Parking space generation method and device, storage medium and electronic equipment

Abstract

The invention discloses a parking space generation method and device, a storage medium and electronic equipment, and relates to the technical field of parking space planning. The parking space generation method comprises the following steps: acquiring a parking boundary line; executing a first layer of iteration, wherein the first layer of iteration is used for searching an iteration point along the parking boundary line according to a first iteration step length; under the condition that a first iteration point of the first-layer iteration search does not meet a preset parking space generation condition, second-layer iteration is executed, and the second-layer iteration is used for searching iteration points along the parking boundary line according to a second iteration step length by taking the first iteration point as a starting point; generating a parking space corresponding to a second iteration point under the condition that the second iteration point of the second layer of iteration search meets a preset parking space generation condition; wherein the first iteration step length is greater than the second iteration step length. Therefore, the parking space planning is more reasonable, the optimal configuration of resources can be realized, and the unmanned scene operation requirement can be met.

Description

Technical Field

[0001] This application relates to the technical field of parking space planning, and specifically to a parking space generation method, a parking space generation device, a machine-readable storage medium, and an electronic device. Background Art

[0002] In various operation scenarios, reasonable parking space planning is a key link to ensure the smooth operation of the operation process, improve work efficiency, and ensure the safety of personnel and vehicles.

[0003] For example: unmanned mines are becoming a major development trend in the mining industry. Unmanned operation can effectively improve production efficiency, reduce operating costs for enterprises, and significantly enhance the economic benefits of mining enterprises. With the further development of technology and the gradual reduction of costs, it is expected that more mines will join the ranks of unmanned operation in the future. The waste dump is a place for stacking waste soil, waste rock, or other ore materials generated during the mining process. The automatic generation and management technology of the unloading parking spaces in the waste dump, as an important part of unmanned mines, has a significant impact on the overall operation efficiency of mine operations, such as reducing vehicle congestion in the waste dump, reducing waiting time, ensuring operation continuity, and improving the passing efficiency of transport vehicles. At the same time, a good parking space design can reduce the risk of accidents, such as avoiding vehicle collisions or overturns, and enhancing operation safety.

[0004] Currently, parking space planning still mainly relies on manual decision-making. Relying on the experience of engineers, it is planned through on-site measurement and historical data, or CAD is used for visual design of parking space layout to plan the parking space position and lane width. These methods are difficult to meet the requirements of optimal resource allocation. Summary of the Invention

[0005] The purpose of the embodiments of this application is to provide a parking space generation method, a parking space generation device, a machine-readable storage medium, and an electronic device to solve the technical problem that it is difficult to meet the requirements of optimal resource allocation in the prior art.

[0006] To achieve the above purpose, the first aspect of this application provides a parking space generation method, including:

[0007] Obtain the parking boundary line;

[0008] Execute the first-layer iteration, where the first-layer iteration is used to search for iteration points along the parking boundary line according to the first iteration step size;

[0009] In the case where the first iteration point searched in the first-layer iteration does not meet the preset parking space generation conditions, execute the second-layer iteration, where the second-layer iteration is used to use the first iteration point as the starting point and search for iteration points along the parking boundary line according to the second iteration step size;

[0010] When the second iteration point in the second-layer iterative search meets the preset parking space generation condition, generate the parking space corresponding to the second iteration point;

[0011] Wherein, the first iteration step size is greater than the second iteration step size.

[0012] In the embodiment of the present application, the method further includes:

[0013] When the second iteration point in the second-layer iterative search meets the preset parking space generation condition, starting from the second iteration point, jump to execute the first-layer iteration.

[0014] In the embodiment of the present application, after executing the second-layer iteration, the method further includes:

[0015] When the second iteration point in the second-layer iterative search does not meet the preset parking space generation condition, and the search distance of the second-layer iteration is greater than or equal to the first iteration step size, starting from the second iteration point, jump to execute the first-layer iteration; the search distance of the second-layer iteration is positively correlated with the number of iterations of the second-layer iteration.

[0016] In the embodiment of the present application, after executing the first-layer iteration, the method further includes:

[0017] When the first iteration point in the first-layer iterative search meets the preset parking space generation condition, generate the parking space corresponding to the first iteration point.

[0018] In the embodiment of the present application, the preset parking space generation condition includes: the minimum distance condition between parking spaces, the non-crossing condition of parking spaces, and the parking space orientation angle condition.

[0019] In the embodiment of the present application, after executing the first-layer iteration, it further includes:

[0020] Within a preset range of rotation angles, determine the initial orientation angle;

[0021] Iterate the orientation angle according to a preset rotation iteration step size, and generate parking spaces corresponding to each orientation angle at the first iteration point in the first-layer iterative search;

[0022] Judge whether there is a parking space that meets the preset parking space generation condition among the parking spaces corresponding to each orientation angle;

[0023] When it is determined that there is a parking space that meets the preset parking space generation condition among the parking spaces corresponding to each orientation angle, determine that the first iteration point in the first-layer iterative search meets the preset parking space generation condition.

[0024] In the embodiment of the present application, it further includes:

[0025] Optimize the layout of the parking spaces to obtain an optimized set of parking spaces.

[0026] In an embodiment of the present application, the optimizing the layout of the parking spaces to obtain an optimized set of parking spaces includes:

[0027] Obtain a parking space optimization target, where the parking space optimization target includes: the number of generated parking spaces, the uniformity index of the generated parking spaces, and the penalty value generated by the intersection and overlap of the generated parking spaces with the boundary;

[0028] Based on the parking space optimization target and the preset constraint conditions of the parking space generation parameters, optimize the parking space generation parameters to obtain optimized parking space generation parameters, where the parking space generation parameters include the first iteration step, the second iteration step, the rotation iteration step, and the parking space interval corresponding to the parking space;

[0029] Based on the optimized parking space generation parameters, adjust the layout of the parking spaces to obtain an optimized set of parking spaces.

[0030] In an embodiment of the present application, it further includes:

[0031] Obtain the current parking boundary line in real time;

[0032] Based on the difference between the current parking boundary line and the ideal parking boundary line, determine the current parking space generation parameters, where the current parking space generation parameters include: the first iteration step, the second iteration step, the rotation iteration step, and the parking space interval corresponding to the current parking boundary line;

[0033] Based on the current parking space generation parameters, generate a real-time set of parking spaces.

[0034] A second aspect of the present application provides a parking space generation device, including:

[0035] An acquisition module for acquiring a parking boundary line;

[0036] A first iteration module for performing a first layer of iteration, where the first layer of iteration is used to search for iteration points along the parking boundary line according to the first iteration step;

[0037] A second iteration module for performing a second layer of iteration when the first iteration point searched in the first layer of iteration does not meet the preset parking space generation conditions, where the second layer of iteration is used to start from the first iteration point and search for iteration points along the parking boundary line according to the second iteration step;

[0038] A parking space generation module for generating a parking space corresponding to the second iteration point when the second iteration point searched in the second layer of iteration meets the preset parking space generation conditions; where the first iteration step is greater than the second iteration step.

[0039] In a third aspect of the present application, an electronic device is provided, which includes:

[0040] At least one processor;

[0041] A memory connected to the at least one processor;

[0042] Wherein, the memory stores instructions executable by the at least one processor, and the at least one processor implements the above-mentioned parking space generation method by executing the instructions stored in the memory.

[0043] In a fourth aspect of the present application, a machine-readable storage medium is provided, on which instructions are stored, and when the instructions are executed by a processor, the processor is configured to execute the above-mentioned parking space generation method.

[0044] Through the above technical solution, by obtaining the parking boundary line; searching for iteration points along the parking boundary line according to the first iteration step size; in the case that the first iteration point in the first-layer iteration search does not meet the preset parking space generation condition, using the first iteration point as a starting point, searching for iteration points along the parking boundary line according to the second iteration step size; in the case that the second iteration point in the second-layer iteration search meets the preset parking space generation condition, generating the parking space corresponding to the second iteration point; wherein, the first iteration step size is greater than the second iteration step size. It is realized to search for the parking space generation position on the parking boundary line by combining the step sizes of "large + small". When encountering obstacles during the large-step search, the small-step size is used to continue the search, which can increase the possibility of finding the parking space generation position, help avoid obstacles and select a suitable parking space generation position to generate a parking space, make the parking space planning more reasonable, and further help to achieve the optimal allocation of resources. This method can automatically generate parking spaces without relying on manual decision-making, and can meet the operation requirements of unmanned scenarios. By iteratively searching for the parking space generation position along the parking boundary line, even for a parking lot with a complex geometric shape, the automatic generation of parking spaces can be realized. The principle of using a double-layer iterative step size search is simple, and the implementation process does not require too many complex algorithms and data structures, and the calculation is simple and convenient.

[0045] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation part. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification, and are used to explain the embodiments of the present application together with the following specific implementation manners, but do not constitute a limitation to the embodiments of the present application. In the drawings:

[0047] Figure 1 Schematically shows a flowchart of a parking space generation method according to an embodiment of the present application;

[0048] Figure 2 Schematically shows a flowchart of a parking space generation determination method according to an embodiment of the present application;

[0049] Figure 3 Schematically shows a comparison diagram of double-layer iteration step size and fixed iteration step size according to an embodiment of the present application;

[0050] Figure 4 Schematically shows a flowchart of a parking space calculation method based on a double-layer iteration step size according to an embodiment of the present application;

[0051] Figure 5 Schematically shows an optimization flowchart of a heuristic parameter optimizer according to an embodiment of the present application;

[0052] Figure 6 Schematically shows a flowchart of a real-time dynamic update method of a parking space according to an embodiment of the present application;

[0053] Figure 7 Schematically shows a structural schematic diagram of a parking space generation device according to an embodiment of the present application;

[0054] Figure 8 Schematically shows an internal structure diagram of a computer device according to an embodiment of the present application.

[0055] Description of reference numerals

[0056] 410 - Acquisition module; 420 - First iteration module; 430 - Second iteration module; 440 - Parking space generation module; A01 - Processor; A02 - Network interface; A03 - Internal memory; A04 - Display screen; A05 - Input device; A06 - Non-volatile storage medium; B01 - Operating system; B02 - Computer program. Detailed implementation manners

[0057] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It should be understood that the specific implementation manners described herein are only for explaining and illustrating the embodiments of the present application, and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0058] It should be noted that in the technical solution of this application, the acquisition, transmission, storage, use, processing, etc. of data all comply with the relevant provisions of national laws and regulations. In the embodiments of this application, some existing solutions in the industry such as certain software, components, models, etc. may be mentioned. They should be regarded as exemplary. The purpose is only to illustrate the feasibility in the implementation of the technical solution of this application, but it does not mean that the applicant has already or necessarily used this solution.

[0059] It should be noted that if there are directional indications (such as up, down, left, right, front, back...) involved in the embodiments of this application, then such directional indications are only used to explain the relative positional relationship, movement conditions, etc. between components in a certain specific posture (as shown in the drawings). If this specific posture changes, then the directional indications will also change accordingly.

[0060] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of this application, then such descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0061] Figure 1 A flowchart of a parking space generation method according to an embodiment of this application is schematically shown. As Figure 1 shown, the embodiments of this application provide a parking space generation method. By using a step size combination of "large + small" to search for parking space generation positions along the parking boundary line, when an obstacle is encountered during the large step size search, a small step size can be used to continue the search to determine the parking space generation position, so as to avoid obstacles, select a suitable parking space generation position to generate a parking space, making the parking space planning more reasonable and contributing to the optimal allocation of resources. This method can automatically generate parking spaces without relying on manual decision-making and can meet the operation requirements of unmanned scenarios.

[0062] It should be noted that for the convenience of explaining the solution, in this embodiment, the scenario of discharging soil in an unmanned mine waste dump is mainly used as an example for explanation. In the scenario of discharging soil in an unmanned mine waste dump, the parking boundary line refers to the boundary line of the waste dump retaining wall.

[0063] The embodiments of this application provide a parking space generation method, and this method may include the following steps:

[0064] Step 210: Obtain the parking boundary line;

[0065] Step 220: Perform the first - layer iteration, where the first - layer iteration is used to search for iteration points along the parking boundary line according to the first iteration step size;

[0066] Step 230: In the case that the first iteration point searched in the first - layer iteration does not meet the preset parking - space generation condition, perform the second - layer iteration, where the second - layer iteration is used to start from the first iteration point and search for iteration points along the parking boundary line according to the second iteration step size;

[0067] Step 240: In the case that the second iteration point searched in the second - layer iteration meets the preset parking - space generation condition, generate the parking space corresponding to the second iteration point; where the first iteration step size is greater than the second iteration step size.

[0068] Through the above - mentioned technical solution, by obtaining the parking boundary line; searching for iteration points along the parking boundary line according to the first iteration step size; in the case that the first iteration point searched in the first - layer iteration does not meet the preset parking - space generation condition, starting from the first iteration point and searching for iteration points along the parking boundary line according to the second iteration step size; in the case that the second iteration point searched in the second - layer iteration meets the preset parking - space generation condition, generating the parking space corresponding to the second iteration point; where the first iteration step size is greater than the second iteration step size. An adaptive iteration method with variable step sizes is adopted for searching the parking - space generation position along the parking boundary line. When the first iteration point searched in the first - layer iteration does not meet the preset parking - space generation condition, continue to search for iteration points along the parking boundary line according to the second iteration step size, so as to realize the search for the parking - space generation position along the parking boundary line with a step - size combination of "large + small". When an obstacle is encountered during the large - step - size search, the small step size is used to continue the search, which can increase the possibility of finding the parking - space generation position, help avoid obstacles and select a suitable parking - space generation position to generate a parking space, making the parking - space planning more reasonable, and further contributing to the realization of optimal resource allocation. This method can automatically generate parking spaces without relying on manual decision - making, and can meet the operation requirements of unmanned scenarios. By iteratively searching for the parking - space generation position along the parking boundary line, even for a parking lot with a complex geometric shape, the automatic generation of parking spaces can be achieved.

[0069] The principle of using a double - layer iteration step - size search is simple, and the implementation process does not require too many complex algorithms and data structures, and the calculation is simple and convenient.

[0070] In the above step 210, the above parking boundary line can be determined according to the actual scenario. For example, taking the dumping of waste rock in an unmanned mine dump as an example, the above parking boundary line is the boundary line of the dump retaining wall. The acquisition of the parking boundary line can be obtained by automatically extracting the visual perception three-dimensional point cloud data, or can be obtained based on map data. For example, it can be through sensors mounted on specific devices (such as intelligent parking cameras, vehicle-mounted lidar, etc.) to collect the environmental information of the parking lot and its surrounding areas, and convert it into a large amount of three-dimensional point cloud data. Subsequently, the three-dimensional point cloud data is deeply processed and analyzed to identify and screen out the point cloud features related to the parking boundary line, and accurately separate them from numerous environmental information, thereby realizing the automatic extraction of the parking boundary line. The above deep processing and analysis of the three-dimensional point cloud data can be achieved by using existing technologies and will not be elaborated here.

[0071] In step 220, the above first iteration step size can be preset according to the actual situation. The first layer of iteration means to perform cyclic iteration along the parking boundary line with the first iteration step size to search for iteration points. Specifically, a starting point and an ending point can be set on the parking boundary line first, and then starting from the starting point, adding the first iteration step size to obtain the first iteration point of the first layer of iteration search, and then taking the first iteration point of the first layer of iteration search as the current iteration point and adding the first iteration step size to obtain the next first iteration point of the first layer of iteration search, and so on in a cycle until the position of the current iteration point exceeds the ending point position.

[0072] Step 230: In the case where the first iteration point obtained from the first layer of iteration search does not meet the preset parking space generation conditions, perform the second layer of iteration, and the second layer of iteration is used to search for iteration points along the parking boundary line with the first iteration point as the starting point and according to the second iteration step size;

[0073] In this embodiment, the above preset parking space generation conditions can be preset, where the preset parking space generation conditions can include: the minimum distance condition between parking spaces, the non-crossing condition of parking spaces, the parking space orientation angle condition, etc. Among them, the minimum distance condition between parking spaces means that the closest distance between the generated parking spaces is not less than the set minimum interval; the non-crossing condition of parking spaces means that the generated parking spaces cannot cross the obstacles on the boundary, and the obstacles on the boundary are all the non-occupiable spaces on the boundary when generating parking spaces; the parking space orientation angle condition means that the included angle between the generated parking space and the boundary must be within the allowable range. By setting the minimum distance condition between parking spaces, the non-crossing condition of parking spaces, and the parking space orientation angle condition as the parking space generation conditions, it is helpful to generate parking spaces that meet the requirements.

[0074] When performing the first - layer iteration, after each iteration, it can be determined whether the first iteration point searched satisfies the preset parking - space generation condition. If the first iteration point searched in the first - layer iteration does not satisfy the preset parking - space generation condition, the iteration point can be continuously searched with a smaller iteration step, that is, the second - layer iteration is performed.

[0075] In some embodiments, before determining whether the first iteration point searched satisfies the preset parking - space generation condition after each iteration, it can also be to first determine whether the position of the first iteration point searched in the current first - layer iteration exceeds the end - point position. When it is determined that the position of the first iteration point searched in the current first - layer iteration does not exceed the end - point position, then it is determined whether the first iteration point searched satisfies the preset parking - space generation condition; otherwise, it ends. By first determining whether the position of the first iteration point searched in the current first - layer iteration exceeds the end - point position, invalid calculations can be avoided and the reliability of the iteration - point search can be improved.

[0076] In some embodiments, determining whether the first iteration point searched satisfies the preset parking - space generation condition can be to determine whether a parking space can be generated at the first iteration point. Specifically, after performing the first - layer iteration, the following steps are further included:

[0077] First, within a preset range of rotation angles, an initial orientation angle is determined;

[0078] In this embodiment, the preset range of rotation angles can be set in advance according to the actual scenario. For example, by setting the rotation - angle range [α1, α2], α1 can be used as the initial orientation angle. The orientation angle is used to determine the orientation of the parking space.

[0079] Then, the orientation angle is iterated according to a preset rotation - iteration step, and parking spaces corresponding to each orientation angle are generated at the first iteration point searched in the first - layer iteration;

[0080] In this embodiment, the preset rotation - iteration step can be set in advance according to the actual situation. The above - mentioned iteration means that the orientation angle obtained in each iteration is the previous orientation angle plus the rotation - iteration step. After determining the orientation angle, a parking space can be generated at the first iteration point searched in the first - layer iteration according to the orientation angle. The above - mentioned process of generating a parking space can be realized by using the existing technology and will not be elaborated here.

[0081] Then, it is determined whether there is a parking space that satisfies the preset parking - space generation condition among the parking spaces corresponding to each orientation angle;

[0082] Finally, when it is determined that there is a parking space that satisfies the preset parking - space generation condition among the parking spaces corresponding to each orientation angle, it is determined that the first iteration point searched in the first - layer iteration satisfies the preset parking - space generation condition.

[0083] In this embodiment, the above-mentioned first iteration point in the search can generate parking spaces with multiple orientation angles. As long as at least one of these parking spaces meets the parking space generation condition, it indicates that the first iteration point meets the preset parking space generation condition; otherwise, it indicates that the first iteration point in the first-layer iterative search does not meet the preset parking space generation condition. During the above determination process, it can be to judge whether the parking space meets the parking space generation condition after generating the parking space corresponding to the orientation angle in each iteration in sequence; or it can be to judge whether each parking space meets the parking space generation condition after generating the parking spaces corresponding to all orientation angles.

[0084] For example, please refer to Figure 2 , Figure 2 which schematically shows a flowchart of a parking space generation determination method according to an embodiment of the present application. Taking the waste dump boundary point P as an example, set the rotation angle range [α1, α2], the rotation iteration step size S3, and the iteration number t3 = 0; after each iteration, at the boundary point P, generate a parking space Pa with the orientation angle: θ = α1 + t3 × S3, and t3 = t3 + 1. If Pa meets the parking space generation condition, the parking space generation is successful and the parking space Pa is output; if Pa does not meet the condition, check whether it holds. When it holds, transfer to execute generating a parking space Pa with the orientation angle: θ = α1 + t3 × S3 at the boundary point P, and t3 = t3 + 1; if it does not hold, the parking space generation fails, indicating that the first iteration point in the first-layer iterative search does not meet the preset parking space generation condition.

[0085] By iteratively searching for the orientation angle according to the preset rotation iteration step size and generating the parking spaces corresponding to each orientation angle at the first iteration point in the first-layer iterative search; by judging whether there is a parking space that meets the preset parking space generation condition among the parking spaces corresponding to each orientation angle, it is possible to more accurately determine whether the first iteration point in the first-layer iterative search meets the preset parking space generation condition.

[0086] In some embodiments, after performing the first-layer iteration, the method further includes: generating the parking space corresponding to the first iteration point when the first iteration point in the first-layer iterative search meets the preset parking space generation condition.

[0087] In this embodiment, if the first iteration point in the first-layer iterative search meets the preset parking space generation condition, it indicates that there is no obstacle at the first iteration point in the first-layer iterative search and a parking space can be generated. Then, at the parking space corresponding to the first iteration point, more parking spaces can be generated, which further helps to achieve the optimal allocation of resources.

[0088] In step 230, when performing the second-layer iteration, the process of the second-layer iteration is the same as that of the first-layer iteration. The difference is that: the second-layer iteration uses the currently searched first iteration point as the starting point and continues to perform cyclic iteration along the parking boundary line with the second iteration step length to search for iteration points. For example, if there is an obstacle at the currently searched first iteration point A and it does not meet the parking space generation condition, then continue to use the first iteration point A as the starting point and continue to search for iteration points along the parking boundary line according to the second iteration step length. The above second iteration step length can be preset as needed, or the specific relationship with the first iteration step length can be preset and then calculated. This embodiment does not make a limitation. For example, if the second iteration step length is set to half of the first iteration step length and the first iteration step length is 10, then the second iteration step length can be calculated to be 5.

[0089] It should be noted that the number of the above first step length and second step length can both be multiple, so as to form a mixed combination of multiple step lengths. When performing the first-layer iteration or the second-layer iteration, the iteration points can be searched along the parking boundary line in the order of the step length from large to small. Specifically, first search for iteration points according to the largest step length. In the case that the searched iteration point does not meet the preset parking space generation condition, switch to the next step length and continue to search for iteration points along the parking boundary line.

[0090] For example, the first step length is 10, and the second step lengths include 8 and 5. In specific implementation, first search for iteration points according to the iteration step length of 10. The searched iteration point B does not meet the preset parking space generation condition, then perform the second-layer iteration, that is, first use the iteration point B as the starting point and continue to search for iteration points along the parking boundary line according to the iteration step length of 8. The searched iteration point C does not meet the preset parking space generation condition, then continue to search for iteration points along the parking boundary line according to the iteration step length of 5.

[0091] Step 240: When the second iteration point searched in the second-layer iteration meets the preset parking space generation condition, generate the parking space corresponding to the second iteration point;

[0092] In this embodiment, it can be judged whether the second iteration point searched in the second-layer iteration meets the preset parking space generation condition. The above judgment process can be the same as the process of judging whether the searched first iteration point meets the preset parking space generation condition in step 230, and will not be elaborated here. If the second iteration point searched in the second-layer iteration meets the preset parking space generation condition, it means that this second iteration point can be the parking space generation position, and then the parking space can be generated. If the second iteration point searched in the second-layer iteration does not meet the preset parking space generation condition, it means that this second iteration point cannot generate the parking space.

[0093] In some embodiments, the method further includes: when the second iteration point of the second-layer iterative search satisfies a preset parking space generation condition, starting from the second iteration point, jumping to execute the first-layer iteration.

[0094] In this embodiment, if the second iteration point of the second-layer iterative search satisfies the preset parking space generation condition, it is also possible to continue starting from the second iteration point and iterating the iteration point along the parking boundary line according to the first iteration step length, that is, executing the first-layer iteration. In this way, multi-layer step-by-step iteration can be performed along the parking boundary line, making the parking space planning more reasonable and further helping to achieve the optimal allocation of resources.

[0095] To more intuitively illustrate the advantages of this solution, please refer to Figure 3 , Figure 3 which schematically shows a comparison diagram of the double-layer iteration step length and the fixed iteration step length according to an embodiment of the present application. The following Figure 3 is a comparison between the double-layer step length based on the "large + small" step length combination and the fixed step length iteration. Among them, red indicates the area where parking spaces cannot be generated, including but not limited to occupied parking spaces and obstacles, blue indicates the parking spaces generated by iteration at a fixed D spacing, green boxes: indicate the parking spaces generated by iteration at a fixed 2D spacing, and yellow boxes indicate the parking spaces generated by double-layer step length iteration using the D + d combination. It can be Figure 3 seen that more parking spaces (i.e., yellow boxes) are generated by double-layer step length iteration using the D + d combination, and the parking space planning is more reasonable. The parking spaces planned in this way can better meet the requirements of optimal resource allocation.

[0096] In some embodiments, after executing the second-layer iteration, the method further includes:

[0097] when the second iteration point of the second-layer iterative search does not satisfy the preset parking space generation condition and the search distance of the second-layer iteration is greater than or equal to the first iteration step length, starting from the second iteration point, jumping to execute the first-layer iteration; the search distance of the second-layer iteration is positively correlated with the number of iterations of the second-layer iteration.

[0098] In this embodiment, when the second iteration point of the second-layer iteration search does not meet the preset parking space generation condition, it can be further determined whether the search distance of the second-layer iteration is greater than or equal to the first iteration step length. If the search distance of the second-layer iteration is greater than or equal to the first iteration step length, the second-layer iteration can be terminated, and starting from the second iteration point, the first-layer iteration can be continued. If the search distance of the second-layer iteration is less than the first iteration step length, the next second-layer iteration search can be continued. The above search distance of the second-layer iteration can be obtained by calculating the product of the iteration times of the second-layer iteration and the second iteration step length. Further, the determination of whether the search distance of the second-layer iteration is greater than or equal to the first iteration step length can be converted into a determination of whether the iteration times of the second-layer iteration is greater than or equal to the ratio of the first iteration step length to the second iteration step length.

[0099] By jumping to execute the first-layer iteration starting from the second iteration point when the search distance of the second-layer iteration is greater than or equal to the first iteration step length, a double-layer stepwise iteration is realized. Through a regular stepwise method, the iteration points are searched more systematically, improving the accuracy and efficiency of the search.

[0100] Taking the parking space planning of a mine waste dump as an example below, the solution will be specifically described. Please refer to Figure 4 , Figure 4 which schematically shows a flowchart of a parking space calculation method based on a double-layer iteration step length according to an embodiment of the present application.

[0101] Taking the starting point P1 and the ending point P2 of the iteration as an example, the specific steps of the parking space calculation method using the double-layer stepwise iteration are as follows:

[0102] Step 1: Set the large iteration step length as S1 (corresponding to the first iteration step length), the small iteration step length as S2 (corresponding to the second iteration step length), the iteration times t1 = 0, and at the same time P = P1;

[0103] Step 2: Starting from P, perform iteration with S1 as the step length, and the iteration point P = P + S1. If P > P2, go to Step 6;

[0104] Step 3: Check whether the P position meets the parking space generation condition: If it meets, then t1 = t1 + 1 and go to Step 2; if it does not meet, then t2 = 1 and go to Step 4;

[0105] Step 4: Starting from P, perform iteration with S2 as the step length, P = P + S2. If P > P2, go to Step 6;

[0106] Step 5: Check whether the P position meets the parking space generation conditions. If it does, go to Step 2. If not, then t2 = t2 + 1, and determine whether t2 < S1 / S2 holds. If it holds, go to Step 4. If it does not hold, then t1 = t1 + 1 and go to Step 2;

[0107] Step 6: Output all parking spaces that meet the parking space generation conditions.

[0108] In some embodiments, the generated parking spaces can be further optimized, that is, the method further includes optimizing the layout of the parking spaces to obtain an optimized set of parking spaces.

[0109] In this embodiment, the above-mentioned parking spaces include the parking spaces corresponding to each second iteration point, the parking spaces corresponding to each first iteration point, etc., which can be specifically determined according to the actual situation. The above optimization can be to optimize parameters such as the large iteration step length, small iteration step length, rotation iteration step length, and parking space spacing corresponding to the parking spaces to achieve the optimization of the parking space layout. The above optimization methods include: optimizing based on the NSGA-II algorithm, similar to optimizing parameters based on algorithms such as heuristic algorithms, deep learning, and reinforcement learning. By optimizing the parking spaces, it is convenient to obtain more parking spaces that meet the requirements and make the distribution of the parking spaces more reasonable.

[0110] In some embodiments, the optimizing the layout of the parking spaces to obtain an optimized set of parking spaces includes:

[0111] The first step is to obtain the parking space optimization objectives, and the parking space optimization objectives include: the number of generated parking spaces, the uniformity index of the generated parking spaces, and the penalty value generated by the intersection and overlap of the generated parking spaces with the boundary;

[0112] In this embodiment, the above parking space optimization objectives can be preset according to the actual scenario. For example, the parking space optimization objectives can be set as: f1 = -N Pa , f2 = U Pa , f3 = Penalty Pa ; the parking space optimization objective is a weighted objective, where N Pa is the number of generated parking spaces; U Pa is the uniformity index of the generated parking spaces; Penalty Pa is the penalty value generated by the intersection and overlap of the generated parking spaces with the boundary.

[0113] The second step is to optimize the parking space generation parameters based on the parking space optimization objectives and the preset parking space generation parameter constraint conditions to obtain optimized parking space generation parameters. The parking space generation parameters include the first iteration step length, second iteration step length, rotation iteration step length, and parking space spacing corresponding to the parking spaces;

[0114] In this embodiment, the parking space generation parameters are used to determine the layout of the parking spaces. Specifically, they can be determined according to the actual situation and at least include the first iteration step length, the second iteration step length, the rotation iteration step length, and the parking space interval corresponding to the parking spaces. Accordingly, corresponding constraints for the parking space generation parameters can be set. The constraints for the parking space generation parameters are used to constrain the parking space generation parameters so that the optimized parking space generation parameters meet the requirements. The preset constraints for the parking space generation parameters can be set in advance according to the actual scenario and include, but are not limited to:

[0115] S1 > W + L, that is, the first iteration step length S1 must be greater than the sum of the parking space width W and the parking space interval L;

[0116] S2 < S1, that is, the second iteration step length S2 must be less than the first iteration step length S1;

[0117] S3 < α2 - α1, that is, the rotation iteration step length S3 must be less than the allowable included angle range [α2 - α1] between the parking space and the boundary;

[0118] L > L min , that is, the parking space interval L must be greater than the minimum interval condition L min .

[0119] The above optimization can take the parking space optimization objective as the optimization objective and the constraints for the parking space generation parameters as the constraints to optimize the parking space generation parameters. Specifically, it can be obtained by using a parameter optimizer for optimization.

[0120] The third step is to adjust the layout of the parking spaces based on the optimized parking space generation parameters to obtain an optimized set of parking spaces.

[0121] In this embodiment, after obtaining the optimized parking space generation parameters, updating the parking space generation parameters of the parking spaces can adjust the parking space layout to obtain an optimized set of parking spaces.

[0122] By setting the parking space optimization objective, which includes: the number of generated parking spaces, the uniformity index of the generated parking spaces, and the penalty value generated by the intersection and overlap of the generated parking spaces with the boundary; combined with the preset constraints for the parking space generation parameters, optimizing the parking space generation parameters can comprehensively consider various actual factors, so that the generated parking spaces not only achieve the best in terms of quantity, uniformity, and avoiding intersection and overlap, but also meet the requirements, thus making the optimized set of parking space generation schemes more feasible and practical.

[0123] Please refer to Figure 5 , Figure 5 , which schematically shows the optimization flowchart of the heuristic parameter optimizer according to the embodiment of the present application. Taking the starting point P1 and the ending point P2 of the waste dump boundary as an example and taking the heuristic parameter optimizer based on NSGA-II as an example, the above optimization process includes:

[0124] Step 1: Set algorithm parameters: population size N pop , maximum number of iterations max_gen, crossover probability P cross , mutation probability P mutation , gen = 0;

[0125] Step 2: Initialize the population pop and calculate the optimization objectives f1, f2, f3, perform fast non-dominated sorting and calculate the crowding degree;

[0126] Step 3: Determine whether gen < max_gen holds. If it holds, update the population pop using the NSGA-II algorithm. Otherwise, go to Step 4; The above update of the population pop means generating the population pop and the objective evaluation functions of all individuals in pop, that is, the optimization objectives f1, f2, f3; Then generate pop1 using the NSGA-II algorithm, and pop = pop1.

[0127] Step 4: Output the set of all parking space generation schemes corresponding to pop.

[0128] In some embodiments, for the scenario where the parking boundary line is constantly changing, the parking spaces can also be updated in real time. The method includes:

[0129] First, obtain the current parking boundary line in real time;

[0130] In this embodiment, the current parking boundary line can be automatically extracted from the real-time visual perception three-dimensional point cloud data, or obtained based on the real-time map data.

[0131] Then, based on the difference between the current parking boundary line and the ideal parking boundary line, determine the current parking space generation parameters. The current parking space generation parameters include: the first iteration step size, the second iteration step size, the rotation iteration step size, and the parking space interval corresponding to the current parking boundary line;

[0132] In this embodiment, the ideal parking boundary line can refer to the final parking boundary line. The difference between the current parking boundary line and the ideal parking boundary line can refer to the deviation degree of each point on the current parking boundary line from the ideal parking boundary line, which can be obtained by calculating the position difference. Different parking space generation parameters corresponding to different differences can be preset, and the corresponding parking space generation parameters can be matched according to the difference between the current parking boundary line and the ideal parking boundary line to obtain the current parking space generation parameters. It can also be predicted by a machine learning algorithm.

[0133] Finally, generate a real-time parking space set based on the current parking space generation parameters.

[0134] In this embodiment, after obtaining the current parking space generation parameters, parking spaces can be generated based on the current parking space generation parameters according to the above-mentioned parking space generation method.

[0135] By determining the current parking space generation parameters based on the difference between the current parking boundary line and the ideal parking boundary line, a real-time parking space set can be generated according to the current parking space generation parameters. By dynamically generating the parking space generation parameters according to the current parking boundary line, the real-time automatic generation and optimization of parking spaces in a dynamic scenario can be effectively realized. At the same time, considering the ideal parking boundary line makes the distribution of the generated parking spaces more reasonable.

[0136] The following takes the real-time update of the boundary parking spaces based on uniform soil dumping and the ideal line as an example to illustrate the solution. Please refer to Figure 6 , Figure 6 which schematically shows the flowchart of the method for real-time dynamic update of parking spaces according to an embodiment of the present application. The logic of the above-mentioned method for real-time dynamic update of boundary parking spaces is as follows:

[0137] Step 1: Set the ideal retaining wall boundary line B1 of the waste dump and set the end condition E; the above-mentioned ideal retaining wall boundary line B1 is the target boundary line after several soil dumpings, including but not limited to information such as shape and position; the end condition E can be set as but not limited to requirements such as soil dumping duration and number of soil dumpings.

[0138] Step 2: Automatically extract the current retaining wall boundary line B2 by the driverless device, and determine whether the end condition is met. If it is met, exit; if not, go to Step 3;

[0139] Step 3: Dynamically set different parking space generation parameters according to the deviation degree of each point on the B2 boundary from B1, generate parking spaces according to the dynamic parameters, and dispatch the driverless device for soil dumping according to the generated parking spaces;

[0140] Step 4: After the soil pushing condition is met, the unmanned soil pushing device performs the soil pushing operation on the dumped soil and goes back to Step 2.

[0141] Figure 1 is a schematic flowchart of the parking space generation method in the embodiment. It should be understood that although Figure 1 the steps in the flowchart are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, Figure 1At least a part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed and completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0142] Please refer to Figure 7 , Figure 7 which schematically shows a structural diagram of a parking space generation device according to an embodiment of the present application. This embodiment provides a parking space generation device, including an acquisition module 410, a first iteration module 420, a second iteration module 430, and a parking space generation module 440, where:

[0143] The acquisition module 410 is used to acquire a parking boundary line;

[0144] The first iteration module 420 is used to perform a first layer of iteration, and the first layer of iteration is used to search for iteration points along the parking boundary line according to a first iteration step size;

[0145] The second iteration module 430 is used to perform a second layer of iteration when the first iteration points searched in the first layer of iteration do not meet the preset parking space generation conditions. The second layer of iteration is used to search for iteration points along the parking boundary line with the first iteration point as the starting point according to a second iteration step size;

[0146] The parking space generation module 440 is used to generate a parking space corresponding to the second iteration point when the second iteration points searched in the second layer of iteration meet the preset parking space generation conditions; where the first iteration step size is greater than the second iteration step size.

[0147] The parking space generation device includes a processor and a memory. The above acquisition module 410, first iteration module 420, second iteration module 430, and parking space generation module 440 are all stored in the memory as program units, and the corresponding functions are implemented by the processor executing the above program modules stored in the memory.

[0148] The processor contains a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be set, and the parking space generation is realized by adjusting the kernel parameters.

[0149] The memory may include non-permanent memory in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM), and the memory includes at least one storage chip.

[0150] An embodiment of the present application provides a processor for running a program, wherein when the program runs, it executes the parking space generation method.

[0151] An embodiment of the present application provides a machine-readable storage medium with a program stored thereon, and when the program is executed by a processor, it implements the above-mentioned parking space generation method.

[0152] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 8 shown. The computer device includes a processor A01, a network interface A02, a display screen A04, an input device A05, and a memory (not shown in the figure) connected through a system bus. Among them, the processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01 and a computer program B02. The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A06. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor A01, it implements a parking space generation method. The display screen A04 of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device A05 of the computer device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0153] Those skilled in the art can understand that Figure 8 the structure shown in

[0154] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0154] In one embodiment, the parking space generation device provided by the present application can be implemented in the form of a computer program, and the computer program can run on a computer device as Figure 8 shown. Each program module constituting the parking space generation device can be stored in the memory of the computer device. For example, Figure 7 the acquisition module 410, the first iteration module 420, the second iteration module 430, and the parking space generation module 440 shown in

[0155] Figure 8 The computer device shown inFigure 7 The obtaining module 410 in the parking space generation device shown executes step 210. The computer device may execute step 220 through the first iteration module 420. The computer device may execute step 230 through the second iteration module 430. The computer device may execute step 240 through the parking space generation module 440.

[0156] An embodiment of the present application provides an electronic device, which includes: at least one processor; a memory connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the at least one processor implements the above-mentioned parking space generation method by executing the instructions stored in the memory. When the processor executes the instructions, the following steps are implemented:

[0157] Obtain the parking boundary line;

[0158] Execute the first layer of iteration, and the first layer of iteration is used to search for iteration points along the parking boundary line according to the first iteration step size;

[0159] In the case that the first iteration point searched in the first layer of iteration does not meet the preset parking space generation condition, execute the second layer of iteration, and the second layer of iteration is used to search for iteration points along the parking boundary line with the first iteration point as the starting point according to the second iteration step size;

[0160] In the case that the second iteration point searched in the second layer of iteration meets the preset parking space generation condition, generate the parking space corresponding to the second iteration point;

[0161] Wherein, the first iteration step size is greater than the second iteration step size.

[0162] In one embodiment, the method further includes:

[0163] In the case that the second iteration point searched in the second layer of iteration meets the preset parking space generation condition, with the second iteration point as the starting point, jump to execute the first layer of iteration.

[0164] In one embodiment, after executing the second layer of iteration, the method further includes:

[0165] In the case that the second iteration point searched in the second layer of iteration does not meet the preset parking space generation condition, and the search distance of the second layer of iteration is greater than or equal to the first iteration step size, with the second iteration point as the starting point, jump to execute the first layer of iteration; the search distance of the second layer of iteration is positively correlated with the number of iterations of the second layer of iteration.

[0166] In one embodiment, after executing the first layer of iteration, the method further includes:

[0167] When the first iteration point in the first-layer iterative search meets the preset parking space generation conditions, generate the parking space corresponding to the first iteration point.

[0168] In one embodiment, the preset parking space generation conditions include: the minimum distance condition between parking spaces, the non-crossing condition of parking spaces, and the parking space orientation angle condition.

[0169] In one embodiment, after performing the first-layer iteration, it further includes:

[0170] Determine an initial orientation angle within a preset range of rotation angles;

[0171] Iterate the orientation angle according to a preset rotation iteration step size, and generate parking spaces corresponding to each orientation angle at the first iteration point in the first-layer iterative search;

[0172] Judge whether there is a parking space that meets the preset parking space generation conditions among the parking spaces corresponding to each orientation angle;

[0173] When it is determined that there is a parking space that meets the preset parking space generation conditions among the parking spaces corresponding to each orientation angle, determine that the first iteration point in the first-layer iterative search meets the preset parking space generation conditions.

[0174] In one embodiment, it further includes:

[0175] Optimize the layout of the parking spaces to obtain an optimized set of parking spaces.

[0176] In one embodiment, the optimizing the layout of the parking spaces to obtain an optimized set of parking spaces includes:

[0177] Obtain a parking space optimization target, where the parking space optimization target includes: the number of generated parking spaces, the uniformity index of the generated parking spaces, and the penalty value generated by the intersection and overlap of the generated parking spaces with the boundary;

[0178] Based on the parking space optimization target and the preset parking space generation parameter constraint conditions, optimize the parking space generation parameters to obtain optimized parking space generation parameters, where the parking space generation parameters include the first iteration step size, the second iteration step size, the rotation iteration step size, and the parking space distance corresponding to the parking space;

[0179] Based on the optimized parking space generation parameters, adjust the layout of the parking spaces to obtain an optimized set of parking spaces.

[0180] In one embodiment, it further includes:

[0181] Obtain the current parking boundary line in real time;

[0182] Based on the difference between the current parking boundary line and the ideal parking boundary line, the current parking space generation parameters are determined. The current parking space generation parameters include: the first iteration step length, the second iteration step length, the rotation iteration step length, and the parking space interval corresponding to the current parking boundary line.

[0183] Based on the current parking space generation parameters, a real-time parking space set is generated.

[0184] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0185] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce means for implementing the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0186] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0187] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0188] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0189] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0190] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0191] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0192] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A parking space generation method, characterized in that, Including: Obtain the parking boundary line; Execute the first-layer iteration, where the first-layer iteration is used to search for iteration points along the parking boundary line according to the first iteration step size; In the case that the first iteration point searched in the first-layer iteration does not meet the preset parking space generation condition, execute the second-layer iteration, where the second-layer iteration is used to start from the first iteration point and search for iteration points along the parking boundary line according to the second iteration step size; In the case that the second iteration point searched in the second-layer iteration meets the preset parking space generation condition, generate the parking space corresponding to the second iteration point; Wherein, the first iteration step size is greater than the second iteration step size.

2. The method according to claim 1, wherein The method further includes: In the case that the second iteration point searched in the second-layer iteration meets the preset parking space generation condition, start from the second iteration point and jump to execute the first-layer iteration.

3. The method according to claim 2, wherein After executing the second-layer iteration, the method further includes: In the case that the second iteration point searched in the second-layer iteration does not meet the preset parking space generation condition, and the search distance of the second-layer iteration is greater than or equal to the first iteration step size, start from the second iteration point and jump to execute the first-layer iteration; the search distance of the second-layer iteration is positively correlated with the number of iterations of the second-layer iteration.

4. The method according to claim 1, characterized in that, After executing the first-layer iteration, the method further includes: In the case that the first iteration point searched in the first-layer iteration meets the preset parking space generation condition, generate the parking space corresponding to the first iteration point.

5. The method according to claim 1, wherein The preset parking space generation condition includes: the minimum distance condition between parking spaces, the non-crossing condition of parking spaces, and the parking space orientation angle condition.

6. The method according to claim 1, characterized in that, After executing the first-layer iteration, it further includes: Determine the initial orientation angle within the preset rotation angle range; Iterate the orientation angle according to the preset rotation iteration step size, and generate parking spaces corresponding to each orientation angle at the first iteration point searched in the first-layer iteration; Judge whether there is a parking space that meets the preset parking space generation condition among the parking spaces corresponding to each orientation angle; In the case that it is determined that there is a parking space that meets the preset parking space generation condition among the parking spaces corresponding to each orientation angle, determine that the first iteration point searched in the first-layer iteration meets the preset parking space generation condition.

7. The method according to any one of claims 1-6, characterized in that, It further includes: Optimize the layout of the parking spaces to obtain an optimized set of parking spaces.

8. The method according to claim 7, characterized in that, The optimizing the layout of the parking spaces to obtain an optimized set of parking spaces includes: Obtain the parking space optimization target, where the parking space optimization target includes: the number of generated parking spaces, the uniformity index of the generated parking spaces, and the penalty value generated by the intersection and overlap of the generated parking spaces with the boundary; Based on the parking space optimization target and the preset parking space generation parameter constraint conditions, optimize the parking space generation parameters to obtain optimized parking space generation parameters, where the parking space generation parameters include the first iteration step size, the second iteration step size, the rotation iteration step size, and the parking space distance corresponding to the parking space; Based on the optimized parking space generation parameters, adjust the layout of the parking spaces to obtain an optimized set of parking spaces.

9. The method according to claim 1, wherein It further includes: Obtain the current parking boundary line in real time; Based on the difference between the current parking boundary line and the ideal parking boundary line, the current parking space generation parameters are determined, and the current parking space generation parameters include: the first iteration step length, the second iteration step length, the rotation iteration step length, and the parking space interval corresponding to the current parking boundary line; Based on the current parking space generation parameters, a real-time parking space set is generated.

10. A parking space generation device, characterized in that, It includes: An acquisition module, configured to acquire a parking boundary line; A first iteration module, configured to perform a first-layer iteration, and the first-layer iteration is used to search for iteration points along the parking boundary line according to the first iteration step length; A second iteration module, configured to perform a second-layer iteration when the first iteration points searched in the first-layer iteration do not meet the preset parking space generation conditions, and the second-layer iteration is used to search for iteration points along the parking boundary line according to the second iteration step length starting from the first iteration points; A parking space generation module, configured to generate a parking space corresponding to the second iteration point when the second iteration points searched in the second-layer iteration meet the preset parking space generation conditions; wherein, the first iteration step length is greater than the second iteration step length.

11. An electronic device, characterized in that, The electronic device includes: At least one processor; A memory, connected to the at least one processor; Wherein, the memory stores instructions executable by the at least one processor, and the at least one processor realizes the parking space generation method according to any one of claims 1 to 9 by executing the instructions stored in the memory.

12. A machine-readable storage medium having instructions stored thereon, characterized in that, When the instructions are executed by the processor, the processor is configured to execute the parking space generation method according to any one of claims 1 to 9.

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