Path tracking control method and device for automatic parking and computer equipment

Abstract

The invention relates to a path tracking control method and device for automatic parking and computer equipment, and the method comprises the steps: obtaining a feedforward steering wheel rotation angle and a deviation distance of a preview feedforward controller, and determining a first scale factor of the preview feedforward controller based on the deviation distance; a feedback steering wheel turning angle of the LQR feedback controller is obtained, and a second scale factor of the LQR feedback controller is preset; the first scale factor and the second scale factor meet a relation condition; determining a steering wheel rotation angle according to the feedforward steering wheel rotation angle, the first scale factor, the feedback steering wheel rotation angle and the second scale factor; and performing tracking control on an expected path track of automatic parking based on the steering wheel angle. According to the method and the device, the problem that the driving experience is affected due to the fact that the parking path tracking precision is low in the prior art is solved, the path tracking precision is improved, and the driving experience is optimized.

Description

[0001] This application is a divisional application with an application date of August 10, 2022, application number 2022109556510, and invention name “Path tracking control method, device and computer equipment for automatic parking”. Technical Field

[0002] The present application relates to the field of unmanned driving technology, and in particular to a path tracking control method, device and computer equipment for automatic parking. Background Art

[0003] Unmanned driving has developed rapidly in recent years. The actual control of unmanned vehicles is related to the safety, stability and comfort of the vehicle, and is a key technology for the implementation of unmanned driving technology. Existing unmanned driving control technologies are divided into lateral control technology and longitudinal control technology. Lateral control is related to the stability of the vehicle. Existing lateral control technologies include pure tracking algorithm, Stanley algorithm, LQR algorithm, MPC algorithm, etc. The dynamic LQR algorithm performs dynamic modeling on the vehicle, so that it can better meet the vehicle's motion characteristics in medium and high-speed movements, and performs better in lateral control effects.

[0004] The current path tracking algorithm uses a preview feedforward algorithm to ensure the correctness of the vehicle tracking overall trend, and then compensates through conventional algorithms such as PID to achieve real-time correction of control variables. However, similar algorithms only apply corresponding parameters and are not general, resulting in low parking path tracking accuracy, affecting the driving experience.

[0005] With regard to the problem in related technologies that the parking path tracking accuracy is low and the driving experience is affected, no effective solution has been proposed so far. Summary of the invention

[0006] In this embodiment, a path tracking control method, device and computer equipment for automatic parking are provided to solve the problem of low parking path tracking accuracy in related technologies, which affects the driving experience.

[0007] In a first aspect, a path tracking control method for automatic parking is provided in this embodiment, comprising:

[0008] Acquire a feedforward steering wheel angle and a deviation distance of a preview feedforward controller, and determine a first proportional factor of the preview feedforward controller based on the deviation distance;

[0009] Acquiring a feedback steering wheel angle of an LQR feedback controller, and presetting a second proportional factor of the LQR feedback controller; the first proportional factor and the second proportional factor satisfy a relationship condition;

[0010] determining a steering wheel angle according to the feedforward steering wheel angle, the first proportional factor, the feedback steering wheel angle, and a second proportional factor;

[0011] The desired path trajectory of automatic parking is tracked and controlled based on the steering wheel angle.

[0012] In some embodiments, the method further comprises:

[0013] Determining a change in the steering wheel angle based on a comparison between the current steering wheel angle and the last steering wheel angle;

[0014] Comparing the steering wheel angle change with a preset steering angle threshold to determine whether the operating condition is abnormal;

[0015] When the angle change of the steering wheel angle does not meet the preset angle threshold, the operating condition is determined to be abnormal; the first proportional factor and the second proportional factor are updated, and the steering wheel angle is re-determined based on the feedforward steering wheel angle, the feedback steering wheel angle, and the updated first proportional factor and the second proportional factor.

[0016] In some embodiments, the first scaling factor is expressed as:

[0017]

[0018] Where a represents the first proportional factor; Indicates the deviation distance; Is a constant.

[0019] In some of the embodiments, the relationship condition is:

[0020] a+b=1;

[0021] Wherein, a represents the first proportional factor; b represents the second proportional factor.

[0022] In some embodiments, obtaining a feedforward steering wheel angle and a deviation distance of a preview feedforward controller includes:

[0023] Obtaining an expected parking path trajectory and current vehicle positioning information, and performing interpolation calculation based on the heading deviation according to the expected path trajectory and the current vehicle positioning information to obtain a theoretical parking point;

[0024] Using the front wheel turning angle at the theoretical parking point as the feedforward steering wheel turning angle of the preview feedforward controller;

[0025] The deviation distance is determined according to the theoretical parking point and the current positioning information of the vehicle.

[0026] In some embodiments, the step of obtaining an expected parking path trajectory and current vehicle location information, and performing interpolation calculation based on the heading deviation according to the expected path trajectory and the current vehicle location information to obtain a theoretical parking point includes:

[0027] Based on the current positioning information of the parking vehicle and the target parking space information, the desired parking path trajectory is obtained using the parking path planning algorithm;

[0028] Traverse the distance between the expected path trajectory and the vehicle's current positioning information to determine two target points;

[0029] The two target points and the longitudinal deviation are interpolated and matched to obtain a theoretical parking point.

[0030] In some embodiments, obtaining a feedback steering wheel angle of the LQR feedback controller includes:

[0031] Obtaining the lateral deviation and the heading deviation of the vehicle posture, and using a preset vehicle Ackermann kinematics model to construct a discrete state space equation of a two-degree-of-freedom vehicle Ackermann kinematics model according to the lateral deviation and the heading deviation;

[0032] Determine the cumulative deviation according to the lateral deviation and the heading deviation; and set the objective function according to the cumulative deviation and the preset control input weighting;

[0033] Based on the vehicle parameters and the objective function, the discrete state space equation is solved by LQR optimization to obtain a feedback steering wheel angle of the LQR feedback controller.

[0034] In a second aspect, a path tracking control device for automatic parking is provided in this embodiment, comprising: a preview feedforward control module, an LQR feedback control module, a calculation module, and a tracking control module;

[0035] The preview feedforward control module is used to obtain a feedforward steering wheel angle of a preview feedforward controller and determine a first proportional factor of the preview feedforward controller based on a deviation distance;

[0036] The LQR feedback control module is used to obtain the feedback steering wheel angle of the LQR feedback controller and preset the second proportional factor of the LQR feedback controller; the first proportional factor and the second proportional factor satisfy a relationship condition;

[0037] The calculation module is used to determine the steering wheel angle according to the feedforward steering wheel angle, the first proportional factor, the feedback steering wheel angle and the second proportional factor;

[0038] The tracking control module is used to track and control the expected path trajectory of automatic parking based on the steering wheel angle.

[0039] In a third aspect, a computer device is provided in this embodiment, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the path tracking control method for automatic parking described in the first aspect is implemented.

[0040] In a fourth aspect, in this embodiment, a storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the path tracking control method for automatic parking described in the first aspect is implemented.

[0041] Compared with the related art, the path tracking control method, device and computer equipment for automatic parking provided in this embodiment obtain the feedforward steering wheel angle and deviation distance of the preview feedforward controller, and determine the first proportional factor of the preview feedforward controller based on the deviation distance; obtain the feedback steering wheel angle of the LQR feedback controller, and preset the second proportional factor of the LQR feedback controller; the first proportional factor and the second proportional factor meet the relationship condition; determine the steering wheel angle according to the feedforward steering wheel angle, the first proportional factor, the feedback steering wheel angle and the second proportional factor; and track and control the expected path trajectory of automatic parking based on the steering wheel angle. The preview feedforward controller adopts an improved preview feedforward algorithm to ensure the correctness of the overall trend of vehicle tracking, and then performs LQR feedback control on the steering wheel angle of the vehicle through the first proportional factor and the second proportional factor in combination with the LQR feedback algorithm, and then controls the front wheel angle and posture of the vehicle to improve the path tracking accuracy, thereby optimizing the driving experience; and solves the problem of low parking path tracking accuracy and affecting the driving experience in the related art.

[0042] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0044] Figure 1 This is a hardware structure block diagram of a terminal device of an automatic parking path tracking control method provided by an embodiment of the present application;

[0045] Figure 2 is a flow chart of a path tracking control method for automatic parking provided by an embodiment of the present application;

[0046] Figure 3 is a flow chart of a path tracking control method for automatic parking provided by an embodiment of the present application;

[0047] Figure 4 It is a schematic diagram of the algorithm principle of the path tracking control method for automatic parking provided by an embodiment of the present application;

[0048] Figure 5 is a schematic diagram of a two-degree-of-freedom vehicle Ackerman kinematic model provided by an embodiment of the present application;

[0049] Figure 6 It is a structural block diagram of a path tracking control device for automatic parking provided in one embodiment of the present application.

[0050] In the figure: 210, preview feedforward control module; 220, LQR feedback control module; 230, calculation module; 240, tracking control module. DETAILED DESCRIPTION

[0051] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0052] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the general meaning understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the", "these" and the like in this application do not represent quantitative restrictions, and they can be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether directly or indirectly. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. Usually, the character " / " indicates that the objects associated with each other are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0053] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. For example, running on a terminal, Figure 1 FIG. 1 is a hardware structure block diagram of a terminal of the path tracking control method for automatic parking of this embodiment. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown in the figure) processor 102 and memory 104 for storing data, wherein processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA. The above terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0054] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the path tracking control method of automatic parking in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0055] The transmission device 106 is used to receive or send data via a network. The above network includes a wireless network provided by the communication provider of the terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0056] In this embodiment, a path tracking control method for automatic parking is provided. Figure 2 is a flow chart of the path tracking control method of automatic parking of this embodiment. Figure 2 As shown, the process includes the following steps:

[0057] Step S210, obtaining a feedforward steering wheel angle and a deviation distance of the preview feedforward controller, and determining a first proportional factor of the preview feedforward controller based on the deviation distance;

[0058] Step S220, obtaining the feedback steering wheel angle of the LQR feedback controller, and presetting the second proportional factor of the LQR feedback controller; the first proportional factor and the second proportional factor satisfy a relationship condition;

[0059] Step S230, determining the steering wheel angle according to the feedforward steering wheel angle, the first proportional factor, the feedback steering wheel angle and the second proportional factor;

[0060] Step S240: tracking and controlling the desired path trajectory of the automatic parking based on the steering wheel angle.

[0061] It should be noted that the automatic parking function (APA, Automatic Parking Assistant, APA) is a function based on radar / camera sensors distributed around the vehicle. It detects the target parking space during low-speed cruising, and then plans and tracks the desired parking path trajectory, controls the vehicle to help the driver move the vehicle to the target parking space. The path tracking control of automatic parking is directly related to the safety of vehicle occupants and the comfort experience of passengers during the movement. Automatic parking is a function under low-speed vehicle conditions, and has high requirements for positioning accuracy. The effectiveness and accuracy of the path tracking control algorithm directly affect the path planning of the next stage. If the tracking error is large, it may lead to path re-planning or parking failure.

[0062] The preview feedforward controller and the LQR feedback controller can be pre-set, and the feedforward steering wheel angle and the deviation distance can be directly obtained from the preview feedforward controller. The first proportional factor of the preview feedforward controller is associated with the deviation distance.

[0063] Among them, the steering wheel angle feedback formula can be used to determine the steering wheel angle according to the feedforward steering wheel angle, the first proportional factor, the feedback steering wheel angle and the second proportional factor; then the desired path trajectory of automatic parking is tracked and controlled based on the steering wheel angle. The expression of the steering wheel angle feedback formula is: Theta = a*Theta1+*Theta2; where Theta represents the steering wheel angle of the vehicle in the current position; Theta1 represents the feedforward steering wheel angle of the preview feedforward controller; Theta2 represents the feedback steering wheel angle of the LQR feedback controller. Within the normal error range, the first proportional factor and the second proportional factor are used to correct it, so as to ensure that the parking path tracking accuracy is within the expected range.

[0064] Through the above steps, the preview feedforward controller uses an improved preview feedforward algorithm to ensure the correctness of the overall trend of vehicle tracking, and then uses the first proportional factor and the second proportional factor, combined with the LQR feedback algorithm, to perform LQR feedback control on the steering wheel angle of the vehicle, and then control the front wheel angle and posture of the vehicle to improve the path tracking accuracy, thereby optimizing the driving experience; solving the problem of low parking path tracking accuracy in related technologies that affects the driving experience. And the use of the preview feedforward controller combined with the LQR feedback controller can not only take into account the advantages of the two controllers, but also avoid the disadvantages of parameter adjustment during the horizontal and vertical separation design, and avoid the problem of parameter conflicts between the two controllers; and under the premise of the global correctness of the parking path tracking, it can ensure that the accuracy of local tracking is the current optimal solution.

[0065] Combine the following Figure 3 and Figure 4 , explain each step of this application in detail:

[0066] The control algorithms such as preview and PID used in the existing schemes can meet the tracking error requirements and correct the error in a timely manner when the planned path has no sudden changes in curvature. However, when the planned path has external interference such as sudden changes in curvature, these simple control algorithms are prone to overshoot, which may cause problems such as sudden acceleration and deceleration and steering wheel shaking.

[0067] In some embodiments, in order to solve the above problems, the path tracking control method for automatic parking further includes the following steps:

[0068] Determining a steering wheel angle change based on a comparison between a current steering wheel angle and a previous steering wheel angle;

[0069] Compare the steering wheel angle change with a preset steering angle threshold to determine whether the operating condition is abnormal;

[0070] When the angle change of the steering wheel angle does not meet the preset angle threshold, the operating condition is determined to be abnormal; the first proportional factor and the second proportional factor are updated, and the steering wheel angle is re-determined based on the feedforward steering wheel angle, the feedback steering wheel angle and the updated first proportional factor and the second proportional factor.

[0071] Specifically, by comparing the steering wheel angle change with the preset angle threshold, it is determined whether the working condition is abnormal; normal working condition means that it is within the normal error range, and the steering wheel angle is calculated using the steering wheel angle feedback formula. At this time: the first proportional factor and the second proportional factor can both be 1, that is, a=b=1; the relationship condition is that the first proportional factor and the second proportional factor are equal.

[0072] Abnormal working conditions refer to exceeding the normal error range; then the first proportional factor and the second proportional factor are updated, and the steering wheel angle is re-determined based on the feedforward steering wheel angle, the feedback steering wheel angle, and the updated first proportional factor and the second proportional factor. It should be noted that if the normal error range is exceeded, it is necessary to re-acquire the deviation distance of the preview feedforward controller to determine the first proportional factor of the preview feedforward controller; then the second proportional factor is determined by the first proportional factor and the relationship condition, thereby updating the first proportional factor and the second proportional factor.

[0073] Specifically, the expression of the first scale factor is:

[0074]

[0075] Where a represents the first proportional factor; Indicates the deviation distance; It is a constant and can be an empirical value, such as 0.25m.

[0076] Among them, the preview feedforward controller adopts an improved preview feedforward algorithm, which can directly obtain the feedback steering wheel angle from the preview feedforward controller; and then determine the second proportional factor by the relationship condition and the first proportional factor. Since the relationship condition is: a+b=1; in the formula, a represents the first proportional factor; b represents the second proportional factor. Then the expression of the second proportional factor can be obtained as:

[0077] Since the tracking deviation of the theoretical parking point changes in real time during this process, the calculation of the preview feedforward controller and the proportional factor of the preview feedforward controller is also real-time; for example: when the preset angle threshold is 50 degrees, when the angle change of the steering wheel angle as the control variable is greater than 50 degrees, the parking controller correction mechanism is triggered. The first proportional factor and the second proportional factor are updated in real time. At this time, the output steering wheel angle is: θ=a*θ j+1 +b*θ2; the first proportional factor is: The second scaling factor is:

[0078]

[0079] In other embodiments, the first proportional factor and the second proportional factor may be other expressions, and the relationship conditions may also be different, which is not limited.

[0080] Automatic parking belongs to low-speed non-steady-state working conditions. It is challenging to smoothly and comfortably move the vehicle along the desired path trajectory during parking, especially in complex working conditions or when there is a set of curvature mutation points in the desired parking path trajectory. At this time, the vehicle system is unstable and the adapted control parameters are likely to fail. This embodiment updates the first proportional factor and the second proportional factor, combines the LQR feedback algorithm to perform LQR feedback control on the steering wheel angle of the vehicle, and then controls the front wheel angle and posture of the vehicle to ensure that the actual trajectory of the vehicle matches the desired path trajectory of parking, thereby ensuring that the parking path tracking accuracy is within the expected range, and can ensure that the actual trajectory of the vehicle matches the desired path trajectory in a timely, effective and non-overshooting manner, and can also have continuity and driving comfort for the desired path trajectory with discontinuous curvature.

[0081] In some embodiments, obtaining the feedforward steering wheel angle and the deviation distance of the preview feedforward controller in step S210 includes the following steps:

[0082] Step S211, obtaining the desired parking path trajectory and the current vehicle positioning information, and performing interpolation calculation based on the heading deviation according to the desired path trajectory and the current vehicle positioning information to obtain a theoretical parking point;

[0083] Step S212, using the front wheel angle at the theoretical parking point as the feedforward steering wheel angle of the preview feedforward controller;

[0084] Step S213, determining the deviation distance according to the theoretical parking point and the current positioning information of the vehicle.

[0085] Specifically, the expected path trajectory can be calculated by various parking path planning algorithms. The expected path trajectory can be expressed as: S = [s1, s1, …, s n ],s i =[X i , Y i , Phi i , k, θ i , v i , t i ] T ; Where S is a discrete desired path trajectory, which has n vectors (s1 to s n ); In each vector, the vehicle's position information X is included i , Yi i , vehicle heading angle information Phi i , front wheel turning angle θ i , curvature k i , the speed of the vehicle v i , the time stamp of the trajectory point is t i; T represents the matrix identifier. The current vehicle positioning information can be provided by a positioning device installed on the vehicle; the current vehicle positioning information VehPos can be expressed as: S k =[X k , Y k , Phi k , k k ,θ k , v k , t k ] T , k is the subscript of a certain moment.

[0086] According to the above-mentioned expected path trajectory and the current positioning information of the vehicle, interpolation calculation is performed based on the heading deviation to obtain the interpolation point closest to the current positioning information of the vehicle on the expected path trajectory as the theoretical parking point; then preview is performed through the theoretical parking points of the subsequent cycle, and the preview distance is the Euclidean distance between the current positioning information of the vehicle and the current nearby theoretical parking point That is the deviation distance. At this time, the front wheel angle in the theoretical parking point is used as the steering wheel angle of the preview feedforward controller, and the vehicle heading angle is determined. For example: the steering wheel angle of the preview feedforward controller is θ1, then the vehicle heading angle is Phi1. In the low-speed parking path tracking process, the distance deviation between the actual vehicle position (the vehicle's current positioning information) and the expected interpolation point (theoretical parking point) is the key input of the improved preview feedforward algorithm. The output of the improved preview feedforward algorithm is the steering wheel angle. Generally, the larger the lateral distance deviation, the larger the steering wheel angle to be adjusted. In the actual parking process, in order to avoid abnormal steering wheel jitter caused by excessive adjustment of the angle and to compensate for the error, the calculation result is corrected based on the first proportional factor designed based on the preview distance.

[0087] In some embodiments, the step S211 of obtaining the desired parking path trajectory and the current vehicle location information, and performing interpolation calculation based on the heading deviation according to the desired path trajectory and the current vehicle location information to obtain the theoretical parking point includes the following steps:

[0088] Based on the current positioning information of the parking vehicle and the target parking space information, the desired parking path trajectory is obtained using the parking path planning algorithm;

[0089] Traverse the distance between the expected path trajectory and the vehicle's current positioning information to determine two target points;

[0090] The two target points and the longitudinal deviation are interpolated and matched to obtain the theoretical parking point.

[0091] Specifically, the current positioning information of the parked vehicle and the target parking space information can be obtained by the corresponding hardware device, and then based on the current positioning information of the parked vehicle and the target parking space information, the desired parking path trajectory S is obtained using the parking path planning algorithm.

[0092] Traverse the expected path trajectory S and the vehicle’s current location information S k Distance min|Ss k |, take the two points corresponding to the minimum distance and the second minimum distance as the target points, the two target points are: s j ,s j+1 Among them, the target point s j =[X j , Yj j , Phi j , k j ,θ j , v j , t j ] T ; Among them, the target point s j+1 =[X j+1 , Y j+1 , Phi j+1 , k j+1 ,θ j+1 , v j+1 , t j+1 ] T ; The two target points s j ,s j+1 Interpolate and match the longitudinal deviation to obtain the matching point, which is the theoretical parking point and also the preview point s t ,s t =[X t , Y t , Phi t , k t ,θ t , v t , t t ] T .

[0093] Among them, the preview point s t The expressions for the variables in can be:

[0094] X t =X k ;

[0095]

[0096]

[0097] in, This is the longitudinal deviation. t、v t and t t It can also be calculated based on a calculation formula similar to the above.

[0098] The lateral deviation between the current vehicle position and the theoretical parking point is:

[0099] ΔY=Y k -Y t ;

[0100] The heading deviation between the current vehicle position and the vehicle at the theoretical parking point is:

[0101] ΔPhi=Phi k -Phi t ;

[0102] The lateral deviation and heading deviation of the vehicle posture calculated above can be updated to the LQR feedback controller to improve the accuracy of the calculation results.

[0103] Specifically, the target point s j+1 The front wheel turning angle θ j+1 As the feedforward steering wheel angle of the preview feedforward controller, the deviation distance is the vehicle's current positioning information VehPos and the theoretical parking point s t The Euclidean distance Δl;

[0104]

[0105] In this embodiment, the theoretical parking point of the optimal solution is obtained in real time to ensure that the deviation distance of the path tracking fluctuates within a certain small range.

[0106] In some embodiments, obtaining a feedback steering wheel angle of an LQR feedback controller includes:

[0107] Obtain the lateral deviation and heading deviation of the vehicle posture, and use the preset vehicle Ackerman kinematics model to construct the discrete state space equation of the two-degree-of-freedom vehicle Ackerman kinematics model according to the lateral deviation and heading deviation;

[0108] Determine the cumulative deviation based on the lateral deviation and the heading deviation; and set the objective function based on the cumulative deviation and the preset control input weighting;

[0109] Based on the vehicle parameters and the objective function, the discrete state space equation is solved by LQR optimization to obtain the feedback steering wheel angle of the LQR feedback controller.

[0110] Specifically, the vehicle Ackerman kinematics model may be pre-set, in which δ represents the front wheel turning angle, l represents the wheelbase, Represents the current vehicle's heading angle.

[0111] like Figure 5 As shown, the two-degree-of-freedom vehicle Ackerman kinematic model can be expressed as:

[0112]

[0113] In the formula, represents the yaw rate of the vehicle; v represents the speed of the rear axle center; It represents the component velocity of the vehicle's yaw rate in the global coordinate system X; It represents the component of the vehicle's yaw rate in the global coordinate system Y.

[0114] The above two-degree-of-freedom vehicle Ackerman kinematic model is simplified to matrix operations:

[0115]

[0116] Since the purpose of parking path tracking is to adjust the vehicle posture to the target parking space; therefore, the state variables are selected based on the vehicle posture. The actual control of the vehicle is achieved by adjusting the vehicle speed and the front wheel angle, so the control variable is selected as u = [v, δ] T , remember a discrete point s on the expected path trajectory r ,in The vehicle Ackerman kinematic model uses Taylor series expansion and ignores higher-order terms above the second order. The change in state quantity It can be expressed as:

[0117]

[0118] According to the Jacobian matrix, the change of the state quantity Find the partial derivative. The deviation of the change in state quantity at this time for:

[0119]

[0120] Based on the deviation of the state quantity change, a linear state space is constructed with a time step of T. The forward Euler discretization can be obtained, and the discrete state space equation is:

[0121]

[0122] In order to make the deviation of path tracking (lateral deviation and heading deviation) be corrected in time and effectively, the objective function J(X) is set according to the tracking cumulative deviation and the control input weighting;

[0123] The objective function can be expressed as:

[0124] Among them, Q is the parameter weighting matrix based on the actual vehicle debugging of lateral distance and heading angle deviation, R is the second-order identity matrix.

[0125] Based on the vehicle's own parameter information and objective function, the discrete state space equation is optimized using a linear quadratic solver to obtain the steering wheel angle θ2 of the LQR feedback controller.

[0126] It should be noted that the steps shown in the above process or the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0127] In this embodiment, a path tracking control device for automatic parking is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated hereafter. The terms "module", "unit", "subunit", etc. used below may be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0128] Figure 6 FIG. 1 is a structural block diagram of the path tracking control device for automatic parking of the present embodiment. Figure 6 As shown, the device includes: a preview feedforward control module 210, an LQR feedback control module 220, a calculation module 230 and a tracking control module 240;

[0129] A preview feedforward control module 210, configured to obtain a feedforward steering wheel angle of a preview feedforward controller and determine a first proportional factor of the preview feedforward controller based on a deviation distance;

[0130] The LQR feedback control module 220 is used to obtain the feedback steering wheel angle of the LQR feedback controller and preset the second proportional factor of the LQR feedback controller; the first proportional factor and the second proportional factor satisfy the relationship condition;

[0131] A calculation module 230, configured to determine a steering wheel angle according to the feedforward steering wheel angle, the first proportional factor, the feedback steering wheel angle, and the second proportional factor;

[0132] The tracking control module 240 is used to track and control the desired path trajectory of the automatic parking based on the steering wheel angle.

[0133] Through the above device, the preview feedforward controller adopts an improved preview feedforward algorithm to ensure the correctness of the overall trend of vehicle tracking, and then performs LQR feedback control on the steering wheel angle of the vehicle through the first proportional factor and the second proportional factor in combination with the LQR feedback algorithm, and then controls the front wheel angle and posture of the vehicle to improve the path tracking accuracy, thereby optimizing the driving experience; and solves the problem of low parking path tracking accuracy in related technologies, which affects the driving experience. And the use of the preview feedforward controller combined with the LQR feedback controller can not only take into account the advantages of the two controllers, but also avoid the disadvantages of parameter adjustment when the horizontal and vertical separation design is used, and avoid the problems of parameter conflicts between the two controllers.

[0134] In some of the embodiments, the path tracking control device for automatic parking further includes a correction module:

[0135] A correction module, for determining a steering wheel angle change based on a comparison between a current steering wheel angle and a previous steering wheel angle;

[0136] Compare the steering wheel angle change with a preset steering angle threshold to determine whether the operating condition is abnormal;

[0137] When the angle change of the steering wheel angle does not meet the preset angle threshold, the operating condition is determined to be abnormal; the first proportional factor and the second proportional factor are updated, and the steering wheel angle is re-determined based on the feedforward steering wheel angle, the feedback steering wheel angle and the updated first proportional factor and the second proportional factor.

[0138] In some of the embodiments, the expression of the first scale factor is:

[0139]

[0140] Where a represents the first proportional factor; Indicates the deviation distance; Is a constant.

[0141] In some of these embodiments, the relationship condition is:

[0142] a+b=1;

[0143] Wherein, a represents the first proportional factor; b represents the second proportional factor.

[0144] In some of the embodiments, the preview feedforward control module 210 is further used to obtain the desired path trajectory of parking and the current location information of the vehicle, and perform interpolation calculation based on the heading deviation according to the desired path trajectory and the current location information of the vehicle to obtain a theoretical parking point;

[0145] The front wheel steering angle at the theoretical parking point is used as the feedforward steering wheel angle of the preview feedforward controller;

[0146] The deviation distance is determined based on the theoretical parking point and the vehicle's current positioning information.

[0147] In some of the embodiments, the preview feedforward control module 210 is further used to obtain a desired parking path trajectory using a parking path planning algorithm based on the current positioning information of the parked vehicle and the target parking space information;

[0148] Traverse the distance between the expected path trajectory and the vehicle's current positioning information to determine two target points;

[0149] The two target points and the longitudinal deviation are interpolated and matched to obtain the theoretical parking point.

[0150] In some of the embodiments, the LQR feedback control module 220 is further used to obtain the lateral deviation and the heading deviation of the vehicle posture, and to construct a discrete state space equation of the two-degree-of-freedom vehicle Ackerman kinematics model according to the lateral deviation and the heading deviation using a preset vehicle Ackerman kinematics model;

[0151] Determine the cumulative deviation based on the lateral deviation and the heading deviation; and set the objective function based on the cumulative deviation and the preset control input weighting;

[0152] Based on the vehicle parameters and the objective function, the discrete state space equation is solved by LQR optimization to obtain the feedback steering wheel angle of the LQR feedback controller.

[0153] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0154] In this embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0155] Optionally, the computer device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0156] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0157] S1, obtaining a feedforward steering wheel angle and a deviation distance of a preview feedforward controller, and determining a first proportional factor of the preview feedforward controller based on the deviation distance;

[0158] S2, obtaining a feedback steering wheel angle of the LQR feedback controller, and presetting a second proportional factor of the LQR feedback controller; the first proportional factor and the second proportional factor satisfy a relationship condition;

[0159] S3, determining a steering wheel angle according to the feedforward steering wheel angle, the first proportional factor, the feedback steering wheel angle, and the second proportional factor;

[0160] S4, tracking and controlling the desired path trajectory of the automatic parking based on the steering wheel angle.

[0161] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and will not be repeated in this embodiment.

[0162] In addition, in combination with the path tracking control method for automatic parking provided in the above embodiments, a storage medium may be provided in this embodiment to implement the method. The storage medium stores a computer program; when the computer program is executed by a processor, any path tracking control method for automatic parking in the above embodiments is implemented.

[0163] It should be understood that the specific embodiments described herein are only used to explain the application, rather than to limit it. Based on the embodiments provided in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of this application.

[0164] Obviously, the drawings are only some examples or embodiments of the present application. For ordinary technicians in the field, the present application can also be applied to other similar situations based on these drawings without creative work. In addition, it is understandable that although the work done in this development process may be complicated and lengthy, for ordinary technicians in the field, certain changes in design, manufacturing or production based on the technical content disclosed in this application are only conventional technical means and should not be regarded as insufficient content disclosed in this application.

[0165] The term "embodiment" in this application refers to a specific feature, structure or characteristic described in conjunction with the embodiment that can be included in at least one embodiment of the present application. The appearance of this phrase in various locations in the specification does not necessarily mean the same embodiment, nor does it mean that it is mutually exclusive with other embodiments and is independent or optional. It is clearly or implicitly understood by those of ordinary skill in the art that the embodiments described in this application can be combined with other embodiments without conflict.

[0166] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of patent protection. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the attached claims.

Claims

1. A path tracking control method for automatic parking, characterized in that: include: Acquire a feedforward steering wheel angle and a deviation distance of a preview feedforward controller, and determine a first proportional factor of the preview feedforward controller based on the deviation distance; Acquiring a feedback steering wheel angle of an LQR feedback controller, and presetting a second proportional factor of the LQR feedback controller; the first proportional factor and the second proportional factor satisfy a relationship condition; determining a steering wheel angle according to the feedforward steering wheel angle, the first proportional factor, the feedback steering wheel angle, and a second proportional factor; Tracking and controlling the desired path trajectory of automatic parking based on the steering wheel angle; The step of obtaining the feedforward steering wheel angle and deviation distance of the preview feedforward controller includes: Obtaining an expected parking path trajectory and current vehicle positioning information, and performing interpolation calculation based on the heading deviation according to the expected path trajectory and the current vehicle positioning information to obtain a theoretical parking point; Using the front wheel turning angle at the theoretical parking point as the feedforward steering wheel turning angle of the preview feedforward controller; The deviation distance is determined according to the theoretical parking point and the current positioning information of the vehicle.

2. The path tracking control method for automatic parking according to claim 1, characterized in that: The method further comprises: Determining a change in the steering wheel angle based on a comparison between the current steering wheel angle and the last steering wheel angle; Comparing the steering wheel angle change with a preset steering angle threshold to determine whether the operating condition is abnormal; When the angle change of the steering wheel angle does not meet the preset angle threshold, the operating condition is determined to be abnormal; the first proportional factor and the second proportional factor are updated, and the steering wheel angle is re-determined based on the feedforward steering wheel angle, the feedback steering wheel angle, and the updated first proportional factor and the second proportional factor.

3. The path tracking control method for automatic parking according to claim 1, characterized in that: The expression of the first scale factor is: a=Δl / l0; Wherein, a represents the first proportional factor; Δl represents the deviation distance; l0 is a constant.

4. The path tracking control method for automatic parking according to claim 1, characterized in that: The relationship conditions are: a+b=1; Wherein, a represents the first proportional factor; b represents the second proportional factor.

5. The path tracking control method for automatic parking according to claim 1, characterized in that: The obtaining of the desired parking path trajectory and the current vehicle positioning information, and performing interpolation calculation based on the heading deviation according to the desired path trajectory and the current vehicle positioning information to obtain a theoretical parking point includes: Based on the current positioning information of the parking vehicle and the target parking space information, the desired parking path trajectory is obtained using the parking path planning algorithm; Traverse the distance between the expected path trajectory and the vehicle's current positioning information to determine two target points; The two target points and the longitudinal deviation are interpolated and matched to obtain a theoretical parking point.

6. The path tracking control method for automatic parking according to any one of claims 1 to 4, characterized in that: The step of obtaining the feedback steering wheel angle of the LQR feedback controller includes: Obtaining the lateral deviation and the heading deviation of the vehicle posture, and using a preset vehicle Ackermann kinematics model to construct a discrete state space equation of a two-degree-of-freedom vehicle Ackermann kinematics model according to the lateral deviation and the heading deviation; Determine the cumulative deviation according to the lateral deviation and the heading deviation; and set the objective function according to the cumulative deviation and the preset control input weighting; Based on the vehicle parameters and the objective function, the discrete state space equation is solved by LQR optimization to obtain a feedback steering wheel angle of the LQR feedback controller.

7. A path tracking control device for automatic parking, characterized in that: include: Preview feedforward control module, LQR feedback control module, calculation module and tracking control module; The preview feedforward control module is used to obtain a feedforward steering wheel angle of a preview feedforward controller and determine a first proportional factor of the preview feedforward controller based on a deviation distance; The preview feedforward control module is further used to obtain the desired path trajectory of parking and the current positioning information of the vehicle, and perform interpolation calculation based on the heading deviation according to the desired path trajectory and the current positioning information of the vehicle to obtain a theoretical parking point; Using the front wheel turning angle at the theoretical parking point as the feedforward steering wheel turning angle of the preview feedforward controller; Determining the deviation distance according to the theoretical parking point and the current positioning information of the vehicle; The LQR feedback control module is used to obtain the feedback steering wheel angle of the LQR feedback controller and preset the second proportional factor of the LQR feedback controller; the first proportional factor and the second proportional factor satisfy a relationship condition; The calculation module is used to determine the steering wheel angle according to the feedforward steering wheel angle, the first proportional factor, the feedback steering wheel angle and the second proportional factor; The tracking control module is used to track and control the expected path trajectory of automatic parking based on the steering wheel angle.

8. A computer device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps of the path tracking control method for automatic parking according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the path tracking control method for automatic parking according to any one of claims 1 to 6 are implemented.

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