space rendering and reduces rendering errors.

[0094] In some embodiments, the parking space layout includes at least one of the following: parking space orientation angle, parking space dividing line length, and parking space entrance line length.

[0095] The parking space orientation angle represents the angle between the parking space entrance line and the parking space dividing line, which determines the orientation of the parking space. For parking spaces within the same parking space group, the orientation angle of each space can be adjusted to ensure that all spaces have the same orientation angle. The lengths of the parking space dividing line and the parking space entrance line correspond to the parking space type. When the parking space orientation angle, parking space dividing line length, and parking space entrance line length are all the same, it ensures that all parking spaces within the parking space group have the same layout.

[0096] In some embodiments, adjusting the parking line layout of parking spaces within the same parking space group includes: adjusting the parking line layout of parking spaces within the same parking space group based on the weighted parking line layout of the parking space group.

[0097] The weighted parking line layout is the parking line layout corresponding to a parking space group. For example, the weighted parking line layout of each parking space within a parking space group is calculated to obtain the weighted parking line layout of the parking space group. The parking line layout of each parking space within a parking space group may vary significantly. In this embodiment, when adjusting the parking line layout of parking spaces within a parking space group, the weighted parking line layout of the parking space group is calculated first, and then the parking line layouts of parking spaces within the same parking space group are adjusted to be the same as the weighted parking line layout of the parking space group. For example, the orientation angle of parking spaces within a parking space group is adjusted to the orientation angle in the weighted parking line layout; the length of the parking entrance line of parking spaces within a parking space group is adjusted to the length of the parking entrance line in the weighted parking line layout; and the length of the parking space dividing line of parking spaces within a parking space group is adjusted to the length of the parking space dividing line in the weighted parking line layout, so that the layout of each parking space in the parking space group is the same.

[0098] In some embodiments, the weighted parking line layout of a parking space group is determined by weighting the parking line layout of parking spaces within the same parking space group.

[0099] The weighted parking line layout of parking spaces within the same parking space group is obtained by weighting the parking line layout of that group. When forming the parking line layout of a parking space group, the characteristics of each parking space in the group can also be taken into account, reducing errors in parking space rendering.

[0100] In some embodiments, the parking space rendering method further includes: determining a first weight of a parking space based on the distance between a vehicle and a parking space within the same parking space group; and determining the parking space line layout of the parking space group based on the first weight of the parking space.

[0101] Before performing weighted calculations on the parking space layout within a parking space group, the weight of each parking space in the same group can be determined first. In this embodiment, the weight of each parking space in the group is determined based on the distance between the parking space and the vehicle, and is denoted as the first weight.

[0102] For example, the distance between a parking space and a vehicle can be determined by setting reference points on both the vehicle and the parking space, and then measuring the distance between the two reference points. For instance, the center point of the parking space can be used as the reference point, and the center point of the vehicle's rear axle can be used as the vehicle's centerline. The distance between the parking space and the vehicle can be determined by calculating the distance between the center point of the parking space and the center point of the vehicle's rear axle. It is understood that for the same parking area, the standards for setting the vehicle reference point and the parking space reference point are the same; however, different vehicle reference points and parking space reference points can be set for different parking areas.

[0103] In some embodiments, determining the first weight of a parking space based on the distance between a vehicle and a parking space within the same parking space group includes: determining a first distance extreme value and a second distance extreme value among the distances between a vehicle and all parking spaces in the parking space group; and determining the first weight of the parking space based on the first distance extreme value, the second distance extreme value, and the actual distance between the vehicle and the current parking space.

[0104] Distance extremes represent the critical values ​​among the distances between a vehicle and all parking spaces in the same parking space group. Specifically, the first distance extreme and the second distance extreme represent two extreme values ​​between the distances between a vehicle and all parking spaces in the same parking space group. For example, the first distance extreme could be the maximum distance, representing the distance between the vehicle and the parking space with the largest distance among all parking spaces; the second distance extreme could be the minimum distance, representing the distance between the vehicle and the parking space with the smallest distance among all parking spaces. In this embodiment, the first weight of a parking space in its parking space group is calculated based on the distance between the vehicle and the parking space. For example, the first weight W of each parking space in the parking space group... i It can be represented as:

[0105]

[0106] Where, d max This represents the first extreme value of distance, i.e., the maximum distance, d. min This represents the second extreme value of distance, i.e., the minimum value of distance, d. i This indicates the distance between the current parking space and the vehicle.

[0107] After determining the first weight of the parking space, taking the length of the parking space entrance line as an example, the weighted entrance line length in the weighted parking space line layout corresponding to the parking space group can be expressed as:

[0108] W1e1+W2e2+…+W n e n

[0109] Among them, e i This represents the length of the parking space entrance line for each parking space in the parking space group. The calculation method for the parking space orientation angle and the length of the parking space dividing line in the weighted parking space layout is similar to that for the parking space entrance line length, and will not be repeated here.

[0110] In some embodiments, the parking space rendering method further includes: clustering parking spaces within at least one parking space group based on the slope of the parking space entrance line of the parking space to be rendered, to obtain at least one large parking space group; wherein, within a large parking space group, the slopes of the parking space entrance lines of all parking spaces are within the same range.

[0111] After forming parking space groups, it is necessary to cluster the parking spaces within each group based on the slope of the parking space entrance line, according to clustering conditions, to obtain at least one large parking space group. If the entrance line slopes of adjacent parking space groups are the same or similar, the corresponding parking space groups are clustered together. Within the same large parking space group, the entrance line slopes of the parking spaces are within the same range; for example, the entrance line slopes of the parking spaces within the large parking space group are all within a preset range, exhibiting a parallel or approximately parallel state. In some embodiments, the parking space rendering method further includes: adjusting the entrance line data of parking spaces within the same large parking space group to ensure that the entrance line slopes of parking spaces within the same large parking space group are consistent.

[0112] After clustering parking spaces into large groups, the entrance line data of parking spaces within each large group is adjusted to ensure that the slopes of the entrance lines are consistent. Consistent entrance line slopes can mean that the slopes of the entrance lines are the same, or that the entrance lines of parking spaces within the same large group are parallel. Typically, parking spaces in a parking lot are perpendicular or parallel to each other. In this embodiment, after clustering into large groups, the parking spaces within each large group are adjusted to ensure consistency in parking space rendering, reduce rendering errors, and improve rendering accuracy. For example, the slopes of the entrance lines of parking spaces within a large group can be adjusted to ensure that the slopes of the entrance lines are consistent.

[0113] In some embodiments, adjusting the entrance line data of parking spaces within the same parking space group includes: weighting the slope of the entrance line of parking spaces within the same parking space group to obtain the slope of the entrance line between parking spaces in the same group; and adjusting the slope of the entrance line of parking spaces within the same parking space group based on the slope of the entrance line between parking spaces in the same group.

[0114] The slope of the entrance line between parking spaces is the slope of the entrance line corresponding to the larger group of parking spaces. When adjusting the slope of the entrance line for parking spaces within a larger group, the slope of the entrance line between the two groups of parking spaces is determined first. For example, the slope of the entrance lines of parking spaces within the same larger group can be weighted to obtain the slope of the entrance line between the two groups.

[0115] The slope of the entrance line for each parking space within a large parking space group is adjusted based on the slope of the entrance lines between groups, ensuring that the entrance lines of each parking space within the large group are parallel to each other. This embodiment of the application adjusts the slope of the entrance lines within a large parking space group to guarantee the regularity and uniformity of the entrance lines, reducing errors during parking space rendering and improving rendering accuracy.

[0116] In some embodiments, the parking space rendering method further includes: determining a second weight of the parking space based on the distance between the vehicle and the parking space within the same parking space group; and determining the slope of the inter-group entrance line of the parking space group based on the second weight of the parking space.

[0117] When calculating the slope of the entrance line between parking spaces within a large group, the weight of each parking space in the large group can be determined first. In this embodiment, the weight of each parking space in the large group is determined based on the distance between each parking space and the vehicle, and is represented as the second weight.

[0118] For example, the distance between a parking space and a vehicle can be determined by setting reference points on both the vehicle and the parking space, and then measuring the distance between the two reference points. For instance, the center point of the parking space can be used as the reference point, and the center point of the vehicle's rear axle can be used as the vehicle's centerline. The distance between the parking space and the vehicle can be determined by calculating the distance between the center point of the parking space and the center point of the vehicle's rear axle. It is understood that for the same parking area, the standards for setting the vehicle reference point and the parking space reference point are the same; however, different vehicle reference points and parking space reference points can be set for different parking areas.

[0119] In some embodiments, when the parking space group includes at least two, the parking space rendering method further includes: adjusting the entrance line data of the parking spaces within each parking space group to ensure that the parking space groups satisfy the constraint relationship.

[0120] Constraints refer to the relationships between parking spaces within a parking area. Generally, parking spaces in a parking area are arranged according to preset rules, and they are usually perpendicular or parallel to each other. In this embodiment, after clustering based on at least two clustering conditions to obtain at least two large groups of parking spaces, the entrance line data of the parking spaces within each large group is adjusted to ensure that the large groups of parking spaces satisfy the constraint relationships. This embodiment adjusts the entrance line data of the parking spaces within the clustered large groups to ensure that the parking spaces within the large groups satisfy the constraint relationships of the parking area where the parking space to be rendered is located, guaranteeing that the adjusted parking spaces are identical to the parking spaces in the parking area, improving the accuracy of parking space rendering, and reducing rendering errors.

[0121] In some embodiments, adjusting the entrance line data of parking spaces within each parking space group to satisfy the constraint relationship between parking space groups includes: adjusting the slope of the entrance line of parking spaces within each parking space group to satisfy the constraint relationship between parking space groups.

[0122] The slope of the entrance line for a parking space group represents the slope of the entrance line for that parking space group. After a parking space group is formed, the slope of the entrance line for each parking space within that group is adjusted to ensure that the slope of the entrance line for each parking space within the group is consistent. Therefore, the slope of the entrance line for a parking space group represents the slope of the entrance line for each parking space within that group.

[0123] In some embodiments, the constraint relationship between parking space groups includes: the angle between the entrance line of a parking space in any parking space group and the entrance line of a parking space in other parking space groups is greater than a preset angle threshold.

[0124] Most parking spaces in a parking area share the same parking line layout, meaning they exhibit similar characteristics. Based on parking space placement rules, the angles between parking spaces are typically identical. This embodiment adjusts the entrance line data within a large group of parking spaces based on the angle of the entrance lines between these groups, ensuring that different groups of parking spaces satisfy the constraints between parking spaces in the parking area. Preset angle thresholds can be 0 degrees, 30 degrees, 60 degrees, 90 degrees, etc. Taking a preset angle threshold of 0 degrees as an example, the angles between large groups of parking spaces can be adjusted to fall within a first angle range of 0 to 30 degrees, a second angle range of 30 to 60 degrees, or a third angle range of 60 to 90 degrees. This embodiment adjusts the entrance line data between large groups of parking spaces to ensure that the adjusted group data matches the actual parking spaces in the parking area to be rendered, thus improving rendering accuracy.

[0125] In one embodiment, the constraint relationship between parking space groups includes: the entrance line of a parking space in any one parking space group is perpendicular to the entrance lines of parking spaces in other parking space groups.

[0126] The fact that the entrance lines between parking space groups are perpendicular means that the angle between the entrance lines of the parking space groups is 90 degrees. This application embodiment adjusts the parking space entrance line data within a parking space group so that the angle between the entrance lines of the parking space groups is 90 degrees, meaning that the entrance lines between the parking space groups are perpendicular to each other.

[0127] In one embodiment, the parking space rendering method further includes: rendering the parking space to be rendered when there is only one parking space to be rendered.

[0128] When there is only one parking space to be rendered in the parking area, there is no need to perform clustering operations on the parking spaces to be rendered, and the parking space can be rendered directly. In some embodiments, when there is only one parking space to be rendered, the parking space line data can be adjusted according to the parking space type before rendering to improve rendering accuracy and reduce rendering errors.

[0129] The parking space rendering method of this application embodiment is illustrated below with a specific example.

[0130] Figure 3 The image shown is a schematic diagram of a parking space to be rendered. Please refer to [link / reference]. Figure 3 The parking area includes the areas on either side of the lane where the vehicle is located. Based on Figure 3 The parking spaces to be rendered shown are as follows: Figure 4 The parking space rendering method shown includes the following steps S410 to S450. Wherein:

[0131] Step S410: Obtain the parking space data of the parking space to be rendered.

[0132] The parking space data to be rendered can be obtained from the perception module. Parking space data typically includes parking space type, parking line data, and parking space identifiers. Parking space types include perpendicular parking spaces, horizontal parking spaces, and angled parking spaces. Parking space identifiers include parking space ID, parking space number, and characters within the parking space. Based on the parking space identifiers, the location of the parking space can be determined when performing operations such as clustering and adjustment of parking spaces.

[0133] Step S420: Adjust the parking lines in the area to be rendered according to the parking space type of the parking space to be rendered.

[0134] The parking lines obtained by the sensing module are adjusted according to the parking space type to make the parking lines correspond to the parking space type.

[0135] Step S430: Cluster the parking spaces to be rendered according to their orientation, type, spacing between dividing lines, and spacing between entrance lines to obtain at least one parking space group.

[0136] The parking spaces to be rendered are clustered according to four clustering conditions: parking space orientation, parking space type, parking space dividing line spacing, and parking space entrance line spacing.

[0137] Figure 5 To determine the orientation of the parking space Figure 3 The diagram shows a clustering process for the parking spaces to be rendered. Figure 5 As shown, the area to be rendered is divided into right parking spaces located to the right of the vehicle and left parking spaces located to the left of the vehicle, based on the orientation of the parking spaces. The left and right parking spaces can be sorted according to the x-coordinate.

[0138] Figure 6 To classify parking spaces according to type Figure 5The diagram shows a clustering operation performed on the two parking space groups on the left and right. Figure 6 As shown, parking spaces in the left and right parking space groups are clustered according to parking space type. Parking spaces with different types within the two groups are then grouped into new subgroups. During clustering by parking space type, the parking spaces in each group are traversed sequentially. If two adjacent parking spaces have different types, they are placed into different parking space groups. The left parking space group is divided into three groups based on parking space type, and the right parking space group is divided into two groups based on parking space type.

[0139] Figure 7 To adjust according to the spacing of parking space dividing lines Figure 6 The diagram illustrates the clustering of the five parking space groups shown. Figure 7 As shown, when clustering based on the spacing of parking space dividing lines, the data is traversed in order. Figure 6 If the distance between the dividing lines of two adjacent parking spaces in each parking space group is greater than a first distance threshold, then the two parking spaces will be placed in different parking space groups. The first parking space group on the right will be divided into two parking space groups based on the distance between the dividing lines.

[0140] Figure 8 To adjust according to the parking space entrance line spacing Figure 7 The diagram illustrates the clustering of the six parking space groups shown. Figure 8 As shown, when clustering based on the spacing of parking space entrance lines, the process is traversed in order. Figure 7 Within each parking space group, if the distance between the entrance lines of two adjacent parking spaces is greater than a second distance threshold, then the two parking spaces are divided into different parking space groups. The first parking space group on the left is divided into two smaller parking space groups based on the distance between the entrance lines.

[0141] Step S440: Adjust the parking line layout of parking spaces within the same parking space group to ensure consistency with the parking line layout of parking spaces within the same parking space group.

[0142] The first weight of each parking space is determined based on its distance from the vehicle within the parking space group. A weighted parking space layout is then calculated by weighting the parking space line layout of each space within the group. Finally, the entrance line layout of each parking space within the group is adjusted to match the weighted parking space layout of the group.

[0143] Each parking space can carry a set of data, represented as {d i ,θ i ,e i ,s i ,t i}. Wherein, d i Let θ represent the distance between the i-th parking space and the vehicle. This distance can be expressed as the distance from the center of the vehicle's rear axle to the center of the parking space. ie represents the orientation angle of the i-th parking space. i Let s represent the length of the entrance line for the i-th parking space. i t represents the length of the parking space dividing line for the i-th parking space. i This indicates the parking space type of the i-th parking space, such as perpendicular parking space, horizontal parking space, or angled parking space.

[0144] For example, suppose the current parking space group has n parking spaces, and the distance between the vehicle and each parking space in the group is represented as {d1, d2, ..., dn}. n The weight W of the parking space i Represented as: Among all the distances between parking spaces in a parking space group, the maximum distance is d. max The minimum distance is d min After obtaining the parking space weights, taking the length of the parking space entrance line as an example, the weighted parking space entrance line length corresponding to the parking space group is expressed as: W1e1 + W2e2 + ... + W n e n Other parking space layouts are calculated using the same method to obtain the final weighted value, and the parking space layout of each parking space in the parking space group is adjusted based on the calculated weighted parking space layout.

[0145] Step S450: Cluster at least one parking space group based on the slope of the parking space entrance line to obtain at least one large parking space group.

[0146] Figure 9 This is a schematic diagram illustrating the clustering of parking space groups based on the slope of the parking space entrance line. For example... Figure 9 As shown, when clustering based on the slope of the parking space entrance line, the parking spaces in each parking space group are traversed in order. If the slopes of the entrance lines of two adjacent parking spaces are in the same slope range, such as being the same or very close, the two parking space groups are divided into one large parking space group; otherwise, they are added to other large parking space groups. Figure 9 The parking spaces were eventually divided into two large groups.

[0147] Step S460: Adjust the entrance line data of parking spaces within the same parking space group to make the slope of the entrance line of parking spaces within the same parking space group consistent.

[0148] A parking space group may comprise several parking space subgroups. In the preceding steps, the parking line layout within each subgroup has been adjusted to ensure that the layout is identical, meaning the entrance line slope is the same for all parking spaces within each subgroup. After forming the parking space group, the entrance line slopes of different subgroups within the group are further adjusted to ensure that the entrance lines of parking spaces within the same group are completely parallel. For example, a second weight can be determined based on the distance between each parking space and the vehicle within the group. Then, the inter-group entrance line slopes of the parking space group are obtained by weighting the entrance line slopes of the parking spaces within the group. Finally, the entrance line slope of each parking space within the group is adjusted to match the weighted inter-group entrance line slopes of the group, ensuring that the entrance line slopes of all parking spaces within the group are consistent.

[0149] Step S470: Adjust the entrance line data of parking spaces within each parking space group to ensure that the constraint relationship between parking space groups is satisfied.

[0150] Since the entrance lines of parking spaces in parking areas are mostly horizontal or vertical, this application embodiment determines the constraint relationship between large groups of parking spaces based on the relationship between parking spaces in the parking area, thereby adjusting the entrance line data of parking spaces between each large group of parking spaces.

[0151] First, calculate the slope of the entrance line for each parking space in the group of parking spaces, denoted as m. i Where i represents the index of the parking space entrance line. Define an optimization objective function, the objective of which is to adjust the slope of the parking space entrance line for each parking space so that as many parking space entrance lines as possible satisfy one of the following conditions:

[0152] The entrance lines between large groups of parking spaces are parallel: the slopes of the entrance lines are equal, denoted as m. i =m j m i and m j This represents the slope value of the parking space entrance line for each parking space in different parking space groups;

[0153] The entrance lines between large groups of parking spaces are perpendicular: the product of the slopes of the entrance lines is -1, expressed as m. i *m j =-1.

[0154] The objective function is expressed as:

[0155] First, calculate the objective function value under the slope of the entrance line for each parking space in the current parking space group. Then, calculate the partial derivative of the slope for each parking space group to obtain the gradient. The gradient corresponds to the parking space in the group with the largest change in the entrance line slope. Update the entrance line slope of the parking spaces in the group based on the gradient, expressed as: Finally, the objective function, gradient, and slope of the parking space entrance line are repeatedly calculated until convergence to the constraint relationship.

[0156] The embodiments of this application optimize the calculation by constructing an objective function, which can globally search for the optimal solution and ensure that the adjustment result of the line segment direction satisfies the perpendicular or parallel relationship as much as possible. Figure 10 The diagram shows the relationship between parking space groups, based on the constraints between them. Figure 9 The diagram shown is a schematic of the optimized parking space group. Figure 10 right Figure 9 The slope of the entrance line is optimized to further improve the accuracy of parking spaces within a large group, reduce parking space rendering errors, and improve the uniformity of the rendering.

[0157] Step S480: Render the adjusted parking spaces in the large group.

[0158] This application embodiment performs multiple clustering of the parking spaces to be rendered based on multiple clustering conditions. The parking spaces are divided into at least one large group based on these clustering conditions, and the rendering is achieved using these large groups of clustered parking spaces. In this application embodiment, when clustering the parking spaces to be rendered, the parking spaces within each small group are adjusted, the parking spaces within each large group are adjusted, and the parking spaces between large groups are also adjusted. Finally, the adjusted parking spaces are rendered. The rendering method of this application embodiment can improve parking space rendering efficiency, reduce errors during parking space rendering, and improve the accuracy of parking space rendering, thereby improving the accuracy and reliability of self-parking for vehicles.

[0159] According to a second aspect of this application, embodiments of this application also provide an electronic device, comprising: a memory storing a computer program thereon; and a processor for executing the computer program in the memory to implement the steps of the above-described parking space rendering method. This electronic device possesses all the beneficial effects of the above-described parking space rendering method, which will not be elaborated upon further herein.

[0160] According to a third aspect of this application, embodiments of this application also provide a computer-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the steps of the parking space rendering method described above. This non-transitory computer-readable storage medium possesses all the beneficial effects of the parking space rendering method described above, which will not be elaborated further here.

[0161] According to a fourth aspect of this application, embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the above-described parking space rendering method. This computer program product possesses all the beneficial effects of the above-described parking space rendering method, which will not be elaborated upon further herein.

[0162] According to a fifth aspect of this application, embodiments of this application also provide a controller having a computer program or instructions stored thereon, which, when executed by a processor, implements the steps of the above-described parking space rendering method. This controller possesses all the beneficial effects of the above-described parking space rendering method, which will not be elaborated further here.

[0163] Computer-readable storage media can be, for example, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof, without particular limitation herein. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0164] In some embodiments of this application, a computer-readable storage medium may be any tangible medium that contains or stores a program that may be used or combined with an instruction execution system, apparatus, or device.

[0165] The aforementioned computer-readable storage medium may be included in the aforementioned electronic device, or it may exist independently without being assembled into the electronic device. The aforementioned computer-readable storage medium carries one or more programs that, when executed by the electronic device, cause the control chip in the electronic device to communicate with the intelligent network system via Ethernet through a physical layer device.

[0166] Computer program code for performing operations of some embodiments of this application can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0167] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function.

[0168] It should also be noted that in some alternative implementations, the functions marked in the box may occur in a different order than those marked in the attached figures.

[0169] For example, two consecutively represented blocks can actually be executed in substantially parallel order, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, as well as combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified functions or operations, or using a combination of dedicated hardware and computer instructions.

[0170] The units described in some embodiments of this application can be implemented in software or in hardware.

[0171] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0172] like Figure 11 As shown, according to a sixth aspect of this application, a vehicle 10 is provided in an embodiment of this application. This vehicle includes the aforementioned electronic equipment or controller. This vehicle possesses all the beneficial effects of the aforementioned electronic equipment or controller, etc., which will not be repeated here. This vehicle may be a plug-in hybrid electric vehicle or a new energy vehicle, etc., and this application does not specifically limit it in this regard.

[0173] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0174] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0175] The embodiments, implementation methods, and related technical features of this application can be combined and substituted for each other without conflict.

[0176] The above are merely preferred embodiments of this application and are not intended to limit this application in any way. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of this application without departing from the scope of the technical solution of this application shall still fall within the scope of the technical solution of this application.

Claims

1. A parking space rendering method, characterized in that, include: If there are at least two parking spaces to be rendered, the parking spaces to be rendered are clustered according to at least two clustering conditions to obtain at least one large group of parking spaces. Render the parking spaces within the aforementioned parking space group.

2. The method according to claim 1, characterized in that, When there are at least two parking spaces in the same parking space group, at least two types of state characteristics of the parking spaces in the same parking space group are consistent, and the state characteristics correspond to the clustering conditions.

3. The method according to claim 1, characterized in that, When the parking space group includes at least two parking spaces, at least one state characteristic of the parking spaces in different parking space groups is different.

4. The method according to claim 1, characterized in that, The method further includes: Adjust the parking lines of the parking space to be rendered according to the parking space type.

5. The method according to claim 4, characterized in that, The parking space type includes at least one of the following: Perpendicular parking spaces, horizontal parking spaces, and angled parking spaces.

6. The method according to any one of claims 1 to 5, characterized in that, The clustering conditions include one of the following: Parking space orientation, parking space type, spacing between parking space dividing lines, spacing between parking space entrance lines, and slope of parking space entrance lines; The status characteristics of the parking space include one of the following: Parking space orientation, parking space type, spacing between parking space dividing lines, spacing between parking space entrance lines, and slope of parking space entrance lines.

7. The method according to claim 6, characterized in that, The method further includes: Based on at least one of the clustering conditions, namely the parking space orientation, the parking space type, the parking space dividing line spacing, and the parking space entrance line spacing, the parking spaces to be rendered are clustered at least once to obtain at least one parking space group.

8. The method according to claim 6, characterized in that, The process of clustering the parking spaces to be rendered based on at least two clustering conditions includes: Based on the parking space orientation, at least one first parking space group is obtained; wherein, the parking spaces in a first parking space group have the same orientation. Within a first parking space group, at least one second parking space group is obtained based on the parking space type; wherein, within a second parking space group, two adjacent parking spaces have the same parking space type.

9. The method according to claim 8, characterized in that, The method further includes: Within a second parking space group, at least one third parking space group is obtained based on the spacing of the parking space dividing lines; In one of the third parking space groups, the spacing between the parking space dividing lines of adjacent parking spaces is less than or equal to a first spacing threshold.

10. The method according to claim 9, characterized in that, The method further includes: Within one of the third parking space groups, at least one parking space group is obtained based on the parking space entrance line spacing. Within one of the parking space groups, the distance between the entrance lines of adjacent parking spaces is less than or equal to a second distance threshold.

11. The method according to claim 7 or 10, characterized in that, The method further includes: Adjust the parking line layout of parking spaces within the same parking space group to make the parking line layout of parking spaces within the same parking space group consistent.

12. The method according to claim 11, characterized in that, The adjustment of the parking space layout within the same parking space group includes: Based on the weighted parking space line layout of the parking space group, the parking space line layout of parking spaces within the same parking space group is adjusted.

13. The method according to claim 12, characterized in that, The parking space layout includes at least one of the following: Parking space orientation and layout, length of parking space dividing lines, length of parking space entrance lines.

14. The method according to claim 12, characterized in that, The weighted parking line layout of the parking space group is determined by weighting the parking line layout of parking spaces within the same parking space group.

15. The method according to any one of claims 12 to 14, characterized in that, The method further includes: The first weight of a parking space is determined based on the distance between the vehicle and the parking space within the same parking space group. The weighted parking line layout of the parking space group is determined based on the first weight of the parking space.

16. The method according to claim 15, characterized in that, The step of determining the first weight of a parking space based on the distance between the vehicle and the parking space within the same parking space group includes: Determine a first extreme value and a second extreme value among the distances between the vehicle and all parking spaces in the parking space group; The first weight of the parking space is determined based on the first extreme distance value, the second extreme distance value, and the actual distance between the vehicle and the current parking space.

17. The method according to any one of claims 7, 10 to 16, characterized in that, The method further includes: Based on the slope of the parking space entrance line of the parking space to be rendered, the parking spaces in at least one parking space group are clustered to obtain at least one large parking space group. Within one of the parking space groups, the slope of the parking space entrance line for all parking spaces falls within the same range.

18. The method according to claim 17, characterized in that, The method further includes: adjusting the entrance line data of parking spaces within the same parking space group to make the slope of the entrance lines of parking spaces within the same parking space group consistent.

19. The method according to claim 18, characterized in that, The adjustment of the entrance line data for parking spaces within the same parking space group includes: The slopes of the entrance lines of parking spaces within the same parking space group are weighted to obtain the inter-group entrance line slopes of the parking space group. Based on the slope of the entrance line between the parking spaces in the same parking space group, the slope of the entrance line of the parking space within the same parking space group is adjusted.

20. The method according to claim 19, characterized in that, The method further includes: The second weight of the parking space is determined based on the distance between the vehicle and the parking space within the same parking space group. The slope of the entrance line between the parking spaces in the large group is determined based on the second weight of the parking spaces.

21. The method according to claim 1, characterized in that, When the group of parking spaces comprises at least two, the method further includes: Adjust the entrance line data of the parking spaces within each parking space group to ensure that the parking space groups satisfy the constraint relationship.

22. The method according to claim 21, characterized in that, The step of adjusting the entrance line data of parking spaces within each parking space group to ensure that the parking space groups satisfy the constraint relationship includes: Adjust the slope of the entrance line of the parking spaces within each parking space group so that the slope of the entrance line of the parking spaces within each parking space group satisfies the constraint relationship between the parking space groups.

23. The method according to claim 21, characterized in that, The constraints between the parking space groups include: The angle between the entrance line of any parking space in a parking space group and the entrance line of any parking space in another parking space group is greater than a preset angle threshold.

24. The method according to claim 23, characterized in that, The constraints between the parking space groups include: The entrance line of any parking space in a parking space group is perpendicular to the entrance lines of parking spaces in other parking space groups.

25. The method according to any one of claims 1 to 24, characterized in that, The method further includes: If there is only one parking space to be rendered, then render that parking space.

26. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the parking space rendering method according to any one of claims 1 to 25.

27. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the parking space rendering method according to any one of claims 1 to 25.

28. A computer program product, characterized in that, Includes a computer program or instructions that, when executed by a processor, implement the steps of the parking space rendering method as described in any one of claims 1 to 25.

29. A vehicle, characterized in that, Including the electronic device as described in claim 26.

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