Vehicle path planning method and device and vehicle

Abstract

The invention provides a vehicle path planning method and device and a vehicle. The method comprises the steps that current vehicle position information, vehicle state information and obstacle position information of a vehicle in the process of executing preset driving operation are acquired; according to the global path key point information and the vehicle position information, determining the position information of the target global path key point and the vehicle state information; the plurality of global path key points are determined based on a global planning path corresponding to the driving operation; and based on a quintic spline difference algorithm, according to the vehicle position information, the vehicle state information, the obstacle position information, the position information of the target global path key point and the vehicle state information, determining a path planning trajectory of the vehicle from the current position to the target global path key point. According to the scheme, the calculation amount can be reduced, the path planning efficiency is improved, and the path planning trajectory is deviated to the global path.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle path planning, and in particular to a vehicle path planning method, device and vehicle. Background Art

[0002] With the development of technology, vehicle trajectory planning can be performed to help vehicles choose the shortest and fastest path, avoid congestion and busy roads to improve driving efficiency, and avoid dangerous areas and traffic accident risks to ensure that vehicles can reach their destination efficiently and safely.

[0003] In related technologies, path planning includes global path planning and local path planning. Global path planning is only applicable when the activity area information is known. Although local path planning can be used when the environment is unknown, it has the problem of large computational complexity and cannot obtain the global optimal path. Summary of the Invention

[0004] The present application aims to provide a vehicle path planning method, device and vehicle.

[0005] According to a first aspect of the present application, a vehicle path planning method is provided, comprising:

[0006] Obtaining the current vehicle position information, vehicle status information, and obstacle position information of the vehicle during the execution of a preset driving operation;

[0007] Determining the position information and vehicle status information of a target global path key point based on the global path key point information and the vehicle position information; wherein the global path key point information includes the position information and vehicle status information corresponding to each of a plurality of global path key points; the plurality of global path key points are determined based on the global planned path corresponding to the driving operation;

[0008] Based on the quintic spline interpolation algorithm, the path planning trajectory from the vehicle's current position to the target global path key point is determined according to the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the target global path key point.

[0009] As a possible implementation method, the position information of the target global path key point and the vehicle state information are determined based on the global path key point information and the vehicle position information, including:

[0010] Determine, based on the vehicle position information, a first global path key point that is located after the current position and closest to the current position from a plurality of global path key points;

[0011] The first global path key point is determined as the target global path key point, and the position information and vehicle state information of the first global path key point are determined as the position information and vehicle state information of the target global path key point.

[0012] In some embodiments of the present application, the global path key point information is obtained in advance through the following steps:

[0013] Perform global path planning for driving operations based on a graph search algorithm to obtain a global path point set;

[0014] Select multiple global path key points from the global path point set;

[0015] Determine the position information and vehicle status information corresponding to multiple global path key points.

[0016] As a possible implementation method, multiple global path key points are selected from the global path point set, including:

[0017] Get multiple landmark points from the global path point set;

[0018] Based on multiple landmark points, multiple global path key points are determined.

[0019] In some embodiments, based on the plurality of landmark points, a plurality of global path key points are determined, including:

[0020] Determine the number of multiple landmark points;

[0021] According to the multiple landmark points and their quantities, multiple global path key points are determined.

[0022] As an example, multiple global path key points are determined based on multiple landmark points and their numbers, including:

[0023] If the number of multiple landmark points is less than a preset landmark point threshold, at least one new landmark point is added based on the global path point set so that the number of newly added landmark points reaches the landmark point threshold;

[0024] The multiple landmark points and at least one newly added landmark point are determined as multiple global path key points.

[0025] As another example, multiple global path key points are determined based on multiple landmark points and their numbers, including:

[0026] If the number of the multiple landmark points is greater than or equal to a preset landmark point threshold, the multiple landmark points are determined as multiple global path key points.

[0027] In some embodiments of the present application, a path planning trajectory between a vehicle's current position and a target global path key point is determined based on a quintic spline interpolation algorithm according to vehicle position information, vehicle state information, obstacle position information, and position information and vehicle state information of a target global path key point, including:

[0028] Based on the quintic spline interpolation algorithm, the candidate driving trajectory between the vehicle's current position and the target global path key point is determined according to the vehicle's position information, vehicle status information, and the position information and vehicle status information of the target global path key point;

[0029] Verify the candidate driving trajectory based on the obstacle location information;

[0030] If the candidate driving trajectory is successfully verified, the candidate driving trajectory is determined as the path planning trajectory between the vehicle's current position and the target global path key point;

[0031] If the candidate driving trajectory fails to be verified, a second global path keypoint is added between the current position and the target global path keypoint based on the current obstacle position information;

[0032] Determining position information and vehicle state information of a second global path key point;

[0033] Based on the quintic spline interpolation algorithm, the path planning trajectory of the vehicle from the current position to the second global path key point is determined according to the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the second global path key point.

[0034] As a possible implementation method, the candidate driving trajectory is verified based on the current obstacle position information, including:

[0035] Determine the area where the obstacle is located based on the current obstacle location information;

[0036] Determine whether the candidate driving trajectory intersects with the area where the obstacle is located;

[0037] If the candidate driving trajectory intersects the area where the obstacle is located, it is determined that the candidate driving trajectory verification has failed;

[0038] If the candidate driving trajectory does not intersect the area where the obstacle is located, it is determined that the candidate driving trajectory verification is successful.

[0039] According to a second aspect of the present application, a vehicle is provided, including a memory, a transceiver, and a processor, wherein:

[0040] A memory for storing a computer program; a transceiver for transmitting and receiving data under the control of a processor; and a processor for reading the computer program in the memory and performing the following operations:

[0041] Obtaining the current vehicle position information, vehicle status information, and obstacle position information of the vehicle during the execution of a preset driving operation;

[0042] Determining the position information and vehicle status information of a target global path key point based on the global path key point information and the vehicle position information; wherein the global path key point information includes the position information and vehicle status information corresponding to each of a plurality of global path key points; the plurality of global path key points are determined based on the global planned path corresponding to the driving operation;

[0043] Based on the quintic spline interpolation algorithm, the path planning trajectory from the vehicle's current position to the target global path key point is determined according to the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the target global path key point.

[0044] As a possible implementation method, the position information of the target global path key point and the vehicle state information are determined based on the global path key point information and the vehicle position information, including:

[0045] Determine, based on the vehicle position information, a first global path key point that is located after the current position and closest to the current position from a plurality of global path key points;

[0046] The first global path key point is determined as the target global path key point, and the position information and vehicle state information of the first global path key point are determined as the position information and vehicle state information of the target global path key point.

[0047] In some embodiments of the present application, the global path key point information is obtained in advance through the following steps:

[0048] Perform global path planning for driving operations based on a graph search algorithm to obtain a global path point set;

[0049] Select multiple global path key points from the global path point set;

[0050] Determine the position information and vehicle status information corresponding to multiple global path key points.

[0051] As a possible implementation method, multiple global path key points are selected from the global path point set, including:

[0052] Get multiple landmark points from the global path point set;

[0053] Based on multiple landmark points, multiple global path key points are determined.

[0054] Among them, based on multiple landmark points, multiple global path key points are determined, including:

[0055] Determine the number of multiple landmark points;

[0056] According to the multiple landmark points and their quantities, multiple global path key points are determined.

[0057] As an example, multiple global path key points are determined based on multiple landmark points and their numbers, including:

[0058] If the number of multiple landmark points is less than a preset landmark point threshold, at least one new landmark point is added based on the global path point set so that the number of newly added landmark points reaches the landmark point threshold;

[0059] The multiple landmark points and at least one newly added landmark point are determined as multiple global path key points.

[0060] As another example, multiple global path key points are determined based on multiple landmark points and their numbers, including:

[0061] If the number of the multiple landmark points is greater than or equal to a preset landmark point threshold, the multiple landmark points are determined as multiple global path key points.

[0062] In some embodiments of the present application, a path planning trajectory between a vehicle's current position and a target global path key point is determined based on a quintic spline interpolation algorithm according to vehicle position information, vehicle state information, obstacle position information, and position information and vehicle state information of a target global path key point, including:

[0063] Based on the quintic spline interpolation algorithm, the candidate driving trajectory between the vehicle's current position and the target global path key point is determined according to the vehicle's position information, vehicle status information, and the position information and vehicle status information of the target global path key point;

[0064] Verify the candidate driving trajectory based on the obstacle location information;

[0065] If the candidate driving trajectory is successfully verified, the candidate driving trajectory is determined as the path planning trajectory between the vehicle's current position and the target global path key point;

[0066] If the candidate driving trajectory fails to be verified, a second global path keypoint is added between the current position and the target global path keypoint based on the current obstacle position information;

[0067] Determining position information and vehicle state information of a second global path key point;

[0068] Based on the quintic spline interpolation algorithm, the path planning trajectory of the vehicle from the current position to the second global path key point is determined according to the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the second global path key point.

[0069] As a possible implementation method, the candidate driving trajectory is verified based on the current obstacle position information, including:

[0070] Determine the area where the obstacle is located based on the current obstacle location information;

[0071] Determine whether the candidate driving trajectory intersects with the area where the obstacle is located;

[0072] If the candidate driving trajectory intersects the area where the obstacle is located, it is determined that the candidate driving trajectory verification has failed;

[0073] If the candidate driving trajectory does not intersect the area where the obstacle is located, it is determined that the candidate driving trajectory verification is successful.

[0074] According to a third aspect of the present application, a vehicle path planning device is provided, comprising:

[0075] An acquisition module is used to obtain the current vehicle position information, vehicle status information and obstacle position information of the vehicle during the execution of a preset driving operation;

[0076] A first determination module is configured to determine position information and vehicle status information of a target global path key point based on the global path key point information and the vehicle position information; wherein the global path key point information includes position information and vehicle status information corresponding to each of a plurality of global path key points; and the plurality of global path key points are determined based on a global planned path corresponding to the driving operation;

[0077] The second determination module is used to determine the path planning trajectory of the vehicle from the current position to the target global path key point based on the quintic spline interpolation algorithm, according to the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the target global path key point.

[0078] According to a fourth aspect of the present application, a processor-readable storage medium is provided, wherein the processor-readable storage medium stores a computer program, and when the computer program is executed by the processor, the vehicle path planning method described in the first aspect is implemented.

[0079] According to the technical solution of the embodiment of the present application, by obtaining the current vehicle position information, vehicle status information and obstacle position information of the vehicle during the execution of the preset driving operation, the position information and vehicle status information of the target global path key point are determined based on the global path key point information and the vehicle position information, and based on the quintic spline difference algorithm, the path planning trajectory of the vehicle from the current position to the target global path key point is determined based on the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the target global path key point. This solution integrates global path planning with local path planning through global path key points, so that the obtained path planning trajectory is biased towards global path planning, thereby obtaining a global optimal path. In addition, this solution uses the quintic spline difference algorithm to calculate the path planning trajectory, which can not only greatly reduce the amount of calculation, but also make the obtained path planning trajectory smoother, thereby improving the efficiency and safety of vehicle driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0081] Figure 1 A flow chart of a vehicle path planning method provided in an embodiment of the present application;

[0082] Figure 2 A flowchart of another vehicle path planning method provided in an embodiment of the present application;

[0083] Figure 3 A flowchart of another vehicle path planning method provided in an embodiment of the present application;

[0084] Figure 4 A flowchart of another vehicle path planning method provided in an embodiment of the present application;

[0085] Figure 5 A structural block diagram of a vehicle provided in an embodiment of the present application;

[0086] Figure 6 This is a structural block diagram of a vehicle path planning device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0087] In embodiments of the present invention, the term "and / or" describes the association relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0088] In the embodiments of the present application, the term "plurality" refers to two or more than two, and other quantifiers are similar.

[0089] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0090] It's important to note that with the advancement of technology, trajectory planning can help vehicles choose the shortest and fastest routes, avoiding congestion and busy roads to improve driving efficiency. It can also avoid dangerous areas and the risk of traffic accidents, ensuring that vehicles can reach their destinations efficiently and safely. Autonomous driving can be broadly divided into three aspects: perception, decision-making, and control. Path planning is the decision-making stage between perception and control. Its primary goal is to provide a safe and collision-free path to the vehicle's destination, taking into account vehicle dynamics, maneuverability, and applicable regulations and road boundary conditions.

[0091] In related technologies, path planning includes two aspects: global path planning and local path planning. Among them, the global path planning algorithm is a static planning algorithm, which performs path planning based on existing map information (SLAM) to find an optimal path from the starting point to the target point. It is only applicable to situations where the activity area information is known. Local path planning is a dynamic planning algorithm, which is a self-driving car that perceives the surrounding environment based on its own sensors and plans a route required for the vehicle to drive safely. It is often used in scenarios such as overtaking and obstacle avoidance. However, the local path planner can usually only plan based on the current position and local map information, and cannot fully understand the situation of the entire environment. This may cause the planned path to be less than optimized or unable to avoid some obstacles. Since local path planning only considers information near the current position, it may cause the algorithm to fall into a local optimal solution and fail to find the global optimal path. In this case, the robot may move back and forth in the local area and fail to reach the target position. In addition, local path planning has the problem of high computational complexity.

[0092] In order to solve the above problems, the present application proposes a vehicle path planning method, device and vehicle.

[0093] Figure 1 This is a flow chart of a vehicle path planning method provided in an embodiment of the present application. It should be noted that the vehicle path planning method of the embodiment of the present application can be applied to the vehicle path planning device of the embodiment of the present application, and the device can be configured in the vehicle. Figure 1 As shown, the vehicle path planning method may include the following steps:

[0094] Step 101: Acquire the current vehicle position information, vehicle status information, and obstacle position information of the vehicle during the execution of a preset driving operation.

[0095] In some embodiments of the present application, the vehicle may be an intelligent networked vehicle with autonomous driving capabilities, wherein the driving operation may be an autonomous operation from a starting point to a destination. The vehicle's location information may include the coordinates of the vehicle's current location, the vehicle's state information may include information such as the vehicle's current speed, acceleration, heading, and curvature, and the obstacle information may include information about obstacles around the vehicle collected by the vehicle's sensors, such as the coordinates of the obstacles.

[0096] Step 102: Determine the position information and vehicle status information of the target global path key point based on the global path key point information and the vehicle position information; wherein the global path key point information includes the position information and vehicle status information corresponding to each of a plurality of global path key points; and the plurality of global path key points are determined based on the global planned path corresponding to the driving operation.

[0097] In some embodiments of the present application, before executing the driving operation, global path planning can be performed based on the starting point and destination of the driving operation, as well as existing map information, to obtain a global path planning trajectory, and multiple global path key points are determined in the global path planning trajectory, and the position information and vehicle status information corresponding to each of the multiple global path key points are determined. Among them, the global path key points are feature points used to characterize the global path planning trajectory. As an example, the global path key points can be key location points, such as intersection location points, building location points, path turning points, etc. The location information of each global path key point can be the coordinate information of the global key point, and the vehicle status information of each global key point can be information such as vehicle orientation, curvature, vehicle speed, and vehicle acceleration determined based on the speed limit requirements, road condition information, etc. at the global keyword.

[0098] The target global path key point may be the global path key point closest to the current vehicle position among the global path key points that the vehicle has not traveled through. As an example, determining the position information and vehicle state information of the target global path key point based on the global path key point information and the vehicle position information includes: determining, based on the vehicle position information, a first global path key point that is located after the current position and closest to the current position from multiple global path key points; determining the first global path key point as the target global path key point, and determining the position information and vehicle state information of the first global path key point as the position information and vehicle state information of the target global path key point.

[0099] Step 103, based on the quintic spline interpolation algorithm, determines the path planning trajectory of the vehicle from the current position to the target global path key point according to the vehicle position information, vehicle state information, obstacle position information, and the position information and vehicle state information of the target global path key point.

[0100] That is to say, the position information of the vehicle at the current position, the vehicle status information, the obstacle position information, and the position information and vehicle status information of the key points of the target global path are used for local path planning. Based on the quintic spline interpolation algorithm, the trajectory of the path with the current position as the starting point and the target global path key point as the end point is calculated, so that the obtained path planning trajectory is close to the global path.

[0101] In some embodiments of the present application, obstacle position information can be added to the quintic spline interpolation algorithm as a constraint condition. Based on the constructed quintic polynomial, the polynomial is first-order and second-order differentiated according to the position information of the vehicle at the current position, the vehicle status information, and the position information and vehicle status information of the target global path key points to obtain the coefficients of the polynomial, thereby obtaining the path planning trajectory of the vehicle from the current position to the target global path key points.

[0102] In other embodiments of the present application, based on the quintic spline interpolation algorithm, the candidate path planning trajectory of the vehicle from the current position to the target global path key point can be determined according to the position information of the vehicle at the current position, the vehicle status information, and the position information and vehicle status information of the target global path key point; according to the obstacle position information, it is judged whether the candidate path planning trajectory intersects with the obstacle; if there is an intersection, the candidate path trajectory is optimized according to the obstacle position information to avoid the obstacle, and the optimized trajectory is determined as the path planning trajectory of the vehicle from the current position to the target global path key point; if there is no intersection, the candidate path trajectory is determined as the path planning trajectory of the vehicle from the current position to the target global path key point.

[0103] According to the vehicle path planning method of the embodiment of the present application, by obtaining the current vehicle position information, vehicle status information and obstacle position information of the vehicle during the execution of a preset driving operation, the position information and vehicle status information of the target global path key point are determined based on the global path key point information and the vehicle position information, and based on the quintic spline difference algorithm, the path planning trajectory of the vehicle from the current position to the target global path key point is determined based on the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the target global path key point. This solution integrates global path planning with local path planning through global path key points, so that the obtained path planning trajectory is biased towards global path planning, thereby obtaining a global optimal path. In addition, this solution uses the quintic spline difference algorithm to calculate the path planning trajectory, which can not only greatly reduce the amount of calculation, but also make the obtained path planning trajectory smoother, thereby improving the efficiency and safety of vehicle driving.

[0104] Next, the process of obtaining global path key point information will be introduced in detail.

[0105] Figure 2 This is a flow chart of another vehicle path planning method provided in an embodiment of the present application. Figure 2 As shown, based on the above embodiment, the method further includes a process of determining global path key point information, which specifically includes the following steps:

[0106] Step 201 : Perform global path planning for the driving operation based on a graph search algorithm to obtain a global path point set.

[0107] Global path planning involves searching for the optimal path from a starting point to a destination within an entire environment. It considers the entire environment's map information and obstacle distribution, using algorithms to search for the shortest or optimal path. Common graph search algorithms include the A* algorithm and the Dijkstra algorithm for finding the shortest path in a graph. The A* algorithm is a heuristic search algorithm that builds upon the Dijkstra algorithm by incorporating a heuristic function to evaluate the priority of each node. By comprehensively considering the actual node cost and the estimated cost of the heuristic function, the A* algorithm selects the node with the highest probability of leading to the shortest path for expansion. This makes the A* algorithm more efficient and particularly suitable for searching large graphs. The Dijkstra algorithm is a classic single-source shortest path algorithm that continuously expands the node closest to the starting point until the destination node is found or all nodes have been expanded. The Dijkstra algorithm ensures that the shortest path for each node is deterministic, but when working with large graphs, its time complexity is high due to the need to traverse all nodes.

[0108] In some embodiments of the present application, an A* algorithm may be used to perform global path planning for a driving operation, wherein the estimated cost of moving from a current node to a destination may be calculated using the Manhattan method.

[0109] Step 202: Select multiple global path key points from the global path point set.

[0110] It can be understood that the global path point set includes all nodes in the global path planning trajectory. In order to integrate global path planning and local path planning, multiple global path key points can be selected from the global path point set to represent the global path, and local path planning can be performed with the global path key points as the target.

[0111] As a possible implementation method, the starting point, target point, important turning points in the path, intersections and other nodes can be selected from the global path point set, and these nodes can be used as global path key points.

[0112] Step 203: Determine the position information and vehicle status information corresponding to each of the multiple global path key points.

[0113] In some embodiments of the present application, the location information of each global key point can be determined based on map information, and the road condition information, speed limit requirements and other information at each global key point can also be determined based on the map information. Based on this information and the vehicle's own configuration, the vehicle status information of the vehicle at each global key point can be determined.

[0114] According to the vehicle path planning method of the embodiment of the present application, global path planning is performed on the driving operation based on the graph search algorithm to obtain a global path point set. From the global path point set, multiple global path key points are selected, and the position information and vehicle status information corresponding to each of the multiple global path key points are determined, thereby obtaining global path key point information. Based on the global path key point information, the integration of global path planning and local path planning is realized to improve the effect of path planning.

[0115] Next, the implementation process of selecting multiple global path key points from the global path point set will be introduced.

[0116] Figure 3 This is a flow chart of another vehicle path planning method provided in an embodiment of the present application. Figure 3 As shown, based on the above embodiment, Figure 2 The implementation process of step 202 may include:

[0117] Step 301: Acquire multiple landmark points from a global path point set.

[0118] As a possible implementation method, the landmark selection method can be used to select multiple landmark points such as starting points, destination points, intersections, buildings, and path turning points from the global path point set based on map information, so as to represent the entire global planning path through multiple landmark points.

[0119] Step 302: Determine multiple global path key points based on multiple landmark points.

[0120] In some embodiments of the present application, multiple landmark points can be directly used as multiple global path key points. However, if the number of landmark points is small, it may not be possible to represent the global planning path. Therefore, when determining multiple global path key points based on multiple landmark points, the number of landmark points can also be considered.

[0121] As a possible implementation method, the process of determining multiple global path key points based on multiple landmark points includes: determining the number of multiple landmark points; and determining multiple global path key points based on the multiple landmark points and their numbers.

[0122] As an example, the process of determining multiple global path key points based on multiple landmark points and their numbers may include: comparing the number of landmark points with a preset landmark point threshold; if the number of multiple landmark points is greater than or equal to the landmark point threshold, determining the multiple landmark points as multiple global path key points.

[0123] As another example, if the number of multiple landmark points is less than the landmark point threshold, at least one new landmark point is added based on the global path point set so that the number of newly added landmark points reaches the landmark point threshold; the multiple landmark points and the at least one newly added landmark point are determined as multiple global path key points.

[0124] Among them, the method of adding new landmark points can adopt the method of equal spacing of paths, and take out the corresponding nodes from the global path point set for adding. Alternatively, the path length between two adjacent landmark points in multiple landmark points can be first calculated, and based on the path length of adjacent landmark points, different numbers of nodes can be selected from the global path point set between each two landmark points as new landmark points.

[0125] According to the vehicle path planning method of the embodiment of the present application, multiple landmark points are obtained from the global path point set, and multiple global path key points are determined based on the multiple landmark points, so that the obtained multiple global path key points can represent the global planning path, thereby making the obtained path planning trajectory closer to the global path and improving the path planning efficiency.

[0126] Next, the implementation process of the local path planning process will be introduced in detail.

[0127] Figure 4This is a flow chart of another vehicle path planning method provided in an embodiment of the present application. Figure 4 As shown, based on the above embodiment, Figure 1 The implementation process of step 103 may include:

[0128] Step 401 , based on a quintic spline interpolation algorithm, determines a candidate driving trajectory of the vehicle from the current position to the target global path key point according to the vehicle position information, vehicle state information, and the position information and vehicle state information of the target global path key point.

[0129] That is to say, based on the quintic spline interpolation algorithm, the trajectory between the current position and the target global path key point is calculated according to the vehicle position information and vehicle status information of the current position, as well as the position information and vehicle position information of the target global path key point.

[0130] In some embodiments of the present application, a fifth-order polynomial between vehicle position and time can be constructed to express the parameter curve of the planned trajectory, as shown in the following equation (1):

[0131]

[0132] Where x(t) is the horizontal coordinate of the vehicle position corresponding to time t. Set t = 0 at the starting point and t = t when the vehicle reaches the destination. f ; y(t) is the vertical coordinate of the vehicle position corresponding to time t; a i and β i They are t in the polynomial i The coefficient of .

[0133] The first-order derivative of equation (1) can be used to obtain the velocity expression as follows (2):

[0134]

[0135] in, is the first-order derivative of x(t), that is, the velocity component of the abscissa corresponding to the vehicle at time t; is the first-order derivative of y(t), that is, the velocity component of the ordinate corresponding to the vehicle at time t; v(t) is the velocity of the vehicle at time t; θ(t) is the direction of the vehicle at time t.

[0136] The second-order derivative of equation (2) can be used to obtain the expression of acceleration as follows (3):

[0137]

[0138] in, is the second-order derivative of x(t), that is, the acceleration component of the horizontal coordinate corresponding to the vehicle at time t; is the second-order derivative of y(t), that is, the acceleration component of the ordinate corresponding to the vehicle at time t; a(t) is the acceleration of the vehicle at time t; θ(t) is the orientation of the vehicle at time t; k(t) is the curvature of the vehicle at time t.

[0139] Based on the above equations (1)-(3), combined with the time corresponding to the current vehicle's travel, the current vehicle's position information and vehicle state information, and the time, vehicle position information, and vehicle state information when the vehicle travels to the target global path key point, the coefficients of the fifth-order polynomial are solved. If the time corresponding to the current vehicle's travel is t1, the current vehicle's position information is (x1, y1), and the vehicle's current speed is v1, the current vehicle's acceleration is a1, the current vehicle's orientation is θ1, and the current vehicle's curvature is k1, the time t2 when the vehicle travels to the target global path key point, the position information at the target global path key point is (x2, y2), the current vehicle's speed at the global path key point is v2, the vehicle's acceleration is a2, the vehicle's orientation is θ2, and the vehicle's curvature is k2, based on the above information, the constraint equation is constructed as follows (4):

[0140]

[0141] Based on the above formulas (1)-(4), we can derive the coefficient a in the fifth-order polynomial of formula (1): i and β i The expression of formula (1) is the candidate driving trajectory of the vehicle from the current position to the key point of the target global path.

[0142] Step 402: Verify the candidate driving trajectory based on the obstacle position information.

[0143] It is understandable that the final path planning trajectory needs to avoid obstacles during driving to ensure safe driving of the vehicle, so the subsequent driving trajectory needs to be verified to determine whether the subsequent driving trajectory can avoid obstacles.

[0144] In some embodiments of the present application, the obstacle position information may include the coordinate information of the obstacle. The implementation process of verifying the subsequent driving trajectory based on the obstacle position information may include: determining the area where the obstacle is located based on the current obstacle position information; judging whether the candidate driving trajectory and the area where the obstacle is located intersect; if the candidate driving trajectory and the area where the obstacle is located intersect, determining that the verification of the candidate driving trajectory has failed; if the candidate driving trajectory and the area where the obstacle is located do not intersect, determining that the verification of the candidate driving trajectory has succeeded.

[0145] Step 403 : If the candidate driving trajectory is successfully verified, the candidate driving trajectory is determined as the path planning trajectory between the vehicle's current position and the target global path key point.

[0146] Step 404: If the candidate driving trajectory fails to be verified, a second global path keypoint is added between the current position and the target global path keypoint based on the current obstacle position information.

[0147] Step 405 : Determine the position information and vehicle status information of the second global path key point.

[0148] Step 406, based on the quintic spline interpolation algorithm, determines the path planning trajectory of the vehicle from the current position to the second global path key point according to the vehicle position information, vehicle state information, obstacle position information, and the position information and vehicle state information of the second global path key point.

[0149] That is to say, if the candidate driving trajectory fails to be verified, a second global path key point can be added between the current position and the target global path key point, the scope of the current local path planning can be narrowed, and only the path planning trajectory between the current position and the second global path key point can be calculated to avoid obstacles.

[0150] As an example, in step 404, the implementation process of adding a second global path key point between the current position and the target global path key point based on the current obstacle position information can be: determining the area where the obstacle is located based on the obstacle position information; determining the extended area of ​​the area where the obstacle is located based on the preset vehicle-obstacle interval; and selecting any point on the boundary line of the extended area of ​​the area where the obstacle is located as the second global path key point.

[0151] In some embodiments of the present application, executing step 406 is equivalent to using the second global path key point as the target global path key point and returning to executing step 401 until the obtained candidate driving route is successfully verified and the route planning trajectory between the current position and the target global path key point is obtained.

[0152] According to the vehicle path planning method of the embodiment of the present application, based on the quintic spline interpolation algorithm, the candidate driving trajectory of the vehicle from the current position to the target global path key point is determined according to the vehicle position information, vehicle status information, and the position information and vehicle status information of the target global path key point. The candidate driving trajectory is then verified according to the obstacle position information. If the candidate driving trajectory verification is successful, the candidate driving trajectory is determined as the path planning trajectory of the vehicle from the current position to the target global path key point. If the candidate driving trajectory verification fails, a second global path key point is added between the current position and the target global path key point according to the current obstacle position information; the position information and vehicle status information of the second global path key point are determined, and the path planning trajectory of the vehicle from the current position to the second global path key point is determined. This solution enables the path planning trajectory to avoid obstacles while not deviating from the global path by verifying the candidate driving trajectory and adding global path key points.

[0153] In order to implement the above embodiments, the present application also provides a vehicle.

[0154] Figure 5 This is a structural block diagram of a vehicle provided in an embodiment of the present application. Figure 5 As shown, the vehicle includes a memory 501 , a transceiver 502 and a processor 503 .

[0155] The transceiver 502 is configured to receive and send data under the control of the processor 503 .

[0156] Among them, Figure 5 In the embodiment, the bus architecture may include any number of interconnected buses and bridges, specifically linking together various circuits of one or more processors represented by processor 503 and memory represented by memory 501. The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are all well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 502 may be a plurality of components, i.e., a transmitter and a receiver, providing a unit for communicating with various other devices on a transmission medium, such as a wireless channel, a wired channel, an optical cable, and the like. The processor 503 is responsible for managing the bus architecture and general processing, and the memory 501 may store data used by the processor 503 when performing operations.

[0157] Optionally, the processor 503 may be a CPU (central processing unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array) or a CPLD (Complex Programmable Logic Device), and the processor may also adopt a multi-core architecture.

[0158] The processor 503 calls the computer program stored in the memory 501 and performs the following operations:

[0159] Obtaining the current vehicle position information, vehicle status information, and obstacle position information of the vehicle during the execution of a preset driving operation;

[0160] Determining the position information and vehicle status information of a target global path key point based on the global path key point information and the vehicle position information; wherein the global path key point information includes the position information and vehicle status information corresponding to each of a plurality of global path key points; the plurality of global path key points are determined based on the global planned path corresponding to the driving operation;

[0161] Based on the quintic spline interpolation algorithm, the path planning trajectory from the vehicle's current position to the target global path key point is determined according to the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the target global path key point.

[0162] As a possible implementation method, the position information of the target global path key point and the vehicle state information are determined based on the global path key point information and the vehicle position information, including:

[0163] Determine, based on the vehicle position information, a first global path key point that is located after the current position and closest to the current position from a plurality of global path key points;

[0164] The first global path key point is determined as the target global path key point, and the position information and vehicle state information of the first global path key point are determined as the position information and vehicle state information of the target global path key point.

[0165] In some embodiments of the present application, the global path key point information is obtained in advance through the following steps:

[0166] Perform global path planning for driving operations based on a graph search algorithm to obtain a global path point set;

[0167] Select multiple global path key points from the global path point set;

[0168] Determine the position information and vehicle status information corresponding to multiple global path key points.

[0169] As a possible implementation method, multiple global path key points are selected from the global path point set, including:

[0170] Get multiple landmark points from the global path point set;

[0171] Based on multiple landmark points, multiple global path key points are determined.

[0172] Among them, based on multiple landmark points, multiple global path key points are determined, including:

[0173] Determine the number of multiple landmark points;

[0174] According to the multiple landmark points and their quantities, multiple global path key points are determined.

[0175] As an example, multiple global path key points are determined based on multiple landmark points and their numbers, including:

[0176] If the number of multiple landmark points is less than a preset landmark point threshold, at least one new landmark point is added based on the global path point set so that the number of newly added landmark points reaches the landmark point threshold;

[0177] The multiple landmark points and at least one newly added landmark point are determined as multiple global path key points.

[0178] As another example, multiple global path key points are determined based on multiple landmark points and their numbers, including:

[0179] If the number of the multiple landmark points is greater than or equal to a preset landmark point threshold, the multiple landmark points are determined as multiple global path key points.

[0180] In some embodiments of the present application, a path planning trajectory between a vehicle's current position and a target global path key point is determined based on a quintic spline interpolation algorithm according to vehicle position information, vehicle state information, obstacle position information, and position information and vehicle state information of a target global path key point, including:

[0181] Based on the quintic spline interpolation algorithm, the candidate driving trajectory between the vehicle's current position and the target global path key point is determined according to the vehicle's position information, vehicle status information, and the position information and vehicle status information of the target global path key point;

[0182] Verify the candidate driving trajectory based on the obstacle location information;

[0183] If the candidate driving trajectory is successfully verified, the candidate driving trajectory is determined as the path planning trajectory between the vehicle's current position and the target global path key point;

[0184] If the candidate driving trajectory fails to be verified, a second global path keypoint is added between the current position and the target global path keypoint based on the current obstacle position information;

[0185] Determining position information and vehicle state information of a second global path key point;

[0186] Based on the quintic spline interpolation algorithm, the path planning trajectory of the vehicle from the current position to the second global path key point is determined according to the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the second global path key point.

[0187] As a possible implementation method, the candidate driving trajectory is verified based on the current obstacle position information, including:

[0188] Determine the area where the obstacle is located based on the current obstacle location information;

[0189] Determine whether the candidate driving trajectory intersects with the area where the obstacle is located;

[0190] If the candidate driving trajectory intersects the area where the obstacle is located, it is determined that the candidate driving trajectory verification has failed;

[0191] If the candidate driving trajectory does not intersect the area where the obstacle is located, it is determined that the candidate driving trajectory verification is successful.

[0192] The processor 503 is configured to execute any of the methods provided in the embodiments of the present application according to the obtained executable instructions by calling the computer program stored in the memory 501. The processor 503 and the memory 401 may also be physically separated.

[0193] It should be noted here that the above-mentioned vehicle provided by the embodiment of the present invention can implement all the method steps implemented by the above-mentioned method embodiment and can achieve the same technical effects. The parts and beneficial effects of this embodiment that are the same as those of the method embodiment will not be described in detail here.

[0194] In order to implement the above embodiments, the present application also provides a vehicle path planning device.

[0195] Figure 6 This is a structural block diagram of a vehicle path planning device provided in an embodiment of the present application. Figure 6 As shown, the apparatus may include an acquisition module 610 , a first determination module 620 , and a second determination module 630 .

[0196] The acquisition module 610 is used to obtain the current vehicle position information, vehicle status information and obstacle position information of the vehicle during the execution of the preset driving operation;

[0197] A first determining module 620 is configured to determine the position information and vehicle status information of a target global path key point based on the global path key point information and the vehicle position information; wherein the global path key point information includes the position information and vehicle status information corresponding to each of a plurality of global path key points; and the plurality of global path key points are determined based on the global planned path corresponding to the driving operation.

[0198] The second determination module 630 is used to determine the path planning trajectory of the vehicle from the current position to the target global path key point based on the quintic spline interpolation algorithm, according to the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the target global path key point.

[0199] In some embodiments of the present application, the first determining module 620 is specifically configured to:

[0200] Determine, based on the vehicle position information, a first global path key point that is located after the current position and closest to the current position from a plurality of global path key points;

[0201] The first global path key point is determined as the target global path key point, and the position information and vehicle state information of the first global path key point are determined as the position information and vehicle state information of the target global path key point.

[0202] In some embodiments of the present application, the apparatus further includes a third determination module 640 for pre-determining global path key point information.

[0203] As a possible implementation, the third determining module 640 includes:

[0204] An acquisition unit 641 is configured to perform global path planning for the driving operation based on a graph search algorithm to obtain a global path point set;

[0205] A selection unit 642 is used to select a plurality of global path key points from the global path point set;

[0206] The determination unit 643 is used to determine the position information and vehicle status information corresponding to each of the multiple global path key points.

[0207] As a possible implementation manner, the selection unit 642 is specifically configured to:

[0208] Get multiple landmark points from the global path point set;

[0209] Based on multiple landmark points, multiple global path key points are determined.

[0210] As another possible implementation, the selection unit 642 is further configured to:

[0211] Determine the number of multiple landmark points;

[0212] According to the multiple landmark points and their quantities, multiple global path key points are determined.

[0213] As an example, the selection unit 642 is further configured to:

[0214] If the number of multiple landmark points is less than a preset landmark point threshold, at least one new landmark point is added based on the global path point set so that the number of newly added landmark points reaches the landmark point threshold;

[0215] The multiple landmark points and at least one newly added landmark point are determined as multiple global path key points.

[0216] As another example, the selection unit 642 is further configured to:

[0217] If the number of the multiple landmark points is greater than or equal to a preset landmark point threshold, the multiple landmark points are determined as multiple global path key points.

[0218] In some embodiments of the present application, the second determining module 630 is specifically configured to:

[0219] Based on the quintic spline interpolation algorithm, the candidate driving trajectory between the vehicle's current position and the target global path key point is determined according to the vehicle's position information, vehicle status information, and the position information and vehicle status information of the target global path key point;

[0220] Verify the candidate driving trajectory based on the obstacle location information;

[0221] If the candidate driving trajectory is successfully verified, the candidate driving trajectory is determined as the path planning trajectory between the vehicle's current position and the target global path key point;

[0222] If the candidate driving trajectory fails to be verified, a second global path keypoint is added between the current position and the target global path keypoint based on the current obstacle position information;

[0223] Determining position information and vehicle state information of a second global path key point;

[0224] Based on the quintic spline interpolation algorithm, the path planning trajectory of the vehicle from the current position to the second global path key point is determined according to the vehicle position information, vehicle status information, obstacle position information, and the position information and vehicle status information of the second global path key point.

[0225] As a possible implementation manner, the second determining module 630 is further configured to:

[0226] Determine the area where the obstacle is located based on the current obstacle location information;

[0227] Determine whether the candidate driving trajectory intersects with the area where the obstacle is located;

[0228] If the candidate driving trajectory intersects the area where the obstacle is located, it is determined that the candidate driving trajectory verification has failed;

[0229] If the candidate driving trajectory does not intersect the area where the obstacle is located, it is determined that the candidate driving trajectory verification is successful.

[0230] It should be noted that the division of units in the embodiments of the present application is schematic and is merely a logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0231] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0232] It should be noted here that the above-mentioned device provided by the embodiment of the present invention can implement all the method steps implemented by the above-mentioned method embodiment and can achieve the same technical effect. The parts and beneficial effects that are the same as the method embodiment in this embodiment will not be described in detail here.

[0233] To implement the above embodiments, the present application further provides a processor-readable storage medium storing a computer program configured to cause a processor to execute any of the vehicle path planning methods described in the above embodiments.

[0234] Among them, the above-mentioned processor-readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disks, hard disks, tapes, magneto-optical disks (MO)), optical storage (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drives (SSDs)), etc.

[0235] In order to implement the above embodiments, the present application also provides a computer program product.

[0236] The computer program product includes a computer program, and when the computer program is executed by a processor, the vehicle path planning method described in the above embodiment is implemented.

[0237] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage and optical storage, etc.) that contain computer-usable program code.

[0238] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0239] These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the processor-readable memory produce an article of manufacture comprising an instruction device that implements the process Figure 1a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0240] These processor-executable instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0241] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A vehicle path planning method, characterized in that: include: Obtaining current vehicle position information, vehicle status information, and obstacle position information of the vehicle during execution of a preset driving operation; Determining the position information and vehicle status information of a target global path key point based on the global path key point information and the vehicle position information; wherein the global path key point information includes the position information and vehicle status information corresponding to each of a plurality of global path key points; the plurality of global path key points are determined based on the global planned path corresponding to the driving operation; Based on the quintic spline interpolation algorithm, the path planning trajectory of the vehicle from the current position to the target global path key point is determined according to the vehicle position information, the vehicle status information, the obstacle position information, and the position information and vehicle status information of the target global path key point.

2. The method according to claim 1, characterized in that The determining, based on the global path key point information and the vehicle position information, the position information of the target global path key point and the vehicle state information includes: Determining, based on the vehicle position information, a first global path key point from the multiple global path key points that is located after the current position and closest to the current position; The first global path key point is determined as the target global path key point, and the position information and vehicle state information of the first global path key point are determined as the position information and vehicle state information of the target global path key point.

3. The method according to claim 1, characterized in that The global path key point information is obtained in advance through the following steps: Performing global path planning on the driving operation based on a graph search algorithm to obtain a global path point set; Selecting the plurality of global path key points from the global path point set; Determine the position information and vehicle status information corresponding to each of the multiple global path key points.

4. The method according to claim 3, characterized in that The step of selecting the plurality of global path key points from the global path point set includes: Acquire multiple landmark points from the global path point set; Based on the multiple landmark points, the multiple global path key points are determined.

5. The method according to claim 4, characterized in that The determining of the plurality of global path key points based on the plurality of landmark points includes: determining a number of the plurality of landmark points; The multiple global path key points are determined based on the multiple landmark points and their quantities.

6. The method according to claim 5, characterized in that The step of determining the plurality of global path key points based on the plurality of landmark points and their quantities includes: If the number of the plurality of landmark points is less than a preset landmark point threshold, adding at least one landmark point based on the global path point set so that the number of the newly added landmark points reaches the landmark point threshold; The multiple landmark points and the at least one newly added landmark point are determined as the multiple global path key points.

7. The method according to claim 5, characterized in that The step of determining the plurality of global path key points based on the plurality of landmark points and their quantities includes: If the number of the multiple landmark points is greater than or equal to a preset landmark point number threshold, the multiple landmark points are determined as the multiple global path key points.

8. The method according to claim 1, characterized in that The quintic spline interpolation algorithm is based on the vehicle position information, the vehicle state information, the obstacle position information, and the position information and vehicle state information of the target global path key point to determine the path planning trajectory of the vehicle from the current position to the target global path key point, including: Determine, based on a quintic spline interpolation algorithm, a candidate driving trajectory of the vehicle from a current position to the target global path key point according to the vehicle position information, the vehicle state information, and the position information and vehicle state information of the target global path key point; Verifying the candidate driving trajectory according to the obstacle position information; If the candidate driving trajectory is successfully verified, the candidate driving trajectory is determined as the path planning trajectory of the vehicle from the current position to the target global path key point; If the candidate driving trajectory fails to be verified, adding a second global path key point between the current position and the target global path key point according to the current obstacle position information; Determining position information and vehicle state information of a second global path key point; Based on the quintic spline interpolation algorithm, the path planning trajectory of the vehicle from the current position to the second global path key point is determined according to the vehicle position information, the vehicle status information, the obstacle position information, and the position information and vehicle status information of the second global path key point.

9. The method according to claim 8, characterized in that The verifying of the candidate driving trajectory according to the current obstacle position information includes: Determine the area where the obstacle is located based on the current obstacle position information; Determining whether the candidate driving trajectory intersects the area where the obstacle is located; If the candidate driving trajectory intersects the area where the obstacle is located, determining that the candidate driving trajectory verification fails; If the candidate driving trajectory does not intersect the area where the obstacle is located, it is determined that the candidate driving trajectory verification is successful.

10. A vehicle, characterized in that: It includes a memory, a transceiver, and a processor, wherein: A memory for storing a computer program; a transceiver for transmitting and receiving data under the control of the processor; and a processor for reading the computer program in the memory and performing the following operations: Obtaining current vehicle position information, vehicle status information, and obstacle position information of the vehicle during execution of a preset driving operation; Determining the position information and vehicle status information of a target global path key point based on the global path key point information and the vehicle position information; wherein the global path key point information includes the position information and vehicle status information corresponding to each of a plurality of global path key points; the plurality of global path key points are determined based on the global planned path corresponding to the driving operation; Based on the quintic spline interpolation algorithm, the path planning trajectory of the vehicle from the current position to the target global path key point is determined according to the vehicle position information, the vehicle status information, the obstacle position information, and the position information and vehicle status information of the target global path key point.

11. The vehicle according to claim 10, characterized in that The determining, based on the global path key point information and the vehicle position information, the position information of the target global path key point and the vehicle state information includes: Determining, based on the vehicle position information, a first global path key point from the multiple global path key points that is located after the current position and closest to the current position; The first global path key point is determined as the target global path key point, and the position information and vehicle state information of the first global path key point are determined as the position information and vehicle state information of the target global path key point.

12. The vehicle according to claim 11, characterized in that The global path key point information is obtained in advance through the following steps: Performing global path planning on the driving operation based on a graph search algorithm to obtain a global path point set; Selecting the plurality of global path key points from the global path point set; Determine the position information and vehicle status information corresponding to each of the multiple global path key points.

13. The vehicle according to claim 12, characterized in that The step of selecting the plurality of global path key points from the global path point set includes: Acquire multiple landmark points from the global path point set; Based on the multiple landmark points, the multiple global path key points are determined.

14. The vehicle according to claim 13, characterized in that The determining of the plurality of global path key points based on the plurality of landmark points includes: determining a number of the plurality of landmark points; The multiple global path key points are determined based on the multiple landmark points and their quantities.

15. The vehicle according to claim 14, characterized in that The step of determining the plurality of global path key points based on the plurality of landmark points and their quantities includes: If the number of the plurality of landmark points is less than a preset landmark point threshold, adding at least one landmark point based on the global path point set so that the number of the newly added landmark points reaches the landmark point threshold; The multiple landmark points and the at least one newly added landmark point are determined as the multiple global path key points.

16. The vehicle according to claim 14, characterized in that The step of determining the plurality of global path key points based on the plurality of landmark points and their quantities includes: If the number of the multiple landmark points is greater than or equal to a preset landmark point number threshold, the multiple landmark points are determined as the multiple global path key points.

17. The vehicle according to claim 10, characterized in that The quintic spline interpolation algorithm is based on the vehicle position information, the vehicle state information, the obstacle position information, and the position information and vehicle state information of the target global path key point to determine the path planning trajectory of the vehicle from the current position to the target global path key point, including: Determine, based on a quintic spline interpolation algorithm, a candidate driving trajectory of the vehicle from a current position to the target global path key point according to the vehicle position information, the vehicle state information, and the position information and vehicle state information of the target global path key point; Verifying the candidate driving trajectory according to the obstacle position information; If the candidate driving trajectory is successfully verified, the candidate driving trajectory is determined as the path planning trajectory of the vehicle from the current position to the target global path key point; If the candidate driving trajectory fails to be verified, adding a second global path key point between the current position and the target global path key point according to the current obstacle position information; Determining position information and vehicle state information of a second global path key point; Based on the quintic spline interpolation algorithm, the path planning trajectory of the vehicle from the current position to the second global path key point is determined according to the vehicle position information, the vehicle status information, the obstacle position information, and the position information and vehicle status information of the second global path key point.

18. The vehicle according to claim 17, characterized in that The verifying of the candidate driving trajectory according to the current obstacle position information includes: Determine the area where the obstacle is located based on the current obstacle position information; Determining whether the candidate driving trajectory intersects the area where the obstacle is located; If the candidate driving trajectory intersects the area where the obstacle is located, determining that the candidate driving trajectory verification fails; If the candidate driving trajectory does not intersect the area where the obstacle is located, it is determined that the candidate driving trajectory verification is successful.

19. A vehicle path planning device, characterized in that: include: An acquisition module, configured to acquire current vehicle position information, vehicle status information, and obstacle position information of the vehicle during execution of a preset driving operation; a first determining module, configured to determine, based on the global path key point information and the vehicle position information, the position information and vehicle status information of a target global path key point; wherein the global path key point information includes the position information and vehicle status information corresponding to each of a plurality of global path key points; and the plurality of global path key points are determined based on the global planned path corresponding to the driving operation; The second determination module is used to determine the path planning trajectory of the vehicle from the current position to the target global path key point based on the vehicle position information, the vehicle state information, the obstacle position information, and the position information and vehicle state information of the target global path key point based on the quintic spline interpolation algorithm.

20. A processor-readable storage medium, characterized in that: The processor-readable storage medium stores a computer program, and the computer program is used to enable the processor to execute the vehicle path planning method according to any one of claims 1 to 9.

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