A method, apparatus, device, and storage medium for determining a detour method

Abstract

This invention discloses a method, apparatus, device, and storage medium for determining detour patterns, relating to the field of vehicle technology. The method includes: determining sampling points within the vehicle's travel area; performing dynamic planning on the vehicle based on obstacles within the travel area and the sampling points to obtain multiple planned coarse trajectories; determining detour labels for the sampling points and secondary sampling points constituting each planned coarse trajectory based on the obstacles; dividing the travel area into multiple sub-regions based on the detour labels of each sampling point and each secondary sampling point; determining the target coarse trajectory for each sub-region; determining the target planned coarse trajectory based on the loss value of each target coarse trajectory; and determining the vehicle's detour pattern for the target obstacle based on the positional relationship between the target obstacle and the target planned coarse trajectory. This technical solution provides accurate detour suggestions for path planning based on the vehicle's detour pattern for the target obstacle, reducing the occurrence of repeated detours around obstacles and improving the accuracy and efficiency of path planning.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a method, apparatus, device and storage medium for determining detour patterns. Background Technology

[0002] In recent years, autonomous driving technology has become a hot topic. Autonomous driving technology mainly includes perception, prediction, planning and decision-making, and control. Traditional planning operations primarily rely on decisions such as longitudinal deceleration or lateral detour to avoid obstacles ahead.

[0003] In existing technologies, lateral detour avoidance decisions generally only consider whether to detour, with little consideration given to the detour direction.

[0004] Therefore, there is an urgent need for a method to determine the detour route of a vehicle to an obstacle. Summary of the Invention

[0005] The present invention provides a method, apparatus, device and storage medium for determining detour patterns of vehicles to obstacles.

[0006] In a first aspect, embodiments of the present invention provide a method for determining a detour route, including:

[0007] Sampling points are determined within the vehicle's travel area. Based on the obstacles within the travel area and the sampling points, the vehicle is dynamically planned to obtain multiple coarse trajectories.

[0008] Based on the obstacles, detour labels for the sampling points and secondary sampling points constituting each of the planned coarse trajectories are determined, and the passage area is divided into multiple sub-regions based on the detour labels for each of the sampling points and secondary sampling points.

[0009] After determining the target coarse trajectory for each sub-region, the target planning coarse trajectory is determined based on the loss value of each target coarse trajectory, wherein the loss value of the target coarse trajectory is determined by the obstacle, the sampling point constituting the target coarse trajectory, the secondary sampling point, and the historical trajectory;

[0010] The vehicle's detour method for the target obstacle is determined based on the positional relationship between the target obstacle and the planned coarse trajectory.

[0011] The technical solution of this invention provides a method for determining a detour pattern, comprising: determining sampling points within the vehicle's travel area; dynamically planning the vehicle based on obstacles within the travel area and the sampling points to obtain multiple planned coarse trajectories; determining detour labels for the sampling points and secondary sampling points constituting each of the planned coarse trajectories based on the obstacles; dividing the travel area into multiple sub-regions based on the detour labels for each of the sampling points and secondary sampling points; determining the target coarse trajectory for each sub-region; determining the target planned coarse trajectory based on the loss value of each target coarse trajectory, wherein the loss value of the target coarse trajectory is determined by the obstacles, the sampling points and secondary sampling points constituting the target coarse trajectory, and historical trajectories; and determining the vehicle's detour pattern for the target obstacle based on the positional relationship between the target obstacle and the target planned coarse trajectory. The above technical solution firstly identifies sampling points within the vehicle's travel area by sampling the area. Based on these sampling points and obstacles, multiple coarse trajectories are dynamically planned to determine the vehicle's initial path. After identifying the sampling points and secondary sampling points that constitute each coarse trajectory, detour labels are determined based on the positional relationship between the vehicle's bounding box and the obstacle bounding boxes within a preset range of these points. The travel area is then divided into multiple sub-regions based on these detour labels. Secondly, the target coarse trajectory in each sub-region is determined based on the dynamic planning loss of each coarse trajectory. The target coarse trajectory is then determined based on the loss value of each target coarse trajectory. Finally, the vehicle's detour method for the target obstacle is determined based on the positional relationship between the obstacle and the target coarse trajectory, providing precise detour suggestions for path planning near the obstacle, reducing repeated detours, and improving the accuracy and efficiency of path planning.

[0012] Furthermore, before determining sampling points within the vehicle's travel area, the following steps are also included:

[0013] A reference line is generated based on the vehicle's current location and the global planned path. The passage area is determined based on the vehicle's current planned starting point, the reference line, and environmental information.

[0014] Further, a reference line is generated based on the vehicle's current position and the globally planned path. The passage area is determined based on the vehicle's current planned starting point, the reference line, and environmental information, including:

[0015] Starting from the current position, the reference line is generated by extending forward a preset distance along the global planning path.

[0016] Starting from the current planning starting point, multiple aiming points are determined on the reference line based on a preset step size. The lane line types on both sides of each aiming point are determined according to the environmental information to determine the boundary on both sides of each aiming point. The passage area is determined according to the boundary on both sides of each aiming point.

[0017] Furthermore, based on the obstacles within the passage area and the sampling points, dynamic planning is performed on the vehicle to obtain multiple coarse trajectories, including:

[0018] The trajectory smoothness loss value of each sampling point is determined based on the location information of each sampling point, the obstacle loss value of each sampling point is determined based on the location information of each sampling point and the obstacle, and the cumulative loss value of each sampling point is determined based on the trajectory smoothness loss value and the obstacle loss value.

[0019] Multiple coarse trajectories are constructed based on the sampling point with the smallest cumulative loss value among the sampling points in each column.

[0020] Further, determining detour labels for the sampling points and secondary sampling points constituting each of the planned coarse trajectories based on the obstacles includes:

[0021] The coarse trajectories of each of the planning trajectories are sampled a second time to obtain the second sampling points that constitute each of the coarse trajectories of the planning trajectories;

[0022] Based on the location information of the sampling points constituting each of the planned coarse trajectories and each of the secondary sampling points, and the obstacles, the detour label of each of the secondary sampling points is determined.

[0023] Further, determining the detour label for each secondary sampling point based on the position information of the sampling points constituting each of the planned coarse trajectories and each of the secondary sampling points, and each of the obstacles, includes:

[0024] When the obstacle is a static obstacle, the detour label of the secondary sampling point is determined based on the positional relationship between the vehicle rectangle when the vehicle is projected onto the sampling point or the secondary sampling point and the obstacle rectangle of the obstacle within a preset range of the sampling point or the secondary sampling point;

[0025] When the obstacle is a dynamic obstacle, the vehicle's bounding box and projection time at the sampling point or the secondary sampling point are determined by projecting the sampling point or the secondary sampling point onto the vehicle's predicted trajectory. The obstacle's bounding box at the projection time is determined in the obstacle's predicted trajectory. The detour label of the sampling point or the secondary sampling point is determined based on the positional relationship between the vehicle bounding box and the obstacle's bounding box corresponding to the same projection time.

[0026] Furthermore, the passage area is divided into multiple sub-regions based on the detour labels of each sampling point and each secondary sampling point, including:

[0027] The passage area is divided into multiple sub-regions based on the detour labels of each sampling point and each secondary sampling point belonging to the same column.

[0028] Further, determining the coarse target trajectory for each of the sub-regions includes:

[0029] Determine the dynamic planning loss value of each coarse trajectory within each sub-region, and determine the coarse trajectory with the smallest dynamic planning loss value within each sub-region as the target coarse trajectory for each sub-region.

[0030] Further, the target planning coarse trajectory is determined based on the loss value of each target coarse trajectory, including:

[0031] Based on the position information of each sampling point constituting each target coarse trajectory and the projection position of each sampling point constituting each target coarse trajectory on the historical trajectory, the historical trajectory deviation loss value of each target coarse trajectory is determined; based on the position information of each sampling point constituting each planned coarse trajectory and each obstacle, the obstacle loss value of each target coarse trajectory is determined; based on the historical trajectory deviation loss value and the obstacle loss value of each target coarse trajectory, the loss value of each target coarse trajectory is determined.

[0032] The coarse trajectory of the target with the minimum loss value is determined as the coarse trajectory of the target planning.

[0033] Furthermore, when determining the obstacle loss value of each sampling point based on the location information of each sampling point and each obstacle, the method further includes:

[0034] If it is determined that the obstacle increases the obstacle loss value at the sampling point, then the obstacle is determined to be the target obstacle.

[0035] Further, determining the vehicle's detour around the target obstacle based on the positional relationship between the target obstacle and the planned coarse trajectory includes:

[0036] The target point corresponding to the target obstacle is determined in the target planning coarse trajectory;

[0037] The vehicle's detour method for the target obstacle is determined based on the positional relationship between the target obstacle and the target point corresponding to the target obstacle.

[0038] Further, determining the vehicle's detour method for the target obstacle based on the positional relationship between the target obstacle and the target point corresponding to the target obstacle includes:

[0039] When the target point corresponding to the target obstacle is located to the left of the target obstacle, the vehicle's detour method for the target obstacle is determined to be to detour to the left;

[0040] When the target point corresponding to the target obstacle is located to the right of the target obstacle, the vehicle's detour method for the target obstacle is determined to be detouring to the right.

[0041] Secondly, embodiments of the present invention also provide a detour pattern determination device, comprising:

[0042] The planning module is used to determine sampling points within the vehicle's travel area, and to perform dynamic planning for the vehicle based on obstacles within the travel area and the sampling points, thereby obtaining multiple coarse planning trajectories.

[0043] The segmentation module is used to determine the detour labels of the sampling points and secondary sampling points that constitute each of the planned coarse trajectories based on the obstacles, and to divide the passage area into multiple sub-regions based on the detour labels of each of the sampling points and secondary sampling points.

[0044] The determination module is used to determine the target coarse trajectory of each sub-region, and then determine the target planning coarse trajectory based on the loss value of each target coarse trajectory, wherein the loss value of the target coarse trajectory is determined by the obstacle, the sampling point constituting the target coarse trajectory, the secondary sampling point, and the historical trajectory;

[0045] The execution module is used to determine the vehicle's detour method for the target obstacle based on the positional relationship between the target obstacle and the target planned coarse trajectory.

[0046] Thirdly, embodiments of the present invention also provide an electronic device, comprising:

[0047] At least one processor; and a memory communicatively connected to said at least one processor;

[0048] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the detour method determination method as described in any of the first aspects.

[0049] Fourthly, embodiments of the present invention also provide a storage medium containing computer-executable instructions, characterized in that the computer-executable instructions, when executed by a computer processor, are used to perform the detour method determination method as described in any of the first aspects.

[0050] Fifthly, this application provides a computer program product including computer instructions that, when executed on a computer, cause the computer to perform the detour method determination method provided in the first aspect.

[0051] It should be noted that the aforementioned computer instructions may be stored, in whole or in part, on a computer-readable storage medium. This computer-readable storage medium may be packaged together with the processor of the bypass mode determining device, or it may be packaged separately from the processor of the bypass mode determining device; this application does not impose any limitations on this.

[0052] The descriptions of the second, third, fourth, and fifth aspects in this application can be referred to the detailed description of the first aspect; and the beneficial effects of the descriptions of the second, third, fourth, and fifth aspects can be referred to the analysis of the beneficial effects of the first aspect, which will not be repeated here.

[0053] In this application, the name of the aforementioned bypass method determination device does not limit the equipment or functional module itself. In actual implementation, these devices or functional modules may appear under other names. As long as the function of each device or functional module is similar to that of this application, it falls within the scope of the claims of this application and its equivalents.

[0054] These or other aspects of this application will become more readily apparent in the following description. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0056] Figure 1 A flowchart of a method for determining a detour route provided in an embodiment of the present invention;

[0057] Figure 2 A flowchart of another method for determining a detour route provided in an embodiment of the present invention;

[0058] Figure 3 This is a schematic diagram illustrating the determination of a dynamic obstacle rectangle in a detour method provided in an embodiment of the present invention;

[0059] Figure 4a and 4b This is a schematic diagram illustrating the division of a passage area in a method for determining a detour route according to an embodiment of the present invention;

[0060] Figure 5 This is a schematic diagram of a bypass mode determination device provided in an embodiment of the present invention;

[0061] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0062] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0063] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0064] The terms "first" and "second," etc., used in the specification and drawings of this application are used to distinguish different objects or to distinguish different treatments of the same object, rather than to describe a specific order of objects.

[0065] Furthermore, the terms "comprising" and "having," and any variations thereof, used in the description of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0066] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the figures. The process can correspond to a method, function, procedure, subroutine, subroutine, etc. Moreover, embodiments and features in the embodiments of the present invention can be combined with each other without conflict.

[0067] It should be noted that in the embodiments of this application, the words "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0068] In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0069] Figure 1 This is a flowchart of a detour method determination method provided by an embodiment of the present invention. This embodiment is applicable to situations where it is necessary to determine the detour method of a vehicle around an obstacle. This method can be executed by a detour method determination device, such as... Figure 1 As shown, the specific steps include the following:

[0070] Step 110: Determine sampling points within the vehicle's travel area, and perform dynamic planning on the vehicle based on obstacles within the travel area and the sampling points to obtain multiple coarse trajectories.

[0071] Specifically, when a vehicle operates in autonomous driving mode, it can plan its trajectory within a designated travel area, which is determined by the lane the vehicle is currently in. After determining the travel area, sampling points can be determined within the travel area based on preset sampling rules. An sl coordinate system is constructed with the reference line origin as the origin, the forward direction of the reference line as the positive s direction, and the left side of the forward direction as the positive l direction. Obstacles within the travel area are identified; these obstacles can include static and dynamic obstacles. For static obstacles, the rectangular outline of the obstacle can be projected onto the sl coordinate system to obtain the sl coordinate set of the four corner points of the static obstacle. An array of static obstacles is then determined based on each static obstacle and its four corner coordinate sets. For dynamic obstacles, a preset dynamic time can be obtained, which is the minimum value between the trajectory prediction time of the dynamic obstacle and the vehicle's speed-planned trajectory time. The system iterates through the preset time steps, obtaining the SL coordinates of the four corner points of the obstacle rectangle projected onto the SL coordinate system for each time step. Based on each dynamic obstacle and its SL coordinates at each time step, a dynamic obstacle array is determined. Furthermore, if there is no predicted trajectory for a dynamic obstacle at any time step, the position of the obstacle is obtained through linear interpolation, and the SL coordinates of the four corner points of the obstacle rectangle projected onto the SL coordinate system for that time step are determined based on the obstacle's position.

[0072] In practical applications, in order to improve the accuracy of calculations, the obstacle rectangle can be appropriately enlarged and expanded during the projection onto the sl coordinate system. The size of the enlargement and expansion is related to the obstacle type and the speed of movement. That is, the expansion factor of dynamic obstacles is greater than that of static obstacles, and the expansion factor of dynamic obstacles with high movement speed is greater than that of dynamic obstacles with low movement speed.

[0073] Obstacle information can be composed of a static obstacle array and a dynamic obstacle array. Based on the sampling points within the passage area and the obstacle information, dynamic planning is performed on the vehicle. Specifically, using the 's' direction in the sl coordinate system as the column direction and the 'l' direction as the row direction, starting from the vehicle's current planning starting point, the sampling points in each row between adjacent columns within the passage area are iterated, and a curve is fitted between the two points using a fifth-order polynomial. The cumulative loss value between each sampling point in the previous column and each sampling point in the next column is calculated according to a preset step size of 's'. As 's' increases, the cumulative loss value gradually increases, eventually yielding the cumulative loss value for all sampling points. The cumulative loss values ​​of each sampling point are compared, and the points with the smallest cumulative loss value in each column are selected to form a point set, resulting in multiple coarse planning trajectories.

[0074] It should be noted that the cumulative loss value is determined by the trajectory smoothness loss function and the obstacle loss function. The trajectory smoothness loss function is used to measure the trajectory smoothness of the planned coarse trajectory formed by the sampling points, and the obstacle loss function is used to measure the distance between the vehicle and obstacles when the vehicle is traveling based on the planned coarse trajectory formed by the sampling points.

[0075] In this embodiment of the invention, dynamic planning of vehicles is performed based on sampling points and obstacles within the passage area to obtain multiple coarse planning trajectories.

[0076] Step 120: Determine the detour labels of the sampling points and secondary sampling points that constitute each of the planned coarse trajectories based on the obstacles, and divide the passage area into multiple sub-regions based on the detour labels of each of the sampling points and secondary sampling points.

[0077] Specifically, for each planned coarse trajectory, secondary sampling can be performed between the sampling points constituting the planned coarse trajectory to obtain secondary sampling points constituting the planned coarse trajectory. Then, based on obstacle information, detour labels for the sampling points and secondary sampling points constituting the planned coarse trajectory can be determined. First, the vehicle can be projected onto each sampling point and each secondary sampling point to obtain the vehicle bounding box corresponding to each sampling point and each secondary sampling point. Second, obstacles within a preset range of each sampling point and each secondary sampling point can be determined. For static obstacles, the detour label for the sampling point or secondary sampling point can be determined based on the positional relationship between the static obstacle bounding box and the vehicle bounding box. For dynamic obstacles, the dynamic preset time of the dynamic obstacle can be traversed according to a preset time step to determine the dynamic obstacle bounding box corresponding to each time step. After determining the time when the vehicle arrives at the sampling point or secondary sampling point, if the time when the vehicle arrives at the sampling point or secondary sampling point overlaps with the time step of the dynamic obstacle, the detour label for the sampling point or secondary sampling point is determined based on the positional relationship between the dynamic obstacle bounding box and the vehicle bounding box.

[0078] Furthermore, the passage area can be divided into multiple sub-regions based on the detour labels of each sampling point and each secondary sampling point. Specifically, if the detour labels of each sampling point and each secondary sampling point in adjacent columns are consistent, the two columns are divided into one sub-region; otherwise, the two columns are divided into different sub-regions, thus dividing the passage area into multiple sub-regions.

[0079] In this embodiment of the invention, the detour labels of the sampling points and secondary sampling points are determined based on the positional relationship between the vehicle rectangles of the sampling points and secondary sampling points constituting each planned coarse trajectory and the obstacle rectangles within the preset range of the sampling points and secondary sampling points. Furthermore, the passage area is divided into multiple sub-regions based on the detour labels of each sampling point and each secondary sampling point, thereby achieving the division of the passage area.

[0080] Step 130: After determining the target coarse trajectory for each sub-region, determine the target planning coarse trajectory based on the loss value of each target coarse trajectory.

[0081] The loss value of the target coarse trajectory is determined by the obstacle, the sampling points constituting the target coarse trajectory, the secondary sampling points, and the historical trajectory.

[0082] Specifically, after dividing the traffic area into multiple sub-regions, the planned coarse trajectory for each sub-region can be determined, as well as the dynamic planning loss for each planned coarse trajectory within each sub-region. The planned coarse trajectory with the minimum loss within each sub-region is then identified as the target coarse trajectory for that sub-region. Furthermore, the loss value for each target coarse trajectory can be determined, specifically based on the historical trajectory deviation loss function and the obstacle loss function. The target coarse trajectory with the highest loss value is then identified as the target planned coarse trajectory.

[0083] In this embodiment of the invention, after determining the target coarse trajectory in each sub-region based on the dynamic planning loss of each planned coarse trajectory in each sub-region, the loss value of each target coarse trajectory is determined, and the target planned coarse trajectory is determined based on the loss value of each target coarse trajectory, thereby realizing the determination of the target planned coarse trajectory.

[0084] Step 140: Determine the vehicle's detour method for the target obstacle based on the positional relationship between the target obstacle and the target planned coarse trajectory.

[0085] When determining the cumulative loss value of each sampling point based on the trajectory smoothness loss function and the obstacle loss function, if an obstacle has an increasing effect on the cumulative loss value of any sampling point, then that obstacle is identified as the target obstacle.

[0086] Specifically, firstly, the corresponding target point of the target obstacle in the target planning coarse trajectory can be determined. That is, the trajectory point closest to the target obstacle in the target coarse trajectory can be determined as the corresponding target point of the target obstacle in the target planning coarse trajectory. Secondly, the positional relationship between the target obstacle and the target planning coarse trajectory can be determined based on the positional relationship between the target obstacle and the corresponding target point of the target obstacle in the target planning coarse trajectory. Then, the detour method of the vehicle for the target obstacle can be determined based on the positional relationship between the target obstacle and the target planning coarse trajectory. That is, if the target planning coarse trajectory is on the left side of the target obstacle, the detour method for the target obstacle is determined to be to the left. If the target planning coarse trajectory is on the right side of the target obstacle, the detour method for the target obstacle is determined to be to the right.

[0087] In this embodiment of the invention, the vehicle's detour method for the target obstacle is determined based on the positional relationship between the target obstacle and the target planned coarse trajectory. This provides accurate detour suggestions for the vehicle when it approaches the target obstacle, reduces the occurrence of repeated detours around the obstacle, and improves the accuracy and efficiency of path planning.

[0088] The detour method provided in this embodiment of the invention includes: determining sampling points within the vehicle's travel area; dynamically planning the vehicle based on obstacles within the travel area and the sampling points to obtain multiple planned coarse trajectories; determining detour labels for the sampling points and secondary sampling points constituting each of the planned coarse trajectories based on the obstacles; dividing the travel area into multiple sub-regions based on the detour labels for each of the sampling points and secondary sampling points; determining the target coarse trajectory for each of the sub-regions; determining the target planned coarse trajectory based on the loss value of each target coarse trajectory, wherein the loss value of the target coarse trajectory is determined by the obstacles, the sampling points and secondary sampling points constituting the target coarse trajectory, and historical trajectories; and determining the vehicle's detour method for the target obstacle based on the positional relationship between the target obstacle and the target planned coarse trajectory. The above technical solution firstly identifies sampling points within the vehicle's travel area by sampling the area. Based on these sampling points and obstacles, multiple coarse trajectories are dynamically planned to determine the vehicle's initial path. After identifying the sampling points and secondary sampling points that constitute each coarse trajectory, detour labels are determined based on the positional relationship between the vehicle's bounding box and the obstacle bounding boxes within a preset range of these points. The travel area is then divided into multiple sub-regions based on these detour labels. Secondly, the target coarse trajectory in each sub-region is determined based on the dynamic planning loss of each coarse trajectory. The target coarse trajectory is then determined based on the loss value of each target coarse trajectory. Finally, the vehicle's detour method for the target obstacle is determined based on the positional relationship between the obstacle and the target coarse trajectory, providing precise detour suggestions for path planning near the obstacle, reducing repeated detours, and improving the accuracy and efficiency of path planning.

[0089] Figure 2 This is a flowchart illustrating another method for determining a detour route according to an embodiment of the present invention. This embodiment is a specific modification based on the above embodiments. Figure 2 As shown, in this embodiment, the method may further include:

[0090] Step 210: Generate a reference line based on the vehicle's current location and the global planned path, and determine the passage area based on the vehicle's current planned starting point, the reference line, and environmental information.

[0091] In one embodiment, step 210 may specifically include:

[0092] Starting from the current position, extend forward a preset distance along the global planning path to generate the reference line; starting from the current planning starting point, determine multiple aiming points on the reference line based on a preset step size; determine the side boundaries corresponding to each aiming point according to the lane line type on both sides of each aiming point determined by the environmental information; and determine the passage area according to the side boundaries corresponding to each aiming point.

[0093] Specifically, the vehicle can acquire information about its surrounding environment and perform global planning based on this information, thus obtaining global planning information. After determining the vehicle's global planning information, a reference line is generated by extending forward a preset distance along the globally planned path from the vehicle's current position. The specific value of the preset distance is related to the accuracy of the radar and image acquisition device installed on the vehicle.

[0094] Furthermore, starting from the vehicle's current planned starting point, multiple aiming points are determined along the reference line based on a preset step size. For example, aiming forward 100m along the reference line at 0.5m increments, 200 aiming points are determined. The lane line type on both sides of each aiming point is determined based on environmental information. Specifically, taking the left side of the aiming point as an example, if the lane line to the left of the aiming point is a solid line, the left boundary of the lane containing the reference line is determined as the left boundary of the passage area; if the lane line to the left of the aiming point is a dashed line, it is determined whether there is an adjacent lane to the left of the aiming point. If there is an adjacent lane to the left, the left boundary of the adjacent lane to the left is determined as the left boundary of the passage area; if there is no adjacent lane to the left, the left boundary of the lane containing the reference line is determined as the left boundary of the passage area. The right boundary of the passage area can be determined using the same steps, and the rear and front boundaries of the passage area can be determined based on the current planned starting point and a preset distance. Furthermore, the passage area can be determined based on the left, right, rear, and front boundaries.

[0095] In this embodiment of the invention, after generating a reference line based on the vehicle's current position and the global planned path, the passable area is determined based on the vehicle's current planned starting point, the reference line, and environmental information, thereby accurately determining the vehicle's passable range and facilitating vehicle path planning.

[0096] Step 220: Determine sampling points within the vehicle's passage area.

[0097] Specifically, sampling can be performed within the passage area based on preset sampling rules to determine sampling points. The preset sampling rules can be sampling at equal intervals or sampling at equal number of points, etc.

[0098] Of course, during sampling, denser sampling can be performed in areas close to vehicles, and sparser sampling can be performed in areas far away from vehicles.

[0099] In this embodiment of the invention, sampling points are determined within the vehicle's passage area.

[0100] Step 230: Perform dynamic planning on the vehicle based on the obstacles in the passage area and the sampling points to obtain multiple coarse trajectories.

[0101] In one implementation, step 230 may specifically include:

[0102] The trajectory smoothness loss value of each sampling point is determined based on the location information of each sampling point, the obstacle loss value of each sampling point is determined based on the location information of each sampling point and the obstacles, and the cumulative loss value of each sampling point is determined based on the trajectory smoothness loss value and the obstacle loss value. Multiple planned coarse trajectories are constructed based on the sampling point with the smallest cumulative loss value among the sampling points in each column.

[0103] Specifically, after determining the coordinates of the sampling point in the sl coordinate system, the trajectory smoothness loss value of the sampling point is determined based on its coordinates in the sl coordinate system. The trajectory smoothness loss function consists of the loss function in the l-direction, the loss function of the derivative of l with respect to s (dl), and the loss function of the second derivative of l with respect to s (ddl). The loss function in the l-direction has the characteristic that the larger l is, the larger the loss function value; the loss function of the derivative of l with respect to s (dl) has the characteristic that the larger dl is, the larger the loss function value; and the loss function of the second derivative of l with respect to s (ddl) has the characteristic that the larger ddl is, the larger the loss function value. The loss functions in the l-direction, the loss function of the derivative of l with respect to s (dl), and the loss function of the second derivative of l with respect to s (ddl) can be composed of proportional functions, exponential functions, or quadratic functions, but are not limited to these functional forms.

[0104] For example, the trajectory smoothness loss value of the sampling points can be determined based on Formula 1.

[0105]

[0106] Where cost1 represents the trajectory smoothness loss function, cost l_i =k l *l*l represents the loss value of the i-th sampling point in the l-direction, where l represents the coordinate of the i-th sampling point in the l-direction, and k l Cost represents the proportionality coefficient. dl_i =k dl *dl*dl, where dl represents the derivative of l with respect to s at the i-th sampling point, k dl Cost represents the proportionality coefficient. ddl_i =k ddl *ddl*ddl, where ddl represents the second derivative of l with respect to s at the i-th sampling point, k ddlThis represents the scaling factor, and n represents the number of sampling points within the passage area.

[0107] When the obstacle is a static obstacle, static obstacles located outside the vehicle's left and right adjacent lanes in the l direction and those located more than a preset distance from the vehicle in the s direction do not cause any loss and can be ignored when calculating the obstacle loss value; for static obstacles located in the vehicle's left and right adjacent lanes in the l direction, the closer they are to the vehicle's lateral distance, the greater the obstacle loss value; if the obstacle rectangle overlaps with the vehicle rectangle projected onto the sampling point, then there is a collision at that sampling point, and the obstacle loss value is infinite.

[0108] When the obstacle is a dynamic obstacle, the current speed planning trajectory of the vehicle is obtained. On the one hand, the speed planning trajectory obtained by the vehicle in the previous cycle can be used as the current speed planning trajectory of the vehicle. On the other hand, taking the current planning starting point as the starting point, only considering the vehicle's cruising speed, lane speed limit, curve speed limit and vehicle dynamics characteristics, a quadratic planning algorithm is applied to obtain the current speed planning trajectory of the vehicle. Figure 3 This is a schematic diagram illustrating the determination of a dynamic obstacle rectangle in a detour method provided in an embodiment of the present invention, as shown below. Figure 3 As shown, the dynamic preset time of the dynamic obstacle is traversed with a preset time step. The vehicle's current speed is used to plan the trajectory. The vehicle is projected onto the corresponding time step position to obtain the dynamic obstacle rectangle at the corresponding time step position. The dynamic obstacle rectangle is used as the static obstacle rectangle to calculate the obstacle loss value.

[0109] For example, the obstacle loss value of the sampling point can be determined based on Formula 2.

[0110]

[0111] Where cost2 represents the obstacle loss function, dis_thred represents the distance threshold, and delta_l j k represents the distance from the i-th sampling point to the j-th obstacle in the l-direction. obs Here, n represents the number of sampling points within the passage area, and m represents the number of obstacles within the passage area.

[0112] Furthermore, the cumulative loss value of a sampling point can be determined by summing the trajectory smoothness loss value and the obstacle loss value, thus establishing COST1 = cost1 + cost2, where COST1 represents the cumulative loss function of the sampling point. After determining the cumulative loss value of each sampling point, the cumulative loss values ​​of each column of sampling points are compared, and multiple coarse trajectories are constructed based on the sampling point with the smallest cumulative loss value among all columns.

[0113] In addition, when determining the obstacle loss value of each sampling point based on the location information of each sampling point and each obstacle, the method further includes:

[0114] If it is determined that the obstacle increases the obstacle loss value at the sampling point, then the obstacle is determined to be the target obstacle.

[0115] When determining the obstacle loss value at each sampling point, for static obstacles, if an obstacle increases the obstacle loss value at any sampling point, then the obstacle is determined to have an impact on lateral planning and is identified as a target obstacle. For dynamic obstacles, if the obstacle projection frame increases the obstacle loss value at any sampling point, the obstacle projection frame is identified as a static obstacle and is identified as a target obstacle. Furthermore, the position information of the target obstacle is determined by the projection position of the obstacle projection frame.

[0116] In this embodiment of the invention, dynamic planning of vehicles is performed based on sampling points and obstacles within the passage area to obtain multiple coarse planning trajectories.

[0117] Step 240: Determine the detour labels of the sampling points and secondary sampling points that constitute each of the planned coarse trajectories based on the obstacles.

[0118] In one implementation, step 240 may specifically include:

[0119] The planned coarse trajectories are sampled a second time to obtain the secondary sampling points that constitute the planned coarse trajectories; based on the location information of the sampling points that constitute the planned coarse trajectories and the secondary sampling points, and the obstacles, the detour labels of the secondary sampling points are determined.

[0120] Specifically, for each planned coarse trajectory, secondary sampling can be performed between the sampling points that constitute the planned coarse trajectory to obtain secondary sampling points that constitute the planned coarse trajectory. The sampling rules can also be equal-interval sampling or equal-number-point sampling, etc.

[0121] Further, determining the detour label for each secondary sampling point based on the position information of the sampling points constituting each of the planned coarse trajectories and each of the secondary sampling points, and each of the obstacles, includes:

[0122] When the obstacle is a static obstacle, the detour label of the secondary sampling point is determined based on the positional relationship between the vehicle rectangle when the vehicle is projected onto the sampling point or the secondary sampling point and the obstacle rectangle within a preset range of the sampling point or the secondary sampling point. When the obstacle is a dynamic obstacle, the vehicle rectangle and projection time of the vehicle at the sampling point or the secondary sampling point are determined by projecting the predicted trajectory of the vehicle onto the sampling point or the secondary sampling point. The obstacle rectangle at the projection time is determined in the predicted trajectory of the obstacle. The detour label of the sampling point or the secondary sampling point is determined based on the positional relationship between the vehicle rectangle and the obstacle rectangle corresponding to the same projection time.

[0123] When the obstacle is a static obstacle, determine the positional relationship between the vehicle's bounding box when projected onto the sampling point or secondary sampling point and the obstacle's bounding box within the preset range of the sampling point or secondary sampling point. If the positional relationship overlaps, the detour label for that point is determined to be "static crossing". If the positional relationship is such that the vehicle's bounding box is to the left of the obstacle's bounding box and the detour label for the preceding point is not unknown, the detour label for that point is determined to be "static crossing". If the positional relationship is such that the vehicle's bounding box is to the left of the obstacle's bounding box and the detour label for the preceding point is unknown, the detour label for that point is determined to be "left detour". If the positional relationship is such that the vehicle's bounding box is to the right of the obstacle's bounding box and the detour label for the preceding point is not unknown, the detour label for that point is determined to be "static crossing". If the positional relationship is such that the vehicle's bounding box is to the right of the obstacle's bounding box and the detour label for the preceding point is unknown, the detour label for that point is determined to be "right detour".

[0124] When the obstacle is a dynamic obstacle, before encountering any obstacle, the detour label of the sampling point or secondary sampling point is determined to be unknown. If there is no obstacle within the preset range of the sampling point or secondary sampling point, the detour label of this point is determined based on the detour label of its preceding point. If there is an obstacle within the preset range of the sampling point or secondary sampling point, the positional relationship between the vehicle rectangle and the obstacle rectangle corresponding to the same projection time is determined. If the positional relationship overlaps, the detour label of this point is determined to be dynamic crossing, and the positional relationship is that the vehicle rectangle is located to the left of the obstacle rectangle and the preceding point of this point... When the detour label of a point is not unknown, the detour label of that point is determined to be dynamic crossing. The positional relationship is that the vehicle rectangle is to the left of the obstacle rectangle and the detour label of the preceding point is unknown. When the detour label of a point is unknown, the detour label of that point is determined to be left detour. When the positional relationship is that the vehicle rectangle is to the right of the obstacle rectangle and the detour label of the preceding point is unknown, the detour label of that point is determined to be dynamic crossing. When the positional relationship is that the vehicle rectangle is to the right of the obstacle rectangle and the detour label of the preceding point is unknown, the detour label of that point is determined to be right detour.

[0125] In this embodiment of the invention, detour labels for sampling points and secondary sampling points are determined based on the positional relationship between the vehicle rectangles constituting each planned coarse trajectory and the obstacle rectangles within a preset range of the sampling points and secondary sampling points.

[0126] Step 250: Divide the passage area into multiple sub-regions according to the detour labels of each sampling point and each secondary sampling point.

[0127] In one implementation, step 250 may specifically include:

[0128] The passage area is divided into multiple sub-regions based on the detour labels of each sampling point and each secondary sampling point belonging to the same column.

[0129] Figure 4a and 4b This is a schematic diagram illustrating the division of traffic areas in a detour method provided by an embodiment of the present invention, as shown below. Figure 4a and 4b As shown, the detour labels of each sampling point and each secondary sampling point belonging to the same column are determined. If the detour labels of each sampling point and each secondary sampling point belonging to adjacent columns are consistent, the two columns are divided into one sub-region. Otherwise, the two columns are divided into different sub-regions, thereby dividing the passage area into multiple sub-regions.

[0130] In this embodiment of the invention, the passage area is divided into multiple sub-regions based on the detour labels of each sampling point and each secondary sampling point, thereby achieving the division of the passage area.

[0131] Step 260: Determine the target coarse trajectory for each of the sub-regions.

[0132] In one implementation, step 260 may specifically include:

[0133] Determine the dynamic planning loss value of each coarse trajectory within each sub-region, and determine the coarse trajectory with the smallest dynamic planning loss value within each sub-region as the target coarse trajectory for each sub-region.

[0134] Before determining the target coarse trajectory for each sub-region, the planned coarse trajectory can be pruned to improve efficiency. Specifically, if any point constituting the planned coarse trajectory has a collision, that point is pruned, and all planned coarse trajectories including that point do not need to be calculated; if the detour label of any point constituting the planned coarse trajectory is a static crossing, that point is pruned, and all planned coarse trajectories including that point do not need to be calculated; if the trajectory curvature of any two adjacent points constituting the planned coarse trajectory is greater than a preset curvature, the planned coarse trajectory is pruned.

[0135] Specifically, the dynamic programming loss value of each planned coarse trajectory in each sub-region can be determined based on position loss, velocity loss, obstacle loss, and time loss. For each sub-region, the dynamic programming loss values ​​of each planned coarse trajectory in the sub-region are sorted, and the planned coarse trajectory corresponding to the minimum dynamic programming loss value is determined as the target coarse trajectory of the sub-region.

[0136] In this embodiment of the invention, the target coarse trajectory in each sub-region is determined based on the dynamic planning loss of each planned coarse trajectory in each sub-region.

[0137] Step 270: Determine the target planning coarse trajectory based on the loss value of each target coarse trajectory.

[0138] The loss value of the target coarse trajectory is determined by the obstacle, the sampling points constituting the target coarse trajectory, the secondary sampling points, and the historical trajectory.

[0139] In one implementation, step 270 may specifically include:

[0140] Based on the location information of each sampling point constituting each target coarse trajectory and the projection position of each sampling point constituting each target coarse trajectory on the historical trajectory, the historical trajectory deviation loss value of each target coarse trajectory is determined; based on the location information of each sampling point constituting each planned coarse trajectory and each obstacle, the obstacle loss value of each target coarse trajectory is determined; based on the historical trajectory deviation loss value and the obstacle loss value of each target coarse trajectory, the loss value of each target coarse trajectory is determined; the target coarse trajectory with the smallest loss value is determined as the target planned coarse trajectory.

[0141] Specifically, the characteristics of the historical trajectory deviation loss function are: the greater the distance of deviation from the historical trajectory in the l direction, the greater the loss value. The historical trajectory deviation loss function can be composed of a proportional function, an exponential function, or a quadratic function, but is not limited to these functional forms.

[0142] For example, the historical trajectory deviation loss value of the target coarse trajectory can be determined based on Formula 3.

[0143]

[0144] Among them, cost his_i The cost represents the trajectory deviation loss function for the i-th sampling point that constitutes the coarse trajectory of the target. his_i =k his *(l curr_i -l his_i )*(l curr_i -l his_i ), l curr_i This represents the l-coordinate of the i-th point in the coarse trajectory of the target after unifying the target coarse trajectory and historical trajectories into the sl coordinate system. his_i This represents the l-coordinate of the projection point of the i-th point on the historical trajectory after unifying the target coarse trajectory and the historical trajectory into the sl coordinate system, where k represents the target coarse trajectory. his This represents the proportionality coefficient.

[0145] Step 230 above has already determined the obstacle loss value of each sampling point. After determining the sampling points that constitute each planned coarse trajectory, the obstacle loss value of each target coarse trajectory can be determined based on the obstacle loss values ​​of the sampling points that constitute each planned coarse trajectory. When determining the obstacle loss value of the sampling points that constitute each planned coarse trajectory based on Formula 2, delta_l j denoted by , n represents the distance in the l direction from the i-th sampling point that constitutes each coarse trajectory of the plan to the j-th obstacle, n represents the number of sampling points that constitute each coarse trajectory of the plan, and m represents the number of obstacles within the preset range of each coarse trajectory of the plan.

[0146] Furthermore, the loss value of each target coarse trajectory can be determined by summing the historical trajectory deviation loss value and obstacle loss value. This allows us to determine COST2 = cost2 + cost3, where COST2 represents the loss function of the target coarse trajectory. After determining the loss value of each target coarse trajectory, the loss values ​​are compared, and the target coarse trajectory with the smallest loss value is determined as the target planning coarse trajectory.

[0147] In this embodiment of the invention, the target planning coarse trajectory is determined based on the loss value of each target coarse trajectory.

[0148] Step 280: Determine the vehicle's detour method for the target obstacle based on the positional relationship between the target obstacle and the target planned coarse trajectory.

[0149] In one implementation, step 280 may specifically include:

[0150] The target point corresponding to the target obstacle is determined in the target planning coarse trajectory; the detour method of the vehicle for the target obstacle is determined according to the positional relationship between the target obstacle and the target point corresponding to the target obstacle.

[0151] Specifically, the corresponding target point of the target obstacle in the target planning coarse trajectory can be determined, that is, the trajectory point closest to the target obstacle in the target coarse trajectory can be determined as the corresponding target point of the target obstacle in the target planning coarse trajectory.

[0152] Further, determining the vehicle's detour method for the target obstacle based on the positional relationship between the target obstacle and the target point corresponding to the target obstacle includes:

[0153] When the target point corresponding to the target obstacle is located to the left of the target obstacle, the vehicle's detour method for the target obstacle is determined to be to detour to the left; when the target point corresponding to the target obstacle is located to the right of the target obstacle, the vehicle's detour method for the target obstacle is determined to be to detour to the right.

[0154] In this embodiment of the invention, the vehicle's detour method for the target obstacle is determined based on the positional relationship between the target obstacle and the target planned coarse trajectory. This provides accurate detour suggestions for the vehicle when it approaches the target obstacle, reduces the occurrence of repeated detours around the obstacle, and improves the accuracy and efficiency of path planning.

[0155] The detour determination method provided in this embodiment of the invention includes: generating a reference line based on the vehicle's current position and a globally planned path; determining the passage area based on the vehicle's current planning starting point, the reference line, and environmental information; determining sampling points within the vehicle's passage area; performing dynamic planning on the vehicle based on obstacles within the passage area and the sampling points to obtain multiple planned coarse trajectories; determining detour labels for the sampling points and secondary sampling points constituting each planned coarse trajectory based on the obstacles; dividing the passage area into multiple sub-regions based on the detour labels of each sampling point and each secondary sampling point; determining the target coarse trajectory for each sub-region; determining the target planned coarse trajectory based on the loss value of each target coarse trajectory; and determining the vehicle's detour method for the target obstacle based on the positional relationship between the target obstacle and the target planned coarse trajectory. The above technical solution first generates a reference line based on the vehicle's current position and the globally planned path. Then, it determines the passable area based on the vehicle's current planning starting point, the reference line, and environmental information, accurately determining the vehicle's passable range and facilitating path planning. Secondly, it identifies sampling points within the passable area by sampling the area, and dynamically plans multiple coarse trajectories based on these sampling points and obstacles, thus determining the initial path plan. After determining the sampling points and secondary sampling points that constitute each coarse trajectory, it identifies obstacles within the vehicle's bounding box and the preset range of these sampling points and secondary sampling points. The positional relationship of the bounding box determines the detour labels of the sampling points and secondary sampling points. Based on the detour labels of each sampling point and secondary sampling point, the passage area is divided into multiple sub-regions, thus achieving the division of the passage area. Then, the target coarse trajectory in each sub-region is determined based on the dynamic planning loss of each planned coarse trajectory. The target planned coarse trajectory is determined based on the loss value of each target coarse trajectory, thus achieving the determination of the target planned coarse trajectory. Furthermore, the detour method of the vehicle for the target obstacle can be determined based on the positional relationship between the target obstacle and the target planned coarse trajectory. This provides accurate detour suggestions for path planning near the target obstacle, reduces the occurrence of repeated detours around the obstacle, and improves the accuracy and efficiency of path planning.

[0156] Figure 5 This is a schematic diagram of a detour pattern determination device provided in an embodiment of the present invention. This device can be applied to situations requiring the determination of a vehicle's detour pattern around obstacles. The device can be implemented through software and / or hardware and is generally integrated into electronic devices, such as computer equipment.

[0157] like Figure 5 As shown, the device includes:

[0158] The planning module 510 is used to determine sampling points within the vehicle's travel area, and to perform dynamic planning for the vehicle based on obstacles within the travel area and the sampling points to obtain multiple coarse planning trajectories.

[0159] The segmentation module 520 is used to determine the detour labels of the sampling points and secondary sampling points that constitute each of the planned coarse trajectories based on the obstacles, and to divide the passage area into multiple sub-regions based on the detour labels of each of the sampling points and secondary sampling points.

[0160] The determination module 530 is used to determine the target coarse trajectory of each sub-region after determining the target coarse trajectory, and then determine the target planning coarse trajectory based on the loss value of each target coarse trajectory, wherein the loss value of the target coarse trajectory is determined by the obstacle, the sampling point constituting the target coarse trajectory, the secondary sampling point, and the historical trajectory;

[0161] The execution module 540 is used to determine the detour method of the vehicle around the target obstacle based on the positional relationship between the target obstacle and the target planned coarse trajectory.

[0162] The detour method determination device provided in this embodiment determines sampling points within the vehicle's travel area, performs dynamic planning on the vehicle based on obstacles within the travel area and the sampling points, and obtains multiple planned coarse trajectories; determines detour labels for the sampling points and secondary sampling points constituting each of the planned coarse trajectories based on the obstacles, and divides the travel area into multiple sub-regions based on the detour labels of each sampling point and each of the secondary sampling points; after determining the target coarse trajectory for each of the sub-regions, determines the target planned coarse trajectory based on the loss value of each target coarse trajectory, wherein the loss value of the target coarse trajectory is determined by the obstacles, the sampling points and secondary sampling points constituting the target coarse trajectory, and historical trajectories; and determines the vehicle's detour method for the target obstacle based on the positional relationship between the target obstacle and the target planned coarse trajectory. The above technical solution firstly identifies sampling points within the vehicle's travel area by sampling the area. Based on these sampling points and obstacles, multiple coarse trajectories are dynamically planned to determine the vehicle's initial path. After identifying the sampling points and secondary sampling points that constitute each coarse trajectory, detour labels are determined based on the positional relationship between the vehicle's bounding box and the obstacle bounding boxes within a preset range of these points. The travel area is then divided into multiple sub-regions based on these detour labels. Secondly, the target coarse trajectory in each sub-region is determined based on the dynamic planning loss of each coarse trajectory. The target coarse trajectory is then determined based on the loss value of each target coarse trajectory. Finally, the vehicle's detour method for the target obstacle is determined based on the positional relationship between the obstacle and the target coarse trajectory, providing precise detour suggestions for path planning near the obstacle, reducing repeated detours, and improving the accuracy and efficiency of path planning.

[0163] Based on the above embodiments, the device further includes:

[0164] The generation module is used to generate a reference line based on the vehicle's current position and global planned path before determining sampling points within the vehicle's travel area, and to determine the travel area based on the vehicle's current planned starting point, the reference line, and environmental information.

[0165] In one embodiment, a reference line is generated based on the vehicle's current position and a globally planned path, and the passage area is determined based on the vehicle's current planned starting point, the reference line, and environmental information. This includes: generating the reference line by extending it forward a preset distance along the globally planned path from the current position; determining multiple aiming points on the reference line based on a preset step size from the current planned starting point; determining the side boundaries corresponding to each aiming point based on the lane line types on both sides of each aiming point determined by the environmental information; and determining the passage area based on the side boundaries corresponding to each aiming point.

[0166] Based on the above embodiments, the planning module 510 is specifically used for:

[0167] Sampling points are determined within the vehicle's passage area; the trajectory smoothness loss value of each sampling point is determined based on its location information; the obstacle loss value of each sampling point is determined based on its location information and the obstacles; the cumulative loss value of each sampling point is determined based on its trajectory smoothness loss value and the obstacle loss value; and multiple planned coarse trajectories are constructed based on the sampling point with the smallest cumulative loss value among the sampling points in each column.

[0168] Based on the above embodiments, module 520 is specifically used for:

[0169] The coarse trajectories of each plan are sampled a second time to obtain the secondary sampling points that constitute each coarse trajectories of each plan; the detour labels of each secondary sampling point are determined based on the location information of the sampling points that constitute each coarse trajectories of each plan and the secondary sampling points and the obstacles; the passage area is divided into multiple sub-regions based on the detour labels of the sampling points and the secondary sampling points that belong to the same column.

[0170] In one embodiment, determining detour labels for each secondary sampling point based on the position information of the sampling points and secondary sampling points constituting each of the planned coarse trajectories and each of the obstacles includes: when the obstacle is a static obstacle, determining the detour label for the secondary sampling point based on the positional relationship between the vehicle rectangle when the vehicle is projected onto the sampling point or the secondary sampling point and the obstacle rectangle of the obstacle within a preset range of the sampling point or the secondary sampling point; when the obstacle is a dynamic obstacle, determining the vehicle rectangle of the vehicle at the sampling point or the secondary sampling point and the projection time by projecting the sampling point or the secondary sampling point onto the predicted trajectory of the vehicle, determining the obstacle rectangle of the obstacle at the projection time in the predicted trajectory of the obstacle, and determining the detour label for the sampling point or the secondary sampling point based on the positional relationship between the vehicle rectangle and the obstacle rectangle of the obstacle corresponding to the same projection time.

[0171] Based on the above embodiments, module 530 is specifically used for:

[0172] The dynamic planning loss value of each planned coarse trajectory within each sub-region is determined, and the planned coarse trajectory with the smallest dynamic planning loss value within each sub-region is determined as the target coarse trajectory for each sub-region; the historical trajectory deviation loss value of each target coarse trajectory is determined based on the location information of each sampling point constituting each target coarse trajectory and the projection position of each sampling point constituting each target coarse trajectory on the historical trajectory; the obstacle loss value of each target coarse trajectory is determined based on the location information of each sampling point constituting each planned coarse trajectory and each obstacle; the loss value of each target coarse trajectory is determined based on the historical trajectory deviation loss value and the obstacle loss value; and the target coarse trajectory with the smallest loss value is determined as the target planned coarse trajectory.

[0173] Based on the above embodiments, the planning module 510 is further configured to:

[0174] When determining the obstacle loss value of each sampling point based on the location information of each sampling point and each obstacle, if it is determined that the obstacle has an increasing effect on the obstacle loss value of the sampling point, then the obstacle is determined to be the target obstacle.

[0175] Based on the above embodiments, the execution module 540 is specifically used for:

[0176] The target point corresponding to the target obstacle is determined in the target planning coarse trajectory; the detour method of the vehicle for the target obstacle is determined according to the positional relationship between the target obstacle and the target point corresponding to the target obstacle.

[0177] In one embodiment, determining the vehicle's detour method for the target obstacle based on the positional relationship between the target obstacle and the target point corresponding to the target obstacle includes: when the target point corresponding to the target obstacle is located to the left of the target obstacle, determining the vehicle's detour method for the target obstacle is to detour to the left; when the target point corresponding to the target obstacle is located to the right of the target obstacle, determining the vehicle's detour method for the target obstacle is to detour to the right.

[0178] The detour method determination device provided in this embodiment of the invention can execute the detour method determination method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the detour method determination method.

[0179] It is worth noting that in the embodiments of the above-mentioned detour method determination device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0180] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Figure 6 A block diagram of an exemplary electronic device 6 suitable for implementing embodiments of the present invention is shown. Figure 6 The electronic device 6 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0181] like Figure 6 As shown, electronic device 6 is represented in the form of a general-purpose computing electronic device. The components of electronic device 6 may include, but are not limited to: one or more processors or processing units 16, system memory 28, and bus 18 connecting different system components (including system memory 28 and processing unit 16).

[0182] Bus 18 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0183] Electronic device 6 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by electronic device 6, including volatile and non-volatile media, removable and non-removable media.

[0184] System memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Electronic device 6 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 6 Not shown; usually referred to as a "hard drive"). Although Figure 6 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0185] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of the present invention.

[0186] Electronic device 6 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable a user to interact with electronic device 6, and / or with any device that enables electronic device 6 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed through input / output (I / O) interface 22. Furthermore, electronic device 6 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 20. Figure 6 As shown, network adapter 20 communicates with other modules of electronic device 6 via bus 18. It should be understood that, although... Figure 6 Not shown, it can be combined with electronic device 6 to use other hardware and / or software modules, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0187] Processing unit 16 executes various functional applications and page displays by running programs stored in system memory 28, such as implementing the detour method determination method provided in this embodiment of the invention, which includes:

[0188] Sampling points are determined within the vehicle's travel area. Based on the obstacles within the travel area and the sampling points, the vehicle is dynamically planned to obtain multiple coarse trajectories.

[0189] Based on the obstacles, detour labels for the sampling points and secondary sampling points constituting each of the planned coarse trajectories are determined, and the passage area is divided into multiple sub-regions based on the detour labels for each of the sampling points and secondary sampling points.

[0190] After determining the target coarse trajectory for each sub-region, the target planning coarse trajectory is determined based on the loss value of each target coarse trajectory, wherein the loss value of the target coarse trajectory is determined by the obstacle, the sampling point constituting the target coarse trajectory, the secondary sampling point, and the historical trajectory;

[0191] The vehicle's detour method for the target obstacle is determined based on the positional relationship between the target obstacle and the planned coarse trajectory.

[0192] Of course, those skilled in the art will understand that the processor can also implement the technical solution of the detour mode determination method provided in any embodiment of the present invention.

[0193] This invention provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the program implements, for example, the detour method determination method provided in this invention, which includes:

[0194] Sampling points are determined within the vehicle's travel area. Based on the obstacles within the travel area and the sampling points, the vehicle is dynamically planned to obtain multiple coarse trajectories.

[0195] Based on the obstacles, detour labels for the sampling points and secondary sampling points constituting each of the planned coarse trajectories are determined, and the passage area is divided into multiple sub-regions based on the detour labels for each of the sampling points and secondary sampling points.

[0196] After determining the target coarse trajectory for each sub-region, the target planning coarse trajectory is determined based on the loss value of each target coarse trajectory, wherein the loss value of the target coarse trajectory is determined by the obstacle, the sampling point constituting the target coarse trajectory, the secondary sampling point, and the historical trajectory;

[0197] The vehicle's detour method for the target obstacle is determined based on the positional relationship between the target obstacle and the planned coarse trajectory.

[0198] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0199] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0200] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0201] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0202] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computing device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0203] Furthermore, the acquisition, storage, use, and processing of data in the technical solution of this invention all comply with the relevant provisions of national laws and regulations.

[0204] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for determining a detour route, characterized in that, include: Sampling points are determined within the vehicle's travel area. Based on the obstacles within the travel area and the sampling points, the vehicle is dynamically planned to obtain multiple coarse trajectories. Based on the obstacles, detour labels for the sampling points and secondary sampling points constituting each of the planned coarse trajectories are determined, and the passage area is divided into multiple sub-regions based on the detour labels for each of the sampling points and secondary sampling points. After determining the target coarse trajectory for each of the sub-regions, the target planning coarse trajectory is determined based on the loss value of each target coarse trajectory, wherein the loss value of the target coarse trajectory is determined by the sampling points constituting the target coarse trajectory, the obstacles, and the historical trajectory; The vehicle's detour method for the target obstacle is determined based on the positional relationship between the target obstacle and the planned coarse trajectory.

2. The method for determining the detour method according to claim 1, characterized in that, Before determining sampling points within the vehicle's travel area, the following steps are also included: A reference line is generated based on the vehicle's current location and the global planned path. The passage area is determined based on the vehicle's current planned starting point, the reference line, and environmental information.

3. The method for determining the detour method according to claim 2, characterized in that, A reference line is generated based on the vehicle's current position and the globally planned path. The passage area is determined based on the vehicle's current planned starting point, the reference line, and environmental information, including: Starting from the current position, the reference line is generated by extending forward a preset distance along the global planning path. Starting from the current planning starting point, multiple aiming points are determined on the reference line based on a preset step size. The lane line types on both sides of each aiming point are determined according to the environmental information to determine the boundary on both sides of each aiming point. The passage area is determined according to the boundary on both sides of each aiming point.

4. The method for determining the detour method according to claim 1, characterized in that, Based on the obstacles within the passage area and the sampling points, dynamic planning is performed on the vehicle to obtain multiple coarse trajectories, including: The trajectory smoothness loss value of each sampling point is determined based on the location information of each sampling point, the obstacle loss value of each sampling point is determined based on the location information of each sampling point and the obstacle, and the cumulative loss value of each sampling point is determined based on the trajectory smoothness loss value and the obstacle loss value. Multiple coarse trajectories are constructed based on the sampling point with the smallest cumulative loss value among the sampling points in each column.

5. The method for determining the detour method according to claim 1, characterized in that, Determining detour labels for the sampling points and secondary sampling points constituting each of the planned coarse trajectories based on the obstacles includes: The coarse trajectories of each of the planning trajectories are sampled a second time to obtain the second sampling points that constitute each of the coarse trajectories of the planning trajectories; Based on the location information of the sampling points constituting each of the planned coarse trajectories and each of the secondary sampling points, and the obstacles, the detour label of each of the secondary sampling points is determined.

6. The method for determining the detour method according to claim 5, characterized in that, Based on the location information of the sampling points constituting each of the planned coarse trajectories and each of the secondary sampling points, and the obstacles, a detour label for each of the secondary sampling points is determined, including: When the obstacle is a static obstacle, the detour label of the secondary sampling point is determined based on the positional relationship between the vehicle rectangle when the vehicle is projected onto the sampling point or the secondary sampling point and the obstacle rectangle of the obstacle within a preset range of the sampling point or the secondary sampling point; When the obstacle is a dynamic obstacle, the vehicle's bounding box and projection time at the sampling point or the secondary sampling point are determined by projecting the sampling point or the secondary sampling point onto the vehicle's predicted trajectory. The obstacle's bounding box at the projection time is determined in the obstacle's predicted trajectory. The detour label of the sampling point or the secondary sampling point is determined based on the positional relationship between the vehicle bounding box and the obstacle's bounding box corresponding to the same projection time.

7. The method for determining the detour method according to claim 5, characterized in that, The passage area is divided into multiple sub-regions based on the detour labels of each sampling point and each secondary sampling point, including: The passage area is divided into multiple sub-regions based on the detour labels of each sampling point and each secondary sampling point belonging to the same column.

8. The method for determining the detour method according to claim 1, characterized in that, Determining the coarse trajectory of the target in each of the sub-regions includes: Determine the dynamic planning loss value of each coarse trajectory within each sub-region, and determine the coarse trajectory with the smallest dynamic planning loss value within each sub-region as the target coarse trajectory for each sub-region.

9. The method for determining the detour method according to claim 1, characterized in that, The target planning coarse trajectory is determined based on the loss value of each target coarse trajectory, including: Based on the position information of each sampling point constituting each target coarse trajectory and the projection position of each sampling point constituting each target coarse trajectory on the historical trajectory, the historical trajectory deviation loss value of each target coarse trajectory is determined; based on the position information of each sampling point constituting each planned coarse trajectory and each obstacle, the obstacle loss value of each target coarse trajectory is determined; based on the historical trajectory deviation loss value and the obstacle loss value of each target coarse trajectory, the loss value of each target coarse trajectory is determined. The coarse trajectory of the target with the minimum loss value is determined as the coarse trajectory of the target planning.

10. The method for determining the detour method according to claim 4, characterized in that, When determining the obstacle loss value of each sampling point based on the location information of each sampling point and each obstacle, the method further includes: If it is determined that the obstacle increases the obstacle loss value at the sampling point, then the obstacle is determined to be the target obstacle.

11. The method for determining the detour method according to claim 10, characterized in that, Determining the vehicle's detour around the target obstacle based on the positional relationship between the target obstacle and the planned coarse trajectory includes: The target point corresponding to the target obstacle is determined in the target planning coarse trajectory; The vehicle's detour method for the target obstacle is determined based on the positional relationship between the target obstacle and the target point corresponding to the target obstacle.

12. The method for determining the detour method according to claim 11, characterized in that, Determining the vehicle's detour around the target obstacle based on the positional relationship between the target obstacle and the target point corresponding to the target obstacle includes: When the target point corresponding to the target obstacle is located to the left of the target obstacle, the vehicle's detour method for the target obstacle is determined to be to detour to the left; When the target point corresponding to the target obstacle is located to the right of the target obstacle, the vehicle's detour method for the target obstacle is determined to be detouring to the right.

13. A device for determining a detour pattern, characterized in that, include: The planning module is used to determine sampling points within the vehicle's travel area, and to perform dynamic planning for the vehicle based on obstacles within the travel area and the sampling points, thereby obtaining multiple coarse planning trajectories. The segmentation module is used to determine the detour labels of the sampling points and secondary sampling points that constitute each of the planned coarse trajectories based on the obstacles, and to divide the passage area into multiple sub-regions based on the detour labels of each of the sampling points and secondary sampling points. The determination module is used to determine the target coarse trajectory of each sub-region, and then determine the target planning coarse trajectory based on the loss value of each target coarse trajectory, wherein the loss value of the target coarse trajectory is determined by the obstacle, the sampling point constituting the target coarse trajectory, the secondary sampling point, and the historical trajectory; The execution module is used to determine the vehicle's detour method for the target obstacle based on the positional relationship between the target obstacle and the target planned coarse trajectory.

14. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to said at least one processor; The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the detour method determination method as described in any one of claims 1-12.

15. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the detour method determination method as described in any one of claims 1-12.

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