CN114889648A

CN114889648A - Vehicle and automatic driving control method and device

Info

Publication number: CN114889648A
Application number: CN202210539653.1A
Authority: CN
Inventors: 崔鑫宇; 刘备; 凌鹏; 许昕; 龚胜波
Original assignee: Hozon New Energy Automobile Co Ltd
Current assignee: Hozon New Energy Automobile Co Ltd
Priority date: 2022-05-17
Filing date: 2022-05-17
Publication date: 2022-08-12

Abstract

The invention provides an automatic driving control method, which is characterized by comprising the following steps: step S1: acquiring output control quantities corresponding to a plurality of prediction points in a preset time period after the current moment based on a prediction model according to the target path and the current vehicle state; step S2: determining a control interval in the preset time period, and acquiring output control quantity of a plurality of corresponding prediction points in the control interval; step S3: determining real-time output control quantity at the current moment according to the current vehicle state and the output control quantity of the corresponding prediction points in the control interval; and step S4: and controlling the automatic driving of the vehicle according to the real-time output control quantity. According to the method and the device, accurate model prediction can be carried out according to the target path input to the control end at the current moment, and then vehicle control is carried out, so that the dependence of automatic driving control on vehicle positioning is effectively eliminated, and the smoothness of vehicle control can be improved.

Description

Vehicle and automatic driving control method and device

Technical Field

The invention relates to the field of automobiles, in particular to a vehicle with an automatic driving function and an automatic driving control method and device.

Background

The current automatic driving vehicle control scheme all relies on the location to do the position control of vehicle, and this kind of technical scheme is simple relatively, nevertheless because the accuracy that absolutely relies on the location is done vehicle control, consequently when the vehicle location drift or shake takes place, current control error just can be corrected immediately in automatic driving vehicle control, causes the control shake of vehicle, can bring uncomfortable experience and very big safety risk to passenger's body. Especially for high speed scenarios, a jerk of control due to positioning drift, once it occurs, causes a momentary imbalance of the vehicle, leading to a series of unpredictable consequences.

In view of the above, it is desirable to provide a method for controlling an autonomous vehicle for positioning, which is capable of getting rid of the dependence of the autonomous control on the positioning.

Disclosure of Invention

The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.

In order to solve the problems that in the prior art, when the positioning is deviated due to the dependence on the current vehicle positioning, the vehicle is controlled too violently, the vehicle is out of control, a user feels uncomfortable, and the vehicle is dangerous, the invention provides a vehicle with an automatic driving function, and an automatic driving control method and device.

An aspect of the present invention provides an automatic driving control method including: step S1: acquiring output control quantities corresponding to a plurality of prediction points in a preset time period after the current moment based on a prediction model according to the target path and the current vehicle state; step S2: determining a control interval in the preset time period, and acquiring output control quantity of a plurality of corresponding prediction points in the control interval; step S3: determining the real-time output control quantity at the current moment according to the current vehicle state and the output control quantities of the corresponding plurality of prediction points in the control interval; and step S4: and controlling the automatic driving of the vehicle according to the real-time output control quantity.

In an embodiment of the above-described automatic driving control method, optionally, the prediction model is constructed based on a yaw moment of inertia, a front-wheel-side cornering stiffness, a rear-wheel-side cornering stiffness, and a yaw rate based on a curvature of a road of the vehicle.

In an embodiment of the above automatic driving control method, optionally, determining the real-time output control amount at the current time according to the current vehicle state and the output control amounts corresponding to the plurality of predicted points in the control section further includes: and performing weighting processing on the output control amounts of the plurality of prediction points, wherein the output control amount of the prediction point closer to the current time is weighted more heavily.

In an embodiment of the above automatic driving control method, optionally, determining the real-time output control amount at the current time according to the current vehicle state and the output control amounts corresponding to the plurality of predicted points in the control section further includes: and performing weighting processing on the current vehicle state and the output control amounts of the plurality of prediction points after the weighting processing.

In an embodiment of the above automatic driving control method, optionally, in response to that the updated target route is not received and the output control amounts of all the predicted points within the preset time period are not all used to determine the real-time output control amount, the steps S2-S4 are repeated.

In an embodiment of the above automatic driving control method, optionally, in response to receiving the updated target route, repeating steps S1-S4 based on the updated target route.

In an embodiment of the above automatic driving control method, optionally, the current vehicle state includes: transverse speed, longitudinal speed, steering wheel angle degree; and/or the output control quantity and the real-time output control quantity comprise: steering wheel angle or lateral torque control, longitudinal speed or acceleration control.

Another aspect of the present invention also provides an automatic driving control apparatus, including: at least one processor; and a memory coupled to the at least one processor, the memory containing instructions stored therein, which when executed by the at least one processor, cause the control apparatus to perform an autopilot control method as described in any one embodiment of the invention.

Another aspect of the present invention also provides a vehicle having an automatic driving function, the vehicle including an automatic driving control apparatus provided in another aspect of the present invention.

Another aspect of the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements an autopilot control method as described in any one of the embodiments of the present invention.

The invention can effectively solve the influence of positioning drift on vehicle control in the automatic driving process of the vehicle. The method can carry out accurate model prediction according to the target path input to the control end at the current moment, then carry out vehicle control, effectively get rid of the dependence of automatic driving control on positioning, only need the low-frequency target path input to the control end, and the control scheme effectively solves the problems of uncomfortable body feeling and violent control safety risk caused by positioning drift on vehicle control.

Drawings

The above features and advantages of the present disclosure will be better understood upon reading the detailed description of embodiments of the disclosure in conjunction with the following drawings. In the drawings, components are not necessarily drawn to scale, and components having similar relative characteristics or features may have the same or similar reference numerals.

Fig. 1 is a flow chart illustrating an embodiment of an automatic driving control method according to an aspect of the present invention.

FIG. 2 illustrates a schematic diagram of a predictive model provided by an aspect of the present invention.

FIG. 3 illustrates a schematic diagram of a de-localized MPC matrix array provided by an aspect of the present invention.

Fig. 4 is a schematic diagram showing the relationship among the vehicle, the target path, and the predicted point in the present invention.

Fig. 5 is a schematic structural diagram of an embodiment of an automatic driving control device provided by another aspect of the present invention.

Detailed Description

The invention is described in detail below with reference to the figures and the specific embodiments. It is noted that the aspects described below in connection with the figures and the specific embodiments are only exemplary and should not be construed as imposing any limitation on the scope of the present invention.

The following description is presented to enable any person skilled in the art to make and use the invention and is incorporated in the context of a particular application. Various modifications, as well as various uses in different applications will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to a wide range of embodiments. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

In the following detailed description, numerous specific details are set forth in order to provide a more thorough understanding of the invention. It will be apparent, however, to one skilled in the art that the practice of the invention may not necessarily be limited to these specific details. In other instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the present invention.

The reader's attention is directed to all papers and documents which are filed concurrently with this specification and which are open to public inspection with this specification, and the contents of all such papers and documents are incorporated herein by reference. All the features disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. Thus, unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features.

Note that where used, the designations left, right, front, back, top, bottom, positive, negative, clockwise, and counterclockwise are used for convenience only and do not imply any particular fixed orientation. In fact, they are used to reflect the relative position and/or orientation between the various parts of the object. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

It is noted that, where used, further, preferably, still further and more preferably is a brief introduction to the exposition of the alternative embodiment on the basis of the preceding embodiment, the contents of the further, preferably, still further or more preferably back band being combined with the preceding embodiment as a complete constituent of the alternative embodiment. Several further, preferred, still further or more preferred arrangements of the belt after the same embodiment may be combined in any combination to form a further embodiment.

In order to solve the problems that in the prior art, when the positioning is deviated due to the dependence on the current vehicle positioning, the control is too violent, the vehicle is out of control, a user feels uncomfortable, and danger is caused, the invention provides a vehicle with an automatic driving function, and an automatic driving control method and device.

First, please refer to fig. 1 to understand the automatic driving control method provided by the present invention. As shown in fig. 1, an automatic driving control method according to an embodiment of the present invention includes:

step S100: acquiring output control quantities corresponding to a plurality of prediction points in a preset time period after the current moment based on a prediction model according to the target path and the current vehicle state;

step S200: determining a control interval in the preset time period, and acquiring output control quantity of a plurality of corresponding prediction points in the control interval;

step S300: determining real-time output control quantity at the current moment according to the current vehicle state and the output control quantity of the corresponding prediction points in the control interval; and

step S400: and controlling the automatic driving of the vehicle according to the real-time output control quantity.

According to step S100, the target path and the measured data related to the current vehicle state need to be acquired. Wherein the target path, i.e. the objectory, characterizing the expected trajectory of the vehicle may be constituted by various points, as will be understood by a person skilled in the art. The measured data related to the current vehicle state may specifically include the lateral speed, the longitudinal speed, the steering wheel angle degree, and the like of the vehicle at the current time.

According to another aspect of the invention, the predictive model is also constructed from the yaw moment of inertia of the vehicle, the front wheel cornering stiffness, the rear wheel cornering stiffness and the yaw rate based on the road curvature. Fig. 2 shows an MPC model applicable to the present invention, and the above prediction model, i.e., the MPC model corresponding to the MPC control algorithm. The MPC control algorithm can carry out accurate model prediction on the vehicle control trend according to the vehicle state at the current moment (such as the transverse speed, the longitudinal speed, the steering wheel angle degree and the like of the vehicle at the current moment), and carry out accurate vehicle control through the obtained model prediction result, thereby effectively getting rid of the mode of obtaining vehicle error control through positioning.

Specifically, referring to steps S200-S300, the controller predicts the system output (the predicted vehicle position at Kn, the lateral control angle at the current point, and the longitudinal control speed) in a future time domain [ k, k + kp ] by combining the current measured value and the prediction model, and obtains a series of control sequences (including the vehicle lateral steering wheel angle or torque control, and the vehicle longitudinal speed and acceleration control) in a control time domain [ k, k + kc ] by solving the objective function optimization problem with constraints, wherein the lateral control quantity is the steering wheel angle control or torque control, and the longitudinal control quantity is the vehicle acceleration control or speed control, or brake pedal control), wherein [ k, k + kc ] is a time domain belonging to [ k, k + kp ] time domain, that is, the control section [ k, k + kc ] is determined within the preset time period [ k, k + kp ] in step S200. And when no new project _ point is input, sequentially outputting the current control sequence as an actual control quantity, waiting until the next moment k +1, repeating the process, performing a rolling optimization control result through an MPC control algorithm, and finally finishing continuous control.

Please refer to fig. 3 to understand that the optimization by solving the objective function with constraint described above results in a series of control sequences in the control time domain [ k, k + kc ]. The objective function with constraints is the upper and lower bound limits for solving the three arrays of matrix A, B, C in the MPC prediction model, respectively. Since the C matrix can be considered as a constant term, the C matrix can be ignored first in the objective function optimization problem. The matrix implementation is shown in fig. 3.

Further, after step S200, determining the real-time output control amount at the current time according to the current vehicle state and the output control amounts at the plurality of prediction points in the control section further includes:

and performing weighting processing on the output control amounts of the plurality of prediction points, wherein the output control amount of the prediction point closer to the current time is weighted more heavily.

And, the current vehicle state and the weighted output control amounts of the plurality of prediction points are weighted, wherein the weight of the current vehicle state and the weight of the output control amounts can be respectively confirmed according to actual demands.

That is to say, the rolling optimization control is finally completed based on the weighted output of the vehicle state at the current moment and the MPC prediction point, and the smoothness and the stability of the control are ensured. The current real-time output transverse control quantity is ul, the current real-time output longitudinal control quantity is us, the current vehicle transverse state is angle _ prev, the current vehicle longitudinal state is long _ prev, the prediction point longitudinal control quantity is Psn (n is 1,2,3.. n), the prediction point transverse control quantity is Pln (n is 1,2,3.. n), the prediction point transverse control weight is Wln (n is 1,2,3.. n), the prediction point longitudinal control weight is Wsn (n is 1,2,3.. n), and the current vehicle state weight is Wp. Then finally:

ul＝angle_prev×Wlp+Pl1×Wl1+Pl2×Wl2+...+Pln×Wln

us＝long_prev×Wsp+Ps1×Ws1+Ps2×Ws2+...+Psn×Wsn。

it can be understood that, in the present invention, the MPC model is used for prediction, for the system data obtained by prediction, a series of control sequences in the control time domain [ k, k + kc ] is obtained by solving the constrained objective function optimization problem, for the series of control sequences, one of the control quantities is not simply taken as the control quantity of the automatic driving control, but a plurality of control quantities are weighted to comprehensively determine the control quantity for controlling the vehicle, so that the whole control is closer to the prediction. Meanwhile, in order to make the entire control smoother and more stable, when the weights of the plurality of controlled variables are determined, the weight of the output controlled variable at the predicted point that is closer to the current time is set to be larger. That is, for the predicted point lateral control weight Wln (

n

1,2,3.. n), the weight of Wl1 is the largest and the weight of Wln is the smallest. For a predicted point longitudinal control weight of Wsn (n ═ 1,2,3.. n), the weight of Ws1 is the largest and the weight of Wsn is the smallest.

Further, when the final control quantity is determined comprehensively, in order to further ensure the smoothness and stability of the control, the automatic driving control method provided by the invention also determines the weight of the current vehicle state and the weight of the output control quantity of a plurality of prediction points according to the actual requirement, so that the whole control is more practical and smoother.

After the output control amount is obtained, step S400 is executed to control the automatic driving of the vehicle according to the real-time output control amount. After the control amount required for the automatic driving has been provided, the technician of the present invention can implement the above step S400 according to the existing or future different automatic driving methods, which is not limited herein.

As described above, when there is no new target _ point input (i.e., no updated target path is received), the current control sequence is sequentially output as the actual control quantity, and the process is repeated until the next time k +1, and the rolling optimization control result is performed by the MPC control algorithm, thereby finally completing the continuous control. That is, in response to that the updated target path is not received and the output control amounts of all the predicted points within the preset time period are not all used to determine the real-time output control amount, the steps S200 to S400 are repeated.

It will be appreciated that when there is an update to the target _ point (i.e. an updated target path is received), the entire subsequent control will need to be updated synchronously, requiring steps S100-S400 to be repeated based on the updated target path.

So far, the specific implementation of the automatic control driving method provided by the invention has been described. As shown in fig. 4, according to the automatic driving vehicle control scheme based on de-positioning provided by the invention, the automatic driving of the vehicle to fit the target path can be smoothly controlled, and the influence of the positioning drift on the vehicle control in the automatic driving process of the vehicle can be effectively solved. The vehicle can carry out accurate model prediction according to the reject that the control end was input to at this moment, then carries out vehicle control, has effectually got rid of the dependence of autopilot control to the location, only need the low frequency to the reject of control end input target can, the effectual safety risk of solving because the body sense that the drift caused vehicle control is uncomfortable and control is shorn.

In another embodiment, shown in fig. 5, the autopilot control apparatus 500 is embodied in the form of a general-purpose computer device for implementing the steps of the autopilot control method described in any of the above embodiments. For details, please refer to the above description of the automatic driving control method, which is not repeated herein.

The components of the autopilot control apparatus 500 may include one or more memories 501, one or more processors 502, and a bus 503 that connects the various system components (including the memory 501 and the processors 502).

The bus 503 includes a data bus, an address bus, and a control bus. The product of the number of bits of the data bus and the operating frequency is proportional to the data transfer rate, the number of bits of the address bus determines the maximum addressable memory space, and the control bus (read/write) indicates the type of bus cycle and the time at which the present I/O operation is completed. The processor 502 is connected to the memory 501 via a bus 503 and is configured to implement the autopilot control method provided by any of the embodiments described above.

The processor 502 is a final execution unit for information processing and program operation as an operation and control core of the automatic driving control apparatus 500. The operation of all software layers in the computer system will eventually be mapped to the operation of the processor 502 by the instruction set. The processor 502 has the main functions of processing instructions, executing operations, controlling time and processing data.

The memory 501 is a variety of storage devices for storing programs and data in the computer. Memory 501 may include computer system readable media in the form of storage volatile memory. Such as Random Access Memory (RAM)504 and/or cache memory 505.

A Random Access Memory (RAM)504 is an internal memory that exchanges data directly with the processor 502. It can be read and written at any time (except for refreshing), and is fast, usually used as a temporary data storage medium for an operating system or other programs in operation, and the stored data will be lost when power is off. Cache memory (Cache)505 is a level one memory that exists between main memory and processor 502, and is relatively small in size but much faster than main memory, approaching the speed of processor 502.

It should be noted that, in the case that the automatic driving control apparatus 500 includes a plurality of memories 501 and a plurality of processors 502, the plurality of memories 501 and the plurality of processors 502 may have a distributed structure, for example, the automatic driving control apparatus may include memories and processors respectively located at the local end and the background cloud end, and the automatic driving control method described above is implemented by the local end and the background cloud end together. Alternatively, the plurality of memories and processors are directed to the memories and processors in the controllers of the plurality of functional systems provided on the vehicle, and the controllers of the plurality of functional systems collectively implement the automatic driving control method described above. Furthermore, in the embodiment adopting the distributed structure, the specific implementation terminal may be adjusted according to the actual situation in each step, and the specific implementation scheme of each step in a specific terminal should not unduly limit the protection scope of the present invention.

Autopilot control apparatus 500 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. In this embodiment, the storage system 506 may be used to read from and write to non-removable, nonvolatile magnetic media.

The memory 501 may also include at least one set of program modules 507. Program modules 507 may be stored in memory 501. Program modules 507 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment. Program modules 507 generally perform the functions and/or methodologies of embodiments of the invention as described herein.

Autopilot control 500 may also communicate with one or more external devices 508. The external device 508 in the present embodiment includes the various sensors and the like described above to acquire the vehicle state.

Autopilot control 500 may also communicate with one or more devices that enable a user to interact with autopilot control 500 and/or with any device (e.g., network card, modem, etc.) that enables autopilot control 500 to communicate with one or more other computing devices. Such communication may be through input/output (I/O) interfaces 509.

Autopilot control apparatus 500 may also 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 network adapter 510. As shown in fig. 5, network adapter 510 communicates with the other modules of autopilot control device 500 via bus 503. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the autopilot control apparatus 500, 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.

Another aspect of the present invention also provides a vehicle having an automatic driving function, the vehicle including an automatic driving control apparatus as provided in another aspect of the present invention.

Another aspect of the present invention further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the steps of the automatic driving control method described in any of the above embodiments are implemented, please refer to the above description, which is not repeated herein. It is to be understood that the computer readable storage medium may be a system, which includes a plurality of computer readable storage sub-media, and the steps of the automatic driving control method described above are jointly implemented by the plurality of computer readable storage sub-media.

The various illustrative logical modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.

In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk (disk) and disc (disc), as used herein, includes Compact Disc (CD), laser disc, optical disc, Digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks (disks) usually reproduce data magnetically, while discs (discs) reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

The previous description is provided to enable any person skilled in the art to practice the various aspects described herein. It is to be understood that the scope of the invention is to be defined by the appended claims and not by the specific constructions and components of the embodiments illustrated above. Those skilled in the art can make various changes and modifications to the embodiments within the spirit and scope of the present invention, and these changes and modifications also fall within the scope of the present invention.

Claims

1. An automatic driving control method characterized by comprising:

step S1: acquiring output control quantities corresponding to a plurality of prediction points in a preset time period after the current moment based on a prediction model according to the target path and the current vehicle state;

step S2: determining a control interval in the preset time period, and acquiring output control quantity of a plurality of corresponding prediction points in the control interval;

step S3: determining real-time output control quantity at the current moment according to the current vehicle state and the output control quantity of the corresponding prediction points in the control interval; and

step S4: and controlling the automatic driving of the vehicle according to the real-time output control quantity.

2. The automatic driving control method according to claim 1, wherein the prediction model is constructed from a yaw moment of inertia of the vehicle, a front wheel-side cornering stiffness, a rear wheel-side cornering stiffness, and a yaw rate based on a curvature of a road.

3. The automatic control method according to claim 1, wherein determining the real-time output control amount at the present time based on the present vehicle state and the output control amounts at the corresponding plurality of predicted points within the control section further comprises:

4. The automatic control method according to claim 3, wherein determining the real-time output control amount at the present time based on the present vehicle state and the output control amounts at the corresponding plurality of predicted points within the control section further comprises:

and performing weighting processing on the current vehicle state and the output control amounts of the plurality of prediction points after the weighting processing.

5. The automatic driving control method according to claim 1, wherein the steps S2-S4 are repeated in response to that an updated target route is not received and the output control amounts of all the predicted points within the preset time period are not all used to determine a real-time output control amount.

6. The autonomous driving control method of claim 1, wherein in response to receiving the updated target path, steps S1-S4 are repeated based on the updated target path.

7. The automatic driving control method according to claim 1, characterized in that the current vehicle state includes: transverse speed, longitudinal speed, steering wheel angle degree; and/or the presence of a gas in the gas,

the output control quantity and the real-time output control quantity comprise: steering wheel angle or lateral torque control, longitudinal speed or acceleration control.

8. An automatic driving control apparatus comprising:

at least one processor; and

a memory coupled to the at least one processor, the memory containing instructions stored therein that, when executed by the at least one processor, cause the control device to perform the autopilot control method of any of claims 1-7.

9. A vehicle having an automatic driving function, characterized in that the vehicle includes the automatic driving control apparatus according to claim 8.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out an autopilot control method according to one of claims 1 to 7.