Vehicle trajectory tracking control method, device, equipment and medium

Abstract

The invention provides a vehicle trajectory tracking control method and device, equipment and a medium. In the method, projection point parameters of a vehicle model at a previous simulation moment are acquired, and an iteration initial value corresponding to the current simulation moment is determined based on the projection point parameters at the previous simulation moment and a motion state of the vehicle model from the previous simulation moment to the current simulation moment; and inputting the iteration initial value and the current position of the vehicle model into a numerical iteration algorithm, outputting a projection point parameter corresponding to the current simulation moment, and generating a vehicle trajectory tracking control signal based on the projection point parameter corresponding to the current simulation moment. The scheme is used for solving the problems of insufficient vertical projection point calculation accuracy, relatively poor reliability and relatively low calculation efficiency in a vehicle trajectory tracking control process in related technologies.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, in particular to a vehicle trajectory tracking control method and device, equipment and a medium. BACKGROUND

[0002] In vehicle multi-body dynamics simulation, especially when testing and verifying automatic driving algorithms and chassis electronic control systems, high-precision vehicle trajectory tracking control is a core evaluation link. The realization of vehicle trajectory tracking control is mainly through real-time calculation of the vertical projection point of the positioning point of the vehicle model at the current time to the preset reference path curve. The calculation accuracy and efficiency of the projection point directly determine the reliability of the dynamics simulation results and the effectiveness of the controller performance verification.

[0003] The main method of related technologies for realizing vehicle trajectory tracking control through real-time calculation of the vertical projection point is the numerical iterative projection method. However, due to the complex and variable simulation conditions and reference path curves, the iterative projection algorithm is prone to iterative divergence, resulting in calculation failure. As a result, not only will the simulation be interrupted, but it is also possible to input an incorrect deviation signal to the tracking controller, causing severe oscillation or even instability of the vehicle in the simulation, which seriously affects the simulation efficiency and confidence. SUMMARY

[0004] The vehicle trajectory tracking control method, device, equipment and medium provided by the embodiments of the present application solve the problems of insufficient accuracy, poor reliability and low calculation efficiency of the vertical projection point calculation in the vehicle trajectory tracking control process in related technologies.

[0005] In a first aspect, the embodiments of the present application provide a vehicle trajectory tracking control method, comprising:

[0006] Obtaining a projection point parameter of a vehicle model at a previous simulation time, wherein the projection point parameter is used to represent the relative position of the projection point of the positioning point of the vehicle model to the preset reference path curve in the preset reference path curve, and the vehicle model is a multi-body dynamics simulation model;

[0007] Based on the projection point parameter at the previous simulation time and the motion state of the vehicle model from the previous simulation time to the current simulation time, determining an iterative initial value corresponding to the current simulation time;

[0008] Inputting the iterative initial value and the current position of the vehicle model into a numerical iterative algorithm to output the projection point parameter corresponding to the current simulation time;

[0009] Based on the projection point parameter corresponding to the current simulation time, generating a control signal for vehicle trajectory tracking.

[0010] In a possible implementation, the acquiring the projection point parameter of the vehicle model at the previous simulation moment comprises: if the current simulation moment is an initial moment, determining a preset initial value as the projection point parameter at the previous simulation moment, or determining the projection point parameter at the previous simulation moment based on a preliminary search on the preset reference path curve; if the current simulation moment is a non-initial moment, reading the projection point parameter obtained at the previous simulation moment from storage.

[0011] In a possible implementation, the determining the iteration initial value corresponding to the current simulation moment based on the projection point parameter at the previous simulation moment and the motion state of the vehicle model from the previous simulation moment to the current simulation moment comprises: determining an estimated change amount of the projection point parameter from the previous simulation moment to the current simulation moment based on the motion state of the vehicle model from the previous simulation moment to the current simulation moment and the simulation step; and adding the projection point parameter at the previous simulation moment and the estimated change amount to obtain the iteration initial value.

[0012] In a possible implementation, the motion state of the vehicle model comprises a vehicle model speed at the current simulation moment; and the determining the estimated change amount of the projection point parameter from the previous simulation moment to the current simulation moment based on the motion state of the vehicle model from the previous simulation moment to the current simulation moment and the simulation step comprises: determining the estimated change amount of the projection point parameter from the previous simulation moment to the current simulation moment based on a heading angle of the vehicle model, a track direction angle of the preset reference path curve, the vehicle model speed at the current simulation moment and the simulation step, and the calculation method of the estimated change amount of the projection point parameter is represented as:

[0013] ,

[0014] wherein, Δs i is the estimated change amount of the projection point parameter at the current simulation moment t i , v i is the vehicle model speed at the current simulation moment t i , and Δt is the simulation step, i-1 is the vehicle model heading angle at the previous simulation moment t i-1 , and θ i-1 is the track direction angle at the projection point at the previous simulation moment t i-1 .

[0015] In a possible implementation, the projection point parameter is an arc length coordinate of the projection point on the preset reference path curve.

[0016] In a possible implementation, the numerical iterative algorithm comprises a Newton iterative algorithm, the iterative initial value and the current position of the vehicle model are input into the numerical iterative algorithm, and a projection point parameter corresponding to a current simulation moment is output, comprising: inputting the iterative initial value and the current position of the vehicle model into a Newton iterative method for solving an equation to obtain the projection point parameter s of the current simulation moment i The Newton iterative method for solving the equation is expressed as:

[0017] ,

[0018] wherein (x c , y c ) is a current position coordinate of the vehicle model, and (x(s), y(s)) is a preset reference path curve equation expressed in an arc length parameter s.

[0019] In a possible implementation, after the iterative initial value and the current position of the vehicle model are input into the numerical iterative algorithm, and a projection point parameter corresponding to a current simulation moment is output, the method further comprises: verifying whether the projection point parameter corresponding to the current simulation moment meets preset convergence conditions and rationality conditions; if the verification result is that the projection point parameter meets the convergence conditions and the rationality conditions, storing the projection point parameter corresponding to the current simulation moment; if the verification result is that the projection point parameter does not meet the convergence conditions and the rationality conditions, reducing a simulation step and re-determining the projection point parameter of the current simulation moment, or inputting the projection point parameters in a plurality of historical records into an interpolation method to output the projection point parameter of the current simulation moment.

[0020] In a second aspect, an embodiment of the present application provides a vehicle trajectory tracking control device, comprising:

[0021] The acquisition module is configured to acquire a projection point parameter of a vehicle model at a previous simulation moment, wherein the projection point parameter is used to represent a relative position of a projection point of a positioning point of the vehicle model to a preset reference path curve in the preset reference path curve, and the vehicle model is a multi-body dynamics simulation model.

[0022] The determination module is configured to determine an iterative initial value corresponding to a current simulation moment based on the projection point parameter at the previous simulation moment and a motion state of the vehicle model from the previous simulation moment to the current simulation moment.

[0023] The calculation module is configured to input the iterative initial value and a current position of the vehicle model into a numerical iterative algorithm, and output a projection point parameter corresponding to the current simulation moment.

[0024] The processing module is configured to generate a control signal for vehicle trajectory tracking based on the projection point parameter corresponding to the current simulation moment.

[0025] In a third aspect, an embodiment of the present application provides an electronic device, comprising:

[0026] a processor, a memory, a communication interface;

[0027] The memory is configured to store executable instructions of the processor.

[0028] The processor is configured to execute the vehicle trajectory tracking control method of any one of the first aspect via execution of the executable instructions.

[0029] In a fourth aspect, an embodiment of the present application provides a readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the vehicle trajectory tracking control method of any one of the first aspect.

[0030] In a fifth aspect, an embodiment of the present application provides a computer program product comprising a computer program, the computer program being executed by a processor to implement the vehicle trajectory tracking control method of any one of the first aspect.

[0031] The vehicle trajectory tracking control method, device, equipment and medium provided by the embodiments of the present application obtain the projection point parameter of the multi-body dynamics simulation vehicle model at the previous simulation moment, intelligently determine the initial value of the numerical iteration algorithm based on the parameter and the vehicle motion state at the current moment, and then calculate the high-precision projection point parameter at the current moment, and finally generate the trajectory tracking control signal. Thus, the time sequence continuity and physical constraints of vehicle motion are utilized, the historical state and real-time kinematic model are combined, and an accurate iteration starting point is provided for nonlinear iteration. The problem of low calculation efficiency caused by improper initial value selection in the traditional numerical iteration method is effectively solved, and the calculation resource consumption is greatly reduced due to the significant improvement of the convergence speed, thereby realizing the synchronous improvement of the vehicle trajectory tracking control simulation in accuracy, reliability and efficiency as a whole. BRIEF DESCRIPTION OF DRAWINGS

[0032] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0033] Figure 1 An application scenario diagram of the vehicle trajectory tracking control method provided by the present application;

[0034] Figure 2 A flowchart of the vehicle trajectory tracking control method embodiment provided by an embodiment of the present application;

[0035] Figure 3 A flowchart of the vehicle trajectory tracking control method embodiment provided by another embodiment of the present application;

[0036] Figure 4 A structural diagram of the vehicle trajectory tracking control device embodiment provided by another embodiment of the present application;

[0037] Figure 5 A structural schematic diagram of an electronic device is provided.

[0038] The specific embodiments of the present application have been shown by the above-described drawings, and will be described in more detail hereinafter. These drawings and the written description are not intended to restrict the scope of the present application concept in any way, but to illustrate the present application concept to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0039] The exemplary embodiments will be described in detail herein with reference to the accompanying drawings. In the following description, unless otherwise indicated, like numbers in the different drawings represent similar or identical elements. The following exemplary embodiments described are not meant to represent all implementations consistent with the present application. Rather, they are simply examples of apparatus and methods consistent with some aspects of the present application as detailed in the appended claims.

[0040] The terms "first", "second", "third", "fourth" and the like in the description and in the claims of the present application, and the above-described drawings, if any, are used to distinguish between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the use of these terms here is not meant to limit the scope of the present application to the particular embodiments described but rather is meant to serve the purpose of distinguishing between similar objects. It is further understood that the use of the terms "including", "containing", "comprising", "having" and variations thereof herein, is meant to encompass the items listed thereafter and equivalents thereof as well as additional items not specifically listed. Accordingly, these terms are meant to be interpreted in the context of this specification as a whole.

[0041] In multi-body dynamics simulation, vehicle trajectory tracking control is the core link to verify the performance of automatic driving algorithm and chassis electronic control system. It simulates the dynamic response of the vehicle under complex working conditions, provides key data support and safety verification for vehicle development, and significantly reduces the research and development cost and risk. Therefore, the accuracy of vehicle trajectory tracking control is crucial for subsequent vehicle development.

[0042] The premise of achieving high-precision control is to calculate the projection point parameter of the vehicle model positioning point to the preset reference path in real time and accurately. This parameter is the basis for solving the lateral and heading deviation. However, the reference path often contains complex geometric features such as intersection and sudden change of curvature, and the vehicle motion state changes rapidly in simulation, which makes the real-time determination of the projection point parameter a typical nonlinear mathematical solving problem. It puts forward extremely strict requirements on the convergence, correctness and efficiency of the calculation.

[0043] In the related art, in the vehicle trajectory control process, the projection point parameters are mainly solved in real time by using a conventional numerical iteration method. However, the iteration process is highly sensitive to the initial value, and the traditional method or random assignment or fixed initial value lacks a reasonable initial value estimation mechanism. This leads to the iteration easily failing due to the initial value deviating too far from the true solution, or converging to an incorrect local solution, especially when the vehicle approaches the path intersection or is in a sharp turning condition in the simulation process. As a result, the simulation is easily interrupted or the controller receives an incorrect deviation signal. However, as described above, the solution of the projection point parameters is based on the idea of solving in real time at each time, which leads to the above problems existing all the time.

[0044] The vehicle trajectory tracking control method provided by the present application introduces and obtains the projection point parameters at the previous simulation time, uses the historical solution as the time anchor point for the current calculation, and combines the current vehicle motion state to determine the iteration initial value close to the true solution. Thus, the iteration process is changed from a blind search at each step to a gradual tracking with a clear direction based on kinematic prediction, ensuring that the numerical iteration algorithm can efficiently and stably converge to the global correct solution, thereby overcoming the problems of convergence failure and insufficient efficiency caused by improper determination of the iteration initial value.

[0045] Figure 1 The application scenario of the vehicle trajectory tracking control method provided by the present application is shown in FIG. 1. Figure 1 In the vehicle trajectory tracking control process, the server 100 obtains the projection point parameters 110 of the vehicle model at the previous simulation time, and generates a control command 120 for controlling the driving trajectory of the vehicle model, so that the vehicle can stably drive along the preset path curve.

[0046] It should be noted that Figure 1 The server, projection point parameters, and control command in the scenario shown are only used as an example for illustration, but the present disclosure is not limited thereto, that is, the number of servers, projection point parameters, and control commands can be any.

[0047] The technical solutions of the present application and how the technical solutions of the present application solve the above technical problems will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described again in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0048] Figure 2 The flowchart of the vehicle trajectory tracking control method provided by the present application is shown in FIG. 2. Figure 1 As shown in FIG. 2, the method comprises the following steps. Figure 2

[0049] ​S201, obtain a projection point parameter of the vehicle model at a previous simulation moment.

[0050] The projection point parameter is used to represent the relative position of the projection point of the positioning point of the vehicle model to the preset reference path curve, and the vehicle model is a multi-body dynamics simulation model.

[0051] Specifically, the embodiment is used to illustrate the main steps of the vehicle trajectory tracking control method.

[0052] The execution subject in the embodiment of the disclosure is a computer, a processor, a server, or the like used for multi-body dynamics simulation analysis of a vehicle, and is collectively referred to as a server for convenience of subsequent description.

[0053] The projection point parameter is used to determine the position of the projection point on the preset reference path curve. The parameter can be an arc length coordinate s of the projection point on the reference path curve, or a normalized parameter, a curvature parameter, or a control parameter of a segmented Bezier curve of the position of the projection point on the curve, as long as it can establish a one-to-one mapping relationship with the path point.

[0054] For example, in an embodiment, the path is composed of a series of ordered waypoints, and at this time, the projection point parameter can be the waypoint index of the previous projection point and the proportional factor on the line segment from the waypoint to the next waypoint.

[0055] In a specific implementation, a continuously updated data storage area is maintained in the server. At a non-initial moment, the server can directly read the result calculated and stored at the previous simulation moment (or simulation period) from the storage area.

[0056] The previous simulation moment herein is determined based on the simulation timing, thereby ensuring the timing continuity of the iteration initial value determination.

[0057] For the initial moment, since there is no historical data, the server needs to call an initialization module.

[0058] The preset initial value determination method that can be used by the module is, for example, the parameters can be initialized to zero, starting from the starting point of the path; or a global rough search is performed, the shortest distances of the initial positioning point of the vehicle to each segment of the path are calculated, and the segment and position with the smallest distance are taken as the initial parameters. The initial parameters (or the initialized parameters) are defined as the projection point parameters at the previous simulation moment (although the previous simulation moment does not exist at the initial moment, in order to facilitate subsequent calculation, the initial parameters are also defined as the projection point parameters at the previous simulation moment to avoid increasing the concept and complicating the calculation).

[0059] Therefore, the iteration initial value determination of the server at the simulation start is ensured to be roughly accurate, thereby laying a reliable data foundation for subsequent steps.

[0060] S202, determine the initial value of iteration corresponding to the current simulation time based on the projection point parameter at the previous simulation time and the motion state of the vehicle model from the previous simulation time to the current simulation time.

[0061] Specifically, the server can utilize the continuity of vehicle motion and physical constraints to convert historical information into intelligent prediction of future state.

[0062] The motion state of the vehicle model can be the driving speed, lateral acceleration, yaw rate, current steering wheel angle, and future heading angle change predicted by the vehicle speed of the vehicle model.

[0063] In an embodiment of the present disclosure, the server can obtain the motion state information at the current time from the vehicle multi-body dynamics model. Then, according to these information, the most possible change amount of the projection point parameter from the previous time to the current time is estimated.

[0064] For example, the server can estimate the instantaneous turning radius R = L / tan(δ) based on the front wheel angle δ, wheelbase L and vehicle speed v of the vehicle, and then calculate the arc length change of the vehicle along the circular arc trajectory combined with the simulation step Δt, and take this arc length change as the parameter estimation change.

[0065] At this time, the server can add the projection point parameter at the previous simulation time obtained in the previous step to the parameter estimation change calculated here, that is, the initial value of iteration of the current time value is obtained.

[0066] Thus, the pure mathematical iteration problem is converted into a tracking problem guided by physical laws, greatly improving the directionality and efficiency of calculation.

[0067] S203, input the initial value of iteration and the current position of the vehicle model into the numerical iteration algorithm, and output the projection point parameter corresponding to the current simulation time.

[0068] Specifically, the numerical iteration algorithm is an algorithm for solving the root of the equation by iterative approximation. For example, the numerical iteration algorithm can be Newton iteration method, according to the characteristics and accuracy requirements of the path curve, it can also be secant method, Brent method, etc., which is not limited here.

[0069] In specific implementation, the server will obtain the current position coordinates (X, Y) of the vehicle model from the simulation environment. Then the initial value of iteration obtained in the previous step is input into the iteration algorithm model together with the current position coordinates to solve the projection point parameter.

[0070] In an embodiment of the present disclosure, the model (which can be processed by a separate module) will start a loop calculation process: in each iteration, the algorithm will calculate the dot product of the vector from the current position of the vehicle to the corresponding path point and the tangent vector of the path at the point according to the current parameter candidate value, and determine whether it is close to zero (satisfy the vertical condition, which means that the point corresponding to the parameter candidate value is the projection point).

[0071] If not, a new and better parameter candidate value is generated according to the specific rules of the algorithm (such as Newton method using derivative information), and the next iteration is entered until the preset convergence accuracy threshold is met.

[0072] For example, for a reference path curve fitted by a high-order polynomial, the server needs to dynamically calculate the first or even second derivative of the polynomial during the iteration process, and finally output a high-precision current time projection point parameter.

[0073] S204, generate a control signal for vehicle trajectory tracking based on the projection point parameter corresponding to the current simulation time.

[0074] Specifically, after obtaining the projection point parameter, the server can query the corresponding path point coordinates (X des , Y des ), the path curvature and the tangent direction (such as the heading angle) of the point from the database corresponding to the reference path curve according to the projection point parameter, and generate a control signal for vehicle trajectory tracking based on the above information.

[0075] In an embodiment of the present disclosure, the specific control signal determination method can be: the server obtains the actual heading angle of the vehicle model, and calculates the lateral position error and the heading error, wherein the lateral position error is the lateral distance from the current position of the vehicle to the target path point, and the heading error is the difference between the actual heading and the expected path heading.

[0076] Then, the server inputs these errors into a control algorithm (such as PID algorithm, preview control algorithm or model predictive control algorithm, etc.). Finally, according to the output of the control algorithm, the specific control instruction is generated.

[0077] For example, the server can generate a target front wheel steering angle instruction, so that the steering system model of the vehicle model performs real-time and closed-loop control on the vehicle driving trajectory based on the instruction, to ensure accurate tracking of the preset path.

[0078] The vehicle trajectory tracking control method provided in the embodiments of the present application obtains the projection point parameter of a multi-body dynamics simulation vehicle model at a previous simulation moment, intelligently determines the initial value of a numerical iteration algorithm based on the parameter and the vehicle motion state at the current moment, and then calculates the high-precision projection point parameter at the current moment to finally generate a trajectory tracking control signal. Thus, the time sequence continuity and physical constraints of vehicle motion are utilized, and the historical state and real-time kinematic model are combined, thereby providing an accurate starting point for nonlinear iteration. The problem of low calculation efficiency caused by improper initial value selection in the traditional numerical iteration method is effectively solved, and the calculation resource consumption is greatly reduced due to the significant improvement in convergence speed, thereby realizing the simultaneous improvement in accuracy, reliability and efficiency of vehicle trajectory tracking control simulation as a whole.

[0079] Figure 3 The flowchart of the vehicle trajectory tracking control provided in the present application Figure 2 As shown in the figure, the embodiments of the present application are based on the vehicle trajectory tracking control method, and the specific process in the method is described in detail. Figure 3 Figure 2 The method comprises the following steps.

[0080] S301, if the current simulation moment is the initial moment, the preset initial value is determined as the projection point parameter at the previous simulation moment.

[0081] Specifically, at the initial moment of simulation, since there is no historical data for reference, the server must adopt a reliable initialization strategy.

[0082] This step provides a most direct and simple initialization method, in which the server directly sets the projection point parameter as a preset fixed value.

[0083] The specific selection of the preset initial value is closely related to the definition method of the reference path curve.

[0084] For example, if the arc length parameter s of the reference path is calculated from the starting point of the road, the server usually presets s0 (the projection point parameter at the initial moment) as 0, which means that the server assumes that the vehicle starts from the starting point of the path to find the projection point.

[0085] The advantage of this method is that it is simple to implement and has minimal calculation overhead, and it is suitable for scenarios where the starting position of the vehicle simulation is basically consistent with the starting point of the path, thereby providing an explicit starting search point for the subsequent iteration calculation.

[0086] Further, the projection point parameter is the arc length coordinate of the projection point on the preset reference path curve.

[0087] ​Specifically, one recommended implementation of the projection point parameter is to use the arc length coordinate s as the projection point parameter.

[0088] At this time, the parameter has a clear physical meaning: it represents the actual path length traveled along the curve from the starting point of the reference path to the projection point.

[0089] The advantage of using the arc length coordinate s is that its first derivative (i.e., the rate of change) is directly related to the vehicle speed in concept, thereby providing an intuitive physical basis for subsequent speed-based parameter change estimation.

[0090] In specific implementations, the reference path curve is usually stored in the server as a sequence of discrete path points sorted by arc length, or a parametric equation (such as a cubic spline curve) with arc length s as the parameter.

[0091] When the server needs to use the path information corresponding to a certain arc length coordinate s, it calculates the exact coordinates (x(s), y(s)), tangent direction (i.e., track direction angle), and curvature of the point from the discrete path points using interpolation algorithms (such as linear interpolation or spline interpolation).

[0092] S302, if the current simulation time is the initial time, determine the projection point parameter of the previous simulation time based on the preliminary search of the preset reference path curve.

[0093] Specifically, this step and step S301 are parallel optional steps, and those skilled in the art can choose either way according to actual conditions.

[0094] When the starting position of the vehicle model is not near the path starting point, or the path shape is very complex, a simple fixed initial value may deviate too far from the true projection point, making subsequent iteration difficult.

[0095] Therefore, the embodiments of the present disclosure also provide another method for determining the projection point parameter corresponding to the initial time.

[0096] At this time, the server will start a preliminary search process. By traversing the entire reference path curve or a key segment thereof, the projection point parameter is determined.

[0097] A common implementation is that the server can calculate the Euclidean distance from the initial position of the vehicle to all discrete path points on the reference path, then select the path point with the smallest distance, and use its arc length coordinate s as the initial projection point parameter.

[0098] In some embodiments, to improve accuracy, the server can also perform more detailed search or interpolation calculation within a small neighborhood centered on the nearest point.

[0099] At this time, although the calculation process will consume slightly more computing resources than the previous step, it can provide a higher quality initial value for the iterator, especially in the scenario where the simulation starting position is random, which can significantly improve the stability and success rate of the subsequent projection point calculation process.

[0100] S303, if the current simulation time is not the initial time, read the stored projection point parameters obtained at the previous simulation time.

[0101] Specifically, unlike the cases in steps S301 and S302, this step is a method for determining the projection point parameters of the previous simulation time for the non-initial simulation time.

[0102] As described in the foregoing embodiments, the server usually maintains a data buffer inside to store the projection point parameters calculated in the last simulation period.

[0103] In fact, in addition to the projection point parameters, the vehicle model heading angle i-1 and the trajectory direction angle θ i-1 may also be included.

[0104] When the calculation of the current time tᵢ starts, the server will first access this data buffer to read s i-1 and other data.

[0105] Thus, the continuity of vehicle motion in time is utilized, that is, the projection point position at the last time is very close to the real projection point position at the current time, to improve the reliability of the estimated initial value of the current time.

[0106] S304, based on the vehicle model motion state from the previous simulation time to the current simulation time and the simulation step, determine the projection point parameter estimated change from the previous simulation time to the current simulation time.

[0107] Specifically, since the motion state of the vehicle is gradual within a very short time interval (i.e., one simulation step or one simulation period Δt), the movement distance of the projection point on the path (in this embodiment, i.e., the change of the arc length coordinate) can be estimated according to the kinematic relationship.

[0108] Thus, the server can introduce physical constraints into the solution process of numerical iteration.

[0109] Further, the vehicle model motion state includes the vehicle model speed at the current simulation time, at which time the method for determining the projection point parameter estimated change can be:

[0110] Based on the vehicle model heading angle, the trajectory direction angle of the preset reference path curve, the vehicle model speed at the current simulation moment, and the simulation step, a projection point parameter estimated change amount from a previous simulation moment to the current simulation moment is determined, and a calculation method of the projection point parameter estimated change amount is represented as:

[0111] ,

[0112] where Δs i is the projection point parameter estimated change amount at the current simulation moment t i , v i is the vehicle model speed at the current simulation moment t i , Δt is the simulation step, i-1 is the vehicle model heading angle at the previous simulation moment t i-1 , θ i-1 is the trajectory direction angle at the projection point at the previous simulation moment t i-1 .

[0113] Specifically, v i · Δt is used to represent the maximum straight-line distance that the vehicle can travel in one simulation step at the current speed. However, in actual situations, the motion direction (heading angle ) of the vehicle model and the local orientation (trajectory direction angle θ) of the path can not be consistent.

[0114] Therefore, the direction difference is corrected by cos( i-1 - θ i-1 ), which represents the projection ratio of the vehicle speed vector in the path tangent direction.

[0115] When the vehicle heading and the path direction are completely consistent, cos( i-1 - θ i-1 ) = 1, and the change amount is the largest; when there is an included angle, the effective change amount will decrease.

[0116] Therefore, not only the speed of motion (vehicle speed) is considered, but also the direction consistency of motion, so that the estimated arc length change amount is more consistent with the real physical situation, and thus the finally obtained iteration initial value is more accurate.

[0117] In some embodiments, to further enhance robustness, the server can impose additional physical constraints. Specifically, before combining the estimated change amount with the projection point parameter at the previous simulation moment, the server can set an upper limit threshold Δs max for the absolute value of the estimated change amount.

[0118] The calculation of the threshold can be based on the maximum possible acceleration amax and the simulation step Δt, for example, its formula can be expressed as:

[0119] Δs max = v i · Δt + 0.5 · a max · (Δt)².

[0120] At this time, Δs max may represent the maximum arc length that the vehicle can move within a simulation step.

[0121] If the calculated |Δs i | is greater than Δs max , the server will correct Δs i to the absolute value of Δs max or Δs max .

[0122] Thus, it effectively prevents the estimated initial value from deviating too far due to instantaneous mutation of simulation step, sensor data singular value or instantaneous dramatic change of vehicle model, thereby ensuring that the algorithm can still run stably under extreme simulation conditions.

[0123] S305, add the projection point parameter of the previous simulation time to the estimated change to obtain the iteration initial value.

[0124] Specifically, after completing the calculation of step S304, a simple addition operation is performed:

[0125] s i (0) = s i-1 + Δs i ,

[0126] That is:

[0127] s i (0) = s i-1 + v i · Δt · cos( i-1 - θ i-1 ),

[0128] Where s i (0) is the iteration initial value at the current simulation time t i , that is, the initial value provided to the next value iteration algorithm; s i-1 is the projection point parameter at the previous simulation time t i-1 .

[0129] Thus, the server will predict information based on physical laws (i.e. the estimated change Δs i) and historical information (i.e. s i-1 ), to generate a high-quality, clear physical meaning of the iterative starting point. Compared with the traditional method of blind or fixed initial value selection strategy, it can improve the convergence success rate and convergence speed of the subsequent numerical iteration process.

[0130] In this embodiment, the numerical iteration algorithm is illustrated by Newton iteration method. At this time, the specific determination process of the projection point parameter can be realized by the following steps.

[0131] S306, input the initial value of iteration and the current position of the vehicle model into the Newton iteration method to solve the equation and obtain the projection point parameter s i .

[0132] Wherein, the equation solved by Newton iteration method is expressed as:

[0133] ,

[0134] Wherein, (x c , y c ) is the current position coordinate of the vehicle model, and (x(s), y(s)) is the preset reference path curve equation expressed in arc length parameter s.

[0135] Specifically, the server takes s i (0) as the search starting point, and starts the Newton iteration method to solve the nonlinear equation corresponding to the projection point.

[0136] The equation is established based on the geometric principle that the perpendicular line from a point to a curve is perpendicular to the tangent of the curve at that point.

[0137] The specific equation is:

[0138] f(s) = [x c - x(s)] · x'(s) + [y c - y(s)] · y'(s) = 0,

[0139] Wherein, (x c , y c ) is the current position coordinate of the vehicle model obtained by the server, (x(s), y(s)) is the parameter equation of the reference path, and x'(s) and y'(s) are the first-order derivatives (i.e. tangent vectors) thereof.

[0140] The server will iterate according to the following Newton iteration formula:

[0141] s k+1 = s k - f(s k ) / f'(sk ),

[0142] Where, f'(s) k ) is f(s) k The derivative of ), where k is the number of iterations.

[0143] Due to the initial value s of the iteration i (0) The results are very close to the actual values; therefore, in practice, only 1 to 3 iterations are usually needed to satisfy the convergence condition (e.g., |f(s)| < 10). -6 This allows for the efficient and high-precision output of the current projection point parameters s. i .

[0144] S307. Verify that the projection point parameters corresponding to the current simulation moment meet the preset convergence and rationality conditions.

[0145] Specifically, after the iterative solution is completed, the server does not directly use the results, but performs result verification to ensure the reliability of the output results.

[0146] Verification involves two aspects:

[0147] First, the convergence condition: the server checks the final residual |f(s) after the iteration is complete. i Whether it is less than the preset error threshold to ensure mathematical convergence.

[0148] Secondly, regarding the reasonableness condition, the server will check the calculated arc length s. i Compared to the previous s i-1 Check whether the difference is within a reasonable range based on the vehicle's maximum physical performance (such as maximum acceleration); or check whether the projection point is within the domain of the reference path.

[0149] Thus, the robustness of the entire system is greatly improved through the dual verification mechanism.

[0150] S308. If the verification result shows that the projection point parameters meet the convergence and rationality conditions, store the projection point parameters corresponding to the current simulation time.

[0151] Specifically, if the verification passes, the server will send the successfully calculated projection point parameters s at the current moment. i and the vehicle's heading angle at this moment. i and the trajectory direction angle θ at the projection point i This data is written into the data cache. This prepares for the calculation of projection point parameters at the next simulation time, forming a complete, closed-loop processing flow and ensuring the continuous and stable operation of the algorithm in the time dimension.

[0152] S309, if the verification result is that the projection point parameter does not satisfy the convergence condition and the rationality condition, reducing the simulation step and re-determining the projection point parameter at the current simulation time, or inputting the projection point parameter in the plurality of historical records into an interpolation method to output the projection point parameter at the current simulation time.

[0153] Specifically, the server is further configured with an exception handling mechanism to further improve system robustness.

[0154] When the verification fails, the server will start the exception handling mechanism.

[0155] One way of handling is to reduce the simulation step.

[0156] At this time, the server temporarily halves the current simulation step Δt, and re-executes the estimation and iterative calculation from S304 based on the state at the last time.

[0157] Because a smaller time step means smaller changes in vehicle state, the estimation is more accurate, so it can usually solve the iteration failure caused by the vehicle's dramatic maneuver.

[0158] Another way of handling is to interpolate based on historical data.

[0159] At this time, the server retrieves the projection point parameters at the last few successful times (such as t i-3 , t i-2 , t i-1 ) from the data cache, and establishes an interpolation function (such as quadratic Lagrange interpolation, linear interpolation or quadratic interpolation algorithm) about time t, and calculates the estimated value of the projection point parameter at the current time t i accordingly.

[0160] In this way, when the iterator is completely disabled, a smooth and reasonable estimated value can be provided to prevent the simulation from being completely interrupted.

[0161] S310, generating a control signal for vehicle trajectory tracking based on the projection point parameter corresponding to the current simulation time.

[0162] Specifically, the server uses the projection point parameter s i output by S306 and verified by S307, and the server can generate a corresponding control signal and can drive the next dynamic response of the vehicle model based on the control signal, thereby achieving accurate trajectory tracking.

[0163] The related content can be referred to the corresponding steps in the embodiments shown in Figure 2 , and will not be described here.

[0164] It should be noted that the technical scheme provided by the embodiments of the present disclosure is particularly prominent when dealing with complex scenarios such as the existence of intersection, branching or very close parallel sections of the reference path. In these scenarios, there may be multiple local nearest points (i.e., multiple points satisfying the vertical condition) in geometry for a vehicle positioning point.

[0165] In the above case, the traditional method is prone to converge to the wrong local nearest point due to the initial value selection being irrelevant to the historical solution, resulting in the controller receiving sudden and wrong path information and causing violent oscillation of the vehicle movement. However, the technical scheme provided by the embodiments of the present disclosure forces the use of the estimated initial value based on the correct solution at the previous time, which is equivalent to pre-specifying the correct path branch for the iterative algorithm.

[0166] For example, when the vehicle model is about to pass through a three-way intersection, as long as its historical trajectory has been located on the target branch, even if its current position is temporarily closer to the wrong branch in geometry, since the iterative initial value is fixed and set near the arc length coordinate of the target branch, the numerical iterative algorithm will naturally find and converge to the projection point on the correct branch. Thus, the jumping of the projection point between branches is avoided from the root, ensuring the smoothness and stability of the path tracking.

[0167] The vehicle trajectory tracking control method provided by the embodiments of the present disclosure overcomes the defects of convergence failure or convergence to the wrong local solution caused by the blindness of initial value selection in the traditional method by specifically limiting the initial time of the multiple projection point parameter determination method, estimating the iterative initial value based on the vehicle speed and heading angle, and introducing the Newton iteration algorithm and the complete process including verification and backup scheme, thereby utilizing the time sequence continuity and physical law of vehicle movement, ensuring high accuracy and high convergence of the projection point parameter calculation, and significantly reducing the number of iterations, thereby significantly improving the overall stability and computational efficiency of the vehicle trajectory tracking control simulation in complex path scenarios.

[0168] Figure 4 The structure schematic diagram of the vehicle trajectory tracking control device provided by the present application is shown in FIG. 4, and the vehicle trajectory tracking control device 400 provided by the embodiments of the present disclosure includes: Figure 4

[0169] The acquisition module 410 is configured to acquire the projection point parameter of the vehicle model at the previous simulation time, wherein the projection point parameter is used to represent the relative position of the projection point of the positioning point of the vehicle model to the preset reference path curve in the preset reference path curve, and the vehicle model is a multi-body dynamics simulation model.

[0170] The determination module 420 is configured to determine the iterative initial value corresponding to the current simulation time based on the projection point parameter at the previous simulation time and the motion state of the vehicle model from the previous simulation time to the current simulation time. ​

[0171] The calculation module 430 is configured to input the iteration initial value and the current position of the vehicle model into the numerical iteration algorithm, and output the projection point parameter corresponding to the current simulation moment;

[0172] The processing module 440 is configured to generate a control signal for vehicle trajectory tracking based on the projection point parameter corresponding to the current simulation moment.

[0173] In an embodiment of the present disclosure, the acquisition module 410 is specifically configured to, if the current simulation moment is an initial moment, determine the preset initial value as the projection point parameter at the previous simulation moment, or determine the projection point parameter at the previous simulation moment based on preliminary searching of the preset reference path curve; if the current simulation moment is a non-initial moment, read the stored projection point parameter at the previous simulation moment.

[0174] In an embodiment of the present disclosure, the determination module 420 is specifically configured to determine, based on the motion state of the vehicle model from the previous simulation moment to the current simulation moment and the simulation step length, a projection point parameter estimated change amount from the previous simulation moment to the current simulation moment; and add the projection point parameter at the previous simulation moment and the estimated change amount to obtain the iteration initial value.

[0175] In an embodiment of the present disclosure, the determination module 420 is specifically configured to, if the motion state of the vehicle model includes a vehicle model speed at the current simulation moment, determine, based on a heading angle of the vehicle model, a trajectory direction angle of the preset reference path curve, the vehicle model speed at the current simulation moment and the simulation step length, a projection point parameter estimated change amount from the previous simulation moment to the current simulation moment, and the calculation method of the projection point parameter estimated change amount is represented as:

[0176] Δs i = v i · Δt · cos( i-1 - θ i-1 ),

[0177] wherein Δs i is the projection point parameter estimated change amount at the current simulation moment t i , v i is the vehicle model speed at the current simulation moment t i , Δt is the simulation step length, i-1 is the vehicle model heading angle at the previous simulation moment t i-1 , θ i-1 is the trajectory direction angle at the projection point at the previous simulation moment t i-1 .

[0178] In an embodiment of the present disclosure, the acquisition module 410 specifically comprises that the projection point parameter is an arc length coordinate of the projection point on the preset reference path curve.

[0179] In an embodiment of the present disclosure, the calculation module 430 is specifically configured to, if the numerical iteration algorithm comprises a Newton iteration algorithm, input the iteration initial value and the current position of the vehicle model into the Newton iteration method to solve the equation, to obtain the projection point parameter s of the current simulation moment i , and the equation solved by the Newton iteration method is expressed as:

[0180] ,

[0181] , wherein (x c , y c ) is the current position coordinate of the vehicle model, and (x(s), y(s)) is the preset reference path curve equation expressed in the arc length parameter s.

[0182] In an embodiment of the present disclosure, the calculation module 430 is further configured to, after inputting the iteration initial value and the current position of the vehicle model into the numerical iteration algorithm and outputting the projection point parameter corresponding to the current simulation moment, verify whether the projection point parameter corresponding to the current simulation moment satisfies the preset convergence condition and the rationality condition; if the verification result is that the projection point parameter satisfies the convergence condition and the rationality condition, store the projection point parameter corresponding to the current simulation moment; if the verification result is that the projection point parameter does not satisfy the convergence condition and the rationality condition, reduce the simulation step and re-determine the projection point parameter of the current simulation moment, or input the projection point parameters in the plurality of historical records into the interpolation method to output the projection point parameter of the current simulation moment.

[0183] The vehicle trajectory tracking control device provided in the embodiment can execute the method provided in the method embodiment, and has similar implementation principles and technical effects, which will not be described here.

[0184] Figure 5 A structural schematic diagram of an electronic device is provided in the present application. As shown in the figure, Figure 5 The electronic device 50 comprises:

[0185] a processor 51, a memory 52, and a communication interface 53;

[0186] The memory 52 is configured to store executable instructions of the processor 51.

[0187] The processor 51 is configured to execute the technical solutions in any of the preceding method embodiments by executing the executable instructions.

[0188] Optionally, the memory 52 can be independent or integrated with the processor 51.

[0189] Optionally, when the memory 52 is a device independent of the processor 51, the electronic device 50 can further include:

[0190] The bus 54, the memory 52 and the communication interface 53 are connected with the processor 51 through the bus 54 and complete communication with each other, and the communication interface 53 is used for communication with other devices.

[0191] Optionally, the communication interface 53 can be implemented by a transceiver. The communication interface is used to realize communication between the database access device and other devices (for example, a client, a read-write library and a read-only library). The memory can include a random access memory (RAM) and can also include a non-volatile memory, for example, at least one disk memory.

[0192] The bus 54 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or only one type of bus.

[0193] The processor described above can be a general-purpose processor, including a central processing unit CPU, a network processor (NP), etc.; can also be a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0194] The electronic device is used to execute the technical solutions in any of the preceding method embodiments, and the implementation principles and technical effects are similar, which will not be described here.

[0195] The embodiment of the present application further provides a readable storage medium, which has a computer program stored thereon, and the computer program is executed by a processor to realize the technical solutions provided by any of the preceding method embodiments.

[0196] The embodiment of the present application further provides a computer program product, which includes a computer program, and the computer program is executed by a processor to realize the technical solutions provided by any of the preceding method embodiments.

[0197] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0198] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A vehicle trajectory tracking control method, characterized in that, include: Obtain the projection point parameters of the vehicle model at the previous simulation time, wherein the projection point parameters are used to represent the relative position of the projection point of the vehicle model positioning point to the preset reference path curve in the preset reference path curve, and the vehicle model is a multibody dynamics simulation model. Based on the projection point parameters of the previous simulation time and the vehicle model motion state from the previous simulation time to the current simulation time, determine the initial value of the iteration corresponding to the current simulation time. The initial value of the iteration and the current position of the vehicle model are input into the numerical iteration algorithm, and the projection point parameters corresponding to the current simulation time are output. Based on the projection point parameters corresponding to the current simulation moment, control signals for vehicle trajectory tracking are generated.

2. The method according to claim 1, characterized in that, The acquisition of the projection point parameters of the vehicle model at the previous simulation moment includes: If the current simulation time is the initial time, then the preset initial value is determined as the projection point parameter of the previous simulation time, or the projection point parameter of the previous simulation time is determined based on the preliminary search of the preset reference path curve. If the current simulation time is not the initial time, then read the projection point parameters obtained from the previous simulation time.

3. The method according to claim 1, characterized in that, The determination of the initial iteration value corresponding to the current simulation moment based on the projection point parameters of the previous simulation moment and the vehicle model motion state from the previous simulation moment to the current simulation moment includes: Based on the vehicle model motion state and simulation step size from the previous simulation time to the current simulation time, the estimated change in projection point parameters from the previous simulation time to the current simulation time is determined. The projection point parameters at the previous simulation moment are added to the estimated change to obtain the initial value for iteration.

4. The method according to claim 3, characterized in that, The vehicle model's motion state includes the vehicle model's speed at the current simulation moment; The step of determining the estimated change in projection point parameters from the previous simulation time to the current simulation time based on the vehicle model motion state and simulation step size from the previous simulation time includes: Based on the heading angle of the vehicle model, the trajectory direction angle of the preset reference path curve, the vehicle model speed and simulation step size at the current simulation moment, the estimated change in projection point parameters from the previous simulation moment to the current simulation moment is determined. The calculation method for the estimated change in projection point parameters is expressed as follows: ， Where, Δs i Let t be the current simulation time. i The estimated change in the projection point parameters, v i Let t be the current simulation time. i The vehicle model's speed, Δt is the simulation step size. i-1 For the previous simulation time t i-1 The vehicle model's heading angle, θ i-1 For the previous simulation time t i-1 The trajectory direction angle at the projection point.

5. The method according to claim 3, characterized in that, The projection point parameter is the arc length coordinate of the projection point on the preset reference path curve.

6. The method according to any one of claims 1 to 5, characterized in that, The numerical iteration algorithm includes Newton's iteration algorithm. The step of inputting the initial iteration value and the current position of the vehicle model into the numerical iteration algorithm, and outputting the projection point parameters corresponding to the current simulation moment, includes: The initial values ​​of the iteration and the current position of the vehicle model are input into the Newton-Raphson iteration method to solve the equations, and the projection point parameters s at the current simulation moment are obtained. i The solution to the equation using Newton's iterative method is expressed as: ， Among them, (x c y c (x(s), y(s)) represents the current position coordinates of the vehicle model, and (x(s), y(s)) represents the equation of the preset reference path curve expressed in terms of the arc length parameter s.

7. The method according to any one of claims 1 to 6, characterized in that, After inputting the initial iteration value and the current position of the vehicle model into the numerical iteration algorithm and outputting the projection point parameters corresponding to the current simulation moment, the algorithm further includes: Verify that the projection point parameters corresponding to the current simulation moment meet the preset convergence and rationality conditions; If the verification result shows that the projection point parameters satisfy the convergence condition and the rationality condition, store the projection point parameters corresponding to the current simulation moment; If the verification result shows that the projection point parameters do not meet the convergence and rationality conditions, reduce the simulation step size and redetermine the projection point parameters at the current simulation moment; or, input the projection point parameters from multiple historical records into the interpolation method and output the projection point parameters at the current simulation moment.

8. A vehicle trajectory tracking and control device, characterized in that, include: The acquisition module is used to acquire the projection point parameters of the vehicle model at the previous simulation time. The projection point parameters are used to represent the relative position of the projection point of the vehicle model positioning point to the preset reference path curve in the preset reference path curve. The vehicle model is a multibody dynamics simulation model. The determination module is used to determine the initial values ​​of the iteration corresponding to the current simulation time based on the projection point parameters of the previous simulation time and the motion state of the vehicle model from the previous simulation time to the current simulation time. The calculation module is used to input the initial value of the iteration and the current position of the vehicle model into the numerical iteration algorithm, and output the projection point parameters corresponding to the current simulation time. The processing module is used to generate control signals for vehicle trajectory tracking based on the projection point parameters corresponding to the current simulation moment.

9. An electronic device, characterized in that, include: Processor, memory, communication interface; The memory is used to store the executable instructions of the processor; The processor is configured to execute the vehicle trajectory tracking control method according to any one of claims 1 to 7 by executing the executable instructions.

10. A readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the vehicle trajectory tracking control method according to any one of claims 1 to 7.

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