Vehicle drift trajectory control method, device, equipment and storage medium

Abstract

The application discloses a vehicle drift track control method, device and equipment and a storage medium, and belongs to the technical field of vehicle control. The application determines target state parameters based on corresponding expected tracks of a vehicle; obtains current state parameters of the vehicle; determines parameter differences between the current state parameters and the target state parameters; calculates reference control parameters according to the parameter differences and a vehicle tracking error model; and controls the vehicle to drift along the expected track according to the reference control parameters. The target control parameters are calculated according to the current state parameters of the vehicle and the target state parameters corresponding to the expected track, the vehicle can drift along the expected track by the target control parameters, the vehicle physical parameters do not need to be calibrated, the experience dynamics model does not need to be relied on, the control parameters are directly calibrated, and the precision of the vehicle drift track control is improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle control technology, and in particular to a method, apparatus, device, and storage medium for controlling vehicle drift trajectory. Background Technology

[0002] Drifting, tail-sliding, and other extreme control techniques can break through the constraints of steady-state control, giving vehicles greater freedom and improving their active safety in conditions such as sideslip, roll, and low road adhesion.

[0003] Current autonomous driving control technology primarily focuses on steady-state vehicle control, where all wheels have good traction, and the vehicle operates on a stable equilibrium surface approximating an ideal Ackermann model. When disturbed, the vehicle tends to automatically return to equilibrium, making control relatively easy. However, in extreme conditions such as sideslip, drifting, or fishtailing, the rear wheels typically slip. To maintain balance, the front wheels need to counter-steer, placing the vehicle on an unstable equilibrium surface. When disturbed, the vehicle tends to deviate further from its equilibrium state, making control more challenging.

[0004] Existing autonomous driving drift control technologies generally require pre-calibrating physical parameters such as the vehicle's center of gravity, moment of inertia, and tire friction curves, and then substituting these parameters into the vehicle dynamics equations to calculate the relationship between control quantities and the vehicle's dynamic response. However, this approach has several drawbacks: 1. Some vehicle parameters are complex and variable, and difficult to calibrate accurately; 2. Friction varies with ground conditions, making pre-calibration difficult; 3. There are discrepancies between empirical dynamic models and actual vehicle conditions, and even minor calculation errors can cause the vehicle to lose control. These shortcomings prevent current methods from guaranteeing the accuracy of vehicle drift trajectory control.

[0005] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] The main objective of this invention is to provide a vehicle drift trajectory control method, device, equipment, and storage medium, aiming to solve the technical problem that the prior art cannot accurately control vehicle drift.

[0007] To achieve the above objectives, the present invention provides a vehicle drift trajectory control method, which includes the following steps:

[0008] Determine the target state parameters based on the desired trajectory corresponding to the vehicle;

[0009] Obtain the current status parameters of the vehicle;

[0010] Determine the parameter difference between the current state parameter and the target state parameter;

[0011] Calculate reference control parameters based on the parameter differences and the vehicle tracking error model;

[0012] The vehicle is controlled to drift along the desired trajectory based on the reference control parameters.

[0013] Optionally, before determining the target state parameters based on the desired trajectory corresponding to the vehicle, the method further includes:

[0014] Construct a vehicle state error model corresponding to the vehicle;

[0015] The vehicle is adjusted to a steady-state drift state based on the vehicle state error model.

[0016] When the vehicle is in the steady-state drift state, the step of determining the target state parameters based on the desired trajectory corresponding to the vehicle is performed.

[0017] Optionally, constructing the vehicle state error model corresponding to the vehicle includes:

[0018] Obtain the historical steady-state parameters and historical steady-state control parameters of the vehicle;

[0019] The model parameters are determined based on the historical steady-state parameters and historical steady-state control parameters.

[0020] The vehicle state error model corresponding to the vehicle is constructed based on the model parameters.

[0021] Optionally, before performing the step of determining the target state parameters based on the desired trajectory corresponding to the vehicle, the method further includes:

[0022] Get the vehicle's current location;

[0023] Determine the trajectory point closest to the vehicle on the desired trajectory based on the current location;

[0024] Determine the difference in state parameters between the vehicle and the trajectory point;

[0025] When the difference in the state parameters is within a preset range, the step of determining the target state parameters based on the desired trajectory corresponding to the vehicle is executed.

[0026] Optionally, before calculating the reference control parameters based on the parameter difference and the vehicle tracking error model, the method further includes:

[0027] Construct a tracking reference line for the vehicle;

[0028] The error between the vehicle and the desired trajectory is determined based on the tracking reference line;

[0029] A vehicle tracking error model is constructed based on the aforementioned error.

[0030] Optionally, the reference control parameters are the control parameters corresponding to the vehicle at the current moment, and controlling the vehicle to drift according to the desired trajectory based on the reference control parameters includes:

[0031] Query the desired tracking state that the vehicle can achieve after a preset time.

[0032] The target control parameters are obtained based on the desired tracking state and the reference control parameters;

[0033] The vehicle is controlled to drift along the desired trajectory according to the target control parameters.

[0034] Optionally, obtaining the target control parameters based on the desired tracking state and the reference control parameters includes:

[0035] Determine the tracking reference control parameters corresponding to the preset time based on the desired tracking state;

[0036] Obtain the state ratio coefficient between the current state of the vehicle and the desired tracking state;

[0037] The target control parameters are calculated based on the state proportional coefficient, the reference control parameters, and the tracking reference control parameters.

[0038] Furthermore, to achieve the above objectives, the present invention also proposes a vehicle drift trajectory control device, the vehicle drift trajectory control device comprising:

[0039] The calculation module is used to determine the target state parameters based on the desired trajectory corresponding to the vehicle.

[0040] The acquisition module is used to acquire the current status parameters of the vehicle;

[0041] The calculation module is also used to determine the parameter difference between the current state parameter and the target state parameter;

[0042] The calculation module is also used to calculate reference control parameters based on the parameter difference and the vehicle tracking error model;

[0043] The control module is used to control the vehicle to drift along the desired trajectory according to the reference control parameters.

[0044] Furthermore, to achieve the above objectives, the present invention also proposes a vehicle drift trajectory control device, which includes: a memory, a processor, and a vehicle drift trajectory control program stored in the memory and running on the processor, wherein the vehicle drift trajectory control program is configured to implement the vehicle drift trajectory control method as described above.

[0045] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing a vehicle drift trajectory control program, which, when executed by a processor, implements the vehicle drift trajectory control method as described above.

[0046] This invention determines target state parameters based on the desired trajectory of a vehicle; obtains the current state parameters of the vehicle; determines the parameter difference between the current state parameters and the target state parameters; calculates reference control parameters based on the parameter difference and the vehicle tracking error model; and controls the vehicle to drift along the desired trajectory based on the reference control parameters. By calculating the target control parameters using the current state parameters of the vehicle and the target state parameters corresponding to the desired trajectory, and then controlling the vehicle to drift along the desired trajectory using the target control parameters, this invention improves the accuracy of vehicle drift trajectory control by directly calibrating control parameters without calibrating vehicle physical parameters or relying on empirical dynamic models. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the structure of the vehicle drift trajectory control device in the hardware operating environment involved in the embodiments of the present invention;

[0048] Figure 2 This is a flowchart illustrating the first embodiment of the vehicle drift trajectory control method of the present invention;

[0049] Figure 3 This is a schematic diagram of a vehicle model in one embodiment of the vehicle drift trajectory control method of the present invention;

[0050] Figure 4 This is a flowchart of an open-loop drift initiation model in one embodiment of the vehicle drift trajectory control method of the present invention;

[0051] Figure 5 This is a two-dimensional surface diagram of state parameters in one embodiment of the vehicle drift trajectory control method of the present invention;

[0052] Figure 6 This is a two-dimensional surface diagram of a control parameter in one embodiment of the vehicle drift trajectory control method of the present invention;

[0053] Figure 7 This is a two-dimensional surface diagram of another control parameter in one embodiment of the vehicle drift trajectory control method of the present invention;

[0054] Figure 8 This is a flowchart illustrating the second embodiment of the vehicle drift trajectory control method of the present invention;

[0055] Figure 9 This is a schematic diagram of tracking error in one embodiment of the vehicle drift trajectory control method of the present invention;

[0056] Figure 10 This is a two-dimensional surface diagram of the state parameters of the vehicle under the error between the vehicle and the desired trajectory in one embodiment of the vehicle drift trajectory control method of the present invention;

[0057] Figure 11 This is a two-dimensional surface schematic diagram of control parameters under the error between the vehicle and the desired trajectory in one embodiment of the vehicle drift trajectory control method of the present invention;

[0058] Figure 12 This is a schematic diagram of a two-dimensional surface representing another control parameter under the error between the vehicle and the desired trajectory in one embodiment of the vehicle drift trajectory control method of the present invention;

[0059] Figure 13 This is a flowchart illustrating the third embodiment of the vehicle drift trajectory control method of the present invention;

[0060] Figure 14 This is a structural block diagram of the first embodiment of the vehicle drift trajectory control device of the present invention.

[0061] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0062] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0063] Reference Figure 1 , Figure 1 This is a schematic diagram of the vehicle drift trajectory control device structure in the hardware operating environment involved in the embodiments of the present invention.

[0064] like Figure 1As shown, the vehicle drift trajectory control device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk storage device. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0065] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the vehicle drift trajectory control device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0066] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and a vehicle drift trajectory control program.

[0067] exist Figure 1 In the vehicle drift trajectory control device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the vehicle drift trajectory control device of the present invention can be set in the vehicle drift trajectory control device, and the vehicle drift trajectory control device calls the vehicle drift trajectory control program stored in the memory 1005 through the processor 1001 and executes the vehicle drift trajectory control method provided in the embodiment of the present invention.

[0068] This invention provides a vehicle drift trajectory control method, referring to... Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of a vehicle drift trajectory control method according to the present invention.

[0069] In this embodiment, the vehicle drift trajectory control method includes the following steps:

[0070] Step S10: Determine the target state parameters based on the desired trajectory corresponding to the vehicle.

[0071] In this embodiment, the executing entity is the vehicle drift trajectory control device, which has functions such as data acquisition, data communication, and program execution. Of course, other devices with similar functions can also be used; this embodiment does not limit this. This embodiment uses a vehicle drift trajectory control device as an example for explanation.

[0072] It's important to note that current autonomous driving control technology primarily focuses on steady-state vehicle control, where all wheels have good grip and the vehicle operates on a stable equilibrium surface approximating an ideal Ackermann model. When disturbed, the vehicle tends to automatically return to equilibrium, making control relatively easy. However, in extreme conditions such as sideslip, drifting, or fishtailing, the rear wheels typically slip. To maintain balance, the front wheels need to counter-steer, placing the vehicle on an unstable equilibrium surface. When disturbed, the vehicle tends to deviate further from equilibrium, making control more difficult. Existing autonomous driving drift control technologies generally require pre-calibrating physical parameters such as the vehicle's center of gravity, moment of inertia, and tire friction curves, and then substituting these parameters into the vehicle's dynamics equations to calculate the relationship between control inputs and dynamic response. However, this approach suffers from several drawbacks: some vehicle parameters are complex and variable, making accurate calibration difficult; friction varies with ground conditions, making pre-calibration challenging; and empirical dynamics models deviate from actual vehicle conditions, with even minor calculation errors causing loss of control. These shortcomings prevent current methods from guaranteeing precise drift trajectory control.

[0073] In this embodiment, to solve the aforementioned technical problem, the target state parameters are determined based on the desired trajectory corresponding to the vehicle; the current state parameters of the vehicle are obtained; the parameter difference between the current state parameters and the target state parameters is determined; reference control parameters are calculated based on the parameter difference and the vehicle tracking error model; and the vehicle is controlled to drift according to the desired trajectory based on the reference control parameters. The target control parameters are calculated using the vehicle's current state parameters and the target state parameters corresponding to the desired trajectory, and then the vehicle is controlled to drift according to the desired trajectory using the target control parameters. This method eliminates the need to calibrate vehicle physical parameters and does not rely on empirical dynamic models; it directly calibrates the control parameters, thus improving the accuracy of vehicle drift trajectory control. Specifically, it can be implemented as follows.

[0074] It should be noted that in this embodiment, drifting is controlled along a certain trajectory. This trajectory can be a desired trajectory, which can be preset. The specific trajectory form can be selected according to actual control requirements, and this embodiment does not impose any restrictions on it. After determining the desired trajectory corresponding to the vehicle, target state parameters can be further determined based on this desired trajectory. The target state parameters represent the state parameters that the vehicle should have when drifting along the desired trajectory. The target state parameters can be derived from various trajectory points on the desired trajectory.

[0075] Step S20: Obtain the current status parameters of the vehicle.

[0076] In this embodiment, no empirical dynamic model is relied upon, and vehicle physical parameter calibration is not required. When drift control of the vehicle is needed, the current state parameters of the vehicle can be directly obtained. The current state parameters of the vehicle obtained in this embodiment include, but are not limited to, center of mass velocity, sideslip angle, yaw rate, and longitudinal axis velocity. When the vehicle enters the drift equilibrium state, it is a three-degree-of-freedom model. By specifying different drift directions, it can be simplified to a two-degree-of-freedom model, that is, specifying two linearly independent dynamic parameters can determine the vehicle state during all other drifts, such as... Figure 3 As shown. Figure 3 In this context, r represents the vehicle's yaw rate, β represents the vehicle's center of gravity velocity and sideslip angle, V represents the vehicle's longitudinal velocity, Fxr and Fxy represent the vehicle's tire driving force, and Φ represents the vehicle's steering wheel angle.

[0077] In this embodiment, the center of gravity velocity sideslip angle and yaw rate are selected as control variables, and the longitudinal axis velocity is used as the key parameter for observing the vehicle's state. Therefore, the current state of the vehicle can be determined through these parameters. It should be emphasized that when the center of gravity velocity sideslip angle, yaw rate, and longitudinal axis velocity are in a stable state, especially when the longitudinal axis velocity is near the steady-state drift point, the vehicle can be considered to be in a steady-state drift state. It should be noted that the above current state parameters are for illustrative purposes only. In specific processes, other parameters can be selected as the vehicle's state parameters based on different control requirements. This embodiment does not impose any restrictions on this.

[0078] It is important to emphasize that after the vehicle enters the drift state from a stationary state, this embodiment first controls it to be in a steady-state drift state, and then controls the vehicle to drift according to the desired trajectory. Therefore, the current state parameters of the vehicle obtained in this embodiment are the vehicle state parameters when the vehicle is in a steady-state drift state. Controlling the vehicle to a steady-state drift state can be achieved using a vehicle state error model. The specific construction process of the vehicle state error model is as follows: For a vehicle with unknown parameters, this embodiment uses an open-loop drift initiation model to control it from a stationary state to a steady-state drift, recording the drift parameters. The flowchart of the open-loop drift initiation model is as follows: Figure 4 As shown, by adjusting the open-loop control parameters of the open-loop drift initiation model, the vehicle can be made to enter different steady-state drift states. Since each steady-state drift state corresponds to a set of drift parameters, multiple sets of drift parameters for the vehicle can be recorded. The recorded drift parameters include at least the longitudinal axis velocity, steering wheel angle, and rear wheel driving force, as well as the center of gravity velocity, sideslip angle, and yaw rate under different drift states. Then, using the multiple sets of parameters recorded in the open-loop drift initiation model under different steady-state drift states—that is, several reference state parameters and several reference control parameters—a two-dimensional surface is constructed. The reference state parameters include the longitudinal axis velocity, center of gravity velocity, sideslip angle, and yaw rate. Based on these parameters, a two-dimensional surface of state parameters can be constructed. The reference control parameters include the steering wheel angle and rear wheel driving force. Based on these parameters, a two-dimensional surface of control parameters can be constructed. The two parameter surfaces obtained in the above process are shown below. Figures 5-7 As shown. (Refer to...) Figure 5 As shown, Figure 5 For state parameter surfaces, Figure 5 In the figure, U_x_low represents the velocity along the vertical axis, yaw_rate_low represents the yaw rate, and bata_low represents the sideslip angle of the center of mass. The coordinate points in the figure represent the vertical velocity, sideslip angle of the center of mass, and yaw rate corresponding to different steady-state drift states. Figure 6 and Figure 7 All are control parameter surfaces. Figure 6 In this context, delta_low represents the steering wheel angle. Figure 7 In this context, Fx_R_low represents the rear-wheel drive force. Finally, based on the constructed parametric two-dimensional surface, an arbitrary set of historical steady-state parameters and historical steady-state control parameters are determined. These parameters are then substituted into the following equation for solution: d(△X)=A*△X+B*△U, where △X is the parameter difference of the state parameters and △U is the parameter difference of the control parameters. Substituting these parameters into the equation yields A and B. It should be noted that A and B differ under different steady-state drift states; each steady-state drift state corresponds to a separate set of A and B. After obtaining the A and B model parameters, the vehicle state error model is complete.

[0079] Furthermore, before controlling the vehicle to drift along the desired trajectory, this embodiment also needs to obtain the vehicle's current position, then determine the trajectory point closest to the vehicle on the desired trajectory based on the vehicle's current position, and determine the state parameter difference between the vehicle and the trajectory point. This state parameter difference can be calculated by subtracting the current state parameter difference of the vehicle from the reference state parameter value corresponding to the trajectory point. If the current vehicle state deviates too much from the state of the matching point, it is considered that the control effect of the current matching point cannot be stably completed. Therefore, the vehicle's drift trajectory is controlled only when the state parameter difference is within a preset range. The preset range can be set according to actual needs, and this embodiment does not impose any restrictions on it.

[0080] Step S30: Determine the parameter difference between the current state parameter and the target state parameter.

[0081] In the specific implementation, after obtaining the current state parameters of the vehicle, this embodiment further needs to calculate the parameter difference between the current state parameters and the target state parameters, where the target state parameters are the state parameters corresponding to the desired trajectory.

[0082] Step S40: Calculate the reference control parameters based on the parameter difference and the vehicle tracking error model.

[0083] It should be noted that the vehicle state error model mentioned above is used to control the vehicle in a steady-state drift state, while the vehicle tracking error model in this embodiment is used to control the drift trajectory of the vehicle in a steady-state drift state.

[0084] In this specific implementation, after calculating the parameter difference, the parameter difference can be substituted into the vehicle tracking error model to obtain the reference control parameters. Specifically, the parameter difference between the control parameters can be calculated based on the parameter difference of the state parameters, and the reference control parameters can be calculated based on the parameter difference between the control parameters.

[0085] Step S50: Control the vehicle to drift along the desired trajectory according to the reference control parameters.

[0086] In practical implementation, the desired trajectory can be viewed as a curve composed of multiple trajectory points. The control parameters differ depending on the relative position of the vehicle to each trajectory point, and these parameters can be determined based on the error between the vehicle and the desired trajectory. After determining the reference control parameters, this embodiment controls the vehicle according to the steering wheel angle and rear-wheel drive force included in the reference control parameters, thus enabling the vehicle to drift along the desired trajectory.

[0087] This embodiment determines target state parameters based on the desired trajectory corresponding to the vehicle; obtains the current state parameters of the vehicle; determines the parameter difference between the current state parameters and the target state parameters; calculates reference control parameters based on the parameter difference and the vehicle tracking error model; and controls the vehicle to drift according to the desired trajectory based on the reference control parameters. By calculating the target control parameters using the current state parameters of the vehicle and the target state parameters corresponding to the desired trajectory, and then controlling the vehicle to drift according to the desired trajectory using the target control parameters, this method eliminates the need to calibrate vehicle physical parameters and does not rely on empirical dynamic models. It directly calibrates the control parameters, thereby improving the accuracy of vehicle drift trajectory control.

[0088] refer to Figure 8 , Figure 8 This is a flowchart illustrating a second embodiment of a vehicle drift trajectory control method according to the present invention.

[0089] Based on the first embodiment described above, the vehicle drift trajectory control method in this embodiment further includes the following step before step S40:

[0090] Step S401: Construct the tracking reference line corresponding to the vehicle.

[0091] It should be noted that in this embodiment, the vehicle's trajectory in a steady-state drift state is changed based on the error between the vehicle and the desired trajectory, so that the vehicle drifts steadily according to the desired trajectory. Before determining the error between the vehicle and the desired trajectory, it is necessary to first construct a tracking reference line corresponding to the vehicle, such as... Figure 9 L1 is shown.

[0092] Step S402: Determine the error between the vehicle and the desired trajectory based on the tracking reference line.

[0093] In practical implementation, the lateral error e between the vehicle and the trajectory, as well as the vehicle's own velocity direction angle, can be determined based on this tracking reference line. With trajectory error From the lateral error e, we can also obtain the derivative of the lateral error, e_dot. Wherein, V = Ux / cos(β), V_dot = Ux_dot / cos(β).

[0094] Step S403: Construct a vehicle tracking error model based on the error.

[0095] It should be noted that, compared to the vehicle state error model, the vehicle tracking error model extends the state variables of the differential equation for tracking error. The constant 1 can compensate for the error caused by the tracking state. Based on these quantities, a vehicle tracking error model can be constructed, d(△X1)=A*△X1+B*△U, where the model parameters A and B are shown below.

[0096]

[0097] Based on the extended differential equations described above, by substituting any set of errors between the vehicles and the desired trajectory, and combining this error with the state parameter differences and control parameter differences between the vehicles regressing from the current trajectory to the desired trajectory, model parameters A and B can be calculated to complete the construction of the vehicle tracking error model. It is important to emphasize that different errors correspond to different sets of model parameters AA and BB. In this embodiment, AA and BB are the same as A and B calculated in the vehicle state error model above. Each set of centroid velocity sideslip angle and yaw rate corresponds to a set of A and B. In the tracking part, AA and BB can be directly looked up based on the centroid velocity sideslip angle and yaw rate, but other parts of A and B need to be calculated in real time.

[0098] Furthermore, in this embodiment, the construction of the two-dimensional surface parameters involved in the steady-state drifting process of the controlled vehicle is the same as that described above. Both are constructed using variables such as longitudinal axis velocity, yaw angle, center of gravity velocity sideslip angle, steering wheel angle, and historical rear-wheel drive force. For example... Figures 10-12 As shown, the definitions of the parameters involved are the same as those mentioned above. Figures 5-7 Similarly, when controlling the vehicle to return to the desired trajectory, it can be done from... Figures 10-12 Find the corresponding status parameters and control parameters in the database.

[0099] This embodiment constructs a tracking reference line corresponding to the vehicle; determines the error between the vehicle and the desired trajectory based on the tracking reference line; and constructs a vehicle tracking error model based on the error. The vehicle tracking error model constructed above can more accurately control the trajectory of the vehicle during the drifting process, thereby improving the control accuracy of vehicle drifting.

[0100] refer to Figure 13 , Figure 13 This is a flowchart illustrating a third embodiment of a vehicle drift trajectory control method according to the present invention.

[0101] Based on the first and second embodiments described above, a third embodiment of the vehicle drift trajectory control method of the present invention is proposed.

[0102] In this embodiment, step S50 specifically includes:

[0103] Step S501: Query the desired tracking state that the vehicle can reach after a preset time.

[0104] In this embodiment, in order to improve the control accuracy of the vehicle's trajectory during drifting, it is also necessary to query the expected tracking state that the vehicle can reach after a preset time, such as the expected tracking state that the vehicle can reach at time T from the current time. The preset time can be obtained according to actual needs, and this embodiment does not impose any restrictions on it.

[0105] Step S502: Obtain the target control parameters based on the desired tracking state and the reference control parameters.

[0106] In the specific implementation, after determining the desired tracking state that the vehicle can reach at a preset time, the tracking reference control parameters corresponding to the desired tracking state can be queried based on this desired tracking state. This is determined by the preset desired trajectory and can be set in advance. Then, the state ratio coefficient between the vehicle's current state and the desired tracking state is obtained. This state ratio coefficient can also be set in advance according to actual needs. Finally, the obtained state ratio coefficient is substituted into the following formula to calculate the target control parameter: U_des=α*Uo_des+(1-α)*Ut_des, where α is the state ratio coefficient, Uo_des is the reference control parameter, Ut_des is the tracking reference control parameter, and U_des is the target control parameter.

[0107] Step S503: Control the vehicle to drift along the desired trajectory according to the target control parameters.

[0108] It is easy to understand that after determining the target control parameters, this embodiment controls the vehicle according to the steering wheel angle and rear wheel drive force included in the target control parameters, so that the vehicle can drift along the desired trajectory.

[0109] This embodiment queries the desired tracking state that the vehicle can reach after a preset time; determines the tracking reference control parameters corresponding to the preset time based on the desired tracking state; obtains the state ratio coefficient between the current state of the vehicle and the desired tracking state; calculates the target control parameters based on the state ratio coefficient, the reference control parameters, and the tracking reference control parameters; and controls the vehicle to drift along the desired trajectory according to the target control parameters. Through the above method, more accurate target control parameters can be obtained, further improving the control accuracy of vehicle drifting.

[0110] Furthermore, this embodiment of the invention also proposes a storage medium storing a vehicle drift trajectory control program, which, when executed by a processor, implements the steps of the vehicle drift trajectory control method described above.

[0111] Since this storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be repeated here.

[0112] Reference Figure 14 , Figure 14 This is a structural block diagram of the first embodiment of the vehicle drift trajectory control device of the present invention.

[0113] like Figure 14 As shown, the vehicle drift trajectory control device proposed in this embodiment of the invention includes:

[0114] The calculation module 10 is used to determine the target state parameters based on the expected trajectory corresponding to the vehicle.

[0115] The acquisition module 20 is used to acquire the current status parameters of the vehicle.

[0116] The calculation module 10 is also used to determine the parameter difference between the current state parameter and the target state parameter.

[0117] The calculation module 10 is also used to calculate reference control parameters based on the parameter difference and the vehicle tracking error model.

[0118] The control module 30 is used to control the vehicle to drift along the desired trajectory according to the reference control parameters.

[0119] This embodiment determines target state parameters based on the desired trajectory corresponding to the vehicle; obtains the current state parameters of the vehicle; determines the parameter difference between the current state parameters and the target state parameters; calculates reference control parameters based on the parameter difference and the vehicle tracking error model; and controls the vehicle to drift according to the desired trajectory based on the reference control parameters. By calculating the target control parameters using the current state parameters of the vehicle and the target state parameters corresponding to the desired trajectory, and then controlling the vehicle to drift according to the desired trajectory using the target control parameters, this method eliminates the need to calibrate vehicle physical parameters and does not rely on empirical dynamic models. It directly calibrates the control parameters, thereby improving the accuracy of vehicle drift trajectory control.

[0120] In one embodiment, the vehicle drift trajectory control device further includes: a construction module;

[0121] The construction module is used to construct the vehicle state error model corresponding to the vehicle;

[0122] The control module 30 is also used to adjust the vehicle to a steady-state drift state according to the vehicle state error model;

[0123] The calculation module 10 is further configured to perform the step of determining the target state parameters based on the desired trajectory corresponding to the vehicle when the vehicle is in the steady-state drift state.

[0124] In one embodiment, the construction module is further configured to obtain the historical steady-state state parameters and historical steady-state control parameters of the vehicle; determine model parameters based on the historical steady-state state parameters and historical steady-state control parameters; and construct a vehicle state error model corresponding to the vehicle based on the model parameters.

[0125] In one embodiment, the vehicle drift trajectory control device further includes: a judgment module;

[0126] The judgment module is used to obtain the current position of the vehicle; determine the trajectory point on the expected trajectory that is closest to the vehicle based on the current position; and determine the state parameter difference between the vehicle and the trajectory point.

[0127] The calculation module 10 is further configured to perform the step of determining the target state parameters based on the expected trajectory corresponding to the vehicle when the state parameter difference is within a preset range.

[0128] In one embodiment, the construction module is further configured to construct a tracking reference line corresponding to the vehicle; determine the error between the vehicle and the desired trajectory based on the tracking reference line; and construct a vehicle tracking error model based on the error.

[0129] In one embodiment, the control module 30 is further configured to query the desired tracking state that the vehicle can reach after a preset time; obtain target control parameters based on the desired tracking state and the reference control parameters; and control the vehicle to drift along the desired trajectory according to the target control parameters.

[0130] In one embodiment, the control module 30 is further configured to determine the tracking reference control parameters corresponding to the preset time based on the desired tracking state; obtain the state ratio coefficient between the current state of the vehicle and the desired tracking state; and calculate the target control parameters based on the state ratio coefficient, the reference control parameters, and the tracking reference control parameters.

[0131] It should be understood that the above are merely illustrative examples and do not constitute any limitation on the technical solutions of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any restrictions on this.

[0132] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0133] In addition, for technical details not described in detail in this embodiment, please refer to the vehicle drift trajectory control method provided in any embodiment of the present invention, which will not be repeated here.

[0134] Furthermore, it should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system 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 system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0135] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0136] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0137] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for controlling vehicle drift trajectory, characterized in that, The vehicle drift trajectory control method includes: Determine the target state parameters based on the desired trajectory corresponding to the vehicle; Obtain the current status parameters of the vehicle; Determine the parameter difference between the current state parameter and the target state parameter; Calculate reference control parameters based on the parameter differences and the vehicle tracking error model; The vehicle is controlled to drift along the desired trajectory based on the reference control parameters. Before determining the target state parameters based on the desired trajectory corresponding to the vehicle, the process also includes: Construct a vehicle state error model corresponding to the vehicle; The vehicle is adjusted to a steady-state drift state based on the vehicle state error model. When the vehicle is in the steady-state drift state, the step of determining the target state parameters based on the desired trajectory corresponding to the vehicle is performed.

2. The vehicle drift trajectory control method as described in claim 1, characterized in that, The construction of the vehicle state error model corresponding to the vehicle includes: Obtain the historical steady-state parameters and historical steady-state control parameters of the vehicle; The model parameters are determined based on the historical steady-state parameters and historical steady-state control parameters. The vehicle state error model corresponding to the vehicle is constructed based on the model parameters.

3. The vehicle drift trajectory control method as described in claim 1, characterized in that, Before performing the step of determining the target state parameters based on the desired trajectory corresponding to the vehicle, the method further includes: Get the vehicle's current location; Determine the trajectory point closest to the vehicle on the desired trajectory based on the current location; Determine the difference in state parameters between the vehicle and the trajectory point; When the difference in the state parameters is within a preset range, the step of determining the target state parameters based on the desired trajectory corresponding to the vehicle is executed.

4. The vehicle drift trajectory control method as described in claim 1, characterized in that, Before calculating the reference control parameters based on the parameter difference and the vehicle tracking error model, the method further includes: Construct a tracking reference line for the vehicle; The error between the vehicle and the desired trajectory is determined based on the tracking reference line; A vehicle tracking error model is constructed based on the aforementioned error.

5. The vehicle drift trajectory control method as described in any one of claims 1 to 4, characterized in that, The reference control parameters are the control parameters corresponding to the vehicle at the current moment. Controlling the vehicle to drift according to the desired trajectory based on the reference control parameters includes: Query the desired tracking state that the vehicle can achieve after a preset time. The target control parameters are obtained based on the desired tracking state and the reference control parameters; The vehicle is controlled to drift along the desired trajectory according to the target control parameters.

6. The vehicle drift trajectory control method as described in claim 5, characterized in that, The step of obtaining the target control parameters based on the desired tracking state and the reference control parameters includes: Determine the tracking reference control parameters corresponding to the preset time based on the desired tracking state; Obtain the state ratio coefficient between the current state of the vehicle and the desired tracking state; The target control parameters are calculated based on the state proportional coefficient, the reference control parameters, and the tracking reference control parameters.

7. A vehicle drift trajectory control device, characterized in that, The vehicle drift trajectory control device includes: The calculation module is used to determine the target state parameters based on the desired trajectory corresponding to the vehicle. The acquisition module is used to acquire the current status parameters of the vehicle; The calculation module is also used to determine the parameter difference between the current state parameter and the target state parameter; The calculation module is also used to calculate reference control parameters based on the parameter difference and the vehicle tracking error model; The control module is used to control the vehicle to drift along the desired trajectory according to the reference control parameters. The vehicle drift trajectory control device further includes: a construction module; the construction module is used to construct a vehicle state error model corresponding to the vehicle; adjust the vehicle to a steady-state drift state according to the vehicle state error model; and when the vehicle is in the steady-state drift state, execute the step of determining the target state parameters based on the desired trajectory corresponding to the vehicle.

8. A vehicle drift trajectory control device, characterized in that, The vehicle drift trajectory control device includes: a memory, a processor, and a vehicle drift trajectory control program stored in the memory and running on the processor, the vehicle drift trajectory control program being configured to implement the vehicle drift trajectory control method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores a vehicle drift trajectory control program, which, when executed by a processor, implements the vehicle drift trajectory control method as described in any one of claims 1 to 6.

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