Path planning method, device, equipment, storage medium and vehicle

Abstract

This application provides a path planning method, apparatus, device, storage medium, and vehicle, relating to the field of autonomous driving technology. The method includes: acquiring road information of a target road where the vehicle is located and first driving information of the vehicle; wherein the first driving information indicates the current driving state of the vehicle; discretizing the target road based on the road information to obtain a discrete target road; wherein the discrete target road includes multiple drivable segments, and each drivable segment includes multiple drivable positions; determining second driving information of the vehicle at each of the drivable positions based on the first driving information and / or the road information; the second driving information indicates the driving state of the vehicle in a preset dimension; and determining the optimal driving path of the vehicle based on the second driving information. The method of this application can improve the accuracy and applicability of path planning.

Description

Technical Field

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

[0002] In the field of autonomous driving, there is a lot of research on optimizing vehicle driving routes. For example, in everyday life scenarios, the driving route with the shortest time or the least cost can be determined based on the driving start and end points specified by the user, so that the user can drive according to the optimal driving route.

[0003] However, the above implementation methods are mainly for path planning in fixed route scenarios, resulting in a relatively singular way of determining the optimal driving path and limited applicability. For example, in racing scenarios, the track is different from a regular road, and the driving requirements in racing scenarios are also different from those in general scenarios. Therefore, the above path planning methods cannot accurately determine the optimal driving path for the vehicle. Summary of the Invention

[0004] This application provides a path planning method, apparatus, device, storage medium, and vehicle that can plan more accurate optimal driving routes for users, thereby meeting the needs of complex scenarios and improving the user's driving experience.

[0005] Firstly, this application provides a path planning method, including:

[0006] Obtain road information of the target road where the vehicle is located and the vehicle's first driving information; wherein, the first driving information indicates the vehicle's current driving status;

[0007] The target road is discretized based on the road information to obtain a discrete target road; wherein, the discrete target road includes multiple drivable road segments, and each drivable road segment includes multiple drivable locations;

[0008] Based on the first driving information and / or the road information, the second driving information of the vehicle at each of the drivable locations is determined; the second driving information indicates the driving status of the vehicle in a preset dimension.

[0009] Based on the second driving information, the optimal driving path of the vehicle is determined.

[0010] In one possible implementation, the preset dimension indicates a driving speed dimension; the driving state under the driving speed dimension indicates the vehicle's exit speed from a curve; the first driving information includes vehicle position information; the road information includes the road friction coefficient; based on the first driving information and / or the road information, determining the second driving information of the vehicle at each of the drivable positions includes:

[0011] Based on the vehicle location information and the target road where the vehicle is located, the road curvature information of the target road is determined;

[0012] Based on the road friction coefficient and the road curvature information, the exit speed of the vehicle at each of the drivable positions included in the last drivable road segment is determined;

[0013] The second driving information is determined based on the exit speed from the curve.

[0014] In one possible implementation, the preset dimension further indicates a travel time dimension; the travel status under the travel time dimension indicates the vehicle's travel time; the method further includes:

[0015] Based on the vehicle's exit speed from the curve, the vehicle's speed at each drivable position within each drivable road segment is determined.

[0016] Based on the vehicle's speed and the distance the vehicle travels in each of the drivable road segments, the vehicle's travel time at each of the drivable positions in each of the drivable road segments is determined.

[0017] The second driving information is determined based on the vehicle's travel time.

[0018] In one possible implementation, the preset dimension indicates a driving safety dimension; the driving state under the driving safety dimension indicates the distance of the vehicle from the road centerline; the road information includes road width information and road boundary information; based on the first driving information and / or the road information, determining the second driving information of the vehicle at each of the drivable positions includes:

[0019] Based on the road width information and the road boundary information, the road centerline corresponding to the target road is determined;

[0020] The distance information between the vehicle and the centerline of the road at each of the drivable positions is determined, and the second driving information is determined based on the distance information.

[0021] In one possible implementation, determining the optimal driving path for the vehicle based on the second driving information includes:

[0022] Obtain third driving information; wherein, the third driving information indicates the boundary information of the vehicle's driving;

[0023] The second driving information is filtered based on the third driving information to obtain the filtered second driving information;

[0024] Based on the filtered second driving information, the optimal driving route for the vehicle is determined.

[0025] In one possible implementation, determining the optimal driving route for the vehicle based on the filtered second driving information includes:

[0026] Determine the weight information corresponding to each of the filtered second driving information;

[0027] Based on the weight information, the filtered second driving information is weighted and summed to determine the driving index data of the vehicle at each driving location.

[0028] Based on the driving index data, the target driving position is determined sequentially from each of the drivable road segments, and the optimal driving route is determined based on the target driving position in each of the drivable road segments.

[0029] In one possible implementation, the method further includes:

[0030] Based on the vehicle's current driving location and the optimal driving route, a driving reminder time and driving reminder information are determined, so that the driver of the vehicle is reminded according to the driving reminder information at the driving reminder time; wherein, the driving reminder information indicates acceleration information or deceleration information.

[0031] Secondly, this application provides a path planning device, comprising:

[0032] The acquisition unit is used to acquire road information of the target road where the vehicle is located and the vehicle's first driving information; wherein, the first driving information indicates the vehicle's current driving status;

[0033] The processing unit is configured to discretize the target road based on the road information to obtain a discrete target road; wherein the discrete target road includes multiple drivable road segments, and each drivable road segment includes multiple drivable locations;

[0034] The first determining unit is configured to determine second driving information of the vehicle at each of the drivable locations based on the first driving information and / or the road information; the second driving information indicates the driving status of the vehicle in a preset dimension.

[0035] The second determining unit is used to determine the optimal driving path of the vehicle based on the second driving information.

[0036] In one possible implementation, the preset dimension indicates the driving speed dimension; the driving state under the driving speed dimension indicates the vehicle's exit speed from a curve; the first driving information includes vehicle position information; the road information includes the road friction coefficient; in this case, the first determining unit is used to:

[0037] Based on the vehicle location information and the target road where the vehicle is located, the road curvature information of the target road is determined;

[0038] Based on the road friction coefficient and the road curvature information, the exit speed of the vehicle at each of the drivable positions included in the last drivable road segment is determined;

[0039] The second driving information is determined based on the exit speed from the curve.

[0040] In one possible implementation, the preset dimension further indicates a travel time dimension; the travel status under the travel time dimension indicates the vehicle's travel time; in this case, the first determining unit is further configured to:

[0041] Based on the vehicle's exit speed from the curve, determine the vehicle's speed at each drivable position within each drivable road segment.

[0042] Based on the vehicle's speed and the distance the vehicle travels in each of the drivable road segments, the vehicle's travel time at each of the drivable positions in each of the drivable road segments is determined.

[0043] The second driving information is determined based on the vehicle's travel time.

[0044] In one possible implementation, the preset dimension indicates a driving safety dimension; the driving state under the driving safety dimension indicates the distance of the vehicle from the road centerline; the road information includes road width information and road boundary information; in this case, the first determining unit is used to:

[0045] Based on the road width information and the road boundary information, the road centerline corresponding to the target road is determined;

[0046] The distance information between the vehicle and the centerline of the road at each of the drivable positions is determined, and the second driving information is determined based on the distance information.

[0047] In one possible implementation, the second determining unit is configured to:

[0048] Obtain third driving information; wherein, the third driving information indicates the boundary information of the vehicle's driving;

[0049] The second driving information is filtered based on the third driving information to obtain the filtered second driving information;

[0050] Based on the filtered second driving information, the optimal driving route for the vehicle is determined.

[0051] In one possible implementation, the second determining unit is configured to:

[0052] Determine the weight information corresponding to each of the filtered second driving information;

[0053] Based on the weight information, the filtered second driving information is weighted and summed to determine the driving index data of the vehicle at each driving location.

[0054] Based on the driving index data, the target driving position is determined sequentially from each of the drivable road segments, and the optimal driving route is determined based on the target driving position in each of the drivable road segments.

[0055] In one possible implementation, the device further includes a reminder unit for:

[0056] Based on the vehicle's current driving location and the optimal driving route, a driving reminder time and driving reminder information are determined, so that the driver of the vehicle is reminded according to the driving reminder information at the driving reminder time; wherein, the driving reminder information indicates acceleration information or deceleration information.

[0057] Thirdly, this application provides a computer device, including: a processor, and a memory communicatively connected to the processor;

[0058] The memory stores computer-executed instructions;

[0059] The processor executes computer execution instructions stored in the memory to implement the method described in any one of the first aspects.

[0060] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in any one of the first aspects.

[0061] Fifthly, this application provides a vehicle including an on-board terminal for implementing the method described in any one of the first aspects above.

[0062] Sixthly, this application provides a computer program product comprising: computer execution instructions stored in a readable storage medium, wherein at least one processor of a computer device can read the computer execution instructions from the readable storage medium, and the at least one processor executes the computer execution instructions to cause the computer device to perform the method described in any one of the first aspects.

[0063] The path planning method, apparatus, device, storage medium, and vehicle provided in this application can first acquire road information of the target road where the vehicle is located and the vehicle's first driving information. Then, the target road is discretized based on the road information to obtain a discrete target road. Afterwards, based on the first driving information and / or the discrete target road, the vehicle's second driving information at the target driving position can be determined, and based on the second driving information, the optimal driving path of the vehicle can be determined. This implementation method, on the one hand, can combine road information and the vehicle's driving state to determine the optimal driving path, thereby combining information from multiple preset dimensions to determine the optimal driving path. This not only allows the determined optimal driving path to adapt to the actual needs of different scenarios, improving the accuracy of the determined optimal driving path and thus enhancing the user's driving experience, but also allows adjustment of the influencing factors during path planning based on the driving state under preset dimensions, thereby improving the flexibility and scalability of path planning. On the other hand, the embodiments of this application can also first determine the optimal target driving position within each drivable road segment, and then determine the optimal driving path, thereby achieving simple and quick dynamic optimization of the path, thus improving the embeddability and real-time performance of the path planning method. Attached Figure Description

[0064] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0065] Figure 1 A flowchart illustrating a path planning method provided in an embodiment of this application;

[0066] Figure 2 A schematic diagram of a discrete target road provided in an embodiment of this application;

[0067] Figure 3 A flowchart illustrating another path planning method provided in an embodiment of this application;

[0068] Figure 4 A schematic diagram illustrating the determination of exit speed for an embodiment of this application;

[0069] Figure 5 A schematic diagram illustrating the determination of vehicle travel time, provided as an embodiment of this application;

[0070] Figure 6 A schematic diagram illustrating the determination of driving reminder time, provided as an embodiment of this application;

[0071] Figure 7 A schematic diagram of a software architecture for implementing a path planning method is provided in an embodiment of this application;

[0072] Figure 8 This is a schematic diagram of the structure of a path planning device provided in an embodiment of this application;

[0073] Figure 9 This is a schematic diagram of another path planning device provided in an embodiment of this application;

[0074] Figure 10 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application.

[0075] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0076] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0077] In this document, the term "and / or" merely describes a relationship, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0078] Currently, the existing methods for determining the optimal driving path in the field of autonomous driving mainly involve planning the path with the shortest travel time or the path with the lowest cost for the user.

[0079] This implementation method results in a single route planning approach with limited applicability, making it unable to plan the optimal driving route that meets various user needs, which can easily affect the user's driving experience.

[0080] The path planning method provided in this application aims to comprehensively consider information under multiple preset dimensions to determine the optimal driving path, thereby solving the above-mentioned technical problems of the prior art.

[0081] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0082] Figure 1 This is a flowchart illustrating a path planning method provided in an embodiment of this application, as shown below. Figure 1 As shown, this path planning method specifically includes the following steps:

[0083] S101. Obtain road information of the target road where the vehicle is located and the vehicle's first driving information; wherein, the first driving information indicates the vehicle's current driving status.

[0084] Currently, in the field of autonomous driving, the determination of the optimal driving path is mainly for fixed route scenarios. In this case, the optimal driving path can only be determined based on road information within the route, resulting in a relatively singular optimal driving path that cannot meet the path planning needs of users in various scenarios. For example, in a racetrack scenario, due to the wide track and the vehicle's non-fixed route, general path planning methods cannot meet the path planning requirements of racetrack scenarios. Therefore, in this application, the vehicle can perform real-time path planning based on road information and the vehicle's current state to obtain the optimal driving path.

[0085] Therefore, the embodiments of this application can first obtain road information of the target road where the vehicle is located and the vehicle's first driving information. Specifically, the road information and the first driving information can be obtained based on various electronic devices installed in the vehicle. For example, the road information can be obtained by processing images of the target road captured by the vehicle's camera, or the road information (e.g., road friction coefficient) can be determined based on data collected by vehicle sensors (e.g., wheel speed sensors, accelerometers, gyroscopes, etc.). In this case, the road information may include, but is not limited to, road width information, road boundary information (e.g., left and right boundary lines of the road), and road friction coefficient. Alternatively, the current driving state of the vehicle, i.e., the first driving information, can be obtained based on wheel speed sensors, a global positioning system (or lidar), an accelerometer, a steering angle sensor, etc., included in the vehicle. In this case, the first driving information can indicate at least the following: vehicle position, vehicle speed, lateral acceleration, longitudinal acceleration, steering wheel angle, etc.

[0086] Then, the optimal driving route can be determined based on the road information of the target road where the vehicle is located and the vehicle's initial driving information, as described in the steps below.

[0087] S102. Discretize the target road based on the road information to obtain a discrete target road; wherein, the discrete target road includes multiple drivable road segments, and each drivable road segment includes multiple drivable locations.

[0088] In one example, when discretizing the target road, it can be divided into multiple levels according to a first discrete parameter, resulting in multiple drivable road segments. Then, each drivable road segment is further divided into multiple drivable locations according to a second discrete parameter. Vehicles can then travel through these drivable locations within each drivable road segment, thus forming their travel path.

[0089] The first discrete parameter can take values ​​of 6, 10, 15, etc., and the second discrete parameter can take values ​​of 3, 5, 6, etc. The values ​​of the first and second discrete parameters are not limited here, and are determined according to actual needs.

[0090] At this point, the values ​​of the first and second discrete parameters can be determined based on the road width and length information of the target road, according to a preset data table. Alternatively, the values ​​of the first and second discrete parameters can be determined according to the road information of the current target road, using a preset calculation method. For example, the first discrete parameter can be determined according to a first distance interval, and the second discrete parameter can be determined according to a second distance interval.

[0091] See one example. Figure 2 , Figure 2 This is a schematic diagram of a discrete target road provided in an embodiment of this application. Figure 2 As shown, the first discrete parameter can be 6, so the target road can be divided into 6 levels, resulting in 5 drivable road segments. Figure 2 As shown, the second discrete parameter can be 6, resulting in 6 adjacent drivable locations. Then, any drivable location can be selected from each drivable road segment, and the selected drivable locations can be connected to form the vehicle's drivable path.

[0092] S103. Based on the first driving information and / or discrete target roads, determine the second driving information of the vehicle at each drivable location; the second driving information indicates the driving status of the vehicle in a preset dimension.

[0093] In one example, preset dimensions can indicate the influencing factors when planning the optimal driving path. There can be multiple preset dimensions, such as driving speed, driving safety, and driving time. Each preset dimension can have one or more influencing factors. For example, the influencing factors under the driving speed dimension could be the vehicle's exit speed from a corner; the influencing factors under the driving safety dimension could be the vehicle's distance from the centerline, the vehicle's distance from obstacles, etc.; and the influencing factors under the driving time dimension could be the vehicle's driving time, etc.

[0094] At this point, the driving status corresponding to the influencing factors under each preset dimension constitutes the second driving information.

[0095] S104. Based on the second driving information, determine the optimal driving path for the vehicle.

[0096] In one example, the optimal target driving position within each drivable road segment can be determined based on the second driving information, and the optimal driving path of the vehicle can be determined based on the optimal target driving position within each drivable road segment.

[0097] As described above, this embodiment of the application can first obtain road information of the target road where the vehicle is located and the vehicle's first driving information. Then, based on the road information, the target road is discretized to obtain a discrete target road. Afterwards, based on the first driving information and / or the discrete target road, the vehicle's second driving information at the target driving position can be determined, and based on the second driving information, the vehicle's optimal driving path can be determined. This implementation method, on the one hand, can combine road information and the vehicle's driving state to determine the vehicle's optimal driving path, thereby combining information from multiple preset dimensions to determine the optimal driving path. This not only allows the determined optimal driving path to adapt to the actual needs of different scenarios, improving the accuracy of the determined optimal driving path and thus enhancing the user's driving experience, but also allows for adjustment of the influencing factors during path planning based on the driving state under preset dimensions, thereby improving the flexibility and scalability of path planning. On the other hand, this embodiment of the application can also first determine the optimal target driving position within each drivable road segment, and then determine the optimal driving path, thereby achieving simple and quick dynamic optimization of the path, thus improving the embeddability and real-time performance of the path planning method.

[0098] Figure 3 A flowchart illustrating another path planning method provided in this application embodiment is shown below. Figure 3 As shown, this path planning method specifically includes the following steps:

[0099] S301. Obtain road information of the target road where the vehicle is located and the vehicle's initial driving information.

[0100] The first driving information indicates the vehicle's current driving status.

[0101] In one example, this step can be referred to the content described in S101 above, and will not be repeated in detail here.

[0102] S302. Discretize the target road based on the road information to obtain a discrete target road.

[0103] The discrete target road includes multiple drivable road segments, and each drivable road segment includes multiple drivable locations.

[0104] In one example, this step can be referred to the content described in S102 above, and will not be repeated in detail here.

[0105] S303. Based on the first driving information and / or discrete target roads, determine the second driving information of the vehicle at each drivable location.

[0106] The second driving information indicates the vehicle's driving status in a preset dimension.

[0107] The following examples, using different preset dimensions, illustrate how the second driving information is determined.

[0108] First, the preset dimension indicates the driving speed dimension, and the driving status under the driving speed dimension indicates the vehicle's exit speed from the curve; at this time, the first driving information includes vehicle position information, and the road information includes the road friction coefficient.

[0109] Based on this, when determining the second driving information of a vehicle at each drivable position based on the first driving information and / or road information, the road curvature information of the target road can be determined first based on the vehicle position information and the target road where the vehicle is located; then, based on the road friction coefficient and road curvature information, the exit speed of the vehicle at each drivable position included in the last drivable road segment can be determined; finally, the second driving information can be determined based on the exit speed.

[0110] See one example. Figure 4 , Figure 4 This is a schematic diagram illustrating the determination of exit speed in an embodiment of this application, as shown below. Figure 4 As shown, the vehicle's driving curve can be determined based on the vehicle's location information and the target road, and the radius information of the circular curve corresponding to the vehicle's driving curve can be determined. Based on this radius information, the road curvature information of the target road can be determined, that is, the road curvature information is the reciprocal of the radius information. Then, the vehicle's cornering speed when passing through the curve can be determined based on the road curvature information and the road friction coefficient, and the vehicle's exit speed can be determined based on the cornering speed and the straight distance traveled by the vehicle after exiting the curve. Among them, the vehicle's cornering speed when passing through the curve can be calculated according to the content described in the following formula (1).

[0111]

[0112] Where μ represents the road friction coefficient, g represents the gravitational acceleration, and c represents the road friction coefficient.

[0113] At this point, after determining the vehicle's cornering speed, the straight-line distance the vehicle travels after exiting the corner can be obtained. Based on this straight-line distance and the vehicle's maximum allowable acceleration, the vehicle's exit speed can be determined. If the straight-line distance traveled after exiting the corner exceeds a preset distance threshold (e.g., 20 meters), the calculation is performed according to this preset distance threshold, thereby improving calculation efficiency.

[0114] This implementation method can predict the vehicle's exit speed on the target road based on road curvature information and road friction data. It then determines the second driving information based on the predicted exit speed, and finally determines the optimal driving path. This method can ensure the accuracy and effectiveness of the exit speed while reducing the number of iterations in the path planning method, thereby improving the speed and efficiency of path planning and ensuring the real-time performance of the path planning method.

[0115] In one example, once the vehicle's exit speed is determined, the vehicle's speed at each drivable position on the discrete target road can be determined based on the exit speed. This allows us to determine the travel time required for the vehicle to travel each drivable segment, and then determine the optimal travel path based on the travel time.

[0116] At this point, the preset dimension also indicates the travel time dimension. The travel status under the travel time dimension indicates the vehicle's travel time. Therefore, the second travel information can also include the vehicle's travel time. Based on this, when determining the vehicle's travel time, i.e., another type of second travel information, we can first determine the vehicle's speed at each drivable position within each drivable road segment based on the vehicle's exit speed from the curve. Then, based on the vehicle's speed and the distance traveled within each drivable road segment, we can determine the vehicle's travel time corresponding to each drivable position within each drivable road segment. Finally, based on the vehicle's travel time, we determine the second travel information.

[0117] See one example. Figure 5 , Figure 5 This is a schematic diagram illustrating the determination of vehicle travel time, as provided in an embodiment of this application. Figure 5 As shown, a schematic diagram can be constructed based on the discrete target road, the drivable road segments determined by road length information, the drivable positions within each drivable road segment determined by road width information, and the vehicle speed corresponding to each drivable position. At this point, as... Figure 5 As shown, it is assumed that the driving state at the current level indicates the various drivable locations of the vehicle within the last level of the discrete target road (e.g., Figure 2 The exit speed at the drivable position within the 6th layer (as shown) can then be used to determine the vehicle's drivable position at the next higher level (e.g., ...). Figure 2The vehicle's speed at each drivable position (as shown in the 5th layer) is used to determine the vehicle's driving status at each drivable position. Then, the average speed of the vehicle between the current two drivable positions can be determined based on the vehicle speed at the current drivable position (if the current layer is the last layer, then the vehicle speed is the exit speed) and the vehicle speed at the drivable position of the previous layer. At this time, the vehicle's driving time at the current two drivable positions can be obtained by dividing the driving distance between the current two drivable positions by the average driving speed. Wherein, if the coordinates of the current drivable position are represented as (x0, y0) and the coordinates of the previous drivable position are represented as (x1, y1), then the driving distance between the current two drivable positions can be represented as shown in the following formula (2).

[0118]

[0119] At this point, we can iterate through the various drivable locations of the current level and the vehicle travel time required to travel to the various drivable locations of the next higher level, thus obtaining the vehicle travel time corresponding to each drivable location within the last drivable road segment.

[0120] This implementation method can determine the optimal route based on the travel time required for the user to reach each target location, thereby ensuring that the vehicle can quickly pass through the optimal travel route.

[0121] Secondly, the preset dimension indicates the driving safety dimension, and the driving status under the driving safety dimension indicates the distance of the vehicle from the road centerline; the road information includes the road width information and road boundary information of the target road; at this time, the first driving information includes the vehicle position information, and the road information of the target road includes the road friction coefficient. At this time, when determining the second driving information of the vehicle at each drivable position based on the first driving information and / or information, the road centerline corresponding to the target road can be determined first based on the road width information and road boundary information; then, the distance information between the vehicle at each drivable position and the road centerline can be determined, and the second driving information can be determined based on the distance information.

[0122] This implementation method can determine the distance between the vehicle and the center line of the road based on the driver's driving ability, and then perform route planning based on this distance information. This makes the obtained optimal driving path more compatible with the driver's driving ability, thereby further improving the accuracy of the determined optimal driving path.

[0123] S304. Obtain third driving information; wherein, the third driving information indicates the boundary information of the vehicle's driving.

[0124] In one example, the boundary information indicating vehicle movement as provided by the third driving information can indicate boundary limit information set by the vehicle system. For example, the boundary information indicating vehicle movement can indicate the capabilities of the vehicle's powertrain, braking system, etc. In this case, the boundary information indicating vehicle movement as provided by the third driving information can include, but is not limited to: the vehicle's longitudinal acceleration, lateral acceleration, adhesion utilization, and steering angle.

[0125] S305. Based on the third driving information, the second driving information is filtered to obtain the filtered second driving information.

[0126] For example, if it is determined that the longitudinal acceleration of the vehicle at the drivable position is less than the longitudinal acceleration of the vehicle determined by the power system's capability, and the lateral acceleration of the vehicle at the drivable position is less than the lateral acceleration of the vehicle determined by the braking system's capability, and the total acceleration of the vehicle at the drivable position (where the total acceleration of the vehicle can be understood as the sum of the squares of the longitudinal acceleration and the lateral acceleration) is less than the square of the vehicle's adhesion system, and the steering angle of the vehicle at the drivable position is less than the vehicle's steering angle requirement, then the drivable position is determined as the target driving position.

[0127] The longitudinal acceleration of a vehicle can be expressed as follows: subtract the vehicle speed of the next lower level from the vehicle speed of the current level, then divide the result by the vehicle's travel time within the current drivable road segment. The lateral acceleration of a vehicle can be expressed as follows: multiply the yaw rate of the vehicle within the current drivable road segment by the average speed of vehicles within the current drivable road segment. The yaw rate of the vehicle within the current drivable road segment is obtained by dividing the steering angle within the current drivable road segment by the vehicle's travel time; the steering angle is the angle formed by the drivable paths of vehicles in the previous drivable road segment and the drivable paths of vehicles in the current drivable road segment.

[0128] This implementation method can determine the target driving position of the vehicle based on the vehicle's driving boundary, which can ensure the feasibility and effectiveness of the target driving position included in the determined optimal driving path, thereby ensuring the effectiveness of the optimal driving path and further improving the accuracy of the determined optimal driving path.

[0129] S306. Based on the filtered second driving information, determine the optimal driving path for the vehicle.

[0130] In practice, the weight information corresponding to each filtered second driving information is determined;

[0131] Based on the weight information, the second driving information after each screening is weighted and summed to determine the driving index data of the vehicle at each driving location.

[0132] Based on driving index data, the target driving position is determined sequentially from each drivable road segment, and the optimal driving route is determined based on the target driving position in each drivable road segment.

[0133] In one example, driving index data (e.g., driving index data denoted as J) can be represented as shown in the following formula (3).

[0134]

[0135] Where n represents the number of drivable road segments that determine the target driving location, for example, when determining such... Figure 2 When the target driving position corresponds to the 5th layer shown, then n is 1. V out K1 represents the exit speed, and K1 represents the weight information corresponding to the exit speed. In this case, the value of K1 is related to the straight-line distance traveled by the vehicle after exiting the corner; the longer the straight-line distance traveled after exiting the corner, the larger the value of K1. center K1 represents the distance between the vehicle's drivable position and the road centerline. K2 represents the weight information corresponding to the distance between the vehicle's drivable position and the road centerline. The value of K2 can be determined based on the driver's driving ability; the higher the driver's ability, the smaller the value of K2. The values ​​of K1 and K2 are not limited here; the achievable value is the only criterion.

[0136] In this embodiment of the application, when determining the optimal driving route based on driving index data, the DP (Dynamic programming) inverse hierarchical numerical method can be used. By superimposing the inverse optimal solutions, the target driving position in each drivable road segment is gradually obtained, thereby determining the optimal driving route.

[0137] The above embodiments combine information from multiple dimensions, such as vehicle travel time, vehicle speed, driver's driving ability, and vehicle system performance, to perform path planning. This ensures that the optimal driving path is more closely matched to the current driving conditions, guaranteeing the real-time performance, accuracy, and effectiveness of the optimal driving path. In actual racing scenarios, this application embodiment can provide drivers with more precise driving paths on key sections of the route (e.g., curves), thereby helping to further improve the participants' performance and enhancing the user experience.

[0138] Furthermore, after determining the optimal driving path (i.e., the target driving position) according to the steps described in the above embodiments, the optimal driving path can also be used to guide the driver of the vehicle. For example, the driver can be guided based on the coordinates of the target driving position corresponding to the optimal driving path and the vehicle speed corresponding to the target driving position.

[0139] In practice, based on the vehicle's current location and optimal driving route, the driving reminder time and driving reminder information are determined so that the driver is reminded according to the driving reminder information at the driving reminder time; among them, the driving reminder information indicates acceleration or deceleration information.

[0140] See one example. Figure 6 , Figure 6 This is a schematic diagram illustrating the determination of driving reminder time, as provided in an embodiment of this application. Figure 6 As shown, assuming braking occurs during a braking scenario, line 1 represents the travel curve of the vehicle's drive unit, line 2 represents the pressure curve of the vehicle's braking system, and line 3 represents the vehicle's deceleration curve. In this case, 0-t0 can represent the driver's reaction time, t0-t1 can represent the vehicle's braking system's reaction time, and t1-t2 can represent the vehicle's reaction time. Therefore, the driving warning time can be determined as: the time t2 before the vehicle needs to accelerate / decelerate.

[0141] In one example, the display format of driving reminder information can be as follows: at the corresponding driving location in the navigation, the corresponding reminder color and reminder distance are displayed according to the reminder type. For example, at the corresponding driving location in the navigation, the road section that needs to be accelerated can be displayed by a red line (or a flashing red line), or the road section that needs to be decelerated can be displayed by a green line (or a flashing green line), etc.

[0142] In another example, the display format of the driving reminder information could be: setting up a warning light in the vehicle, illuminating a red warning light when acceleration is needed, and illuminating a green warning light when deceleration is needed, etc.

[0143] There are no restrictions on the display format of driving reminder information; the format that can be implemented shall prevail.

[0144] In one possible implementation, after determining the vehicle's exit speed according to the above-described implementation method, the exit speed can be expanded within an acceptable error range to obtain multiple exit speeds to be processed. Then, after determining the vehicle's travel time corresponding to each exit speed to be processed, the exit speed with the shortest travel time can be determined as the vehicle's exit speed. Subsequently, the optimal driving path of the vehicle is determined based on the determined exit speed, thereby further improving the accuracy of the optimal driving path.

[0145] See Figure 7 , Figure 7 This is a schematic diagram of a software architecture for implementing a path planning method, provided as an embodiment of this application. This architecture can be embedded in an in-vehicle terminal. Figure 7 As shown, the architecture may include an input module, a data processing module, a corner exit speed prediction module, an optimal driving path calculation module, a driving reminder module, and an output module. The input module acquires road information of the target road, the vehicle's first driving information, and its third driving information. It preprocesses this information (e.g., data cleaning, data format conversion). Then, on one hand, the road information is input to the data processing module for discretization, resulting in a discrete target road. On the other hand, the vehicle's road information and first driving information are input to the corner exit speed prediction module to determine the vehicle's corner exit speed on the target road. Next, the road information, first driving information, the discrete target road, corner exit speed, and third driving information are input to the optimal driving path calculation module for processing, yielding the vehicle's optimal driving path. Finally, the information related to the optimal driving path is input to the driving reminder module to determine the driving reminder time and information. The output module then outputs the driving reminder information to guide the driver.

[0146] Those skilled in the art will understand that, in the above-described method of the specific implementation, the order in which each step is written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0147] Figure 8 This is a schematic diagram of the structure of a path planning device provided in an embodiment of this application, as shown below. Figure 8 As shown, the path planning device 800 includes:

[0148] The acquisition unit 801 is used to acquire road information of the target road where the vehicle is located and the vehicle's first driving information; wherein, the first driving information indicates the vehicle's current driving status.

[0149] The processing unit 802 is used to discretize the target road based on road information to obtain a discrete target road; wherein the discrete target road includes multiple drivable road segments, and each drivable road segment includes multiple drivable locations.

[0150] The first determining unit 803 is used to determine the second driving information of the vehicle at each drivable location based on the first driving information and / or road information; the second driving information indicates the driving status of the vehicle in a preset dimension.

[0151] The second determining unit 804 is used to determine the optimal driving path of the vehicle based on the second driving information.

[0152] Figure 9 This is a schematic diagram of another path planning device provided in an embodiment of this application, as shown below. Figure 9 As shown, the path planning device 900 includes:

[0153] The acquisition unit 901 is used to acquire road information of the target road where the vehicle is located and the vehicle's first driving information; wherein, the first driving information indicates the vehicle's current driving status.

[0154] The processing unit 902 is used to discretize the target road based on road information to obtain a discrete target road; wherein the discrete target road includes multiple drivable road segments, and each drivable road segment includes multiple drivable locations.

[0155] The first determining unit 903 is used to determine the second driving information of the vehicle at each drivable location based on the first driving information and / or road information; the second driving information indicates the driving status of the vehicle in a preset dimension.

[0156] The second determining unit 904 is used to determine the optimal driving path of the vehicle based on the second driving information.

[0157] In one possible implementation, the preset dimension indicates the driving speed dimension; the driving state under the driving speed dimension indicates the vehicle's exit speed from the curve; the first driving information includes vehicle position information; the road information includes the road friction coefficient; at this time, the first determining unit 903 is used to:

[0158] Based on the vehicle location information and the target road where the vehicle is located, determine the road curvature information of the target road;

[0159] Based on road friction coefficient and road curvature information, determine the exit speed of the vehicle at each drivable position within the last drivable road segment.

[0160] The second driving information is determined based on the exit speed from the curve.

[0161] In one possible implementation, the preset dimension further indicates the travel time dimension; the travel status under the travel time dimension indicates the vehicle travel time; at this time, the first determining unit 903 is further configured to:

[0162] Based on the vehicle's exit speed from the curve, determine the vehicle's speed at each drivable location within each drivable road segment.

[0163] Based on the vehicle's speed and the distance the vehicle travels in each drivable road segment, determine the vehicle's travel time at each drivable location in each drivable road segment.

[0164] The second driving information is determined based on the vehicle's travel time.

[0165] In one possible implementation, the preset dimension indicates the driving safety dimension; the driving status under the driving safety dimension indicates the distance of the vehicle from the road centerline; the road information includes road width information and road boundary information; at this time, the first determining unit 903 is used for:

[0166] Based on road width and road boundary information, determine the road centerline corresponding to the target road;

[0167] Determine the distance information between the vehicle and the center line of the road at each drivable position, and determine the second driving information based on the distance information.

[0168] In one possible implementation, the second determining unit 904 is configured to:

[0169] Obtain third-party driving information; wherein, the third-party driving information indicates the boundary information of the vehicle's driving.

[0170] The second driving information is filtered based on the third driving information to obtain the filtered second driving information;

[0171] Based on the filtered second driving information, the optimal driving route for the vehicle is determined.

[0172] In one possible implementation, the second determining unit 904 is configured to:

[0173] Determine the weight information corresponding to each filtered second driving information;

[0174] Based on the weight information, the second driving information after each screening is weighted and summed to determine the driving index data of the vehicle at each driving location.

[0175] Based on driving index data, the target driving position is determined sequentially from each drivable road segment, and the optimal driving route is determined based on the target driving position in each drivable road segment.

[0176] In one possible implementation, the device further includes a reminder unit 905, for:

[0177] Based on the vehicle's current location and optimal driving route, the driving reminder time and driving reminder information are determined so that the driver is reminded according to the driving reminder information at the driving reminder time; wherein, the driving reminder information indicates acceleration or deceleration information.

[0178] Figure 10 This application provides a schematic diagram of the structure of a computer device, as shown in the embodiment of the present application. Figure 10 As shown, the computer device 1000 includes: a memory 1001 and a processor 1002.

[0179] Memory 1001; a memory used to store computer-executed instructions in processor 1002.

[0180] The processor 1002 is configured to perform the method provided in the above embodiments.

[0181] The computer device also includes a receiver 1003 and a transmitter 1004. The receiver 1003 is used to receive instructions and data sent by external devices, and the transmitter 1004 is used to send instructions and data to external devices.

[0182] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, perform the steps of the path planning method in the above-described method embodiments. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0183] This application also provides a vehicle, including: an on-board terminal, which is used to implement the path planning method in the above embodiments.

[0184] This application also provides a computer program product that carries computer execution instructions. The computer execution instructions include instructions that can be used to execute the steps of the path planning method in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0185] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0186] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0187] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0188] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0189] When an integrated unit / module is implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0190] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0191] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0192] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0193] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A path planning method, characterized in that, include: Obtain road information of the target road where the vehicle is located and the vehicle's first driving information; wherein, the first driving information indicates the vehicle's current driving status; The target road is discretized based on the road information to obtain a discrete target road; wherein, the discrete target road includes multiple drivable road segments, and each drivable road segment includes multiple drivable locations; Based on the first driving information and / or the road information, the second driving information of the vehicle at each of the drivable locations is determined; the second driving information indicates the driving status of the vehicle in a preset dimension. Based on the second driving information, the optimal driving path of the vehicle is determined.

2. The method according to claim 1, characterized in that, The preset dimension indicates the driving speed dimension; the driving status under the driving speed dimension indicates the vehicle's exit speed from the curve; the first driving information includes vehicle position information; the road information includes the road friction coefficient; Based on the first driving information and / or the road information, determining the second driving information of the vehicle at each of the drivable locations includes: Based on the vehicle location information and the target road where the vehicle is located, the road curvature information of the target road is determined; Based on the road friction coefficient and the road curvature information, the exit speed of the vehicle at each of the drivable positions included in the last drivable road segment is determined; The second driving information is determined based on the exit speed from the curve.

3. The method according to claim 2, characterized in that, The preset dimension also indicates the travel time dimension; The driving status under the driving time dimension indicates the vehicle's driving time; the method further includes: Based on the vehicle's exit speed from the curve, the vehicle's speed at each drivable position within each drivable road segment is determined. Based on the vehicle's speed and the distance the vehicle travels in each of the drivable road segments, the vehicle's travel time at each of the drivable positions in each of the drivable road segments is determined. The second driving information is determined based on the vehicle's travel time.

4. The method according to claim 1, characterized in that, The preset dimension indicates the driving safety dimension; the driving status under the driving safety dimension indicates the distance of the vehicle from the center line of the road; the road information includes road width information and road boundary information; Based on the first driving information and / or the road information, determining the second driving information of the vehicle at each of the drivable locations includes: Based on the road width information and the road boundary information, the road centerline corresponding to the target road is determined; The distance information between the vehicle and the centerline of the road at each of the drivable positions is determined, and the second driving information is determined based on the distance information.

5. The method according to any one of claims 1-4, characterized in that, Based on the second driving information, the optimal driving route of the vehicle is determined, including: Obtain third driving information; wherein, the third driving information indicates the boundary information of the vehicle's driving; The second driving information is filtered based on the third driving information to obtain the filtered second driving information; Based on the filtered second driving information, the optimal driving route for the vehicle is determined.

6. The method according to claim 5, characterized in that, Determining the optimal driving route for the vehicle based on the filtered second driving information includes: Determine the weight information corresponding to each of the filtered second driving information; Based on the weight information, the filtered second driving information is weighted and summed to determine the driving index data of the vehicle at each driving location. Based on the driving index data, the target driving position is determined sequentially from each of the drivable road segments, and the optimal driving route is determined based on the target driving position in each of the drivable road segments.

7. The method according to claim 1, characterized in that, The method further includes: Based on the vehicle's current driving location and the optimal driving route, a driving reminder time and driving reminder information are determined, so that the driver of the vehicle is reminded according to the driving reminder information at the driving reminder time; wherein, the driving reminder information indicates acceleration information or deceleration information.

8. A path planning device, characterized in that, include: The acquisition unit is used to acquire road information of the target road where the vehicle is located and the vehicle's first driving information; wherein, the first driving information indicates the vehicle's current driving status; The processing unit is configured to discretize the target road based on the road information to obtain a discrete target road; wherein the discrete target road includes multiple drivable road segments, and each drivable road segment includes multiple drivable locations; The first determining unit is configured to determine second driving information of the vehicle at each of the drivable locations based on the first driving information and / or the road information; the second driving information indicates the driving status of the vehicle in a preset dimension. The second determining unit is used to determine the optimal driving path of the vehicle based on the second driving information.

9. A computer device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the path planning method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the path planning method as described in any one of claims 1 to 7.

11. A vehicle, characterized in that, include: Vehicle-mounted terminal; the vehicle-mounted terminal is used to implement the path planning method as described in any one of claims 1 to 7.

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