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 obtains a state deviation between a vehicle and a target track point on an expected track; when the state deviation exceeds a preset range, the state of the vehicle is pre-adjusted according to control parameters obtained by substituting a state parameter difference value between the vehicle and the target track point into a vehicle state error model and a target transition track; a parameter difference value between current state parameters of the pre-adjusted vehicle and target state parameters determined based on the expected track; reference control parameters are calculated according to the parameter difference value and a vehicle tracking error model; and the vehicle is controlled to drift along the expected track according to the reference control parameters. In the above manner, when the state of the vehicle deviates greatly from the track matching point state, the vehicle is first transitioned to an equilibrium state, and then the vehicle is controlled according to the expected track, thereby improving the precision of vehicle drift track control.

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] Current control methods used in autonomous driving tracking are mainly aimed at vehicle steady-state control. The vehicle state is similar to the Ackerman model, which makes control relatively easy. In the process of vehicle tracking and drifting, it is generally assumed that the vehicle state is near the drift steady-state equilibrium point. However, the problem is that when the vehicle deviates far from the tracking matching point, it is difficult for the vehicle to converge to the desired steady state, and the accuracy of vehicle drift trajectory control cannot be guaranteed.

[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 accuracy of vehicle drift trajectory control cannot be guaranteed in the prior art.

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

[0008] Obtain the state deviation between the vehicle and the target trajectory point on the desired trajectory;

[0009] When the state deviation exceeds the preset range, the state parameter difference between the vehicle and the target trajectory point is substituted into the vehicle state error model to calculate the control parameters, and the state of the vehicle is pre-adjusted according to the target transition trajectory based on the control parameters.

[0010] Obtain the current state parameters of the pre-adjusted vehicle, and determine the target state parameters based on the desired trajectory;

[0011] Determine the parameter difference between the current state parameter and the target state parameter;

[0012] Calculate reference control parameters based on the parameter differences and the vehicle tracking error model;

[0013] The vehicle is controlled to drift along the desired trajectory based on the reference control parameters.

[0014] Optionally, before pre-adjusting the vehicle's state according to the target transition trajectory, the method further includes:

[0015] Obtain the current speed of the vehicle;

[0016] The predicted travel distance of the vehicle is obtained based on the vehicle speed and the preset forward look-ahead time;

[0017] The predicted position of the vehicle is determined based on the predicted movement distance;

[0018] Determine the forward matching point based on the predicted location;

[0019] The errors between the vehicle and the forward-looking matching point and the target trajectory point are obtained respectively;

[0020] The target transition trajectory is determined based on the error and the predicted movement distance.

[0021] Optionally, the error includes at least the lateral error between the vehicle and the target trajectory point, the velocity-angle error between the vehicle and the target trajectory point, the lateral error between the vehicle and the forward-looking matching point, and the velocity-angle error between the vehicle and the forward-looking matching point. Determining the target transition trajectory based on the error and the predicted travel distance includes:

[0022] The curvature increment is calculated based on the lateral error between the vehicle and the target trajectory point, the velocity-angle error between the vehicle and the target trajectory point, the lateral error between the vehicle and the forward-looking matching point, and the velocity-angle error between the vehicle and the forward-looking matching point, as well as their respective error weights. The error weights corresponding to the lateral error between the vehicle and the forward-looking matching point and the velocity-angle error between the vehicle and the forward-looking matching point are determined by the predicted movement distance.

[0023] The target curvature is determined based on the reference curvature corresponding to the target trajectory point and the curvature increment;

[0024] The trajectory radius is determined based on the target curvature, and the target transition trajectory is determined based on the trajectory radius.

[0025] Optionally, the pre-adjustment of the vehicle's state according to the target transition trajectory includes:

[0026] Determine the forward-looking matching point corresponding to the target transition trajectory;

[0027] The minimum adjustment amount required for state adjustment is calculated based on the yaw rate of the forward matching point and the yaw rate of the target trajectory point.

[0028] The target yaw rate is determined based on the vehicle's current yaw rate and the minimum adjustment amount;

[0029] The vehicle's state is pre-adjusted based on the target yaw rate.

[0030] Optionally, obtaining the state deviation between the vehicle and the target trajectory point on the desired trajectory includes:

[0031] Get the vehicle's current location;

[0032] Based on the current location, determine the target trajectory point on the desired trajectory that is closest to the vehicle;

[0033] Calculate the state parameter difference between the vehicle and the trajectory point, and use the state parameter difference as the state deviation.

[0034] Optionally, before obtaining the state deviation between the vehicle and the target trajectory point on the desired trajectory, the method further includes:

[0035] Construct a vehicle state error model corresponding to the vehicle;

[0036] The vehicle is adjusted to a steady-state drift state based on the vehicle state error model.

[0037] When the vehicle is in the steady-state drift state, the step of obtaining the state deviation between the vehicle and the target trajectory point on the desired trajectory is performed.

[0038] Optionally, controlling the vehicle to drift according to the desired trajectory based on the reference control parameters includes:

[0039] Query the desired tracking state that the vehicle can achieve after a preset time.

[0040] Determine the tracking reference control parameters corresponding to the preset time based on the desired tracking state;

[0041] Obtain the state ratio coefficient between the current state of the vehicle and the desired tracking state;

[0042] Calculate the target control parameters based on the state proportional coefficient, the reference control parameters, and the tracking reference control parameters;

[0043] The vehicle is controlled to drift along the desired trajectory according to the target control parameters.

[0044] Furthermore, to achieve the above objectives, the present invention also proposes a vehicle drift trajectory control device, the vehicle drift trajectory control device comprising:

[0045] The acquisition module is used to acquire the state deviation between the vehicle and the target trajectory point on the desired trajectory.

[0046] The control module is used to calculate control parameters by substituting the difference in state parameters between the vehicle and the target trajectory point into the vehicle state error model when the state deviation exceeds a preset range, and to pre-adjust the state of the vehicle according to the target transition trajectory based on the control parameters.

[0047] The calculation module is used to obtain the current state parameters of the pre-adjusted vehicle and determine the target state parameters based on the desired trajectory;

[0048] The calculation module is also used to determine the parameter difference between the current state parameter and the target state parameter;

[0049] The calculation module is also used to calculate reference control parameters based on the parameter difference and the vehicle tracking error model;

[0050] The control module is also used to control the vehicle to drift along the desired trajectory according to the reference control parameters.

[0051] 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.

[0052] 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.

[0053] This invention obtains the state deviation between the vehicle and the target trajectory point on the desired trajectory; when the state deviation exceeds a preset range, the vehicle's state is pre-adjusted by substituting the state parameter difference between the vehicle and the target trajectory point into the control parameters calculated by the vehicle state error model and the target transition trajectory; based on the parameter difference between the current state parameters of the pre-adjusted vehicle and the target state parameters determined based on the desired trajectory; reference control parameters are calculated based on the parameter difference and the vehicle tracking error model; and the vehicle is controlled to drift along the desired trajectory based on the reference control parameters. This method improves the accuracy of vehicle drift trajectory control by first transitioning the vehicle to a balanced state when its state deviates significantly from the trajectory matching point, and then controlling the vehicle according to the desired trajectory. Attached Figure Description

[0054] 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;

[0055] Figure 2 This is a flowchart illustrating the first embodiment of the vehicle drift trajectory control method of the present invention;

[0056] 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;

[0057] 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;

[0058] 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;

[0059] 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;

[0060] 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;

[0061] Figure 8 This is a schematic diagram of tracking error in one embodiment of the vehicle drift trajectory control method of the present invention;

[0062] Figure 9 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;

[0063] Figure 10 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;

[0064] Figure 11 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;

[0065] Figure 12 This is a flowchart illustrating the second embodiment of the vehicle drift trajectory control method of the present invention;

[0066] Figure 13 This is a schematic diagram of the transition trajectory in one embodiment of the vehicle drift trajectory control method of the present invention;

[0067] Figure 14 This is a flowchart illustrating the third embodiment of the vehicle drift trajectory control method of the present invention;

[0068] Figure 15 This is a structural block diagram of the first embodiment of the vehicle drift trajectory control device of the present invention.

[0069] 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

[0070] 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.

[0071] 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.

[0072] 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.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] 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.

[0077] In this embodiment, the vehicle drift trajectory control method includes the following steps:

[0078] Step S10: Obtain the state deviation between the vehicle and the target trajectory point on the desired trajectory.

[0079] 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.

[0080] It should be noted that the current control methods used for autonomous driving tracking are mainly aimed at vehicle steady-state control. The vehicle state is similar to the Ackerman model, which makes the control relatively easy. In addition, during the vehicle tracking drift, it is generally assumed that the vehicle state is near the drift steady-state equilibrium point. However, the problem is that when the vehicle deviates far from the tracking matching point, it is difficult for the vehicle to converge to the desired steady state, and the accuracy of the vehicle drift trajectory control cannot be guaranteed.

[0081] In this embodiment, to solve the aforementioned technical problem, the state deviation between the vehicle and the target trajectory point on the desired trajectory is obtained; when the state deviation exceeds a preset range, the vehicle's state is pre-adjusted according to the target transition trajectory; the current state parameters of the pre-adjusted vehicle are obtained, and the target state parameters are determined based on the desired trajectory; 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. This method allows the vehicle to transition to a balanced state before being controlled according to the desired trajectory when its state deviates significantly from the trajectory matching point, thus improving the accuracy of vehicle drift trajectory control. Specifically, this can be implemented as follows.

[0082] In this specific implementation, the state deviation between the vehicle and the target trajectory point on the desired trajectory can be obtained. This state deviation can be the difference in state parameters between the vehicle and the target trajectory point. This 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. The target trajectory point can be the closest trajectory point to the vehicle on the desired trajectory, based on the vehicle's current position.

[0083] Furthermore, before performing the above operations, this embodiment needs to first control the vehicle to a steady-state drift state. Controlling the vehicle to a steady-state drift state can be achieved using a vehicle state error model. Since this embodiment does not rely on an empirical dynamics model, 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, the center of mass velocity, sideslip angle, yaw rate, and longitudinal axis velocity. When the vehicle enters a drift equilibrium state, it is a three-degree-of-freedom model. Specifying different drift directions simplifies it to a two-degree-of-freedom model, that is, specifying two linearly independent dynamic parameters determines 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.

[0084] 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.

[0085] by Figure 3 Based on a simplified model, the specific construction process of the vehicle state error model in this embodiment 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, and records the drift parameters. The flowchart of the open-loop drift initiation model is as follows: Figure 4As 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.

[0086] Step S20: When the state deviation exceeds the preset range, substitute the state parameter difference between the vehicle and the target trajectory point into the vehicle state error model to calculate the control parameters, and pre-adjust the state of the vehicle according to the target transition trajectory based on the control parameters.

[0087] It should be noted that when the detected state deviation between the vehicle and the target trajectory point on the desired trajectory exceeds a preset range, directly controlling the vehicle's drift trajectory at this time is difficult, making it hard to keep the vehicle on the drift equilibrium surface and greatly reducing control accuracy. In this situation, the approach adopted in this embodiment is to find a target transition trajectory that satisfies the drift equilibrium state, allowing the vehicle to transition along the target transition trajectory before controlling the vehicle according to the desired trajectory. The control parameters required for controlling the vehicle to transition along the target transition trajectory can be calculated based on the state parameter difference between the vehicle and the target trajectory point. Specifically, after obtaining the state parameter difference between the vehicle and the target trajectory point, this state parameter difference is substituted into the vehicle state error model to calculate the control parameters. Controlling the vehicle according to these control parameters ensures that the vehicle remains in a drift equilibrium state after the transition. The parameter value range corresponding to the preset range can be set according to control requirements. Furthermore, the target transition trajectory in this embodiment can be set as a circular arc trajectory, although other types of trajectories can also be selected; this embodiment does not impose any restrictions on these options.

[0088] In practical implementation, the vehicle's state can be pre-adjusted using the target transition trajectory in this embodiment. Pre-adjustments can include adjusting the vehicle's yaw rate, and the specific adjustment method can be selected according to the actual situation.

[0089] Step S30: Obtain the current state parameters of the pre-adjusted vehicle, and determine the target state parameters based on the desired trajectory.

[0090] In practical implementation, if the state deviation between the pre-adjusted vehicle and the target trajectory point on the desired trajectory is within a preset range, the vehicle can be considered to have reached a drift equilibrium state and is near a steady-state point. In this case, subsequent drift trajectory control can be performed on the vehicle in this embodiment. When performing drift trajectory control on the vehicle, it is necessary to first obtain the current state parameters of the pre-adjusted vehicle and the target state parameters determined based on the desired trajectory. The target state parameters can be the state parameter values ​​of the target trajectory point on the desired trajectory.

[0091] Step S40: Determine the parameter difference between the current state parameter and the target state parameter.

[0092] In specific implementation, after obtaining the above state parameters, this embodiment further needs to calculate the parameter difference between the current state parameters and the target state parameters. For example, if the yaw rate and the center of mass velocity and the sideslip angle in the current state parameters and the preset state parameters have not changed, the only difference between the current state of the vehicle and the target trajectory point is the longitudinal axis velocity of the vehicle. Assuming that the current longitudinal axis velocity of the vehicle is 11 m / s and the longitudinal axis velocity of the target trajectory point is 10 m / s, the parameter difference at this time can be calculated to be 1 m / s.

[0093] Step S50: Calculate the reference control parameters based on the parameter difference and the vehicle tracking error model.

[0094] 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.

[0095] 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.

[0096] Furthermore, in this embodiment, before constructing the vehicle tracking error model, it is necessary to first construct the tracking reference line corresponding to the vehicle, such as... Figure 8 L1 is shown.

[0097] 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),

[0098] V_dot = Ux_dot / cos(β).

[0099] 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.

[0100]

[0101]

[0102] 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.

[0103] 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 9-11 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 9-11 Find the corresponding status parameters and control parameters in the database.

[0104] Step S60: Control the vehicle to drift along the desired trajectory according to the reference control parameters.

[0105] In practice, 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.

[0106] Furthermore, to improve the control accuracy of the vehicle's trajectory during drifting, this embodiment also needs to query the desired tracking state that the vehicle can reach after a preset time. For example, the desired 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. After determining the desired tracking state that the vehicle can reach at the preset time, the tracking reference control parameters corresponding to the desired tracking state can be queried based on the 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. After determining the target control parameters, in this embodiment, the vehicle is controlled 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.

[0107] This embodiment obtains the state deviation between the vehicle and the target trajectory point on the desired trajectory; when the state deviation exceeds a preset range, the vehicle's state is pre-adjusted by substituting the state parameter difference between the vehicle and the target trajectory point into the control parameters calculated by the vehicle state error model and the target transition trajectory; based on the parameter difference between the current state parameters of the vehicle after pre-adjustment and the target state parameters determined based on the desired trajectory; 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. In this way, when the vehicle's state deviates significantly from the trajectory matching point, the vehicle can first be transitioned to a balanced state, and then the vehicle can be controlled according to the desired trajectory, thus improving the accuracy of vehicle drift trajectory control.

[0108] refer to Figure 12 , Figure 12 This is a flowchart illustrating a second embodiment of a vehicle drift trajectory control method according to the present invention.

[0109] Based on the first embodiment described above, the vehicle drift trajectory control method of this embodiment further includes the following steps before step S20:

[0110] Step S020: Obtain the current speed of the vehicle.

[0111] Step S120: Obtain the predicted travel distance of the vehicle based on the vehicle speed and the preset forward look-ahead time.

[0112] In this embodiment, before pre-adjusting the vehicle to transition it to a drift equilibrium state, a corresponding target transition trajectory needs to be constructed. Specifically, when constructing the target transition trajectory, the vehicle's current speed needs to be obtained first. Based on the current speed and a preset forward look-ahead time, the predicted movement distance of the vehicle can be calculated, that is, the distance the vehicle can move at the current speed and the preset forward look-ahead time. The preset forward look-ahead time can be set according to actual needs, and this embodiment does not impose any restrictions on it.

[0113] Step S220: Determine the predicted position of the vehicle based on the predicted movement distance.

[0114] Step S320: Determine the forward matching point based on the predicted position.

[0115] In practical implementation, after calculating the predicted movement distance, this embodiment can also determine the predicted position of the vehicle based on the movement distance. This predicted position corresponds to a trajectory point on the desired trajectory that can be used to find a forward-looking matching point. (Refer to...) Figure 13 As shown. Figure 13 In this diagram, A represents the target trajectory point, B represents the forward-looking matching point, K represents the curvature, and R represents the trajectory radius.

[0116] Step S420: Obtain the errors between the vehicle and the forward-looking matching point and the target trajectory point, respectively.

[0117] In specific implementation, after determining the forward-looking matching point, this embodiment will further obtain the error between the vehicle and the forward-looking matching point, as well as the error between the vehicle and the target trajectory point. The error between the vehicle and the forward-looking matching point includes at least the lateral error between the vehicle and the forward-looking matching point and the velocity angle error between the vehicle and the forward-looking matching point. The error between the vehicle and the target trajectory point includes at least the lateral error between the vehicle and the target trajectory point and the velocity angle error between the vehicle and the target trajectory point.

[0118] Step S520: Determine the target transition trajectory based on the error and the predicted movement distance.

[0119] In practical implementation, after determining the errors, this embodiment also sets corresponding weights for each error. Specifically, the error weights corresponding to the lateral error between the vehicle and the target trajectory point, and the velocity-angle error between the vehicle and the target trajectory point, can be preset according to actual needs. Furthermore, considering the influence of the forward-looking point error, the weight of the forward-looking point error is increased based on the distance from the current position to the forward-looking point (i.e., the predicted movement distance). The greater the distance, the smaller the error impact, thereby ensuring a smooth transition for the vehicle. Therefore, in this embodiment, the lateral error between the vehicle and the forward-looking matching point, and the velocity-angle error between the vehicle and the forward-looking matching point, are based on preset error weights combined with the predicted movement distance.

[0120] The curvature increment can be calculated using the above parameters. The specific calculation formula is as follows: delta_kappa=w1*(-1)*e+w2*(-1)*v_heading_error+w3*(-1)*e_ahead / travelling_distance+w4*(-1)*v_heading_error_ahead / travelling_distance, where delta_kappa is the curvature increment, e is the lateral error between the vehicle and the target trajectory point with a preset error weight of w1, v_heading_error is the velocity-angle error between the vehicle and the target trajectory point with a preset error weight of w2, e_ahead is the lateral error between the vehicle and the forward-looking matching point with a preset error weight of w3, v_heading_error_ahead is the velocity-angle error between the vehicle and the forward-looking matching point with a preset error weight of w4, and traveling_distance is the predicted travel distance.

[0121] Furthermore, the target curvature can be determined based on the reference curvature and curvature increment corresponding to the target trajectory point. For example, kappa_des = kappa_ref + delta_kappa, where delta_kappa is the curvature increment, kappa_ref is the reference curvature corresponding to the target trajectory point, and kappa_des is the target curvature. Finally, the trajectory radius can be calculated based on the target curvature. For example, radius_ref = 1 / (kappa_des), and radius_ref is the trajectory radius.

[0122] Furthermore, when the lateral error of the vehicle is considered to be greater than 0 (i.e.) Figure 13In the case where e > 0, if the vehicle is inside the reference line, the curvature should be reduced to increase the turning radius and thus get closer to the trajectory. Similarly, when the error between the vehicle's speed and the reference trajectory is greater than zero, meaning the vehicle's direction tends to quickly approach the trajectory, the curvature should be reduced and the turning radius increased to allow for a smooth transition.

[0123] This embodiment obtains the vehicle's current speed; calculates the predicted movement distance of the vehicle based on the speed and a preset forward look time; determines the predicted position of the vehicle based on the predicted movement distance; determines a forward look matching point based on the predicted position; obtains the errors between the vehicle and the forward look matching point and the target trajectory point respectively; calculates the curvature increment based on the lateral error between the vehicle and the target trajectory point, the velocity angle error between the vehicle and the target trajectory point, the lateral error between the vehicle and the forward look matching point, and the velocity angle error between the vehicle and the forward look matching point, and their respective error weights; determines the target curvature based on the reference curvature corresponding to the target trajectory point and the curvature increment; determines the trajectory radius based on the target curvature, and determines the target transition trajectory based on the trajectory radius. Through this method, the vehicle can effectively transition to a drift equilibrium state, improving the control effect and further ensuring the accuracy of vehicle drift trajectory control.

[0124] refer to Figure 14 , Figure 14 This is a flowchart illustrating a third embodiment of a vehicle drift trajectory control method according to the present invention.

[0125] Based on the first embodiment described above, a third embodiment of the vehicle drift trajectory control method of the present invention is proposed.

[0126] In this embodiment, step S20 specifically includes:

[0127] Step S201: Determine the forward matching point corresponding to the target transition trajectory.

[0128] It is easy to understand that the construction of the target transition trajectory requires the use of the target trajectory points and the forward matching points. Therefore, after the construction of the target transition trajectory is completed, the corresponding forward matching points can be found based on the target transition trajectory in this embodiment.

[0129] Step S202: Calculate the minimum adjustment amount required for state adjustment based on the yaw rate of the forward matching point and the yaw rate of the target trajectory point.

[0130] In specific implementation, after determining the forward-looking matching point, this embodiment will obtain the yaw rate of the forward-looking matching point and the yaw rate of the target trajectory point. The minimum adjustment amount required for state adjustment can be calculated according to the calculation formula, for example, min_yawrate=(yawrate_ref+yawrate_ahead) / 2, where yawrate_ref is the yaw rate of the target trajectory point, yawrate_ahead is the yaw rate of the forward-looking matching point, and min_yawrate is the minimum adjustment amount required for state adjustment.

[0131] Step S203: Determine the target yaw rate based on the vehicle's current yaw rate and the minimum adjustment amount.

[0132] In practice, after obtaining the minimum adjustment amount, the target yaw rate can be calculated by combining the vehicle's current yaw rate, such as yawrate_des = w5 * yawrate + (1 - w5) * min_yawrate, where yawrate is the vehicle's current yaw rate, min_yawrate is the minimum adjustment amount, yawrate_des is the target yaw rate, and w5 is the adjustment coefficient, which can be set according to actual needs. This embodiment does not impose any restrictions on this.

[0133] Step S204: Pre-adjust the state of the vehicle according to the target yaw rate.

[0134] It is easy to understand that by adjusting the vehicle's current yaw rate to the target yaw rate, the vehicle can achieve a drift balance state, which facilitates subsequent drift trajectory control.

[0135] This embodiment determines the forward-looking matching point corresponding to the target transition trajectory; calculates the minimum adjustment amount required for state adjustment based on the yaw rate of the forward-looking matching point and the yaw rate of the target trajectory point; determines the target yaw rate based on the vehicle's current yaw rate and the minimum adjustment amount; and pre-adjusts the vehicle's state based on the target yaw rate. Through the above method, the vehicle can be effectively transitioned to a drift balance state, improving the control effect and further ensuring the accuracy of vehicle drift trajectory control.

[0136] 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.

[0137] 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.

[0138] Reference Figure 15 , Figure 15 This is a structural block diagram of the first embodiment of the vehicle drift trajectory control device of the present invention.

[0139] like Figure 15 As shown, the vehicle drift trajectory control device proposed in this embodiment of the invention includes:

[0140] The acquisition module 10 is used to acquire the state deviation between the vehicle and the target trajectory point on the desired trajectory.

[0141] The control module 20 is used to calculate control parameters by substituting the difference in state parameters between the vehicle and the target trajectory point into the vehicle state error model when the state deviation exceeds a preset range, and to pre-adjust the state of the vehicle according to the target transition trajectory based on the control parameters.

[0142] The calculation module 30 is used to obtain the current state parameters of the pre-adjusted vehicle and determine the target state parameters based on the desired trajectory.

[0143] The calculation module 30 is also used to determine the parameter difference between the current state parameter and the target state parameter.

[0144] The calculation module 30 is also used to calculate reference control parameters based on the parameter difference and the vehicle tracking error model.

[0145] The control module 20 is also used to control the vehicle to drift along the desired trajectory according to the reference control parameters.

[0146] This embodiment obtains the state deviation between the vehicle and the target trajectory point on the desired trajectory; when the state deviation exceeds a preset range, the vehicle's state is pre-adjusted by substituting the state parameter difference between the vehicle and the target trajectory point into the control parameters calculated by the vehicle state error model and the target transition trajectory; based on the parameter difference between the current state parameters of the vehicle after pre-adjustment and the target state parameters determined based on the desired trajectory; 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. In this way, when the vehicle's state deviates significantly from the trajectory matching point, the vehicle can first be transitioned to a balanced state, and then the vehicle can be controlled according to the desired trajectory, thus improving the accuracy of vehicle drift trajectory control.

[0147] In one embodiment, the vehicle drift trajectory control device further includes: a construction module;

[0148] The construction module is used to obtain the current speed of the vehicle; obtain the predicted moving distance of the vehicle based on the vehicle speed and a preset forward look time; determine the predicted position of the vehicle based on the predicted moving distance; determine the forward look matching point based on the predicted position; obtain the error between the vehicle and the forward look matching point and the target trajectory point respectively; and determine the target transition trajectory based on the error and the predicted moving distance.

[0149] In one embodiment, the error includes at least the lateral error between the vehicle and the target trajectory point, the velocity-angle error between the vehicle and the target trajectory point, the lateral error between the vehicle and the forward-looking matching point, and the velocity-angle error between the vehicle and the forward-looking matching point;

[0150] The construction module is further configured to calculate curvature increment based on the lateral error between the vehicle and the target trajectory point, the velocity-angle error between the vehicle and the target trajectory point, the lateral error between the vehicle and the forward-looking matching point, and the velocity-angle error between the vehicle and the forward-looking matching point, and their respective error weights. The error weights corresponding to the lateral error between the vehicle and the forward-looking matching point and the velocity-angle error between the vehicle and the forward-looking matching point are affected by the predicted movement distance. The module also determines the target curvature based on the reference curvature corresponding to the target trajectory point and the curvature increment; determines the trajectory radius based on the target curvature; and determines the target transition trajectory based on the trajectory radius.

[0151] In one embodiment, the control module 20 is further configured to: determine the forward matching point corresponding to the target transition trajectory; calculate the minimum adjustment amount required for state adjustment based on the yaw rate of the forward matching point and the yaw rate of the target trajectory point; determine the target yaw rate based on the current yaw rate of the vehicle and the minimum adjustment amount; and pre-adjust the state of the vehicle based on the target yaw rate.

[0152] In one embodiment, the acquisition module 10 is further configured to acquire the current position of the vehicle; determine the target trajectory point closest to the vehicle on the desired trajectory based on the current position; calculate the state parameter difference between the vehicle and the trajectory point, and use the state parameter difference as a state deviation.

[0153] In one embodiment, the construction module is further configured to construct a vehicle state error model corresponding to the vehicle;

[0154] The control module 20 is also used to adjust the vehicle to a steady-state drift state according to the vehicle state error model;

[0155] The acquisition 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 vehicle is in the steady-state drift state.

[0156] In one embodiment, the control module 20 is further configured to query the desired tracking state that the vehicle can reach after a preset time; 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; calculate the target control parameters based on the state ratio coefficient, the reference control parameters, and the tracking reference control parameters; and control the vehicle to drift according to the desired trajectory according to the target control parameters.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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: Obtain the state deviation between the vehicle and the target trajectory point on the desired trajectory; When the state deviation exceeds the preset range, the state parameter difference between the vehicle and the target trajectory point is substituted into the vehicle state error model to calculate the control parameters, and the state of the vehicle is pre-adjusted according to the target transition trajectory based on the control parameters. The target transition trajectory is the trajectory that makes the vehicle meet the drift equilibrium state. Obtain the current state parameters of the pre-adjusted vehicle, and determine the target state parameters based on the desired trajectory; 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 pre-adjusting the vehicle's state according to the target transition trajectory, the method further includes: Obtain the current speed of the vehicle; The predicted travel distance of the vehicle is obtained based on the vehicle speed and the preset forward look-ahead time; The predicted position of the vehicle is determined based on the predicted movement distance; Determine the forward matching point based on the predicted location; The errors between the vehicle and the forward-looking matching point and the target trajectory point are obtained respectively; The target transition trajectory is determined based on the error and the predicted movement distance.

2. The vehicle drift trajectory control method as described in claim 1, characterized in that, The error includes at least the lateral error between the vehicle and the target trajectory point, the velocity-angle error between the vehicle and the target trajectory point, the lateral error between the vehicle and the forward-looking matching point, and the velocity-angle error between the vehicle and the forward-looking matching point. Determining the target transition trajectory based on the error and the predicted travel distance includes: The curvature increment is calculated based on the lateral error between the vehicle and the target trajectory point, the velocity-angle error between the vehicle and the target trajectory point, the lateral error between the vehicle and the forward-looking matching point, and the velocity-angle error between the vehicle and the forward-looking matching point, as well as their respective error weights. The error weights corresponding to the lateral error between the vehicle and the forward-looking matching point and the velocity-angle error between the vehicle and the forward-looking matching point are affected by the predicted travel distance. The target curvature is determined based on the reference curvature corresponding to the target trajectory point and the curvature increment; The trajectory radius is determined based on the target curvature, and the target transition trajectory is determined based on the trajectory radius.

3. The vehicle drift trajectory control method as described in claim 1, characterized in that, The pre-adjustment of the vehicle's state according to the target transition trajectory includes: Determine the forward-looking matching point corresponding to the target transition trajectory; The minimum adjustment amount required for state adjustment is calculated based on the yaw rate of the forward matching point and the yaw rate of the target trajectory point. The target yaw rate is determined based on the vehicle's current yaw rate and the minimum adjustment amount; The vehicle's state is pre-adjusted based on the target yaw rate.

4. The vehicle drift trajectory control method as described in claim 1, characterized in that, The acquisition of the state deviation between the vehicle and the target trajectory point on the desired trajectory includes: Get the vehicle's current location; Based on the current location, determine the target trajectory point on the desired trajectory that is closest to the vehicle; Calculate the state parameter difference between the vehicle and the trajectory point, and use the state parameter difference as the state deviation.

5. The vehicle drift trajectory control method as described in claim 1, characterized in that, Before obtaining the state deviation between the vehicle and the target trajectory point on the desired trajectory, the method further 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 obtaining the state deviation between the vehicle and the target trajectory point on the desired trajectory is performed.

6. The vehicle drift trajectory control method according to any one of claims 1 to 5, characterized in that, The step of controlling the vehicle to drift along the desired trajectory according to the reference control parameters includes: Query the desired tracking state that the vehicle can achieve after a preset time. 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; Calculate the target control parameters based on the state proportional coefficient, the reference control parameters, and the tracking reference control parameters; The vehicle is controlled to drift along the desired trajectory according to the target control parameters.

7. A vehicle drift trajectory control device, characterized in that, The vehicle drift trajectory control device includes: The acquisition module is used to acquire the state deviation between the vehicle and the target trajectory point on the desired trajectory. The control module is used to calculate control parameters by substituting the difference in state parameters between the vehicle and the target trajectory point into the vehicle state error model when the state deviation exceeds a preset range, and to pre-adjust the state of the vehicle according to the target transition trajectory based on the control parameters, wherein the target transition trajectory is the trajectory that makes the vehicle meet the drift equilibrium state. The calculation module is used to obtain the current state parameters of the pre-adjusted vehicle and determine the target state parameters based on the desired trajectory; 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 also used to control the vehicle to drift according to the desired trajectory based on the reference control parameters; The vehicle drift trajectory control device further includes: a construction module, which is used to acquire the current speed of the vehicle; obtain the predicted movement distance of the vehicle based on the vehicle speed and a preset forward look time; determine the predicted position of the vehicle based on the predicted movement distance; determine the forward look matching point based on the predicted position; acquire the error between the vehicle and the forward look matching point and the target trajectory point respectively; and determine the target transition trajectory based on the error and the predicted movement distance.

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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