CN115542813A - Unmanned vehicle control method, device, electronic device and storage medium - Google Patents

Abstract

The disclosure provides a method and a device for controlling an unmanned vehicle, electronic equipment and a storage medium, and relates to the technical field of unmanned driving. The method comprises the following steps: acquiring the track tracking precision, stability index and wheel slip rate of the unmanned vehicle under different operating conditions; determining the front wheel rotation angle and the wheel moment of the unmanned vehicle which tracks the target speed and runs by referring to the track information in a stable state under different running conditions according to the track tracking precision, the stability index and the wheel slip rate of the unmanned vehicle under different running conditions; and controlling the unmanned vehicle to run according to the determined front wheel turning angle and the determined wheel torque. The method and the device can comprehensively consider the vehicle stability and the tracking precision of the unmanned vehicle under different running conditions to control the running of the unmanned vehicle, and can realize the integrated coordination control of the trajectory tracking and the stability adapting to different running conditions.

Description

Unmanned vehicle control method, device, electronic device and storage medium

technical field

The present disclosure relates to the technical field of unmanned driving, and in particular to an unmanned vehicle control method, device, electronic equipment and storage medium.

Background technique

With the continuous development of electronic information and communication technology and the continuous improvement of related new infrastructure construction, the process of electrification, intelligence and networking of vehicles is accelerating. Compared with traditional vehicles, unmanned electric vehicles with four-wheel independent drive have significant advantages in reducing environmental pollution, reducing energy consumption, alleviating traffic congestion, improving road utilization, reducing vehicle safety accidents, and improving vehicle safety. It provides solutions to meet people's safe, comfortable and convenient daily life needs and efficient, energy-saving and intelligent travel needs.

Unmanned vehicles are a complex system, mainly including four core key technologies of environment perception, behavior decision-making, motion planning and trajectory tracking control. Among them, the trajectory tracking control is based on the road environment information and reference trajectory information obtained by the perception planning layer, combined with the state of the vehicle itself, by controlling the steering, acceleration or braking of the vehicle, while ensuring the stable driving of the vehicle, the tracking of the reference trajectory and the target vehicle speed can be realized. . Therefore, trajectory tracking control, as a functional module that controls the actual movement of the vehicle, is very important to ensure the stability, safety and comfort of the vehicle.

At present, most of the trajectory tracking control schemes for unmanned vehicles are based on the regular working conditions of low-to-medium vehicle speed and good road surface with fixed weights, and rarely consider the control of stability and desired vehicle speed at the same time, or combine stability control and trajectory tracking. The control is considered separately. As a result, once the operating conditions of the vehicle change, it is difficult for the controller to comprehensively consider the weight priorities of multiple control objectives such as stability and tracking accuracy, resulting in a significant decrease in trajectory tracking accuracy and even causing the vehicle to slip , instability and other dangerous working conditions, it is difficult to adapt to the complex and changeable real road traffic environment. Therefore, a coordinated control method for trajectory tracking and stability of unmanned vehicles (for example, four-wheel independent drive unmanned electric vehicles) is designed to improve the trajectory of unmanned vehicles under different operating conditions. Tracking accuracy, stability and working condition adaptability are technical problems to be solved urgently in this field.

It should be noted that the information disclosed in the above background section is only for enhancing the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to those of ordinary skill in the art.

Contents of the invention

The present disclosure provides an unmanned vehicle control method, device, electronic equipment and storage medium, at least to a certain extent, overcomes the difficulties in the related art to realize the tracking accuracy and stability of the unmanned vehicle under different operating conditions. Technical issues of coordinated control.

Other features and advantages of the present disclosure will become apparent from the following detailed description, or in part, be learned by practice of the present disclosure.

According to one aspect of the present disclosure, there is provided a method for controlling an unmanned vehicle, the method comprising: acquiring the trajectory tracking accuracy, stability index and wheel slip ratio of the unmanned vehicle under different operating conditions; according to the The trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions, determine the progress of the unmanned vehicle under different operating conditions to track the target vehicle speed and reference trajectory information in a steady state Wheel angle and wheel torque; according to the determined front wheel angle and wheel torque, control the driving of the unmanned vehicle.

According to another aspect of the present disclosure, there is also provided a control device for an unmanned vehicle, which includes: a state information acquisition module, used to acquire trajectory tracking accuracy and stability indicators of the unmanned vehicle under different operating conditions and wheel slip ratio; the control variable determination module is used to determine the unmanned vehicle in different operating conditions according to the trajectory tracking accuracy, stability index and wheel slip ratio of the unmanned vehicle under different operating conditions. Under working conditions, track the target vehicle speed and the front wheel angle and wheel torque of the reference trajectory information in a steady state; the control module is used to control the driving of the unmanned vehicle according to the determined front wheel angle and wheel torque.

According to another aspect of the present disclosure, there is also provided an electronic device, which includes: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the The executable instructions are used to execute any one of the unmanned vehicle control methods described above.

According to another aspect of the present disclosure, there is also provided a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the unmanned vehicle control method described in any one of the above is implemented.

The unmanned vehicle control method, device, electronic device, and computer-readable storage medium provided by the embodiments of the present disclosure obtain the trajectory tracking accuracy, stability index, and wheel slip of the unmanned vehicle under different operating conditions. Then, according to the trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions, it is determined that the unmanned vehicle can track the target speed and reference trajectory information in a stable state under different operating conditions. The front wheel angle and wheel torque can be determined in order to control the driving of the unmanned vehicle according to the determined front wheel angle and wheel torque. Through the embodiments of the present disclosure, the vehicle stability and tracking accuracy of the unmanned vehicle under different operating conditions can be comprehensively considered to control the driving of the unmanned vehicle, and the trajectory tracking and stability adapting to different operating conditions can be realized. integrated coordinated control.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description serve to explain the principles of the disclosure. Apparently, the drawings in the following description are only some embodiments of the present disclosure, and those skilled in the art can obtain other drawings according to these drawings without creative efforts.

Fig. 1 shows a flow chart of a method for controlling an unmanned vehicle in an embodiment of the disclosure;

FIG. 2 shows a schematic diagram of a specific implementation architecture of a control method for an unmanned vehicle in an embodiment of the present disclosure;

Fig. 3 shows a schematic diagram of a longitudinal PID motion controller in an embodiment of the present disclosure;

FIG. 4 shows a schematic diagram of a relative position model between a vehicle and a path in an embodiment of the present disclosure;

5 shows a schematic diagram of a seven-degree-of-freedom dual-track vehicle dynamics model in an embodiment of the present disclosure;

Fig. 6 shows a schematic diagram of a tire model model in an embodiment of the present disclosure;

Fig. 7 shows a schematic diagram of a stability index design based on the phase plane of the tire slip angle in an embodiment of the present disclosure;

8 shows a schematic diagram of an adaptive adjustment curve for vehicle trajectory tracking accuracy, maneuverability, and stability weights in an embodiment of the present disclosure;

FIG. 9 shows a schematic diagram of a four-wheel slip ratio deviation weight adaptive adjustment curve in an embodiment of the present disclosure;

Fig. 10 shows a schematic diagram of an unmanned vehicle control device in an embodiment of the present disclosure;

FIG. 11 shows a structural block diagram of an electronic device in an embodiment of the present disclosure;

Fig. 12 shows a schematic diagram of a computer-readable storage medium in an embodiment of the present disclosure.

detailed description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different network and/or processor means and/or microcontroller means.

The specific implementation manners of the embodiments of the present disclosure will be described in detail below in conjunction with the accompanying drawings.

In order to solve the problem of coordinated control of trajectory tracking accuracy and stability of vehicles under different operating conditions, an embodiment of the present disclosure provides a control method for unmanned vehicles, which can be applied to but not limited to four-wheel independent drive electric unmanned vehicles. Coordinated control of trajectory tracking and stability of a driving vehicle.

It should be noted that the method for controlling an unmanned vehicle provided in the embodiments of the present disclosure may be executed by any electronic device with computing and processing capabilities. In some embodiments, the unmanned vehicle control method provided in the embodiments of the present disclosure can be executed by a vehicle control device; in other embodiments, the unmanned vehicle control method provided in the embodiments of the present disclosure can be implemented by a remote In some other embodiments, the method for controlling an unmanned vehicle provided in the embodiments of the present disclosure may also be implemented by an on-vehicle control device and a remote control device in an interactive manner.

Figure 1 shows a flowchart of a control method for an unmanned vehicle in an embodiment of the disclosure. As shown in Figure 1, the control method for an unmanned vehicle provided in an embodiment of the disclosure includes the following steps:

S102, acquiring trajectory tracking accuracy, stability index and wheel slip ratio of the unmanned vehicle under different operating conditions.

It should be noted that the unmanned vehicle in the embodiments of the present disclosure may be, but not limited to, an electric unmanned vehicle driven independently by four wheels. to explain. For the control of unmanned vehicles in the related art, the stability control and the trajectory tracking control are considered separately. Once the working conditions of the vehicle change, it may cause the vehicle’s trajectory tracking accuracy to decrease, or may cause the vehicle to slip and fail. Wait for the dangerous situation. The four-wheel slip ratio deviation can reflect the rolling state of the wheels. In the embodiment of the present disclosure, the trajectory tracking accuracy, stability index and wheel slip ratio of the unmanned vehicle under different operating conditions can be obtained, and these control objectives can be integrated to obtain Realize the control of unmanned vehicles,

S104, according to the trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions, determine the tracking target speed and reference trajectory information of the unmanned vehicle under different operating conditions Front wheel angle and wheel torque.

During specific implementation, above-mentioned S104 can be realized through the following steps: with trajectory tracking accuracy, stability index and wheel slip rate target, build objective function; Determine the constraint condition of objective function; According to objective function and constraint condition, determine no The front wheel angle and wheel moment of the human-driven vehicle track the target speed and the reference trajectory information in a steady state under different operating conditions.

In some embodiments, the objective function is:

in,

u＝[δ _f T _fl T _fr T _rl T _rr s _v s _r ] ^T (2)

表示航向角偏差；e_wfl表示左前轮滑移率偏差；e_wfr表示右前轮滑移率偏差；e_wrl表示左后轮滑移率偏差；e_wrr表示右后轮滑移率偏差；V中的第一个元素表示参考前轮转角，取值为0；T_all表示总驱动或制动力矩；F_zf表示前轴垂直载荷；F_zr表示后轴垂直载荷。Among them, J represents the function value of the objective function; k represents the time; N _p represents the forecast time domain; η ^k represents the actual output at k time; η ^k _ref represents the reference output at k time; u ^k represents the actual control at k time V ^k represents the reference control value at time k; u ^k-1 represents the actual control value at time k-1; Q, S, R, P represent weight coefficients; δ _f represents the front wheel angle; T _fl represents the left front wheel Longitudinal driving or braking torque; T _fr represents the longitudinal driving or braking torque of the right front wheel; T _rl represents the longitudinal driving or braking torque of the left rear wheel; T _rr represents the longitudinal driving or braking torque of the right rear wheel; s _v and s _r represents the slack variable; v _y represents the lateral velocity; r represents the yaw rate; e _y represents the lateral displacement deviation;

Indicates the heading angle deviation; e _wfl indicates the slip rate deviation of the left front wheel; e _wfr indicates the slip rate deviation of the right front wheel; e _wrl indicates the slip rate deviation of the left rear wheel; e _wrr indicates the slip rate deviation of the right rear wheel; The first element in represents the reference front wheel angle, and the value is 0; T _all represents the total driving or braking torque; F _zf represents the vertical load of the front axle; F _zr represents the vertical load of the rear axle.

In some embodiments, in the embodiments of the present disclosure, the constraint conditions for the optimization of the above objective function may include:

Constraints on the front wheel angle:

δ _f min ≤ δ _f ≤ δ f _max (5)

Constraints for four tire longitudinal driving or braking moments:

Constraints for front wheel angle increment:

-Δδ _fmax ≤Δδ _f ≤Δδ _fmax (7)

Constraints for four tire longitudinal driving or braking torque increments:

-ΔT _ij,max ≤ΔT _ij ≤ΔT _ij,max (8)

Safe Phase Plane Constraints Constraints:

M|ξ _k |≤E+s _k (9)

in,

E＝[α^sat r^sat]，

M=[M ₁ |0 _2×8 ],

E=[α ^sat r ^sat ],

s _k ≥ 0, and s _k ＝su _k , s＝[0 _2×5 |I _2×2 ];

表示四个车轮的纵向力最大值；F_yij表示四个车轮的侧向力；

表示四个车轮的侧向力最大值；R_e表示车轮有效半径；Δδ_f表示前轮转角增量；Δδ_fmax表示前轮转角增量的最大值；ΔT_ij表示四个车轮纵向驱动或制动力矩增量；ΔT_ij,max表示四个车轮纵向驱动或制动力矩增量的最大值；M表示安全相平面约束相关的构造矩阵；ξ_k表示离散后的状态量；v_y表示侧向速度；r表示横摆角速度；e_y表示侧向位移偏差；

表示航向角偏差；e_wfl表示左前轮滑移率偏差；e_wfr表示右前轮滑移率偏差；e_wrl表示左后轮滑移率偏差；e_wrr表示右后轮滑移率偏差；α_f表示前轴车轮侧偏角；α_r表示后轴车轮侧偏角；E表示曲率因子；v_x表示纵向车速；l_r表示车辆质心到后轴的距离；α^sat表示后轮侧偏角饱和值；β^sat表示质心侧偏角；r^sat表示横摆角速度；s_k表示松弛变量；s表示系数；u_k表示离散后的控制量；I表示单位矩阵。Among them, δ _f represents the front wheel angle; δ _fmin represents the minimum value of the front wheel angle; δ _fmax represents the maximum value of the front wheel angle; T _ij represents the longitudinal driving or braking torque of the four wheels, ij = fl, fr, rl , rr, represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively; T _max represents the maximum driving or braking torque output by the motor;

Indicates the maximum longitudinal force of the four wheels; F _yij indicates the lateral force of the four wheels;

Represents the maximum lateral force of the four wheels; R _e represents the effective radius of the wheel; Δδ _f represents the increment of the front wheel angle; Δδ _fmax represents the maximum value of the front wheel angle increment; ΔT _ij represents the longitudinal driving or braking of the four wheels Torque increment; ΔT _ij,max represents the maximum value of the longitudinal driving or braking torque increment of the four wheels; M represents the construction matrix related to the safety phase plane constraints; ξ _k represents the discretized state quantity; v _y represents the lateral velocity ; r represents the yaw rate; e _y represents the lateral displacement deviation;

Indicates the heading angle deviation; e _wfl indicates the slip rate deviation of the left front wheel; e _wfr indicates the slip rate deviation of the right front wheel; e _wrl indicates the slip rate deviation of the left rear wheel; e _wrr indicates the slip rate deviation of the right rear wheel; _f represents the front axle wheel slip angle; α _r represents the rear axle wheel slip angle; E represents the curvature factor; v _x represents the longitudinal speed; l _r represents the distance from the center of mass of the vehicle to the rear axle; α ^sat represents the saturation of the rear wheel slip angle β ^sat represents the side slip angle of the center of mass; r ^sat represents the yaw rate; s _k represents the slack variable; s represents the coefficient; u _k represents the discretized control quantity; I represents the identity matrix.

In some embodiments, the weight coefficient of the output is adaptively adjusted by the following formula:

in,

表示侧向速度v_y的权重系数；Q_r表示横摆角速度r的权重系数；

表示侧向位移偏差e_y的权重系数；

表示航向角偏差

的权重系数；

表示四个车轮滑移率偏差的权重系数，ij＝fl,fr,rl,rr，分别表示左前轮、右前轮、左后轮、右后轮；ε表示稳定性指标；κ_ij表示四个车轮的滑移率；s₁＝400；s₂＝5；s₃＝400；s₄＝0.65；s₅＝500；s₆＝0.65；s₇＝500；s₈＝0.67；a₁＝1.5；a₂＝1.5；b₁＝1.2；b₂＝1.2；a'₁＝30；b'₁＝3；c'₁＝0.5；range＝0.15。Among them, Q represents the matrix symbol of the output weight coefficient;

Represents the weight coefficient of lateral velocity v _y ; Q _r represents the weight coefficient of yaw rate r;

Indicates the weight coefficient of lateral displacement deviation e _y ;

Indicates the heading angle deviation

The weight factor of;

Indicates the weight coefficients of the four wheel slip ratio deviations, ij=fl, fr, rl, rr, respectively represent the left front wheel, right front wheel, left rear wheel, right rear wheel; ε represents the stability index; κ _ij represents the four slip ratio of each wheel; s ₁ =400; s ₂ =5; s ₃ =400; s ₄ =0.65; s ₅ =500; _{s 6} =0.65; _{s 7} =500; 1.5; a ₂ =1.5; b ₁ =1.2; b ₂ =1.2; a' ₁ =30; b' ₁ =3; c' ₁ =0.5; range=0.15.

It should be noted that in the embodiments of the present disclosure, s ₁ , s ₂ , s ₃ , s ₄ , s ₅ , s ₆ , s ₇ , s ₈ , a ₁ , a ₂ , b ₁ , b ₂ , a' ₁ , The values of b' ₁ , c' ₁ and range are a set of reference values based on the debugging experience of the own system. Since the structural parameters of the controlled objects are different, in actual use, skilled technicians can make adjustments according to the characteristics of their own system. Debugging in order to achieve better control effect.

In some embodiments, the weight coefficient of the control variable is adaptively adjusted by the following formula:

in,

Adaptively adjust the weight coefficient of the control amount increment through the following formula:

表示前轮转角的权重系数；

表示左前轮纵向驱动或制动力矩的权重系数；

表示右前轮纵向驱动或制动力矩的权重系数；

表示左后轮纵向驱动或制动力矩的权重系数；

表示右后轮纵向驱动或制动力矩的权重系数；

和

表示松弛变量增量对应权重系数；S表示控制量增量权重系数的矩阵符号；

表示前轮转角增量的权重系数；

表示左前轮纵向驱动或制动力矩增量的权重系数；

表示右前轮纵向驱动或制动力矩增量的权重系数；

表示左后轮纵向驱动或制动力矩增量的权重系数；

表示右后轮纵向驱动或制动力矩增量的权重系数；a'₂＝15；b'₂＝3；c'₂＝0.6；rangeR＝300。Among them, R represents the matrix symbol of the weight coefficient of the control quantity;

Indicates the weight coefficient of the front wheel angle;

Indicates the weight coefficient of the longitudinal driving or braking moment of the left front wheel;

Indicates the weight coefficient of the longitudinal driving or braking moment of the right front wheel;

Indicates the weight coefficient of the longitudinal driving or braking moment of the left rear wheel;

Indicates the weight coefficient of the longitudinal driving or braking moment of the right rear wheel;

and

Represents the weight coefficient corresponding to the slack variable increment; S represents the matrix symbol of the weight coefficient of the control variable increment;

Indicates the weight coefficient of the front wheel rotation angle increment;

Indicates the weight coefficient of the left front wheel longitudinal driving or braking torque increment;

Indicates the weight coefficient of the right front wheel longitudinal driving or braking torque increment;

Indicates the weight coefficient of the left rear wheel longitudinal driving or braking torque increment;

Indicates the weight coefficient of the right rear wheel longitudinal driving or braking torque increment; a' ₂ =15; b' ₂ =3; c' ₂ =0.6; rangeR=300.

It should be noted that the values of a' ₂ , b' ₂ , c' ₂ and rangeR in the embodiments of the present disclosure are a set of reference values based on the debugging experience of the own system. Due to the different structural parameters of the controlled objects, In actual use, skilled personnel can debug according to their own system characteristics in order to obtain better control effects.

In some embodiments, the weight coefficient of the slack variable is adaptively adjusted by the following formula:

P＝[0 _1×5 σ _v ^P σ _r ^P ] (15)

表示松弛变量s_v的权重系数；

表示松弛变量s_r的权重系数。Among them, P represents the matrix symbol;

Indicates the weight coefficient of the slack variable s _v ;

Indicates the weight coefficient of the slack variable s _r .

S106. Control the driving of the unmanned vehicle according to the determined front wheel angle and wheel torque.

It should be noted that the control quantities used to control the driving of the unmanned vehicle are mainly the front wheel angle and the wheel torque, where the wheel torque includes the longitudinal driving or braking torque of each wheel. The front wheel angle and wheel torque for controlling the driving of the unmanned vehicle in the above S106 are determined by comprehensively considering the trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions. Therefore, the present disclosure The unmanned vehicle control method provided in the embodiment can ensure that the vehicle tracks the target vehicle speed and the reference trajectory in a steady state under different operating conditions, which not only meets the stability requirements of the vehicle, but also meets the trajectory tracking accuracy of the vehicle.

It can be seen from the above that the unmanned vehicle control method provided in the embodiment of the present disclosure, by obtaining the trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions, and then according to the unmanned vehicle Trajectory tracking accuracy, stability index and wheel slip rate under different operating conditions, determine the front wheel angle and wheel torque of the unmanned vehicle to track the target speed and reference trajectory information in a steady state under different operating conditions, In order to control the driving of the unmanned vehicle according to the determined front wheel angle and wheel torque. Through the embodiments of the present disclosure, the vehicle stability and tracking accuracy of the unmanned vehicle under different operating conditions can be comprehensively considered to control the driving of the unmanned vehicle, and the trajectory tracking and stability adapting to different operating conditions can be realized. integrated coordinated control.

In some embodiments, the unmanned vehicle control method provided in the embodiments of the present disclosure may further include the following steps: obtaining the target speed and reference trajectory information of the unmanned vehicle; , to determine the front wheel angle of the unmanned vehicle tracking target speed and reference trajectory information; according to the target speed and actual speed of the unmanned vehicle, determine the total driving or braking torque required for the unmanned vehicle to track the target speed; according to The vertical load distribution of the front and rear axles of the unmanned vehicle, the total driving or braking torque required for the unmanned vehicle to track the target speed is distributed to each wheel, and the longitudinal driving or braking torque of each wheel is obtained; according to the unmanned vehicle The wheel slip ratio under different operating conditions constrains the longitudinal driving or braking torque of each wheel.

Further, in some embodiments, the total driving or braking torque required for the unmanned vehicle to track the target vehicle speed can be determined by the following formula:

T _des =k ₁ (v _x -v _xdes )+k ₂ ∫(v _x -v _xdes )dt (16)

Among them, T _des represents the total driving or braking torque; v _x represents the actual vehicle speed; v _xdes represents the target vehicle speed; k ₁ represents the proportional coefficient; k ₂ represents the integral coefficient.

Furthermore, in some embodiments, the unmanned vehicle control method provided in the embodiments of the present disclosure can limit the total driving or braking torque required for the unmanned vehicle to track the target vehicle speed through the following steps : Obtain the maximum driving or braking torque output by the motor on the unmanned vehicle; according to the maximum driving or braking torque output by the motor on the unmanned vehicle, the total driving or braking torque required for the unmanned vehicle to track the target speed Perform limit processing.

In some embodiments, the total driving or braking torque required for the unmanned vehicle to track the target vehicle speed is limited by the following formula:

Among them, T _all represents the total driving or braking torque after limiting processing; T _des represents the total driving or braking torque before limiting processing; T _max represents the maximum driving or braking torque output by a single motor; n represents the output drive or the number of motors with braking torque.

In some embodiments, the unmanned vehicle control method provided in the embodiments of the present disclosure may further include the following steps: acquiring the lateral displacement deviation and Heading angle deviation; according to the lateral displacement deviation and heading angle deviation of the unmanned vehicle tracking the target vehicle speed and reference track information under different operating conditions, determine the unmanned vehicle tracking target vehicle speed and Trajectory tracking accuracy for driving with reference to trajectory information.

In some embodiments, the unmanned vehicle control method provided in the embodiments of the present disclosure may further include the following steps: obtaining the lateral speed, yaw rate, and front and rear axle wheel lateral deflection of the unmanned vehicle under different operating conditions According to the lateral speed, yaw rate and side slip angle of the front and rear axle wheels of the unmanned vehicle under different operating conditions, determine the tracking target speed and reference trajectory information of the unmanned vehicle under different operating conditions. stability indicator.

In some embodiments, the following formula is used to determine the stability index of the unmanned vehicle tracking the target vehicle speed and the reference trajectory information under different operating conditions:

(α_f,s,α_r,s)表示距离原点更近的鞍点坐标；

表示无人驾驶车辆当前状态到原点位置的距离。Among them, R ₁ ＝max(|α _f,sat |,|α _r,sat |) represents the larger value among the saturated side slip angle of the front wheel and the saturated side slip angle of the rear wheel;

(α _f,s ,α _r,s ) represents the saddle point coordinates closer to the origin;

Indicates the distance from the current state of the unmanned vehicle to the origin.

In some embodiments, the method further includes: determining lateral velocity, yaw rate, lateral displacement deviation, heading angle deviation, wheel slip rate, and front and rear axle wheel sideslip angles as state variables, and establishing a state space expression; According to the stable state of the unmanned vehicle under different operating conditions, the weight coefficients of the lateral vehicle speed, yaw rate and tracking deviation are adaptively adjusted.

Further, in some embodiments, the state space expression is established as:

in,

表示状态量的变化速度；ξ表示状态量；u表示控制量；f()表示状态量的变化速度与状态量、控制量之间的函数关系；η表示输出量；h()表示输出量与状态量之间的函数关系；α_f表示前轴车轮侧偏角；α_r表示后轴车轮侧偏角。in,

Indicates the change speed of the state quantity; ξ indicates the state quantity; u indicates the control quantity; f() indicates the functional relationship between the change speed of the state quantity and the state quantity and the control quantity; η indicates the output quantity; h() indicates the output quantity and The functional relationship between the state quantities; α _f represents the front axle wheel slip angle; α _r represents the rear axle wheel slip angle.

Further, in some embodiments, the weight coefficients of lateral vehicle speed, yaw rate and tracking deviation can be adaptively adjusted through the following steps: if the unmanned vehicle is in a stable state, then reduce the weight coefficient of lateral vehicle speed, Increase the weight coefficient of yaw angle and tracking deviation; if the unmanned vehicle is in an unstable state, increase the weight coefficient of lateral vehicle speed, and reduce the weight coefficient of yaw angle and tracking deviation.

以及实时车辆状态信息，通过设计PID控制器跟踪目标车速变化，得到所需的总驱动力矩T_all，即驾驶员的总力矩需求，之后按照前后轴垂直载荷分布情况对总的驱动力矩进行分配，得到参考四轮力矩值T_ref。之后设计基于MPC的一体化控制器，选择表征跟踪精度的侧向位移偏差和航向角偏差，描述车辆横摆动力学特性的侧向速度和横摆角速度，以及表征轮胎滚动状态的四轮滑移率偏差作为状态量，此外为了进一步保证车辆的稳定性，选择前后轴轮胎侧偏角作为状态量，通过基于前后轮侧偏角相平面设计的稳定性评价指标，实时对车辆的稳定状态进行判断，并设计一套基于该稳定性评价指标的轨迹跟踪精度、操纵性与稳定性目标的权重自适应调节策略，根据实时的轮胎滑移率信息，引入双曲函数对四轮滑移率偏差的权重进行相应调节，决策出相应的转角和力矩，保证车辆稳定行驶的同时，实现对参考轨迹和目标车速的跟踪。Figure 2 shows a specific implementation architecture of a control method for an unmanned vehicle in an embodiment of the disclosure, which can be applied but not limited to trajectory tracking and stability coordination of four-wheel independent drive electric unmanned vehicles for different operating conditions Control, as shown in Figure 2, the general idea is: first, based on the target vehicle speed v _xref and reference trajectory information Y _ref and

As well as real-time vehicle status information, by designing a PID controller to track the target vehicle speed change, the required total drive torque T _all is obtained, that is, the driver's total torque demand, and then the total drive torque is distributed according to the vertical load distribution of the front and rear axles. The reference four-wheel torque value T _ref is obtained. Then design an integrated controller based on MPC, select the lateral displacement deviation and yaw angle deviation to characterize the tracking accuracy, the lateral velocity and yaw rate to describe the vehicle yaw dynamics, and the four-wheel slip rate to characterize the tire rolling state The deviation is used as the state quantity. In addition, in order to further ensure the stability of the vehicle, the side slip angle of the front and rear axle tires is selected as the state quantity, and the stability of the vehicle is judged in real time through the stability evaluation index based on the phase plane design of the front and rear wheel side slip angle. And design a set of weight adaptive adjustment strategies based on the trajectory tracking accuracy, maneuverability and stability goals based on the stability evaluation index, according to the real-time tire slip rate information, introduce the weight of the hyperbolic function to the four-wheel slip rate deviation Make corresponding adjustments, determine the corresponding rotation angle and torque, and realize the tracking of the reference trajectory and the target vehicle speed while ensuring the stable driving of the vehicle.

During specific implementation, the following steps may be included:

1) Establish a PI longitudinal motion controller to calculate the total driving or braking torque required for the unmanned vehicle to track the target speed and reference trajectory information:

As shown in Figure 3, according to the deviation between the current vehicle speed (actual vehicle speed) and the desired vehicle speed (target vehicle speed), the proportional integral principle is used to calculate the total driving torque required to track the desired vehicle speed. The specific calculation formula is shown in formula (16), I won't repeat them here.

Then, according to the maximum driving or braking torque T _max that can be output by a single motor, the total driving or braking torque is limited, and the actual total driving or braking torque T _all is obtained as:

Thereafter, according to the front and rear axle load distribution, the total driving/braking torque T _all is distributed, and the wheels on the left and right sides are evenly distributed as the reference control variable V, as shown in the above formula (4).

2) Establish an integrated controller based on MPC to realize coordinated control of trajectory tracking and stability:

Combined with the relative position model of the vehicle and the path shown in Figure 4 and the seven-degree-of-freedom dual-track vehicle dynamics model shown in Figure 5, the process of establishing the prediction model is described in detail:

A1. Establish state space expression:

The lateral displacement and heading angle deviation derivatives are calculated based on the relative position model of the vehicle and the path, and the calculation formulas are as follows:

Based on the seven-degree-of-freedom vehicle dynamics model, the lateral vehicle speed, yaw rate, four-wheel slip rate deviation, and side slip angle change rate are calculated. The calculation formulas are as follows:

Among them, Mz is the external yaw moment generated by the longitudinal force of the four wheels around the center of mass of the vehicle, specifically expressed as:

Among them, κ(ρ) is the curvature of the road; m is the mass of the vehicle; I _z is the moment of inertia of the vehicle around the z-axis, v _x and v _y are the longitudinal and lateral vehicle speeds, r is the yaw rate, and δ is the front wheel Corner, F _xij , F _yij are tire longitudinal force and lateral force respectively, where the subscripts ij=fl, fr, rl, rr represent left front wheel, right front wheel, left rear wheel, right rear wheel respectively; l _a , l _b is the distance from the center of mass to the front and rear axles, and c is the wheelbase of the vehicle.

The derivative of the four-wheel slip ratio deviation is:

The desired angular velocity of the tire is:

Then the expected angular acceleration of tire rotation is:

Among them, ζ _r =-ζ _l =1;

The actual rotational angular acceleration of the tire is:

Among them, ω _ij is the actual rotation angular velocity of the tire, T _ij is the four-wheel moment, I _z is the moment of inertia, R _e is the effective radius of the wheel;

The side slip angle of the four tires can be written as:

Among them, ζ _f = -ζ _r = 1, δ _f = δ, δ _r = 0;

The derivative of the tire slip angle can be obtained as follows:

in,

After the derivation of the above formula, the state space expression shown in the above formula (19) can be established.

In order to ensure that the vehicle can track the reference trajectory well while driving stably, the determined state variable is shown in the above formula (20); the selected control quantity is shown in the above formula (2); the selected output quantity is shown in the above formula (3) Shown; the selected disturbance is shown in formula (22).

为估计得到的四轮纵向力。Among them, a _x is the longitudinal acceleration,

is the estimated four-wheel longitudinal force.

A2. Linearize the state space expression to obtain a linear time-varying system:

Tire stress plays a vital role in the handling stability and ride comfort of the vehicle. The unified tire model (UniTire tire model) shown in FIG. For description, the model can uniformly express the tire longitudinal slipping characteristics of pure working conditions and compound working conditions, and the specific expression form is:

为无量纲的总切向力；F_x和F_y分别表示实际的纵向力和侧向力；E为曲率因子；μ为方向摩擦系数；F_z为垂直载荷；φ_x，φ_y和φ分别表示相对纵向、侧向和综合滑移率，定义为：in,

is the dimensionless total tangential force; F _x and F _y represent the actual longitudinal force and lateral force respectively; E is the curvature factor; μ is the direction friction coefficient; F _z is the vertical load; φ _x , φ _y and φ respectively Indicates the relative longitudinal, lateral and combined slip ratios, defined as:

Among them, K _x , K _y are longitudinal slip and cornering stiffness of tire respectively; F _z is vertical load; μ _x , μ _y are longitudinal and lateral friction coefficients respectively, S _x and S _y are tire longitudinal slip rate respectively and lateral slip rate, the calculation formula is as follows:

Among them, R _e is the effective rolling radius; V _sx and V _sy represent the longitudinal and lateral slip velocity, respectively.

After bringing the above tire force into the state space equation, a nonlinear vehicle dynamics model will be obtained as a predictive model.

In order to meet the real-time requirements of the controller in the actual application process, the model (state space expression) must be properly linearized. According to the Taylor expansion formula, Taylor expansion is carried out at the operating point (ξ ₀ (k), u ₀ (k), w ₀ (k)), only the first term is kept, and all higher-order terms are ignored, and the following linear time-varying system is obtained :

Among them, A(t) represents the coefficient matrix of the state quantity, B(t) represents the coefficient matrix of the control quantity, and D(t) represents the coefficient matrix of the disturbance quantity;

A3. The state space expression is discretized by the first-order difference quotient method, and the discretized state space expression is obtained as:

ξ(k+1)=A(k)ξ(k)+B(k)u(k)+D(k)w(k) (39)

In the formula, ξ(k) represents the discretized state quantity, u(k) represents the discretized control quantity, and A(k) represents the discretized state quantity coefficient matrix, satisfying A(k)=I+A(t) T, B(k) and D(k) respectively denote the discretized control and disturbance coefficient matrices, satisfying B(k)=B(t)T, D(k)=D(t)T; where, I Represents the identity matrix; T represents the sampling period.

Due to the large dimension of the system matrix, in order to reduce the huge amount of calculation and reduce the error rate of the manual derivation operation, the jacobian function of matlab is used to solve the state quantity, control quantity and disturbance quantity coefficient matrices A(k), B(k), D (k);

A4. Calculate the expected reference output:

Taking the vehicle speed at the current moment and the front wheel angle determined by the controller at the previous moment as input, the desired yaw rate is calculated by the two-degree-of-freedom vehicle model as:

In the formula, r _des is the desired yaw rate, r ₀ and r _max are the target yaw rate and its maximum value respectively, specifically expressed as:

Among them, μ is the adhesion coefficient of the road surface; C _r is the stiffness of the rear wheel; C _f is the stiffness of the front wheel; l _f is the distance from the center of mass of the vehicle to the front axle; l _r is the distance from the center of mass of the vehicle to the rear axle.

When the center-of-mass slip angle β is small, the desired lateral vehicle speed is defined as the lateral speed of the actual vehicle. Once the center-of-mass slip angle increases and exceeds a certain threshold, the desired lateral vehicle speed is set to zero, that is:

The center of mass sideslip angle threshold is: β _max =atan(0.02μg), and the expected value of the lateral displacement and heading angle deviation that characterizes the tracking accuracy is 0, namely:

In order to keep the tires in a pure rolling state as much as possible, the desired speed is set to the pure rolling state of the tires. While controlling the vehicle handling stability, it also controls the slip rate of the wheels to prevent excessive wheel slippage, so four-wheel slippage The expected value of rate deviation is 0, namely: e _wij,des =0.

So the total reference output is:

表示期望的航向角偏差；e_wfl,des表示期望的左前轮滑移率偏差；e_wfr,des表示期望的右前轮滑移率偏差；e_wrl,des表示期望的左后轮滑移率偏差；e_wrr,des表示期望的右后轮滑移率偏差。Among them, η _ref represents the desired reference output; v _ydes represents the desired lateral velocity; r _des represents the desired yaw rate; _eydes represents the desired lateral displacement deviation;

Indicates the expected heading angle deviation; e _{wfl, des} indicates the expected left front wheel slip rate deviation; e _{wfr, des} indicates the expected right front wheel slip rate deviation; e wrl, _des indicates the expected left rear wheel slip rate Deviation; e _{wrr, des} represents the desired right rear wheel slip ratio deviation.

A5. Establish the objective function:

Assuming that the current moment is k, in order to calculate the front wheel angle and four-wheel torque required for the vehicle to quickly and smoothly track the reference trajectory, an objective function as shown in the above formula (1) is established, where the first item is the comparison between the actual output and the reference The penalty for the deviation between outputs is used to ensure the trajectory tracking accuracy and vehicle stability. The second item is the penalty for the deviation between the front wheel angle amplitude and the actual torque output and the reference value. The torque determined by the normal working condition should track the change of the driver's expectation as much as possible, so as to better track the expected vehicle speed. The third item is the penalty for the increment of the control amount to ensure the smooth change of the actuator. The fourth item is the control of the safety phase plane. The penalty of the slack variable ensures the feasibility of the controller solution.

A6. Consider the relevant constraints:

Firstly, considering the physical constraints of the actuator and the frictional ellipse constraints, the front wheel rotation angle and the four-wheel torque range are given, as shown in the above formula (5) and formula (6), respectively.

In order to ensure the smooth change of the actuator, improve the comfort of the vehicle and the comprehensive control effect, the increment of the control amount is constrained, and the constraint formula is shown in the above formula (7) and formula (8).

In order to ensure the stability of the vehicle, the safety phase plane constraints are designed based on the side slip angle β ^e obtained from the peak side slip angle and the yaw rate r ^e , as shown in the above formula (9), and will not be repeated here.

A7. Calculation of vehicle stability evaluation index:

The quantitative stability evaluation index based on the phase plane of front and rear wheel slip angles is adopted, as shown in formula (18).

的圆，由于此时车辆前后轮侧偏角都达到了较大的值，并且一部分超过饱和值，因而状态位于该区域时车辆存在失稳的可能性。区域1被定义为不稳定区域，它是以原点为圆心，半径为

的圆，其中点(α_f,s,α_r,s)表示距离原点更近的鞍点坐标，前轮或后轮侧偏角进入到严重下降区域，车辆容易失去转向能力，或发生“甩尾”，为不稳定区域。Combining with the stability index design based on the tire slip angle phase plane in Figure 7, area 3 represents the stable area, which is a circle with the origin as the center and radius R ₁ , R ₁ =max(|α _f,sat |,| α _r,sat |) indicates the larger value of the front or rear wheel saturation side slip angle, in which the vehicle has better stability, and the main control objectives are the trajectory tracking accuracy and maneuverability of the vehicle; area 2 represents The transition area, which is centered at the origin and has a radius of

The circle of , since the side slip angles of the front and rear wheels of the vehicle have reached a large value at this time, and some of them exceed the saturation value, so the vehicle may be unstable when the state is in this area. Region 1 is defined as an unstable region, which is centered at the origin and has a radius of

, where the point (α _f,s ,α _r,s ) represents the saddle point coordinates that are closer to the origin, the front or rear wheel slip angle enters the serious drop zone, and the vehicle is prone to lose steering ability, or "flick" ”, which is an unstable region.

表示当前车辆实际状态到原点位置的距离。

Indicates the distance from the actual state of the current vehicle to the origin.

When ε∈(0,1], the vehicle state is stable, and the larger the value of ε, the higher the degree of stability; when ε∈(-1,0], the vehicle state is in the transition region, and the vehicle may be unstable ; When ε∈[-2,-1], the vehicle is in the limit state and is about to lose stability.

A8. Weight adaptive adjustment strategy based on quantitative stability evaluation indicators:

Trajectory tracking accuracy is similar to the vehicle's maneuverability control objectives, but the maneuverability and stability control objectives are usually contradictory. Therefore, in order to better meet different operating conditions, the vehicle's trajectory tracking accuracy, maneuverability, stability In order to control the weight priority of control objectives, a set of weight adaptive adjustment strategy based on stability evaluation index and hyperbolic tangent slip rate deviation weight adaptive adjustment based on four-wheel slip rate is designed. Specifically, the above formula (11) Show.

Combined with the tracking accuracy, maneuverability and stability weight adaptive graph in Figure 8, the vehicle is in a stable state when ε≥0.2, and the trajectory tracking accuracy and vehicle maneuverability are the main control objectives, so the weight of lateral vehicle speed is small , the weight of yaw rate and tracking deviation is relatively large; when ε<0.2, with the decrease of ε, the stability of the vehicle gradually deteriorates, so the weight of lateral vehicle speed is gradually increased, and the weight of yaw rate and tracking deviation is correspondingly reduced Deviation weight, so as to realize adaptive adjustment. In the embodiment of the present disclosure, a hyperbolic function is introduced to adjust the weight adjustment of the four-wheel slip ratio deviation adaptively. According to the curve shown in FIG. After the slip rate increases, the corresponding rapid increase in weight will constrain the slip rate within a small range, prevent wheel slippage, and further improve the safety of the vehicle.

Therefore, the final output weight is:

The adaptive adjustment of the control variable weight based on the torque increment is specifically shown in the above formula (13); the control variable weight is shown in the above formula (12); the control increment weight is shown in the above formula (14); the slack variable The weights are shown in the above formula (15).

A9. Optimal solution of objective function:

Based on the objective function of formula (4), considering the constraints of the actuator and the safety phase plane, the optimization solution is performed by the qpOASESsolver solver, namely:

Solving the above objective function obtains a series of control input increments and slack variables in the control time domain:

表示t时刻的控制量增量；

表示t+1时刻的控制量增量；

表示t+N_c-1时刻的控制量增量；σ_v和σ_r表示松弛变量。Among them, Δu represents the control quantity increment;

Indicates the control quantity increment at time t;

Indicates the increment of control quantity at time t+1;

Indicates the increment of control quantity at time t+N _c -1; σ _v and σ _r represent slack variables.

The final control amount is the sum of the control amount corresponding to the first element in the above control sequence and the previous moment.

A10. Steps A1-A9 are repeated at time t+1, and the rolling optimization is repeated in this way, so as to track the reference trajectory.

It can be seen from the above that the unmanned vehicle control method provided in the embodiment of the present disclosure adopts the integrated control method based on MPC, comprehensively considers the trajectory tracking accuracy, the vehicle stability control target and the four-wheel slip rate control target, and through The stability evaluation index of the wheel slip angle phase plane design judges the running state of the vehicle, correspondingly adjusts the multiple control target weights of the MPC in real time, and finally decides the corresponding rotation angle and four-wheel torque, so as to adapt to different running conditions Integrated coordinated control of trajectory tracking and stability of working conditions.

Compared with the existing trajectory tracking controller, the unmanned vehicle control method provided in the embodiment of the present disclosure has the following advantages:

1) The trajectory tracking and stability coordination control method of four-wheel independent driving unmanned electric vehicles for different operating conditions can ensure that the vehicle has high stability while tracking the reference trajectory.

2) An integrated controller for different operating conditions is designed based on the model predictive control algorithm, which can comprehensively consider the trajectory tracking accuracy, vehicle stability and four-wheel slip ratio control objectives under different operating conditions, and the physical constraints of the actuator , frictional ellipse constraints, and phase plane security constraints, determine the relatively optimal control quantity, and have good comprehensive control performance.

3) Based on the quantitative stability evaluation index, a set of weight adaptive adjustment strategies for different control objectives is designed to coordinate the trajectory tracking accuracy and the weight priority of vehicle maneuverability objectives and vehicle stability objectives under different operating conditions, and A hyperbolic function is introduced to adaptively adjust the weight of the four-wheel slip ratio deviation to prevent tire slippage and further improve vehicle safety performance. It has good adaptability and robustness to different operating conditions.

4) Design phase plane safety constraints based on the corresponding yaw rate and center of mass sideslip angle when the rear wheel slip angle is saturated, to further ensure the stability of the vehicle; and by introducing slack variables to ensure that the controller can still be able to Find a feasible solution, that is, allow the vehicle to temporarily exceed the safety constraint boundary slightly to ensure the control performance of the whole vehicle and prevent the vehicle from getting out of control due to the failure of the controller to solve.

Based on the same inventive concept, embodiments of the present disclosure also provide a control device for an unmanned vehicle, as described in the following embodiments. Since the problem-solving principle of this device embodiment is similar to that of the above-mentioned method embodiment, the implementation of this device embodiment can refer to the implementation of the above-mentioned method embodiment, and repeated descriptions will not be repeated.

FIG. 10 shows a schematic diagram of an unmanned vehicle control device in an embodiment of the present disclosure. As shown in FIG. 10 , the device includes: a state information acquisition module 1001 , a control amount determination module 1002 and a control module 1003 .

Among them, the state information acquisition module 1001 is used to obtain the trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions; Trajectory tracking accuracy, stability index and wheel slip rate under operating conditions, determine the front wheel angle and wheel torque of the unmanned vehicle to track the target speed and reference trajectory information in a steady state under different operating conditions; control module 1003, configured to control the driving of the unmanned vehicle according to the determined front wheel rotation angle and wheel torque.

It should be noted here that the above-mentioned state information acquisition module 1001, control quantity determination module 1002 and control module 1003 correspond to S102-S106 in the method embodiment, and the examples and application scenarios implemented by the above-mentioned modules and corresponding steps are the same, but It is not limited to the content disclosed in the above method embodiments. It should be noted that, as a part of the apparatus, the above-mentioned modules can be executed in a computer system such as a set of computer-executable instructions.

In some embodiments, according to the trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions, it is determined that the unmanned vehicle tracks the target vehicle speed and the reference speed in a steady state under different operating conditions. The front wheel angle and wheel torque of trajectory information driving, including: constructing an objective function based on trajectory tracking accuracy, stability index and wheel slip rate; determining the constraints of the objective function; determining the unmanned The steering angle and wheel torque of the driving vehicle track the target vehicle speed and the reference trajectory information in a steady state under different operating conditions.

In some embodiments, the above-mentioned control amount determination module 1002 is also used to: acquire the target vehicle speed and reference trajectory information of the unmanned vehicle; determine the tracking target vehicle speed of the unmanned vehicle according to the target vehicle speed and reference trajectory information of the unmanned vehicle and the front wheel angle of the reference track information; according to the target speed and actual speed of the unmanned vehicle, determine the total driving or braking torque required for the unmanned vehicle to track the target speed; according to the vertical load of the front and rear axles of the unmanned vehicle According to the distribution situation, the total driving or braking torque required by the unmanned vehicle to track the target speed is distributed to each wheel to obtain the longitudinal driving or braking torque of each wheel; according to the wheel slippage of the unmanned vehicle under different operating conditions The shift rate is used to constrain the longitudinal driving or braking torque of each wheel.

In some embodiments, the above-mentioned control amount determination module 1002 is also used to: obtain the maximum driving or braking torque output by the motor on the unmanned vehicle; according to the maximum driving or braking torque output by the motor on the unmanned vehicle, The total driving or braking torque required by the human-driven vehicle to track the target vehicle speed is limited.

In some embodiments, the above-mentioned control amount determination module 1002 is also used to: obtain the lateral displacement deviation and heading angle deviation of the unmanned vehicle tracking the target vehicle speed and reference trajectory information under different operating conditions; The lateral displacement deviation and heading angle deviation of the vehicle tracking target speed and reference trajectory information under different operating conditions determine the trajectory tracking accuracy of unmanned vehicles tracking target speed and reference trajectory information under different operating conditions .

In some embodiments, the above-mentioned control variable determination module 1002 is also used to: obtain the lateral speed, yaw rate, and side slip angle of the front and rear axle wheels of the unmanned vehicle under different operating conditions; The lateral speed, yaw rate, and side slip angle of the front and rear axles under operating conditions determine the stability index of the unmanned vehicle tracking the target speed and reference trajectory information under different operating conditions.

In some embodiments, the above-mentioned control variable determination module 1002 is also used to: determine the lateral velocity, yaw rate, lateral displacement deviation, heading angle deviation, wheel slip rate and front and rear axle wheel side slip angles as state variables, Establish a state space expression; according to the vehicle steady state of the unmanned vehicle under different operating conditions, adaptively adjust the weight coefficients of lateral vehicle speed, yaw rate and tracking deviation.

In some embodiments, the above-mentioned control amount determination module 1002 is also used for: if the unmanned vehicle is in a stable state, then reduce the weight coefficient of the lateral vehicle speed, and increase the weight coefficient of the yaw angle and the tracking deviation; if When the unmanned vehicle is in an unstable state, the weight coefficient of the lateral vehicle speed is increased, and the weight coefficient of the yaw angle and the tracking deviation is decreased.

Those skilled in the art can understand that various aspects of the present disclosure can be implemented as a system, method or program product. Therefore, various aspects of the present disclosure can be embodied in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which can be collectively referred to herein as "circuit", "module" or "system".

An electronic device 1100 according to this embodiment of the present disclosure is described below with reference to FIG. 11 . The electronic device 1100 shown in FIG. 11 is only an example, and should not limit the functions and scope of use of the embodiments of the present disclosure.

As shown in FIG. 11 , electronic device 1100 takes the form of a general-purpose computing device. Components of the electronic device 1100 may include, but are not limited to: at least one processing unit 1110, at least one storage unit 1120, and a bus 1130 connecting different system components (including the storage unit 1120 and the processing unit 1110).

Wherein, the storage unit stores program codes, and the program codes can be executed by the processing unit 1110, so that the processing unit 1110 executes various exemplary methods according to the present disclosure described in the "Exemplary Methods" section of this specification. Implementation steps. For example, the processing unit 1110 may perform the following steps in the above-mentioned method embodiment: obtain the trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions; Trajectory tracking accuracy, stability index and wheel slip rate under working conditions, to determine the front wheel angle and wheel torque for the unmanned vehicle to track the target speed and reference trajectory information in a steady state under different operating conditions; according to the determined The front wheel angle and wheel torque are used to control the driving of the unmanned vehicle.

The storage unit 1120 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 11201 and/or a cache storage unit 11202 , and may further include a read-only storage unit (ROM) 11203 .

Storage unit 1120 may also include programs/utilities 11204 having a set (at least one) of program modules 11205, such program modules 11205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, Implementations of networked environments may be included in each or some combination of these examples.

Bus 1130 may represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local area using any of a variety of bus structures. bus.

The electronic device 1100 can also communicate with one or more external devices 1140 (such as keyboards, pointing devices, Bluetooth devices, etc.), and can also communicate with one or more devices that enable the user to interact with the electronic device 1100, and/or communicate with Any device (eg, router, modem, etc.) that enables the electronic device 1100 to communicate with one or more other computing devices. Such communication may occur through input/output (I/O) interface 1150 . Moreover, the electronic device 1100 can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN) and/or a public network such as the Internet) through the network adapter 1160 . As shown, the network adapter 1160 communicates with other modules of the electronic device 1100 through the bus 1130 . It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with electronic device 1100, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives And data backup storage system, etc.

Through the description of the above implementations, those skilled in the art can easily understand that the example implementations described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of software products, and the software products can be stored in a non-volatile storage medium (which can be CD-ROM, U disk, mobile hard disk, etc.) or on the network , including several instructions to make a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) execute the method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, and the computer-readable storage medium may be a readable signal medium or a readable storage medium. FIG. 12 shows a schematic diagram of a computer-readable storage medium in an embodiment of the present disclosure. As shown in FIG. 12 , the computer-readable storage medium 1200 stores a program product capable of implementing the above method of the present disclosure. In some possible implementation manners, various aspects of the present disclosure may also be implemented in the form of a program product, which includes program code, and when the program product is run on a terminal device, the program code is used to make the The terminal device executes the steps according to various exemplary embodiments of the present disclosure described in the "Exemplary Method" section above in this specification.

More specific examples of computer-readable storage media in this disclosure may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), Erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.

In the present disclosure, a computer-readable storage medium may include a data signal carrying readable program code in baseband or as part of a carrier wave traveling as a data signal. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

Alternatively, program code contained on a computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, cable, optical cable, RF, etc., or any suitable combination of the above.

During specific implementation, the program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, and the programming language includes an object-oriented programming language—such as Java, C++, etc., or Includes conventional procedural programming languages - such as the "C" language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server to execute. In cases involving a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., using an Internet service provider). business to connect via the Internet).

It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. Actually, according to the embodiment of the present disclosure, the features and functions of two or more modules or units described above may be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided to be embodied by a plurality of modules or units.

In addition, although steps of the methods of the present disclosure are depicted in the drawings in a particular order, there is no requirement or implication that the steps must be performed in that particular order, or that all illustrated steps must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step for execution, and/or one step may be decomposed into multiple steps for execution, etc.

Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of software products, and the software products can be stored in a non-volatile storage medium (which can be CD-ROM, U disk, mobile hard disk, etc.) or on the network , including several instructions to make a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) execute the method according to the embodiments of the present disclosure.

Other embodiments of the present disclosure will be readily apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. The present disclosure is intended to cover any modification, use or adaptation of the present disclosure. These modifications, uses or adaptations follow the general principles of the present disclosure and include common knowledge or conventional technical means in the technical field not disclosed in the present disclosure. . The specification and examples are to be considered exemplary only, with the true scope and spirit of the disclosure indicated by the appended claims.

Claims (10)

1. A method for controlling an unmanned vehicle, comprising: Obtain the trajectory tracking accuracy, stability index and wheel slip rate of unmanned vehicles under different operating conditions; According to the trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions, determine that the unmanned vehicle tracks the target vehicle speed and reference trajectory information in a steady state under different operating conditions Front wheel angles and wheel moments traveled; According to the determined front wheel angle and wheel torque, control the driving of the unmanned vehicle. 2. The unmanned vehicle control method according to claim 1, characterized in that, according to the trajectory tracking accuracy, stability index and wheel slip ratio of the unmanned vehicle under different operating conditions, determine the The unmanned vehicle tracks the front wheel angle and wheel torque of the target vehicle speed and reference trajectory information in a steady state under different operating conditions, including: Construct an objective function based on trajectory tracking accuracy, stability index and wheel slip rate; determining constraints on the objective function; According to the objective function and the constraint conditions, the front wheel angle and wheel torque of the unmanned vehicle tracking the target vehicle speed and the reference trajectory information in a steady state under different operating conditions are determined. 3. The unmanned vehicle control method according to claim 1, wherein the method further comprises: Obtain the target speed and reference trajectory information of the unmanned vehicle; According to the target vehicle speed and reference trajectory information of the unmanned vehicle, determine the front wheel angle at which the unmanned vehicle tracks the target vehicle speed and the reference trajectory information; determining the total driving or braking torque required for the unmanned vehicle to track the target vehicle speed according to the target vehicle speed and the actual vehicle speed of the unmanned vehicle; According to the vertical load distribution of the front and rear axles of the unmanned vehicle, the total driving or braking torque required by the unmanned vehicle to track the target speed is distributed to each wheel to obtain the longitudinal driving or braking of each wheel torque; According to the wheel slip ratio of the unmanned vehicle under different operating conditions, the longitudinal driving or braking torque of each wheel is constrained. 4. The unmanned vehicle control method according to claim 3, wherein, according to the target vehicle speed and the actual vehicle speed of the unmanned vehicle, determine the required speed of the unmanned vehicle to track the target vehicle speed. After the total driving or braking torque, the method also includes: Obtain the maximum driving or braking torque output by the motor on the unmanned vehicle; Limiting processing is performed on the total driving or braking torque required by the unmanned vehicle to track the target vehicle speed according to the maximum driving or braking torque output by the motor on the unmanned vehicle. 5. The unmanned vehicle control method according to claim 1, wherein the method further comprises: Obtaining the lateral displacement deviation and heading angle deviation of the unmanned vehicle tracking the target vehicle speed and reference trajectory information under different operating conditions; According to the lateral displacement deviation and heading angle deviation of the unmanned vehicle tracking the target vehicle speed and the reference track information under different operating conditions, it is determined that the unmanned vehicle tracks the target vehicle speed and the reference track information under different operating conditions. Trajectory tracking accuracy of trajectory information driving. 6. The unmanned vehicle control method according to claim 1, wherein the method further comprises: Acquiring the lateral speed, yaw rate and side slip angle of the front and rear axle wheels of the unmanned vehicle under different operating conditions; According to the lateral speed, yaw rate and side slip angle of the front and rear axle wheels of the unmanned vehicle under different operating conditions, it is determined that the unmanned vehicle is tracking the target vehicle speed and the reference track information under different operating conditions. the stability index. 7. The unmanned vehicle control method according to claim 1, wherein the method further comprises: Determine the lateral velocity, yaw rate, lateral displacement deviation, heading angle deviation, wheel slip rate and front and rear axle slip angles as state variables, and establish a state space expression; According to the stable state of the vehicle under different operating conditions of the unmanned vehicle, the weight coefficients of the lateral vehicle speed, the yaw rate and the tracking deviation are adaptively adjusted. 8. An unmanned vehicle control device, characterized in that it comprises: The state information acquisition module is used to obtain the trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions; The control quantity determination module is used to determine the stable state of the unmanned vehicle under different operating conditions according to the trajectory tracking accuracy, stability index and wheel slip rate of the unmanned vehicle under different operating conditions. Track the target vehicle speed and the front wheel angle and wheel torque of the reference track information; The control module is used to control the driving of the unmanned vehicle according to the determined front wheel angle and wheel torque. 9. An electronic device, characterized in that it comprises: processor; and a memory for storing executable instructions of the processor; Wherein, the processor is configured to execute the unmanned vehicle control method in any one of claims 1-7 by executing the executable instructions. 10. A computer-readable storage medium, on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the unmanned vehicle control method according to any one of claims 1-7 is realized.

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