A vehicle driving path planning method and device and a vehicle controller
By utilizing drivable area information collected by multiple cameras for rasterization and Bézier curve planning, the problem of high cost of high-precision maps and LiDAR is solved, realizing low-cost autonomous driving path planning and avoiding unreasonable turns of vehicles at intersections.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- GUANGZHOU AUTOMOBILE GROUP CO LTD
- Filing Date
- 2021-03-11
- Publication Date
- 2026-06-19
Smart Images
Figure CN115077542B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of path planning technology, and in particular to a vehicle driving path planning method, a vehicle, and a vehicle controller. Background Technology
[0002] Urban road intersections are the most complex sections of road in terms of traffic conditions. Vehicle sensors alone are insufficient to effectively identify the shape of intersections, let alone determine their location and direction before entering them. Therefore, effective intersection positioning and guidance are crucial for rationally planning local paths at intersection turns. Currently, autonomous driving primarily relies on high-precision maps for high-precision global path planning, achieving lane-level accuracy. This is combined with laser point cloud information for positioning and obstacle detection, correcting local paths to enable intersection turns. However, high-precision maps and LiDAR solutions require extremely high-quality map information, are costly, and lack flexibility, making large-scale deployment on low-cost autonomous vehicles difficult. Summary of the Invention
[0003] The technical problem to be solved by the present invention is to provide a method, device and vehicle controller for planning the driving path of a vehicle at an intersection, so as to overcome the shortcomings of existing technologies such as high requirements for map information, high cost and poor flexibility of high-precision maps and lidar.
[0004] To address the aforementioned technical problems, the present invention provides a vehicle driving path planning method, comprising:
[0005] The system acquires the starting point location information, ending point location information, current vehicle location information, and current heading information for global path planning of the vehicle. Based on the starting point location information, ending point location information, current vehicle location information, and current heading information, the system determines the current navigation path information of the vehicle. It also acquires environmental images collected by multiple cameras installed on the vehicle in real time and determines the drivable area information of the vehicle based on the environmental images.
[0006] The vehicle's current location information, current heading information, current navigation path information, and drivable area information are respectively rasterized to obtain the vehicle's current location information, current heading information, current navigation path information, and drivable area information in the raster map.
[0007] Based on the current location information, current heading information, current navigation path information, and drivable area information in the grid map, the starting point, target point, and control point of the local planned path are determined. The local planned driving path is then determined based on the starting point, target point, and control point, and sent to the vehicle's autonomous driving decision module to control the vehicle to drive according to the local planned driving path.
[0008] Specifically, determining the starting point, target point, and control point of the local planned path based on the current location information, current heading information, current navigation path information, and drivable area information in the grid map includes:
[0009] The starting point is determined by the vehicle's current location information in the grid map. The target point is determined by the current navigation path information and the drivable area information in the grid map. The control point is determined by the vehicle's current heading extension line information and the current navigation path information in the grid map.
[0010] Specifically, determining the locally planned driving path based on the starting point, target point, and control point includes:
[0011] Substituting the coordinates of the starting point, the target point, and the control point into the Bézier curve formula, the expression for the Bézier curve is obtained.
[0012] Local path points are obtained by sampling at set intervals on the Bézier curve corresponding to the Bézier expression.
[0013] Specifically, determining the target point based on the current navigation path information in the grid map and the drivable area information in the grid map includes:
[0014] The system sequentially retrieves pathpoints for the current navigation path from the grid map. It then determines whether the retrieved pathpoint is within a drivable area of the grid map. If so, it retrieves the next pathpoint for the current navigation path and determines whether the next pathpoint is within a drivable area of the grid map. If the retrieved pathpoint is not within a drivable area of the grid map, it calculates the distance between the retrieved pathpoint and the retrieved previous pathpoint and further determines whether the distance is less than a set value. If the distance is less than the set value, the previous pathpoint is designated as the target. If the distance value is not less than a set value, then the midpoint between the previous path point and the current path point is further obtained, and it is determined whether the midpoint is in the drivable area of the grid map. If the midpoint is not in the drivable area of the grid map, then the midpoint is determined as the current extraction point, and the distance between the current extraction point and the previous path point is calculated. If the midpoint is in the drivable area of the grid map, then the midpoint is determined as the previous path point, and the distance between the current extraction point and the previous path point is calculated, until the target point corresponding to the currently extracted path point is obtained.
[0015] Specifically, determining the control point based on the vehicle's current heading extension information and the current navigation path information in the grid map includes:
[0016] Determine the intersection point between the vehicle's current heading extension line in the grid map and the current navigation path in the grid map;
[0017] Determine whether the intersection point is within the drivable area of the grid map. If so, determine the intersection point as the control point of the local path; otherwise, take a point on the extension line of the vehicle's current heading in the grid map as the control point of the local path.
[0018] A second aspect of the present invention provides a vehicle driving path planning device, comprising:
[0019] The current navigation path determination unit is used to acquire the starting point location information, ending point location information, current vehicle location information, and current navigation information of the vehicle's global path planning, and to determine the current navigation path of the vehicle based on the starting point location information, ending point location information, current vehicle location information, and current navigation information;
[0020] The feasible domain information determination unit is used to acquire environmental images collected by multiple cameras installed on the vehicle in real time, and determine the feasible domain information of the vehicle based on the environmental images.
[0021] The conversion unit is used to rasterize the vehicle's current location information, current heading information, current navigation path information, and drivable area information respectively, and obtain the vehicle's current location information, current heading information, current navigation path information, and drivable area information in the raster map.
[0022] The local path planning unit is used to determine the start point, target point, and control point of a locally planned path based on the current location information, current heading information, current navigation path information, and drivable area information in the grid map. It then determines the locally planned driving path based on the start point, target point, and control points, and sends the locally planned driving path to the vehicle's autonomous driving decision module, controlling the vehicle to drive according to the locally planned driving path.
[0023] Specifically, the local path planning unit includes:
[0024] The starting point determination unit is used to determine the current position of the vehicle in the grid map as the starting point of the locally planned driving path;
[0025] The target point determination unit is used to determine the target point of the locally planned driving path based on the current navigation path in the grid map and the feasible region of the grid map.
[0026] The control point determination unit is used to determine the control points of the locally planned driving path based on the vehicle's current heading extension line in the grid map and the current navigation path in the grid map.
[0027] The path determination unit is used to determine the local planned driving path based on the starting point, target point, and control point of the local planned driving path.
[0028] Specifically, the target point determination unit is used for:
[0029] The system sequentially retrieves pathpoints for the current navigation path from the grid map. It then determines whether the retrieved pathpoint is within a drivable area of the grid map. If so, it retrieves the next pathpoint for the current navigation path and determines whether the next pathpoint is within a drivable area of the grid map. If the retrieved pathpoint is not within a drivable area of the grid map, it calculates the distance between the retrieved pathpoint and the retrieved previous pathpoint and further determines whether the distance is less than a set value. If the distance is less than the set value, the previous pathpoint is designated as the target. If the distance value is not less than a set value, then the midpoint between the previous path point and the current path point is further obtained, and it is determined whether the midpoint is in the drivable area of the grid map. If the midpoint is not in the drivable area of the grid map, then the midpoint is determined as the current extraction point, and the distance between the current extraction point and the previous path point is calculated. If the midpoint is in the drivable area of the grid map, then the midpoint is determined as the previous path point, and the distance between the current extraction point and the previous path point is calculated, until the target point corresponding to the currently extracted path point is obtained.
[0030] Specifically, the control point determination unit is used for:
[0031] Determine the intersection point between the vehicle's current heading extension line in the grid map and the current navigation path in the grid map;
[0032] Determine whether the intersection point is within the drivable area of the grid map. If so, determine the intersection point as the control point of the local path; otherwise, take a point on the extension line of the vehicle's current heading in the grid map as the control point of the local path.
[0033] A third aspect of the present invention provides a vehicle controller, including a memory and a processor, wherein the memory stores computer-readable instructions, and when executed by the processor, the computer-readable instructions cause the processor to perform steps according to the aforementioned vehicle driving path planning method.
[0034] The beneficial effects of this invention are as follows: The vehicle path planning method of this invention forms a global navigation path based on the starting point and ending point location information, and forms drivable area information based on the image information collected by the vehicle. It then rasterizes the vehicle's current navigation path information, current location information, current heading information, and drivable area information, and determines the starting point, target point, and control point of the local planned path based on the rasterized information. Finally, it determines the local planned driving path based on the starting point, target point, and control point. This method eliminates the reliance on high-precision maps for path planning, effectively avoiding the disadvantages of high-precision map production difficulties, high usage costs, insufficient coverage, and difficulties in real-time data updates. Furthermore, it eliminates the need for point cloud collection of drivable areas using lidar, effectively reducing costs. Finally, this method can plan reasonable intersection path curves based on the global path planning and the limitations of the drivable area, effectively preventing problems such as vehicles entering oncoming lanes after turning. Attached Figure Description
[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0036] Figure 1 This is a flowchart illustrating a vehicle driving path planning method according to an embodiment of the present invention;
[0037] Figure 2 This is a more detailed flowchart of a vehicle driving path planning method according to an embodiment of the present invention;
[0038] Figure 3(a) is a schematic diagram of a partial path planning at a left-turn intersection according to an embodiment of the present invention.
[0039] Figure 3(b) is a schematic diagram of a right-turn intersection local path planning method according to an embodiment of the present invention;
[0040] Figure 4 This is a flowchart of the bisection method for finding the target point of a Bezier curve in a vehicle driving path planning method according to an embodiment of the present invention. Detailed Implementation
[0041] The following description of the embodiments is taken with reference to the accompanying drawings, which illustrate specific embodiments in which the invention can be implemented.
[0042] The following is for reference Figure 1As shown, Embodiment 1 of the present invention provides a vehicle driving path planning method, including the following steps:
[0043] S1. Obtain the starting point location information, ending point location information, current vehicle location information, and current heading information of the vehicle's global path planning; determine the current navigation path information of the vehicle based on the starting point location information, ending point location information, current vehicle location information, and current heading information; and obtain environmental images collected by multiple cameras installed on the vehicle in real time, and determine the drivable area information of the vehicle based on the environmental images.
[0044] In one specific implementation, road network data of a designated area is obtained, a global path is generated based on the starting point location information, the ending point location information, and the road network data, the current location information of the vehicle is obtained, the current road segment of the vehicle is determined based on the current location information and the global path, the path points of the current road segment and the path points of a set number of road segments after the current road segment are obtained, and the path points of the current road segment and the path points of the set number of road segments form the current navigation path.
[0045] Specifically, OpenStreetMap map data for a specified area is obtained from the OpenStreetMap website. This data contains information about the entire road network. By setting the start and end points of the global navigation path, a global navigation route containing only sparse pathpoints can be planned. Based on the current GPS information and the global navigation route planned by OpenStreetMap, the vehicle's current road segment can be located, and the pathpoints of the current segment and the pathpoints of the next nine road segments can be extracted as the current navigation route.
[0046] In one specific implementation, for the current frame image captured by each camera, a semantic segmentation algorithm based on deep learning is used to segment the road, obtaining road edge points. These road edge points are projected onto the vehicle coordinate system to obtain corresponding road edge points in the vehicle coordinate system. The road edge points in the vehicle coordinate system corresponding to the current frame images captured by all cameras are connected to form a first closed polygon region. This first closed polygon region represents the currently drivable area corresponding to the current frame images of all cameras. A second closed polygon region is formed by the road edge points in the vehicle coordinate system corresponding to the previous frame images captured by multiple cameras. This second closed polygon region represents the historical drivable area corresponding to the previous frame images of all cameras. The first and second closed polygon regions are transformed to obtain the first and second closed polygon regions in the world coordinate system. The first and second closed polygon regions in the world coordinate system are superimposed to obtain a third closed polygon region, which represents the drivable domain of the vehicle. By superimposing the first closed polygon region corresponding to the current frame image and the second closed polygon region corresponding to the previous frame image, drivable areas for consecutive frames can be obtained, creating drivable areas containing historical information.
[0047] By using visual sensors to acquire drivable areas from multiple cameras and multi-frame fusion, and thus obtaining drivable areas with historical information, vehicles can plan local paths within the drivable area, eliminating the need for LiDAR to collect point cloud data of the drivable area and effectively reducing costs.
[0048] S2. The vehicle's current location information, current heading information, current navigation path information, and drivable area information are rasterized respectively to obtain the vehicle's current location information, current heading information, current navigation path information, and drivable area information in the raster map.
[0049] In one specific implementation, the feasible region of the vehicle is converted into a binary map to obtain the feasible region of the grid map, and the current location information of the vehicle, the current navigation path, and the extension line of the current heading of the vehicle are projected onto the grid map respectively to obtain the current location information of the vehicle, the current navigation path, and the extension line of the current heading of the vehicle in the grid map.
[0050] S3. Determine the starting point, target point, and control point of the local planned path based on the current location information, current heading information, current navigation path information, and drivable area information in the grid map. Determine the local planned driving path based on the starting point, target point, and control point of the local planned path, and send the local planned driving path to the vehicle's autonomous driving decision module to control the vehicle to drive according to the local planned driving path.
[0051] Specifically, the current location information of the vehicle in the grid map is determined as the starting point of the local path. The target point of the local path is determined based on the current navigation path in the grid map and the feasible region of the grid map. The control point of the local path is determined based on the vehicle's current heading extension line in the grid map and the current navigation path in the grid map. The local planned driving path is determined based on the starting point, target point and control point of the local planned driving path.
[0052] Specifically, the pathpoints of the current navigation path in the grid map are retrieved sequentially. It is determined whether the retrieved pathpoint is within the drivable area of the grid map. If so, the next pathpoint of the current navigation path is retrieved from the grid map, and it is determined whether the next pathpoint is within the drivable area of the grid map. If the retrieved pathpoint is not within the drivable area of the grid map, the distance between the retrieved pathpoint and the retrieved previous pathpoint is calculated, and it is further determined whether the distance is less than a set value. If the distance is less than the set value, the previous pathpoint is determined as the drivable area of the current navigation path. If the distance value is not less than a set value, then the midpoint between the previous path point and the current path point is further obtained. It is determined whether the midpoint is in the drivable area of the grid map. If the midpoint is not in the drivable area of the grid map, the midpoint is determined as the current extraction point, and the distance between the current extraction point and the previous path point is calculated. If the midpoint is in the drivable area of the grid map, the midpoint is determined as the previous path point, and the distance between the current extraction point and the previous path point is calculated, until the target point corresponding to the currently extracted path point is obtained.
[0053] Specifically, the intersection of the vehicle's current heading extension line and the current navigation path in the grid map is determined, and it is determined whether the intersection point is in the feasible region of the grid map. If it is, the intersection point is determined as the control point of the local path; otherwise, a point is selected as the control point of the local path on the vehicle's current heading extension line in the grid map.
[0054] Specifically, the expression of the Bézier curve is obtained based on the starting point, target point, and control point of the local path. Path points of the local path are sampled at intervals of 0.5 meters on the Bézier curve. The coordinates of the path points of the planned local path are transformed into the world coordinate system. The path points of the local path are sent to the autonomous driving decision module in the form of a point set.
[0055] This invention discloses a vehicle path planning method that forms a global navigation path based on start-point and end-point location information, and forms feasible region information based on image information collected by the vehicle. The method rasterizes the vehicle's current navigation path, current location, current heading, and drivable area information, and determines the start-point, target point, and control points of a locally planned path based on the rasterized information. The method then determines the locally planned driving path based on the start-point, target point, and control points. This method eliminates the reliance on high-precision maps for path planning, effectively avoiding the drawbacks of high-precision map production difficulties, high costs, insufficient coverage, and difficulties in real-time data updates. Furthermore, it eliminates the need for point cloud collection of drivable areas using lidar, effectively reducing costs. Finally, this method can plan reasonable intersection path curves based on global path planning and drivable area constraints, effectively preventing problems such as vehicles entering oncoming lanes after turning.
[0056] In a specific embodiment of the present invention, such as Figure 2As shown, the starting and ending point information for global path planning is obtained. OpenStreetMap map data for the specified area is obtained from the OpenStreetMap website. Based on the starting and ending point information and the OpenStreetMap map data, the global path of the vehicle is planned. Then, combined with the vehicle's current position information and current heading angle information, the road segment in which the vehicle is located in the global path is determined. The path points of the current road segment and the next 9 road segments are extracted as the current navigation path. Environmental images around the vehicle are collected by multiple cameras installed on the vehicle. For each frame of image collected by each camera, the road is segmented using a deep learning semantic segmentation algorithm to obtain road edge points. The edge points are projected onto the vehicle coordinate system, and the projected point sets are connected to form a closed polymorph. The drivable areas corresponding to multiple frames of images collected by multiple cameras at the same time are superimposed to obtain a larger field of view of the drivable area. Based on the GPS information between consecutive frames, the drivable area of the current frame can be superimposed on the previous drivable area to obtain the drivable area corresponding to consecutive frames, thus creating a drivable area containing historical information. After obtaining the current navigation path point and drivable area, the drivable area is binarized to obtain drivable area information in the grid map. Similarly, the current navigation path, vehicle current position information, and vehicle current heading information are gridded to obtain the current navigation path information, vehicle current position information, and vehicle current heading information in the grid map. The vehicle current position is determined as the starting point of local location planning. Based on the vehicle current position information, vehicle current heading information, current navigation path, and drivable area information in the grid map, the target point of the local road path is found using the binary search method. The control point is determined based on the intersection of the vehicle heading extension line and the current navigation path in the grid map. The coordinates of the starting point, target point, and control point are substituted into the Bézier formula for solving to obtain the Bézier curve. A point is sampled every 0.5 meters on the Bézier curve to form the local planning path of the intersection. The specific local planning paths of the left-turn intersection and the right-turn intersection obtained by this method are shown in Figure 3(a) and Figure 3(b).
[0057] Specifically, a binary search method is used to find the target point of a local road path based on the vehicle's current location, current heading, current navigation path, and drivable area information in the grid map. Figure 4As shown, each path point ahead of the vehicle in the current navigation path is retrieved sequentially. It is determined whether the currently retrieved path point `point_out` is within the drivable area of the grid map. If `point_out` is within the drivable area, the next path point is retrieved and the process is repeated. If `point_out` is not within the drivable area, the previous path point `point_in` is retrieved, and the distance between the current path point and the previous path point `distance` is calculated. It is determined whether the distance is less than 1 meter. If the distance is less than 1 meter, the previous path point `point_in` is moved to the next path point. If n is determined as the target point, then the midpoint point point_middle between the current retrieval path point point_out and the previous path point point_in is determined. It is then determined whether this midpoint point_middle is within the drivable area of the grid map. If it is within the drivable area, then this midpoint is determined as the previous retrieval path point of the current retrieval path point, and the distance between the current retrieval path point and the previous path point is calculated. If this midpoint point_middle is not within the drivable area, then this midpoint is determined as the current retrieval path point, and the distance between the current retrieval path point and the previous retrieval path point is calculated, until the target point corresponding to the current retrieval path point is found.
[0058] Based on Embodiment 1 of the present invention, Embodiment 2 of the present invention provides a vehicle driving path planning device, including a current navigation path determination unit, a drivable area information determination unit, a conversion unit, and a local path planning unit. The current navigation path determination unit is used to acquire the starting point location information, ending point location information, current vehicle location information, and current navigation information of the vehicle's global path planning, and determine the current navigation path of the vehicle based on the starting point location information, ending point location information, current vehicle location information, and current navigation information. The drivable area information determination unit is used to acquire environmental images collected by multiple cameras installed on the vehicle in real time, and determine the drivable area information of the vehicle based on the environmental images. The conversion unit is used to convert the current navigation path of the vehicle into a drivable area information determination unit and a local path planning unit. The vehicle's current position information, current heading information, current navigation path information, and drivable area information are rasterized to obtain the vehicle's current position information, current heading information, current navigation path information, and drivable area information in the raster map. The local path planning unit is used to determine the start point, target point, and control point of the local planned path based on the current position information, current heading information, current navigation path information, and drivable area information in the raster map. The local planned driving path is determined based on the start point, target point, and control point, and the local planned driving path is sent to the vehicle's autonomous driving decision module to control the vehicle to drive according to the local planned driving path.
[0059] In one specific embodiment, the local path planning unit specifically includes a starting point determination unit, a target point determination unit, a control point determination unit, and a path determination unit. The starting point determination unit determines the vehicle's current position in the grid map as the starting point of the locally planned driving path. The target point determination unit determines the target point of the locally planned driving path based on the current navigation path in the grid map and the feasible region of the grid map. The control point determination unit determines the control point of the locally planned driving path based on the vehicle's current heading extension line in the grid map and the current navigation path in the grid map. The path determination unit determines the locally planned driving path based on the starting point, target point, and control point of the locally planned driving path.
[0060] In one specific embodiment, the target point determination unit is specifically used to sequentially extract path points of the current navigation path in the grid map, determine whether the currently extracted path point is within the drivable area of the grid map, and if so, extract the next path point of the current navigation path in the grid map and determine whether the next path point is within the drivable area of the grid map. If the currently extracted path point is not within the drivable area of the grid map, calculate the distance between the currently extracted path point and the extracted previous path point, and further determine whether the distance value is less than a set value. If the distance value is less than the set value, then... The previous path point is determined as the target point. If the distance value is not less than a set value, the midpoint between the previous path point and the current path point is further obtained. It is determined whether the midpoint is in the drivable area of the grid map. If the midpoint is not in the drivable area of the grid map, the midpoint is determined as the current extraction point, and the distance between the current extraction point and the previous path point is calculated. If the midpoint is in the drivable area of the grid map, the midpoint is determined as the previous path point, and the distance between the current extraction point and the previous path point is calculated, until the target point corresponding to the currently extracted path point is obtained.
[0061] In one specific embodiment, the control point determination unit is specifically used to determine the intersection of the vehicle's current heading extension line in the grid map and the current navigation path in the grid map, and to determine whether the intersection point is in the drivable area in the grid map. If so, the intersection point is determined as the control point of the local path; otherwise, a point is selected as the control point of the local path on the vehicle's current heading extension line in the grid map.
[0062] A third aspect of the present invention provides a vehicle controller, including a memory and a processor, wherein the memory stores computer-readable instructions, and when executed by the processor, the computer-readable instructions cause the processor to perform the steps of the vehicle driving path planning method according to the above embodiments.
[0063] Of course, the vehicle controller may also have wired or wireless network interfaces, keyboards, and input / output interfaces for input and output. The vehicle controller may also include other components for implementing device functions, which will not be elaborated here.
[0064] For example, the computer program may be divided into one or more units, which are stored in the memory and executed by the processor to perform the present invention. The one or more units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the vehicle controller.
[0065] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the vehicle controller, connecting various parts of the vehicle controller via various interfaces and lines.
[0066] The memory can be used to store the computer program and / or units. The processor implements various functions of the vehicle controller by running or executing the computer program and / or units stored in the memory and by calling data stored in the memory. Furthermore, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device. For the working principle and beneficial effects of this embodiment, please refer to the description of Embodiment 1 of the present invention, which will not be repeated here.
[0067] The above description discloses only preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.
Claims
1. A vehicle travel path planning method, characterized in that, include: The system acquires the starting point location information, ending point location information, current vehicle location information, and current heading information for global path planning of the vehicle. Based on the starting point location information, ending point location information, current vehicle location information, and current heading information, the system determines the current navigation path of the vehicle. It also acquires environmental images collected by multiple cameras installed on the vehicle in real time and determines the drivable area information of the vehicle based on the environmental images. The vehicle's current location information, current heading information, current navigation path information, and drivable area information are respectively rasterized to obtain the vehicle's current location information, current heading information, current navigation path information, and drivable area information in the raster map. The starting point, target point, and control point of a locally planned driving path are determined based on the vehicle's current location information, current heading information, current navigation path information, and drivable area information in the grid map. Specifically, the vehicle's current location information in the grid map is determined as the starting point of the locally planned driving path; the target point is determined based on the current navigation path information and drivable area information in the grid map; and the control point is determined based on the vehicle's current heading extension line information and current navigation path information in the grid map. The locally planned driving path is then determined based on the starting point, target point, and control point, and is sent to the vehicle's autonomous driving decision module to control the vehicle to drive according to the locally planned driving path.
2. The method according to claim 1, characterized in that, The step of determining the locally planned driving path based on the starting point, target point, and control point of the locally planned driving path specifically includes: Substituting the coordinates of the starting point, target point, and control point of the locally planned driving path into the Bézier curve formula, the expression for the Bézier curve is obtained. Local path points are obtained by sampling at set intervals on the Bézier curve corresponding to the Bézier curve expression.
3. The method according to claim 2, characterized in that, The step of determining the target point based on the current navigation path information in the grid map and the drivable area information in the grid map specifically includes: The system sequentially retrieves pathpoints for the current navigation path from the grid map. It then determines whether the retrieved pathpoint is within a drivable area of the grid map. If so, it retrieves the next pathpoint for the current navigation path and determines whether the next pathpoint is within a drivable area of the grid map. If the retrieved pathpoint is not within a drivable area of the grid map, it calculates the distance between the retrieved pathpoint and the retrieved previous pathpoint and further determines whether the distance is less than a set value. If the distance is less than the set value, the previous pathpoint is designated as the target point. If the distance value is not less than a set value, then the midpoint between the previous path point and the currently retrieved path point is further obtained, and it is determined whether the midpoint is in the drivable area of the grid map. If the midpoint is not in the drivable area of the grid map, then the midpoint is determined as the current retrieval point, and the distance between the current retrieval point and the previous path point is calculated. If the midpoint is in the drivable area of the grid map, then the midpoint is determined as the previous path point, and the distance between the current retrieval point and the previous path point is calculated, until the target point corresponding to the currently retrieved path point is obtained.
4. The method according to claim 3, characterized in that, The step of determining the control points for the local path based on the vehicle's current heading extension line in the grid map and the current navigation path in the grid map specifically includes: Determine the intersection point between the vehicle's current heading extension line in the grid map and the current navigation path in the grid map; Determine whether the intersection point is within the feasible region of the grid map. If so, determine the intersection point as the control point of the local path; otherwise, take a point on the extension line of the vehicle's current heading in the grid map as the control point of the local path.
5. A vehicle driving path planning device, characterized in that, include: The current navigation path determination unit is used to acquire the starting point location information, ending point location information, current vehicle location information, and current navigation information of the vehicle's global path planning, and to determine the current navigation path of the vehicle based on the starting point location information, ending point location information, current vehicle location information, and current navigation information; The feasible domain information determination unit is used to acquire environmental images collected by multiple cameras installed on the vehicle in real time, and determine the feasible domain information of the vehicle based on the environmental images. The conversion unit is used to rasterize the vehicle's current location information, current heading information, current navigation path information, and drivable area information respectively, and obtain the vehicle's current location information, current heading information, current navigation path information, and drivable area information in the raster map. The local path planning unit is used to determine the starting point, target point, and control point of the local planned driving path based on the current location information, current heading information, current navigation path information, and drivable area information in the grid map, determine the local planned driving path based on the starting point, target point, and control point, and send the local planned driving path to the vehicle's autonomous driving decision module to control the vehicle to drive according to the local planned driving path; The local path planning unit specifically includes: The starting point determination unit is used to determine the current position of the vehicle in the grid map as the starting point of the locally planned driving path; The target point determination unit is used to determine the target point of the locally planned driving path based on the current navigation path in the grid map and the feasible region of the grid map. The control point determination unit is used to determine the control points of the locally planned driving path based on the vehicle's current heading extension line in the grid map and the current navigation path in the grid map. The path determination unit is used to determine the local planned driving path based on the starting point, target point, and control point of the local planned driving path.
6. The apparatus according to claim 5, characterized in that, The target point determination unit is specifically used for: The system sequentially retrieves pathpoints for the current navigation path from the grid map. It then determines whether the retrieved pathpoint is within a drivable area of the grid map. If so, it retrieves the next pathpoint for the current navigation path and determines whether the next pathpoint is within a drivable area of the grid map. If the retrieved pathpoint is not within a drivable area of the grid map, it calculates the distance between the retrieved pathpoint and the retrieved previous pathpoint and further determines whether the distance is less than a set value. If the distance is less than the set value, the previous pathpoint is designated as the target point. If the distance value is not less than a set value, then the midpoint between the previous path point and the currently retrieved path point is further obtained, and it is determined whether the midpoint is in the drivable area of the grid map. If the midpoint is not in the drivable area of the grid map, then the midpoint is determined as the current retrieval point, and the distance between the current retrieval point and the previous path point is calculated. If the midpoint is in the drivable area of the grid map, then the midpoint is determined as the previous path point, and the distance between the current retrieval point and the previous path point is calculated, until the target point corresponding to the currently retrieved path point is obtained.
7. The apparatus according to claim 5, characterized in that, The control point determination unit is specifically used for: Determine the intersection point between the vehicle's current heading extension line in the grid map and the current navigation path in the grid map; Determine whether the intersection point is within the drivable area of the grid map. If so, determine the intersection point as the control point of the locally planned driving path. Otherwise, take a point on the extension line of the vehicle's current heading in the grid map as the control point of the locally planned driving path.
8. A vehicle controller, comprising a memory and a processor, the memory storing computer-readable instructions, which, when executed by the processor, cause the processor to perform the steps of the vehicle driving path planning method according to any one of claims 1-4.