CN116373993A - Vehicle steering control method and device, electronic equipment and storage medium - Google Patents
Vehicle steering control method and device, electronic equipment and storage medium Download PDFInfo
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- CN116373993A CN116373993A CN202310271931.4A CN202310271931A CN116373993A CN 116373993 A CN116373993 A CN 116373993A CN 202310271931 A CN202310271931 A CN 202310271931A CN 116373993 A CN116373993 A CN 116373993A
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Abstract
The disclosure provides a vehicle steering control method, a device, electronic equipment and a storage medium, and relates to the field of artificial intelligence such as automatic driving and intelligent traffic. The method may include: acquiring a compensated steering signal to be optimized generated in the previous processing, taking the compensated steering signal as a target steering signal, performing steering control on a vehicle according to the target steering signal, and acquiring vehicle state information after performing steering control; determining a clearance parameter according to the target steering signal and the vehicle state information; and obtaining a steering signal to be optimized, and performing inverse clearance compensation on the steering signal to be optimized according to the clearance parameter to obtain a compensated steering signal to be optimized generated in the current process. By applying the scheme disclosed by the disclosure, the running stability, safety and the like of the vehicle can be improved.
Description
Technical Field
The present disclosure relates to the field of artificial intelligence, and in particular, to a vehicle steering control method, apparatus, electronic device, and storage medium in the fields of automatic driving, intelligent transportation, and the like.
Background
For an automatic steering vehicle steering system, a clearance problem (or referred to as a clearance nonlinearity problem) is a relatively common nonlinearity problem, and the clearance is derived from gaps between transmission components such as gears, shaft heads and the like, and the nonlinearity problem can cause steering control to be not in place, particularly in a straight running scene, such as vehicle side-to-side rocking and the like.
Disclosure of Invention
The present disclosure provides a vehicle steering control method, apparatus, electronic device, and storage medium.
A vehicle steering control method, comprising:
acquiring a compensated steering signal to be optimized generated in the previous processing, taking the compensated steering signal as a target steering signal, performing steering control on a vehicle according to the target steering signal, and acquiring vehicle state information after the steering control;
determining a clearance parameter according to the target steering signal and the vehicle state information;
and obtaining a steering signal to be optimized, and performing inverse clearance compensation on the steering signal to be optimized according to the clearance parameter to obtain a compensated steering signal to be optimized generated by the current processing.
A vehicle steering control apparatus comprising: the control identification module and the signal compensation module;
the control identification module is used for acquiring the compensated steering signal to be optimized generated in the previous processing, taking the compensated steering signal as a target steering signal, carrying out steering control on the vehicle according to the target steering signal, acquiring vehicle state information after steering control, determining a clearance parameter according to the target steering signal and the vehicle state information, and providing the clearance parameter to the signal compensation module;
the signal compensation module is used for obtaining a steering signal to be optimized, carrying out inverse gap compensation on the steering signal to be optimized according to the gap parameter, obtaining a compensated steering signal to be optimized generated by the current processing, and providing the compensated steering signal to the control identification module.
An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method as described above.
A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform a method as described above.
A computer program product comprising computer programs/instructions which when executed by a processor implement a method as described above.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is a flow chart of an embodiment of a vehicle steering control method according to the present disclosure;
FIG. 2 is a schematic diagram of an equivalent representation of a vehicle steering system according to the present disclosure;
FIG. 3 is a schematic diagram of an inverse gap compensation process according to the present disclosure;
FIG. 4 is a schematic diagram of an overall implementation of the vehicle steering control method of the present disclosure;
fig. 5 is a schematic view showing the composition of an embodiment 500 of a steering control device for a vehicle according to the present disclosure;
fig. 6 shows a schematic block diagram of an electronic device 600 that may be used to implement embodiments of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In addition, it should be understood that the term "and/or" herein is merely one association relationship describing the associated object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
Fig. 1 is a flowchart of an embodiment of a vehicle steering control method according to the present disclosure. As shown in fig. 1, the following detailed implementation is included.
In step 101, a compensated steering signal to be optimized generated in the previous processing is obtained and used as a target steering signal, steering control is performed on the vehicle according to the target steering signal, and vehicle state information after the steering control is obtained.
In step 102, a clearance parameter is determined based on the target steering signal and the vehicle status information.
In step 103, obtaining a steering signal to be optimized, performing inverse gap compensation on the steering signal to be optimized according to the gap parameter to obtain a compensated steering signal to be optimized generated by the current processing, and repeating step 101.
According to the scheme of the embodiment of the method, the self-adaptive mode can be adopted to conduct on-line identification and compensation on the problem of the gap nonlinearity of the vehicle steering system, so that the problem that the vehicle is not controlled in place due to the gap nonlinearity can be effectively solved, for example, the problem that the vehicle swings left and right when being in straight due to the gap nonlinearity can be effectively eliminated, and the running stability and safety of the vehicle are further improved.
Preferably, the vehicle is an autonomous vehicle. In the running process of the vehicle, the scheme described in the above method embodiment may be repeatedly executed, that is, the target steering signal may be continuously generated, and the processes shown in steps 101 to 103 may be executed for each generated target steering signal.
The steering control method comprises the steps of acquiring a target steering signal, wherein the steering control can be carried out on a vehicle according to the target steering signal, and vehicle state information after the steering control can be acquired.
The vehicle state information may include information which is specific to the actual need, and may include various information related to a steering operation performed by the vehicle, for example.
Then, a clearance parameter may be determined based on the target steering signal and the vehicle status information. Preferably, vehicle state information corresponding to a last target steering signal adjacent to the target steering signal may be acquired as vehicle history state information, and the clearance parameter may be determined based on the target steering signal, the vehicle state information, and the vehicle history state information.
That is, in addition to the vehicle state information corresponding to the current target steering signal, the vehicle state information corresponding to one target steering signal before (adjacent to) the current target steering signal can be obtained and used as the vehicle history state information, and accordingly, the target steering signal, the vehicle state information and the vehicle history state information can be combined at the same time to determine the required clearance parameter, so that the accuracy of the determined clearance parameter and the like is further improved.
Preferably, the required clearance parameter is determined by recursive least squares (RLS, recursive Least Square) based on the target steering signal, the vehicle status information, the vehicle history status information, and a predetermined first mathematical model.
Preferably, the first mathematical model may be a mathematical model determined by combining a second mathematical model and a third mathematical model, the second mathematical model may be a mathematical model corresponding to the first-order inertial link, and the third mathematical model may be a mathematical model corresponding to the gap nonlinearity, wherein the steering system of the vehicle is equivalent to a serial combination model of the first-order inertial link and the gap nonlinearity.
Additionally, preferably, the gap parameters may include: a first gap parameter and a second gap parameter.
Fig. 2 is a schematic diagram of an equivalent expression of the steering system of the vehicle according to the present disclosure. As shown in fig. 2, the vehicle steering system can be equivalent to a series combination model of a first-order inertia link and a gap nonlinearity, and the recognition of steering control and gap parameters can be completed based on the model, wherein u represents a target steering signal, w represents intermediate result information, and y represents vehicle state information.
Wherein, the Euler backward difference method and the like can be combined to determine the mathematical model (second mathematical model) of the discrete form corresponding to the first-order inertia link as follows:
w(k)＝a*w(k-1)+b*u(k)； (1)
wherein,,
t represents the sampling time interval of the Euler backward difference method, k represents the current moment, k-1 represents the previous moment, for example, w (k) represents the latest intermediate result information, w (k-1) represents the last intermediate result information, and a0 and a1 are both model coefficients.
In addition, a mathematical model (third mathematical model) of the gap nonlinearity correspondence is as follows:
wherein y (k) represents vehicle state information, y (k-1) represents vehicle history state information, d l Represents a first gap parameter, d r Represents a second gap parameter, additionally, d l And d r The left and right gap parameters (left and right gap values), respectively.
Combining equation (2) and equation (3) yields the following form:
wherein,,
representing the derivative of y (k-1).
Let ψ= [ y (k-1),u(k),1],Θ l ＝[a,b,(1-a)d l ] T ，Θ r ＝[a,b,(a-1)d r ] T equation (4) can be converted into the following standard least squares form, i.e., the first mathematical model:
accordingly, the required clearance parameter d can be determined by the existing RLS method based on the target steering signal u (k), the vehicle state information y (k), the vehicle history state information y (k-1), the formula (5) and the like l And d r 。
In the processing mode, the first mathematical model corresponding to the vehicle steering system can be effectively constructed by carrying out equivalent expression on the vehicle steering system and combining the second mathematical model and the third mathematical model, and further, the required clearance parameters can be efficiently and accurately determined based on various acquired information, the first mathematical model and the like, so that a good foundation is laid for subsequent processing.
It should be noted that the above manner of determining the gap parameter is merely illustrative, and is not intended to limit the technical solution of the present disclosure. For example, the target steering signal and the vehicle state information (or the target steering signal, the vehicle state information, and the vehicle history state information) may be input into a predictive model trained in advance, and the clearance parameter may be determined using the predictive model.
For the determined clearance parameter, the clearance parameter can be utilized to realize inverse clearance compensation, namely the steering signal to be optimized can be obtained, the inverse clearance compensation is carried out on the steering signal to be optimized according to the clearance parameter, and the compensated steering signal to be optimized is used as a new target steering signal.
Fig. 3 is a schematic diagram of the inverse gap compensation process according to the present disclosure. As shown in fig. 3, v represents a steering signal to be optimized, which may be a steering signal generated by using an existing steering control algorithm, and u represents a new target steering signal obtained after performing inverse gap compensation.
Preferably, the way of performing inverse gap compensation on the steering signal to be optimized according to the gap parameter may include: obtaining a derivative of the steering signal to be optimized, obtaining a difference between the steering signal to be optimized and the first clearance parameter in response to determining that the derivative is smaller than 0, taking the obtained difference as a compensated steering signal to be optimized generated in the current processing, namely as a target steering signal, obtaining a sum of the steering signal to be optimized and the second clearance parameter in response to determining that the derivative is larger than 0, and taking the obtained sum as the target steering signal.
And the reverse gap compensation is carried out on the steering signal to be optimized in a corresponding mode according to the difference of the values of the derivatives, so that the compensation is more targeted, and the accuracy of the compensation result is further improved.
Further, preferably, in response to determining that the derivative is equal to 0, the turn signal to be optimized may be taken as the target turn signal.
Namely, when the derivative is equal to 0, the steering signal to be optimized can be directly used as a target steering signal without performing reverse gap compensation, so that the processing efficiency and the like are improved.
Accordingly, there may be:
wherein,,
representing the derivative of the turn signal to be optimized.
In connection with the foregoing description, fig. 4 is a schematic diagram of an overall implementation process of the vehicle steering control method according to the present disclosure. As shown in fig. 4, the vehicle may be steered according to the target steering signal at the current moment, and the vehicle state information after steering control may be obtained, and accordingly, gap identification may be performed according to the target steering signal and the vehicle state information, that is, a gap parameter may be determined, in addition, the steering control algorithm may generate a steering signal to be optimized according to the vehicle state information, that is, a steering signal at the next moment, and then may perform inverse gap compensation on the steering signal to be optimized by using the gap parameter, so as to obtain the target steering signal at the next moment, and further, steering control may be performed on the vehicle by using the target steering signal at the next moment, and the process may be repeated continuously.
It should be noted that, for the sake of simplicity of description, the foregoing method embodiments are expressed as a series of combinations of actions, but it should be understood by those skilled in the art that the present disclosure is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present disclosure. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all of the preferred embodiments, and that the acts and modules referred to are not necessarily required by the present disclosure.
In a word, by adopting the scheme of the embodiment of the method disclosed by the invention, the problem that the vehicle is not controlled in place due to the nonlinearity of the gap can be effectively solved, for example, the problem that the vehicle swings left and right when the vehicle is straight due to the nonlinearity of the gap can be effectively eliminated, so that the running stability and safety of the vehicle are improved, and the mode is simple and convenient to realize, and the realization and maintenance costs are reduced.
The foregoing is a description of embodiments of the method, and the following further describes embodiments of the present disclosure through examples of apparatus.
Fig. 5 is a schematic view showing the composition of an embodiment 500 of a steering control device for a vehicle according to the present disclosure. As shown in fig. 5, includes: the control and identification module 501 and the signal compensation module 502.
The control identification module 501 is configured to obtain the compensated steering signal to be optimized generated in the previous processing, take the compensated steering signal as a target steering signal, perform steering control on the vehicle according to the target steering signal, obtain vehicle state information after performing steering control, determine a clearance parameter according to the target steering signal and the vehicle state information, and provide the clearance parameter to the signal compensation module 502.
The signal compensation module 502 is configured to obtain a signal to be optimized, perform inverse gap compensation on the signal to be optimized according to the gap parameter, obtain a compensated signal to be optimized generated by the current process, and provide the compensated signal to be optimized to the control identification module 501.
In the scheme of the embodiment of the device, the self-adaptive mode can be adopted to identify and compensate the gap nonlinearity problem of the vehicle steering system on line, so that the problem that the vehicle is not controlled in place due to the gap nonlinearity can be effectively solved, for example, the problem that the vehicle swings left and right when being in straight due to the gap nonlinearity can be effectively eliminated, and the running stability and the running safety of the vehicle are further improved.
Preferably, the vehicle is an autonomous vehicle. During the running process of the vehicle, the process corresponding to the scheme described in the device embodiment can be repeatedly executed.
For each obtained target steering signal, the control identification module 501 may perform steering control on the vehicle according to the target steering signal, may obtain vehicle state information after steering control, and may determine the clearance parameter according to the target steering signal and the vehicle state information.
The vehicle state information may include information which is specific to the actual need, and may include various information related to a steering operation performed by the vehicle, for example.
Preferably, the control identifying module 501 may acquire, as the vehicle history state information, the vehicle state information corresponding to the last target steering signal adjacent to the target steering signal, and may determine the clearance parameter according to the target steering signal, the vehicle state information, and the vehicle history state information.
That is, in addition to the vehicle state information corresponding to the current target steering signal, the vehicle state information corresponding to one target steering signal before (adjacent to) the current target steering signal may be obtained as the vehicle history state information, and accordingly, the target steering signal, the vehicle state information and the vehicle history state information may be combined at the same time to determine the required gap parameter.
Preferably, the control identification module 501 may determine the required clearance parameter by RLS mode according to the target steering signal, the vehicle state information, the vehicle history state information and the predetermined first mathematical model.
Preferably, the first mathematical model may be a mathematical model determined by combining a second mathematical model and a third mathematical model, the second mathematical model may be a mathematical model corresponding to the first-order inertial link, and the third mathematical model may be a mathematical model corresponding to the gap nonlinearity, wherein the steering system of the vehicle is equivalent to a serial combination model of the first-order inertial link and the gap nonlinearity.
Additionally, preferably, the determined gap parameters may include: a first gap parameter and a second gap parameter.
The control identifying module 501 may send the determined gap parameter to the signal compensating module 502, and accordingly, for the obtained gap parameter, the signal compensating module 502 may use the determined gap parameter to implement inverse gap compensation, that is, obtain the steering signal to be optimized, perform inverse gap compensation on the steering signal to be optimized according to the gap parameter, and use the compensated steering signal to be optimized as a new target steering signal.
Preferably, the manner of the signal compensation module 502 performing inverse gap compensation on the steering signal to be optimized according to the gap parameter may include: obtaining a derivative of the steering signal to be optimized, obtaining a difference between the steering signal to be optimized and the first clearance parameter in response to determining that the derivative is smaller than 0, taking the obtained difference as a compensated steering signal to be optimized generated in the current processing, namely as a target steering signal, obtaining a sum of the steering signal to be optimized and the second clearance parameter in response to determining that the derivative is larger than 0, and taking the obtained sum as the target steering signal.
Additionally, preferably, the signal compensation module 502 may treat the turn signal to be optimized as the target turn signal in response to determining that the derivative is equal to 0.
I.e. when the derivative is equal to 0, the steering signal to be optimized can be directly used as the target steering signal without performing the inverse gap compensation.
Further, the signal compensation module 502 may send the compensated turn signal to be optimized generated by the present process to the control identification module 501 as a new target turn signal, and accordingly, the control identification module 501 may repeatedly execute the process.
The specific workflow of the embodiment of the apparatus shown in fig. 5 may refer to the related description in the foregoing method embodiment, and will not be repeated.
In a word, by adopting the scheme of the embodiment of the disclosure, the problem that the vehicle is not controlled in place due to the nonlinearity of the gap can be effectively solved, for example, the problem that the vehicle swings left and right when the vehicle is straight due to the nonlinearity of the gap can be effectively eliminated, so that the running stability and safety of the vehicle are improved, and the mode is simple and convenient to realize, and the realization and maintenance costs are reduced.
The scheme disclosed by the disclosure can be applied to the field of artificial intelligence, and particularly relates to the fields of automatic driving, intelligent traffic and the like. Artificial intelligence is the subject of studying certain thinking processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.) that make a computer simulate a person, and has technology at both hardware and software levels, and artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing, etc., and artificial intelligence software technologies mainly include computer vision technologies, speech recognition technologies, natural language processing technologies, machine learning/deep learning, big data processing technologies, knowledge graph technologies, etc.
In the technical scheme of the disclosure, the related processes of collecting, storing, using, processing, transmitting, providing, disclosing and the like of the personal information of the user accord with the regulations of related laws and regulations, and the public order colloquial is not violated.
According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.
Fig. 6 shows a schematic block diagram of an electronic device 600 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile apparatuses, such as personal digital assistants, cellular telephones, smartphones, wearable devices, and other similar computing apparatuses. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 6, the apparatus 600 includes a computing unit 601 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 may also be stored. The computing unit 601, ROM 602, and RAM 603 are connected to each other by a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
Various components in the device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, mouse, etc.; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as the methods described in this disclosure. For example, in some embodiments, the methods described in the present disclosure may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609. One or more steps of the methods described in this disclosure may be performed when a computer program is loaded into RAM 603 and executed by computing unit 601. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the methods described in the present disclosure in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel or sequentially or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (17)
1. A vehicle steering control method, comprising:
acquiring a compensated steering signal to be optimized generated in the previous processing, taking the compensated steering signal as a target steering signal, performing steering control on a vehicle according to the target steering signal, and acquiring vehicle state information after the steering control;
determining a clearance parameter according to the target steering signal and the vehicle state information;
and obtaining a steering signal to be optimized, and performing inverse clearance compensation on the steering signal to be optimized according to the clearance parameter to obtain a compensated steering signal to be optimized generated by the current processing.
2. The method of claim 1, wherein,
the determining a clearance parameter according to the target steering signal and the vehicle state information comprises:
acquiring vehicle state information corresponding to a last target steering signal adjacent to the target steering signal as vehicle history state information;
and determining the clearance parameter according to the target steering signal, the vehicle state information and the vehicle history state information.
3. The method of claim 2, wherein,
the determining the clearance parameter according to the target steering signal, the vehicle state information and the vehicle history state information comprises:
and determining the clearance parameter through a recursive least square mode according to the target steering signal, the vehicle state information, the vehicle history state information and a first predetermined mathematical model.
4. The method of claim 3, wherein,
the first mathematical model is a mathematical model determined by combining the second mathematical model and the third mathematical model;
the second mathematical model is a mathematical model corresponding to a first-order inertial link, and the third mathematical model is a mathematical model corresponding to a gap nonlinearity, wherein the steering system of the vehicle is equivalent to a serial combination model of the first-order inertial link and the gap nonlinearity.
5. The method according to any one of claims 1 to 4, wherein,
the gap parameters include: a first gap parameter and a second gap parameter.
6. The method of claim 5, wherein,
the performing inverse gap compensation on the steering signal to be optimized according to the gap parameter includes:
acquiring a derivative of the steering signal to be optimized;
in response to determining that the derivative is less than 0, obtaining a difference between the steering signal to be optimized and the first gap parameter, and taking the obtained difference as a compensated steering signal to be optimized generated by the current process;
and responding to the determination that the derivative is larger than 0, acquiring the sum of the steering signal to be optimized and the second clearance parameter, and taking the obtained sum as the compensated steering signal to be optimized generated in the current processing.
7. The method of claim 6, further comprising:
in response to determining that the derivative is equal to 0, the turn signal to be optimized is taken as the target turn signal.
8. A vehicle steering control apparatus comprising: the control identification module and the signal compensation module;
the control identification module is used for acquiring the compensated steering signal to be optimized generated in the previous processing, taking the compensated steering signal as a target steering signal, carrying out steering control on the vehicle according to the target steering signal, acquiring vehicle state information after steering control, determining a clearance parameter according to the target steering signal and the vehicle state information, and providing the clearance parameter to the signal compensation module;
the signal compensation module is used for obtaining a steering signal to be optimized, carrying out inverse gap compensation on the steering signal to be optimized according to the gap parameter, obtaining a compensated steering signal to be optimized generated by the current processing, and providing the compensated steering signal to the control identification module.
9. The apparatus of claim 8, wherein,
the control identification module acquires vehicle state information corresponding to a last target steering signal adjacent to the target steering signal as vehicle history state information, and determines the clearance parameter according to the target steering signal, the vehicle state information and the vehicle history state information.
10. The apparatus of claim 9, wherein,
the control identification module determines the clearance parameter through a recursive least square mode according to the target steering signal, the vehicle state information, the vehicle historical state information and a first predetermined mathematical model.
11. The apparatus of claim 10, wherein,
the first mathematical model is a mathematical model determined by combining the second mathematical model and the third mathematical model;
the second mathematical model is a mathematical model corresponding to a first-order inertial link, and the third mathematical model is a mathematical model corresponding to a gap nonlinearity, wherein the steering system of the vehicle is equivalent to a serial combination model of the first-order inertial link and the gap nonlinearity.
12. The device according to any one of claims 8 to 11, wherein,
the gap parameters include: a first gap parameter and a second gap parameter.
13. The apparatus of claim 12, wherein,
the signal compensation module obtains the derivative of the steering signal to be optimized, responds to the fact that the derivative is smaller than 0, obtains the difference between the steering signal to be optimized and the first gap parameter, takes the obtained difference as a compensated steering signal to be optimized generated in the current process, responds to the fact that the derivative is larger than 0, obtains the sum of the steering signal to be optimized and the second gap parameter, and takes the obtained sum as the compensated steering signal to be optimized generated in the current process.
14. The apparatus of claim 13, wherein,
the signal compensation module is further configured to, in response to determining that the derivative is equal to 0, treat the turn signal to be optimized as the target turn signal.
15. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
16. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1-7.
17. A computer program product comprising computer programs/instructions which, when executed by a processor, implement the method of any of claims 1-7.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310271931.4A CN116373993A (en) | 2023-03-16 | 2023-03-16 | Vehicle steering control method and device, electronic equipment and storage medium |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310271931.4A CN116373993A (en) | 2023-03-16 | 2023-03-16 | Vehicle steering control method and device, electronic equipment and storage medium |
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| CN116373993A true CN116373993A (en) | 2023-07-04 |
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| CN202310271931.4A Pending CN116373993A (en) | 2023-03-16 | 2023-03-16 | Vehicle steering control method and device, electronic equipment and storage medium |
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