Vehicle route planning methods and electronic equipment

Abstract

This application provides a vehicle driving path planning method and electronic device. The method includes: determining the current target grid map corresponding to the target vehicle based on the current vehicle status information of the target vehicle, and determining the occupancy matrix information and occupancy line segment information corresponding to the current target grid map; determining the grid occupancy rate of the target grid within a first range along the driving direction of the target vehicle based on the occupancy matrix information, and determining the line segment occupancy rate of the target line segment corresponding to the target grid within the first range based on the occupancy line segment information; and determining the driving path information of the target vehicle based on the grid occupancy rate of the target grid within the first range and the line segment occupancy rate of the target line segment corresponding to the target grid within the first range. This effectively improves the accuracy of vehicle driving path planning in confined space scenarios, thereby improving vehicle traffic efficiency and driving safety.

Description

Technical Field

[0001] This application relates to the field of vehicle path planning technology, and in particular to a vehicle path planning method and electronic device. Background Technology

[0002] With the development of vehicle intelligence, assisted driving functions can plan the vehicle's trajectory based on the surrounding environment and quickly select and execute the optimal path. However, in narrow spaces such as underground parking garages, due to limited drivable roads, dim lighting, and large areas occupied by obstacles, assisted driving functions suffer from inaccurate path planning, including low obstacle recognition accuracy and the inability to anticipate potential conflicts. This affects vehicle traffic efficiency and driving safety. In other words, existing technologies address the challenge of improving the accuracy of vehicle path planning in narrow spaces to enhance traffic efficiency and driving safety. Summary of the Invention

[0003] This application provides a vehicle driving path planning method and electronic device to solve the problem in the prior art of how to improve the accuracy of vehicle driving path planning in narrow space scenarios, thereby improving vehicle traffic efficiency and vehicle driving safety.

[0004] To address the aforementioned technical problems, in a first aspect, this application discloses a vehicle driving path planning method. The method includes: determining a current target grid map corresponding to the target vehicle based on the current vehicle status information of the target vehicle; determining occupancy matrix information and occupancy line segment information corresponding to the current target grid map; the occupancy matrix information includes grid occupancy rate information of multiple target grids included in the current target grid map; the occupancy line segment information includes line segment occupancy rate information corresponding to target line segments connecting the left and right boundaries of the road where the target vehicle is located; determining the grid occupancy rate of target grids within a first range along the driving direction of the target vehicle based on the occupancy matrix information; determining the line segment occupancy rate of target line segments corresponding to target grids within the first range based on the occupancy line segment information; and determining the driving path information of the target vehicle based on the grid occupancy rate of target grids within the first range and the line segment occupancy rate of target line segments corresponding to target grids within the first range.

[0005] By employing the above technical solution, the current target grid map corresponding to the target vehicle can be determined based on the target vehicle's current vehicle status information. This involves determining the occupancy matrix information (including grid occupancy rate information for multiple target grids) and the occupancy line segment information (including line segment occupancy rate information for target line segments connecting the left and right boundaries of the road where the target vehicle is located). Then, based on the occupancy matrix information, the grid occupancy rate of target grids within a first range along the target vehicle's driving direction is determined. Furthermore, based on the occupancy line segment information, the line segment occupancy rate of target line segments corresponding to target grids within the first range is determined. Finally, based on the grid occupancy rate of target grids and the line segment occupancy rate of target line segments within the first range, the driving path information of the target vehicle is determined. Therefore, in the process of determining the vehicle's driving path, information from the narrow space scenario in which the target vehicle is driving can be projected onto the grid map, and path planning can be performed for the target vehicle based on the grid occupancy rate information and the line segment occupancy rate information. This effectively improves the accuracy of vehicle driving path planning in narrow space scenarios, thereby improving vehicle traffic efficiency and driving safety.

[0006] According to another specific implementation of this application, a vehicle driving path planning method is disclosed in this implementation. Based on the grid occupancy rate of a target grid within a first range and the segment occupancy rate of the target line segment corresponding to the target grid within the first range, the driving path information of a target vehicle is determined. This includes: if the maximum value of the grid occupancy rate is greater than a first occupancy rate threshold, determining the current planned driving path corresponding to the target vehicle as a collision path, and adjusting the current planned driving path corresponding to the target vehicle to determine the driving path information of the target vehicle; if the maximum value of the grid occupancy rate is less than a second occupancy rate threshold, determining the current planned driving path corresponding to the target vehicle as a safe path, and determining the driving path information of the target vehicle based on the current planned driving path corresponding to the target vehicle. The driving path information of the target vehicle is determined. If the maximum value of the grid occupancy rate is less than or equal to the first occupancy rate threshold and greater than or equal to the second occupancy rate threshold, the current planned driving path corresponding to the target vehicle is determined as a dangerous path. Furthermore, if the segment occupancy rate of the target line segment corresponding to the target grid in the first range is greater than the third occupancy rate threshold, the grid occupancy rate of the target grid in the second range in the driving direction of the target vehicle is determined according to the occupancy matrix information, and the segment occupancy rate of the target line segment corresponding to the target grid in the second range is determined according to the occupancy line segment information. Based on the grid occupancy rate of the target grid in the second range and the segment occupancy rate of the target line segment corresponding to the target grid in the second range, the driving path information of the target vehicle is determined.

[0007] By employing the above technical solution, the type of the current planned driving path for the target vehicle (i.e., collision, dangerous, or safe path) is determined based on the grid occupancy rate of the target grid within the first range. Then, based on the path type and the segment occupancy rate of the target line segments corresponding to the target grid within the first range, the current planned driving path for the target vehicle is determined or adjusted, thereby determining the accurate driving path information of the target vehicle. This effectively improves the accuracy of vehicle driving path planning in narrow spaces, thereby improving vehicle traffic efficiency and driving safety.

[0008] According to another specific implementation of this application, the implementation of this application discloses a vehicle driving path planning method, the method comprising: determining the current target grid map corresponding to the target vehicle by: determining the driving road boundary information corresponding to the target vehicle based on the current vehicle status information of the target vehicle, the driving road boundary information including the right boundary information and the left boundary information of the driving road; and determining the current target grid map corresponding to the target vehicle based on the current vehicle status information and the driving road boundary information.

[0009] By adopting the above technical solution, the accurate driving road boundary information corresponding to the target vehicle can be determined based on the current vehicle status information of the target vehicle, thereby improving the accuracy of the current target grid map corresponding to the target vehicle.

[0010] According to another specific implementation of this application, a vehicle driving path planning method is disclosed in this implementation. Based on the current vehicle status information and driving road boundary information of the target vehicle, the method determines the current target grid map corresponding to the target vehicle, including: determining the initial grid map range based on the right boundary information and left boundary information of the driving road; determining the initial grid map origin point information based on the current vehicle status information of the target vehicle; and determining the current target grid map corresponding to the target vehicle based on the initial grid map range, the initial grid map origin point information, and a preset grid resolution.

[0011] By adopting the above technical solution, the accuracy of the current target grid map corresponding to the identified target vehicle is effectively improved.

[0012] According to another specific implementation of this application, a vehicle driving path planning method is disclosed in this implementation. The method includes determining occupancy matrix information in the following ways: determining the inner boundary grid and outer boundary grid of the current target grid map based on the driving road boundary information, wherein the inner boundary grid is the grid located in the area between the right boundary and the left boundary of the driving road, and the outer boundary grid is the grid located outside the area between the right boundary and the left boundary of the driving road; determining the target plane occupancy area of ​​the target obstacle; determining the first occupancy rate corresponding to the inner boundary grid based on the target plane occupancy area; and determining the occupancy matrix information based on the first occupancy rate corresponding to the inner boundary grid and the preset second occupancy rate corresponding to the outer boundary grid.

[0013] The above technical solution first determines the inner and outer grids of the current target grid map based on the road boundary information. Then, based on the first occupancy rate of the inner grids determined by the target plane occupancy area of ​​the target obstacle, and the preset second occupancy rate of the outer grids, the occupancy matrix information is determined. This improves the accuracy of the occupancy matrix information, thereby improving the accuracy of the target vehicle's travel path planned based on grid occupancy rate information and line segment occupancy rate information.

[0014] According to another specific implementation of this application, a vehicle driving path planning method is disclosed in this implementation. Based on the driving road boundary information, it determines the inner and outer grids of multiple target grids, including: connecting corresponding points of the right and left boundaries of the driving road to obtain multiple connecting line segments; obtaining multiple first planar graphics based on the multiple connecting line segments; and dividing the multiple target grids included in the current target grid map into blocks to obtain multiple first grid blocks, each first grid block including at least one target grid; and determining the inner and outer grids of the current target grid map based on the position information of the first planar graphics and the position information of the first grid blocks.

[0015] By using the above technical solution, it is possible to obtain accurate intra-boundary and extra-boundary rasters included in the current target raster map.

[0016] According to another specific implementation of this application, the vehicle driving path planning method disclosed in this implementation further includes: if the first grid block is determined to be a boundary grid intersecting with the road boundary based on the position information of the first planar graphic and the position information of the first grid block, the first grid block is divided into multiple second grid blocks, and the inner boundary grid and outer boundary grid included in the first grid block are determined based on the position information of the first planar graphic and the position information of the second grid blocks.

[0017] By adopting the above technical solution, the accurate inner and outer grid cells included in the first grid block can be obtained.

[0018] According to another specific implementation of this application, a vehicle driving path planning method disclosed in this implementation method determines a first occupancy rate corresponding to a grid within a boundary based on the target plane's occupied area. This includes: determining a second planar graphic corresponding to the grid within the boundary; if the second planar graphic corresponding to the grid within the boundary is located within the target plane's occupied area, determining the grid within the boundary as a fully occupied grid, and determining the first occupancy rate corresponding to the grid within the boundary as a first target value; if the second planar graphic corresponding to the grid within the boundary is located outside the target plane's occupied area, determining the grid within the boundary as an unoccupied grid, and determining the first occupancy rate corresponding to the grid within the boundary as a second target value; if the second planar graphic corresponding to the grid within the boundary intersects with the target plane's occupied area, dividing the grid within the boundary into sub-grids within the boundary, and determining the first occupancy rate corresponding to the grid within the boundary based on the relative positional relationship between the third planar graphic corresponding to the sub-grid within the boundary and the target plane's occupied area.

[0019] By adopting the above technical solution, the accuracy of the first occupancy rate corresponding to the grid within the boundary is effectively improved based on the relative positional relationship between the second planar graphic corresponding to the grid within the boundary and the target plane occupied area corresponding to the target obstacle.

[0020] According to another specific implementation of this application, the implementation of this application discloses a vehicle driving path planning method, which includes determining the occupied line segment information by: connecting the corresponding target points of the right boundary and the left boundary of the driving road to obtain multiple target line segments; determining the target grids passed by the target line segments; determining the line segment occupancy information corresponding to the target line segments based on the grid occupancy information corresponding to the target grids passed by the target line segments; and determining the occupied line segment information based on the line segment occupancy information.

[0021] By adopting the above technical solution, the occupancy information of the target grid corresponding to the target grid obtained by connecting the corresponding target points of the right boundary and the left boundary of the driving road is more accurate, thereby improving the accuracy of the determined occupancy information.

[0022] Secondly, this application also discloses a vehicle driving path planning device, comprising: a first processing module, configured to determine the current target grid map corresponding to the target vehicle based on the current vehicle status information of the target vehicle, and to determine the occupancy matrix information and occupancy line segment information corresponding to the current target grid map, wherein the occupancy matrix information includes grid occupancy rate information of multiple target grids included in the current target grid map, and the occupancy line segment information includes line segment occupancy rate information corresponding to the target line segment connecting the left and right boundaries of the road where the target vehicle is located; a second processing module, configured to determine the grid occupancy rate of the target grids within a first range in the driving direction of the target vehicle based on the occupancy matrix information, and to determine the line segment occupancy rate of the target line segments corresponding to the target grids within the first range based on the occupancy line segment information; and a third processing module, configured to determine the driving path information of the target vehicle based on the grid occupancy rate of the target grids within the first range and the line segment occupancy rate of the target line segments corresponding to the target grids within the first range.

[0023] Thirdly, this application also discloses an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores a computer program; the processor executes the computer program stored in the memory to enable the electronic device to perform the corresponding processing in the vehicle driving path planning method provided by any of the implementations of the first aspect above.

[0024] Fourthly, the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, is used to implement the corresponding processing in the vehicle driving path planning method provided by any of the implementations of the first aspect above.

[0025] Fifthly, an implementation of this application provides a computer program product, including a computer program that, when executed by a processor, implements the corresponding processing in the vehicle driving path planning method provided by any of the implementations of the first aspect above.

[0026] It is understood that the beneficial effects of the second to fifth aspects mentioned above can also be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0027] Figure 1 This is a schematic flowchart of a vehicle driving path planning method provided in an embodiment of this application;

[0028] Figure 2 This is a schematic diagram of a grid block and road area segmentation Polygond2d provided in an embodiment of this application;

[0029] Figure 3This is a schematic diagram of a grid map with occupancy rate in a scenario where two vehicles occupy the center of the road, as provided in an embodiment of this application.

[0030] Figure 4 This is a schematic diagram of a target line segment connecting the left and right boundaries of the road where the target vehicle is located, provided in an embodiment of this application.

[0031] Figure 5 This is a flowchart illustrating how to determine the current target grid map corresponding to a target vehicle based on the vehicle status information of the target vehicle, as provided in this application embodiment.

[0032] Figure 6 This is a flowchart illustrating how to determine the current target grid map corresponding to a target vehicle based on the vehicle status information and the driving road boundary information provided in this application embodiment.

[0033] Figure 7 This is a flowchart illustrating a method for determining occupancy matrix information provided in an embodiment of this application;

[0034] Figure 8 This is a flowchart illustrating how to determine the inner and outer grid cells of the current target grid map based on the boundary information of the driving road, according to an embodiment of this application.

[0035] Figure 9 This is a schematic diagram of a grid corresponding to a sub-graph provided in an embodiment of this application;

[0036] Figure 10 This is a flowchart illustrating a method for determining occupied line segment information provided in an embodiment of this application;

[0037] Figure 11 This is a schematic diagram of a vehicle driving path planning device provided in an embodiment of this application.

[0038] Figure 12 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0039] As mentioned earlier, there is a problem in the existing technology of how to improve the accuracy of vehicle driving path planning in narrow space scenarios, thereby improving vehicle traffic efficiency and vehicle driving safety.

[0040] Based on this, this application provides a vehicle driving path planning method. During the determination of the vehicle driving path, information from the narrow space scenario in which the target vehicle is driving is projected onto a grid map, and path planning is performed for the target vehicle based on grid occupancy information and line segment occupancy information. This effectively improves the accuracy of vehicle driving path planning in narrow space scenarios, thereby improving vehicle traffic efficiency and driving safety.

[0041] Next, with reference to the accompanying drawings, the steps and advantages of the vehicle driving path planning method provided in this application will be described in detail.

[0042] First, the mathematical symbols used in this application will be explained. The units of all mathematical symbols and their corresponding variables are in the International System of Units (SI).

[0043] : Running frame, corresponding to i=0 as the initial frame.

[0044] : The timestamp of the i-th frame.

[0045] The state of the vehicle observed in the i-th frame, specifically the state variable is: , representing the x-coordinate, y-coordinate, and yaw angle of the vehicle, respectively. Bicycle motion curvature Bicycle speed Vehicle acceleration .

[0046] Global reference lines consist of a series of reference points, corresponding to the states of those reference points. for , representing the x-coordinate, y-coordinate, and yaw angle of the reference point, respectively. Bicycle motion curvature and vehicle mileage .

[0047] Global map boundary information, including the left and right boundaries. The format of the map boundaries is similar to that of reference lines, consisting of a series of boundary points. Each boundary point corresponds one-to-one with a reference line and has [specific characteristics]. The state description, where s represents the s value of the point on the corresponding reference line.

[0048] : The state of the j-th obstacle observed in the i-th frame, where the obstacle is of type Polygon2d (planar polygon).

[0049] : The raster map built from the observation of the i-th frame, where k represents the depth of the raster map, and is obtained through... This represents the set of all parent and child raster maps in the i-th frame.

[0050] The parameter set for the raster map includes the following:

[0051] The original point corresponding to the raster map.

[0052] The minimum x, maximum x, minimum y, and maximum y coordinates of the raster map.

[0053] : Resolution of the raster map.

[0054] Raster index is The corresponding grid has a single grid cell with a Box2d (planar rectangle) appearance type.

[0055] : grid The corresponding occupancy rate has a value range of [0,1].

[0056] : The occupancy matrix corresponding to the raster map established in the i-th frame.

[0057] : All boundary connecting line segments within the range of the i-th frame raster map, i.e., road segments.

[0058] In one implementation of this application, such as Figure 1 As shown, the vehicle driving path planning method provided in this application includes the following steps.

[0059] S100: Based on the current vehicle status information of the target vehicle, determine the current target grid map corresponding to the target vehicle, as well as the occupancy matrix information and occupancy line segment information corresponding to the current target grid map.

[0060] The occupancy matrix information includes the grid occupancy rate information of multiple target grids included in the current target grid map, and the occupancy line segment information includes the line segment occupancy rate information corresponding to the target line segment connecting the left and right boundaries of the road where the target vehicle is located.

[0061] The current target grid map, which is the grid map corresponding to the current frame (e.g., the i-th frame) in which the target vehicle is traveling, and the current vehicle status information, which is the vehicle status information corresponding to the current frame (e.g., the i-th frame).

[0062] For example, such as Figure 2The diagram shows a defined current target raster map. The coordinates include X-coordinates (XCoordinate) and Y-coordinates (Y Coordinate). The yellow arrowed line represents the target vehicle's direction of travel. The blue lines represent the left and right boundaries of the road during the target vehicle's travel. The green area represents the extent of the current target raster map at the current moment of the target vehicle's travel, and the small green squares represent the target rasters included in the current target raster map. Information indicated by the red and yellow boxes will be explained later.

[0063] like Figure 3 The image shows a raster map with occupancy rates (i.e., grid occupancy rates) in a scenario where two vehicles occupy the center of the road. Different colors of the target grid represent different occupancy rates, and the specific occupancy rate corresponds to the color in the image, as shown below. Figure 3 The grid potential value is shown on the right. The potential value for the target grid outside the boundary is 2.0.

[0064] like Figure 4 The diagram illustrates the segmentation method for the target line segment connecting the left and right boundaries of the road where the target vehicle is located. In the diagram, the black line between the left and right boundaries of the road represents the target line segment connecting the left and right boundaries of the road where the target vehicle is located.

[0065] S200: Based on the occupancy matrix information, determine the grid occupancy rate of the target grid within the first range along the target vehicle's driving direction, and based on the occupancy line segment information, determine the line segment occupancy rate of the target line segment corresponding to the target grid within the first range.

[0066] The first range can be a certain distance within the preset target vehicle's direction of travel. For example, when the vehicle is driving forward, starting from the front of the vehicle, the range can be a certain distance ahead (e.g., 0.3 meters, 0.4 meters, 0.5 meters, 0.6 meters, etc., which can be set as needed) and the front wheel turning angle can be a certain angle (e.g., 10 degrees, 15 degrees, etc., which can be set as needed). Or when the vehicle is reversing, starting from the rear of the vehicle, the range can be a certain distance backward (e.g., 0.3 meters, 0.4 meters, 0.5 meters, 0.6 meters, etc., which can be set as needed) and the front wheel turning angle can be a certain angle (e.g., 10 degrees, 15 degrees, etc., which can be set as needed).

[0067] S300: Determine the driving path information of the target vehicle based on the grid occupancy rate of the target grid within the first range and the line segment occupancy rate of the target line segment corresponding to the target grid within the first range.

[0068] The vehicle path planning method provided in this application can determine the current target grid map corresponding to the target vehicle based on the target vehicle's current vehicle status information, and determine the occupancy matrix information, which includes grid occupancy rate information of multiple target grids, and the occupancy line segment information, which includes the line segment occupancy rate information of the target line segments connecting the left and right boundaries of the road where the target vehicle is located. Then, based on the occupancy matrix information, the grid occupancy rate of the target grids within a first range in the target vehicle's driving direction is determined, and based on the occupancy line segment information, the line segment occupancy rate of the target line segments corresponding to the target grids within the first range is determined. Finally, based on the grid occupancy rate of the target grids within the first range and the line segment occupancy rate of the target line segments corresponding to the target grids within the first range, the driving path information of the target vehicle is determined. Therefore, in the process of determining the vehicle driving path, information in the narrow space scene where the target vehicle is driving can be projected onto the grid map, and path planning can be performed for the target vehicle based on the grid occupancy rate information and the line segment occupancy rate information. This effectively improves the accuracy of vehicle driving path planning in narrow space scenes, thereby improving vehicle traffic efficiency and driving safety.

[0069] In one implementation of this application, determining the driving path information of a target vehicle based on the grid occupancy rate of the target grid within a first range and the segment occupancy rate of the target line segment corresponding to the target grid within the first range includes: if the maximum value of the grid occupancy rate is greater than a first occupancy rate threshold, determining the current planned driving path corresponding to the target vehicle as a collision path, adjusting the current planned driving path corresponding to the target vehicle, and thus determining the driving path information of the target vehicle; if the maximum value of the grid occupancy rate is less than a second occupancy rate threshold, determining the current planned driving path corresponding to the target vehicle as a safe path, and thus determining the driving path information of the target vehicle based on the current planned driving path corresponding to the target vehicle. If the maximum value of the grid occupancy rate is less than or equal to the first occupancy rate threshold and greater than or equal to the second occupancy rate threshold, the current planned driving path corresponding to the target vehicle is determined to be a dangerous path. Furthermore, if the segment occupancy rate of the target line segment corresponding to the target grid in the first range is greater than the third occupancy rate threshold, the grid occupancy rate of the target grid in the second range in the direction of the target vehicle is determined according to the occupancy matrix information, and the segment occupancy rate of the target line segment corresponding to the target grid in the second range is determined according to the occupancy line segment information. Based on the grid occupancy rate of the target grid in the second range and the segment occupancy rate of the target line segment corresponding to the target grid in the second range, the driving path information of the target vehicle is determined.

[0070] In one implementation of this application, after determining the target grid map and the corresponding occupancy matrix information and occupancy line segment information, a hybrid A* algorithm is used to explore (i.e. plan) the target vehicle's path. This method treats the target vehicle as a rigid object and the target vehicle's running state in each frame as the node to be explored, and performs path planning for the target vehicle.

[0071] In one implementation of this application, the path planning of the target vehicle uses the following logic related to the occupancy map (i.e., a grid map with grid occupancy).

[0072] Logical judgment is made based on the maximum occupancy rate of all occupied grids (i.e., the target grid) of the node.

[0073] Specifically, if the maximum occupancy rate is greater than the upper threshold, it is considered a collision node; if the maximum occupancy rate is less than the lower threshold, it is considered a safe node; and if the maximum occupancy rate is between the upper and lower thresholds, it is considered a dangerous node. When a node is determined to be a dangerous node, the angular interval of the exploration process of the node preceding the dangerous node is reduced to increase the exploration accuracy, and exploration is performed again.

[0074] For example, as mentioned earlier, when a vehicle is driving ahead, the first exploration range includes the area where the front wheel angle of the vehicle is 10 degrees. If the planned path of the target vehicle is a dangerous path when the exploration range is determined to be the first range, the exploration range can be modified, for example, to the second exploration range, which is the area where the front wheel angle of the vehicle is 5 degrees.

[0075] Furthermore, the relevant logic for the path planning of the target vehicle using occupied interval segments (i.e., segment occupancy information) is as follows.

[0076] Find the grid corresponding to the current target vehicle node coordinates. and find the grid The nearest connecting line segment (For example, the target line segment mentioned above, passing through the grid) (center), if If there is a large occupancy rate in all connecting line segments within a range of s in front or behind (which can be set as needed), then increase the exploration accuracy of the corresponding forward or backward node, i.e., reduce the exploration angle interval and the length of each exploration; otherwise, reduce the exploration accuracy of the current node.

[0077] For example, when a vehicle is driving ahead, the first exploration range includes a distance of 0.3 meters in front of the vehicle. If the planned path of the target vehicle is a dangerous path when the first exploration range is determined, the exploration range can be modified, for example, to a second exploration range, which includes a distance of 0.2 meters in front of the vehicle.

[0078] Further location, if If there is a large occupancy rate among all connecting segments within a range of s in front or behind (which can be set as needed), an additional exploration is temporarily performed. That is, the nearest occupant segment in front or behind is found, and the center of the largest sub-segment into which the occupant segment is divided is taken as the exploration endpoint. A Hill-Climbing (HC) connection is performed. If the HC connection is successful, the node after the HC connection is taken as the priority node for the next exploration.

[0079] In one implementation of this application, such as Figure 5 As shown, determining the current target grid map corresponding to the target vehicle includes the following steps.

[0080] S110: Determine the road boundary information corresponding to the target vehicle based on the target vehicle's current vehicle status information.

[0081] The road boundary information includes the right boundary information and the left boundary information of the road.

[0082] S120: Determine the current target grid map corresponding to the target vehicle based on the target vehicle's current vehicle status information and the driving road boundary information.

[0083] In one implementation of this application, such as Figure 6 As shown, the current target grid map corresponding to the target vehicle is determined based on the current vehicle status information and the driving road boundary information, including the following steps.

[0084] S121: Determine the initial grid map range based on the right boundary information and left boundary information of the driving road.

[0085] S122: Determine the initial grid map origin point information based on the current vehicle status information of the target vehicle.

[0086] S123: Determine the current target grid map corresponding to the target vehicle based on the initial grid map range, the initial grid map origin point information, and the preset grid resolution.

[0087] For example, currently running as the number Frame, corresponding to the vehicle's state ,Will Corresponding coordinates As the parent image of the current frame raster Original point parameters, i.e.

[0088]

[0089]

[0090] Based on the projection method of the vehicle's current position, it can be projected onto the reference line. Find the corresponding vehicle matching point .

[0091] Based on vehicle matching point This allows for further acquisition of the vehicle's position on the reference line. The s value of the upper match .

[0092] At the vehicle matching point Taking a certain range forward and backward, we get A reference line .

[0093] according to Obtain the left and right boundaries of a road segment .

[0094] According to the left and right boundaries of the road The maximum and minimum x and y coordinates occupied are obtained. The map range, i.e.

[0095]

[0096]

[0097]

[0098]

[0099] in and In order to ensure The remaining amount of all points within the map.

[0100] Based on the map parameters obtained above, and the preset map resolution It can construct a complete basic raster parent image. .

[0101] In one implementation of this application, such as Figure 7 As shown, determining the occupancy matrix information includes the following steps.

[0102] S130: Based on the road boundary information, determine the grid cells within and outside the boundary included in the current target grid map.

[0103] Among them, the grid inside the boundary is the grid located in the area between the right boundary and the left boundary of the driving road, and the grid outside the boundary is the grid located outside the area between the right boundary and the left boundary of the driving road.

[0104] For example, the boundary envelope region is constructed first.

[0105] like Figure 2 As shown, in the constructed basic grid map (i.e. the current target grid map), by connecting the corresponding points of the left and right boundary points and the line segments of the left and right boundaries, a Polygon2d graphic can be formed (such as the graphic enclosed by the yellow line segments). Then, the grid corresponding to the envelope area of ​​all Polygon2d formed by the left and right boundaries is the grid within the boundary.

[0106] Then, grid segmentation is performed.

[0107] Divide the raster (i.e., the target raster) into N*N (e.g., 4*4) blocks. For example... Figure 2 The red rectangle in the image corresponds to a 4x4 grid block, from which a grid block list can be obtained. .

[0108] The boundary corresponds to polygon segments.

[0109] The s value is divided into segments at intervals ds, and each segment generates a Polygon2d region, thus obtaining a list of Polygon2d regions at the boundary. .

[0110] Traversal and The relative positions of raster block B and boundary Polygon2d region P are detected respectively, and the raster blocks are grouped.

[0111] If all grid cells within a grid block are within the left and right boundaries, then the target grid cell within the grid block is determined to be completely within the left and right boundaries. If all grid cells within a grid block are outside the left and right boundaries, then the target grid cell within the grid block is determined to be completely outside the left and right boundaries. If any grid cell within a grid block intersects with the left and right boundaries, then a subgraph is created within the grid, all grid cells in the subgraph are traversed, and precise calculations are performed with the intersecting Polygon2d cells. If the current grid resolution is already less than the critical value, then even if the grid cell intersects with the boundary, it is considered to be outside the boundary.

[0112] Finally, the relative positions of all grids and boundaries in the multi-level parent-child graph can be obtained, and in the lowest level subgraph, the grids only exist in two states: inside the boundary and outside the boundary.

[0113] In one implementation of this application, such as Figure 8 As shown, based on the road boundary information, the grid cells within and outside the boundary of the current target grid map are determined, including the following steps.

[0114] S131: Connect the corresponding points of the right boundary and the left boundary of the driving road to obtain multiple connecting line segments.

[0115] S132: Based on multiple connecting line segments, multiple first planar figures are obtained.

[0116] S133: Divide the current target raster map into multiple target rasters to obtain multiple first raster blocks, each first raster block including at least one target raster.

[0117] S134: Based on the position information of the first planar graphic and the position information of the first grid block, determine the grid cells within the boundary and the grid cells outside the boundary included in the current target grid map.

[0118] In one implementation of this application, the method further includes: if the first grid block is determined to be a boundary grid intersecting with the road boundary based on the position information of the first planar graphic and the position information of the first grid block, the first grid block is divided into multiple second grid blocks, and the inner boundary grid and outer boundary grid included in the first grid block are determined based on the position information of the first planar graphic and the position information of the second grid blocks.

[0119] S140: Determine the target plane area occupied by the target obstacle.

[0120] S150: Determine the first occupancy rate of the grid cells within the boundary based on the target plane's occupied area.

[0121] S160: Determine the occupancy matrix information based on the first occupancy rate corresponding to the grid inside the boundary and the preset second occupancy rate corresponding to the grid outside the boundary.

[0122] For example, firstly, obstacle projection is performed, which involves projecting all obstacles perceived at the current moment. Project onto the raster map (i.e., the current target raster map) and generate a raster map atlas. .

[0123] A: Traverse all obstacles and obtain any... The corresponding Polygon2d occupies the area of ​​the plane (i.e., the area occupied by the target plane). and Then, based on the occupied area, iterate through all the grids (i.e., the target grid) within this area.

[0124] If the Box2d region of the grid is completely within Within the corresponding Polygon2d region, the raster is considered to be fully occupied, denoted as... .

[0125] If the Box2d region of the grid is completely within Outside the corresponding Polygon2d region, the raster is considered to occupy no space at all, denoted as... .

[0126] If the grid Box2d region and If the corresponding Polygon2d regions intersect, it is considered that the raster partially occupies the raster, and further processing is performed in the subgraph.

[0127] B: For the partially occupied raster set in step A Establish specified parameters within each grid region of the grid set. By selecting appropriate parameters for the subgraph, the maximum and minimum [x, y] regions corresponding to the subgraph will be exactly the Box2d region of the raster.

[0128] For example, such as Figure 9 As shown, in the original green target raster area, the division parameters are: The subgraph (i.e., the yellow area includes multiple grids).

[0129] C: Continuing to repeat processes A and B in the sub-map will yield the obstacles in the sub-grid map. The projection continues until the raster resolution of the subgraph is less than a critical value.

[0130] D: Finally, we can obtain a set of raster maps containing only fully occupied and completely unoccupied maps. .

[0131] Then, the occupancy matrix (i.e., occupancy matrix information) is constructed.

[0132] Based on the resolution of the smallest subgraph, it can be... The occupancy of all grids is converted into a matrix. Specifically, the occupancy value of the outer grid is set to 2.0.

[0133] The map created by the aforementioned steps and the corresponding occupancy matrix If i > 0, meaning for each frame during the target vehicle's movement, the occupancy matrix can be updated using the following formula:

[0134]

[0135] in, Let w be the occupancy matrix corresponding to the i-th frame, and w be the update weight. This is the occupancy matrix corresponding to frame i-1.

[0136] If the occupancy rate is less than the threshold, the occupancy rate is considered to be 0.

[0137] That is, in one implementation of this application, determining the first occupancy rate of the grid within the boundary based on the target plane occupancy area includes the following steps.

[0138] Determine the second planar graphic corresponding to the grid within the boundary.

[0139] If the second planar graphic corresponding to the grid within the boundary is located within the target plane's occupied area, the grid within the boundary is determined to be a fully occupied grid, and the first occupancy rate corresponding to the grid within the boundary is determined to be the first target value.

[0140] If the second planar graphic corresponding to the grid within the boundary is located outside the target plane's occupied area, the grid within the boundary is determined to be an unoccupied grid, and the first occupancy rate corresponding to the grid within the boundary is determined to be the second target value.

[0141] If the second planar graphic corresponding to the grid within the boundary intersects with the area occupied by the target plane, the grid within the boundary is divided to obtain sub-grids within the boundary. Based on the relative positional relationship between the third planar graphic corresponding to the sub-grid within the boundary and the area occupied by the target plane, the first occupancy rate corresponding to the grid within the boundary is determined.

[0142] In one implementation of this application, a method for quickly obtaining the occupied grid in the path planning of a target vehicle is provided.

[0143] This path planning method employs a hybrid A* exploration approach combined with HC curves, setting the exploration endpoint as a point on the reference line relatively far from the vehicle. During each path search, all occupied grid cells can be retrieved based on the Box2d corresponding to the node's state. Since the Box2d dimensions corresponding to each vehicle's node are identical, and the map grid is linear, key-value pairs matching the grid indices and occupied grid cells of the vehicle's Box2d at different relative positions and angles are pre-stored. Real-time lookups are then performed based on these key-value pairs. Because the pre-stored calculations do not require real-time execution, the computational cost of grid lookups is significantly reduced.

[0144] For any raster The grid can be divided into regions of size n*n. Each region has center coordinates, thus obtaining the set of center coordinates for the grid. .

[0145] The angle [0, 2pi] is determined according to... Discretize the angles to obtain a set of angles uniformly distributed in the interval [0, 2π]. .

[0146] By traversing the center coordinate set and angle set, and based on the obtained center coordinate and angle pairs, as well as the vehicle parameters, the corresponding Box2d can be generated. Subsequently, the list of raster relative indices occupied by the Box2d can be calculated. The relative index list represents the target raster and the source raster. The relative index. Ultimately, this can be obtained with the center coordinates and angle. As the key, a list of raster relative indices key-value pairs with values List.

[0147] In real-time path planning, for any node, the node state can be used as a basis for decision-making. Find the node occupying the grid Then find the nearest center of this grid. The closest angle After that, you can Quickly retrieve the relative indices of all occupied grid cells corresponding to a node in the list, and finally obtain all occupied grid cells based on the relative indices.

[0148] In one implementation of this application, such as Figure 10 As shown, determining the occupied line segment information includes the following steps.

[0149] S10: Connect the corresponding target points on the right and left boundaries of the driving road to obtain multiple target line segments.

[0150] S20: Determine the target grid that the target line segment passes through.

[0151] S30: Determine the segment occupancy information corresponding to the target segment based on the grid occupancy information of the target grid through which the target segment passes.

[0152] S40: Determine the occupied line segment information based on the line segment occupancy rate information.

[0153] For example, this part also involves road segment processing, which preprocesses the map grid (i.e., the target grid) in the direction of the road.

[0154] At regular intervals (distances smaller than the minimum obstacle size for general perception and detection), corresponding line segments (i.e., target line segments) are formed by connecting the boundary points, such as... Figure 4 As shown by the black lines in the diagram, these line segments are defined as .

[0155] Calculate the line segment set separately Each line segment occupies a grid, and the occupancy rate list of the occupied grids is used as the occupancy rate list of the line segments (i.e., occupied line segment information), and the information is stored in the corresponding line segment.

[0156] Specifically, if a line segment does not pass through a grid cell with a high occupancy rate, it is considered an unoccupied line segment; otherwise, it is considered an occupied line segment. For occupied line segments, the length of the consecutive unoccupied interval is taken as the maximum unoccupied value of the line segment. The consecutive unoccupied interval is the length of the target line segment that has not passed through any occupied grid cells.

[0157] The vehicle driving path planning method provided in this application is designed for narrow space scenarios in underground parking lots. By projecting elements such as obstacles and boundaries onto a grid map, it provides grid occupancy rates and road segment occupancy rates. Furthermore, by using pre-calculated grid occupancy information and occupancy rate information of the vehicle itself during the path planning process, the success rate of path planning in this scenario is improved.

[0158] In summary, the vehicle driving path planning method provided in this application may include the following steps.

[0159] First, based on the vehicle's status, determine the original point parameters of the basic raster parent image and the left and right boundaries of the road corresponding to the vehicle. Then, based on the left and right road boundaries, determine the map extent of the basic raster parent image. Finally, based on the original point parameters, map extent, and preset raster resolution, create the basic raster map (i.e., the current target raster map, also known as the basic raster parent image).

[0160] Then, based on the position of each grid cell in the basic grid map and the positional relationship between the left and right boundaries of the road, the grid cells inside and outside the boundaries in the basic grid map are determined.

[0161] Traverse all obstacles perceived at the current moment and obtain the occupied area of ​​the corresponding planar graphic in the basic grid map. Based on the occupied area and the positional relationship of each grid, determine the occupancy rate of each grid in the basic grid map. Based on the occupancy rate of each grid, obtain the occupancy rate matrix.

[0162] In the basic grid map, at intervals (this distance should be smaller than the minimum obstacle size for general perception and detection), the corresponding boundary points are connected to form line segments. The occupied grid of each line segment is calculated, and the occupancy rate list of the occupied grid is used as the occupancy rate list of the line segments. The information is stored in the corresponding line segments.

[0163] Specifically, if a line segment does not pass through a grid cell with a high occupancy rate, it is considered an unoccupied line segment; otherwise, it is considered an occupied line segment. For occupied line segments, the length of the consecutive unoccupied intervals is taken as the maximum unoccupied value of the line segment.

[0164] Finally, based on the grid information traversed by the vehicle (which can be considered a node at this point), the planned driving path of the vehicle is determined. Specifically, if the maximum occupancy rate in the grid is greater than the upper threshold, it is considered a collision node (meaning the vehicle's planned driving path is at risk of collision and needs to be replanned). If the maximum occupancy rate is less than the lower threshold, it is considered a safe node. If the maximum occupancy rate is between the upper and lower thresholds, it is considered a dangerous node.

[0165] For each dangerous node, locate the grid corresponding to the current node's coordinates and find the nearest connecting line segment. If all connecting line segments within a range of 's' (which can be set as needed) in front of or behind this connecting line segment have a high occupancy rate, increase the exploration accuracy of the corresponding forward or backward node, i.e., decrease the exploration angle interval and the length of each exploration; otherwise, decrease the exploration accuracy of the current node.

[0166] The vehicle path planning method provided in this application generates a distribution law regarding uncertainty based on the observed obstacle type and motion state, ensuring good distance preservation between the generated trajectory and obstacles. It projects some road features onto a grid map, and optimizes the exploration process using these road features during path planning. It pre-reserves some fixed calculation results for the grid map to reduce computational consumption during path planning. It applies a block-based and subgraph-based approach to accurately calculate the grid cells occupied by obstacles.

[0167] like Figure 11 As shown, this application also provides a vehicle driving path planning device, including: a first processing module, used to determine the current target grid map corresponding to the target vehicle based on the current vehicle status information of the target vehicle, and to determine the occupancy matrix information and occupancy line segment information corresponding to the current target grid map, wherein the occupancy matrix information includes the grid occupancy rate information of multiple target grids included in the current target grid map, and the occupancy line segment information includes the line segment occupancy rate information corresponding to the target line segment connecting the left and right boundaries of the road where the target vehicle is located; a second processing module, used to determine the grid occupancy rate of the target grids within a first range in the driving direction of the target vehicle based on the occupancy matrix information, and to determine the line segment occupancy rate of the target line segments corresponding to the target grids within the first range based on the occupancy line segment information; and a third processing module, used to determine the driving path information of the target vehicle based on the grid occupancy rate of the target grids within the first range and the line segment occupancy rate of the target line segments corresponding to the target grids within the first range.

[0168] The vehicle driving path planning device provided in this application may further include more modules for performing the steps in the aforementioned vehicle driving path planning method.

[0169] In one implementation of this application, a vehicle is also provided that can implement the aforementioned vehicle driving path planning method.

[0170] like Figure 12 As shown in the embodiments of this application, an electronic device is also provided, including: a processor and a memory communicatively connected to the processor; the memory stores a computer program; the processor executes the computer program stored in the memory to enable the electronic device to implement the corresponding technical solution in the vehicle driving path planning method described above.

[0171] This application also provides a chip for executing instructions, which is used to execute the corresponding technical solutions in the vehicle driving path planning method in the above embodiments.

[0172] This application also provides a computer-readable storage medium storing computer instructions. When these computer instructions are executed on the vehicle's processor, the vehicle's processor performs the corresponding technical solution in the vehicle driving path planning method described above.

[0173] This application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When the at least one processor executes the computer program, it can implement the corresponding technical solution in the vehicle driving path planning method in the above embodiments.

[0174] This application is described with reference to flowchart illustrations and / or block diagrams of the methods, apparatus, and computer program products according to this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable information processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable information processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0175] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable information processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0176] These computer program instructions may also be loaded onto a computer or other programmable information processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0177] It should be noted that, in addition to the specific embodiments described above, those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Although the description of this application is presented in conjunction with preferred embodiments, this does not mean that the features of this invention are limited to this implementation. On the contrary, the purpose of describing the invention in conjunction with the implementation is to cover other options or modifications that may be derived based on the claims of this application. To provide a thorough understanding of this application, many specific details are included in the above description, and this application may also be implemented without using these details. Furthermore, to avoid confusion or obscuring the focus of this application, some specific details will be omitted in the description. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other.

[0178] It should be noted that in this specification, similar reference numerals and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0179] Although this application has been illustrated and described with reference to certain preferred embodiments, those skilled in the art should understand that the above description is a further detailed explanation of the application in conjunction with specific implementations, and should not be construed as limiting the specific implementation of the application to these descriptions. Those skilled in the art can make various changes in form and detail, including some simple deductions or substitutions, without departing from the spirit and scope of this application.

Claims

1. A vehicle travel path planning method characterized by comprising: The method comprises: According to the current vehicle state information of the target vehicle, the current target grid map corresponding to the target vehicle is determined, and the occupation matrix information and the occupation line segment information corresponding to the current target grid map are determined, the occupation matrix information comprises the grid occupation rate information of a plurality of target grids included in the current target grid map, and the occupation line segment information comprises the line segment occupation rate information corresponding to the target line segment connecting the left and right boundaries of the road where the target vehicle is located; According to the occupation matrix information, the grid occupation rate of the target grid in the first range in the driving direction of the target vehicle is determined, and according to the occupation line segment information, the line segment occupation rate of the target line segment corresponding to the target grid in the first range is determined; According to the grid occupation rate of the target grid in the first range and the line segment occupation rate of the target line segment corresponding to the target grid in the first range, the driving path information of the target vehicle is determined, wherein the driving path information of the target vehicle is determined according to the grid occupation rate of the target grid in the first range and the line segment occupation rate of the target line segment corresponding to the target grid in the first range, comprising: In the case that the maximum value in the grid occupation rate is greater than the first occupation rate threshold, it is determined that the current planned driving path corresponding to the target vehicle is a collision path, and the current planned driving path corresponding to the target vehicle is adjusted to determine the driving path information of the target vehicle; In the case that the maximum value in the grid occupation rate is less than the second occupation rate threshold, it is determined that the current planned driving path corresponding to the target vehicle is a safe path, and the driving path information of the target vehicle is determined according to the current planned driving path corresponding to the target vehicle; In the case that the maximum value in the grid occupation rate is less than or equal to the first occupation rate threshold and greater than or equal to the second occupation rate threshold, it is determined that the current planned driving path corresponding to the target vehicle is a dangerous path, and in the case that the line segment occupation rate of the target line segment corresponding to the target grid in the first range is greater than the third occupation rate threshold, the grid occupation rate of the target grid in the second range in the driving direction of the target vehicle is determined according to the occupation matrix information, and the line segment occupation rate of the target line segment corresponding to the target grid in the second range is determined according to the occupation line segment information, and the driving path information of the target vehicle is determined according to the grid occupation rate of the target grid in the second range and the line segment occupation rate of the target line segment corresponding to the target grid in the second range.

2. The vehicle travel path planning method according to claim 1, characterized by, The method comprises determining the current target grid map corresponding to the target vehicle by the following way: According to the current vehicle state information of the target vehicle, the driving road boundary information corresponding to the target vehicle is determined, the driving road boundary information comprises driving road right boundary information and driving road left boundary information; According to the current vehicle state information of the target vehicle and the driving road boundary information, a current target grid map corresponding to the target vehicle is determined.

3. The vehicle travel path planning method according to claim 2, characterized by, According to the current vehicle state information of the target vehicle and the driving road boundary information, a current target grid map corresponding to the target vehicle is determined, including: According to the driving road right boundary information and the driving road left boundary information, an initial grid map range is determined; According to the current vehicle state information of the target vehicle, initial grid map original point information is determined; According to the initial grid map range, the initial grid map original point information and a preset grid resolution, the current target grid map corresponding to the target vehicle is determined.

4. The vehicle travel path planning method according to claim 3, characterized by, The method includes determining the occupancy matrix information by the following ways: According to the driving road boundary information, the boundary inside grid and the boundary outside grid included in the current target grid map are determined, the boundary inside grid is a grid located in the area between the driving road right boundary and the driving road left boundary, and the boundary outside grid is a grid located outside the area between the driving road right boundary and the driving road left boundary; A target plane occupancy area of the target obstacle is determined; According to the target plane occupancy area, a first occupancy rate corresponding to the boundary inside grid is determined; According to the first occupancy rate corresponding to the boundary inside grid and a preset second occupancy rate corresponding to the boundary outside grid, the occupancy matrix information is determined.

5. The vehicle travel path planning method according to claim 4, characterized by, According to the driving road boundary information, the boundary inside grid and the boundary outside grid included in the current target grid map are determined, including: Connecting corresponding points of the driving road right boundary and the driving road left boundary to obtain a plurality of connection line segments; According to the plurality of connection line segments, a plurality of first plane graphics are obtained; and The plurality of target grids included in the current target grid map are subjected to block processing to obtain a plurality of first grid blocks, and each first grid block includes at least one target grid; According to the position information of the first plane graphic and the position information of the first grid block, the boundary inside grid and the boundary outside grid included in the current target grid map are determined.

6. The vehicle travel path planning method according to claim 5, characterized by, The method further includes: If it is determined according to the position information of the first plane graphic and the position information of the first grid block that the first grid block is a boundary grid intersecting with the road boundary, the first grid block is subjected to block processing to obtain a plurality of second grid blocks, and according to the position information of the first plane graphic and the position information of the second grid block, the boundary inside grid and the boundary outside grid included in the first grid block are determined.

7. The vehicle travel path planning method according to claim 6, characterized by, According to the target plane occupancy area, a first occupancy rate corresponding to the boundary inside grid is determined, including: A second plane graphic corresponding to the boundary inside grid is determined; If the second plane graphic corresponding to the boundary inside grid is located in the target plane occupancy area, it is determined that the boundary inside grid is a completely occupied grid, and a first occupancy rate corresponding to the boundary inside grid is determined as a first target value; If the second planar graph corresponding to the boundary-in-grid is located outside the target planar occupancy region, the boundary-in-grid is determined as an unoccupied grid, and a first occupancy rate corresponding to the boundary-in-grid is determined as a second target value; If the second planar graph corresponding to the boundary-in-grid intersects with the target planar occupancy region, the boundary-in-grid is divided to obtain a boundary-in-sub-grid, and a first occupancy rate corresponding to the boundary-in-grid is determined according to a relative positional relationship between a third planar graph corresponding to the boundary-in-sub-grid and the target planar occupancy region.

8. The vehicle travel path planning method according to any one of claims 1-7, characterized by, The method comprises determining the occupancy line segment information by the following ways: Connecting corresponding target points of the right boundary of the driving road and the left boundary of the driving road to obtain a plurality of target line segments; Determining the target grid passed by the target line segment; Determining line segment occupancy rate information corresponding to the target line segment according to the grid occupancy rate information corresponding to the target grid passed by the target line segment; Determining the occupancy line segment information according to the line segment occupancy rate information.

9. An electronic device, comprising: Comprise: A processor, and a memory connected in communication with the processor; The memory stores a computer program; The processor executes the computer program stored in the memory, so that the electronic device implements the vehicle driving path planning method according to any one of claims 1-8.

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