Path planning method, storage medium and electronic equipment
By acquiring and fusion of intersection section data and running the A* algorithm in the forward and reverse directions, the existing path planning algorithm is solved and a faster path planning process is achieved.
Patent Information
- Application Number
- CN202411653627.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-18
- Publication Date
- 2025-02-25
AI Technical Summary
The existing path planning algorithms are less efficient, especially when the path distance is large, resulting in longer calculation time.
By obtaining the intersection section data, including intersection data, section data connected to the intersection, and the connection point data of the section and the intersection, and fusing these data according to the starting position and the terminating position, the A* algorithm is run in the forward and reverse directions respectively to obtain the set of the shortest path sections.
This method shortens the response time of path planning and improves the efficiency of the algorithm by reducing the depth of data traversal and reducing the time complexity of the algorithm.
Smart Images
Figure CN119509570A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of path planning during vehicle driving, and in particular to a path planning method, a storage medium and an electronic device. Background Art
[0002] At present, in the path planning algorithm during vehicle driving, the shortest path is usually selected from multiple alternative paths. At present, the commonly used path planning method is the A* (A-tar) algorithm. The A* algorithm is an effective and direct search algorithm for solving the shortest path in a static network. The A* algorithm is a one-way search, that is, starting from the starting point, searching in the direction of road connectivity, and extending to the end point to stop. When the path distance is large, the time required for path planning using this algorithm is also longer. Therefore, the efficiency of existing path planning algorithms needs to be improved. Summary of the invention
[0003] The technical problem to be solved by the present application is that the efficiency of the path planning algorithm in the prior art is relatively low, and thus a path planning method, a storage medium and an electronic device are provided.
[0004] In a first aspect, the technical solution of the present application provides a path planning method, comprising:
[0005] Acquire intersection section data, wherein the intersection section data includes intersection data, section data of a section connected to the intersection, and connection point data of the section and the intersection;
[0006] Acquire the starting position and the ending position of the path planning, merge the starting position and the ending position into the intersection section data, and obtain multiple initial planned paths according to the initial position and the ending position;
[0007] For each of the initial planned paths, the A* algorithm is run in a forward direction and a reverse direction respectively to determine a set of shortest path segments when the vehicle travels from the current position to the end position; wherein the direction of travel from the starting position to the end position is taken as the forward direction, and the direction of travel from the end position to the starting position is taken as the reverse direction;
[0008] If the shortest path along the positive direction and the shortest path along the reverse direction overlap, the A* algorithm is stopped, and the shortest path segments obtained in the positive direction and the reverse direction are merged to obtain the shortest path.
[0009] In some embodiments of the path planning method, the step of obtaining intersection section data includes intersection data, section data of a section connected to the intersection, and connection point data of the section and the intersection, including:
[0010] Acquire original map data, extract intersections, road sections and connection points in the original map data to obtain map data;
[0011] Filtering the road sections within the intersection and the dead-end road sections in the map data;
[0012] Identifiers are assigned to the intersections, sections and connection points retained in the map data to obtain the intersection and section data.
[0013] In the path planning method described in some solutions, in filtering the road sections within the intersection and the dead-end road sections in the map data, the road sections within the intersection are filtered in the following manner:
[0014] Determine whether a road section is within an intersection based on the road section attributes or the spatial position relationship between the intersection surface and the road line of the road section;
[0015] Filter out the road segments within the intersection.
[0016] In some embodiments of the path planning method, the filtering of the road sections within the intersection and the dead-end road sections in the map data is performed by filtering the dead-end road sections in the following manner:
[0017] Determine whether the current road section has a subsequent road section according to a recursive algorithm;
[0018] If the current road section is not within the intersection and there is no subsequent road section for the current road section, the current road section is determined to be an end road section and is filtered.
[0019] In some embodiments, the path planning method, wherein the A* algorithm is run in a forward direction and a reverse direction respectively to determine a set of shortest path segments when the vehicle travels from the current position to the end position, comprises:
[0020] Establish a set of path segments that have been reached in the positive direction S1 and a set of path segments that will be reached U1, and a set of path segments that have been reached in the reverse direction S2 and a set of path segments that will be reached U2;
[0021] Traverse all path segments in the set U1, select the first path segment with the shortest distance, and then transfer the first path segment from the set U1 to the set S1; traverse all path segments in the set U2, select the second path segment with the shortest distance, and then transfer the second path segment from the set U2 to the set S2;
[0022] A first judgment result is obtained by judging whether the vehicle has reached the end position or the first path segment already exists in the set S2 in the positive direction, and a second judgment result is obtained by judging whether the vehicle has reached the start position or the second path segment already exists in the set S1 in the reverse direction;
[0023] If the first judgment result or the second judgment result is yes, all the first path segments in the set S1 and all the second path segments in the set S2 are merged into the set of the shortest path segments.
[0024] Some of the path planning methods described in the scheme:
[0025] The traversing all the path segments in the set U1 and selecting the first path segment with the shortest distance includes:
[0026] Calculate the distance d11 along all the route segments that have been reached;
[0027] Calculate the straight-line distance d12 between the starting point and the end point of each path segment to be reached;
[0028] Selecting a path segment to be reached that satisfies the minimum sum of d11 and d12 as the first path segment;
[0029] The traversing all the path segments in the set U2 and selecting the second path segment with the shortest distance includes:
[0030] Calculate the distance d21 along all the route segments that have been reached;
[0031] Calculate the straight-line distance d22 between the starting point and the end point of each path segment to be reached;
[0032] The path segment to be reached that satisfies the minimum sum of d21 and d22 is selected as the second path segment.
[0033] In a second aspect, the technical solution of the present application provides a path planning device, comprising:
[0034] A road section data acquisition module is configured to acquire road section data of an intersection, wherein the road section data of the intersection includes road section data, road section data of a road section connected to the intersection, and connection point data of a road section and an intersection;
[0035] A path planning module is configured to obtain a starting position and an ending position of the path planning, merge the starting position and the ending position into the intersection section data, and obtain a plurality of initial planned paths according to the initial position and the ending position;
[0036] The path screening module is configured to run the A* algorithm in a forward direction and a reverse direction for each of the initial planned paths, respectively, to determine a set of shortest path segments when the vehicle travels from the current position to the end position; wherein the direction of travel from the starting position to the end position is taken as the forward direction, and the direction of travel from the end position to the starting position is taken as the reverse direction;
[0037] The path output module is configured to stop running the A* algorithm if the shortest path along the positive direction and the shortest path along the reverse direction overlap, and merge the shortest path segments obtained in the positive direction and the reverse direction to obtain the shortest path.
[0038] In a third aspect, the technical solution of the present application provides a computer-readable storage medium, in which program information is stored. After a computer reads the program information, the computer executes the steps of the path planning method described in any one of the first aspects.
[0039] In a fourth aspect, the technical solution of the present application provides a computer program product, including a computer program / instruction, characterized in that when the computer program / instruction is executed by a processor, the steps of the path planning method described in any one of the first aspects are implemented.
[0040] In a fifth aspect, the technical solution of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the path planning method described in any one of the first aspects.
[0041] Compared with the prior art, the above technical solution provided by this application has the following technical effects:
[0042] The path planning method, storage medium and electronic device provided by the present application use the intersection section data as the basis for path planning. The intersection section data only needs to include the intersection data, the section data of the section connected to the intersection, and the connection point data between the section and the intersection, thereby reducing the depth of data traversal and reducing the time complexity of the algorithm. When performing path planning, the A* algorithm is run in the forward direction and the reverse direction respectively to obtain the shortest path, and the one-way depth traversal is changed to the parallel calculation of the two-way depth traversal, further shortening the response time of the algorithm. BRIEF DESCRIPTION OF THE DRAWINGS
[0043] Figure 1 This is a flow chart of a path planning method according to an embodiment of the present application;
[0044] Figure 2 A schematic diagram of the relationship between intersections, road sections and connection points described in one embodiment of the present application;
[0045] Figure 3 A schematic diagram of the original map data according to an embodiment of the present application;
[0046] Figure 4 Based on Figure 3 A schematic diagram of a road network composed of intersection and section data obtained from the original map data;
[0047] Figure 5 A flow chart of a method for filtering dead-end roads according to an embodiment of the present application;
[0048] Figure 6 A flowchart of an embodiment of the present application for running the A* algorithm in a forward direction and a reverse direction for an initial planned path to finally obtain a set of shortest path segments;
[0049] Figure 7 A flowchart of another embodiment of the present application for running the A* algorithm in a forward direction and a reverse direction for an initial planned path to finally obtain a set of shortest path segments;
[0050] Figure 8 This is a structural block diagram of a path planning device according to an embodiment of the present application;
[0051] Fig. 9 A schematic diagram of the hardware connection relationship of an electronic device that executes a path planning method according to an embodiment of the present application. DETAILED DESCRIPTION
[0052] The specific implementation of the present application is further described below with reference to the accompanying drawings.
[0053] It is easy to understand that according to the technical solution of the present application, without changing the essential spirit of the present application, a variety of structural modes and implementation modes that can be replaced by those skilled in the art can be replaced with each other. Therefore, the following specific implementation modes and drawings are only exemplary descriptions of the technical solution of the present application, and should not be regarded as the entirety of the present application or as a limitation or restriction on the technical solution of the application.
[0054] The directional terms such as up, down, left, right, front, back, front, back, top, bottom, etc. mentioned or may be mentioned in this specification are defined relative to the structures shown in the drawings. They are relative concepts and may change accordingly according to different positions and different usage conditions. Therefore, these or other directional terms should not be interpreted as restrictive terms.
[0055] This embodiment provides a path planning method, which is applied to a vehicle terminal or a cloud terminal. Figure 1 As shown, including:
[0056] S100: Obtaining intersection section data, wherein the intersection section data includes intersection data, section data of a section connected to the intersection, and connection point data of the section and the intersection.
[0057] Among them, Figure 2As shown in the figure, intersection data refers to road intersections, such as junction1 and junction2 in the figure, and road segment data refers to road segments directly connected by one or more lines between two intersections, and the intersections are not interrupted, and the starting and ending points of the road segments are both at the edge of the intersection surface, such as road1 and road2 in the figure. The connection point is the shape point connecting the intersection and the road segment, such as node1 and node2 in the figure. As shown in the figure, the node point refers to the shape point connecting the intersection and the road segment. A road segment data contains two node points, the starting point and the end point. The node point can be calculated based on the entry and exit of the intersection in the original map data. From intersection jucntion1 to intersection junction2, the exit of intersection junction1 and the entry of intersection junction2 are road segment road1 and road segment road2 respectively. This data can be obtained from the original map data. The starting point of section raod1 can be directly extracted as the connection point node1, and the end point of section road2 can be directly extracted as the connection point node2.
[0058] Will Figure 2 The data relationship shown in is recorded in the database, and the table structure is shown in Table 1:
[0059] Table 1 Definition of logo
[0060]
[0061] S200: Acquire a starting position and an ending position of the path planning, merge the starting position and the ending position into the intersection section data, and obtain a plurality of initial planned paths according to the initial position and the ending position.
[0062] That is, during the path planning process, intersection and road section data can be used to replace the conventional maps used in the prior art, thereby reducing the amount of data calculation and analysis.
[0063] S300: For each of the initial planned paths, run the A* algorithm in the forward direction and the reverse direction respectively to determine a set of shortest path segments when the vehicle travels from the current position to the end position; wherein the driving direction from the starting position to the end position is taken as the forward direction, and the driving direction from the end position to the starting position is taken as the reverse direction.
[0064] The A* algorithm is a shortest path algorithm. It adds a heuristic function to the Dijkstra algorithm to reduce the complexity of the algorithm and improve the calculation speed. Dijkstra is a breadth-first traversal algorithm, and the A* algorithm is a depth-first traversal algorithm. Based on the existing A* algorithm, this application adopts a bidirectional search strategy in the forward and reverse directions to further reduce the complexity of the algorithm.
[0065] S400: If the shortest path along the forward direction and the shortest path along the reverse direction overlap, stop running the A* algorithm, and merge the shortest path segments obtained in the forward direction and the reverse direction to obtain the shortest path.
[0066] Specifically, it is to calculate from both the positive and negative dimensions simultaneously until the depth traversal paths in the two directions intersect.
[0067] The scheme of the above embodiment uses the intersection section data as the basis of path planning. The intersection section data only needs to include the intersection data, the section data of the section connected to the intersection, and the connection point data of the section and the intersection, thereby reducing the depth of data traversal and reducing the time complexity of the algorithm. When performing path planning, the A* algorithm is run in the positive direction and the reverse direction respectively to obtain the shortest path, and the one-way depth traversal is changed to the parallel calculation of the two-way depth traversal, further shortening the response time of the algorithm. Based on the above two reasons, the path planning method provided by the present application can optimize the navigation algorithm in the prior art, and has greatly improved the performance.
[0068] Preferably, in the path planning method described in 1, the step S100 of obtaining the intersection section data includes the intersection data, the section data of the section connected to the intersection, and the connection point data of the section and the intersection, including:
[0069] S101: Acquire original map data, extract intersections, road sections and connection points in the original map data to obtain map data.
[0070] The original map data is as follows Figure 3 Road network data shown.
[0071] S102: Filter the road sections within the intersection and the dead-end road sections in the map data.
[0072] The original map data has the following two problems: first, the road sections within the intersection do not need to be separately analyzed during route planning; second, the dead-end roads do not need to be separately analyzed during route planning. Therefore, when the application solution generates the intersection section data, the dead-end road sections and the road sections within the intersection need to be filtered out.
[0073] S103: assigning identifiers to the intersections, sections and connection points reserved in the map data to obtain the intersection and section data.
[0074] The above table 1 can be referred to for representation allocation. After deleting the dead-end road sections and the sections within the intersection, the final result is a road network of intersection sections with complete connectivity. Figure 4 Shown is Figure 3The original map data shown filters out dead-end road sections and sections within intersections, and the point data is intersection section data in the form of node points.
[0075] The data source of the intersection section data in this application is the original map data. The core logic of making the intersection section data is to merge the road data with connectivity and exclude the road data and dead-end road data within the intersection. If a merging situation is encountered, the road with the smallest angle change is selected. In this way, a road connecting the two intersections is obtained, and this road is the section in the intersection section data.
[0076] Furthermore, in the path planning method of the above scheme, in step S102, the filtering of the road sections within the intersection and the dead-end road sections in the map data is performed by filtering the road sections within the intersection in the following manner: determining whether the road section is within the intersection based on the road section attribute or the spatial position relationship between the intersection surface and the road line of the road section; filtering out the road sections within the intersection. Based on the original map data, it can be determined whether the coordinates of a certain road section are located within the intersection plane, thereby determining whether the road section is within the intersection. Further preferably, as Figure 5 As shown, the dead-end road section is filtered in the following manner: determine whether the current road section has a subsequent road section according to a recursive algorithm; if the current road section is not within the intersection and the current road section does not have a subsequent road section, the current road section is determined to be a dead-end road section and filtered. Figure 5 The recursive algorithm shown is performed. Figure 5 As shown, for the current road section, if it is not in an intersection and has no subsequent road section, it is considered to be a dead end road.
[0077] Preferably, in the path planning method, the step S300 of running the A* algorithm in the forward direction and the reverse direction respectively to determine the set of shortest path segments when the vehicle travels from the current position to the end position includes:
[0078] S301: Establish a set of path segments that have been reached in the positive direction S1 and a set of path segments that will be reached U1, and a set of path segments that have been reached in the reverse direction S2 and a set of path segments that will be reached U2.
[0079] S302: traverse all path segments in the set U1, select the first path segment with the shortest distance and then transfer the first path segment from the set U1 to the set S1; traverse all path segments in the set U2, select the second path segment with the shortest distance and then transfer the second path segment from the set U2 to the set S2.
[0080] S303: Determine along the positive direction whether the vehicle has reached the end position or whether the first path segment already exists in the set S2 to obtain a first judgment result, and determine along the reverse direction whether the vehicle has reached the start position or whether the second path segment already exists in the set S1 to obtain a second judgment result.
[0081] S304: If the first judgment result or the second judgment result is yes, all the first path segments in the set S1 and all the second path segments in the set S2 are merged into the set of the shortest path segments.
[0082] The present application scheme adopts the strategy of executing A* algorithm in both positive and negative directions, and searching in parallel, searching recursively from the starting position and the ending position in both directions. The logic of A* algorithm is to establish two sets S and U, which respectively represent the set of the path section that has been reached and the path section to be reached. The function of S set is to record the path section that has been traversed and reached, to prevent repeated traversal, and the function of U is to record the path section with the shortest distance from the starting and ending positions of the current path section. By operating the path sections in S and U, A* algorithm can be extended according to road connectivity. The extension in the reverse direction is opposite to the positive direction, and is calculated according to the reverse extension of the road, and the data structure involved is the same. Perform and extend operations from the positive direction and the negative direction until the two cross and meet, that is, the traversal of the path section is completed, which can greatly save the operation time compared to the method of traversing and extending along one direction.
[0083] Preferably, the traversal of all path segments in the set U1 and the selection of the first path segment with the shortest distance include: calculating the along-the-road distance d11 of all path segments that have been reached; calculating the straight-line distance d12 between the starting point and the end position of each path segment to be reached; and selecting the path segment to be reached that satisfies the minimum sum of d11 and d12 as the first path segment.
[0084] The traversal of all path segments in the set U2 and the selection of the second path segment with the shortest distance include: calculating the along-the-road distance d21 of all path segments that have been reached; calculating the straight-line distance d22 between the starting point and the end point of each path segment to be reached; and selecting the path segment to be reached that satisfies the minimum sum of d21 and d22 as the second path segment.
[0085] The specific traversal method is as follows Figure 7 In the scheme of this application, when traversing and extending in the forward and reverse directions, a general direction (towards the end position) is required. Therefore, the scheme of this application uses a heuristic method, that is, the straight-line distance from the current path section to the end position is used as the heuristic function (process Figure 7 d12 and d22 in the figure), the sum of the distance along the path and the heuristic distance of the reached path section is used as the screening basis, so as to ensure that the traversal extension direction does not deviate from the terminal position.
[0086] The present application also provides a path planning device, such as Figure 8 Said, including:
[0087] The intersection section data acquisition module 100 is configured to acquire intersection section data, wherein the intersection section data includes intersection data, section data of a section connected to the intersection, and connection point data of the section and the intersection;
[0088] The path planning module 200 is configured to obtain a starting position and an ending position of the path planning, merge the starting position and the ending position into the intersection section data, and obtain a plurality of initial planned paths according to the initial position and the ending position;
[0089] The path screening module 300 is configured to run the A* algorithm in a forward direction and a reverse direction for each of the initial planned paths, respectively, to determine a set of shortest path segments when the vehicle travels from the current position to the end position; wherein the direction of travel from the starting position to the end position is taken as the forward direction, and the direction of travel from the end position to the starting position is taken as the reverse direction;
[0090] The path output module 400 is configured to stop running the A* algorithm if the shortest path along the forward direction and the shortest path along the reverse direction overlap, and merge the shortest path segments obtained in the forward direction and the reverse direction to obtain the shortest path.
[0091] When the above-mentioned device provided in the present application is used for path planning, the intersection and road section data are used to reduce the depth of data traversal and reduce the time complexity of the algorithm; the bidirectional parallel A* algorithm is used to change the one-way depth traversal to the parallel calculation of the bidirectional depth traversal, further shortening the response time of the algorithm.
[0092] An embodiment of the present application also provides a computer-readable storage medium, in which program information is stored. After the computer reads the program information, the steps of the path planning method described in any of the above solutions are executed.
[0093] An embodiment of the present application also provides a computer program product, including a computer program / instruction, characterized in that when the computer program / instruction is executed by a processor, the steps of the path planning method described in any of the above solutions are implemented.
[0094] The present application also provides an electronic device, such as Fig. 9As shown, the electronic device includes at least one processor 91 and at least one memory 92, at least one of the memories 92 stores program information, and at least one of the processors 91 reads the program information and executes the path planning method described in any one of the above method embodiments. The device may also include: an input device 93 and an output device 94. The processor 91, the memory 92, the input device 93 and the output device 94 can be connected in communication. The memory 92, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The processor 91 executes various functional applications and data processing by running the non-volatile software programs, instructions and modules stored in the memory 92, that is, the path planning method provided by any of the above schemes is realized. The memory 92 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required by at least one function; the data storage area may store data created according to the use of the path planning method, etc. In addition, the memory 92 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 92 may optionally include a memory remotely arranged relative to the processor 91, and these remote memories may be connected to a device for executing the path planning method via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The input device 93 may receive input user clicks, and generate signal inputs related to user settings and function controls of the path planning method. The output device 94 may include a display device such as a display screen. When the one or more modules are stored in the memory 92, when the one or more processors 91 are run, the path planning method in any of the above-mentioned method embodiments is executed.
[0095] As needed, the above technical solutions can be combined to achieve the best technical effect.
[0096] The above are only the principles and preferred embodiments of the present application. It should be noted that, for ordinary technicians in this field, on the basis of the principles of the present application, several other modifications can be made, which should also be considered as the protection scope of the present application.
Claims
1. A path planning method, characterized in that: include: Acquire intersection section data, wherein the intersection section data includes intersection data, section data of a section connected to the intersection, and connection point data of the section and the intersection; Acquire the starting position and the ending position of the path planning, merge the starting position and the ending position into the intersection section data, and obtain multiple initial planned paths according to the initial position and the ending position; For each of the initial planned paths, the A* algorithm is run in a forward direction and a reverse direction respectively to determine a set of shortest path segments when the vehicle travels from the current position to the end position; wherein the direction of travel from the starting position to the end position is taken as the forward direction, and the direction of travel from the end position to the starting position is taken as the reverse direction; If the shortest path along the positive direction and the shortest path along the reverse direction overlap, the A* algorithm is stopped, and the shortest path segments obtained in the positive direction and the reverse direction are merged to obtain the shortest path.
2. The path planning method according to claim 1, characterized in that: The obtaining of intersection section data, wherein the intersection section data includes intersection data, section data of a section connected to the intersection, and connection point data of the section and the intersection, includes: Acquire original map data, extract intersections, road sections and connection points in the original map data to obtain map data; Filtering the road sections within the intersection and the dead-end road sections in the map data; Identifiers are assigned to the intersections, sections and connection points retained in the map data to obtain the intersection and section data.
3. The path planning method according to claim 2, characterized in that: In filtering the road sections within the intersection and the dead-end road sections in the map data, the road sections within the intersection are filtered in the following manner: Determine whether a road section is within an intersection based on the road section attributes or the spatial position relationship between the intersection surface and the road line of the road section; Filter out the road segments within the intersection.
4. The path planning method according to claim 2, characterized in that: In filtering the road sections within the intersection and the dead-end road sections in the map data, the dead-end road sections are filtered in the following manner: Determine whether the current road section has a subsequent road section according to a recursive algorithm; If the current road section is not within the intersection and there is no subsequent road section for the current road section, the current road section is determined to be an end road section and is filtered.
5. The path planning method according to any one of claims 1 to 4, characterized in that: The A* algorithm is run in the forward direction and the reverse direction respectively to determine the set of shortest path segments when the vehicle travels from the current position to the end position, including: Establish a set of path segments that have been reached in the positive direction S1 and a set of path segments that will be reached U1, and a set of path segments that have been reached in the reverse direction S2 and a set of path segments that will be reached U2; Traverse all path segments in the set U1, select the first path segment with the shortest distance, and then transfer the first path segment from the set U1 to the set S1; traverse all path segments in the set U2, select the second path segment with the shortest distance, and then transfer the second path segment from the set U2 to the set S2; A first judgment result is obtained by judging whether the vehicle has reached the end position or the first path segment already exists in the set S2 in the positive direction, and a second judgment result is obtained by judging whether the vehicle has reached the start position or the second path segment already exists in the set S1 in the reverse direction; If the first judgment result or the second judgment result is yes, all the first path segments in the set S1 and all the second path segments in the set S2 are merged into the set of the shortest path segments.
6. The path planning method according to claim 5, characterized in that: The traversing all the path segments in the set U1 and selecting the first path segment with the shortest distance includes: Calculate the distance d11 along all the route segments that have been reached; Calculate the straight-line distance d12 between the starting point and the end point of each path segment to be reached; Selecting a path segment to be reached that satisfies the minimum sum of d11 and d12 as the first path segment; The traversing all the path segments in the set U2 and selecting the second path segment with the shortest distance includes: Calculate the distance d21 along all the route segments that have been reached; Calculate the straight-line distance d22 between the starting point and the end point of each path segment to be reached; The path segment to be reached that satisfies the minimum sum of d21 and d22 is selected as the second path segment.
7. A path planning device, characterized in that: include: A road section data acquisition module is configured to acquire road section data of an intersection, wherein the road section data of the intersection includes road section data, road section data of a road section connected to the intersection, and connection point data of a road section and an intersection; A path planning module is configured to obtain a starting position and an ending position of the path planning, merge the starting position and the ending position into the intersection section data, and obtain a plurality of initial planned paths according to the initial position and the ending position; The path screening module is configured to run the A* algorithm in a forward direction and a reverse direction for each of the initial planned paths, respectively, to determine a set of shortest path segments when the vehicle travels from the current position to the end position; wherein the direction of travel from the starting position to the end position is taken as the forward direction, and the direction of travel from the end position to the starting position is taken as the reverse direction; The path output module is configured to stop running the A* algorithm if the shortest path along the positive direction and the shortest path along the reverse direction overlap, and merge the shortest path segments obtained in the positive direction and the reverse direction to obtain the shortest path.
8. A computer-readable storage medium, characterized in that: The storage medium stores program information, and the computer reads the program information and executes the steps of the path planning method according to any one of claims 1 to 6.
9. A computer program product, characterized in that The method comprises a computer program / instruction, wherein the computer program / instruction, when executed by a processor, implements the steps of the path planning method according to any one of claims 1 to 6.
10. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the path planning method according to any one of claims 1 to 6.