Intelligent network connection vehicle track generation method and device, equipment, storage medium and product

Abstract

The invention provides an intelligent network connection vehicle track generation method and device, equipment, a storage medium and a product. The method comprises the following steps: acquiring a starting steering radius, an ending steering radius and a vehicle steering angle corresponding to a vehicle track; the vehicle steering angle is divided into a plurality of angle interval points; the plurality of angle interval points correspond to different angle variations of the vehicle; for the multiple angle interval points, corresponding steering radiuses are determined according to the angle changes of the angle interval points, the starting steering radius and the ending steering radius, corresponding position differential increments are calculated based on the steering radiuses, and multiple path points corresponding to the multiple angle interval points are obtained; and obtaining a vehicle track according to the plurality of path points. On the basis, position differential increments are calculated according to the angle sequence and the corresponding radiuses, so that path points are generated, it is guaranteed that the bending degree and path changes can be accurately controlled in a high-speed steering scene, and a smooth steering track is generated.

Description

Technical Field

[0001] This application relates to the field of intelligent driving technology, and in particular to a method, apparatus, device, storage medium and product for generating the trajectory of intelligent connected vehicles. Background Technology

[0002] As a core development direction of modern automotive technology, intelligent connected vehicles require deep integration of vehicle networking and autonomous driving technologies to achieve collaborative interaction between the vehicle and its external environment through communication and intelligent decision-making systems. Among the autonomous driving technologies used in intelligent connected vehicles, trajectory generation is one of the most crucial components. Trajectory generation refers to planning a driving trajectory for the vehicle from its current location to a target location using algorithms and technical means. This trajectory is typically generated after considering motion constraints, environmental obstacles, and other targets, providing a smooth path for the vehicle in scenarios such as lane changes and steering.

[0003] In existing technologies, trajectory generation methods based on geometric curves are widely used. These methods generate smooth paths by adjusting control points, but they are therefore sensitive to the distribution of control points. If the position of the control points is not accurate enough, the curvature of the curve may be discontinuous. As a result, they are not suitable for high-speed turning scenarios, as they are difficult to control the degree of curvature and path changes precisely, and the generated trajectory is not smooth enough during the turning process. Summary of the Invention

[0004] This application provides a method, apparatus, device, storage medium, and product for generating intelligent connected vehicle trajectories, which can solve the technical problem of insufficient smoothness of the generated vehicle trajectories.

[0005] Firstly, this application provides a method for generating the trajectory of an intelligent connected vehicle, the method comprising: Obtain the starting turning radius, ending turning radius, and vehicle turning angle corresponding to the vehicle trajectory; The vehicle's steering angle is divided into multiple angular intervals; these multiple angular intervals correspond to different angular changes in the vehicle. For multiple angular interval points, the corresponding turning radius is determined according to the angular change of the angular interval points, the starting turning radius, and the ending turning radius, and the corresponding position differential increment is calculated based on the turning radius to obtain multiple path points corresponding to the multiple angular interval points. The vehicle trajectory is obtained based on multiple waypoints.

[0006] In some possible implementations, for multiple angular interval points, the corresponding turning radius is determined based on the angular change at each interval point, as well as the starting and ending turning radii. Then, the corresponding position differential increment is calculated based on the turning radius to obtain multiple path points corresponding to each angular interval point, including: Based on the initial turning radius and the final turning radius, determine the turning radius corresponding to multiple angular interval points respectively; According to the sequence of vehicle angle changes, the corresponding position differential increments are determined sequentially based on the turning radii corresponding to multiple angle interval points. Starting from the vehicle's initial position, determine the next path point based on the positional differential increments corresponding to the current path point and the current angular interval point, until all path points corresponding to the angular interval points are obtained.

[0007] In some possible implementations, the turning radius corresponding to multiple angular interval points is determined based on the initial turning radius and the final turning radius, including: Calculate the difference between the final turning radius and the initial turning radius; For each angular interval point, the corresponding weighting coefficient is determined based on the ratio of the angular change at the angular interval point to the vehicle steering angle. Based on the differences and weighting coefficients corresponding to multiple angular interval points, the turning radius corresponding to each of the multiple angular interval points is determined.

[0008] In some possible implementations, the corresponding position differential increments are determined sequentially based on the turning radii corresponding to multiple angular intervals, according to the order of vehicle angle changes. These include: Following the sequence of vehicle angle changes, perform the following steps sequentially at each angle interval: Based on the angle change corresponding to the current angle interval point and the difference in turning radius between the current angle interval point and the previous angle interval point, calculate the corresponding horizontal position differential increment and vertical position differential increment.

[0009] In some possible implementations, after obtaining the vehicle trajectory based on multiple waypoints, the following steps are also included: The vehicle trajectory is matched with preset constraints to obtain the matching result; If the matching result is a mismatch, adjust the starting radius and ending radius and return to the following steps: For multiple angular interval points, determine the corresponding turning radius based on the starting turning radius and ending turning radius, and calculate the corresponding position differential increment based on the turning radius to obtain the path points corresponding to the multiple angular interval points.

[0010] In some possible implementations, the vehicle trajectory is matched against preset constraints to obtain the matching result, including: The minimum trajectory length of the vehicle trajectory is determined based on preset constraints; The matching result is obtained by matching the trajectory length corresponding to the vehicle trajectory with the minimum trajectory length.

[0011] In some possible implementations, when the vehicle driving scenario is a lane-changing scenario, the vehicle trajectory includes a first trajectory and a second trajectory. The vehicle trajectory is obtained based on multiple waypoints, including: The first trajectory is obtained based on multiple path points; The second trajectory is obtained by rotating the trajectory around the end of the first trajectory by a preset rotation angle; The vehicle trajectory is determined based on the first and second trajectories.

[0012] Secondly, this application provides an intelligent connected vehicle trajectory generation device, the device comprising: The acquisition module is used to acquire the starting turning radius, ending turning radius, and vehicle turning angle corresponding to the vehicle trajectory; The segmentation module is used to divide the vehicle's steering angle into multiple angular interval points; these multiple angular interval points correspond to different angular changes in the vehicle. The calculation module is used to determine the corresponding turning radius for multiple angular interval points based on the angular change of the angular interval points, as well as the starting turning radius and the ending turning radius, and to calculate the corresponding position differential increment based on the turning radius, so as to obtain multiple path points corresponding to the multiple angular interval points respectively. The determination module is used to obtain the vehicle trajectory based on multiple waypoints.

[0013] Thirdly, this application provides an intelligent connected vehicle trajectory generation device, the device including: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the intelligent connected vehicle trajectory generation method described above.

[0014] Fourthly, this application provides a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the intelligent connected vehicle trajectory generation method described above.

[0015] Fifthly, this application provides a computer program product in which the instructions are executed by the processor of an electronic device, causing the electronic device to perform the intelligent connected vehicle trajectory generation method described above.

[0016] The intelligent connected vehicle trajectory generation method, apparatus, device, storage medium, and product provided in this application determine the vehicle's initial turning radius, ending turning radius, and turning angle based on the vehicle's starting and ending positions. Then, the turning angle is divided into multiple interval points to ensure a smooth transition of the heading angle. Simultaneously, the turning radius of each interval point is dynamically allocated based on the starting and ending radii, allowing for a continuous and gradual change in curvature, eliminating the curvature jump problem of traditional methods. Based on this, position differential increments are calculated according to the angle sequence and corresponding radii to generate path points, thereby ensuring precise control of curvature and path changes even in high-speed turning scenarios, generating a smooth turning trajectory. Attached Figure Description

[0017] This application can be better understood from the following description of specific embodiments in conjunction with the accompanying drawings, wherein: Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings, wherein the same or similar reference numerals denote the same or similar features.

[0018] Figure 1 This is a flowchart illustrating a method for generating the trajectory of an intelligent connected vehicle according to an embodiment of this application; Figure 2 This is a flowchart illustrating a method for generating the trajectory of an intelligent connected vehicle according to another embodiment of this application; Figure 3 This is a flowchart illustrating a method for generating the trajectory of an intelligent connected vehicle according to another embodiment of this application; Figure 4 This is a schematic diagram of the structure of an intelligent connected vehicle trajectory generation device provided in one embodiment of this application; Figure 5 This is a schematic diagram of the hardware structure of the intelligent connected vehicle trajectory generation device provided in the embodiments of this application. Detailed Implementation

[0019] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0020] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0021] Intelligent connected vehicles represent a crucial development direction for modern automotive technology. Current technological solutions typically rely on geometric curve equations to generate smooth trajectories. A common method is the use of Bézier curves. Bézier curves are mathematical curves used in 2D graphics applications, defined by a set of vectors called control points. Given control points connected sequentially form a control polygon, and the Bézier curve approximates this polygon, thus altering the curve's shape by adjusting the control point coordinates. However, Bézier curves are highly sensitive to the distribution of control points. Too many or too few control points can lead to an uneven or overly smooth curve, meaning its curvature changes discontinuously, making it unsuitable for high-speed cornering. Furthermore, as the curve's arc length increases, control points require manual adjustment, making it difficult to precisely control the degree of curvature and path changes.

[0022] To address the problems of the prior art, embodiments of this application provide a method, apparatus, device, storage medium, and product for generating the trajectory of intelligent connected vehicles. The method for generating the trajectory of intelligent connected vehicles provided in this application embodiment will be described first below.

[0023] Figure 1 A flowchart illustrating an embodiment of the intelligent connected vehicle trajectory generation method provided in this application is shown. Figure 1 As shown, the method may include the following steps: S101 to S104.

[0024] S101: Obtain the starting turning radius, ending turning radius, and vehicle turning angle corresponding to the vehicle trajectory.

[0025] The initial turning radius refers to the pre-set turning radius required for the vehicle at the beginning of the trajectory. The final turning radius refers to the pre-set turning radius required for the vehicle at the end of the trajectory.

[0026] Vehicle steering angle refers to the angular change in the direction of travel of a vehicle within its trajectory.

[0027] In the specific implementation, the vehicle trajectory is generated with a starting point and an ending point. Based on these starting and ending points, the corresponding starting trajectory segment and ending trajectory segment can be obtained, thereby obtaining the starting turning radius, ending turning radius, and vehicle turning angle corresponding to the vehicle trajectory.

[0028] S102: Divide the vehicle steering angle into multiple angular intervals. These multiple angular intervals correspond to different angular changes in the vehicle.

[0029] In practice, the change in vehicle steering angle is divided into multiple smaller angular intervals, each corresponding to a small change in vehicle angle. This process is achieved by setting an angle increment. For example, if each angular interval is set to 5 degrees, the vehicle's steering angle will be divided into multiple angle values, with a difference of 5 degrees between these angles. Alternatively, if the vehicle's steering angle increases from 0 degrees to 90 degrees, it can be divided into 15 intervals, with a steering angle difference of 6 degrees between each point.

[0030] S103: For multiple angular interval points, determine the corresponding turning radius based on the angular change of the angular interval points, the starting turning radius, and the ending turning radius, and calculate the corresponding position differential increment based on the turning radius to obtain multiple path points corresponding to the multiple angular interval points.

[0031] The position differential increment represents the distance between a vehicle and the next waypoint.

[0032] In practical implementation, given each angle change, we can calculate a new turning radius using the initial and final turning radii. Then, based on this turning radius, we can calculate the vehicle's path points at these angle intervals. These path points are the multiple path points corresponding to various angle intervals during the vehicle's journey.

[0033] S104: Obtain the vehicle trajectory based on multiple waypoints.

[0034] In practice, each waypoint represents the vehicle's position at different times or different steering angles. By connecting these waypoints into a smooth curve, the vehicle's trajectory can be depicted. This trajectory is typically smoothed using interpolation or curve fitting methods.

[0035] The intelligent connected vehicle trajectory generation method provided in this application determines the vehicle's initial turning radius, final turning radius, and turning angle based on the vehicle's starting and ending positions. The turning angle is then divided into multiple interval points to ensure a smooth transition in heading angle. Simultaneously, the turning radius of each interval point is dynamically allocated based on the starting and ending radii, ensuring a continuous and gradual change in curvature and eliminating the curvature jump problem of traditional methods. Based on this, position differential increments are calculated according to the angle sequence and corresponding radii to generate path points, thereby ensuring precise control of curvature and path changes even in high-speed turning scenarios, generating a smooth turning trajectory.

[0036] To ensure path accuracy, in some implementations, S103 may include the following steps: S1031 to S1033.

[0037] S1031: Determine the turning radius corresponding to multiple angular interval points based on the starting turning radius and the ending turning radius.

[0038] In practice, interpolation is performed between the initial and final turning radii to obtain the turning radii corresponding to multiple angular intervals. For example, suppose the vehicle starts turning left, and the turning radius gradually increases from 10 meters to 20 meters. At each angular increment (e.g., every 5 degrees), the turning radius for each angular increment can be calculated using linear interpolation or more complex interpolation methods (e.g., spline interpolation).

[0039] S1032: According to the sequence of vehicle angle changes, determine the corresponding position differential increments based on the turning radii corresponding to multiple angle interval points.

[0040] The angle change sequence refers to the order in which the vehicle turns, typically starting from the initial steering angle and gradually changing in increments. The steering radius corresponding to each change can be obtained from the result calculated in S1031.

[0041] In practical implementation, the corresponding position differential increment is calculated based on the turning radius at each angular interval. The position differential increment refers to the displacement increment of the vehicle from one position to another during its journey along a curve. Specifically, the position differential increment can be calculated based on the vehicle's turning radius using the arc length formula.

[0042] S1033: Starting from the vehicle's initial position, determine the next path point based on the position differential increment corresponding to the current path point and the current angle interval point, until the path points corresponding to all angle interval points are obtained.

[0043] In the specific implementation, the complete vehicle trajectory is formed by progressively calculating the path points corresponding to each angular interval. Starting from the initial position, the position is updated by combining the turning radius of each angular increment with the calculated differential increment, until the path points corresponding to all angular intervals are obtained.

[0044] The intelligent connected vehicle trajectory generation method provided in this application starts from the initial turning radius and the final turning radius, and obtains the complete trajectory of the vehicle by gradually calculating the turning radius and position differential increment for each angle increment. By calculating the position of each path point, the accuracy of the path is ensured by using radius interpolation and displacement calculation.

[0045] In order to eliminate abrupt changes in trajectory curvature, in some implementations, S1031 may include the following steps: S10311 to S10313.

[0046] S10311: Calculate the difference between the final turning radius and the initial turning radius.

[0047] In practice, the difference between the ending turning radius and the starting turning radius represents the total adjustment required to change the turning radius throughout the entire path. Assuming the starting turning radius is 8 meters and the ending turning radius is 20 meters, the difference is 20 - 8 = 12 meters. This difference will be used in subsequent steps to calculate the weights and interpolate the gradual changes in the turning radius.

[0048] S10312: For each angular interval point, determine the corresponding weighting coefficient based on the ratio of the angular change at the angular interval point to the vehicle steering angle.

[0049] In the specific implementation, the total steering angle of the vehicle during path planning is first obtained; this angle represents the total change from the starting angle to the ending angle. Then, for each angle interval point on the path, the cumulative angle change corresponding to that point is obtained. The angle change at that point is divided by the total steering angle of the vehicle to obtain a proportional value between 0 and 1, which determines the corresponding weight coefficient. This proportional value reflects the relative position of the vehicle's current path point throughout the entire steering process; the closer the weight is to 0, the closer it is to the starting point, and the closer it is to 1, the closer it is to the ending point.

[0050] S10313: Determine the turning radius corresponding to multiple angle interval points based on the difference and weighting coefficients.

[0051] In the specific implementation, based on the previously calculated difference and weighting coefficient, the corresponding turning radius is calculated for each angular interval point on the path, achieving a smooth change in the turning radius. Taking an 8-meter starting radius, an 20-meter ending radius, and a difference of 12 meters as an example, if the weighting coefficient for a certain angular point is 0.5, then the turning radius at that point is 8 + 12 × 0.5 = 14 meters. Thus, when the weighting coefficient is 0, the turning radius is the starting radius; when the weighting coefficient is 1, the turning radius is the ending radius. When the weighting coefficient is between 0 and 1, the turning radius is linearly interpolated between the starting and ending radii.

[0052] The intelligent connected vehicle trajectory generation method provided in this application converts the numerical difference between the starting and ending turning radii into the turning radius corresponding to each angular interval point, achieving a gradual and smooth transition of the turning radius. This ensures that the turning radius changes uniformly with the angular progress, guaranteeing the continuity and smoothness of turning in vehicle path planning and eliminating abrupt changes in trajectory curvature.

[0053] To ensure a smooth trajectory that conforms to changes in curvature, in some implementations, S1032 may include performing the following steps sequentially at each angular interval point according to the order of the vehicle's angular changes: Based on the angle change corresponding to the current angle interval point and the difference in turning radius between the current angle interval point and the previous angle interval point, calculate the corresponding horizontal position differential increment and vertical position differential increment.

[0054] In the specific implementation, the angle change at the current angle interval point is determined, then the difference in turning radius between the current angle interval point and the previous angle interval point is determined, and then the differential increment of the horizontal position is calculated based on the angle change and the difference in turning radius. Finally, the differential increment of the vertical position is calculated based on the angle change and the difference in turning radius.

[0055] The intelligent connected vehicle trajectory generation method provided in this application enables precise navigation of the vehicle on complex turning paths by refining the changes at each angular interval and fine-tuning the path. By calculating the differential increments of the horizontal and vertical positions, it ensures that the vehicle travels smoothly along the predetermined trajectory, and the trajectory smoothly conforms to the curvature changes.

[0056] In order to verify the trajectory based on preset constraints, in some implementations, reference is made to... Figure 2 After S104, the following steps may also be included: S105 to S106.

[0057] S105: Match the vehicle trajectory with the preset constraints to obtain the matching result.

[0058] In practice, the vehicle's actual driving trajectory needs to be compared with preset constraints. These constraints may include the maximum turning radius of the path, the minimum turning radius of the vehicle, the road width, and the turning angle. These constraints are usually defined through pre-defined rules or map data. During the operation, the current vehicle's trajectory data is acquired, which includes information such as the vehicle's position at each angular interval on the path, its turning radius, etc. Then, this data is compared with the preset constraints one by one. For example, the software might check whether the turning radius at a certain angular point exceeds the maximum turning radius limit, or whether the path meets the road width requirements. If all conditions are met, the matching result is "match"; otherwise, it is "mismatch".

[0059] S106: If the matching result is a mismatch, adjust the starting radius and the ending radius and return to the following steps: For multiple angular interval points, determine the corresponding turning radius based on the starting turning radius and the ending turning radius respectively, and calculate the corresponding position differential increment based on the turning radius to obtain the path points corresponding to the multiple angular interval points.

[0060] In the implementation, when the matching result is "mismatch," the turning radii at the start and end positions of the path are adjusted based on the matching result to make the path more in line with the constraints. For example, if the turning radius at the start position is too large, it can be appropriately reduced so that the vehicle does not exceed the predetermined maximum turning radius while traveling on the path. Similarly, the turning radius at the end position can also be adjusted as needed to ensure that the vehicle can smoothly complete the final turn. Once the start and end radii are adjusted, the turning radius at each angular interval is recalculated.

[0061] The intelligent connected vehicle trajectory generation method provided in this application optimizes the path by progressively comparing and adjusting the vehicle trajectory with preset conditions, and by calculating the turning radius and position increment. After adjustment, the method returns and re-checks the path to ensure that the vehicle's driving trajectory meets all constraints. Ultimately, this ensures that the vehicle travels along the most suitable path, and verifies the trajectory based on preset constraints to avoid trajectories that do not conform to reality.

[0062] In order to ensure that the trajectory meets the constraints, in some implementations, S105 may include the following steps: S1051 to S1052.

[0063] S1051: Determine the minimum trajectory length of the vehicle trajectory based on preset constraints.

[0064] Minimum trajectory length refers to the shortest path length that a vehicle can travel from the starting point to the ending point under preset constraints.

[0065] In practical implementation, the shortest trajectory length that the vehicle can travel is calculated based on preset constraints. For example, on a road with a turning radius of 10 meters, the minimum trajectory length of the vehicle will be affected by this turning radius, and the vehicle needs a radius of at least 10 meters to complete the turn.

[0066] S1052: Match the trajectory length corresponding to the vehicle trajectory with the minimum trajectory length to obtain the matching result.

[0067] In the implementation, the vehicle's trajectory is compared with the minimum trajectory length calculated based on preset conditions. If the actual trajectory length is greater than or equal to the minimum trajectory length, the matching result is "match". If the actual trajectory length is less than the minimum trajectory length, the matching result is "mismatch". For example, suppose the minimum trajectory length calculated based on the aforementioned constraints is 100 meters, while the vehicle's actual trajectory length is only 90 meters. In this case, the system will determine the trajectory as "mismatch" because the actual trajectory length does not meet the minimum trajectory length requirement. Conversely, if the actual trajectory length of the vehicle is 105 meters, the system will determine the trajectory as "match", meeting the minimum trajectory length requirement.

[0068] The intelligent connected vehicle trajectory generation method provided in this application first determines a feasible path by calculating the minimum trajectory length, and then obtains a matching result by comparing the actual trajectory length with the minimum trajectory length. If there is a mismatch, further path optimization or adjustments may be necessary to ensure that the vehicle trajectory meets the minimum safety requirements under preset constraints, thus guaranteeing that the trajectory conforms to the constraints.

[0069] In order to reuse trajectories in symmetrical scenarios, in some implementations, when the vehicle driving scenario is a lane changing scenario, the vehicle trajectory includes a first trajectory and a second trajectory. S104 may include the following steps: S1041 to S1043.

[0070] S1041: Obtain the first trajectory based on multiple path points.

[0071] In the specific implementation, the first trajectory is obtained by connecting multiple consecutive path points.

[0072] S1042: Rotate the second trajectory by a preset trajectory rotation angle around the end of the first trajectory.

[0073] The end of the first trajectory refers to the last path point of the vehicle's current path. By calculating the coordinates of the last path point of the first trajectory, the center point of rotation, i.e., the end point, can be determined.

[0074] The preset trajectory rotation angle refers to the rotation angle required for the vehicle to complete the lane change.

[0075] In the specific implementation, the second trajectory is obtained by taking the end point of the first trajectory as the rotation center and rotating the entire trajectory around that point by a preset angle.

[0076] S1043: Determine the vehicle trajectory based on the first trajectory and the second trajectory.

[0077] In the actual implementation, the first and second trajectories are merged into a single continuous trajectory. The trajectory can be smoothed to ensure a natural and smooth transition between trajectories.

[0078] The intelligent connected vehicle trajectory generation method provided in this application calculates the trajectory through path points in lane-changing scenarios, adjusts the trajectory direction by rotation angle, and finally merges the two trajectories into a single path that meets driving requirements. By utilizing precise calculation, trajectory smoothing, and dynamic considerations, it ensures smooth vehicle operation during lane changes, reuses trajectories in symmetrical scenarios, and avoids redundant planning overhead.

[0079] In some implementation methods, the above implementation steps are described in further detail, which can be found in reference to... Figure 3 The input parameters in the scheme are the starting radius, ending radius, starting angle, and arc length. The scheme includes the following steps: steps S1 to S10.

[0080] Step S1: Convert the angle to radians. Since the trajectory curve needs to be generated in the Cartesian coordinate system, it needs to be converted to radians.

[0081] Step S2: Obtain N points within the range of 0 to radians through uniform distribution, denoted by t. t can be understood as the time parameter for calculating the angle change.

[0082] Step S3: Calculate the radius for each time parameter t based on the given starting radius, ending radius, and the normalized ratio of radians, representing the uniform change of the radius.

[0083] Step S4: Obtain the current angle through the initial angle and angle changes, obtain the radius of each differential through the radius changes, and obtain the X-axis differential increment and Y-axis differential increment of this differential through trigonometric functions.

[0084] Step S5: Obtain the current point, which is the coordinate point to be drawn, by adding the origin coordinates to the X-axis increment and the Y-axis increment.

[0085] Step S6: Calculate the arc length c by accumulating the Euclidean distance between the current point and the previous point, which is the distance the arc segment travels.

[0086] Step S7: If the arc length c is less than the arc length parameter, continue to calculate the differential increment of the X-axis and the differential increment of the Y-axis. If the arc length is greater than or equal to the arc length parameter, end the loop.

[0087] Step S8: Rotate the generated curve portion around the end point of the generated curve by a specified number of angles using geometric reflection. This step is for turning or lane-changing scenarios.

[0088] Step S9: Generate a trajectory curve image in the Cartesian coordinate system based on the generated coordinate points, and save it to a file for viewing the trajectory shape.

[0089] Step S10: Convert the generated Cartesian trajectory curve into latitude and longitude points for use in real-world vehicle driving tests.

[0090] This method achieves a smoother, more natural transition between curve segments through differential increments. This transition effectively reduces sudden changes in trajectory curvature, avoiding sharp angles or unnatural transitions that occur with Bézier curves in complex trajectory designs, thus improving trajectory controllability. Furthermore, this method can adapt to variations in radius and angle, making it suitable for dynamic trajectory planning requests in different scenarios. This flexibility enables in-vehicle navigation systems to handle real-time trajectory generation under various road conditions. The application of geometric reflection reduces the coordinate point calculation logic in scenarios with repetition differences, making it suitable for trajectory generation in symmetrical scenarios.

[0091] Based on the intelligent connected vehicle trajectory generation method provided in the above embodiments, this application also provides specific implementation methods of the vehicle trajectory generation device. Please refer to the following embodiments.

[0092] First see Figure 4 The vehicle trajectory generation device 400 provided in this application embodiment includes the following modules: The acquisition module 401 is used to acquire the starting turning radius, ending turning radius and vehicle turning angle corresponding to the vehicle trajectory.

[0093] The segmentation module 402 is used to divide the vehicle steering angle into multiple angular interval points. These multiple angular interval points correspond to different angular changes in the vehicle.

[0094] The calculation module 403 is used to determine the corresponding turning radius for multiple angular interval points based on the angular change of the angular interval points, the starting turning radius, and the ending turning radius, and to calculate the corresponding position differential increment based on the turning radius, so as to obtain multiple path points corresponding to the multiple angular interval points.

[0095] The determination module 404 is used to obtain the vehicle trajectory based on multiple waypoints.

[0096] As one implementation of this application, the computing module 403 includes: The determining unit is used to determine the turning radius corresponding to multiple angular interval points based on the starting turning radius and the ending turning radius.

[0097] The unit is also used to determine the corresponding position differential increment according to the turning radius corresponding to multiple angular interval points in sequence according to the vehicle's angular change sequence.

[0098] The determining unit is also used to determine the next path point starting from the vehicle's starting position, based on the position differential increments corresponding to the current path point and the current angular interval point, until the path points corresponding to all angular interval points are obtained.

[0099] As one implementation of this application, the defined unit includes: The calculation sub-unit is used to calculate the difference between the final turning radius and the initial turning radius.

[0100] Define a sub-unit to determine the corresponding weighting coefficient for each angular interval point based on the ratio of the angular change at the angular interval point to the vehicle steering angle.

[0101] The sub-unit is also used to determine the turning radius corresponding to multiple angular interval points based on the difference and weighting coefficients corresponding to multiple angular interval points.

[0102] As one implementation of this application, the defined unit includes: The calculation sub-unit is used to calculate the corresponding horizontal position differential increment and vertical position differential increment based on the angle change corresponding to the current angle interval point and the difference in turning radius between the current angle interval point and the previous angle interval point.

[0103] As one implementation of this application, the vehicle trajectory generation device 400 includes: The matching module is used to match vehicle trajectories with preset constraints to obtain matching results.

[0104] The adjustment module is used to adjust the starting radius and ending radius and return to the previous step when the matching result is a mismatch: For multiple angular interval points, the corresponding turning radius is determined according to the starting turning radius and the ending turning radius, and the corresponding position differential increment is calculated based on the turning radius to obtain the path points corresponding to the multiple angular interval points.

[0105] As one implementation of this application, the matching module includes: The determining unit is used to determine the minimum trajectory length of the vehicle trajectory based on preset constraints.

[0106] The matching unit is used to match the trajectory length corresponding to the vehicle trajectory with the minimum trajectory length to obtain the matching result.

[0107] As one implementation of this application, module 404 is defined, including: The determination unit is used to obtain the first trajectory based on multiple path points.

[0108] The determining unit is also used to rotate a preset trajectory rotation angle around the end of the first trajectory to obtain the second trajectory.

[0109] The determining unit is also used to determine the vehicle trajectory based on the first trajectory and the second trajectory.

[0110] Each module in the vehicle trajectory generation device provided in this application embodiment can implement each step in the above-mentioned intelligent connected vehicle trajectory generation method and achieve the corresponding effect. For the sake of brevity, it will not be described in detail here.

[0111] Figure 5 A schematic diagram of the vehicle trajectory generation hardware provided in an embodiment of this application is shown.

[0112] The vehicle trajectory generation device may include a processor 501 and a memory 502 storing computer program instructions.

[0113] Specifically, the processor 501 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0114] Memory 502 may include mass storage for data or instructions. For example, and not limitingly, memory 502 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 502 may include removable or non-removable (or fixed) media. Where appropriate, memory 502 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 502 is non-volatile solid-state memory.

[0115] The memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the intelligent connected vehicle trajectory generation method according to any embodiment of this disclosure.

[0116] The processor 501 reads and executes computer program instructions stored in the memory 502 to implement any of the intelligent connected vehicle trajectory generation methods in the above embodiments.

[0117] In one example, the vehicle trajectory generation device may further include a communication interface 503 and a bus 510. For example, Figure 5 As shown, the processor 501, memory 502, and communication interface 503 are connected through bus 510 and complete communication with each other.

[0118] The communication interface 503 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0119] Bus 510 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 510 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0120] Furthermore, in conjunction with the vehicle trajectory generation methods described in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the vehicle trajectory generation methods described in the above embodiments.

[0121] This application also provides a computer program product, including a computer program that, when executed, implements any of the vehicle trajectory generation methods described in the above embodiments.

[0122] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0123] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0124] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0125] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0126] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for generating the trajectory of an intelligent connected vehicle, characterized in that, The method includes: Obtain the starting turning radius, ending turning radius, and vehicle turning angle corresponding to the vehicle trajectory; The vehicle steering angle is divided into multiple angle interval points; the multiple angle interval points correspond to different angle changes of the vehicle. For multiple angle interval points, the corresponding turning radius is determined according to the angle change of the angle interval points, the starting turning radius, and the ending turning radius, and the corresponding position differential increment is calculated based on the turning radius to obtain multiple path points corresponding to the multiple angle interval points respectively; The vehicle trajectory is obtained based on the multiple path points mentioned.

2. The intelligent connected vehicle trajectory generation method according to claim 1, characterized in that, For multiple angle interval points, the corresponding turning radius is determined based on the angle change of each angle interval point, the starting turning radius, and the ending turning radius. The corresponding position differential increment is then calculated based on the turning radius to obtain multiple path points corresponding to each angle interval point, including: Based on the starting turning radius and the ending turning radius, the turning radii corresponding to the multiple angle interval points are determined respectively; According to the order of the vehicle's angle changes, the corresponding position differential increments are determined sequentially based on the turning radii corresponding to multiple angle interval points. Starting from the vehicle's initial position, determine the next path point based on the positional differential increments corresponding to the current path point and the current angular interval point, until all path points corresponding to the angular interval points are obtained.

3. The intelligent connected vehicle trajectory generation method according to claim 2, characterized in that, The step of determining the turning radius corresponding to multiple angular interval points based on the initial turning radius and the final turning radius includes: Calculate the difference between the final turning radius and the initial turning radius; For each angular interval point, a corresponding weighting coefficient is determined based on the ratio of the angular change corresponding to the angular interval point to the vehicle steering angle. The turning radius corresponding to each of the multiple angle interval points is determined based on the difference and the weighting coefficient.

4. The intelligent connected vehicle trajectory generation method according to claim 2, characterized in that, The step of determining the corresponding position differential increment according to the turning radius corresponding to multiple angular interval points in the order of the vehicle's angle change includes: According to the order of the vehicle's angle changes, the following steps are performed sequentially at each angle interval: Based on the angle change corresponding to the current angle interval point and the difference in turning radius between the current angle interval point and the previous angle interval point, calculate the corresponding horizontal position differential increment and vertical position differential increment.

5. The intelligent connected vehicle trajectory generation method according to claim 1, characterized in that, After obtaining the vehicle trajectory based on the multiple path points, the process further includes: The vehicle trajectory is matched with preset constraints to obtain the matching result; If the matching result is a mismatch, adjust the starting radius and the ending radius and return to the following steps: For multiple angle interval points, determine the corresponding turning radius according to the starting turning radius and the ending turning radius respectively, and calculate the corresponding position differential increment based on the turning radius to obtain the path points corresponding to the multiple angle interval points.

6. The intelligent connected vehicle trajectory generation method according to claim 5, characterized in that, The step of matching the vehicle trajectory with preset constraints to obtain a matching result includes: The minimum trajectory length of the vehicle trajectory is determined based on preset constraints; The trajectory length corresponding to the vehicle trajectory is matched with the minimum trajectory length to obtain a matching result.

7. The intelligent connected vehicle trajectory generation method according to claim 1, characterized in that, In the case of a lane-changing driving scenario, the vehicle trajectory includes a first trajectory and a second trajectory. Obtaining the vehicle trajectory based on multiple path points includes: Based on the multiple path points, a first trajectory is obtained; A second trajectory is obtained by rotating the trajectory around the end of the first trajectory by a preset trajectory rotation angle; The vehicle trajectory is determined based on the first trajectory and the second trajectory.

8. A device for generating the trajectory of an intelligent connected vehicle, characterized in that, The device includes: The acquisition module is used to acquire the starting turning radius, ending turning radius, and vehicle turning angle corresponding to the vehicle trajectory; The segmentation module is used to divide the vehicle steering angle into multiple angle interval points; the multiple angle interval points correspond to different angle changes of the vehicle. The calculation module is used to determine the corresponding turning radius for multiple angle interval points based on the angle change of the angle interval points, the starting turning radius, and the ending turning radius, and to calculate the corresponding position differential increment based on the turning radius to obtain multiple path points corresponding to the multiple angle interval points respectively. The determination module is used to obtain the vehicle trajectory based on multiple path points.

9. A device for generating the trajectory of an intelligent connected vehicle, characterized in that, The device includes: a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the intelligent connected vehicle trajectory generation method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the intelligent connected vehicle trajectory generation method as described in any one of claims 1-7.

11. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the intelligent connected vehicle trajectory generation method as described in any one of claims 1-7.

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