CN115489543A

CN115489543A - Vehicle lateral control method, device, system, electronic device and storage medium

Info

Publication number: CN115489543A
Application number: CN202211037447.7A
Authority: CN
Inventors: 任崇岭; 王耀农; 余伟
Original assignee: Zhejiang Zero Run Technology Co Ltd
Current assignee: Zhejiang Zero Run Technology Co Ltd
Priority date: 2022-08-26
Filing date: 2022-08-26
Publication date: 2022-12-20

Abstract

The application relates to a vehicle lateral control method, a device, a system, an electronic device and a storage medium, wherein the vehicle lateral control method comprises the following steps: acquiring vehicle speed information and road curvature information of the vehicle, and a first transverse position deviation between the vehicle and a preset track reference point; generating a dynamic control weight of the vehicle based on a mapping relation between the vehicle speed information and the road curvature information, and calculating a front wheel steering angle result according to the first transverse position deviation and the dynamic control weight; and generating a transverse control result of the vehicle according to the front wheel steering angle result, and performing transverse control on the vehicle according to the transverse control result. Through the method and the device, the problem of low stability of the transverse control of the vehicle is solved, and the precise and stable transverse control of the vehicle is realized.

Description

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

Technical Field

The present application relates to the field of automatic driving technologies, and in particular, to a method, an apparatus, a system, an electronic apparatus, and a storage medium for controlling a lateral direction of a vehicle.

Background

The track tracking control of the automatic driving vehicle is one of key technologies for realizing the automatic driving of the vehicle, and the transverse control function in the track tracking is mainly to control the front wheel steering angle of the vehicle, reduce the transverse deviation between the vehicle and the track and realize that the vehicle runs along the planned track; the tracking accuracy between the vehicle and the trajectory is the main consideration for lateral control. In the related art, the lateral motion control of the automatic driving is usually realized by a pure tracking algorithm, a proportional-integral-derivative control (PID) control, a model predictive control, and other control methods. The control tracking precision of model predictive control is good, but the algorithm of iterative solution sequence quadratic programming has high hardware requirement, the calculation speed is not easy to meet the real-time control requirement of the vehicle, the PID control is simple, but the algorithm cannot cover all scenes, the control gradual stability is general, and the stability of the transverse control of the vehicle is low.

At present, no effective solution is provided for the problem of low stability of the vehicle transverse control in the related art.

Disclosure of Invention

The embodiment of the application provides a vehicle transverse control method, a vehicle transverse control device, a vehicle transverse control system, an electronic device and a storage medium, and aims to at least solve the problem of low stability of vehicle transverse control in the related art.

In a first aspect, an embodiment of the present application provides a vehicle lateral control method, where the method includes:

acquiring speed information and road curvature information of the vehicle, and a first transverse position deviation between the vehicle and a preset track reference point;

generating dynamic control weight of the vehicle based on the mapping relation between the vehicle speed information and the road curvature information, and calculating according to the first transverse position deviation and the dynamic control weight to obtain a front wheel steering angle result;

and generating a transverse control result of the vehicle according to the front wheel steering angle result, and performing transverse control on the vehicle according to the transverse control result.

In some of these embodiments, said generating a lateral control result of the vehicle as a function of the front wheel steering result comprises:

acquiring a pre-aiming distance and a preset path planning track, and calculating to obtain a pre-aiming point according to the vehicle speed information and the path planning track;

calculating to obtain a second transverse position deviation between the vehicle and the preview point according to the preview distance, and obtaining a corner compensation result according to the second transverse position deviation;

and generating the transverse control result according to the front wheel steering angle result and the steering angle compensation result.

In some embodiments, the calculating a second lateral position deviation between the vehicle and the preview point according to the preview distance and the obtaining a rotation angle compensation result according to the second lateral position deviation includes:

obtaining the deviation of a vehicle course angle, and calculating to obtain the transverse deviation of the course angle according to the pre-aiming distance and the deviation of the vehicle course angle;

calculating to obtain a first vertical distance between the pre-aiming point and the front extension line of the center of the vehicle and a second vertical distance between the center of the rear axle of the vehicle and the path planning track; calculating to obtain a second transverse position deviation according to the first vertical distance, the second vertical distance and the course angle transverse deviation;

and calculating to obtain an expected yaw angular speed according to the pre-aiming distance, the vehicle speed information and the second transverse position deviation, and calculating to obtain the corner compensation result based on the expected yaw angular speed.

In some of these embodiments, said generating said lateral control result based on said front wheel steering result and said steering angle compensation result comprises:

generating a target corner result according to the front wheel corner result and the corner compensation result;

and acquiring a transmission ratio between a target steering angle result and a steering wheel, and generating the transverse control result according to the transmission ratio and the target steering angle result.

In some of these embodiments, said calculating a front wheel steering result based on said first lateral position offset and said dynamic steering weights comprises:

and performing iterative solution calculation by using a preset Linear Quadratic Regulator (LQR) controller model according to the first transverse position deviation and the dynamic control weight to obtain an objective function value, and calculating according to the objective function value to obtain the front wheel steering angle result.

In some embodiments, the performing, by using a preset LQR controller model, an iterative solution calculation according to the first lateral position deviation and the dynamic control weight to obtain an objective function value:

generating a state weight matrix according to at least the first lateral position deviation and generating a control weight matrix according to the dynamic control weight;

and acquiring a preset LQR state space equation and a target function for indicating the constraint relation between the state weight matrix and the control weight matrix, and performing iterative solution on the target function according to the LQR state space equation by using the LQR controller model to obtain the target function value.

In some of these embodiments, the generating the dynamic control weight of the vehicle based on the mapping relationship between the vehicle speed information and the road curvature information includes:

obtaining historical vehicle speed information and historical road curvature information, and calculating to obtain a corresponding preset control weight value according to the historical vehicle speed information and the historical road curvature information;

acquiring a preset mapping relation table according to the historical vehicle speed information, the historical road curvature information and the preset control weight value, inquiring the preset mapping relation table according to the mapping relation between the vehicle speed information and the road curvature information, and generating the dynamic control weight according to the inquired preset control weight value.

In some of these embodiments, obtaining a first lateral position deviation between the vehicle and the preset trajectory reference point comprises:

acquiring vehicle state information of the vehicle, and acquiring a path planning track according to the vehicle state information; wherein the path planning trajectory comprises a first reference point generated based on the vehicle state information, the first reference point being located under a global coordinate system;

acquiring a coordinate conversion relation between the global coordinate system and a self-vehicle coordinate system of the vehicle, and converting the first reference point into the self-vehicle coordinate system according to the coordinate conversion relation to obtain a second reference point after coordinate conversion;

and calculating to obtain a track point which is closest to the centroid position of the vehicle in the second reference point, determining the preset track reference point based on the track point, and calculating to obtain the first transverse position deviation.

In a second aspect, an embodiment of the present application provides a vehicle lateral control apparatus, including: the device comprises an acquisition module, a weight module and a generation module;

the acquisition module is used for acquiring the speed information and the road curvature information of the vehicle and a first transverse position deviation between the vehicle and a preset track reference point;

the weight module is used for generating a dynamic control weight of the vehicle based on a mapping relation between the vehicle speed information and the road curvature information, and calculating a front wheel steering angle result according to the first transverse position deviation and the dynamic control weight;

and the generating module is used for generating a transverse control result of the vehicle according to the front wheel steering angle result and carrying out transverse control on the vehicle according to the transverse control result.

In a third aspect, an embodiment of the present application provides a vehicle lateral control system, including: a control device and a vehicle body;

the control device is connected with the vehicle body and is used for executing the vehicle transverse control method in the first aspect.

In a fourth aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the vehicle lateral control method according to the first aspect is implemented.

In a fifth aspect, embodiments of the present application provide a storage medium having a computer program stored thereon, where the computer program is executed by a processor to implement the vehicle lateral control method according to the first aspect.

Compared with the related art, the vehicle transverse control method, the vehicle transverse control device, the vehicle transverse control system, the electronic device and the storage medium provided by the embodiment of the application have the advantages that the vehicle speed information and the road curvature information of the vehicle are obtained, and the first transverse position deviation between the vehicle and the preset track reference point is obtained; generating a dynamic control weight of the vehicle based on a mapping relation between the vehicle speed information and the road curvature information, and calculating a front wheel steering angle result according to the first transverse position deviation and the dynamic control weight; and generating a transverse control result of the vehicle according to the front wheel steering angle result, and transversely controlling the vehicle according to the transverse control result, so that the problem of low stability of transverse control of the vehicle is solved, and accurate and stable transverse control of the vehicle is realized.

The details of one or more embodiments of the application are set forth in the accompanying drawings and the description below to provide a more concise and understandable description of the application, and features, objects, and advantages of the application.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

FIG. 1 is a diagram of an application environment of a lateral vehicle control method according to an embodiment of the application;

FIG. 2 is a flow chart of a method of lateral vehicle control according to an embodiment of the present application;

FIG. 3 is a flow chart of another method of lateral vehicle control according to an embodiment of the present application;

FIG. 4 is a flow chart of a method of lateral vehicle control according to a preferred embodiment of the present application;

FIG. 5 is a block diagram of a vehicle lateral control apparatus according to an embodiment of the present application;

FIG. 6 is a block diagram of a vehicle lateral control system according to an embodiment of the present application;

fig. 7 is a block diagram of the inside of a computer device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.

Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is to be expressly and implicitly understood by one of ordinary skill in the art that the embodiments described herein may be combined with other embodiments without conflict.

Unless otherwise defined, technical or scientific terms referred to herein should have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The use of the terms "a" and "an" and "the" and similar referents in the context of describing the invention (including a single reference) are to be construed in a non-limiting sense as indicating either the singular or the plural. The present application is directed to the use of the terms "including," "comprising," "having," and any variations thereof, which are intended to cover non-exclusive inclusions; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Reference to "connected," "coupled," and the like in this application is not intended to be limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. Reference herein to "a plurality" means greater than or equal to two. "and/or" describes the association relationship of the associated object, indicating that there may be three relationships, for example, "a and/or B" may indicate: a exists alone, A and B exist simultaneously, and B exists alone. Reference herein to the terms "first," "second," "third," and the like, are merely to distinguish similar objects and do not denote a particular ordering for the objects.

The vehicle transverse control method provided by the application can be applied to application scenes such as vehicle automatic driving and wheeled robot navigation control. Fig. 1 is a diagram of an application environment of a lateral vehicle control method according to an embodiment of the present application, and as shown in fig. 1, a vehicle 102 communicates with a server 104 through a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be placed on the cloud or other network server. The server 104 acquires speed information and road curvature information of the vehicle 102 and a first transverse position deviation between the vehicle 102 and a preset track reference point; the server 104 generates a dynamic control weight of the vehicle 102 based on the mapping relationship between the vehicle speed information and the road curvature information, calculates a front wheel steering angle result according to the first lateral position deviation and the dynamic control weight, and finally generates a lateral control result for the vehicle 102 according to the front wheel steering angle result to laterally control the vehicle according to the lateral control result. The server 104 may be implemented as a stand-alone server or a server cluster composed of a plurality of servers.

The present embodiment provides a vehicle lateral control method, and fig. 2 is a flowchart of a vehicle lateral control method according to an embodiment of the present application, where as shown in fig. 2, the flowchart includes the following steps:

step S210, vehicle speed information and road curvature information of the vehicle are obtained, and a first transverse position deviation between the vehicle and a preset track reference point is obtained.

The vehicle speed information refers to the real-time running speed of the corresponding vehicle; the vehicle information can be acquired in real time by sensing equipment such as a speed sensor of the vehicle. The road curvature information refers to the curvature information of the road when the corresponding vehicle runs to the current road; the road curvature information may be calculated from information such as the motion state of the vehicle using a technique such as computer vision. The preset track reference point refers to a track point adjacent to the vehicle on a path planning track generated in advance, and the coordinate position offset relation between the vehicle and the preset track reference point is calculated, so that the first transverse position deviation can be obtained.

Step S220 is performed to generate a dynamic control weight of the vehicle based on the mapping relationship between the vehicle speed information and the road curvature information, and calculate a front wheel steering angle result according to the first lateral position deviation and the dynamic control weight.

Wherein, the dynamic control weight of the vehicle can be detected based on the mapping relationship. Further, the generating of the dynamic control weight of the vehicle based on the mapping relationship between the vehicle speed information and the road curvature information further includes: acquiring a preset mapping relation table; the preset mapping relation table can be generated by calculation according to historical speed information and historical road curvature information obtained through simulation experiment data or test data of automatic driving of vehicles in regions such as a garden; and inquiring the preset mapping relation table through the mapping relation between the vehicle speed information and the road curvature information to obtain the dynamic control weight.

Alternatively, the above-described generation of the dynamic control weight of the vehicle based on the mapping relationship between the vehicle speed information and the road curvature information may be implemented based on a neural network. For example, the vehicle speed information to be trained and the road curvature information to be trained can be obtained in advance according to simulation experiment data or test data of automatic driving of a vehicle in a region such as a park, the vehicle speed information to be trained and the road curvature information to be trained serve as sample data, the sample data is input into a preset neural network model for training and output of a control weight value, and a well-trained neural network model is obtained after the sample data is iterated; the current vehicle speed information and the road curvature information are input to the neural network model, and then a dynamic control weight corresponding to a mapping relationship between the vehicle speed information and the road curvature information can be output.

After the dynamic control weight of the vehicle is calculated in the above step, a feedback matrix K may be obtained by solving the dynamic control weight and the first lateral position deviation, and the front wheel steering angle result may be calculated from the feedback matrix K using the LQR controller model. It can be understood that the control stability under different self-vehicle states and different driving scenes can be effectively improved by performing real-time dynamic adjustment on the control weight parameters in the LQR control process.

In step S230, a lateral control result of the vehicle is generated based on the front wheel steering angle result.

After the front wheel steering angle result is calculated in steps S210 to S220, a rotation ratio between the generated front wheel steering angle and the steering wheel may be stored or calculated in advance, the front wheel steering angle result may be converted into an angle required to rotate the steering wheel, and the angle required to rotate the steering wheel may be used as a lateral control result for the vehicle. It is understood that the lateral control result, that is, the angle of the required turning of the steering wheel, may be sent to a steering execution control mechanism in the vehicle, and the steering execution control mechanism performs a steering control operation on the steering wheel according to the angle of the required turning of the steering wheel, so that the lateral control of the vehicle is achieved based on the lateral control result.

Through the steps S210 to S230, the dynamic control weight is generated through the mapping relation between the vehicle speed information and the road curvature information, and the front wheel steering angle result is obtained through calculation according to the dynamic control weight and the acquired first transverse position deviation, so that the real-time dynamic adjustment of the control weight parameters is realized, the automatic driving control precision and the self-adaptability are effectively improved, the problem of low stability of the transverse control of the vehicle is solved, and the accurate and stable transverse control method of the vehicle is realized.

In some embodiments, a vehicle lateral control method is provided, and fig. 3 is a flowchart of another vehicle lateral control method according to the embodiment of the present application, as shown in fig. 3, the flowchart includes steps S210 and S220 in fig. 2, and further includes the following steps:

and step S310, acquiring a pre-aiming distance and a preset path planning track, and calculating according to the vehicle speed information and the path planning track to obtain a pre-aiming point.

The preview distance may be calculated according to a preset path planning trajectory and vehicle speed information, and is not described herein again. After the pre-aiming distance is determined through the steps, the time interval of the selected target point can be calculated according to the current speed information of the vehicle, namely, two track points with the nearest time are determined according to the time stamps of the track points on the path planning track and the time stamps of the vehicle positions of all points acquired by the current vehicle in the automatic driving process, and then the pre-aiming point on the path planning track is determined and obtained by utilizing methods such as linear difference and the like.

And step S320, calculating to obtain a second transverse position deviation between the vehicle and the preview point according to the preview distance, and obtaining a rotation angle compensation result according to the second transverse position deviation.

Specifically, the second lateral position deviation may be obtained by calculating a coordinate position offset relationship between the vehicle and a home point based on the home distance. And deducing a vehicle preview kinematic model based on the second transverse position deviation to obtain an expected yaw rate, finally deducing a conversion relation between the front wheels of the vehicle and the yaw rate according to the expected yaw rate, and calculating an expected front wheel angle compensation value based on the conversion relation and the expected yaw rate to obtain the corner compensation result.

Step S330 generates the lateral control result according to the front wheel steering angle result and the steering angle compensation result.

It is understood that the compensation correction of the front wheel steering angle result according to the steering angle compensation result can generate a more accurate target steering angle value, so that a final steering control amount, that is, the lateral control result, can be obtained according to the target steering angle value, and the steering execution control mechanism of the vehicle is instructed to implement the autonomous steering control of the vehicle steering wheel based on the steering control amount.

Through the steps S310 to S330, the second transverse position deviation of the vehicle and the preview point piece is calculated by setting the preview distance, and the front wheel steering angle compensation result is solved based on the second transverse position deviation, so that the transverse steering angle compensation method based on the preview point and the self-adaptive LQR transverse control method are effectively combined to realize the autonomous transverse control of the vehicle, the effect of vehicle advanced control under specific driving scenes such as curves or lane change centering and the like is improved, the problems of overshoot or swing and the like of the vehicle transverse control under different road scenes are avoided, the vehicle track tracking is more accurate, the stability and the progressiveness of vehicle control are better, and the stability and the accuracy of the vehicle transverse control are effectively improved.

In some embodiments, the calculating a second lateral position deviation between the vehicle and the preview point according to the preview distance further includes the following steps:

step S321, obtaining the vehicle course angle deviation, and calculating to obtain the course angle transverse deviation according to the pre-aiming distance and the vehicle course angle deviation.

The vehicle course angle deviation can be acquired by a sensor on the vehicle. Specifically, the course angle lateral deviation can be calculated by the pre-aiming distance and a trigonometric function calculation result of the vehicle course angle deviation; the calculation formula of the lateral deviation of the heading angle is shown as formula 1:

ΔL _he ＝L _ef x Sin (. DELTA.. Theta.) formula 1

Wherein, the above-mentioned DeltaL _he For indicating a course angle lateral deviation due to vehicle course angle travel; l is _ef For representing the preview distance; Δ θ is used to represent the vehicle heading angle deviation.

Step S322, calculating a first vertical distance between the preview point and a front line of the center of the vehicle and a second vertical distance between the center of a rear axle of the vehicle and the path planning track; and calculating to obtain the second transverse position deviation according to the first vertical distance, the second vertical distance and the course angle transverse deviation.

Wherein the vertical distance from the preview point to the extension line in front of the center of the vehicle, i.e. the first vertical distance, can be Y ₁ Representing; the second vertical distance may be Y, which is a vertical distance between the center point of the rear axle of the vehicle and the path planning trajectory ₂ And (4) showing. The above-mentioned calculation formula of the second lateral position deviation is shown in equation 2:

ΔYL _ef ＝Y ₁ －Y ₂ －L _ef x Sin (. DELTA.. Theta.) formula 2

In the above formula 2,. DELTA.YL _ef For representing the second lateral position deviation.

Step S323, calculating a desired yaw rate according to the preview distance, the vehicle speed information, and the second lateral position deviation, and calculating the rotation angle compensation result based on the desired yaw rate.

Specifically, by using a vehicle preview kinematics model, the yaw rate and the rotation angle compensation result of the expected cross can be calculated according to the second transverse position deviation. Wherein the vehicle preview kinematic model is as follows

Formula 3 and formula 4 show:

in the above formula, ω _des For representing the desired yaw rate, V for representing the current speed information of the vehicle. Delta. For the preparation of a coating _Curv For representing the above-mentioned rotation angle compensation result; from equation 4, δ _Curv The value of (d) may be positive or negative. m is used to represent vehicle mass; cr is used for representing the rear wheel cornering stiffness of the vehicle, cf is used for representing the front wheel cornering stiffness of the vehicle, lr is used for representing the distance from the center of a rear axle of the vehicle to the center of mass of the vehicle, and lf is used for representing the distance from the center of a front axle of the vehicle to the center of mass of the vehicle; wherein m and C _r 、C _f 、l _r And l _f Each constant can be obtained in advance through vehicle factory configuration information and the like and stored.

Through the steps S321 to S323, the second transverse position deviation is obtained through calculation of the preview distance and the preview point, the vehicle preview kinematic model is utilized, and the rotation angle compensation result is obtained through calculation based on the second transverse position deviation, so that a distance ahead of the vehicle is previewed in the vehicle running process, an accurate vehicle preview error is obtained through solution, a rotation angle compensation result aiming at the front wheel rotation angle result is obtained through calculation based on the error, and the accuracy and the stability of the vehicle transverse control are further improved.

In some embodiments, the generating the lateral control result according to the front wheel steering angle result and the steering angle compensation result further includes:

and step S331, generating a target steering angle result according to the front wheel steering angle result and the steering angle compensation result.

Specifically, the target rudder angle result after compensation may be generated by performing calculation processing such as addition or multiplication of the front wheel rudder angle results based on the rudder angle compensation result obtained by the above calculation. Taking the above equation 4 as an example, the target rudder angle result may be generated by directly adding the rudder angle compensation result calculated by equation 4 to the front wheel rudder angle result.

Step S332, obtaining a transmission ratio between the target steering angle result and the steering wheel, and generating the lateral control result according to the transmission ratio and the target steering angle result.

Wherein, the transmission ratio between the front wheel corner of the vehicle and the steering wheel corner can be obtained by pre-calculation, and the target corner result is converted into the steering wheel rotating angle according to the transmission ratio; and taking the steering wheel rotation angle as the transverse control result, sending the steering wheel rotation angle to a steering execution control mechanism of the vehicle, and finally realizing the rotation control of the steering wheel by the steering execution control mechanism based on the steering wheel rotation angle so as to further realize the transverse control of the vehicle.

Through the steps S331 to S332, the front wheel steering angle result is subjected to preview compensation through the steering angle compensation result to obtain a target steering angle result, and the target steering angle result is converted into the steering wheel steering angle result based on the transmission ratio, so that the steering execution control mechanism can be instructed to control the vehicle steering based on the steering wheel steering angle result, the efficiency and the accuracy of the vehicle transverse control are higher, and the improvement of the efficiency and the accuracy of the vehicle transverse control is facilitated.

In some embodiments, the generating the dynamic control weight of the vehicle based on the mapping relationship between the vehicle speed information and the road curvature information further includes:

and step S221, historical vehicle speed information and historical road curvature information are obtained, and a corresponding preset control weight value is obtained through calculation according to the historical vehicle speed information and the historical road curvature information.

Specifically, the historical vehicle speed information and the historical road curvature information may be acquired in a manner of: acquiring simulation experiment results, or acquiring a series of simulation experiment results or test data in advance by utilizing algorithms such as an interpolation method and the like through the test data of automatic driving of the vehicle in a park or other working condition scenes; and then, the preset control weight values corresponding to the discrete historical vehicle speed information and the historical road curvature information can be calculated. The historical vehicle speed information, the historical road curvature information and the preset control weight value obtained through calculation in the above mode can be statistical data in the forms of mean values or median values and the like.

Step S222, obtaining a preset mapping table according to the historical vehicle speed information, the historical road curvature information, and the preset control weight value, performing query processing on the preset mapping table according to the mapping relationship between the vehicle speed information and the road curvature information, and generating the dynamic control weight value according to the queried preset control weight value.

The preset mapping relation table is used for indicating the corresponding relation among the vehicle speed information, the road curvature information and the control weight; the preset mapping relation table can be represented in a form of a chart, and table 1 is a two-dimensional table of the preset mapping relation table, as shown in table 1:

TABLE 1 Preset mapping relationship two-dimensional Table

In table 1, the first row data is used to indicate the historical vehicle speed information, and the unit may be km/h; the first column data may represent the historical road curvature information and may be in m ^-1 (ii) a And the data filled in the tables with overlapped rows and columns are the preset control weight values corresponding to the historical speed information and the historical road curvature information. It can be understood that each data in the preset relationship two-dimensional table may be a real vehicle calibration value; alternatively, the remaining portion of the data in the table may be determined by determining a portion of the calibration values and then using an algorithm such as a median method. Based on the table 1, it can be known that the larger the curvature of the road is, the larger the corresponding control weight value is, and the larger the vehicle speed is, the smaller the corresponding control weight value is, so that when the vehicle speed and the curvature input from the outside are linearly changed, the control weight value in the two-dimensional table is also linearly changed in a corresponding trend. After the current vehicle speed information and the current road curvature information of the vehicle are obtained through the steps, the preset mapping relation table can be inquired based on the vehicle speed information and the road curvature information, and finally the preset mapping relation table is inquiredAnd a certain preset control weight value corresponding to the mapping relation between the vehicle speed information and the road curvature information in the preset mapping relation table, wherein the inquired preset control weight value is the dynamic control weight.

Through the steps S221 to S222, the preset mapping relation table is queried based on the mapping relation between the vehicle speed information and the road curvature information, so that the current dynamic control weight can be quickly and accurately queried, the control weight parameter adjustment method with small calculation amount is realized, and the efficiency and the accuracy of the vehicle transverse control method are further improved.

In some embodiments, the calculating the front wheel steering result according to the first lateral position deviation and the dynamic control weight further includes: and performing iterative solution calculation according to the first transverse position deviation and the dynamic control weight by using a preset LQR controller model to obtain an objective function value, and calculating according to the objective function value to obtain the front wheel steering angle result.

Further, the above iterative solution calculation using the preset LQR controller model according to the first lateral position deviation and the dynamic control weight to obtain the objective function value further includes the following steps:

in step S223, a state weight matrix is generated at least according to the first lateral position deviation, and a control weight matrix is generated according to the dynamic control weight.

Wherein the state weight matrix may be represented as Q = diag [ Q1, Q2, Q3, Q4]; diag [ ] is used to represent the diagonal matrix. Each matrix element Q1, Q2, Q3, Q4 on the diagonal of the matrix is used for expressing the first lateral position deviation, the change rate of the lateral position deviation, the course error, the change rate of the course error respectively; the transverse position deviation change rate can be calculated based on a series of first transverse position deviations acquired in a certain time period; the course error and the course error change rate can be calculated based on the preset track reference point and the self-vehicle motion state information collected in real time by the vehicle sensing equipment. The above control weight matrix may be represented as R = [ R ]; r is used to represent the dynamic control weights described above.

Step S224, obtaining a preset LQR state space equation and an objective function used for indicating a constraint relationship between the state weight matrix and the control weight matrix, and performing iterative solution on the objective function according to the LQR state space equation by using the LQR controller model to obtain the objective function value.

Specifically, the LQR state space equation may be pre-constructed; the LQR state space equation is a discrete equation, as shown in equation 5:

χ(k+1)＝A×χ(k)+B _d ×u+C _d equation 5

In the above equation 5, χ represents the state matrix, u represents the control matrix, A, B _d 、C _d K is a constant greater than 0, which is a coefficient of the above state space equation. Through the LQR controller module, an objective function value J can be obtained by carrying out iterative solution on the objective function; wherein the objective function is shown in equation 6:

J＝∑(χ ^T Qχ+u ^T ru) formula 6

In the above equation 6,% ^T Transposed matrix u for representing the state matrix χ ^T And substituting the formula 5 into the formula 6, performing iterative calculation on the formula 6 by using an LQR controller model, and finally calculating a function value K with the minimum value in the objective function values J so as to obtain an optimal solution K. The front wheel steering angle result can be obtained by conversion according to the calculated K value, and can be expressed as delta _LQR 。

According to the embodiment, the objective function is generated through dynamic control weight, the objective function is iteratively solved by using the LQR controller model to obtain an objective function value, and finally a front wheel steering angle result is obtained through calculation according to the objective function value, so that the self-adaptive LQR transverse control method is realized.

In some embodiments, the obtaining a first lateral position deviation between the vehicle and the preset track reference point further comprises:

step S211, obtaining vehicle state information of the vehicle, and obtaining a path planning track according to the vehicle state information; wherein the path planning trajectory includes a first reference point generated based on the vehicle state information, the first reference point being located under a global coordinate system.

The vehicle state information may include vehicle motion state information and vehicle position state information; the vehicle state information can be acquired in real time through vehicle sensing equipment. A path planning trajectory for the current map can be calculated from the vehicle state information. It will be appreciated that each reference point in the path planning trajectory is located under the global coordinate system and serves as the first reference point.

Step S212, obtaining a coordinate transformation relationship between the global coordinate system and the vehicle coordinate system of the vehicle, transforming the first reference point to the vehicle coordinate system according to the coordinate transformation relationship, and obtaining a second reference point after coordinate transformation.

The transformation relation between the global coordinate system and the own vehicle coordinate system can be obtained by calibrating a camera of the vehicle; for example, the camera device may perform camera calibration by deploying a calibration object such as a calibration board installed in the field, thereby obtaining a coordinate conversion relationship between the own vehicle coordinate system and the global coordinate system. And performing coordinate conversion on the first reference point according to the coordinate conversion relation to obtain a second reference point under the own vehicle coordinate system so as to realize coordinate unification between each reference point and the vehicle on the path specification track. In addition, the unified coordinate system is a self-vehicle coordinate system taking a self-vehicle position as an original point, so that subsequent calculation can be performed under the self-vehicle coordinate system conveniently, the transverse control of the vehicle can be realized, and the improvement of the accuracy of the transverse control of the vehicle is facilitated.

And step S213, calculating to obtain a track point which is closest to the centroid position of the vehicle in the second reference point, determining the preset track reference point based on the track point, and calculating to obtain the first transverse position deviation.

The centroid position of the vehicle can be determined by the vehicle position state information. Specifically, two adjacent track points closest to the centroid position of the vehicle in the second reference point may be calculated, the preset track reference point is determined by using a linear interpolation method, and then the first transverse position deviation between the vehicle and the preset track reference point is calculated.

Through the steps S211 to S213, coordinate conversion is performed on the plurality of first reference points on the path planning track to obtain the second reference point in the coordinate system of the host vehicle, so that each reference point on the path planning track and the position information of the vehicle can be unified in the same coordinate system, which is beneficial to improving the calculation efficiency of the first transverse position deviation, and further improving the efficiency of the transverse control of the vehicle.

The embodiment of the present application will be described in detail with reference to practical application scenarios, and fig. 4 is a flowchart of a vehicle lateral control method according to a preferred embodiment of the present application, and as shown in fig. 4, the flowchart includes the following steps:

step S401, acquiring current own vehicle position state information and own vehicle motion state information; and acquiring a preset path planning track. The vehicle position state information comprises information such as a vehicle position or vehicle mass center position information and a course angle, and the vehicle motion state information comprises information such as a vehicle speed, a yaw angular velocity and a steering execution control mechanism.

Step S402, selecting a current preset track reference point according to the current position state information and the current motion state information of the vehicle; and selecting a current preview point according to the path planning track.

Step S403, calculating a lateral error including a first lateral position deviation and a second lateral position deviation; specifically, calculating to obtain a vehicle mass center deviation, namely a first transverse position deviation, based on the preset track reference point; and calculating the position deviation caused by the heading or the road curvature based on the pre-aiming point, namely obtaining a second transverse position deviation.

Step S404, obtaining road curvature and vehicle speed information according to the vehicle position state information and the vehicle motion state information, and adjusting a weight coefficient according to the road curvature and the vehicle information to generate a current dynamic control weight of the vehicle.

Step S405, according to the first transverse position deviation and the dynamic control weight, calculating by using an LQR controller model to generate a front wheel steering angle result; and determining a pre-aiming distance and vehicle speed information according to the path planning track, and calculating and generating a corner compensation result by using a vehicle pre-aiming kinematic model according to the pre-aiming distance, the vehicle speed information and the second transverse position deviation.

And step S406, calculating to obtain the steering wheel angle quantity according to the front wheel steering angle result and the steering angle compensation result.

Step S407, implementing lateral control of automatic vehicle driving based on the steering wheel angle calculated in the above step; and continuously acquiring the position information, the motion information and the path planning track of the vehicle at the next moment based on the real-time feedback result of the automatically driven vehicle, and realizing the transverse control of the automatic driving of the vehicle until the vehicle stops or reaches the destination.

Through the steps S401 to S407, the transverse deviation caused by the vehicle slip angle and the course angle and the transverse position deviation caused by the curvature of the road in front of the vehicle are calculated according to the pre-aiming kinematic model, so that the advanced control of the vehicle is ensured, the rapid convergence of the control under the condition that the vehicle bends or swings is ensured, and the control stability and the accuracy of the tracking track are ensured; meanwhile, a method for dynamically adjusting the control weight by taking the speed and the curvature of the road as LQR weight parameter adjustment basis is also provided, so that the stability of the LQR parameter adjustment strategy is ensured, poor control circulation can be reduced only according to the motion state of the vehicle and the external road conditions, the vehicle swing caused by the conditions of excessive control overshoot and the like which possibly occur in special road working conditions such as a curve or a lane change road with a large curvature and the like is avoided, and the control stability under each scene is realized.

It should be noted that the steps illustrated in the above-described flow diagrams or in the flow diagrams of the figures may be performed in a computer system, such as a set of computer-executable instructions, and that, although a logical order is illustrated in the flow diagrams, in some cases, the steps illustrated or described may be performed in an order different than here.

The present embodiment further provides a vehicle lateral control device, which is used to implement the foregoing embodiments and preferred embodiments, and the description of the device is omitted. As used hereinafter, the terms "module," "unit," "subunit," and the like may implement a combination of software and/or hardware for a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Fig. 5 is a block diagram of a vehicle lateral control apparatus according to an embodiment of the present application, as shown in fig. 5, the apparatus including: an acquisition module 52, a weighting module 54, and a generation module 56; the obtaining module 52 is configured to obtain vehicle speed information and road curvature information of the vehicle, and a first lateral position deviation between the vehicle and a preset track reference point; the weight module 54 is configured to generate a dynamic control weight of the vehicle based on a mapping relationship between the vehicle speed information and the road curvature information, and calculate a front wheel steering angle result according to the first lateral position deviation and the dynamic control weight; the generating module 56 is configured to generate a lateral control result of the vehicle according to the front wheel steering angle result, and perform lateral control on the vehicle according to the lateral control result.

Through the above embodiment, the weight module 54 generates the dynamic control weight through the mapping relationship between the vehicle speed information and the road curvature information, and calculates the front wheel steering angle result according to the dynamic control weight and the acquired first transverse position deviation, thereby implementing real-time dynamic adjustment of the control weight parameter, effectively improving the automatic driving control precision and the adaptability, solving the problem of low stability of the transverse control of the vehicle, and implementing an accurate and stable transverse vehicle control device.

In some embodiments, the generating module 56 is further configured to obtain a pre-aiming distance and a preset path planning trajectory, and calculate a pre-aiming point according to the vehicle speed information and the path planning trajectory; the generating module 56 calculates a second transverse position deviation between the vehicle and the preview point according to the preview distance, and obtains a rotation angle compensation result according to the second transverse position deviation; the generating module 56 generates the lateral control result based on the front wheel steering result and the steering angle compensation result.

In some embodiments, the generating module 56 is further configured to obtain a vehicle heading angle deviation, and calculate a heading angle lateral deviation according to the pre-aiming distance and the vehicle heading angle deviation; the generating module 56 calculates a first vertical distance between the preview point and a forward line of the center of the vehicle, and a second vertical distance between the center of the rear axle of the vehicle and the path planning track; the generating module 56 calculates the second lateral position deviation according to the first vertical distance, the second vertical distance and the course angle lateral deviation; the generating module 56 calculates a desired yaw rate according to the preview distance, the vehicle speed information and the second lateral position deviation, and calculates the rotation angle compensation result based on the desired yaw rate.

In some embodiments, the generating module 56 is further configured to generate a target steering angle result according to the front wheel steering angle result and the steering angle compensation result; the generation module 56 obtains a target steering angle result and a gear ratio between the steering wheels, and generates the lateral control result based on the gear ratio and the target steering angle result.

In some embodiments, the weight module 54 is further configured to perform an iterative solution calculation according to the first lateral position deviation and the dynamic control weight by using a preset LQR controller model to obtain an objective function value, and calculate the front wheel steering angle result according to the objective function value.

In some embodiments, the weight module 54 is further configured to generate a state weight matrix according to at least the first lateral position deviation and a control weight matrix according to the dynamic control weight; the weight module 54 obtains a preset LQR state space equation, generates a target function for indicating a constraint relationship between the state weight matrix and the control weight matrix according to the LQR state space equation, and performs iterative solution on the target function by using the LQR controller model to obtain the target function value.

In some embodiments, the weighting module 54 is further configured to obtain historical vehicle speed information and historical road curvature information, and calculate a corresponding preset control weight value according to the historical vehicle speed information and the historical road curvature information; the weight module 54 obtains a preset mapping table according to the historical vehicle speed information, the historical road curvature information, and the preset control weight value, performs query processing on the preset mapping table according to the mapping relationship between the vehicle speed information and the road curvature information, and generates the dynamic control weight value according to the queried preset control weight value.

In some embodiments, the obtaining module 52 is further configured to obtain vehicle state information of the vehicle, and obtain a path planning track according to the vehicle state information; the path planning track comprises a first reference point generated based on the vehicle state information, and the first reference point is positioned under a global coordinate system; the obtaining module 52 obtains a coordinate transformation relationship between the global coordinate system and the vehicle coordinate system of the vehicle, and transforms the first reference point to the vehicle coordinate system according to the coordinate transformation relationship to obtain a second reference point after coordinate transformation; the obtaining module 52 calculates a track point closest to the centroid position of the vehicle in the second reference point, determines the preset track reference point based on the track point, and calculates the first transverse position deviation.

It should be noted that the above modules may be functional modules or program modules, and may be implemented by software or hardware. For a module implemented by hardware, the modules may be located in the same processor; or the modules can be respectively positioned in different processors in any combination.

The present embodiment also provides a vehicle lateral control system, and fig. 6 is a block diagram of a vehicle lateral control system according to an embodiment of the present application, and as shown in fig. 6, the system includes: a control device 62 and a vehicle body 64; the control device 62 is connected to the vehicle body 64 and is used for executing any one of the vehicle transverse control methods in the above embodiments to control the vehicle body 62 to automatically steer. The control device 62 may be a chip, a microprocessor, or other devices integrated on the vehicle body 64 for controlling the vehicle body 64, or the control device 62 may also be a server or other devices that communicate with the vehicle body 64 through a remote or local area network, and the like, which are not described herein again.

Through the embodiment, the control device generates the dynamic control weight through the mapping relation between the vehicle speed information and the road curvature information, and calculates the front wheel steering angle result according to the dynamic control weight and the acquired first transverse position deviation, so that the real-time dynamic adjustment of the control weight parameters is realized, the automatic driving control precision and the self-adaptability are effectively improved, the problem of low stability of the transverse control of the vehicle is solved, and the accurate and stable transverse control system of the vehicle is realized.

In some embodiments, a computer device is provided, and the computer device may be a server, and fig. 7 is a structural diagram of the inside of a computer device according to the embodiment of the present application, as shown in fig. 7. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The database of the computer device is used for storing the lateral control results. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement the vehicle lateral control method described above.

Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

The present embodiment also provides an electronic device, comprising a memory having a computer program stored therein and a processor configured to run the computer program to perform the steps of any of the method embodiments described above.

Optionally, the electronic apparatus 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.

Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:

s1, vehicle speed information and road curvature information of the vehicle and a first transverse position deviation between the vehicle and a preset track reference point are obtained.

And S2, generating dynamic control weight of the vehicle based on the mapping relation between the vehicle speed information and the road curvature information, and calculating a front wheel steering angle result according to the first transverse position deviation and the dynamic control weight.

And S3, generating a transverse control result of the vehicle according to the front wheel steering angle result, and carrying out transverse control on the vehicle according to the transverse control result.

It should be noted that, for specific examples in this embodiment, reference may be made to examples described in the foregoing embodiments and optional implementations, and details of this embodiment are not described herein again.

In addition, in combination with the vehicle lateral control method in the above embodiments, the embodiments of the present application may be implemented by providing a storage medium. The storage medium having stored thereon a computer program; the computer program, when executed by a processor, implements any of the vehicle lateral control methods in the above embodiments.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct Rambus Dynamic RAM (DRDRAM), and Rambus Dynamic RAM (RDRAM), among others.

It should be understood by those skilled in the art that various features of the above-described embodiments can be combined in any combination, and for the sake of brevity, all possible combinations of features in the above-described embodiments are not described in detail, but rather, all combinations of features which are not inconsistent with each other should be construed as being within the scope of the present disclosure.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent application shall be subject to the appended claims.

Claims

1. A vehicle lateral control method, characterized in that the method comprises:

generating dynamic control weight of the vehicle based on the mapping relation between the vehicle speed information and the road curvature information, and calculating to obtain a front wheel steering angle result according to the first transverse position deviation and the dynamic control weight;

and generating a transverse control result of the vehicle according to the front wheel steering angle result, and carrying out transverse control on the vehicle according to the transverse control result.

2. The vehicle lateral control method of claim 1, wherein the generating a lateral control result of the vehicle as a function of the front wheel steering angle result comprises:

3. The vehicle lateral control method of claim 2, wherein the calculating a second lateral position deviation between the vehicle and the home sight point according to the home sight distance and the obtaining a rotation angle compensation result according to the second lateral position deviation comprises:

obtaining the deviation of the vehicle heading angle, and calculating to obtain the lateral deviation of the heading angle according to the pre-aiming distance and the deviation of the vehicle heading angle;

and calculating to obtain an expected yaw rate according to the pre-aiming distance, the vehicle speed information and the second transverse position deviation, and calculating to obtain the rotation angle compensation result based on the expected yaw rate.

4. The vehicle lateral control method according to claim 2, wherein the generating the lateral control result based on the front wheel steering angle result and the steering angle compensation result includes:

5. The vehicle lateral control method according to claim 1, wherein the calculating a front wheel steering angle result based on the first lateral position deviation and the dynamic control weight includes:

and performing iterative solution calculation according to the first transverse position deviation and the dynamic control weight by using a preset LQR controller model to obtain an objective function value, and calculating according to the objective function value to obtain a front wheel steering angle result.

6. The vehicle lateral control method according to claim 5, wherein the objective function value is obtained by performing iterative solution calculation according to the first lateral position deviation and the dynamic control weight by using a preset LQR controller model:

generating a state weight matrix according to at least the first transverse position deviation, and generating a control weight matrix according to the dynamic control weight;

7. The vehicle lateral control method according to claim 1, characterized in that the generating of the dynamic control weight of the vehicle based on the mapping relationship between the vehicle speed information and the road curvature information includes:

obtaining historical vehicle speed information and historical road curvature information, and calculating according to the historical vehicle speed information and the historical road curvature information to obtain a corresponding preset control weight value;

8. The vehicle lateral control method according to any one of claims 1 to 7, characterized in that acquiring a first lateral position deviation between the vehicle and the preset trajectory reference point includes:

acquiring vehicle state information of the vehicle, and acquiring a path planning track according to the vehicle state information; the path planning track comprises a first reference point generated based on the vehicle state information, and the first reference point is positioned under a global coordinate system;

calculating to obtain a track point closest to the centroid position of the vehicle in the second reference point, determining the preset track reference point based on the track point, and calculating to obtain the first transverse position deviation.

9. A vehicle lateral control apparatus, characterized in that the apparatus comprises: the device comprises an acquisition module, a weight module and a generation module;

the generating module is used for generating a transverse control result of the vehicle according to the front wheel steering angle result and carrying out transverse control on the vehicle according to the transverse control result.

10. A vehicle lateral control system, characterized in that the system comprises: a control device and a vehicle body;

the control device, connected to the vehicle body, for performing the vehicle lateral control method according to any one of claims 1 to 8.

11. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and the processor is configured to execute the computer program to perform the vehicle lateral control method of any of claims 1 to 8.

12. A storage medium, in which a computer program is stored, wherein the computer program is arranged to carry out the vehicle lateral control method according to any one of claims 1 to 8 when run.