Control method, device and electronic equipment of vehicle

Abstract

The application discloses a control method, device and electronic equipment of a vehicle, the method comprises the following steps: acquiring a planning position of the vehicle in a planning track, and a projection position of an actual position of the vehicle projected on the planning track; determining compensation information for compensating an actual driving parameter of the vehicle based on the planning position and the projection position; determining a longitudinal control parameter of the vehicle based on the compensation information, the actual driving parameter and a planning driving parameter of the vehicle, wherein the planning driving parameter is used for representing a driving parameter planned for the vehicle, and the longitudinal control parameter is used for representing a control parameter for longitudinally controlling driving of the vehicle; and controlling driving of the vehicle by a longitudinal controller of the vehicle based on the longitudinal control parameter. The application solves the technical problem of low effectiveness of control of the vehicle.

Description

Technical Field

[0001] This application relates to the field of vehicles, and more specifically, to a vehicle control method, apparatus, and electronic device. Background Technology

[0002] Currently, there are two types of longitudinal control methods for vehicles: one is the longitudinal control method based on the proportional-integral-derivative (PID) algorithm, and the other is the longitudinal control method based on the model predictive control algorithm.

[0003] However, there are drawbacks in implementing these two methods. For example, when implementing a longitudinal control method based on PID algorithms to control vehicle movement, it can only guarantee control performance under normal driving conditions. It cannot guarantee good speed control under driving conditions such as going uphill or downhill, or crossing speed bumps at low speeds. Moreover, during acceleration and deceleration tracking, the vehicle is prone to frequent speed oscillations and vibrations. When implementing a longitudinal control method based on model predictive control algorithms to control vehicle movement, it requires excessive computing power, which is unsuitable for hardware platforms with low to medium computing power.

[0004] Therefore, regardless of which method is used, there will be limitations in controlling the vehicle under different operating conditions, resulting in a low effectiveness of vehicle control.

[0005] There is currently no effective solution to the technical problem of low control effectiveness of the aforementioned vehicles. Summary of the Invention

[0006] This application provides a vehicle control method, apparatus, and electronic device to at least address the technical problem of low vehicle control effectiveness.

[0007] According to one aspect of the embodiments of this application, a vehicle control method is provided. The method includes: acquiring the planned position of the vehicle in a planned trajectory, and the projected position of the vehicle's actual position onto the planned trajectory; determining compensation information for compensating the actual driving parameters of the vehicle based on the planned position and the projected position; determining longitudinal control parameters of the vehicle based on the compensation information, the actual driving parameters, and the planned driving parameters of the vehicle, wherein the planned driving parameters are used to represent the planned driving parameters of the vehicle, and the longitudinal control parameters are used to represent the control parameters for longitudinally controlling the driving of the vehicle; and controlling the vehicle's driving based on the longitudinal control parameters using the vehicle's longitudinal controller.

[0008] Furthermore, based on the compensation information, actual driving parameters, and planned driving parameters of the vehicle, the longitudinal control parameters of the vehicle are determined, including: inputting the compensation information, actual driving parameters, and planned driving parameters into the vehicle's active disturbance rejection controller for disturbance rejection processing to obtain the disturbance rejection processing result, wherein the disturbance rejection processing result is used to represent the acceleration that the vehicle should achieve when the disturbance factors affecting the vehicle's driving are eliminated; and based on the disturbance rejection processing result, the longitudinal control parameters are determined.

[0009] Furthermore, the planned driving parameters include: the planned speed and planned acceleration for the vehicle. The active disturbance rejection controller includes: a differentiator and an observer. The active disturbance rejection controller inputs compensation information, actual driving parameters, and planned driving parameters to the vehicle for disturbance rejection processing to obtain the disturbance rejection processing result. This includes: superimposing the speed compensation amount corresponding to the compensation information with the planned speed to obtain the input signal of the active disturbance rejection controller; inputting the input signal to the differentiator for differentiating processing to obtain the differentiating processing result; and inputting the actual speed, including the actual driving parameters, to the observer for observation processing to obtain the observation result. The differentiating processing result represents the differential value of the input signal, and the observation result represents the observation speed the vehicle is to reach, as well as the degree of disturbance caused by disturbance factors causing the vehicle to deviate from the observation speed. In the active disturbance rejection controller, the disturbance rejection processing result is determined based on the differentiating processing result, the observation result, and the planned acceleration.

[0010] Furthermore, the active disturbance rejection controller includes a virtual generator, wherein, in the active disturbance rejection controller, based on the differential processing result, the observation result, and the planned acceleration, the disturbance rejection processing result is determined, including: inputting the difference between the differential value corresponding to the differential processing result and the observed velocity corresponding to the observation result into the virtual generator to generate a signal, thereby obtaining a virtual control signal; in the active disturbance rejection controller, the virtual control signal and the planned acceleration are superimposed to obtain a superposition result; in the active disturbance rejection controller, the disturbance rejection processing result is determined based on the superposition result, the observation result, and the vehicle's gain parameters.

[0011] Furthermore, in the active disturbance rejection controller, based on the superposition result, the observation result, and the vehicle's gain parameter, the disturbance rejection processing result is determined, including: in the active disturbance rejection controller, removing the disturbance degree corresponding to the observation result from the superposition result to obtain the removal result; in the active disturbance rejection controller, determining the quotient between the removal result and the gain parameter as the acceleration corresponding to the disturbance rejection processing result.

[0012] Furthermore, based on the disturbance rejection processing results, the longitudinal control parameters are determined, including: determining the interface type of the longitudinal controller; and determining the longitudinal control parameters based on the interface type and the disturbance rejection processing results.

[0013] Furthermore, based on the interface type and the disturbance rejection processing result, the longitudinal control parameters are determined, including: in response to the interface type being a torque interface type, a preset torque matching the acceleration corresponding to the disturbance rejection processing result is determined from the calibration library as the longitudinal control parameter, wherein the calibration library includes: different preset torques matching different accelerations; in response to the interface type being an acceleration interface type, the acceleration corresponding to the disturbance rejection processing result is determined as the longitudinal control parameter.

[0014] Furthermore, based on the planned position and the projected position, compensation information is determined to compensate for the actual driving parameters of the vehicle, including: determining the longitudinal position deviation between the planned position and the projected position; compensating for the longitudinal position deviation to obtain compensation information.

[0015] According to another aspect of the embodiments of this application, a vehicle control device is also provided. The device includes: an acquisition unit, configured to acquire the planned position of the vehicle in a planned trajectory, and the projected position of the vehicle's actual position onto the planned trajectory; a first determination unit, configured to determine compensation information for compensating the actual driving parameters of the vehicle based on the planned position and the projected position; a second determination unit, configured to determine longitudinal control parameters of the vehicle based on the compensation information, the actual driving parameters, and the planned driving parameters of the vehicle, wherein the planned driving parameters are used to represent the planned driving parameters of the vehicle, and the longitudinal control parameters are used to represent the control parameters for longitudinally controlling the driving of the vehicle; and a control unit, configured to control the driving of the vehicle based on the longitudinal control parameters through the vehicle's longitudinal controller.

[0016] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0017] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0018] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0019] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0020] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0021] According to another aspect of the embodiments of this application, a vehicle is also provided, which includes the electronic equipment described in this application.

[0022] In this embodiment, the planned position of the vehicle on the planned trajectory and the projected position of the vehicle's actual position onto the planned trajectory are obtained. Based on the planned position and the projected position, compensation information for compensating the vehicle's actual driving parameters is determined. Based on the compensation information, the actual driving parameters, and the planned driving parameters, the longitudinal control parameters of the vehicle are determined. The vehicle's driving is then controlled by the vehicle's longitudinal controller based on the longitudinal control parameters. Because this embodiment, when controlling the vehicle, determines the compensation information for compensating the vehicle's actual driving parameters based on the obtained planned position and projected position, and then determines the longitudinal control parameters for controlling the vehicle's driving based on the compensation information, actual driving parameters, and planned driving parameters, and then controls the vehicle's driving based on the longitudinal control parameters, it achieves the goal of avoiding frequent vehicle vibration, thus solving the technical problem of low vehicle control effectiveness and improving the technical effect of vehicle control effectiveness. Attached Figure Description

[0023] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0024] Figure 1 This is a schematic diagram illustrating an application scenario of a vehicle control method according to an embodiment of this application;

[0025] Figure 2 This is a flowchart of a vehicle control method according to an embodiment of this application;

[0026] Figure 3(a) is a flowchart of a vehicle intelligent driving longitudinal control method according to an embodiment of this application;

[0027] Figure 3(b) is a schematic diagram of an ADRC speed controller according to an embodiment of this application;

[0028] Figure 4 This is a schematic diagram of a longitudinal control architecture for intelligent driving of a vehicle according to an embodiment of this application;

[0029] Figure 5 This is a structural block diagram of a vehicle control device according to an embodiment of this application;

[0030] Figure 6 This is a schematic diagram of an electronic device according to an embodiment of this application; Detailed Implementation

[0031] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] According to an embodiment of this application, an embodiment of a vehicle control method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0034] As an optional implementation, the above-described vehicle control method can be applied, but is not limited to, to applications such as... Figure 1 The application scenarios shown. Figure 1 This is a schematic diagram illustrating an application scenario of a vehicle control method according to an embodiment of this application, such as... Figure 1As shown, in the application scenario, terminal device 10 can communicate with server 13 via network 11, but is not limited to this. Server 13 can perform operations on the database, such as write or read data operations. Terminal device 10 may include, but is not limited to, a human-computer interaction screen, a processor, and a memory. The human-computer interaction screen can be used to display virtual machines on mobile terminal 10, but is not limited to this. Vehicle 12 can be used to respond to the aforementioned human-computer interaction operations, execute corresponding operations, or generate corresponding instructions and send the generated instructions to server 13.

[0035] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be executed in a different order than that shown here. The vehicle control method of this application may include: step S102, obtaining the planned position of the vehicle on the planned trajectory, and the projected position of the vehicle's actual position onto the planned trajectory; step S104, determining compensation information for compensating the actual driving parameters of the vehicle based on the planned position and the projected position; step S106, determining the longitudinal control parameters of the vehicle based on the compensation information, the actual driving parameters, and the planned driving parameters of the vehicle; and step S108, controlling the vehicle's movement based on the longitudinal control parameters using the vehicle's longitudinal controller.

[0036] It should be noted that all information and data involved in this application (including but not limited to actual location and actual driving parameters) are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of such data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0037] Figure 2 This is a flowchart of a vehicle control method according to an embodiment of this application, such as... Figure 2 As shown, the method may include the following steps.

[0038] Step S202: Obtain the planned position of the vehicle in the planned trajectory, and the projected position of the vehicle's actual position onto the planned trajectory.

[0039] In the technical solution provided by step S202 of this application, the planned trajectory can be used to represent the driving trajectory planned by the vehicle. For example, if the vehicle is driving intelligently on a highway, the planned trajectory can be used to represent the driving trajectory planned by the vehicle that meets the driving requirements of the highway. This is only an example and is not specifically limited.

[0040] In this embodiment, the planned location corresponds one-to-one with the travel time. That is, if the travel time is the current time, then the planned location is the location planned within the planned trajectory for the current time. For example, the current time may also be referred to as the current time in the following text; this is only an example and not a specific limitation.

[0041] In this embodiment, the aforementioned actual position can be used to represent the position reached by the vehicle during actual driving. The aforementioned actual position also corresponds one-to-one with the driving time. That is, if the driving time is the current time, then the aforementioned actual position is the position reached at the current time.

[0042] In this embodiment, the aforementioned projection position can be used to represent the position of the projection point on the planned trajectory from the actual position. For example, the aforementioned projection position can also be referred to as the projection point position in the following text.

[0043] In this embodiment, the planned position of the vehicle within the planned trajectory and the projected position of the vehicle's actual position onto the planned trajectory are obtained. Optionally, when the vehicle's intelligent driving or autonomous driving function is activated, the planned trajectory can be extracted from the vehicle's planning data. This planning data may include the planned trajectory and driving parameters for the vehicle. The planned position, i.e., the planned position for the current driving time, can be obtained from the planned trajectory. Furthermore, the actual position reached by the vehicle during the driving time is collected, and the collected actual position is projected onto the planned trajectory to obtain the projected position, thereby achieving the goal of obtaining both the planned position and the projected position.

[0044] Step S204: Based on the planned location and the projected location, determine the compensation information used to compensate for the actual driving parameters of the vehicle.

[0045] In the technical solution provided by step S204 of this application, the above compensation information can be used to represent the speed compensation amount (speed_offset) of the actual speed included in the compensation of the actual driving parameters.

[0046] In this embodiment, the aforementioned actual driving parameters can be used to represent the driving parameters achieved by the vehicle during actual driving. These actual driving parameters may include at least one of the following: actual speed, actual acceleration, and actual torque.

[0047] In this embodiment, after obtaining the planned position of the vehicle on the planned trajectory and the projected position of the vehicle's actual position onto the planned trajectory, compensation information for compensating the vehicle's actual driving parameters is determined based on the planned position and the projected position. Optionally, this embodiment compares the deviation between the planned position and the projected position to obtain the longitudinal position deviation between them. Based on this longitudinal position deviation, compensation information can be determined, thereby achieving the goal of combining the planned position and the projected position to determine the compensation information for compensating the actual driving parameters.

[0048] Optionally, if the planned time corresponding to the above-mentioned projected position on the planned trajectory is earlier than or equal to the actual time of reaching the above-mentioned actual position, then the above-mentioned longitudinal position deviation is increased, and the increased above-mentioned longitudinal position deviation is determined as the speed compensation amount used to compensate for the actual speed.

[0049] Optionally, if the planned time corresponding to the above-mentioned projected position on the planned trajectory is later than the actual time of arrival at the above-mentioned actual position, the above-mentioned longitudinal position deviation is reduced, and the reduced above-mentioned longitudinal position deviation is determined as the speed compensation amount used to compensate for the actual speed.

[0050] Step S206: Based on the compensation information, actual driving parameters, and planned driving parameters of the vehicle, determine the longitudinal control parameters of the vehicle.

[0051] In the technical solution provided by step S206 of this application, the aforementioned planned driving parameters can be used to represent the planned driving parameters of the vehicle. These planned driving parameters may include: planned speed, planned acceleration, and planned torque, etc., for the vehicle.

[0052] In this embodiment, the aforementioned longitudinal control parameters can be used to represent control parameters for longitudinally controlling vehicle movement. These longitudinal control parameters may include: torque and / or acceleration for longitudinally controlling vehicle movement.

[0053] In this embodiment, after determining compensation information for compensating the vehicle's actual driving parameters based on the planned and projected positions, the vehicle's longitudinal control parameters are determined based on the compensation information, the actual driving parameters, and the vehicle's planned driving parameters. Optionally, based on the determined compensation information for the actual driving parameters, this embodiment utilizes an anti-disturbance processing model to perform anti-disturbance processing on the aforementioned compensation information, actual driving parameters, and the vehicle's planned driving parameters, obtaining an anti-disturbance processing result. The anti-disturbance processing model can be used to represent the anti-disturbance processing relationship between the compensation information, actual driving parameters, planned driving parameters, and the anti-disturbance processing result. The anti-disturbance processing result can be used to represent the acceleration the vehicle needs to achieve after eliminating disturbance factors affecting vehicle movement. Based on the aforementioned anti-disturbance processing result, the longitudinal control parameters can be determined, thereby achieving the goal of determining the control parameters for longitudinal vehicle movement.

[0054] Optionally, a preset torque that matches the acceleration corresponding to the above disturbance rejection processing result is determined as the torque in the longitudinal control parameters, and / or, the acceleration corresponding to the above disturbance rejection processing result is determined as the acceleration in the longitudinal control parameters.

[0055] It should be noted that the above-described method for determining the longitudinal control parameters of a vehicle is merely illustrative and is not intended to impose specific limitations. Any method that can combine compensation information, actual driving parameters, and the vehicle's planned driving parameters to determine the aforementioned longitudinal control parameters falls within the protection scope of this application's embodiments, and will not be described in detail here.

[0056] Step S208: The vehicle's driving is controlled by the vehicle's longitudinal controller based on the longitudinal control parameters.

[0057] In the technical solution provided by step S208 of this application, the aforementioned longitudinal controller is the longitudinal actuator of the vehicle. Specifically, the longitudinal controller can be used to accelerate and brake the vehicle in the longitudinal dimension.

[0058] In this embodiment, after determining the longitudinal control parameters of the vehicle based on compensation information, actual driving parameters, and the planned driving parameters of the vehicle, the vehicle's driving is controlled by the vehicle's longitudinal controller based on the longitudinal control parameters.

[0059] Optionally, based on the determined longitudinal control parameters, this embodiment controls the vehicle's movement according to the torque in the longitudinal control parameters by the vehicle's longitudinal controller, and / or controls the vehicle's movement according to the acceleration in the longitudinal control parameters by the vehicle's longitudinal controller, thereby achieving the purpose of controlling the vehicle's movement based on the longitudinal control parameters by the longitudinal controller.

[0060] In steps S202 to S208 of this application, the planned position of the vehicle on the planned trajectory and the projected position of the vehicle's actual position onto the planned trajectory are obtained. Based on the planned position and the projected position, compensation information for compensating the actual driving parameters of the vehicle is determined. Based on the compensation information, the actual driving parameters, and the planned driving parameters of the vehicle, the longitudinal control parameters of the vehicle are determined. The vehicle's driving is then controlled by the vehicle's longitudinal controller based on the longitudinal control parameters. Because this embodiment of the application, when controlling the vehicle, after obtaining the planned position and the projected position, combines these two positions to determine the compensation information for compensating the actual driving parameters of the vehicle, and then combines the compensation information, the actual driving parameters, and the planned driving parameters to determine the longitudinal control parameters for controlling the vehicle's driving, and then controls the vehicle's driving by the vehicle's longitudinal controller based on the longitudinal control parameters for controlling the vehicle's driving, the purpose of avoiding frequent vehicle vibration is achieved, thereby solving the technical problem of low vehicle control effectiveness and thus realizing the technical effect of improving the effectiveness of vehicle control.

[0061] The following section further describes the steps of determining the longitudinal control parameters of the vehicle based on compensation information, actual driving parameters, and planned driving parameters of the vehicle in this embodiment.

[0062] As an optional embodiment, step S206, based on compensation information, actual driving parameters and planned driving parameters of the vehicle, determines the longitudinal control parameters of the vehicle, including: inputting compensation information, actual driving parameters and planned driving parameters into the vehicle's active disturbance rejection controller for disturbance rejection processing to obtain disturbance rejection processing results; and determining the longitudinal control parameters based on the disturbance rejection processing results.

[0063] In this embodiment, the active disturbance rejection controller can be an active disturbance rejection speed controller (ADRC).

[0064] In this embodiment, the disturbance rejection processing result can be used to represent the acceleration that the vehicle needs to achieve after eliminating disturbances affecting the vehicle's movement. For example, the disturbance rejection processing result can be a control quantity u, which can also be called a control signal.

[0065] In this embodiment, the aforementioned disturbance factors can be used to represent factors that disturb vehicle movement. These disturbance factors may include at least one of the following: gravity component disturbance caused by changes in road slope, disturbance caused by changes in air resistance and wind speed, disturbance caused by changes in tire-road adhesion coefficient, and disturbance caused by transmission system losses and mechanical clearances, etc.

[0066] In this embodiment, after determining the compensation information for compensating the actual driving parameters of the vehicle based on the planned location and the projected location, the compensation information, the actual driving parameters and the planned driving parameters are input to the vehicle's active anti-disturbance controller for anti-disturbance processing to obtain the anti-disturbance processing result.

[0067] Optionally, based on the compensation information of the actual driving parameters, this embodiment inputs the speed compensation amount speed_offset corresponding to the compensation information, the actual speed included in the actual driving parameters, and the planned speed and planned acceleration included in the planned driving parameters to the ADRC speed controller for disturbance rejection processing, so as to obtain the control amount u.

[0068] In this embodiment, after inputting compensation information, actual driving parameters, and planned driving parameters into the vehicle's active disturbance rejection controller for disturbance rejection processing and obtaining the disturbance rejection processing result, the longitudinal control parameters are determined based on the disturbance rejection processing result.

[0069] Optionally, this embodiment determines the acceleration corresponding to the disturbance rejection processing result, and then determines the longitudinal control parameters based on the acceleration corresponding to the disturbance rejection processing result. For example, a preset torque matching the acceleration corresponding to the disturbance rejection processing result is determined as the torque in the longitudinal control parameters, and / or the acceleration corresponding to the disturbance rejection processing result is determined as the acceleration in the longitudinal control parameters. This achieves the purpose of determining the control parameters for longitudinal vehicle movement, thereby realizing the technical effect of improving the accuracy of the longitudinal control parameters.

[0070] The following section further explains the steps of inputting compensation information, actual driving parameters, and planned driving parameters into the vehicle's active anti-disturbance controller to perform anti-disturbance processing and obtain the anti-disturbance processing result.

[0071] As an optional embodiment, the compensation information, actual driving parameters, and planned driving parameters are input to the vehicle's active disturbance rejection controller for disturbance rejection processing to obtain the disturbance rejection processing result. This includes: superimposing the speed compensation amount corresponding to the compensation information and the planned speed to obtain the input signal of the active disturbance rejection controller; inputting the input signal to a differentiator for differentiation processing to obtain the differentiation processing result; and inputting the actual speed, including the actual driving parameters, to an observer for observation processing to obtain the observation result. In the active disturbance rejection controller, the disturbance rejection processing result is determined based on the differentiation processing result, the observation result, and the planned acceleration.

[0072] In this embodiment, the planned driving parameters may include a planned speed (plan_v) and a planned acceleration (plan_accel) for the vehicle. For example, the planned speed may also be referred to as the planned vehicle speed below.

[0073] In this embodiment, the active disturbance rejection controller may include a differentiator and an observer. The differentiator may be a tracking differentiator (TD), and the observer may be a linear extended state observer (LESO).

[0074] In this embodiment, the result of the differentiation process described above can be used to represent the differential value of the input signal. x 1.

[0075] In this embodiment, the above observation results can be used to represent the observed speed that the vehicle is expected to reach, and the degree of disturbance caused by perturbation factors that cause the vehicle to deviate from the observed speed. For example, the above observed speed can be represented by... The degree of the above disturbance can be expressed as follows: To express.

[0076] In this embodiment, after determining the compensation information for compensating the actual driving parameters of the vehicle based on the planned position and the projected position, the speed compensation amount corresponding to the compensation information and the planned speed are superimposed to obtain the input signal of the active disturbance rejection controller. The input signal is input to the differentiator for differentiation processing to obtain the differentiation processing result. The actual speed, including the actual driving parameters, is input to the observer for observation processing to obtain the observation result.

[0077] Optionally, in this embodiment, the planned vehicle speed *plan_v* plus the speed compensation amount *speed_offset* output by the position controller is used as the input signal for the ADRC speed controller. This input signal is then fed into a tracking differentiator *TD* for tracking and differentiation processing to obtain the derivative of the input signal. This tracking differentiator can be implemented using the Fhan function, and its output value is the tracked value of the planned vehicle speed. x 1. The vehicle's actual speed v is also input into the Linear Extended State Observer (LESO) for observation processing, which yields the observed speed the vehicle is expected to reach. and total disturbance .

[0078] For example, the extended state observer LESO described above can be constructed using equations (1) to (6) as follows.

[0079] (1)

[0080] in, It can be used to represent an estimated value of the expanded state of an autonomous driving system. The above equation (1) can be used to represent the total disturbance of the autonomous driving system, u can be used to represent the input data of the autonomous driving system, and b can be used to represent the gain of the input data. The above equation (1) can be further written as the following equation (2).

[0081] (2)

[0082] Here, b0 can be used to represent the estimated value of the gain of the input data.

[0083] Let y, Given f as shown in equation (3), we can obtain the state transition equation shown in equation (4):

[0084] (3)

[0085] (4)

[0086] in, . That is, The state transition equation shown in equation (4) above can be expressed as equation (5) below.

[0087] (5)

[0088] in, It can be used to represent an estimate of the state. It can be used to represent an estimated value of the output. It can be used to represent the observer gain matrix. Substituting equation (5.2) into equation (5.1), we can obtain equation (6), and expand equation (6) into equation (7).

[0089] (6)

[0090] (7)

[0091] According to observer-related theory, the observer gain matrix The system matrix of the state observer can be expressed as follows (8). We use the characteristic roots to find them.

[0092] (8)

[0093] The poles are uniformly set at -w0, that is, Therefore, the gain of LESO is .

[0094] By constructing a well-defined extended state observer, the vehicle speed can be estimated. Total disturbance In other words, by following the above procedure to debug and calibrate appropriate w0 and b0, the system gain can be obtained, and then the vehicle speed can be calculated. Total disturbance .

[0095] In this embodiment, after obtaining the differential processing result and the observation result, the active disturbance rejection controller determines the disturbance rejection result based on the differential processing result, the observation result and the planned acceleration.

[0096] Optionally, in this embodiment, the derivative of the input signal in the ADRC speed controller... x 1. Observe vehicle speed Total disturbance By performing an acceleration conversion with the planned acceleration plan_accel, the control quantity u that the vehicle needs to achieve can be obtained after eliminating disturbance factors that affect the vehicle's movement. This achieves the goal of determining the anti-disturbance processing result and thus realizes the technical effect of improving the accuracy of the anti-disturbance processing result.

[0097] The following section further explains the steps of determining the disturbance rejection result based on the differential processing result, the observation result, and the planned acceleration in the active disturbance rejection controller of this embodiment.

[0098] As an optional embodiment, in the active disturbance rejection controller, the disturbance rejection result is determined based on the differential processing result, the observation result, and the planned acceleration. This includes: inputting the difference between the differential value corresponding to the differential processing result and the observed velocity corresponding to the observation result into a virtual generator to generate a signal, thereby obtaining a virtual control signal; in the active disturbance rejection controller, superimposing the virtual control signal and the planned acceleration to obtain a superposition result; and in the active disturbance rejection controller, determining the disturbance rejection result based on the superposition result, the observation result, and the vehicle's gain parameters.

[0099] In this embodiment, the active disturbance rejection controller may include a virtual generator. For example, the virtual generator may also be referred to as a virtual controller in the following text.

[0100] In this embodiment, the virtual control signal can be the result of a nonlinear transformation. For example, the virtual control signal can be represented by u0.

[0101] In this embodiment, after obtaining the differential processing result and the observation result, the difference between the differential value corresponding to the differential processing result and the observed velocity corresponding to the observation result is input into the virtual generator to generate a signal and obtain a virtual control signal. In the active disturbance rejection controller, the virtual control signal and the planned acceleration are superimposed to obtain the superposition result. Then, in the active disturbance rejection controller, the disturbance rejection processing result is determined based on the superposition result, the observation result and the vehicle's gain parameters.

[0102] Optionally, in this embodiment, the derivative value of the input signal is determined in the ADRC speed controller. x 1. Observed vehicle speed The difference e between them is input into the virtual generator for nonlinear transformation, yielding the nonlinear transformation result fal(e, α, δ). Using the calibrated parameters k... p By adjusting the nonlinear transformation result fal(e, α, δ), an adjusted nonlinear transformation result can be obtained. For example, the calibrated parameter k... p The product k between the nonlinear transformation result fal(e, α, δ) and the product k p fal(e, α, δ) is the adjusted nonlinear transformation result.

[0103] Optionally, the adjusted nonlinear transformation result can be superimposed with the planning acceleration plan_accel, for example, by combining the above product k. p The superposition of fal(e, α, δ) and plan_accel yields the superposition result k. p fal(e, α, δ) + plan_accel, that is, u0 + plan_accel.

[0104] In this embodiment, the aforementioned gain parameter can be the estimated gain b0 of the autonomous driving system.

[0105] Optionally, the adjusted nonlinear transformation result can be superimposed with the planned acceleration plan_accel to obtain a superimposed result. In the ADRC velocity controller, this superimposed result is combined with the total disturbance. The gain parameter can be used to determine the control quantity u that the vehicle needs to achieve after eliminating disturbances to its movement. For example, in an ADRC speed controller, the total disturbance is removed from the above superposition result. By adjusting the superposition result after removing the total disturbance using the gain parameter, the adjusted superposition result can be obtained. This adjusted superposition result is then used as the control variable u, thereby achieving the goal of determining the disturbance rejection processing result and improving the accuracy of the disturbance rejection processing result.

[0106] The following section further explains the steps in this embodiment for determining the anti-interference processing result based on the superposition result, the observation result, and the vehicle's gain parameter in the active anti-interference controller.

[0107] As an optional embodiment, in the active disturbance rejection controller, the disturbance rejection processing result is determined based on the superposition result, the observation result, and the vehicle's gain parameter. This includes: in the active disturbance rejection controller, removing the disturbance degree corresponding to the observation result from the superposition result to obtain the removal result; and in the active disturbance rejection controller, determining the quotient between the removal result and the gain parameter as the acceleration corresponding to the disturbance rejection processing result.

[0108] In this embodiment, the virtual control signal and the planned acceleration are superimposed in the active disturbance rejection controller to obtain the superposition result. Then, the disturbance degree corresponding to the observation result is removed from the superposition result to obtain the removal result.

[0109] Optionally, in the ADRC speed controller, the total disturbance is removed from the superposition result of u0 + plan_accel. For example, the superposition result determined as u0+plan_accel and the total disturbance The difference between them is used as the removal result, that is, the removal result is u0 + plan_accel - .

[0110] In this embodiment, in the active disturbance rejection controller, after removing the disturbance level corresponding to the observation result from the superposition result to obtain the removal result, the quotient between the removal result and the gain parameter is determined as the acceleration corresponding to the disturbance rejection processing result in the active disturbance rejection controller.

[0111] Optionally, in the ADRC speed controller, u0+plan_accel- The quotient between the removal result and the estimated gain b0 is determined as the control quantity u, thereby achieving the purpose of determining the anti-disturbance processing result and thus realizing the technical effect of improving the accuracy of the anti-disturbance processing result.

[0112] For example, the process of determining the control quantity u described above can be shown in equation (9) below.

[0113] (9)

[0114] The above fal function can be defined as follows (10).

[0115] (10)

[0116] Here, e can be used to represent the system error. u0 can be used to represent the virtual control signal generated by the virtual controller. k pα and δ can be used to represent the calibrated parameters. u can be used to represent the control quantity (acceleration). That is, in the above equation (9), the planned acceleration is introduced as a feedforward and superimposed with the virtual control signal, and the observed system disturbance is subtracted. Divide by the system's predicted gain The control variable u can then be obtained.

[0117] The following section further explains the steps for determining longitudinal control parameters based on the anti-disturbance processing results in this embodiment.

[0118] As an optional implementation method, determining the longitudinal control parameters based on the disturbance rejection processing results includes: determining the interface type of the longitudinal controller; and determining the longitudinal control parameters based on the interface type and the disturbance rejection processing results.

[0119] In this embodiment, the interface type can be a torque interface type or an acceleration interface type.

[0120] In this embodiment, after inputting compensation information, actual driving parameters, and planned driving parameters into the vehicle's active disturbance rejection controller for disturbance rejection processing and obtaining the disturbance rejection processing result, the interface type of the longitudinal controller is determined.

[0121] Optionally, this embodiment performs type identification on the interface of the longitudinal controller to obtain the interface type of the longitudinal controller. For example, by performing type detection on the interface of the longitudinal actuator, it can be determined whether the interface type of the longitudinal actuator is a torque interface type or an acceleration interface type.

[0122] In this embodiment, after determining the interface type of the longitudinal controller, the longitudinal control parameters are determined based on the interface type and the disturbance rejection processing results.

[0123] Optionally, in this embodiment, based on determining the interface type of the longitudinal controller, if the interface type is a torque interface type, then the preset torque matching the acceleration corresponding to the disturbance rejection processing result is determined as the torque in the longitudinal control parameters. If the interface type is an acceleration interface type, then the acceleration corresponding to the disturbance rejection processing result is determined as the acceleration in the longitudinal control parameters. This achieves the goal of determining the longitudinal control parameters by combining the interface type and the disturbance rejection processing result, thereby improving the accuracy of the longitudinal control parameters.

[0124] The following section further explains the steps of determining the longitudinal control parameters based on the interface type and the anti-interference processing results in this embodiment.

[0125] As an optional implementation method, the longitudinal control parameters are determined based on the interface type and the disturbance rejection processing result, including: in response to the interface type being a torque interface type, determining a preset torque that matches the acceleration corresponding to the disturbance rejection processing result from the calibration library as the longitudinal control parameter; and in response to the interface type being an acceleration interface type, determining the acceleration corresponding to the disturbance rejection processing result as the longitudinal control parameter.

[0126] In this embodiment, the torque interface type described above may also be referred to as the torque control interface type in the following text.

[0127] In this embodiment, the calibration library may include different preset torques matched for different accelerations. The calibration library can be used to store acceleration-torque calibration tables, and these tables can be used to record different preset torques matched for different accelerations.

[0128] In this embodiment, after determining the interface type of the longitudinal controller, in response to the interface type being a torque interface type, a preset torque that matches the acceleration corresponding to the disturbance rejection processing result is determined as the longitudinal control parameter from the calibration library.

[0129] Optionally, in this embodiment, when the determined interface type is a torque interface type, the acceleration-torque calibration table is looked up to obtain a preset torque that matches the control quantity u. The preset torque that matches the control quantity u obtained from the table lookup is determined as the torque in the longitudinal control parameters. This achieves the goal of determining the torque in the longitudinal control parameters by combining the interface type and the disturbance rejection processing results, thereby achieving the technical effect of improving the accuracy of the torque.

[0130] In this embodiment, after determining the interface type of the longitudinal controller, in response to the interface type being an acceleration interface type, the acceleration corresponding to the disturbance rejection processing result is determined as the longitudinal control parameter.

[0131] Optionally, in this embodiment, when the determined interface type is an acceleration interface type, the control quantity u output from the ADRC speed controller is determined as the acceleration in the longitudinal control parameters. This achieves the goal of determining the acceleration in the longitudinal control parameters by combining the interface type and the anti-disturbance processing results, thereby realizing the technical effect of improving the accuracy of acceleration.

[0132] The following section further explains the steps of determining compensation information for compensating the actual driving parameters of the vehicle based on the planned location and the projected location in this embodiment.

[0133] As an optional embodiment, step S204 involves determining compensation information for compensating the actual driving parameters of the vehicle based on the planned position and the projected position, including: determining the longitudinal position deviation between the planned position and the projected position; and compensating for the longitudinal position deviation to obtain compensation information.

[0134] In this embodiment, after obtaining the planned position of the vehicle on the planned trajectory and the projected position of the vehicle's actual position on the planned trajectory, the longitudinal position deviation between the planned position and the projected position is determined.

[0135] Optionally, this embodiment, based on obtaining the planned position and the projected position, compares the deviations between the planned position and the projected position to obtain the longitudinal positional deviation between them. For example, the trajectory length between the planned position and the projected position can be determined as the longitudinal positional deviation.

[0136] In this embodiment, after determining the longitudinal positional deviation between the planned position and the projected position, the longitudinal positional deviation is compensated to obtain compensation information.

[0137] Optionally, if the planned time corresponding to the above-mentioned projected position on the planned trajectory is earlier than or equal to the actual time of arriving at the above-mentioned actual position, then the trajectory length between the above-mentioned planned position and the projected position is increased, and the increased trajectory length is determined as the speed compensation amount used to compensate for the actual speed. This achieves the purpose of combining the planned position and the projected position to determine the compensation information used to compensate for the above-mentioned actual driving parameters, thereby achieving the technical effect of improving the accuracy of the compensation information.

[0138] Optionally, in this embodiment, based on the determination of the longitudinal position deviation, if the planned time corresponding to the above-mentioned projected position on the planned trajectory is later than the actual time of arrival at the above-mentioned actual position, then the trajectory length between the above-mentioned planned position and the projected point position is reduced, and the reduced trajectory length is determined as the speed compensation amount used to compensate for the actual speed.

[0139] In this embodiment, the planned position of the vehicle on the planned trajectory and the projected position of the vehicle's actual position onto the planned trajectory are obtained. Based on the planned position and the projected position, compensation information for compensating the vehicle's actual driving parameters is determined. Based on the compensation information, the actual driving parameters, and the planned driving parameters, the longitudinal control parameters of the vehicle are determined. The vehicle's driving is then controlled by the vehicle's longitudinal controller based on the longitudinal control parameters. Because this embodiment, when controlling the vehicle, determines the compensation information for compensating the vehicle's actual driving parameters based on the obtained planned position and projected position, and then determines the longitudinal control parameters for controlling the vehicle's driving based on the compensation information, actual driving parameters, and planned driving parameters, and then controls the vehicle's driving based on the longitudinal control parameters, it achieves the goal of avoiding frequent vehicle vibration, thus solving the technical problem of low vehicle control effectiveness and improving the technical effect of vehicle control effectiveness.

[0140] The technical solutions of the embodiments of this application will be illustrated below with reference to preferred embodiments.

[0141] Currently, there are two types of longitudinal control methods for vehicles: one is the longitudinal control method based on the PID algorithm, and the other is the longitudinal control method based on the model predictive control algorithm.

[0142] However, there are drawbacks in implementing these two methods. For example, when implementing a longitudinal control method based on PID algorithms to control vehicle movement, it can only guarantee control performance under normal driving conditions. It cannot guarantee good speed control under driving conditions such as going uphill or downhill, or crossing speed bumps at low speeds. Moreover, during acceleration and deceleration tracking, the vehicle is prone to frequent speed oscillations and vibrations. When implementing a longitudinal control method based on model predictive control algorithms to control vehicle movement, it requires excessive computing power, which is unsuitable for hardware platforms with low to medium computing power.

[0143] Therefore, regardless of which method is used, there will be limitations in controlling the vehicle under different operating conditions, resulting in a low effectiveness of vehicle control.

[0144] However, this application proposes a vehicle control method. When controlling the vehicle, based on the obtained planned position and projected position, compensation information for compensating the actual driving parameters of the vehicle is determined by combining the two positions. Then, by combining the compensation information, the actual driving parameters, and the planned driving parameters, control parameters for longitudinal vehicle driving are determined. Subsequently, the vehicle's longitudinal controller controls the vehicle's driving based on the longitudinal vehicle driving control parameters. This achieves the goal of avoiding frequent vehicle shaking, thereby solving the technical problem of low vehicle control effectiveness and achieving the technical effect of improving the effectiveness of vehicle control.

[0145] In this embodiment, by executing the intelligent driving longitudinal control method for the vehicle, the vehicle can be controlled to drive based on longitudinal control information by the longitudinal controller. For example, Figure 3(a) is a flowchart of an intelligent driving longitudinal control method for a vehicle according to an embodiment of this application. As shown in Figure 3(a), the method may include the following steps.

[0146] Step S301: Obtain the planned position on the planned trajectory at the current time, and calculate the projection point of the vehicle's actual position on the planned trajectory. Using the position controller, adjust the longitudinal position deviation between the planned position and the actual position to obtain and output the speed compensation.

[0147] In the technical solution provided by step S301 of this application, the trajectory length between the planned position and the projection point position is the current longitudinal position deviation.

[0148] After obtaining and outputting the speed compensation, step S302 is executed, where the speed compensation, planned speed, planned acceleration, and actual speed are input into the active disturbance rejection controller, and the acceleration / deceleration can be obtained and output.

[0149] In the technical solution provided in step S302 of this application, the ADRC speed controller can estimate the total unknown disturbance to the intelligent driving system through the Extended State Observer (ESO), and add the estimated values ​​of these disturbances as compensation terms to the error state feedback control signal, thereby achieving the purpose of eliminating or reducing the impact of disturbances on the performance of the system.

[0150] For example, Figure 3(b) is a schematic diagram of an ADRC speed controller according to an embodiment of this application. The design of the ADRC speed controller can be as shown in Figure 3(b). In the ADRC speed controller, the input signal is the planned vehicle speed plan_v plus the speed compensation speed_offset output by the PID position controller. Since the input signal sometimes changes unevenly, in order to obtain a smooth and stable input signal, a tracking differentiator (TD) is used to track the input signal quickly and without overshoot, and simultaneously provides the derivative of the signal. The tracking differentiator can be implemented using the Fhan function, and the output value is the tracked value of the planned vehicle speed. .

[0151] In the ADRC speed controller described above, the ESO can be a linear extended state observer (LESO). The LESO can be constructed using equations (1) to (6) as follows.

[0152] (1)

[0153] in, It can be used to represent an estimated value of the expanded state of an autonomous driving system. The above equation (1) can be used to represent the total disturbance of the autonomous driving system, u can be used to represent the input data of the autonomous driving system, and b can be used to represent the gain of the input data. The above equation (1) can be further written as the following equation (2).

[0154] (2)

[0155] Here, b0 can be used to represent the estimated value of the gain of the input data.

[0156] Let y, Given f as shown in equation (3), we can obtain the state transition equation shown in equation (4):

[0157] (3)

[0158] (4)

[0159] in, . That is, The state transition equation shown in equation (4) above can be expressed as equation (5) below.

[0160] (5)

[0161] in, It can be used to represent an estimate of the state. It can be used to represent an estimated value of the output. It can be used to represent the observer gain matrix. Substituting equation (5.2) into equation (5.1), we can obtain equation (6), and expand equation (6) into equation (7).

[0162] (6)

[0163] (7)

[0164] According to observer-related theory, the observer gain matrix The system matrix of the state observer can be expressed as follows (8). We use the characteristic roots to find them.

[0165] (8)

[0166] The poles are uniformly set at -w0, that is, Therefore, the gain of LESO is .

[0167] By constructing a well-defined extended state observer, the vehicle speed can be estimated. Total disturbance In other words, by following the above procedure to debug and calibrate appropriate w0 and b0, the system gain can be obtained, and then the vehicle speed can be calculated. Total disturbance .

[0168] According to the following formula (9), a control signal can be generated based on error feedback.

[0169] (9)

[0170] The above fal function can be defined as follows (10).

[0171] (10)

[0172] Here, e can be used to represent the system error. u0 can be used to represent the virtual control signal generated by the virtual controller. k p α and δ can be used to represent the calibrated parameters. u can be used to represent the control quantity (acceleration). That is, in the above equation (9), the planned acceleration is introduced as a feedforward and superimposed with the virtual control signal, and the observed system disturbance is subtracted. Divide by the system's predicted gain The control variable u can then be obtained.

[0173] After obtaining and outputting the acceleration / deceleration, step S303 is executed to determine whether the vehicle's longitudinal actuator is a torque control interface or an acceleration interface.

[0174] If it is determined that the longitudinal actuator is a torque control interface, then step S304 is executed to pre-calibrate the vehicle's acceleration-torque calibration table, convert the acceleration output by the speed controller into torque by looking up the table, and output the torque to the longitudinal actuator.

[0175] If it is determined that the longitudinal actuator is an acceleration interface, then step S305 is executed to directly output the acceleration.

[0176] In this embodiment, the intelligent driving longitudinal control method of the vehicle can be executed through the vehicle's intelligent driving longitudinal control architecture. For example, Figure 4 This is a schematic diagram of a longitudinal control architecture for intelligent driving of a vehicle according to an embodiment of this application, such as... Figure 4 As shown, the architecture may include a position controller 401, a speed controller 402, and a vehicle 403. The position controller 401 is a PID position controller, which receives the longitudinal position deviation between the planned position and the actual position, adjusts the longitudinal position deviation, and outputs speed compensation. The speed controller 402 is an ADRC speed controller, which receives speed compensation, planned speed, planned acceleration, and the actual speed from the vehicle 403, and calculates the acceleration / deceleration. The vehicle 403 can obtain the acceleration torque / deceleration torque by looking up an acceleration-torque calibration table.

[0177] In this embodiment, when controlling the vehicle, based on the obtained planned position and projected position, compensation information for compensating the actual driving parameters of the vehicle is determined by combining the two positions. Then, by combining the compensation information, the actual driving parameters and the planned driving parameters, the control parameters for longitudinal vehicle driving are determined. Subsequently, the vehicle's longitudinal controller controls the vehicle's driving based on the control parameters for longitudinal vehicle driving, thereby achieving the goal of avoiding frequent vehicle shaking, thus solving the technical problem of low vehicle control effectiveness, and achieving the technical effect of improving the effectiveness of vehicle control.

[0178] According to another aspect of the embodiments of this application, corresponding to the embodiments of the above-described vehicle control method, the embodiments of this application also provide a vehicle control device. Figure 5 This is a structural block diagram of a vehicle control device according to an embodiment of this application, such as... Figure 5 As shown, the vehicle control device 500 may include: an acquisition unit 502, a first determination unit 504, a second determination unit 506, and a control unit 508.

[0179] The acquisition unit 502 is used to acquire the planned position of the vehicle in the planned trajectory, and the projected position of the vehicle's actual position onto the planned trajectory.

[0180] The first determining unit 504 is used to determine compensation information for compensating the actual driving parameters of the vehicle based on the planned position and the projected position.

[0181] The second determining unit 506 is used to determine the longitudinal control parameters of the vehicle based on compensation information, actual driving parameters and planned driving parameters of the vehicle, wherein the planned driving parameters are used to represent the planned driving parameters of the vehicle, and the longitudinal control parameters are used to represent the control parameters for longitudinally controlling the driving of the vehicle.

[0182] Control unit 508 is used to control the vehicle's movement based on longitudinal control parameters via the vehicle's longitudinal controller.

[0183] Optionally, the second determining unit 506 may include: a processing module, used to input compensation information, actual driving parameters and planned driving parameters to the vehicle's active disturbance rejection controller for disturbance rejection processing to obtain disturbance rejection processing results, wherein the disturbance rejection processing results are used to represent the acceleration that the vehicle should achieve when the disturbance factors affecting the vehicle's driving are eliminated; and a first determining module, used to determine longitudinal control parameters based on the disturbance rejection processing results.

[0184] Optionally, the planned driving parameters include: a planned speed and a planned acceleration for the vehicle. The active disturbance rejection controller includes: a differentiator and an observer. The processing module may include: a superposition submodule, used to superimpose the speed compensation amount corresponding to the compensation information and the planned speed to obtain the input signal of the active disturbance rejection controller; a processing submodule, used to input the input signal to the differentiator for differentiating processing to obtain the differentiating processing result, and input the actual speed, including the actual driving parameters, to the observer for observing processing to obtain the observing result. The differentiating processing result is used to represent the differential value of the input signal, and the observing result is used to represent the observed speed to be reached by the vehicle, and the degree of disturbance caused by the disturbance factor to cause the vehicle to deviate from the observed speed; and a first determination submodule, used to determine the disturbance rejection processing result in the active disturbance rejection controller based on the differentiating processing result, the observing result, and the planned acceleration.

[0185] Optionally, the first determining submodule can determine the disturbance rejection result in the active disturbance rejection controller by performing the following steps: the difference between the differential value corresponding to the differential processing result and the observed velocity corresponding to the observed result is input into the virtual generator to generate a signal to obtain a virtual control signal; the virtual control signal and the planned acceleration are superimposed in the active disturbance rejection controller to obtain a superposition result; and the disturbance rejection result is determined in the active disturbance rejection controller based on the superposition result, the observed result, and the vehicle's gain parameters.

[0186] Optionally, the first determining submodule can determine the anti-disturbance processing result in the active disturbance rejection controller based on the superposition result, the observation result, and the vehicle's gain parameter by performing the following steps: in the active disturbance rejection controller, the disturbance degree corresponding to the observation result is removed from the superposition result to obtain the removal result; in the active disturbance rejection controller, the quotient between the removal result and the gain parameter is determined as the acceleration corresponding to the anti-disturbance processing result.

[0187] Optionally, the first determining module may include: a second determining submodule for determining the interface type of the longitudinal controller; and a third determining submodule for determining the longitudinal control parameters based on the interface type and the disturbance rejection processing results.

[0188] Optionally, the third determining submodule can determine the longitudinal control parameters based on the interface type and the disturbance rejection processing result by performing the following steps: in response to the interface type being a torque interface type, a preset torque matching the acceleration corresponding to the disturbance rejection processing result is determined from the calibration library as the longitudinal control parameter, wherein the calibration library includes different preset torques matching different accelerations; in response to the interface type being an acceleration interface type, the acceleration corresponding to the disturbance rejection processing result is determined as the longitudinal control parameter.

[0189] Optionally, the first determining unit 504 may include: a second determining module for determining the longitudinal position deviation between the planned position and the projected position; and a compensation module for compensating the longitudinal position deviation to obtain compensation information.

[0190] In this embodiment, the vehicle control device includes the following units: an acquisition unit, used to acquire the planned position of the vehicle on the planned trajectory, and the projected position of the vehicle's actual position onto the planned trajectory; a first determination unit, used to determine compensation information for compensating the actual driving parameters of the vehicle based on the planned position and the projected position; a second determination unit, used to determine the longitudinal control parameters of the vehicle based on the compensation information, the actual driving parameters, and the planned driving parameters of the vehicle, wherein the planned driving parameters are used to represent the planned driving parameters of the vehicle, and the longitudinal control parameters are used to represent the control parameters for longitudinally controlling the vehicle's driving; and a control unit, used to control the vehicle's driving based on the longitudinal control parameters through the vehicle's longitudinal controller, thereby achieving the goal of avoiding frequent vehicle vibration, thus solving the technical problem of low vehicle control effectiveness, and further achieving the technical effect of improving the effectiveness of vehicle control.

[0191] Embodiments of this application also provide an electronic device, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0192] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0193] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0194] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0195] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of this application.

[0196] Embodiments of this application also provide a vehicle that includes the electronic devices described in this application.

[0197] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0198] According to an embodiment of this application, an electronic device is also provided. Figure 6 This is a schematic diagram of an electronic device according to an embodiment of this application, such as... Figure 6 As shown, the electronic device 600 may include a memory 610 and a processor 620, wherein the memory 610 is used to store an executable program; and the processor 620 is used to run the program stored in the memory 610, and the program executes the method of this application when it runs.

[0199] In this application, "multiple" refers to two or more.

[0200] In this application, unless otherwise expressly defined, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0201] The terms “first,” “second,” “third,” “fourth,” etc., in this application (if present) are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0202] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0203] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the device control method for the vehicle in the embodiment.

[0204] Computer-readable storage media, also known as computer storage media, may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. These propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable storage media can transmit, propagate, or transfer programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0205] The program code contained in a computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, radio frequency, or any suitable combination thereof.

[0206] In the embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0207] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0208] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0209] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0210] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for controlling a vehicle, characterized in that, include: Obtain the planned position of the vehicle on the planned trajectory, and the projected position of the vehicle's actual position onto the planned trajectory; Based on the planned location and the projected location, compensation information is determined to compensate for the actual driving parameters of the vehicle; Based on the compensation information, the actual driving parameters, and the planned driving parameters of the vehicle, the longitudinal control parameters of the vehicle are determined, wherein the planned driving parameters are used to represent the planned driving parameters of the vehicle, and the longitudinal control parameters are used to represent the control parameters for longitudinally controlling the driving of the vehicle. The vehicle's movement is controlled by the vehicle's longitudinal controller based on the longitudinal control parameters.

2. The method according to claim 1, characterized in that, Based on the compensation information, the actual driving parameters, and the planned driving parameters of the vehicle, the longitudinal control parameters of the vehicle are determined, including: The compensation information, the actual driving parameters, and the planned driving parameters are input to the vehicle's active disturbance rejection controller for disturbance rejection processing to obtain the disturbance rejection processing result. The disturbance rejection processing result is used to represent the acceleration that the vehicle should achieve after eliminating the disturbance factors that affect the vehicle's driving. Based on the disturbance rejection processing results, the longitudinal control parameters are determined.

3. The method according to claim 2, characterized in that, The planned driving parameters include: a planned speed and a planned acceleration for the vehicle. The active disturbance rejection controller includes: a differentiator and an observer. The compensation information, the actual driving parameters, and the planned driving information are input to the vehicle's active disturbance rejection controller for disturbance rejection processing to obtain the disturbance rejection processing result, including: The speed compensation amount corresponding to the compensation information and the planned speed are superimposed to obtain the input signal of the active disturbance rejection controller; The input signal is input to the differentiator for differentiation processing to obtain a differentiation processing result, and the actual speed, including the actual driving parameters, is input to the observer for observation processing to obtain an observation result. The differentiation processing result is used to represent the differential value of the input signal, and the observation result is used to represent the observation speed that the vehicle is to reach, and the degree of disturbance caused by the disturbance factor that causes the vehicle to deviate from the observation speed. In the active disturbance rejection controller, the disturbance rejection result is determined based on the differential processing result, the observation result, and the planned acceleration.

4. The method according to claim 3, characterized in that, The active disturbance rejection controller includes a virtual generator, wherein, in the active disturbance rejection controller, the disturbance rejection result is determined based on the differential processing result, the observation result, and the planned acceleration, including: The difference between the differential value corresponding to the differential processing result and the observation velocity corresponding to the observation result is input into the virtual generator to generate a signal, thereby obtaining a virtual control signal. In the active disturbance rejection controller, the virtual control signal and the planned acceleration are superimposed to obtain the superposition result; In the active anti-interference controller, the anti-interference processing result is determined based on the superposition result, the observation result, and the gain parameter of the vehicle.

5. The method according to claim 4, characterized in that, In the active disturbance rejection controller, the disturbance rejection processing result is determined based on the superposition result, the observation result, and the vehicle's gain parameter, including: In the active disturbance rejection controller, the disturbance level corresponding to the observation result is removed from the superposition result to obtain the removal result; In the active anti-interference controller, the quotient between the removal result and the gain parameter is determined as the acceleration corresponding to the anti-interference processing result.

6. The method according to claim 2, characterized in that, Based on the disturbance rejection processing results, the longitudinal control parameters are determined, including: Determine the interface type of the longitudinal controller; Based on the interface type and the disturbance rejection processing result, the longitudinal control parameters are determined.

7. The method according to claim 6, characterized in that, Based on the interface type and the disturbance rejection processing result, the longitudinal control parameters are determined, including: In response to the interface type being a torque interface type, a preset torque matching the acceleration corresponding to the disturbance rejection processing result is determined from the calibration library as the longitudinal control parameter. The calibration library includes different preset torques matching different accelerations. In response to the interface type being an acceleration interface type, the acceleration corresponding to the disturbance rejection processing result is determined as the longitudinal control parameter.

8. The method according to claim 1, characterized in that, Based on the planned location and the projected location, compensation information is determined to compensate for the actual driving parameters of the vehicle, including: Determine the longitudinal positional deviation between the planned position and the projected position; The longitudinal position deviation is compensated to obtain the compensation information.

9. A vehicle control device, characterized in that, include: The acquisition unit is used to acquire the planned position of the vehicle in the planned trajectory, and the projected position of the vehicle's actual position onto the planned trajectory; The first determining unit is used to determine compensation information for compensating the actual driving parameters of the vehicle based on the planned location and the projected location. The second determining unit is used to determine the longitudinal control parameters of the vehicle based on the compensation information, the actual driving parameters, and the planned driving parameters of the vehicle, wherein the planned driving parameters are used to represent the planned driving parameters of the vehicle, and the longitudinal control parameters are used to represent the control parameters for longitudinally controlling the driving of the vehicle. A control unit is used to control the movement of the vehicle based on the longitudinal control parameters via the vehicle's longitudinal controller.

10. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 8.

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