Global path static planning simulation method and device and terminal equipment

Abstract

The invention discloses a global path static planning simulation method and device and terminal equipment, and the method comprises the steps: determining a target parking space and a driving range, and setting starting point coordinate information and vehicle course angle information based on vehicle information and the driving range; obtaining all starting point parameter sets in a driving range based on the starting point coordinate information, the vehicle course angle information and a preset change step length, wherein the starting point parameter sets comprise combinations of all starting point coordinates and vehicle course angles in the driving range; calculating an end point coordinate of the target parking space and a parking space line coordinate of the target parking space based on the point coordinate of the target parking space; and generating all vehicle driving routes in a driving range based on the starting point parameter set, the terminal point coordinates and the parking space line coordinates. According to the method, the path planning from different starting points to the destination of the target parking space is tested in batches, so that the test time is shortened, the simulation efficiency is improved, and the path planning effect of the algorithm at different starting points and vehicle course angles is quickly evaluated.

Description

Technical Field

[0001] The present invention relates to the field of simulation test technology, and in particular to a global path static planning simulation method, device and terminal equipment. Background Art

[0002] At present, path planning algorithms are widely used in automation fields such as automatic parking. Therefore, ensuring the effectiveness and reliability of these algorithms is crucial to the safety and user experience of automatic parking systems. Simulation testing plays an indispensable role in the development of automatic parking systems. It can not only detect problems at an early stage, but also significantly save development costs, improve the safety and performance of algorithms, and lay a solid foundation for subsequent real vehicle testing.

[0003] Existing path planning simulation methods can often only plan paths for a single starting point and end point, lack the means to batch simulate the path effects of different starting points, and lack tools to automatically generate path images, making it difficult to comprehensively evaluate the performance of path planning algorithms in different scenarios. In addition, when generating path visualizations, existing path planning simulation methods usually need to rely on manual operations, run simulations one by one, and save results, resulting in low efficiency and the inability to quickly conduct large-scale testing. Summary of the invention

[0004] The present invention provides a global path static planning simulation method, device and terminal equipment to batch generate path images with different starting points, thereby improving simulation efficiency and practicability.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a global path static planning simulation method, including:

[0006] Determine the target parking space and driving range, and set the starting point coordinate information and vehicle heading angle information based on the vehicle information and driving range;

[0007] Based on the starting point coordinate information, the vehicle heading angle information and a preset change step length, a set of all starting point parameters within the driving range is acquired, wherein the starting point parameter set includes a combination of all starting point coordinates and vehicle heading angles within the driving range;

[0008] Calculate the end point coordinates of the target parking space and the parking space line coordinates of the target parking space based on the point coordinates of the target parking space;

[0009] All vehicle driving routes within the driving range are generated based on the starting point parameter set, the end point coordinates and the parking space line coordinates.

[0010] The present invention generates all starting points within the driving range according to the target parking space and vehicle information, thereby batch testing the path planning from different starting points to the target parking space end point, reducing the time required for testing, improving simulation efficiency, and quickly evaluating the path planning effect of the algorithm at different starting points and vehicle heading angles.

[0011] Further, the determining of the target parking space and the driving range, and setting the starting point information and the vehicle heading angle information based on the vehicle information and the driving range, include:

[0012] Determine a target parking space, and determine a driving range based on the target parking space;

[0013] A two-dimensional coordinate system is constructed based on the target parking space, and starting point information and vehicle heading angle information are set based on the vehicle length, vehicle width, the driving range and the two-dimensional coordinate system; the starting point information includes a minimum horizontal coordinate value of the starting point, a maximum horizontal coordinate value of the starting point, a minimum vertical coordinate value of the starting point and a maximum vertical coordinate value of the starting point; the vehicle heading angle information includes a minimum heading angle value and a maximum heading angle value.

[0014] Furthermore, the obtaining of all starting point parameter sets within the driving range based on the starting point coordinate information, the vehicle heading angle information and a preset change step size includes:

[0015] Based on the minimum value of the starting point abscissa, the minimum value of the starting point ordinate and the minimum value of the heading angle as initial starting point parameters;

[0016] All starting point parameters within the driving range are iteratively generated based on the initial starting point parameters and the change step size; the change step size includes abscissa step size, ordinate step size and heading angle step size.

[0017] Further, the iterative generation of all starting point parameters within the driving range based on the initial starting point parameter and the change step size includes:

[0018] Iteratively generate the starting point abscissa based on the abscissa step size and the minimum value of the starting point abscissa until the starting point abscissa reaches the maximum value of the starting point abscissa, and obtain a starting point abscissa set;

[0019] Iteratively generate the starting point ordinate based on the ordinate step size and the minimum value of the starting point ordinate, until the starting point ordinate reaches the maximum value of the starting point ordinate, and obtain a starting point ordinate set;

[0020] Iteratively generate a heading angle based on the heading angle step size and the minimum heading angle value, until the heading angle reaches the maximum heading angle value, and obtain a heading angle set;

[0021] A starting point parameter set is generated based on the combination of the starting point abscissa set, the starting point ordinate set and the heading angle set.

[0022] Further, the generating of all vehicle driving routes within the driving range based on the starting point parameter set, the end point coordinates and the parking space line coordinates includes:

[0023] Traversing all starting point parameters in the starting point parameter set, performing path simulation based on the starting point parameters, the end point coordinates, the parking space line coordinates and a preset path planning algorithm, and generating path simulation information, wherein the path simulation information includes a planning state;

[0024] The planning status corresponding to each starting point parameter is obtained, and when the planning status is successful, the corresponding vehicle driving route is generated.

[0025] Furthermore, after performing path simulation based on the starting point parameters, the end point coordinates, the parking space line coordinates and a preset path planning algorithm to generate path simulation information, the method further includes:

[0026] The path simulation information is stored in a preset path, wherein the path simulation information includes starting point parameters, parking space end point, planning time and parking number.

[0027] Furthermore, when the planning state is successful, after generating the corresponding vehicle driving route, the method further includes:

[0028] The vehicle driving route is visualized to generate a path image.

[0029] In a second aspect, the present invention provides a global path static planning simulation device, including: an information setting module, a starting point generation module, a coordinate calculation module and a planning module;

[0030] The information setting module is used to determine the target parking space and the driving range, and to set the starting point coordinate information and the vehicle heading angle information based on the vehicle information and the driving range;

[0031] The starting point generation module is used to obtain all starting point parameter sets within the driving range based on the starting point coordinate information, the vehicle heading angle information and a preset change step size, wherein the starting point parameter set includes a combination of all starting point coordinates and vehicle heading angles within the driving range;

[0032] The coordinate calculation module is used to calculate the end point coordinates of the target parking space and the parking space line coordinates of the target parking space based on the point coordinates of the target parking space;

[0033] The planning module is used to generate driving routes for all vehicles within the driving range based on the starting point parameter set, the end point coordinates and the parking space line coordinates.

[0034] Furthermore, a visualization module is included, which is used to:

[0035] The vehicle driving route is visualized to generate a path image.

[0036] In a third aspect, the present invention provides a terminal device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the processor implements a global path static planning simulation method as described in any one of claims 1 to 7. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A schematic diagram of a flow chart of a global path static planning simulation method provided by an embodiment of the present invention;

[0038] Figure 2 Another schematic diagram of a global path static planning simulation method provided by an embodiment of the present invention;

[0039] Figure 3 A schematic diagram of a simulation scenario provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0041] The terms "first" and "second" and the like in the specification, claims and drawings of this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0042] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0043] Example 1

[0044] See also Figure 1 , Figure 1A flowchart of a global path static planning simulation method provided by an embodiment of the present invention. The embodiment of the present invention provides a global path static planning simulation method, including steps 101 to 104, which are as follows:

[0045] Step 101: Determine the target parking space and driving range, and set the starting point coordinate information and vehicle heading angle information based on the vehicle information and the driving range;

[0046] In this embodiment, the determination of the target parking space and the driving range, and setting the starting point information and the vehicle heading angle information based on the vehicle information and the driving range include:

[0047] Determine a target parking space, and determine a driving range based on the target parking space;

[0048] A two-dimensional coordinate system is constructed based on the target parking space, and starting point information and vehicle heading angle information are set based on the vehicle length, vehicle width, the driving range and the two-dimensional coordinate system; the starting point information includes a minimum horizontal coordinate value of the starting point, a maximum horizontal coordinate value of the starting point, a minimum vertical coordinate value of the starting point and a maximum vertical coordinate value of the starting point; the vehicle heading angle information includes a minimum heading angle value and a maximum heading angle value.

[0049] In this embodiment, a target parking space is determined, and a driving range for vehicle parking that can be route-planned is determined based on the position of the target parking space and the current position of the vehicle. The driving range is the area directly in front of the vehicle and directly in front of the target parking space.

[0050] In this embodiment, after the target parking space is determined, the four corner points of the target parking space are located, and a two-dimensional rectangular coordinate system is constructed based on any one of the corner points as the origin.

[0051] In this embodiment, the starting point information and vehicle heading angle information of the vehicle parking route are set in consideration of the vehicle length, vehicle width and the size of the driving range in front of the parking space, wherein the vehicle starting point information includes a value range of the horizontal coordinate of the starting point and a value range of the vertical coordinate of the starting point; the vehicle heading angle information includes a value range of the vehicle heading angle.

[0052] In this embodiment, the starting point information and vehicle heading angle information are set in the simulation script according to the vehicle length, vehicle width, the size of the driving range in front of the parking space and the test requirements. Specifically, the minimum horizontal coordinate value Xmin, the maximum horizontal coordinate value Xmax, the minimum vertical coordinate value Ymin, the maximum vertical coordinate value Ymax, the minimum heading angle value Tmin, and the maximum heading angle value Tmax of the starting point are set.

[0053] Step 102: Acquire all starting point parameter sets within the driving range based on the starting point coordinate information, the vehicle heading angle information and a preset change step size, wherein the starting point parameter set includes a combination of all starting point coordinates and vehicle heading angles within the driving range;

[0054] In this embodiment, the acquisition of all starting point parameter sets within the driving range based on the starting point coordinate information, the vehicle heading angle information and a preset change step size includes:

[0055] Based on the minimum value of the starting point abscissa, the minimum value of the starting point ordinate and the minimum value of the heading angle as initial starting point parameters;

[0056] All starting point parameters within the driving range are iteratively generated based on the initial starting point parameters and the change step size; the change step size includes abscissa step size, ordinate step size and heading angle step size.

[0057] In this embodiment, the minimum value of the horizontal coordinate of the starting point and the minimum value of the vertical coordinate of the starting point are used as the initial starting point for the vehicle to start automatic parking, the minimum value of the vehicle heading angle is used as the initial heading angle for automatic parking, and the initial starting point and the initial heading angle are used as the initial starting point parameters for automatic parking of the vehicle, thereby generating all starting point parameters within the driving range based on the initial starting point parameters and the preset change step size.

[0058] In this embodiment, the starting point parameter is a combination of the starting point coordinates and the starting point heading angle.

[0059] In this embodiment, the iterative generation of all starting point parameters within the driving range based on the initial starting point parameter and the change step size includes:

[0060] Iteratively generate the starting point abscissa based on the abscissa step size and the minimum value of the starting point abscissa until the starting point abscissa reaches the maximum value of the starting point abscissa, and obtain a starting point abscissa set;

[0061] Iteratively generate the starting point ordinate based on the ordinate step size and the minimum value of the starting point ordinate, until the starting point ordinate reaches the maximum value of the starting point ordinate, and obtain a starting point ordinate set;

[0062] Iteratively generate a heading angle based on the heading angle step size and the minimum heading angle value, until the heading angle reaches the maximum heading angle value, and obtain a heading angle set;

[0063] A starting point parameter set is generated based on the combination of the starting point abscissa set, the starting point ordinate set and the heading angle set.

[0064] In this embodiment, the minimum value of the horizontal coordinate is taken as the starting point and the maximum value of the horizontal coordinate is taken as the end point. The horizontal coordinate is updated according to the horizontal coordinate step length in each iteration, so as to obtain all the horizontal coordinates of the starting point within the driving range and generate the horizontal coordinate set of the starting point. The minimum value of the vertical coordinate is taken as the starting point and the maximum value of the vertical coordinate is taken as the end point. The vertical coordinate is updated according to the vertical coordinate step length in each iteration, so as to obtain all the vertical coordinates within the driving range and generate the vertical coordinate set of the starting point. The minimum value of the heading angle is taken as the starting point and the maximum value of the heading angle is taken as the end point. The vertical coordinate is updated according to the heading angle step length in each iteration, so as to obtain all the heading angles within the driving range and generate the heading angle set of the starting point.

[0065] In this embodiment, the parameters in the abscissa set, the ordinate set and the heading angle set are randomly combined to generate a starting point parameter set.

[0066] In this embodiment, the horizontal coordinate step size StepX, the vertical coordinate step size StepY and the heading angle step size StepT are set respectively. The iteration is started with the initial starting point parameters, and the starting point parameters are updated according to the horizontal coordinate step size StepX, the vertical coordinate step size StepY and the heading angle step size StepT, wherein the initial starting point parameters include: starting point coordinates (Xstart, Ystart) and heading angle (Tstart).

[0067] In this embodiment, a three-layer loop is set to traverse the starting point horizontal coordinate, starting point vertical coordinate and heading angle in turn. The starting point will update the parameters according to the set step size in each iteration to generate new starting point parameters and enter the next iteration.

[0068] In this embodiment, if the variable step size is set larger, the moving distance of the starting point in each iteration increases or the number of heading angles decreases, which will effectively reduce the number of simulations and shorten the required time, and is suitable for quickly evaluating the basic performance of the algorithm. However, the reduction in the number of starting points may result in incomplete simulation results. On the contrary, if the step size is smaller, the moving distance of the starting point in each iteration decreases or the number of heading angles increases, which will increase the number of starting points and make the evaluation more comprehensive, but will increase the overall simulation time. Therefore, it is necessary to flexibly adjust the size of StepX, StepY, and StepT according to the actual scenario to improve the efficiency and comprehensiveness of route planning.

[0069] Step 103: Calculating the end point coordinates of the target parking space and the parking space line coordinates of the target parking space based on the point coordinates of the target parking space;

[0070] In this embodiment, after constructing a two-dimensional coordinate system according to the target parking space, the point cloud coordinates of the parking space line of the target parking space are obtained according to the coordinate system, and the vehicle end point is determined according to the target parking space, and the end point coordinates are calculated based on the two-dimensional coordinate system.

[0071] In this embodiment, the vehicle end point is the final stop point of the vehicle, which can be set according to the vehicle size, vehicle length, vehicle width and the size of the target parking space.

[0072] Step 104: Generate driving routes for all vehicles within the driving range based on the starting point parameter set, the end point coordinates and the parking space line coordinates.

[0073] In this embodiment, the generating of all vehicle driving routes within the driving range based on the starting point parameter set, the end point coordinates and the parking space line coordinates includes:

[0074] Traversing all starting point parameters in the starting point parameter set, performing path simulation based on the starting point parameters, the end point coordinates, the parking space line coordinates and a preset path planning algorithm, and generating path simulation information, wherein the path simulation information includes a planning state;

[0075] The planning status corresponding to each starting point parameter is obtained, and when the planning status is successful, the corresponding vehicle driving route is generated.

[0076] In this embodiment, after all starting point parameters within the driving range are obtained, all starting point parameters are traversed, and a path simulation is performed by calling a path planning algorithm according to each starting point parameter, and corresponding path simulation information is generated for each starting point parameter.

[0077] In this embodiment, the path planning algorithm includes A* algorithm, dynamic window algorithm, model predictive control method and artificial potential field method.

[0078] In this embodiment, the path simulation information includes a planning status. If the planning status is successful, a vehicle driving route corresponding to the starting point parameter is generated.

[0079] In this embodiment, after performing path simulation based on the starting point parameters, the end point coordinates, the parking space line coordinates and a preset path planning algorithm to generate path simulation information, the method further includes:

[0080] The path simulation information is stored in a preset path, wherein the path simulation information includes starting point parameters, parking space end point, planning time and parking number.

[0081] In this embodiment, after route planning is performed, regardless of whether the planning status is successful, the starting point parameters, parking space end point, planning time and number of parking times are stored in the preset path so that the user can clearly observe the vehicle planning information in the background.

[0082] In this embodiment, by performing path planning for different starting positions and heading angles, all possible initial states of the vehicle within the starting range can be fully covered, thereby ensuring the comprehensiveness and completeness of the simulation test.

[0083] In this embodiment, when the planning state is successful, after generating the corresponding vehicle driving route, the method further includes:

[0084] The vehicle driving route is visualized to generate a path image.

[0085] In this embodiment, for the starting point parameter whose planning status is successful planning, a corresponding vehicle form route is generated, and visualization processing is performed based on the vehicle driving route to generate a path image.

[0086] In this embodiment, the starting point, the end point and the track line of the vehicle driving route are displayed as arrows, and each vehicle driving route is numbered.

[0087] In this embodiment, by batch testing the path planning from different starting points to the target parking space end point, the time required for testing is reduced and the simulation efficiency is improved. At the same time, the path images planned from different starting points are automatically generated in batches, which can quickly evaluate the path planning effect of the algorithm at different starting points and vehicle heading angles. In addition, by automatically recording data such as planning status, number of parking lot rotations, planning time and other information into a table, it is convenient to statistically analyze the planning success rate, the proportion of parking lot rotations and the proportion of planning time in the simulation area, avoiding the tedious operation of manual data recording, assisting developers to identify and correct potential safety hazards, iterating and optimizing algorithms more quickly, and improving the reliability of path planning algorithms in practical applications.

[0088] Please refer to Figure 2 , Figure 2 Another flowchart of a global path static planning simulation method provided by an embodiment of the present invention.

[0089] In this embodiment, firstly, the coordinates of the four corner points of the parking space are set according to the size of the parking space to be simulated and tested. The coordinates of the end point of the vehicle entering the parking space and the point cloud coordinates of the parking space line are calculated through the coordinates of these corner points.

[0090] In this embodiment, the range of the starting point coordinates and the vehicle heading angle is defined by considering the length and width of the vehicle, the size of the drivable area in front of the parking space, and the test requirements. The change step of the starting point coordinates and the heading angle is set, and the starting point abscissa, starting point ordinate, and heading angle are traversed in turn through three layers of loops. The starting point will be updated according to the set step size in each iteration, and a new starting point will be generated for the next simulation.

[0091] In this embodiment, the path planning algorithm is called to perform path planning based on the end coordinates of the parking space, the parking space line point cloud coordinates and the starting point coordinates, and the path planning status is confirmed. When the path planning is successful, the path planning route is generated. When the path planning fails, the path planning route is not generated.

[0092] In this embodiment, a path image is generated for a successfully planned path planning route, and path planning information corresponding to each starting point is recorded, wherein the path planning information includes planning status, number of library passes, and planning time.

[0093] As a specific example of an embodiment of the present invention, please refer to Figure 3 , Figure 3 A schematic diagram of a simulation scenario provided by an embodiment of the present invention.

[0094] In this embodiment, it is assumed that a simulation test needs to be performed on a parking space that is 4 meters long and 2.3 meters wide, and the middle parking space is used as the target parking space for the simulation test.

[0095] In this embodiment, a coordinate system is established with the lower left corner point as the origin to obtain the coordinates of the four corner points of the parking space. The range of the vehicle's starting point is set in combination with the length and width of the vehicle and the test requirements. The dotted box marks the horizontal coordinate range of the vehicle's starting point as -2.3 meters to 4.6 meters, and the vertical coordinate range is 5.5 meters to 9.5 meters. The vehicle's heading angle is set between 30 degrees and 90 degrees.

[0096] In this embodiment, the minimum value of the range of the starting point coordinates and heading angles is used as the initial starting point. Assuming that the step size is set to StepX=0.3, StepY=0.3, and StepT=5, all coordinates and heading angles within the starting point range are traversed through three layers of loops, and the path planning algorithm is called to perform path simulation to generate path planning information for each starting point. The simulation ends when all heading angles under different starting point coordinates (X, Y) within the starting point range are traversed.

[0097] In this embodiment, path images are generated in batches for successfully planned vehicle driving routes and the images are automatically saved to a designated path. The path images include vehicle driving routes with different starting points.

[0098] In this embodiment, the path planning information of each starting point is stored in the preset path, and a table is generated to facilitate statistical data and analysis of information such as the planning success rate, the proportion of library rubbing times and the proportion of planning time in the simulation area, thereby avoiding the tedious operation of manually recording data, assisting developers in identifying and correcting potential safety hazards, iterating and optimizing algorithms more quickly, and improving the reliability of path planning algorithms in practical applications.

[0099] The embodiment of the present invention also provides a global path static planning simulation device, including: an information setting module, a starting point generation module, a coordinate calculation module and a planning module;

[0100] The information setting module is used to determine the target parking space and the driving range, and to set the starting point coordinate information and the vehicle heading angle information based on the vehicle information and the driving range;

[0101] The starting point generation module is used to obtain all starting point parameter sets within the driving range based on the starting point coordinate information, the vehicle heading angle information and a preset change step size, wherein the starting point parameter set includes a combination of all starting point coordinates and vehicle heading angles within the driving range;

[0102] The coordinate calculation module is used to calculate the end point coordinates of the target parking space and the parking space line coordinates of the target parking space based on the point coordinates of the target parking space;

[0103] The planning module is used to generate driving routes for all vehicles within the driving range based on the starting point parameter set, the end point coordinates and the parking space line coordinates.

[0104] In this embodiment, the information setting module is used to:

[0105] Determine a target parking space, and determine a driving range based on the target parking space;

[0106] A two-dimensional coordinate system is constructed based on the target parking space, and starting point information and vehicle heading angle information are set based on the vehicle length, vehicle width, the driving range and the two-dimensional coordinate system; the starting point information includes a minimum horizontal coordinate value of the starting point, a maximum horizontal coordinate value of the starting point, a minimum vertical coordinate value of the starting point and a maximum vertical coordinate value of the starting point; the vehicle heading angle information includes a minimum heading angle value and a maximum heading angle value.

[0107] In this embodiment, the starting point generation module is used to:

[0108] Based on the minimum value of the starting point abscissa, the minimum value of the starting point ordinate and the minimum value of the heading angle as initial starting point parameters;

[0109] All starting point parameters within the driving range are iteratively generated based on the initial starting point parameters and the change step size; the change step size includes abscissa step size, ordinate step size and heading angle step size.

[0110] In this embodiment, the starting point generation module is used to:

[0111] Iteratively generate the starting point abscissa based on the abscissa step size and the minimum value of the starting point abscissa until the starting point abscissa reaches the maximum value of the starting point abscissa, and obtain a starting point abscissa set;

[0112] Iteratively generate the starting point ordinate based on the ordinate step size and the minimum value of the starting point ordinate, until the starting point ordinate reaches the maximum value of the starting point ordinate, and obtain a starting point ordinate set;

[0113] Iteratively generate a heading angle based on the heading angle step size and the minimum heading angle value, until the heading angle reaches the maximum heading angle value, and obtain a heading angle set;

[0114] A starting point parameter set is generated based on the combination of the starting point abscissa set, the starting point ordinate set and the heading angle set.

[0115] In this embodiment, the planning module is used to:

[0116] Traversing all starting point parameters in the starting point parameter set, performing path simulation based on the starting point parameters, the end point coordinates, the parking space line coordinates and a preset path planning algorithm, and generating path simulation information, wherein the path simulation information includes a planning state;

[0117] The planning status corresponding to each starting point parameter is obtained, and when the planning status is successful, the corresponding vehicle driving route is generated.

[0118] In this embodiment, the planning module is used to:

[0119] The path simulation information is stored in a preset path, wherein the path simulation information includes starting point parameters, parking space end point, planning time and parking number.

[0120] In this embodiment, a visualization module is also included, which is used to:

[0121] The vehicle driving route is visualized to generate a path image.

[0122] An embodiment of the present invention further provides a car, comprising a processor, wherein the processor performs path simulation planning based on the global path static planning simulation method as described above.

[0123] In an embodiment of the present invention, a terminal device is also provided, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the above-mentioned global path static planning simulation method when executing the computer program.

[0124] In an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned global path static planning simulation method.

[0125] Exemplarily, the computer program may be divided into one or more modules, one or more modules are stored in a memory and executed by a processor to implement the present invention. One or more modules may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program in a terminal device.

[0126] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The terminal device may include, but is not limited to, a processor, a memory, and a display. Those skilled in the art will appreciate that the above components are merely examples of the terminal device and do not constitute a limitation on the terminal device. The terminal device may include more or fewer components than the components, or may combine certain components, or different components. For example, the terminal device may also include input and output devices, network access devices, buses, etc.

[0127] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0128] The memory can be used to store computer programs and / or modules. The processor realizes various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function (such as a sound playback function, a text conversion function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, text message data, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Med ia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0129] Among them, if the module based on the processing of the multi-device access platform is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium, etc. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0130] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A global path static planning simulation method, characterized in that: include: Determine the target parking space and driving range, and set the starting point coordinate information and vehicle heading angle information based on the vehicle information and driving range; Based on the starting point coordinate information, the vehicle heading angle information and a preset change step length, a set of all starting point parameters within the driving range is acquired, wherein the starting point parameter set includes a combination of all starting point coordinates and vehicle heading angles within the driving range; Calculate the end point coordinates of the target parking space and the parking space line coordinates of the target parking space based on the point coordinates of the target parking space; All vehicle driving routes within the driving range are generated based on the starting point parameter set, the end point coordinates and the parking space line coordinates.

2. A global path static planning simulation method as claimed in claim 1, characterized in that: The determining of the target parking space and the driving range, and setting the starting point information and the vehicle heading angle information based on the vehicle information and the driving range, include: Determine a target parking space, and determine a driving range based on the target parking space; A two-dimensional coordinate system is constructed based on the target parking space, and starting point information and vehicle heading angle information are set based on the vehicle length, vehicle width, the driving range and the two-dimensional coordinate system; the starting point information includes a minimum horizontal coordinate value of the starting point, a maximum horizontal coordinate value of the starting point, a minimum vertical coordinate value of the starting point and a maximum vertical coordinate value of the starting point; the vehicle heading angle information includes a minimum heading angle value and a maximum heading angle value.

3. A global path static planning simulation method as claimed in claim 2, characterized in that: The obtaining of all starting point parameter sets within the driving range based on the starting point coordinate information, the vehicle heading angle information and a preset change step size includes: Based on the minimum value of the starting point abscissa, the minimum value of the starting point ordinate and the minimum value of the heading angle as initial starting point parameters; All starting point parameters within the driving range are iteratively generated based on the initial starting point parameters and the change step size; the change step size includes abscissa step size, ordinate step size and heading angle step size.

4. A global path static planning simulation method as claimed in claim 3, characterized in that: The iterative generation of all starting point parameters within the driving range based on the initial starting point parameter and the change step size includes: Iteratively generate the starting point abscissa based on the abscissa step size and the minimum value of the starting point abscissa until the starting point abscissa reaches the maximum value of the starting point abscissa, and obtain a starting point abscissa set; Iteratively generate the starting point ordinate based on the ordinate step size and the minimum value of the starting point ordinate until the starting point ordinate reaches the maximum value of the starting point ordinate, and obtain a starting point ordinate set; Iteratively generate a heading angle based on the heading angle step size and the minimum heading angle value, until the heading angle reaches the maximum heading angle value, and obtain a heading angle set; A starting point parameter set is generated based on the combination of the starting point abscissa set, the starting point ordinate set and the heading angle set.

5. A global path static planning simulation method as claimed in claim 4, characterized in that: The generating of all vehicle driving routes within the driving range based on the starting point parameter set, the end point coordinates and the parking space line coordinates includes: Traversing all starting point parameters in the starting point parameter set, performing path simulation based on the starting point parameters, the end point coordinates, the parking space line coordinates and a preset path planning algorithm, and generating path simulation information, wherein the path simulation information includes a planning state; The planning status corresponding to each starting point parameter is obtained, and when the planning status is successful, the corresponding vehicle driving route is generated.

6. A global path static planning simulation method as claimed in claim 5, characterized in that: After performing path simulation based on the starting point parameters, the end point coordinates, the parking space line coordinates and a preset path planning algorithm to generate path simulation information, the method further includes: The path simulation information is stored in a preset path, wherein the path simulation information includes starting point parameters, parking space end point, planning time and parking number.

7. A global path static planning simulation method as claimed in claim 5, characterized in that: When the planning state is successful, after generating the corresponding vehicle driving route, the method further includes: The vehicle driving route is visualized to generate a path image.

8. A global path static planning simulation device, characterized in that: include: Information setting module, starting point generation module, coordinate calculation module and planning module; The information setting module is used to determine the target parking space and the driving range, and to set the starting point coordinate information and the vehicle heading angle information based on the vehicle information and the driving range; The starting point generation module is used to obtain all starting point parameter sets within the driving range based on the starting point coordinate information, the vehicle heading angle information and a preset change step size, wherein the starting point parameter set includes a combination of all starting point coordinates and vehicle heading angles within the driving range; The coordinate calculation module is used to calculate the end point coordinates of the target parking space and the parking space line coordinates of the target parking space based on the point coordinates of the target parking space; The planning module is used to generate driving routes for all vehicles within the driving range based on the starting point parameter set, the end point coordinates and the parking space line coordinates.

9. A global path static planning simulation device as claimed in claim 8, characterized in that: Also included is a visualization module, which is used to: The vehicle driving route is visualized to generate a path image.

10. A terminal device, characterized in that: The invention comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, a global path static planning simulation method as described in any one of claims 1 to 7 is implemented.

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