CN111016882B - Vehicle control signal calculation method, device, equipment and storage medium - Google Patents
Vehicle control signal calculation method, device, equipment and storage medium Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- 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
- B60W30/02—Control of vehicle driving stability
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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
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
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- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0002—Automatic control, details of type of controller or control system architecture
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Abstract
The embodiment of the specification provides a vehicle control signal calculation method, a vehicle control signal calculation device, vehicle control equipment and a storage medium. The method comprises the following steps: acquiring a reference track, state data and a control signal of a vehicle at the current moment; calculating an initial control signal of the vehicle at the next moment by utilizing a first preset algorithm according to the reference track, the state data and the control signal at the current moment; adjusting the initial control signal by utilizing a second preset algorithm to obtain a reference control signal; and compensating the reference control signal by using the compensation data to obtain a final control signal of the vehicle at the next moment. By the method, when the control signal is calculated, the response data is calculated by different algorithms respectively, and finally the corresponding data is compensated by the compensation data, so that the calculated control signal is more in line with the requirements in practical application, and the vehicle can be stably and accurately controlled.
Description
Technical Field
The embodiment of the specification relates to the technical field of automatic driving, in particular to a vehicle control signal calculation method, a vehicle control signal calculation device, vehicle control equipment and a storage medium.
Background
In recent years, the unmanned technology has been developed rapidly, and unmanned driving is becoming a reality. In the driving process, a calculation module in the unmanned vehicle needs to control an accelerator, a brake and other operation units of the vehicle according to a running path and the state of the vehicle, so as to realize longitudinal control of the vehicle.
However, in the process of controlling the unmanned vehicle, the control signal for the vehicle is often calculated according to the current state and the demand state of the vehicle. However, in the process of practical application, different vehicles have different execution characteristics when executing control signals, for example, heavy trucks often carry non-rigidly connected trailers, have a large mass, and are more prone to dangerous accidents such as rollover and tail flicking compared with automobiles without adjusting the control signals according to the self condition of the trucks; in addition, the vehicle cannot completely adjust the state according to the control signal due to factors such as gear shifting and environmental influence during the driving process. Therefore, the prior art has insufficient stability when unmanned driving is realized, and the robustness of the control system is not robust enough, so that the control of the vehicle cannot be well realized. Therefore, a method for generating a control signal according to the state of the vehicle and the actual driving state to accurately and stably control the unmanned vehicle is needed.
Disclosure of Invention
An object of the embodiments of the present specification is to provide a vehicle control signal calculation method, apparatus, device and storage medium, so as to solve the problem of how to accurately and stably generate a control signal to control an unmanned vehicle.
In order to solve the above technical problem, a vehicle control signal calculation method, an apparatus, a device and a storage medium provided in the embodiments of the present specification are implemented as follows:
a vehicle control signal calculation method includes
Acquiring a reference track, state data and a control signal of a vehicle at the current moment;
calculating an initial control signal of the vehicle at the next moment by utilizing a first preset algorithm according to the reference track, the state data and the control signal at the current moment;
adjusting the initial control signal by utilizing a second preset algorithm to obtain a reference control signal;
and compensating the reference control signal by using the compensation data to obtain a final control signal of the vehicle at the next moment.
A vehicle control signal calculation device comprising:
the data acquisition module is used for acquiring a reference track, state data and a control signal at the current moment of the vehicle;
the initial control signal calculation module is used for calculating an initial control signal of the vehicle at the next moment by utilizing a first preset algorithm according to the reference track, the state data and the control signal at the current moment;
the reference control signal acquisition module is used for adjusting the initial control signal by utilizing a second preset algorithm to obtain a reference control signal;
and the final control signal acquisition module is used for compensating the reference control signal by using the compensation data to obtain a final control signal of the vehicle at the next moment.
A vehicle control signal calculation device comprising a memory and a processor;
the memory to store computer instructions;
the processor to execute the computer instructions to implement the steps of: acquiring a reference track, state data and a control signal of a vehicle at the current moment; calculating an initial control signal of the vehicle at the next moment by utilizing a first preset algorithm according to the reference track, the state data and the control signal at the current moment; adjusting the initial control signal by utilizing a second preset algorithm to obtain a reference control signal; and compensating the reference control signal by using the compensation data to obtain a final control signal of the vehicle at the next moment.
A storage medium having stored thereon computer program instructions which, when executed, implement the vehicle control signal calculation method.
As can be seen from the technical solutions provided by the embodiments of the present specification, when the control signal corresponding to the vehicle is calculated, different prediction algorithms are combined in the calculation process, and not only the state data and the reference trajectory of the vehicle are considered, but also the initial control signal is further adjusted after the initial control signal is calculated. In addition, the compensation data is used for further compensating and correcting the adjustment control signal, so that a final control signal which is more in line with the actual application requirement is obtained, and the stable and accurate control of the vehicle is realized.
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In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the specification, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a method for calculating a vehicle control signal according to an embodiment of the present disclosure;
FIG. 2 is a block diagram of a vehicle control signal calculation device according to an embodiment of the present disclosure;
fig. 3 is a block diagram of a vehicle control signal calculation device according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present specification without any creative effort shall fall within the protection scope of the present specification.
The embodiment of the specification is a method for calculating a vehicle control signal. The control signal may be used to control a motion state of the vehicle. Specifically, the control signal may adjust an acceleration of the vehicle, so as to change a speed of the vehicle, thereby implementing a change of a motion state of the vehicle.
The control signal is used to adjust the speed of the vehicle so that it can reach a predetermined location at a predetermined time. For the vehicle, the control signals include a throttle controller control signal and a brake controller control signal. And the corresponding accelerator controller or brake controller adjusts the control amplitude of the accelerator or brake after receiving the control signal, so that the acceleration of the vehicle is controlled, and the vehicle can be ensured to run according to the received strategy of the planning module.
An embodiment of a vehicle control signal calculation method according to the present specification will be described with reference to fig. 1. The execution main body of the method is computer equipment, and the computer equipment comprises but is not limited to a server, an industrial personal computer, a PC (personal computer) and an all-in-one machine. The method comprises the following specific steps:
s110: a reference trajectory, state data, and a control signal at a current time of the vehicle are obtained.
The reference trajectory is a travel path that the vehicle needs to follow during subsequent movement. For example, after acquiring the specific distribution condition of the road ahead, the detection module in the vehicle determines a driving route behind the vehicle according to the acquired image, and feeds the driving route back to the computer device. The reference trajectory may be a set of several target waypoints, a target waypoint being a respective point on the target travel path. The target path points may be distributed according to a fixed distance, or may be distributed according to other manners, which is not limited herein.
The vehicle is the object on which the control signal acts. The vehicle includes, but is not limited to, a truck, an automobile, a tractor, an electric vehicle, and the like, and in particular, the vehicle may be an autonomous vehicle. The vehicle comprises a detection module for detecting the surrounding environment and the state of the vehicle, a decision module for deciding the operation needed after the operation according to the information detected by the detection module, and a control module for controlling the vehicle according to the decision made by the decision module. In the embodiments of the present description, the computer device implements the control of the motion state and position of the vehicle mainly based on the decision made by the decision module, for example, the reference trajectory.
The state data is used to indicate the state of the vehicle. The status data may include current status data and target status data corresponding to the vehicle. The current state data corresponds to a state of the vehicle at a current time; the target state data represents a state requirement that the vehicle needs to meet. The target state data may be target state data corresponding to at least one future time instant. The target state data may be associated with the reference trajectory, for example, a target state corresponding to a target path point in the reference trajectory may be determined, and all target states may be used as target state data. When the target path point includes more than one target path point, a plurality of target state data may exist correspondingly. The target state data may be determined by a decision module in the vehicle in determining a driving route, a road state, and a state of the vehicle, which is not described herein again.
In particular, the status data may comprise at least one of position data, velocity data and acceleration data. The control of the movement state of the vehicle can be achieved by analyzing and adjusting the position data, the speed data and the acceleration data of the vehicle.
The state data may further include attitude data of the vehicle. The attitude data represents the current attitude of the vehicle relative to the road. Since the vehicle is not a rigid body, the posture of the vehicle itself may be affected during the movement of the vehicle due to the influence thereof caused by the motion state of itself and the surrounding environment. By way of illustration, in a specific example, when a vehicle travels on a left-turn curve, the vehicle as a whole tilts to the left within a certain range with respect to the horizontal plane; when the vehicle takes braking measures, the vehicle as a whole will also tilt forward relative to the horizontal plane. The attitude condition of the vehicle has certain influence on controlling the motion condition of the vehicle, and the influence of the attitude data of the vehicle on the calculation result and the actual application effect needs to be considered when calculating the control signal.
Specifically, the attitude data may include a pitch angle, a roll angle, and the like. The vehicle advancing direction is taken as an x-axis, the direction perpendicular to the x-axis and pointing to the side of the vehicle is taken as a y-axis, and the direction perpendicular to the x-axis and pointing to the lower side of the vehicle is taken as a z-axis. The pitch angle represents the deviation between the x-axis of the vehicle and the ground, and the roll angle represents the deviation between the z-axis of the vehicle and the ground. The accurate and quantitative measurement of the attitude state of the vehicle can be realized through the pitch angle and the roll angle.
S120: and calculating an initial control signal of the vehicle at the next moment by utilizing a first preset algorithm according to the reference track, the state data and the control signal at the current moment.
The initial control signal is a control signal calculated directly from the state data and the reference trajectory without considering the vehicle itself and the current state of the vehicle.
Given the current vehicle state data and the reference trajectory required to travel and the target state data corresponding to the reference trajectory, the change of the motion state of the vehicle while traveling on the reference trajectory, for example, the change of the acceleration or speed of the vehicle, can be calculated. According to the specific change condition of the vehicle motion state, the corresponding control signal corresponding to the vehicle can be solved.
In the process of practical application, certain limitations exist on the state data of the vehicle. For example, the influence of the throttle and the brake on the vehicle speed is limited within a certain interval. In order to ensure that the initial control signal obtained by calculation meets the requirements of practical application, a signal limit range can be set for the initial control signal, and when the initial control signal is calculated, the calculated initial control signal is ensured to be positioned in the signal limit range, so that the requirements of practical application are met better.
In one embodiment, to adapt to dynamic changes in the vehicle motion process and achieve better computational results, a model predictive control algorithm (MPC) may be used to compute the initial control signal. The model predictive control algorithm is combined with a predictive model, an objective function is solved based on a constraint condition to obtain a group of optimal control sequences, actual control quantity is obtained according to the optimal control sequences, and after the actual control quantity is applied, the optimal control sequences are recalculated based on corresponding feedback results, so that rolling optimization is realized.
When the model predictive control algorithm is applied to the embodiment of the specification, the state equation of the system can be set as
And
formula, A, B, C is a coefficient, N isThe number of track points in the reference track,
is the state data of the vehicle,
as a control signal in the present vehicle,
is composed of
At the same time, in pair
And
may be used to convert the solving initial control signal into a solving function
Wherein N is the number of track points in the reference track,
in order to correspond to the state data of the vehicle,
for the control signal corresponding to the vehicle, P, Q, R is a coefficient,
respectively corresponding transpose matrices. By solving the solution of the function and taking the result of the calculation as the initial control signal.
The initial control signal can be used for controlling the vehicle, but because the initial control signal ignores the influence of the vehicle and the current state data on the vehicle motion process, in practical application, the corresponding motion state control cannot be realized based on decision information and the corresponding control effect cannot be obtained. For example, during acceleration of the vehicle, the vehicle may cause jerks due to gear shifting, and a corresponding speed increase may not be achieved directly according to the effect on the throttle control. Therefore, the initial control signal needs to be adjusted to meet the requirements of practical applications.
S130: and adjusting the initial control signal by utilizing a second preset algorithm to obtain a reference control signal.
The adjustment of the initial control signal may result in a reference control signal, taking into account the vehicle itself. The second preset algorithm is a mode of combining an actual application model corresponding to the vehicle and corresponding state data in an application process, and adjusts the initial control signal to obtain a reference control signal, for example, the second preset algorithm may be a model reference adaptive algorithm. The system aimed by the model reference adaptive algorithm generally comprises a reference model, an adjustable system and an adaptive mechanism, so that the adaptive control of the vehicle is realized.
Specifically, adjusting the initial control signal may obtain a vehicle model corresponding to the vehicle, and then adjust the initial control signal based on the vehicle model to obtain the reference control signal.
The signal adjustment model may be a predetermined model constructed according to parameters of a specific vehicle. For example, a signal adjustment model corresponding to the vehicle may be constructed by way of system recognition or big data modeling. The signal adjusting model is used for adjusting the control signal into a signal which is suitable for the actual application condition of the vehicle. For example, the initial control signal may be a rigid body model applied to theory, but in the case where the vehicle is a truck, since the truck is mounted with a trailer, the truck does not move as a continuous whole when moving, and the control signal needs to be adjusted by using a corresponding signal adjustment model so as to conform to the movement law of the truck.
After the initial control signal is adjusted to obtain the reference control signal, an error may occur in the model adaptive control signal during actual application, and therefore, the reference control signal may be corrected according to the state data. Error data corresponding to the model-adapted control signal may be calculated based on the model-adapted control signal and the state data, and the model-adapted control signal may be modified using the error data to obtain a reference control signal.
Specifically, the current control amount may be determined by comparing the reference control signal with a current state amount corresponding to the vehicle, such as a current acceleration. The error data can be calculated, for example, by taking the difference between the reference control signal and the status data and taking the difference as the error data. The method for calculating the error data in practical application is not limited to the above example, and is not described herein again.
After the error data is obtained, the reference control signal can be corrected using the error data. And after the model adaptive control signal is corrected by using the error data, taking the correction result as a corrected reference control signal. Correspondingly, if the reference control signal is corrected, the corrected reference control signal is used to calculate the final control signal in the subsequent steps.
The reference control signal basically can realize the control of the motion state of the vehicle according to a preset target under the condition of conforming to the actual application of the vehicle. However, since the normal moving process of the vehicle may be affected by other factors during the moving process, the posture of the vehicle may not be stable and constant during the moving process of the vehicle, and thus some deviation may occur during the application process. For example, during a turn of the vehicle, the vehicle itself may be slightly tilted to the side, and the vehicle may roll over if the vehicle is not properly controlled.
The initial control signal is adjusted under the condition that the vehicle is considered to obtain the reference control signal, so that the parameter disturbance of the linear control platform in practical application can be better processed, and better longitudinal control precision and control signal calculation robustness are achieved.
S140: and compensating the reference control signal by using the compensation data to obtain a final control signal of the vehicle at the next moment.
The compensation data is a parameter for adjusting the reference control signal based on the attitude data, and is used for ensuring that the vehicle cannot keep balance due to self attitude in practical application. The reference control signal may be adjusted using a feed forward control algorithm.
The feedforward control algorithm can directly adjust the motion system according to the disturbance amount of the motion system, namely when the system disturbance occurs, the correction function is directly generated according to the disturbance amount, so that the deviation caused by the disturbance is eliminated. Accordingly, in the embodiments of the present specification, the corresponding compensation amount is directly calculated according to the current posture data corresponding to the object, and is used for compensating the influence of the state quantity which is not considered when the reference control signal is calculated.
After the compensation data is calculated, the reference control signal may be combined with the compensation data to obtain a final control signal. The final control signal is used for being sent to an execution module of a vehicle to adjust the motion state of the control module. For example, the final control signal may be a throttle controller control signal or a brake controller control signal, so as to control a throttle or a brake of the vehicle, and then regulate and control a motion state of the vehicle.
In one embodiment, a reference control signal weight value and a signal compensation weight value may be set for the reference control signal and the compensation data, and when the final control signal is calculated, the reference control signal and the compensation data may be combined based on the corresponding weight values, so that the calculated final control signal is more suitable for the requirements of practical applications.
In practical application, after the final control signal is obtained, the vehicle can be controlled by using the final control signal; or the final control signal is converted into information which CAN be understood by the corresponding drive-by-wire platform, for example, the information is converted into information in a CAN format.
Through the introduction of the embodiment of the method, the control signal generation method can determine the actual control situation according to the real-time motion state of the vehicle when generating the control signal, also considers the execution situation, the attitude change and other situations of the vehicle, the motion process and the like, and can feed back the external interference, so that the response performance in the control process is enhanced, and the control precision and the robustness are improved.
Fig. 2 is a block diagram of a vehicle control signal calculation apparatus according to the present specification. The vehicle control signal calculation device may be disposed in the computer apparatus, and specifically includes:
a data acquisition module 210 for acquiring a reference trajectory, status data, and a control signal at a current time of the vehicle;
an initial control signal calculation module 220, configured to calculate an initial control signal of the vehicle at a next time by using a first preset algorithm according to the reference trajectory, the state data, and the control signal at the current time;
a reference control signal obtaining module 230, configured to adjust the initial control signal by using a second preset algorithm to obtain a reference control signal;
and a final control signal obtaining module 240, configured to compensate the reference control signal by using the compensation data, so as to obtain a final control signal of the vehicle at the next time.
Fig. 3 is a block diagram of a computer device according to the present disclosure. The computer device may include a memory and a processor.
In this embodiment, the memory may be implemented in any suitable manner. For example, the memory may be a read-only memory, a mechanical hard disk, a solid state disk, a U disk, or the like. The memory may be used to store computer instructions.
In this embodiment, the processor may be implemented in any suitable manner. For example, the processor may take the form of, for example, a microprocessor or processor and a computer-readable medium that stores computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, an embedded microcontroller, and so forth. The processor may execute the computer instructions to perform the steps of: acquiring state data and posture data of a reference track and a vehicle; calculating an initial control signal by using a first preset algorithm according to the reference track and the state data; adjusting the initial control signal by utilizing a second preset algorithm to obtain a reference control signal; calculating compensation data from the attitude data using a third prediction algorithm; and combining the reference control signal and the compensation data to obtain a final control signal.
This specification also provides one embodiment of a computer storage medium. The computer storage medium includes, but is not limited to, a Random Access Memory (RAM), a Read-Only Memory (ROM), a Cache (Cache), a Hard Disk (HDD), a Memory Card (Memory Card), and the like. The computer storage medium stores computer program instructions. The computer program instructions when executed implement: the program instructions or modules of the embodiments corresponding to fig. 1 in this description.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardbyscript Description Language (vhr Description Language), and the like, which are currently used by Hardware compiler-software (Hardware Description Language-software). It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
From the above description of the embodiments, it is clear to those skilled in the art that the present specification can be implemented by software plus a necessary general hardware platform. Based on such understanding, the technical solutions of the present specification may be essentially or partially implemented in the form of software products, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and include instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments of the present specification.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The description is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
While the specification has been described with examples, those skilled in the art will appreciate that there are numerous variations and permutations of the specification that do not depart from the spirit of the specification, and it is intended that the appended claims include such variations and modifications that do not depart from the spirit of the specification.
Claims (15)
1. A vehicle control signal calculation method, characterized in that the method comprises
Acquiring a reference track, state data and a control signal of a vehicle at the current moment; the state data comprises attitude data;
calculating an initial control signal of the vehicle at the next moment by utilizing a first preset algorithm according to the reference track, the state data and the control signal at the current moment; the initial control signal comprises a control signal calculated without regard to the vehicle itself and the current state of the vehicle;
adjusting the initial control signal by utilizing a second preset algorithm to obtain a reference control signal; the second preset algorithm includes an algorithm corresponding to an actual application model of the vehicle and the state data;
compensating the reference control signal by using compensation data to obtain a final control signal of the vehicle at the next moment; the compensation data is obtained according to the following mode: and calculating compensation data by using a feedforward control algorithm according to the attitude data.
2. The method of claim 1, wherein the status data comprises at least one of: current time state data, at least one future time target state data.
3. The method of claim 1, wherein the status data comprises at least one of: position data, velocity data, acceleration data.
4. The method of claim 1, wherein the initial control signal corresponds to a signal limit range; the calculating of the first preset algorithm of the reference track of the initial control signal of the vehicle at the next moment by using the first preset algorithm according to the reference track, the state data and the control signal at the current moment comprises the following steps:
and calculating the initial control signal of the vehicle reference track at the next moment within the signal limit range by utilizing a first preset algorithm according to the reference track, the state data and the control signal at the current moment.
5. The method of claim 1, wherein calculating an initial control signal reference trajectory for the vehicle at a next time using a first preset algorithm based on the reference trajectory, the state data, and the control signal at the current time comprises:
and calculating an initial control signal of the vehicle at the next moment by using a model predictive control algorithm according to the reference track, the state data and the control signal at the current moment.
6. The method of claim 1, wherein said adjusting the initial control signal using a second predetermined algorithm to obtain a second predetermined algorithm for the reference control signal comprises:
and adjusting the initial control signal by using a model reference adaptive algorithm to obtain a reference control signal.
7. The method of claim 6, wherein said adjusting the initial control signal using a model reference adaptive algorithm to obtain a reference control signal comprises:
obtaining a vehicle model corresponding to the vehicle;
and calculating the initial control signal based on the vehicle model to obtain a reference control signal.
8. The method of claim 7, wherein after calculating the initial control signal based on the vehicle model to obtain a reference control signal, further comprising:
calculating error data corresponding to the reference control signal based on the reference control signal and the control signal at the current time;
correcting the reference control signal using the error data;
correspondingly, the compensating the reference control signal by using the compensation data to obtain a final control signal of the vehicle at the next time includes:
and compensating the corrected reference control signal by using the step data to obtain a final control signal of the vehicle at the next moment.
9. The method of claim 8, wherein said calculating error data corresponding to the reference control signal based on the reference control signal and the control signal at the current time comprises:
and calculating the difference value of the reference control signal and the control signal at the current moment as error data.
10. The method of claim 1, wherein the pose data comprises at least one of: pitch angle, roll angle.
11. The method of claim 1, wherein the reference control signal corresponds to a reference control signal weight value; the compensation data corresponds to a signal compensation weight value; the compensating the reference control signal by using the compensation data to obtain a final control signal of the vehicle at the next moment comprises:
and obtaining a final control signal of the vehicle at the next moment by combining the reference control signal and the compensation data based on the reference control signal weight value and the signal compensation weight value.
12. The method of claim 1, wherein the final control signal comprises at least one of: throttle controller control signal, brake controller control signal.
13. A vehicle control signal calculation device characterized by comprising:
the data acquisition module is used for acquiring a reference track, state data and a control signal at the current moment of the vehicle; the state data comprises attitude data;
the initial control signal calculation module is used for calculating an initial control signal of the vehicle at the next moment by utilizing a first preset algorithm according to the reference track, the state data and the control signal at the current moment; the initial control signal comprises a control signal calculated without regard to the vehicle itself and the current state of the vehicle;
the reference control signal acquisition module is used for adjusting the initial control signal by utilizing a second preset algorithm to obtain a reference control signal; the second preset algorithm includes an algorithm corresponding to an actual application model of the vehicle and the state data;
the final control signal acquisition module is used for compensating the reference control signal by using compensation data to obtain a final control signal of the vehicle at the next moment; the compensation data is obtained according to the following mode: and calculating compensation data by using a feedforward control algorithm according to the attitude data.
14. A vehicle control signal calculation device comprising a memory and a processor;
the memory to store computer instructions;
the processor to execute the computer instructions to implement the steps of: acquiring a reference track, state data and a control signal of a vehicle at the current moment; the state data comprises attitude data; calculating an initial control signal of the vehicle at the next moment by utilizing a first preset algorithm according to the reference track, the state data and the control signal at the current moment; the initial control signal comprises a control signal calculated without regard to the vehicle itself and the current state of the vehicle; adjusting the initial control signal by utilizing a second preset algorithm to obtain a reference control signal; the second preset algorithm includes an algorithm corresponding to an actual application model of the vehicle and the state data; compensating the reference control signal by using compensation data to obtain a final control signal of the vehicle at the next moment; the compensation data is obtained according to the following mode: and calculating compensation data by using a feedforward control algorithm according to the attitude data.
15. A storage medium having computer program instructions stored thereon, the computer program instructions, when executed, implementing the method steps of any of claims 1-12.
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