CN117724501A - Path tracking control method, device, vehicle and medium - Google Patents
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Abstract
The invention provides a path tracking control method, a device, a vehicle and a medium, comprising the following steps: acquiring an actual position, an actual state parameter and an expected path state parameter of a vehicle in the actual running process of the vehicle; determining a second-order degree-of-freedom vehicle dynamics model, a lateral deviation equation and a second-order steering model of the vehicle based on the actual position, the actual state parameters and the expected path state parameters; determining a state equation of the vehicle based on the second-order degree-of-freedom vehicle dynamics model, the lateral deviation equation and the second-order steering model; constructing a cost function, and adopting a Rickettsia equation to iteratively solve a state equation based on the cost function to obtain a front wheel corner at the current moment of the vehicle; the front wheel steering angle at the present time is input to the steering system of the vehicle to control the operation of the vehicle. The invention improves the actual control performance and effect of path tracking.
Description
Technical Field
The present invention relates to the field of autopilot technology, and in particular, to a path tracking control method, apparatus, vehicle, and medium.
Background
The vehicle path tracking problem, a core technology of intelligent driving vehicle lateral motion control research, reflects the ability of an unmanned vehicle to smoothly and accurately follow a predetermined desired trajectory. At present, one of the core algorithms in the transverse motion control is an LQR control algorithm, and the existing LQR algorithm only usually considers a vehicle kinematics or vehicle dynamics model, and the method can meet certain transverse control performance requirements, but does not consider the characteristics of a key actuator-steering system, so that the actual control effect is not ideal, and a great deal of time and effort are required for debugging parameters and adding a compensation algorithm.
Disclosure of Invention
In view of the above, the present invention aims to provide a path tracking control method, a device, a vehicle and a medium, so as to improve the actual control performance and effect of path tracking.
In order to achieve the above object, the technical scheme adopted by the embodiment of the invention is as follows:
in a first aspect, an embodiment of the present invention provides a path tracking control method, including: acquiring an actual position, an actual state parameter and an expected path state parameter of a vehicle in the actual running process of the vehicle; determining a second-order degree-of-freedom vehicle dynamics model, a lateral deviation equation and a second-order steering model of the vehicle based on the actual position, the actual state parameters and the expected path state parameters; determining a state equation of the vehicle based on the second-order degree-of-freedom vehicle dynamics model, the lateral deviation equation and the second-order steering model; constructing a cost function, and adopting a Rickettsia equation to iteratively solve a state equation based on the cost function to obtain a front wheel corner at the current moment of the vehicle; the front wheel steering angle at the present time is input to the steering system of the vehicle to control the operation of the vehicle.
In one embodiment, the second degree of freedom vehicle dynamics model of the vehicle is:
wherein,representing vehicle lateral offset acceleration, K f Represents the cornering stiffness of the front wheel of the vehicle, K r Represents the cornering stiffness of the rear wheels of the vehicle, delta represents the turning angle of the front wheels of the vehicle, beta represents the cornering angle of the mass center of the vehicle, m represents the mass of the vehicle, v x Represents the longitudinal speed of the vehicle, w represents the actual yaw rate of the vehicle, l f Representing the distance from the front axle to the centre of mass of the vehicle, l r Representing the distance from the rear axle to the center of mass of the vehicle, I z Representing the moment of inertia of the vehicle.
In one embodiment, the lateral deviation equation is:
wherein,representing the lateral offset velocity, v, of the actual position of the vehicle relative to the projected point on the desired path y Representing the lateral speed of the vehicle, v x Representing the longitudinal speed of the vehicle>Representing the difference between the actual heading angle of the vehicle and the heading angle of the projected point on the desired path, +.>Representing the difference between the actual yaw rate of the vehicle and the desired yaw rate, ±>Representing the actual yaw rate of the vehicle, +.>Indicating the desired yaw rate, K a Represents the actual turning radius of the vehicle, K t Representation ofA desired turning radius.
In one embodiment, the second order steering model is:
wherein,representing the actual front wheel angular acceleration of the vehicle, +.>Representing the actual front wheel rotational speed, delta, of a vehicle a Represents the actual front wheel steering angle of the vehicle, ζ represents the damping ratio, w n Representing the natural angular frequency, delta tl Indicating the target front wheel rotation angle at the previous time.
In one embodiment, the state equation of the vehicle is:
wherein,representing the state quantity of the vehicle->The control amount of the vehicle is represented, and the control amount is the front wheel rotational speed.
In one embodiment, constructing the cost function includes:
constructing an initial cost function, and simplifying the initial cost function based on a transverse deviation equation to obtain a final cost function;
wherein, the initial cost function is:
wherein,a lateral jerk value representing the vehicle;
the final cost function is:
J＝(Q 0 +Q 1 +Q 2 )X 2 +RU 2 ＝QX 2 +RU 2
wherein X represents a state quantity, U represents a control quantity, Q represents a weight matrix of the state quantity, and R represents a weight matrix of the control quantity.
In one embodiment, iteratively solving a state equation based on a cost function using a licardi equation to obtain a front wheel corner at a current time of the vehicle, the method comprising: solving and obtaining a full state feedback equation and a control equation based on the cost function and the state equation; iterative solution of P according to the continuous form of the Li-Kadi equation k+1 A matrix; will P k+1 Substituting the matrix into a control equation to obtain a full-state feedback vector; substituting the full state feedback vector into the full state feedback equation to obtain the front wheel angular speed at the previous moment, and calculating to obtain the front wheel rotation angle at the current moment of the vehicle based on the front wheel angular speed at the previous moment, the front wheel rotation angle at the previous moment and the sampling time.
In a second aspect, an embodiment of the present invention provides a path tracking control device, including: the parameter acquisition module is used for acquiring the actual position, the actual state parameter and the expected path state parameter of the vehicle in the actual running process of the vehicle; the model determining module is used for determining a second-order degree-of-freedom vehicle dynamics model, a transverse deviation equation and a second-order steering model of the vehicle based on the actual position, the actual state parameters and the expected path state parameters; the state equation determining module is used for determining a state equation of the vehicle based on the second-order degree-of-freedom vehicle dynamics model, the transverse deviation equation and the second-order steering model; the iteration solving module is used for constructing a cost function, and adopting a Rickettsia equation to iteratively solve a state equation based on the cost function to obtain a front wheel corner of the vehicle at the current moment; and the control module is used for inputting the front wheel steering angle at the current moment into a steering system of the vehicle so as to control the operation of the vehicle.
In a third aspect, an embodiment of the present invention provides an electronic device comprising a processor and a memory storing computer executable instructions executable by the processor to perform the steps of the method of any one of the first aspects described above.
In a fourth aspect, embodiments of the present invention provide a computer readable storage medium having a computer program stored thereon, which when executed by a processor performs the steps of the method of any of the first aspects provided above.
The embodiment of the invention has the following beneficial effects:
the embodiment of the invention provides the path tracking control method, the device, the vehicle and the medium, wherein firstly, the actual position, the actual state parameter and the expected path state parameter of the vehicle in the actual running process of the vehicle are obtained; then, determining a second-order degree-of-freedom vehicle dynamics model, a lateral deviation equation and a second-order steering model of the vehicle based on the actual position, the actual state parameters and the expected path state parameters; then, determining a state equation of the vehicle based on the second-order degree-of-freedom vehicle dynamics model, the lateral deviation equation and the second-order steering model; then, constructing a cost function, and adopting a Rickettsia equation to iteratively solve a state equation based on the cost function to obtain a front wheel corner of the vehicle at the current moment; finally, the front wheel steering angle at the current moment is input to a steering system of the vehicle to control the operation of the vehicle. The method comprehensively considers the steering system characteristic, the vehicle dynamics characteristic and the deviation equation of the vehicle motion, combines a second-order degree-of-freedom vehicle dynamics model, a transverse deviation equation and a second-order steering model when constructing the state equation of the vehicle, considers the vehicle turning performance weight when designing the cost function, adopts the Rickettsia equation for iterative solution, and can obtain the optimal solution at each moment, thereby improving the problems in the prior art and improving the actual control performance and effect of path tracking.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a path tracking control method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a path tracking control device according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a vehicle according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, one of the core algorithms in the transverse motion control is an LQR control algorithm, and the existing LQR algorithm only usually considers a vehicle kinematics or vehicle dynamics model, and the method can meet certain transverse control performance requirements, but does not consider the characteristics of a key actuator-steering system, so that the actual control effect is not ideal, and a great deal of time and effort are required for debugging parameters and adding a compensation algorithm.
Based on the above, the path tracking control method, the device, the vehicle and the medium provided by the embodiment of the invention can improve the actual control performance and effect of path tracking.
For the sake of understanding the present embodiment, a detailed description will be given first of a path tracking control method disclosed in the present embodiment, which may be executed by a control system of a vehicle. Referring to the flowchart of a path tracking control method shown in fig. 1, it is shown that the method mainly includes the following steps S101 to S105:
step S101: the method comprises the steps of obtaining an actual position, an actual state parameter and an expected path state parameter of a vehicle in the actual running process of the vehicle.
In one embodiment, the method for acquiring the actual position and the actual state parameters of the vehicle during the actual running process through the sensor of the vehicle comprises the following steps: lateral vehicle offset acceleration, vehicle front wheel rotation angle, actual yaw rate of the vehicle, longitudinal speed of the vehicle, lateral speed of the vehicle, actual yaw rate of the vehicle, and the like.
Step S102: a second order degree of freedom vehicle dynamics model, a lateral deviation equation, and a second order steering model of the vehicle are determined based on the actual position, the actual state parameters, and the desired path state parameters.
In one embodiment, the second degree of freedom vehicle dynamics model of the vehicle describes the dynamics of the vehicle when moving laterally, as follows:
in the method, in the process of the invention,representing vehicle lateral offset acceleration, K f Represents the cornering stiffness of the front wheel of the vehicle, K r Represents the cornering stiffness of the rear wheels of the vehicle, delta represents the turning angle of the front wheels of the vehicle, beta represents the cornering angle of the mass center of the vehicle, m represents the mass of the vehicle, v x Represents the longitudinal speed of the vehicle, w represents the actual yaw rate of the vehicle, l f Representing the distance from the front axle to the centre of mass of the vehicle, l r Representing the distance from the rear axle to the center of mass of the vehicle, I z Representing the moment of inertia of the vehicle.
The lateral deviation equation describes the deviation relationship between the actual position of the vehicle and the expected waypoint, as follows:
in the method, in the process of the invention,representing the lateral offset velocity, v, of the actual position of the vehicle relative to the projected point on the desired path y Representing the lateral speed of the vehicle, v x Representing the longitudinal speed of the vehicle>Representing the difference between the actual heading angle of the vehicle and the heading angle of the projected point on the desired path, +.>Representing the difference between the actual yaw rate of the vehicle and the desired yaw rate, ±>Representing the actual yaw rate of the vehicle, +.>Indicating the desired yaw rate, K a Represents the actual turning radius of the vehicle, K t Indicating the desired turning radius.
The second order steering model describes the steering system characteristics, as follows:
in the method, in the process of the invention,representing the actual front wheel angular acceleration of the vehicle, +.>Representing the actual front wheel rotational speed, delta, of a vehicle a Represents the actual front wheel steering angle of the vehicle, ζ represents the damping ratio, w n Representing the natural angular frequency, delta tl Indicating the target front wheel rotation angle at the previous time.
Step S103: and determining a state equation of the vehicle based on the second-order degree-of-freedom vehicle dynamics model, the lateral deviation equation and the second-order steering model.
In one embodiment, the state equation of the vehicle embodies the steering system and vehicle state as the vehicle moves toward the target point, which is generally in the form of:x represents a state quantity, u represents a control quantity, a represents a matrix of state quantities, and B represents a matrix of control quantities.
The state equation of the vehicle in this embodiment is as follows:
wherein,representing the state quantity of the vehicle->The control amount of the vehicle is represented, and the control amount is the front wheel rotational speed.
Step S104: and constructing a cost function, and adopting a Rickettsia equation to iteratively solve a state equation based on the cost function to obtain the front wheel corner of the vehicle at the current moment.
Step S105: the front wheel steering angle at the present time is input to the steering system of the vehicle to control the operation of the vehicle.
According to the path tracking control method provided by the embodiment of the invention, the steering system characteristic, the vehicle dynamics characteristic and the deviation equation of the vehicle motion are comprehensively considered, a second-order degree-of-freedom vehicle dynamics model, a transverse deviation equation and a second-order steering model are combined when the state equation of the vehicle is constructed, meanwhile, the vehicle turning performance weight is considered when the cost function is designed, and the Li-Kadi equation is adopted for iterative solution, so that the optimal solution at each moment can be obtained, the problems in the prior art are solved, and the actual control performance and effect of path tracking are improved.
In one embodiment, for the aforementioned step S104, i.e., when constructing the cost function, the following means may be employed, including but not limited to: constructing an initial cost function, and simplifying the initial cost function based on a transverse deviation equation to obtain a final cost function;
wherein, the initial cost function is:
wherein the state quantity of the vehicleMainly consider the lateral jerk value when the vehicle turns,>mainly taking into account the lateral speed variation during cornering, these two quantities need to be taken into accountThe final weight matrix Q and R can be obtained by one-step conversion to be related to the state quantity or the control quantity.
Based on this, in the present embodiment, it is possible toAnd->The simplification is carried out, and the method specifically comprises the following steps:
then it is possible to obtain:
further simplified to obtain:
from the lateral deviation equation:
thus, it is possible to obtain:
to sum up, the final cost function is given only in this embodimentThe situation considered in the state quantity:
J＝(Q 0 +Q 1 +Q 2 )X 2 +RU 2 ＝QX 2 +RU 2
wherein X represents a state quantity, U represents a control quantity, Q represents a weight matrix of the state quantity, and R represents a weight matrix of the control quantity.
In one embodiment, for the foregoing step S104, that is, when the state equation is solved iteratively using the licardi equation based on the cost function, the front wheel corner at the current moment of the vehicle is obtained, the following manners may be adopted, including but not limited to:
firstly, solving based on a cost function and a state equation to obtain a full state feedback equation and a control equation.
In practice, the full state feedback equation can be expressed as: u= -Kx, K represents a full state feedback vector, and the control equation may be expressed as: k=r -1 B T P k+1 。
Then, iteratively solving P according to the Li-Kadi equation in continuous form k+1 A matrix.
In practice, a state equation set for a period of time (within 8s is assumed) is first determined, and an A matrix in each state equation set is time-varying, and a B matrix, a weight matrix Q and R are time-invariant; then, iteratively solving P according to the continuous form of the Li-Kadi equation (matrix differential equation) k+1 A matrix whose equation is as follows:
where t represents the sampling time, A, B represents a matrix of state equations, and the boundary condition is P (t end ) S, S represents the state matrix of the last state, set to zero matrix.
The recurrence formula is:
further, based on integration of the backward Euler method, recursion is performed, and the method mainly comprises the following steps:
(1) The integration interval is set, the start time (pre-aiming time) is 8s, the end time is 0s, the step length is-0.01 s, namely, the end state is set as a zero matrix backwards.
(2) Substituting the matrix A at the 8s moment and the constant matrix B, Q, R into the Li-Kadi equation to obtain
(3) P (k+799) is obtained from the recurrence formula.
(4) Substituting the matrix A at the moment of 7.99s and the matrix B, Q, R which is unchanged in time into the Li-Kadi equation to obtain
(5) P (k+798) is found according to the recurrence formula and the above steps are repeated until P (k+1) is obtained.
Next, P is k+1 The matrix is substituted into the control equation to obtain the full state feedback vector.
Specifically, the form of the full state feedback vector is as follows: k=r -1 B T P k+1 。
And finally, substituting the full state feedback vector into a full state feedback equation to obtain the front wheel angular speed at the previous moment, and calculating to obtain the front wheel rotation angle at the current moment of the vehicle based on the front wheel angular speed at the previous moment, the front wheel rotation angle at the previous moment and the sampling time.
Specifically, the control amount command (i.e., the front wheel steering angular velocity) is calculated according to the full state feedback equation, and the formula is as follows:
u k ＝-Kx k
at this time, the obtained control amount command is the front wheel angular velocity at the previous time, and the front wheel rotation angle at the current time=the front wheel rotation angle at the previous time+the front wheel angular velocity at the previous time.
According to the method provided by the embodiment of the invention, the steering system characteristic, the vehicle dynamics characteristic and the deviation equation of the vehicle motion are comprehensively considered; when designing the cost function, the turning performance weight of the vehicle is mainly considered; the state equation of the future moment is considered, and the continuous Li-Car equation is adopted to solve, so that the optimal solution of each moment can be obtained theoretically, the problems existing in the prior art are improved, the performance requirement of path tracking control under the full-speed domain can be better met, and the actual control performance and effect of path tracking are improved.
For the path tracking control method provided in the foregoing embodiment, the present invention further provides a path tracking control device, referring to a schematic structural diagram of the path tracking control device shown in fig. 2, which illustrates that the device mainly includes the following parts:
a parameter obtaining module 201, configured to obtain an actual position, an actual state parameter, and an expected path state parameter of the vehicle during actual running of the vehicle;
a model determination module 202 for determining a second degree of freedom vehicle dynamics model, a lateral deviation equation, and a second order steering model of the vehicle based on the actual position, the actual state parameter, and the desired path state parameter;
a state equation determining module 203 for determining a state equation of the vehicle based on the second degree of freedom vehicle dynamics model, the lateral deviation equation and the second degree of steering model;
the iteration solving module 204 is configured to construct a cost function, and iteratively solve a state equation by using a licardi equation based on the cost function to obtain a front wheel corner at the current moment of the vehicle;
the control module 205 is configured to input the front wheel steering angle at the current time to a steering system of the vehicle to control the operation of the vehicle.
According to the path tracking control device provided by the embodiment of the invention, the steering system characteristic, the vehicle dynamics characteristic and the deviation equation of the vehicle motion are comprehensively considered, a second-order degree-of-freedom vehicle dynamics model, a transverse deviation equation and a second-order steering model are combined when the state equation of the vehicle is constructed, meanwhile, the vehicle turning performance weight is considered when the cost function is designed, and the Li-Kadi equation is adopted for iterative solution, so that the optimal solution at each moment can be obtained, the problems in the prior art are solved, and the actual control performance and effect of path tracking are improved.
It should be noted that, for the sake of brevity, reference may be made to the corresponding contents of the foregoing method embodiments for the description of the device embodiment, where the principles and technical effects of the device provided in the embodiment are the same as those of the foregoing method embodiments.
The embodiment of the invention also provides a vehicle, which specifically comprises a processor and a storage device; the storage means has stored thereon a computer program which, when run by a processor, performs the method according to any of the above embodiments.
Fig. 3 is a schematic structural diagram of a vehicle according to an embodiment of the present invention, where the vehicle 100 includes: a processor 30, a memory 31, a bus 32 and a communication interface 33, the processor 30, the communication interface 33 and the memory 31 being connected by the bus 32; the processor 30 is arranged to execute executable modules, such as computer programs, stored in the memory 31.
The memory 31 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and the at least one other network element is achieved via at least one communication interface 33 (which may be wired or wireless), the internet, a wide area network, a local network, a metropolitan area network, etc. may be used.
Bus 32 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 3, but not only one bus or type of bus.
The memory 31 is configured to store a program, and the processor 30 executes the program after receiving an execution instruction, and the method executed by the apparatus for flow defining disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 30 or implemented by the processor 30.
The processor 30 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in the processor 30. The processor 30 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but may also be a digital signal processor (Digital Signal Processing, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 31 and the processor 30 reads the information in the memory 31 and in combination with its hardware performs the steps of the above method.
The computer program product of the readable storage medium provided by the embodiment of the present invention includes a computer readable storage medium storing a program code, where the program code includes instructions for executing the method described in the foregoing method embodiment, and the specific implementation may refer to the foregoing method embodiment and will not be described herein.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A path tracking control method, comprising:
acquiring an actual position, an actual state parameter and an expected path state parameter of a vehicle in the actual running process of the vehicle;
determining a second order degree of freedom vehicle dynamics model, a lateral deviation equation, and a second order steering model of the vehicle based on the actual position, the actual state parameter, and the desired path state parameter;
determining a state equation of the vehicle based on the second order degree of freedom vehicle dynamics model, the lateral deviation equation, and the second order steering model;
constructing a cost function, and iteratively solving the state equation by adopting a Rickettsia equation based on the cost function to obtain a front wheel corner of the vehicle at the current moment;
and inputting the front wheel steering angle at the current moment into a steering system of the vehicle so as to control the operation of the vehicle.
2. The method of claim 1, wherein the second degree of freedom vehicle dynamics model of the vehicle is:
wherein,representing vehicle lateral offset acceleration, K f Represents the cornering stiffness of the front wheel of the vehicle, K r Represents the cornering stiffness of the rear wheels of the vehicle, delta represents the turning angle of the front wheels of the vehicle, beta represents the cornering angle of the mass center of the vehicle, m represents the mass of the vehicle, v x Represents the longitudinal speed of the vehicle, w represents the actual yaw rate of the vehicle, l f Representing the distance from the front axle to the centre of mass of the vehicle, l r Representing the distance from the rear axle to the center of mass of the vehicle, I z Representing the moment of inertia of the vehicle.
3. The method of claim 1, wherein the lateral deviation equation is:
wherein,representing the actual position of the vehicleSetting the lateral offset velocity, v, relative to the projected point on the desired path y Representing the lateral speed of the vehicle, v x Representing the longitudinal speed of the vehicle>Representing the difference between the actual heading angle of the vehicle and the heading angle of the projected point on the desired path, +.>Representing the difference between the actual yaw rate of the vehicle and the desired yaw rate, ±>Representing the actual yaw rate of the vehicle, +.>Indicating the desired yaw rate, K a Represents the actual turning radius of the vehicle, K t Indicating the desired turning radius.
4. The method of claim 1, wherein the second order steering model is:
wherein,representing the actual front wheel angular acceleration of the vehicle, +.>Representing the actual front wheel rotational speed, delta, of a vehicle a Represents the actual front wheel steering angle of the vehicle, ζ represents the damping ratio, w n Representing the natural angular frequency, delta tl Indicating the target front wheel rotation angle at the previous time.
5. The method of claim 1, wherein the equation of state of the vehicle is:
wherein,representing the state quantity of the vehicle->The control amount of the vehicle, which is the front wheel steering angular velocity, is represented.
6. The method of claim 1, wherein constructing the cost function comprises:
constructing an initial cost function, and simplifying the initial cost function based on the transverse deviation equation to obtain a final cost function;
wherein the initial cost function is:
wherein,a lateral jerk value representing the vehicle;
the final cost function is:
J＝(Q 0 +Q 1 +Q 2 )X 2 +RU 2 ＝QX 2 +RU 2
wherein X represents a state quantity, U represents a control quantity, Q represents a weight matrix of the state quantity, and R represents a weight matrix of the control quantity.
7. The method of claim 1, wherein iteratively solving the state equation using a licardi equation based on the cost function to obtain a front wheel corner for the current time of the vehicle comprises:
solving and obtaining a full state feedback equation and a control equation based on the cost function and the state equation;
iterative solution of P according to the continuous form of the Li-Kadi equation k+1 A matrix;
will P k+1 Substituting the matrix into the control equation to obtain a full-state feedback vector;
substituting the full state feedback vector into the full state feedback equation to obtain the front wheel angular speed at the previous moment, and calculating the front wheel rotation angle at the current moment of the vehicle based on the front wheel angular speed at the previous moment, the front wheel rotation angle at the previous moment and the sampling time.
8. A path tracking control device, comprising:
the parameter acquisition module is used for acquiring the actual position, the actual state parameter and the expected path state parameter of the vehicle in the actual running process of the vehicle;
a model determination module for determining a second order degree of freedom vehicle dynamics model, a lateral deviation equation, and a second order steering model of the vehicle based on the actual position, the actual state parameter, and the desired path state parameter;
a state equation determining module configured to determine a state equation of the vehicle based on the second-order degree-of-freedom vehicle dynamics model, the lateral deviation equation, and the second-order steering model;
the iteration solving module is used for constructing a cost function, and adopting a Li-Kadi equation to iteratively solve the state equation based on the cost function to obtain a front wheel corner of the vehicle at the current moment;
and the control module is used for inputting the front wheel steering angle at the current moment into a steering system of the vehicle so as to control the operation of the vehicle.
9. A vehicle comprising a processor and a memory, the memory storing computer executable instructions executable by the processor, the processor executing the computer executable instructions to implement the steps of the method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, performs the steps of the method of any of the preceding claims 1 to 7.
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| CN118112935A (en) * | 2024-04-23 | 2024-05-31 | 上海易咖智车科技有限公司 | Vehicle path tracking control method, device, equipment and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN118112935A (en) * | 2024-04-23 | 2024-05-31 | 上海易咖智车科技有限公司 | Vehicle path tracking control method, device, equipment and storage medium |
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