CN111216733A - Vehicle control method and device, vehicle and storage medium - Google Patents
Vehicle control method and device, vehicle and storage medium Download PDFInfo
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- CN111216733A CN111216733A CN202010116042.7A CN202010116042A CN111216733A CN 111216733 A CN111216733 A CN 111216733A CN 202010116042 A CN202010116042 A CN 202010116042A CN 111216733 A CN111216733 A CN 111216733A
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- vehicle
- rear wheel
- steering angle
- wheel steering
- angle value
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
- B60W2520/105—Longitudinal acceleration
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/28—Wheel speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/18—Steering angle
Abstract
The invention discloses a vehicle control method, a vehicle control device, a vehicle and a storage medium. The method comprises the following steps: acquiring state parameters of a vehicle; judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle; if so, calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle, and controlling the vehicle according to the estimated rear wheel steering angle value; if not, the state parameters of the vehicle are input into a pre-trained target rear wheel steering angle value determination model, an estimated rear wheel steering angle value is determined according to the output result of the target rear wheel steering angle value determination model, and the vehicle is controlled according to the estimated rear wheel steering angle value.
Description
Technical Field
The embodiment of the invention relates to the field of vehicles, in particular to a vehicle control method, a vehicle control device, a vehicle and a storage medium.
Background
The rear wheel steering system is equipped to current commercially available high-end passenger car, and this system possesses an electromechanical actuator, can provide the rear wheel steering function to help promoting vehicle dynamic performance, driving safety and travelling comfort. The system estimates the rear wheel steering angle value according to the centroid slip angle by receiving signals of the steering angle, the wheel acceleration, the yaw rate and the like of the vehicle, calculating and outputting a required rear wheel steering angle signal through an algorithm (such as centroid slip angle control) already specified in the ECU.
In the prior art, the collected vehicle signals and the calculated corner signals are repeatedly calculated in an iterative manner, and then the final corner signals are output, but the response time is not fast enough, the redundancy of the control system is not enough, and the functional requirements of the intelligent chassis cannot be met.
Disclosure of Invention
The embodiment of the invention provides a vehicle control method, a vehicle control device, a vehicle and a storage medium, which are used for achieving the functional requirements of improving the response speed and an intelligent chassis.
In a first aspect, an embodiment of the present invention provides a vehicle control method, including: acquiring state parameters of a vehicle;
judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle;
if so, calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle, and controlling the vehicle according to the estimated rear wheel steering angle value;
if not, inputting the state parameters of the vehicle into a pre-trained target rear wheel steering angle value determination model, determining an estimated rear wheel steering angle value according to the output result of the target rear wheel steering angle value determination model, and controlling the vehicle according to the estimated rear wheel steering angle value, wherein the model structure and the model parameters of the target rear wheel steering angle value determination model are determined by training according to the state parameters of a sample vehicle and the sample rear wheel steering angle value respectively.
In a second aspect, an embodiment of the present invention further provides a vehicle control apparatus, including: the parameter acquisition module is used for acquiring the state parameters of the vehicle;
the judging module is used for judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle;
the first control module is used for calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle and controlling the vehicle according to the estimated rear wheel steering angle value if the vehicle is in the state parameters;
and the second control module is used for inputting the state parameters of the vehicle into a pre-trained target rear wheel steering angle value determination model if the state parameters of the vehicle are not determined, determining an estimated rear wheel steering angle value according to the output result of the target rear wheel steering angle value determination model, and controlling the vehicle according to the estimated rear wheel steering angle value, wherein the model structure and the model parameters of the target rear wheel steering angle value determination model are determined by respectively training according to the state parameters of the sample vehicle and the sample rear wheel steering angle value.
In a third aspect, embodiments of the present invention further provide a vehicle, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the vehicle control method according to any one of the embodiments of the present invention.
In a fourth aspect, the embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the vehicle control method according to any one of the embodiments of the present invention.
According to the embodiment of the invention, the state parameters of the vehicle are obtained; judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle; if so, calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle, and controlling the vehicle according to the estimated rear wheel steering angle value; if not, the state parameters of the vehicle are input into a pre-trained target rear wheel steering angle value determination model, an estimated rear wheel steering angle value is determined according to the output result of the target rear wheel steering angle value determination model, and the vehicle is controlled according to the estimated rear wheel steering angle value, wherein the model structure and the model parameters of the target rear wheel steering angle value determination model are determined by training according to the state parameters of a sample vehicle and the sample rear wheel steering angle value respectively, so that the functional requirements of improving the response speed and the intelligent chassis are met.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1A is a flow chart of a vehicle control method according to a first embodiment of the present invention;
FIG. 1B is a flowchart illustrating estimation of the rear wheel steering angle according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a vehicle control apparatus according to a second embodiment of the invention;
fig. 3 is a schematic structural diagram of a vehicle according to a third embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example one
Fig. 1A is a flowchart of a vehicle control method according to a first embodiment of the present invention, where this embodiment is applicable to a vehicle control situation, and the method may be executed by a vehicle control device according to an embodiment of the present invention, where the device may be implemented in a software and/or hardware manner, as shown in fig. 1A, where the method specifically includes the following steps:
and S110, acquiring the state parameters of the vehicle.
Wherein the state parameter of the vehicle may include at least one of a steering wheel angle, a steering wheel torque, a front wheel angle ratio, a vehicle speed, a wheel speed, an acceleration, a yaw rate, and a wheel jump stroke.
The state parameters of the vehicle are acquired by a sensor on the vehicle, and the sensor may be an acceleration sensor or a gyroscope, which is not limited in this embodiment of the present invention.
Specifically, the state parameter of the vehicle may be, for example, a steering wheel angle, a steering wheel torque, a front wheel angular ratio, a vehicle speed, a wheel speed, an acceleration, a yaw rate, and a wheel hop stroke within a preset time period, and for example, the sensor may acquire the steering wheel angle, the steering wheel torque, the front wheel angular ratio, the vehicle speed, the wheel speed, the acceleration, the yaw rate, and the wheel hop stroke in real time, and transmit the steering wheel angle, the steering wheel torque, the front wheel angular ratio, the vehicle speed, the wheel speed, the acceleration, the yaw rate, and the wheel hop stroke within 100ms to the controller, and the controller may acquire the steering wheel angle, the steering wheel torque, the front wheel angular ratio, the vehicle speed, the wheel speed, the acceleration, the yaw rate, and the wheel hop stroke within 100 ms.
Optionally, the state parameters of the vehicle include: at least one of a steering wheel angle, a steering wheel torque, a front wheel angle ratio, a vehicle speed, a wheel speed, an acceleration, a yaw rate, and a wheel jump stroke.
The wheel jump stroke is the height of a wheel, and the setting of the zero point of the wheel jump stroke is not limited in the embodiment of the invention.
Specifically, at least one of a steering wheel angle, a steering wheel torque, a front wheel angular transmission ratio, a vehicle speed, a wheel speed, an acceleration, a yaw rate, and a wheel jump stroke is acquired by a sensor.
S120, judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle; if yes, go to S130, otherwise go to S140.
Wherein the special operating conditions include: the embodiments of the present invention are not limited to this, and the specific working conditions are pothole, low- μ, and the like.
Specifically, the manner of determining whether the state parameter of the vehicle belongs to the special condition of the vehicle may be determining whether the road surface on which the vehicle is located is the special road surface according to the state parameter of the vehicle, if so, the vehicle is in the special condition, or may be directly determining according to the state parameter of the vehicle, and if the state parameter of the vehicle meets the condition that the state parameter corresponding to the special condition meets, the vehicle is determined to be in the special condition.
Optionally, the determining, according to the state parameter of the vehicle, whether the vehicle is in a special working condition includes:
judging the road surface state of the vehicle according to the state parameters of the vehicle;
and if the road surface state is a special road surface, determining that the vehicle is in a special working condition.
The road surface state of the vehicle can be a common road surface or a special road surface.
Specifically, if the road surface state of the vehicle is judged to be a special road surface according to the state parameters of the vehicle, the working state of the vehicle is determined to be a special working condition.
Optionally, the special road surface includes: at least one of a tunnel, an ice surface, a split road surface, and a rail.
The pit bag road surface comprises a pit road surface and a raised road surface, the pits can be refined according to different pit heights, and the embodiment of the invention is not limited to this.
Wherein, the split road surface is the road surface on two sides of the wheel with different adhesion coefficients; butt-jointed roads means that the car drives from one road surface with one coefficient of adhesion to another road surface with another coefficient of adhesion.
S130, calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle, and controlling the vehicle according to the estimated rear wheel steering angle value.
Specifically, if the vehicle is in a special working condition, the rear wheel steering angle value is estimated according to a method for estimating the rear wheel steering angle value in the prior art.
Specifically, after the rear wheel steering angle value is estimated, the vehicle is controlled according to the estimated rear wheel steering angle value.
S140, inputting the state parameters of the vehicle into a pre-trained target rear wheel steering angle value determination model, determining an estimated rear wheel steering angle value according to the output result of the target rear wheel steering angle value determination model, and controlling the vehicle according to the estimated rear wheel steering angle value.
And the model structure and the model parameters of the target rear wheel steering angle value determination model are determined by training according to the state parameters of the sample vehicle and the sample rear wheel steering angle values respectively.
Optionally, the training method for determining the model of the target rear wheel steering angle value includes:
acquiring state parameters of a sample vehicle and rear wheel steering angle values corresponding to the state parameters of the sample vehicle, and establishing a first rear wheel steering angle value determination model;
and training the first rear wheel steering angle value determination model according to the state parameters of the sample vehicle and the rear wheel steering angle values corresponding to the state parameters of the sample vehicle to generate the target rear wheel steering angle value determination model.
Optionally, the method further includes, after inputting the state parameter of the vehicle into a pre-trained target rear wheel steering angle value determination model, determining an estimated rear wheel steering angle value according to an output result of the target rear wheel steering angle value determination model, and controlling the vehicle according to the estimated rear wheel steering angle value:
acquiring an actual rear wheel steering angle value acquired by a sensor;
and training the target rear wheel steering angle value determination model according to the state parameters of the vehicle and the actual rear wheel steering angle value.
Wherein the sensor is used for acquiring an actual rear wheel steering angle value.
Specifically, after the vehicle is controlled according to the estimated rear wheel steering angle value, the rear wheel steering angle value corresponding to the state parameter of the vehicle is collected, for example, the estimated rear wheel steering angle value may be estimated according to the state parameter of the vehicle collected in the time period a, and after the vehicle is controlled according to the estimated rear wheel steering angle value, the sensor collects an actual rear wheel steering angle value corresponding to the state parameter of the vehicle in the time period a. And taking the state parameter of the vehicle in the time period A and the actual rear wheel steering angle value as a pair of sample data, and training the target rear wheel steering angle value determination model according to the state parameter of the vehicle in the time period A and the actual rear wheel steering angle value so as to optimize the target rear wheel steering angle value determination model.
In a specific example, as shown in fig. 1B, after the state parameter of the vehicle is input to a vehicle state observer, the state parameter of the vehicle is received and analyzed by a vehicle state confirmation module, a vehicle state estimated signal is output to a steering angle storage module, and the steering angle storage module calls and outputs a historical steering angle value in a storage library by comparing a rear wheel steering angle signal and a vehicle state signal which are input simultaneously; if there is no corresponding signal in the bank, no signal is output. And meanwhile, outputting a vehicle state prediction signal to a corner output judgment module, wherein the corner output judgment module is used for judging special working conditions (such as the working conditions of a pothole, low-mu and the like), when the input vehicle state signal triggers a judgment threshold value of the special working conditions, namely the judgment threshold value is consistent with the starting conditions of the special working conditions, the corner output judgment module considers that a prediction rear wheel corner value cannot be obtained through calculation of a target rear wheel corner value determination model, the corner output judgment module outputs a forbidden signal, after the corner arbitration module integrates a historical corner value and a corner output judgment signal, the corner output judgment module does not output the prediction rear wheel corner value obtained through calculation of the target rear wheel corner value determination model, and otherwise, the target rear wheel corner value determination model is output according to the historical corner value to obtain the prediction rear wheel corner value. The steering angle storage module stores the vehicle state signal input each time and a rear wheel steering angle signal of later action of a rear wheel steering actuator into the module to serve as a training sample of a target rear wheel steering angle value determination model. If the original vehicle state signal is identical to the newly stored value but the output corner signal is different, the new corner value is overlaid on the original stored value, wherein the rear wheel steering forms a displacement sensor for acquiring the actual rear wheel corner value.
The rear wheel steering angle storage module stores a vehicle state signal input each time and a rear wheel steering angle signal of later action of a rear wheel steering actuator into the module. If the original vehicle state signal is consistent with the newly stored value but the output corner signal is different, the new corner value is overlaid on the original stored value
In the embodiment of the invention, the rear wheel steering actuator body is fixed on the auxiliary frame and is respectively connected with two rear wheels of a vehicle through the steering pull rod. The rear wheel steering ECU receives a steering wheel angle, steering wheel torque, a steering angle transmission ratio, wheel speed, acceleration, yaw rate and wheel height of a vehicle, outputs a pre-estimated rear wheel steering angle value according to the steering wheel angle, the steering wheel torque, the steering angle transmission ratio, the wheel speed, the acceleration, the yaw rate and the wheel height, can accumulate scene signals and output steering angle signals in the using process of a real vehicle, and outputs the pre-estimated rear wheel steering angle value in real time.
According to the technical scheme of the embodiment, the state parameters of the vehicle are obtained; judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle; if so, calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle, and controlling the vehicle according to the estimated rear wheel steering angle value; if not, the state parameters of the vehicle are input into a pre-trained target rear wheel steering angle value determination model, an estimated rear wheel steering angle value is determined according to the output result of the target rear wheel steering angle value determination model, and the vehicle is controlled according to the estimated rear wheel steering angle value, wherein the model structure and the model parameters of the target rear wheel steering angle value determination model are determined by training according to the state parameters of a sample vehicle and the sample rear wheel steering angle value respectively, so that the functional requirements of improving the response speed and the intelligent chassis are met.
Example two
Fig. 2 is a schematic structural diagram of a vehicle control device according to a second embodiment of the present invention. The present embodiment may be applied to a vehicle control situation, and the apparatus may be implemented in a software and/or hardware manner, and may be integrated into any device that provides a function of vehicle control, as shown in fig. 2, where the vehicle control apparatus specifically includes: a parameter obtaining module 210, a judging module 220, a first control module 230 and a second control module 240.
The parameter obtaining module 210 is configured to obtain a state parameter of a vehicle;
the judging module 220 is configured to judge whether the vehicle is in a special working condition according to the state parameter of the vehicle;
the first control module 230 is configured to calculate a centroid slip angle according to the state parameters of the vehicle, estimate a rear wheel angle value according to the centroid slip angle, and control the vehicle according to the estimated rear wheel angle value if the vehicle is in the middle of the driving range;
and a second control module 240, configured to, if not, input the state parameter of the vehicle into a pre-trained target rear wheel steering angle value determination model, determine an estimated rear wheel steering angle value according to an output result of the target rear wheel steering angle value determination model, and control the vehicle according to the estimated rear wheel steering angle value, where a model structure and a model parameter of the target rear wheel steering angle value determination model are determined by training according to the state parameter of the sample vehicle and the sample rear wheel steering angle value, respectively.
Optionally, the method further includes:
the rear wheel steering angle value acquisition module is used for acquiring an actual rear wheel steering angle value acquired by the sensor;
and the optimization module is used for optimizing the target rear wheel steering angle value determination model according to the state parameters of the vehicle and the actual rear wheel steering angle value.
Optionally, the second control module is specifically configured to:
acquiring state parameters of a sample vehicle and rear wheel steering angle values corresponding to the state parameters of the sample vehicle, and establishing a first rear wheel steering angle value determination model;
and training the first rear wheel steering angle value determination model according to the state parameters of the sample vehicle and the rear wheel steering angle values corresponding to the state parameters of the sample vehicle to generate the target rear wheel steering angle value determination model.
The product can execute the method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
According to the technical scheme of the embodiment, the state parameters of the vehicle are obtained; judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle; if so, calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle, and controlling the vehicle according to the estimated rear wheel steering angle value; if not, the state parameters of the vehicle are input into a pre-trained target rear wheel steering angle value determination model, an estimated rear wheel steering angle value is determined according to the output result of the target rear wheel steering angle value determination model, and the vehicle is controlled according to the estimated rear wheel steering angle value, wherein the model structure and the model parameters of the target rear wheel steering angle value determination model are determined by training according to the state parameters of a sample vehicle and the sample rear wheel steering angle value respectively, so that the functional requirements of improving the response speed and the intelligent chassis are met.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a vehicle according to a third embodiment of the present invention. FIG. 3 illustrates a block diagram of an exemplary vehicle 12 suitable for use in implementing embodiments of the present invention. The vehicle 12 shown in FIG. 3 is only one example and should not impose any limitations on the functionality or scope of use of embodiments of the present invention.
As shown in FIG. 3, the vehicle 12 is embodied in the form of a general purpose computing device. The components of the vehicle 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The vehicle 12 typically includes a variety of computer system readable media. These media may be any available media that is accessible by the vehicle 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. The vehicle 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 3, and commonly referred to as a "hard drive"). Although not shown in FIG. 3, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The vehicle 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with the vehicle 12, and/or with any devices (e.g., network card, modem, etc.) that enable the vehicle 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. In the vehicle 12 of the present embodiment, the display 24 is not provided as a separate body, but is embedded in the mirror surface, and when the display surface of the display 24 is not displayed, the display surface of the display 24 and the mirror surface are visually integrated. Also, the vehicle 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via the network adapter 20. As shown, the network adapter 20 communicates with other modules of the vehicle 12 via the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the vehicle 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing a vehicle control method provided by an embodiment of the present invention: acquiring state parameters of a vehicle; judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle; if so, calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle, and controlling the vehicle according to the estimated rear wheel steering angle value; if not, inputting the state parameters of the vehicle into a pre-trained target rear wheel steering angle value determination model, determining an estimated rear wheel steering angle value according to the output result of the target rear wheel steering angle value determination model, and controlling the vehicle according to the estimated rear wheel steering angle value, wherein the model structure and the model parameters of the target rear wheel steering angle value determination model are determined by training according to the state parameters of a sample vehicle and the sample rear wheel steering angle value respectively.
EXAMPLE five
Fifth embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a vehicle control method according to any of the fifth embodiment of the present invention: acquiring state parameters of a vehicle; judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle; if so, calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle, and controlling the vehicle according to the estimated rear wheel steering angle value; if not, inputting the state parameters of the vehicle into a pre-trained target rear wheel steering angle value determination model, determining an estimated rear wheel steering angle value according to the output result of the target rear wheel steering angle value determination model, and controlling the vehicle according to the estimated rear wheel steering angle value, wherein the model structure and the model parameters of the target rear wheel steering angle value determination model are determined by training according to the state parameters of a sample vehicle and the sample rear wheel steering angle value respectively.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having 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. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A vehicle control method characterized by comprising:
acquiring state parameters of a vehicle;
judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle;
if so, calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle, and controlling the vehicle according to the estimated rear wheel steering angle value;
if not, inputting the state parameters of the vehicle into a pre-trained target rear wheel steering angle value determination model, determining an estimated rear wheel steering angle value according to the output result of the target rear wheel steering angle value determination model, and controlling the vehicle according to the estimated rear wheel steering angle value, wherein the model structure and the model parameters of the target rear wheel steering angle value determination model are determined by training according to the state parameters of a sample vehicle and the sample rear wheel steering angle value respectively.
2. The method according to claim 1, wherein the method further comprises the steps of inputting the state parameters of the vehicle into a pre-trained target rear wheel steering angle value determination model, determining an estimated rear wheel steering angle value according to an output result of the target rear wheel steering angle value determination model, and controlling the vehicle according to the estimated rear wheel steering angle value, and the steps of:
acquiring an actual rear wheel steering angle value acquired by a sensor;
and training the target rear wheel steering angle value determination model according to the state parameters of the vehicle and the actual rear wheel steering angle value.
3. The method of claim 1, wherein the training method of the target rear wheel steering value determination model comprises:
acquiring state parameters of a sample vehicle and rear wheel steering angle values corresponding to the state parameters of the sample vehicle, and establishing a first rear wheel steering angle value determination model;
and training the first rear wheel steering angle value determination model according to the state parameters of the sample vehicle and the rear wheel steering angle values corresponding to the state parameters of the sample vehicle to generate the target rear wheel steering angle value determination model.
4. The method of claim 1, wherein determining whether the vehicle is in a special operating condition based on the state parameter of the vehicle comprises:
judging the road surface state of the vehicle according to the state parameters of the vehicle;
and if the road surface state is a special road surface, determining that the vehicle is in a special working condition.
5. The method according to claim 4, characterized in that said special road surface comprises: at least one of a tunnel, an ice surface, a split road surface, and a rail.
6. The method according to any one of claims 1-5, wherein the state parameters of the vehicle include: at least one of a steering wheel angle, a steering wheel torque, a front wheel angle ratio, a vehicle speed, a wheel speed, an acceleration, a yaw rate, and a wheel jump stroke.
7. A vehicle control apparatus characterized by comprising:
the parameter acquisition module is used for acquiring the state parameters of the vehicle;
the judging module is used for judging whether the vehicle is in a special working condition or not according to the state parameters of the vehicle;
the first control module is used for calculating to obtain a mass center slip angle according to the state parameters of the vehicle, estimating a rear wheel steering angle value according to the mass center slip angle and controlling the vehicle according to the estimated rear wheel steering angle value if the vehicle is in the state parameters;
and the second control module is used for inputting the state parameters of the vehicle into a pre-trained target rear wheel steering angle value determination model if the state parameters of the vehicle are not determined, determining an estimated rear wheel steering angle value according to the output result of the target rear wheel steering angle value determination model, and controlling the vehicle according to the estimated rear wheel steering angle value, wherein the model structure and the model parameters of the target rear wheel steering angle value determination model are determined by respectively training according to the state parameters of the sample vehicle and the sample rear wheel steering angle value.
8. The apparatus of claim 7, further comprising:
the rear wheel steering angle value acquisition module is used for acquiring an actual rear wheel steering angle value acquired by the sensor;
and the optimization module is used for training the target rear wheel steering angle value determination model according to the state parameters of the vehicle and the actual rear wheel steering angle value.
9. A vehicle comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-6 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-6.
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