Vehicle lateral control method and device, electronic equipment and storage medium

Abstract

The present disclosure provides a vehicle lateral control method, device, electronic equipment and storage medium. The vehicle lateral control method of the present disclosure comprises: obtaining current real-time position information of the vehicle and planning path information, the planning path information comprising information of a reference position corresponding to the current real-time position on a current planning path, a current speed of the vehicle, and a wheelbase of the vehicle; determining a current heading angle deviation and a road lateral deviation of the vehicle according to the current real-time position information of the vehicle and the information of the reference position; and determining a front wheel turning angle of the vehicle at a future time according to the wheelbase of the vehicle and the current heading angle deviation, the road lateral deviation, the speed and a feedforward turning angle of the vehicle. The present disclosure can realize decoupling control of the lateral and longitudinal directions of the vehicle, and has high control accuracy in scenarios such as large front wheel turning angle and low-speed movement of the vehicle.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to a vehicle lateral control method, device, electronic equipment and storage medium. BACKGROUND

[0002] The control model of a vehicle is the core of the automatic driving vehicle control module, and a simple and reliable control model is the basis for ensuring control accuracy. With the development of automatic driving technology, the operation area of automatic driving is gradually expanding, and the scenarios faced by automatic driving vehicles are becoming more and more complex, and high-precision vehicle control for specific scenarios is becoming increasingly important.

[0003] In related technologies, the lateral control of a vehicle is mainly realized based on a lateral dynamics model or a kinematics model coupled with lateral and longitudinal directions. The lateral dynamics model is mainly suitable for high-speed scenarios with small front wheel steering angles. When the vehicle has a large front wheel steering angle, the accuracy of the model will be very low, and it cannot meet the actual needs of real-time lateral control of the vehicle. The kinematics model coupled with lateral and longitudinal directions is not suitable for vehicle control in low-speed scenarios with lateral and longitudinal decoupling, and the control of the coupled lateral and longitudinal directions is difficult. In addition, the patent document with publication number 113525384A discloses a vehicle lateral control method and controller, which uses a control matrix related to the vehicle reference front wheel steering angle. When the vehicle passes through a large-curvature curve, the difference between the vehicle reference front wheel steering angle and the expected front wheel steering angle will affect the control accuracy, and the lateral control error is large, which also cannot meet the actual needs of real-time lateral control of the vehicle. SUMMARY

[0004] To solve at least one of the above technical problems, the present disclosure provides a vehicle lateral control method, device, electronic equipment and storage medium.

[0005] According to a first aspect of the present disclosure, a vehicle lateral control method is provided, comprising:

[0006] obtaining current real-time position information of the vehicle and planning path information, the planning path information including information of a reference position corresponding to the current real-time position on a current planning path, a current speed of the vehicle, and an axle distance of the vehicle;

[0007] determining a current heading angle deviation and a road lateral deviation of the vehicle according to the current real-time position information of the vehicle and the information of the reference position;

[0008] determining a front wheel steering angle of the vehicle at a future time according to the axle distance of the vehicle and the current heading angle deviation, the road lateral deviation, the speed, and the feedforward steering angle of the vehicle.

[0009] In some embodiments, the determining the front wheel steering angle of the vehicle at the future time according to the wheel base of the vehicle and the current cross track error, the current heading angle error, the current speed, and the current feedforward steering angle of the vehicle comprises: determining a current feedback steering angle factor of the vehicle according to the current feedforward steering angle; calculating a current feedback steering angle of the vehicle based on a predetermined state space equation according to the wheel base of the vehicle, the current feedback steering angle factor of the vehicle, and the current cross track error, the current heading angle error, the current speed, and the current feedforward steering angle of the vehicle; and determining the front wheel steering angle of the vehicle at the future time according to the current feedback steering angle and the current feedforward steering angle of the vehicle.

[0010] In some embodiments, the current feedback steering angle of the vehicle is calculated by a state space equation as follows:

[0011]

[0012]

[0013]

[0014]

[0015]

[0016]

[0017] wherein v represents the current speed of the vehicle, L represents the wheel base of the vehicle, u represents the feedback steering angle of the vehicle, λ represents the current feedback steering angle factor of the vehicle, δ f represents the current feedforward steering angle of the vehicle, e1 represents the current cross track error of the vehicle, e2 represents the current heading angle error of the vehicle, represents the first order derivative of e1 with respect to time, represents the first order derivative of e2 with respect to time.

[0018] In some embodiments, the vehicle current planning path information further comprises a road curvature of the reference position; and the current feedforward steering angle of the vehicle is determined according to the wheel base of the vehicle and the road curvature of the reference position.

[0019] In some embodiments, the determining the current feedback steering angle factor of the vehicle according to the current feedforward steering angle comprises: determining the current feedback steering angle factor of the vehicle by equal-probability sampling and linear fitting according to the current feedforward steering angle and probability distribution function calibration data; wherein the probability distribution function calibration data comprises a feedback steering angle calibration value and a corresponding probability distribution function calibration value.

[0020] In some embodiments, the determining the current feedback steering factor of the vehicle according to the current feedforward steering angle comprises: determining a difference of the probability distribution function between adjacent sampling points corresponding to the current feedforward steering angle according to the current feedforward steering angle and the probability distribution function value calibration data; generating equal-probability sampling data according to the difference of the probability distribution function between the adjacent sampling points and pre-configured probability distribution function calibration data, the equal-probability sampling data comprising front wheel steering angles and tangents of the front wheel steering angles of N sampling points, N being an integer greater than 1; and performing linear fitting on the equal-probability sampling data to obtain the current feedback steering factor.

[0021] In some embodiments, the probability distribution function value calibration data is determined according to a normal distribution rule of the feedback steering angle of the vehicle.

[0022] According to a second aspect of the present disclosure, a vehicle lateral control device is provided, comprising:

[0023] an acquisition unit configured to acquire current real-time position information of the vehicle and planning path information, the planning path information comprising information of a reference position on a current planning path corresponding to the current real-time position, a current speed of the vehicle, and a wheelbase of the vehicle;

[0024] a deviation determination unit configured to determine a current heading angle deviation and a road lateral deviation of the vehicle according to the current real-time position information of the vehicle and the information of the reference position;

[0025] a front wheel steering angle determination unit configured to determine a front wheel steering angle of the vehicle at a future time according to the wheelbase of the vehicle and the current heading angle deviation, the road lateral deviation, the speed, and a feedforward steering angle of the vehicle.

[0026] According to a third aspect of the present disclosure, an electronic device is provided, comprising:

[0027] a memory configured to store execution instructions; and

[0028] a processor configured to execute the execution instructions stored in the memory, so that the processor performs the vehicle lateral control method described above.

[0029] According to a fourth aspect of the present disclosure, a readable storage medium is provided, the readable storage medium storing execution instructions, the execution instructions being executed by a processor to implement the vehicle lateral control method described above.

[0030] The embodiments of the present disclosure can realize decoupling control of the vehicle in the lateral and longitudinal directions, reduce the control difficulty, and improve the control precision. The embodiments of the present disclosure have high control precision in scenarios such as large front wheel steering angle and low-speed movement of the vehicle, and also have high control robustness. BRIEF DESCRIPTION OF DRAWINGS

[0031] The accompanying drawings illustrate exemplary embodiments of the present disclosure and together with the general description given above, and the detailed description given below, serve to explain the principles of the present disclosure. These drawings should not be taken to be exclusive of other embodiments that can be implemented.

[0032] Figure 1 is a flowchart of a vehicle lateral control method according to some embodiments of the present disclosure.

[0033] Figure 2 is a schematic diagram of the relative relationship between the vehicle real-time position and the vehicle planned path according to some embodiments of the present disclosure.

[0034] Figure 3 is a schematic block diagram of a vehicle lateral control device according to one embodiment of the present disclosure in a hardware implementation using a processing system. DETAILED DESCRIPTION

[0035] The present disclosure will be further described with reference to the drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the present disclosure and are not to be taken in a limiting sense. It is further understood that the drawings are not necessarily to scale and that, unless otherwise indicated, like reference numerals are used throughout the several views to denote like components.

[0036] It should be noted that the embodiments and features of the embodiments in the present disclosure can be combined with each other without conflict. The technical solutions of the present disclosure will be described in detail below with reference to the drawings and in combination with the embodiments.

[0037] Unless otherwise stated, the exemplary embodiments / examples shown are to be understood as providing exemplary features of various details that can be implemented in practice to embody the technical concepts of the present disclosure. Therefore, unless otherwise stated, the features of the various embodiments / examples can be additionally combined, separated, interchanged and / or rearranged without departing from the technical concepts of the present disclosure.

[0038] Cross-hatching and / or shading in the drawings is generally used for making boundaries between adjacent parts clear. Thus, the presence or absence of cross-hatching and / or shading does not convey or imply any preference or requirement as to the specific material, material properties, dimensions, proportions, commonality of parts between illustrated parts, and / or any other characteristic, attribute, property, etc. of the parts. Moreover, in the drawings, the size and relative sizes of parts can be exaggerated for clarity and / or descriptive purposes. When exemplary embodiments can be practiced differently, a specific sequence of processes can be performed in a different order than described. For example, two consecutively described processes can be performed at substantially the same time or in the reverse order of the described sequence. Moreover, like reference numerals designate like parts throughout the specification.

[0039] When a component is referred to as being "on" or "over", "connected to", or "coupled to" another component, it can be directly on, connected, or coupled to the other component, or intervening components can be present. When a component is referred to as being "directly on", "directly connected to", or "directly coupled to" another component, there are no intervening components present. By the term "connected" as used herein, can mean physical, electrical, and / or the like, with or without intervening components.

[0040] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, to the extent that the terms "including", "includes", "having", "has", "a", "an", "one" or "said" and variants thereof are used in either the detailed description and / or the claims, such terms are intended to be inclusive in a manner similar to the term "comprising" as an open transition term without precluding any additional or other elements. It is also noted that, as used herein, the terms "substantially", "approximately" and other similar terms are used as synonyms for "about", and are employed to account for inherent variations in measuring, calculating, and / or providing a value or quantity, as such variations are recognized by those of ordinary skill in the art.

[0041] Figure 1 A flowchart of a vehicle lateral control method of some embodiments of the present disclosure is shown. As shown, the vehicle lateral control method of the embodiments of the present disclosure can include the following steps: Figure 1

[0042] At step S102, real-time position information of the vehicle and planning path information are obtained, the planning path information including information of a reference position corresponding to the current real-time position on the current planning path, a current speed of the vehicle, and a wheelbase of the vehicle.

[0043] At step S104, a current heading angle deviation and a road lateral deviation of the vehicle are determined according to the real-time position information of the vehicle and the information of the reference position.

[0044] At step S106, a front wheel steering angle of the vehicle at a future time is determined according to the wheelbase of the vehicle and the current heading angle deviation, the road lateral deviation, the speed, and a feedforward steering angle of the vehicle.

[0045] In the embodiments of the present disclosure, the future time can be a next time of the current time, or a time interval of a fixed time length or a specific time length from the current time.

[0046] ​The real-time position information of the vehicle can be obtained from a positioning module of the vehicle through a vehicle control bus (e.g., a CAN bus), the planned path information of the vehicle can be obtained from a path planning module of the vehicle through the vehicle control bus, and the wheelbase and other parameters of the vehicle can be read from the pre-stored vehicle self parameters.

[0047] In the embodiments of the present disclosure, the feedforward steering angle can be a desired front wheel steering angle, the feedback steering angle can be a front wheel steering angle change amount determined based on the real-time state of the vehicle, and the front wheel steering angle determined in step S106 can be used as the front wheel steering angle of the vehicle at a future time. The front wheel steering angle can be provided to an actuator through a vehicle control bus (e.g., a CAN bus) to control the front wheel of the vehicle to steer according to the front wheel steering angle at the future time.

[0048] In the embodiments of the present disclosure, the reference position can be flexibly selected according to actual needs. For example, the reference position can be, but is not limited to, the position of a point on the current planned path that is closest to the current real-time position of the vehicle, and the point is referred to as a reference point.

[0049] In some embodiments, the current real-time position information of the vehicle can include the current real-time position of the vehicle (e.g., the real-time position can be the real-time position coordinates of the vehicle in a Cartesian rectangular coordinate system parallel to the ground) and the current heading angle of the vehicle. Step S104 can include: calculating the projection length of the distance between the current real-time position of the vehicle and the corresponding reference position in the normal direction of the reference position, which is the current road lateral deviation of the vehicle; and calculating the included angle between the current heading angle direction of the vehicle and the tangent direction of the reference position, that is, subtracting the included angle between the tangent direction of the reference position and the horizontal axis of the Cartesian rectangular coordinate system from the current heading angle of the vehicle to obtain a difference value, and the included angle or the difference value is the current heading angle deviation of the vehicle.

[0050] Figure 2 A schematic diagram showing the relative relationship between the real-time position of the vehicle and the planned path of the vehicle is shown. Figure 2 In the embodiments, xoy is a Cartesian rectangular coordinate system parallel to the road surface, p represents the real-time position of the rear axle center of the vehicle, that is, the current real-time position of the vehicle; r represents the point on the current planned path that is closest to the current real-time position of the vehicle, and the position of the point r is the reference position corresponding to the current real-time position of the vehicle on the planned path; τ represents the tangent direction of the point r, and the positive direction is along the forward direction of the path; n represents the normal direction of the point r, and the positive direction points to the left side of the forward direction; e1 represents the projection of the distance between the current real-time position of the vehicle and the reference position in the normal direction of the reference point, that is, the road lateral deviation of the embodiments of the present disclosure; and e2 represents the included angle between the heading angle direction of the vehicle and the tangent direction of the reference position, that is, the heading angle deviation of the embodiments of the present disclosure. e1 and e2 are in the range of [-L, L], where L is the wheelbase of the vehicle. Figure 2In the shown case, e1 is positive. If the current real-time position p of the vehicle is located on the right side of the tangent direction of the reference point r, e1 is negative. If the heading angle of the vehicle is smaller than the angle of the tangent direction of the reference point, e2 is negative.

[0051] In some embodiments, step S106 can include steps a1-a3 as follows:

[0052] Step a1, determining a current feedback steering angle factor of the vehicle according to the current feedforward steering angle;

[0053] Step a2, calculating a current feedback steering angle of the vehicle based on a predetermined state space equation according to the wheelbase of the vehicle, the current feedback steering angle factor of the vehicle, and the current heading angle deviation of the vehicle, the road lateral deviation, the speed and the feedforward steering angle;

[0054] Step a3, determining a front wheel steering angle at a future time of the vehicle according to the current feedback steering angle of the vehicle and the current feedforward steering angle thereof.

[0055] In some embodiments, the state space equation can be expressed as the following equations (1)-(6):

[0056]

[0057]

[0058]

[0059]

[0060]

[0061]

[0062] In equation (1), A is a system matrix describing the motion state of the vehicle, B is a control matrix describing the motion state of the vehicle, W represents the disturbance noise of the motion state of the vehicle, and x is a state variable of the motion state of the vehicle. The state space equation can accurately describe the lateral motion state of the vehicle and reflect the actual motion state of the vehicle, and the lateral and longitudinal motion decoupling of the vehicle in a low-speed driving scenario can be realized through equation (1).

[0063] In equations (1)-(6), v represents the current speed of the vehicle, L represents the wheelbase of the vehicle, u represents the feedback steering angle of the vehicle, λ represents the current feedback steering angle factor of the vehicle, δ f represents the current feedforward steering angle of the vehicle, e1 represents the current road lateral deviation of the vehicle, e2 represents the current heading angle deviation of the vehicle, represents the first-order derivative of e1 with respect to time, represents the first-order derivative of e2 with respect to time.

[0064] In some embodiments, the current planned path information of the vehicle can further include a road curvature at the reference position. The current feedforward steering angle of the vehicle can be determined according to the wheelbase of the vehicle and the road curvature at the reference position.

[0065] In some embodiments, the current feedforward steering angle δ f of the vehicle can be calculated according to the following equation (7):

[0066] δ f = arctan(Lk f ) (7)

[0067] wherein δ f represents the current feedforward steering angle of the vehicle, L represents the wheelbase of the vehicle, k f represents the road curvature at the reference position, and “Lk f ” represents the product of the wheelbase of the vehicle and the road curvature at the reference position.

[0068] In step a1, the current feedback steering angle factor λ can be determined by various applicable linearization fitting methods. In some embodiments, in step a1, the current feedback steering angle factor λ can be determined by equal-probability sampling and linearization fitting according to the current feedforward steering angle and the probability distribution function calibration data. The first-order derivative approximation of the equal-probability sampling points by linear fitting can achieve the purpose of improving the control accuracy. In other embodiments, step a1 can also use, for example, Taylor expansion or any other applicable linearization fitting method to determine the feedback steering angle factor λ.

[0069] wherein the probability distribution function calibration data can include feedback steering angle calibration values and their corresponding probability distribution function calibration values.

[0070] The desired state or ideal state of the vehicle lateral control is that the front wheel steering angle is subject to a normal distribution with the mean equal to the feedforward steering angle δ f and the standard deviation equal to the calibration value σ (for example, 5). That is, the feedback steering angle u in the ideal state of the vehicle lateral control is subject to a normal distribution shown in the following equation (8).

[0071] u + δ f ~ N(δ f , σ 2 ) (8)

[0072] That is, the feedback steering angle u in the ideal state of the vehicle lateral control is subject to a normal distribution shown in the following equation (9), in other words, the feedback steering angle u is subject to a normal distribution with the mean equal to 0 and the standard deviation equal to the calibration value σ.

[0073] u ~ N(0, σ 2 ) (9)

[0074] To avoid the vehicle front wheel angle being too large and affecting the vehicle driving safety, the vehicle front wheel angle is usually set with an upper limit value (for example, 30 degrees), and the upper limit value of the front wheel angle of different types of vehicles is different.

[0075] Based on the normal distribution principle and the upper limit of the vehicle front wheel angle, the embodiment of the disclosure determines the probability distribution function calibration data based on the normal distribution principle in advance, so that the probability distribution function calibration data can be directly called in the lateral control of the vehicle to determine the feedback angle factor in real time. Not only can the purpose of improving the lateral control accuracy of the vehicle be achieved, but also the calculation efficiency can be improved, the time consumption can be reduced, and the real-time demand of the vehicle can be better met.

[0076] In some embodiments, the probability distribution function calibration data can adopt empirical values or pre-set fixed values. In specific applications, the probability distribution function calibration data can be flexibly adjusted in combination with actual scenes, actual use conditions, etc.

[0077] Specifically, assuming that the upper limit value of the vehicle front wheel angle is set to Q°, indicating that the value interval of the vehicle front wheel angle is [-Q, Q], the feedback angle calibration value is selected in the value interval (for example, one value is taken every 1°, and the feedback angle calibration value can be 0, 1, 2, 3, 4, …, Q, -1, -2, -3, …, -Q), the probability distribution function value corresponding to these feedback angle calibration values (for example, the probability distribution function value can be but not limited to the cumulative probability function value) is selected based on the normal distribution law as the probability distribution function calibration value, and the feedback angle calibration value and the corresponding probability distribution function calibration value are recorded and saved (for example, stored in the storage or memory) to form the probability distribution function calibration data of the vehicle.

[0078] In specific applications, a plurality of sets of probability distribution function calibration data can be selected, and one set of probability distribution function calibration data is selected as the final probability distribution function calibration data in combination with the application of these probability distribution calibration data. In addition, the values of part of the data can be adjusted in real time in combination with the application of the probability distribution function calibration data.

[0079] In some embodiments, the feedback angle factor λ can be determined by the following steps:

[0080] Step b1, determining the difference value of the probability distribution function between the adjacent sampling points corresponding to the current feedforward angle according to the current feedforward angle and the probability distribution function value calibration data;

[0081] Specifically, assuming that the maximum difference δ between the feedback angle and the feedforward angle is 15°, and the current feedforward angle is equal to δ max f ​, the number of sampling points used for calculating λ is N equals to 7, the current feedforward steering angle δ f The difference t of the probability distribution function between adjacent sampling points near the current feedforward steering angle δ

[0082] F max = Interp(D, F, δ max - δ f ) (10)

[0083] F min = Interp(D, F, - δ max - δ f ) (11)

[0084]

[0085] wherein F max represents the upper boundary value of the probability distribution function of the sampling points near the current feedforward steering angle δ f , F min represents the lower boundary value of the probability distribution function of the sampling points near the current feedforward steering angle δ f , D represents the feedback steering angle calibration value in the probability distribution function calibration data, F represents the probability distribution function calibration value in the probability distribution function calibration data, Interp represents the interpolation function, and t represents the difference of the probability distribution function between adjacent sampling points near the current feedforward steering angle δ f . As can be seen from the equations (10) to (12), the difference of the probability distribution function between adjacent sampling points near the current feedforward steering angle δ f is fixed, that is, the equal-probability sampling near the current feedforward steering angle δ f is realized.

[0086] In step b2, the equal-probability sampling data is generated according to the difference of the probability distribution function between adjacent sampling points and the pre-configured probability distribution function calibration data, and the equal-probability sampling data includes the front wheel steering angle and the tangent value of the front wheel steering angle of N sampling points, wherein N is an integer greater than 1.

[0087] Specifically, assuming that the number of sampling points N equals to 7, the front wheel steering angle x f and the tangent value y i of each sampling point near the current feedforward steering angle δ i may be determined by the following equations (13) to (16):

[0088] F i = 0.5 + (i-4)t (13)

[0089] d i = Interp(F, D, F i ) (14)

[0090] x i = d i + δ f (15)

[0091] y i = tan(x i ) (16)

[0092] where t represents the difference of the probability distribution function between the adjacent sampling points near the current feedforward steering angle δ f , x i represents the front wheel steering angle of the i-th sampling point near the current feedforward steering angle δ f , y i represents the tangent value of the front wheel steering angle of the i-th sampling point near the current feedforward steering angle δ f , d i represents the feedback steering angle of the i-th sampling point near the current feedforward steering angle δ f , F i represents the probability distribution function value of the i-th sampling point near the current feedforward steering angle δ f , D represents the feedback steering angle calibration value in the probability distribution function calibration data, F represents the probability distribution function calibration value in the probability distribution function calibration data, Interp represents an interpolation function, "0.5" in equation (13) represents the middle value of the cumulative probability distribution function under the standard normal distribution, and i represents the number of the i-th sampling point near the current feedforward steering angle δ f . Assuming that the number of sampling points N is 7, i = {1, 2, 3, 4, 5, 6, 7}.

[0093] It should be noted that Interp in the embodiments of the present disclosure can be any applicable interpolation function. For example, Interp can be, but is not limited to, a bilinear interpolation function or any other interpolation function.

[0094] In step b3, linear fitting is performed using the equal-probability sampling data to obtain the current feedback steering angle factor.

[0095] Specifically, various applicable linear fitting algorithms can be used to calculate the current feedback steering angle factor. For example, the least square method can be used to calculate the current feedback steering angle factor λ.

[0096] In some embodiments, the sampling point data (x i , y i ) near the current feedforward steering angle δ f and the corresponding weight ω i of the sampling points are known, and the current feedback steering angle factor λ can be calculated by equations (17)-(19) derived by the least square method:

[0097]

[0098]

[0099]

[0100] wherein, N represents the number of sampling points, i represents the sampling point number, assuming that the number of sampling points N is 7, i = {1, 2, 3, 4, 5, 6, 7}. σ represents the standard deviation calibration value in the normal distribution shown in the foregoing formula (8)-(9), ω i represents the weight corresponding to the i-th sampling point near the current feedforward steering angle δ f i represents the front wheel steering angle of the i-th sampling point near the current feedforward steering angle δ f i represents the tangent value of the front wheel steering angle of the i-th sampling point near the current feedforward steering angle δ f i represents the feedback steering angle of the i-th sampling point near the current feedforward steering angle δ f

[0101] In the embodiments of the present disclosure, in the process of determining the feedback steering angle factor, the sampling points are obtained by sampling near the feedforward steering angle at the corresponding moment with equal probability when linear fitting is performed to determine the feedback steering angle factor and further determine the feedback steering angle, which can effectively improve the robustness and precision of vehicle lateral control.

[0102] In step a2, the linear quadratic regulator (LQR), model predictive control (MPC) or other similar methods can be used to calculate the current feedback steering angle of the vehicle in combination with formula (1)-(6). It should be noted that the specific algorithm for determining the feedback steering angle based on the foregoing state space equation is not limited in the embodiments of the present disclosure.

[0103] In step a3, the front wheel steering angle of the vehicle at the future moment can be equal to the sum of the current feedforward steering angle of the vehicle and the current feedback steering angle thereof.

[0104] ​​​​The vehicle lateral control method of the embodiments of the present disclosure proposes a vehicle kinematics model (i.e., the aforementioned state space equation) that can adapt to a larger front wheel steering angle, only needs to consider the lateral motion of the vehicle, and conforms to the motion law of the vehicle. Not only can the vehicle lateral and longitudinal motion be decoupled, but also can be applied to low-speed scenarios and large front wheel steering angle scenarios, solving the technical problems of poor accuracy in low-speed scenarios, large control difficulty caused by lateral and longitudinal coupling, and the like in the related art. In addition, the embodiments of the present disclosure can effectively improve the accuracy and robustness of vehicle lateral control by linearizing around the current feedforward steering angle to determine the feedback steering angle in real time, solving the technical problem of large lateral control error in a large-curvature curve in the related art.

[0105] Figure 3 is a structural schematic block diagram of a vehicle lateral control device of an embodiment of the present disclosure in a hardware implementation using a processing system.

[0106] The device can include corresponding modules that perform one or several steps in the above flowcharts. Therefore, each step or several steps in the above flowcharts can be performed by corresponding modules, and the device can include one or more of these modules. The modules can be one or more hardware modules specially configured to perform the corresponding steps, or implemented by a processor configured to perform the corresponding steps, or stored in a computer-readable medium for implementation by a processor, or implemented through some combination.

[0107] The hardware structure can be implemented using a bus architecture. The bus architecture can include any number of interconnected buses and bridges, depending on the particular application of the hardware and overall design constraints. The bus 400 connects various circuits including one or more processors 500, memories 600, and / or hardware modules together. The bus 400 can also connect various other circuits 700 such as peripheral devices, voltage regulators, power management circuits, external antennas, and the like.

[0108] The bus 400 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, and the like. The bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one connection line is shown in the figure, but it does not mean that there is only one bus or only one type of bus.

[0109] Any processes or methods described in the flowcharts or otherwise described herein can be understood as representing code modules, segments, or portions of code which include one or more executable instructions for implementing specific logic functions (or steps) of the process, and / or that the various embodiments of the present disclosure can represent alternative process or methods including the steps thereof which can be implemented by other than the recited ordering and / or flow, such will be obvious to those having skill in the art of the disclosed embodiments' technical fields. The processors execute the various ones of the methods and processes described above. For example, the method embodiments of the present disclosure can be implemented as a software program which is tangibly embodied within a machine-readable medium, such as a memory. In some embodiments, portions of the software program can be loaded and / or installed via the memory and / or communication interface. When the software program is loaded into the memory and executed by the processor, one or more of the steps of the methods described above can be performed. Alternatively, in other embodiments, the processor can be configured to perform one of the methods described above by other means, such as by way of firmware.

[0110] Logic and / or steps represented in the flowcharts and / or otherwise described herein can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.

[0111] For the purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can specifically include the following, which are non-exhaustive examples: electrical connection (electrical device), portable computer diskette (magnetic device), Random Access Memory (RAM), Read-Only Memory (ROM), Erasable Programmable Read-Only Memory (EPROM or Flash memory), optical fiber device, and portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable medium upon which the program can be printed, as the program can be electronically captured, for example via the optical scanner, then compiled, interpreted, or otherwise processed in the electronic manner, and then stored in the memory.

[0112] It should be understood that various parts of the present disclosure can be realized in hardware, software, or a combination thereof. In the above-described embodiments, a plurality of steps or methods can be realized by software stored in a memory and executed by a suitable instruction execution system. For example, if realized in hardware, and as in another embodiment, any one or a combination of the following technologies known in the art can be used: discrete logic circuit having logic gates for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), etc.

[0113] Those skilled in the art of the present technology can understand that all or part of the steps of the above-described embodiments can be completed by programs instructing related hardware, and the programs can be stored in a readable storage medium, and when executed, include one or a combination of the steps of the method embodiments.

[0114] In addition, each functional unit in each embodiment of the present disclosure can be integrated into one processing module, or each unit can be physically present separately, or two or more units can be integrated into one module. The above-mentioned integrated module can be realized in the form of hardware or in the form of a software functional module. The integrated module, if realized in the form of a software functional module and sold or used as an independent product, can also be stored in a readable storage medium. The storage medium can be a read-only memory, a magnetic disk or an optical disk, etc.

[0115] Figure 3 is a schematic diagram of a structure of a vehicle lateral control device 300 according to an embodiment of the present disclosure. As shown in Figure 3 The vehicle lateral control device 300 according to the present disclosure can include:

[0116] An acquisition unit 302 is configured to acquire current real-time position information of the vehicle and planned path information, the planned path information including information of a reference position corresponding to the current real-time position on a current planned path, a current speed of the vehicle, and a wheelbase of the vehicle.

[0117] A deviation determination unit 304 is configured to determine a current heading angle deviation and a road lateral deviation of the vehicle according to the current real-time position information of the vehicle and the information of the reference position.

[0118] A front wheel steering angle determination unit 306 is configured to determine a front wheel steering angle of the vehicle at a future time according to the wheelbase of the vehicle and the current heading angle deviation, the road lateral deviation, the speed of the vehicle, and a feedforward steering angle.

[0119] In some embodiments, the front wheel steering angle determination unit 306 is configured to determine a current feedback steering angle factor of the vehicle according to the current feedforward steering angle; calculate a current feedback steering angle of the vehicle based on a predetermined state space equation according to the wheel base of the vehicle, the current feedback steering angle factor of the vehicle, and the current heading angle deviation, the road lateral deviation, the speed of the vehicle, and the feedforward steering angle; and determine the front wheel steering angle of the vehicle at a future time according to the current feedback steering angle of the vehicle and the current feedforward steering angle of the vehicle.

[0120] Other technical details of the vehicle lateral control device 300 according to the embodiments of the present disclosure can be found in the method part above, and will not be repeated here.

[0121] The present disclosure also provides an electronic device, comprising: a memory storing execution instructions; and a processor or other hardware module executing the execution instructions stored in the memory, so that the processor or other hardware module executes the vehicle lateral control method described above.

[0122] The present disclosure also provides a readable storage medium, which stores execution instructions, and the execution instructions are executed by a processor to implement the vehicle lateral control method described above.

[0123] In the description of the present specification, the description of the terms "one embodiment / way", "some embodiments / ways", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment / way or example are included in at least one embodiment / way or example of the present application. In the present specification, the illustrative description of the above terms is not necessarily the same embodiment / way or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments / ways or examples. In addition, the person skilled in the art can combine and combine the different embodiments / ways or examples described in the present specification and the features of the different embodiments / ways or examples, without contradiction.

[0124] In addition, the terms "first", "second" are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise specifically limited.

[0125] Those skilled in the art should understand that the above embodiments are only for clearly illustrating the present disclosure, and are not intended to limit the scope of the present disclosure. Based on the above disclosure, other changes or modifications can also be made by those skilled in the art, and these changes or modifications are still within the scope of the present disclosure.

Claims

1. A vehicle lateral control method, characterized in that, include: The vehicle's current real-time location information and planned path information are obtained. The planned path information includes the reference position information corresponding to the current real-time location on the current planned path, the vehicle's current speed, and the vehicle's wheelbase. Based on the vehicle's current real-time location information and reference location information, determine the vehicle's current heading angle deviation and road lateral deviation; as well as Based on the vehicle's wheelbase, current heading angle deviation, road lateral deviation, speed, and feedforward steering angle, determine the vehicle's future front wheel steering angle, including: The current feedback steering angle factor of the vehicle is determined based on the current feedforward steering angle; the current feedback steering angle of the vehicle is calculated based on the vehicle's wheelbase, the current feedback steering angle factor, the current heading angle deviation, the road lateral deviation, the speed, and the feedforward steering angle, according to a predetermined state-space equation; the front wheel steering angle of the vehicle at future moments is determined based on the current feedback steering angle and the current feedforward steering angle. The process of determining the vehicle's current feedback steering angle factor based on the current feedforward steering angle includes: Based on the current feedforward steering angle and probability distribution function calibration data, the current feedback steering angle factor of the vehicle is obtained through equal probability sampling and linear fitting; wherein, the probability distribution function calibration data includes the feedback steering angle calibration value and its corresponding probability distribution function calibration value.

2. The vehicle lateral control method according to claim 1, characterized in that, The vehicle's current feedback steering angle is calculated using the following state-space equation: in, Indicates the vehicle's current speed. Indicates the vehicle's wheelbase. Indicates the vehicle's feedback steering angle. This indicates the vehicle's current feedback steering angle factor. This indicates the vehicle's current feedforward angle. This indicates the vehicle's current lateral deviation from the road. This indicates the vehicle's current heading angle deviation. express The first derivative with respect to time, express The first derivative with respect to time.

3. The vehicle lateral control method according to claim 1, characterized in that, The vehicle's current planned path information also includes the road curvature at the reference location; the vehicle's current feedforward angle is determined based on the vehicle's wheelbase and the road curvature at the reference location.

4. The vehicle lateral control method according to claim 1, characterized in that, The process of determining the vehicle's current feedback steering angle factor based on the current feedforward steering angle includes: Based on the current feedforward rotation angle and probability distribution function value calibration data, determine the difference in probability distribution function between adjacent sampling points corresponding to the current feedforward rotation angle; Equal probability sampling data is generated based on the difference in probability distribution functions between adjacent sampling points and pre-configured probability distribution function calibration data. The equal probability sampling data includes the front wheel steering angle and its tangent value of N sampling points, where N is an integer greater than 1. The current feedback turning factor is obtained by performing linear fitting using the equal probability sampling data.

5. The vehicle lateral control method according to claim 4, characterized in that, The calibration data for the probability distribution function value is determined based on the normal distribution law of the vehicle feedback steering angle.

6. A vehicle lateral control device, characterized in that, include: The acquisition unit is used to acquire the vehicle's current real-time location information and planned path information. The planned path information includes information on the reference position corresponding to the current real-time location on the current planned path, the vehicle's current speed, and the vehicle's wheelbase. The deviation determination unit is used to determine the vehicle's current heading angle deviation and road lateral deviation based on the vehicle's current real-time position information and reference position information; The front wheel steering angle determination unit is used to determine the vehicle's front wheel steering angle at future moments based on the vehicle's wheelbase, current heading angle deviation, road lateral deviation, speed, and feedforward steering angle, including: The current feedback steering angle factor of the vehicle is determined based on the current feedforward steering angle; the current feedback steering angle of the vehicle is calculated based on the vehicle's wheelbase, the current feedback steering angle factor, the current heading angle deviation, the road lateral deviation, the speed, and the feedforward steering angle, according to a predetermined state-space equation; the front wheel steering angle of the vehicle at future moments is determined based on the current feedback steering angle and the current feedforward steering angle. The process of determining the vehicle's current feedback steering angle factor based on the current feedforward steering angle includes: Based on the current feedforward steering angle and probability distribution function calibration data, the current feedback steering angle factor of the vehicle is obtained through equal probability sampling and linear fitting; wherein, the probability distribution function calibration data includes the feedback steering angle calibration value and its corresponding probability distribution function calibration value.

7. An electronic device, characterized in that, include: The memory stores execution instructions; as well as A processor that executes execution instructions stored in the memory, causing the processor to perform the vehicle lateral control method according to any one of claims 1 to 5.

8. A readable storage medium, characterized in that, The readable storage medium stores execution instructions, which, when executed by a processor, are used to implement the vehicle lateral control method according to any one of claims 1 to 5.

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