Method, device and storage medium for controlling a vehicle platoon

Abstract

The application discloses a kind of control method, device and storage medium of vehicle queue.Therein, the method comprises: in response to receiving control instruction for controlling vehicle queue, control controller in vehicle queue obtains target driving state parameter of first vehicle and initial driving state parameter of second vehicle, wherein control instruction is used to control multiple vehicles in vehicle queue according to preset interval strategy driving;Control controller controls second vehicle according to target driving state parameter of first vehicle, initial driving state parameter of second vehicle and preset interval strategy, and obtains target position of second vehicle;Expansion state observer of second vehicle is controlled according to target position, and estimates target driving state parameter of second vehicle, wherein target driving state parameter is applied to the scene in which multiple vehicles in vehicle queue are controlled.

Description

Technical Field

[0001] This invention relates to the field of vehicle control, and more specifically, to a method, apparatus, and storage medium for controlling a vehicle platoon. Background Technology

[0002] Most research on vehicle platooning control technology is based on multi-agent models. Existing research generally assumes that the vehicle's speed and acceleration state are known when designing connected vehicle platooning control algorithms. In reality, the vehicle's speed state can usually be accurately measured by onboard speed sensors. However, acceleration sensors inevitably produce measurement errors or output drift due to changes in temperature, mechanical stress / pressure, and humidity. Furthermore, accurate calibration during long-term deployment is quite difficult. Some vehicles are even not equipped with onboard acceleration sensors due to cost constraints. In addition, when directly performing numerical differentiation on the speed measurement value to obtain acceleration information, the measurement noise is further amplified by the differentiation operation, resulting in a large error between the calculated acceleration value and the true value. This leads to the technical problem of low efficiency in vehicle platooning control in related technologies.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This invention provides a vehicle platoon control method, apparatus, and storage medium to at least solve the technical problem of low driving control efficiency of vehicle platoons in related technologies.

[0005] According to one aspect of the present invention, a vehicle queue control method is provided, comprising: in response to receiving a control command for controlling the vehicle queue, controlling a controller in the vehicle queue to acquire target driving state parameters of a first vehicle and initial driving state parameters of a second vehicle, wherein the control command is used to control multiple vehicles in the vehicle queue to drive according to a preset interval strategy; the controller controls the second vehicle according to the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy to obtain a target position of the second vehicle; and an extended state observer controlling the second vehicle estimates the target driving state parameters of the second vehicle according to the target position, wherein the target driving state parameters are applied in a scenario where multiple vehicles in the vehicle queue are controlled.

[0006] Furthermore, the controller controls the second vehicle based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy to obtain the target position of the second vehicle. This includes: the controller obtaining control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy; and the controller obtaining the target position of the second vehicle after controlling the second vehicle based on the control parameters.

[0007] Furthermore, the control controller obtains control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and a preset interval strategy. This includes: in response to the first vehicle being the lead vehicle in the vehicle convoy, the control controller obtains control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy; in response to the first vehicle not being the lead vehicle in the vehicle convoy, the control controller obtains control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, the target driving state parameters of the third vehicle, and the preset interval strategy, wherein the first vehicle is a vehicle between the second and third vehicles.

[0008] Furthermore, in response to the first vehicle being the leading vehicle, the target driving state parameters of the first vehicle are determined to be preset driving state parameters. The preset driving state parameters are driving state parameters output based on the first vehicle driving according to a preset curve. The preset curve is used to represent the correspondence between the vehicle's driving speed and driving time.

[0009] Furthermore, the extended state observer is constructed based on the system disturbance state parameters and a third-order nonlinear dynamic model, which is constructed based on the vehicle's position state parameters, velocity state parameters, and acceleration state parameters.

[0010] Furthermore, the extended state observer controlling the second vehicle estimates the target driving state parameters of the second vehicle based on the target position, including: decomposing the extended state observer into multiple sub-models using a backstepping design method; controlling the multiple sub-models to a stable state based on the target control quantity and / or objective function and the target position, wherein the target control quantity is the control quantity used to control the multiple sub-models to a stable state, and the objective function is the equation used to control the multiple sub-models to a stable state; and aggregating the multiple sub-models in a stable state to obtain the target driving state parameters.

[0011] According to another aspect of the present invention, a vehicle queue control device is also provided, comprising: a first control module, configured to, in response to receiving a control command for controlling the vehicle queue, control a controller in the vehicle queue to acquire target driving state parameters of a first vehicle and initial driving state parameters of a second vehicle, wherein the control command is used to control multiple vehicles in the vehicle queue to drive according to a preset interval strategy; a second control module, configured to control the controller to control the second vehicle according to the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy to obtain a target position of the second vehicle; and an estimation module, configured to control an extended state observer of the second vehicle to estimate the target driving state parameters of the second vehicle according to the target position, wherein the target driving state parameters are applied in a scenario where multiple vehicles in the vehicle queue are controlled.

[0012] According to a third aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, the above-described vehicle queue control method is executed in a processor of the device.

[0013] According to a fourth aspect of the present invention, a vehicle is also provided, comprising: one or more processors; a storage device for storing one or more programs; wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above-described vehicle queue control method.

[0014] In this embodiment of the invention, in response to receiving a control command to control a vehicle queue, the controller in the vehicle queue obtains the target driving state parameters of the first vehicle and the initial driving state parameters of the second vehicle. The control command is used to control multiple vehicles in the queue to drive according to a preset interval strategy. The controller controls the second vehicle based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy to obtain the target position of the second vehicle. An extended state observer controlling the second vehicle estimates the target driving state parameters of the second vehicle based on the target position. These target driving state parameters are applied in scenarios where multiple vehicles in a queue are controlled. It is noteworthy that, based on the vehicle's position information, the target driving state parameters of the vehicle to be controlled can be obtained through the extended state observer. This achieves the goal of obtaining the corresponding target driving state parameters only through the vehicle's position information, without needing to explicitly know the speed, acceleration, or other information of the vehicles in the queue. This improves the driving control efficiency of the vehicle queue and solves the technical problem of low driving control efficiency in related technologies. Attached Figure Description

[0015] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0016] Figure 1 This is a flowchart of a vehicle queue control method according to an embodiment of the present invention;

[0017] Figure 2 This is a schematic diagram of an optional vehicle queue spacing strategy according to an embodiment of the present invention;

[0018] Figure 3 This is a schematic diagram illustrating the control principle of an optional vehicle queue according to an embodiment of the present invention;

[0019] Figure 4 This is a flowchart of an optional distributed vehicle queue control method based on an extended state observer according to an embodiment of the present invention;

[0020] Figure 5 This is a schematic diagram of an optional extended state observer according to an embodiment of the present invention;

[0021] Figure 6 This is a schematic diagram of a vehicle queue control device according to an embodiment of the present invention. Detailed Implementation

[0022] Current research on vehicle platooning control technology is mostly based on multi-agent models. Existing research generally assumes that the vehicle's speed and acceleration state are known when designing connected vehicle platooning control algorithms. In reality, the vehicle's speed state can usually be accurately measured by onboard speed sensors, but acceleration sensors inevitably produce measurement errors or output drift due to changes in temperature, mechanical stress / pressure, and humidity. Furthermore, accurate calibration during long-term deployment is quite difficult. Some vehicles are even not equipped with onboard acceleration sensors due to cost constraints. In addition, when directly performing numerical differentiation on the speed measurement value to obtain acceleration information, the measurement noise is further amplified by the differentiation operation, resulting in a large error between the calculated acceleration value and the true value. All these factors make acceleration measurement values ​​unusable as feedback values. On the other hand, most current research literature simplifies the longitudinal dynamics model of a vehicle into a linear model by using precise feedback linearization technology for the convenience of control design. However, this requires precise prior knowledge of the vehicle's dynamic analytical model and model parameters, such as air resistance coefficient, rolling resistance coefficient, and vehicle mass. Once the vehicle is affected by unknown external disturbances such as gusts of wind or uneven road surfaces during driving, causing perturbation of model parameters, the control effect of the connected vehicle queuing controller based on feedback linearization technology will be greatly reduced or even fail.

[0023] Therefore, in order to ensure that the longitudinal queuing of vehicles has high precision and robust control performance under conditions where speed and acceleration measurements are unavailable, model parameters are uncertain, and there are unknown external disturbances, it is urgent to study a distributed control method for connected vehicle queuing that does not require speed and acceleration measurement information.

[0024] This application establishes a third-order nonlinear dynamic model of the vehicle. Based on the principle of the extended state observer and the established third-order nonlinear dynamic model, an extended state observer is designed that can accurately observe the vehicle's speed, acceleration state information and external disturbances with only the vehicle's position information. Finally, based on the output value of the designed state observer, a control method that considers the external disturbances of the vehicle is designed using the backstepping design method. Under the premise that the vehicle is subjected to external disturbances and the vehicle's speed and acceleration state information is unknown, a good control effect for connected vehicle platooning is achieved.

[0025] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention 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 the invention 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 a 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.

[0027] Example 1

[0028] According to an embodiment of the present invention, an embodiment of a vehicle queue 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.

[0029] Figure 1 This is a flowchart of a vehicle queue control method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0030] Step S102: In response to receiving a control command to control the vehicle queue, the controller in the vehicle queue is controlled to obtain the target driving state parameters of the first vehicle and the initial driving state parameters of the second vehicle. The control command is used to control multiple vehicles in the vehicle queue to drive according to a preset interval strategy.

[0031] Specifically, the aforementioned control commands can be used to indicate instructions for controlling the spacing between multiple vehicles in a vehicle platoon during their journey.

[0032] The aforementioned preset interval strategy can be used to represent the driving interval strategy between vehicles in a pre-set vehicle queue. Here, no specific settings are made for the preset interval strategy.

[0033] For example, Figure 2 This is a schematic diagram of an optional vehicle queue spacing strategy according to an embodiment of the present invention. Figure 2 As shown, the actual distance between the i-th and (i-1)-th vehicles can be obtained by subtracting the position of the rear of the i-th vehicle from the position of the rear of the (i-1)-th vehicle, i.e.: y i =p i-1 -p i -l i-1 , where p i-1 With p i It is the position of the (i-1)th and the i-th vehicles, l i It is the body length of the i-th vehicle.

[0034] The aforementioned target driving state parameters can be used to represent the parameters corresponding to the current driving state of the first vehicle in the vehicle queue, including but not limited to the first vehicle's current speed, current acceleration, current position, etc.

[0035] The aforementioned initial driving state parameters can be used to represent the parameters corresponding to the initial driving state of the second vehicle in the vehicle queue, including but not limited to the second vehicle's driving speed, driving acceleration, initial position, etc., wherein the second vehicle in the vehicle queue is positioned behind the first vehicle.

[0036] In one optional embodiment, during the process of controlling the vehicle queue, it is necessary to obtain the target driving state parameters of the first vehicle and the initial driving state parameters of the second vehicle in the vehicle queue, so as to control the second vehicle during the driving process through a preset interval strategy.

[0037] Step S104: The controller controls the second vehicle according to the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy to obtain the target position of the second vehicle.

[0038] Specifically, the aforementioned target location can be used to represent the current location information of the second vehicle. Generally, the controller needs to calculate the target driving state parameters of the first vehicle in the vehicle queue and the initial driving state parameters of the second vehicle using a preset interval strategy to obtain the aforementioned target location.

[0039] In one alternative embodiment, Figure 3 This is a schematic diagram illustrating an optional vehicle queuing control principle according to an embodiment of the present invention. Figure 3 As shown, the target driving state parameters of the leading vehicle (i.e., the first vehicle mentioned above) are obtained through controller1 (the first controller), namely the current speed, current acceleration, current position and other parameters. At the same time, the initial driving state parameters of the first vehicle (i.e., the second vehicle mentioned above) are obtained, namely the driving speed, driving acceleration, initial position and other parameters. Then, the first controller calculates the above parameters using a preset interval strategy to obtain the p (i.e., the target position mentioned above) output by the first vehicle.

[0040] Step S106: The extended state observer of the second vehicle estimates the target driving state parameters of the second vehicle based on the target position. The target driving state parameters are applied in a scenario where multiple vehicles in a vehicle queue are controlled.

[0041] Specifically, the aforementioned extended state observer can be used to represent a state observer that integrates the uncertainties in the system model with the external disturbances experienced by the system, treating them as a new state of the established extended state observer, and then estimates the original system state parameters and the total disturbances experienced in real time through the system's input and output.

[0042] The aforementioned target driving state parameters can be used to represent the parameters corresponding to the current driving state of the second vehicle, including but not limited to the current speed, acceleration, and position information of the second vehicle. It should be noted that the target driving state parameters, along with the aforementioned initial driving state parameters, represent the parameters corresponding to different driving states of the second vehicle at different times, and these state parameters can be represented using speed information, acceleration information, position information, etc.

[0043] In one optional embodiment, after obtaining the target position of the second vehicle, the target position needs to be uploaded to the extended state observer of the second vehicle for processing, so as to obtain the target driving state parameters of the second vehicle output by the extended state observer, that is, the current speed information, acceleration information, position information, etc. of the second vehicle, so as to facilitate the control of the second vehicle based on the target driving state parameters.

[0044] In another alternative embodiment, in response to the vehicle queue including at least three vehicles, similarly, during the control of the third vehicle, the controller of the third vehicle needs to obtain the position, speed, acceleration information, etc. of the first and second vehicles, and during the control of the nth vehicle, the controller of the nth vehicle needs to obtain the position, speed, acceleration information, etc. of the (n-1)th and (n-2)th vehicles, where n is a natural number greater than or equal to 3.

[0045] Figure 4 This is a flowchart of an optional distributed vehicle queue control method based on an extended state observer according to an embodiment of the present invention. Figure 4 As shown, a third-order nonlinear dynamic model of the vehicle is first established, employing a two-phase following communication topology. This eliminates the need to transmit the state information of the lead vehicle to every vehicle, reducing the impact of communication delay on the stability of the vehicle platoon and making it easier to implement in practice. For ease of implementation, a fixed spacing strategy is chosen as the desired interval distance between vehicles. The impact of disturbances during vehicle platoon movement is also considered to maintain platoon stability. Furthermore, using the established third-order nonlinear mathematical model of the vehicle and the principle of the extended state observer, an extended state observer is designed that can accurately observe vehicle speed, acceleration state parameters, and external disturbances using only vehicle position information. The convergence of its observation error is proven. Finally, based on the designed extended state observer, a distributed vehicle platoon control method based on the extended state observer is designed using the backstepping design method and Lyapunov, achieving good control performance.

[0046] In summary, in response to a received control command for controlling a vehicle queue, the controller in the vehicle queue obtains the target driving state parameters of the first vehicle and the initial driving state parameters of the second vehicle. The control command is used to control multiple vehicles in the queue to drive according to a preset interval strategy. The controller controls the second vehicle based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy to obtain the target position of the second vehicle. An extended state observer controlling the second vehicle estimates the target driving state parameters of the second vehicle based on the target position. These target driving state parameters are applied in scenarios where multiple vehicles in a queue are controlled. It is noteworthy that, based on the vehicle's position information, the target driving state parameters of the vehicle to be controlled can be obtained through the extended state observer. This achieves the goal of obtaining the corresponding target driving state parameters only through the vehicle's position information, without needing to explicitly know the speed, acceleration, or other information of the vehicles in the queue. This improves the driving control efficiency of the vehicle queue and solves the technical problem of low driving control efficiency in related technologies.

[0047] Optionally, the control controller controls the second vehicle based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and a preset interval strategy to obtain the target position of the second vehicle. This includes: the control controller obtaining control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy; and the control controller obtaining the target position of the second vehicle after controlling the second vehicle based on the control parameters.

[0048] Specifically, the aforementioned control parameters can be used to represent parameters for controlling the movement of the second vehicle, including but not limited to speed control parameters and acceleration control parameters.

[0049] In one optional embodiment, during the process of obtaining the target position of the second vehicle, it is necessary to calculate the control parameters of the second vehicle based on the target driving state parameters of the first vehicle and the initial driving state parameters of the second vehicle by the controller, and then control the second vehicle based on the control parameters to obtain the target position of the second vehicle after control.

[0050] For example, such as Figure 3 As shown, the first controller calculates the target driving state parameters of the leading vehicle and the initial driving state parameters of the first vehicle using a preset interval strategy, thereby obtaining the control parameters for the first vehicle. The first vehicle is then controlled using these control parameters to obtain the target position p of the first vehicle after control.

[0051] Optionally, the control controller obtains control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and a preset interval strategy, including: in response to the first vehicle being the lead vehicle in the vehicle convoy, the control controller obtains control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy; in response to the first vehicle not being the lead vehicle in the vehicle convoy, the control controller obtains control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, the target driving state parameters of the third vehicle, and the preset interval strategy, wherein the first vehicle is a vehicle between the second and third vehicles.

[0052] Specifically, the aforementioned lead vehicle can be used to refer to the vehicle located at the beginning of the vehicle queue.

[0053] In one optional embodiment, in response to the first vehicle being the lead vehicle in the vehicle queue, i.e., the first vehicle being located at the beginning of the vehicle queue, during the process of obtaining the control parameters for the second vehicle, the controller can calculate the target driving state parameters of the first vehicle and the initial driving state parameters of the second vehicle using a preset interval strategy to obtain the control parameters for the second vehicle.

[0054] In another optional embodiment, in response to the first vehicle not being the lead vehicle in the vehicle queue, i.e., the first vehicle being located at a non-starting position in the vehicle queue, to obtain the control parameters for the second vehicle, after obtaining the target driving state parameters of the first vehicle, it is also necessary to obtain the target driving state parameters of the third vehicle, wherein the third vehicle is located in front of the first vehicle, i.e., the first vehicle is a vehicle between the second and third vehicles. Then, the controller can calculate the control parameters for the second vehicle by performing a preset interval strategy on the target driving state parameters of the first vehicle, the target driving state parameters of the third vehicle, and the initial driving state parameters of the second vehicle.

[0055] Optionally, in response to the first vehicle being the lead vehicle, the target driving state parameters of the first vehicle are determined to be preset driving state parameters, wherein the preset driving state parameters are driving state parameters output based on the first vehicle driving according to a preset curve, and the preset curve is used to represent the correspondence between the vehicle's driving speed and driving time.

[0056] Specifically, the aforementioned preset curve can be used to represent the driving curve of a pre-set leading vehicle, that is, the curve composed of the pre-set driving speed and driving time of the leading vehicle. Here, the driving speed and driving time are not specifically set.

[0057] The aforementioned preset driving state parameters can be used to represent the speed information, acceleration information, etc., output by the lead vehicle at a certain moment.

[0058] In one optional embodiment, in response to the first vehicle being the lead vehicle, the preset driving state parameters of the first vehicle can be acquired in real time during the first vehicle's driving based on the preset curve, and then the target driving state parameters of the first vehicle can be determined based on the preset driving state parameters. It should be noted that the target driving state parameters are not specifically set here, but need to be acquired according to the actual situation.

[0059] Optionally, the extended state observer is constructed based on the system disturbance state parameters and a third-order nonlinear dynamic model, which is constructed based on the vehicle's position state parameters, velocity state parameters, and acceleration state parameters.

[0060] Specifically, Figure 5 This is a schematic diagram of an optional extended state observer according to an embodiment of the present invention, such as... Figure 5 As shown, the original system state parameters and the total disturbance are estimated in real time through the system's input and output. Based on the established third-order nonlinear model of the vehicle, an extended state observer is designed, including:

[0061] The third-order nonlinear model of the vehicle is as follows:

[0062]

[0063] Where ξ(t)∈R is the derivative of the uncertainty term of the established model with respect to external disturbances, p(t), u(t), and a(t) represent the vehicle's position, velocity, and acceleration, respectively. Based on the previous analysis of the extended state observer, T... t (t) can be considered as the input υ(t) of the extended system. These are parameters related to the vehicles in the queue.

[0064] Will Treating the unknown function of the model parameters as an unknown function, introducing external disturbances, and integrating the unknown function of the model with the external disturbances as an extended state of the established linear extended state observer, a fourth-order linear extended state observer can be established as follows:

[0065]

[0066] in These represent the estimated values ​​of position, velocity, and acceleration for the original system model, respectively. For the expanded state, β i ∈R are adjustable parameters of the linear state observer. The observation error of the corresponding extended state observer can be expressed in the following form:

[0067]

[0068] Written in matrix form as follows:

[0069]

[0070] Right now: in, E = [e1, e2, e3, e4] T ∈R 4 , Then the characteristic polynomial of A is: f(λ) = λ 4 +β1λ 3 +β2λ 2 +β3λ+β4, if it satisfies the following characteristic polynomial:

[0071]

[0072] That is, β1 = 4ω0, The observation error of the established extended state observer satisfies the Hurwitz stability condition, and the following linear extended state observer is established:

[0073]

[0074] Optionally, the extended state observer controlling the second vehicle estimates the target driving state parameters of the second vehicle based on the target position, including: decomposing the extended state observer into multiple sub-models using a backstepping design method; controlling the multiple sub-models to a stable state based on the target control quantity and / or objective function and the target position, wherein the target control quantity is the control quantity used to control the multiple sub-models to a stable state, and the objective function is the equation used to control the multiple sub-models to a stable state; and aggregating the multiple sub-models in a stable state to obtain the target driving state parameters.

[0075] Specifically, the backstepping design method described above is a method commonly used in the design of controllers for nonlinear systems. It decomposes a complex nonlinear system into multiple subsystems that do not exceed the system order, then designs virtual control variables and Lyapunov equations for each subsystem, and after ensuring the stability of each subsystem, combines the decomposed subsystems to complete the design of the entire system controller.

[0076] The target control variable mentioned above can be used to represent the virtual control variable mentioned above.

[0077] The objective function described above can be used to represent the Lyapunov equations described above.

[0078] In an alternative embodiment, the expanded state of the expanded state observer is assumed to be, i.e. The derivative of is unknown but bounded, i.e. in It is an unknown positive constant. The Lyapunov equation is established as follows: V0 = σ T Pσ, whose derivative is:

[0079]

[0080] Based on the preceding assumptions Therefore, the following formula holds true:

[0081]

[0082] in By selecting an appropriate matrix N such that ω0N-I>0, the designed extended state observer can estimate the vehicle's state and the total disturbance it experiences.

[0083] In addition, based on the established extended state observer, a distributed control method for vehicle queues was designed using the backstepping design method.

[0084] The control objective between the lead vehicle and the first vehicle is to make formula z 11 =p1-p0+l0+d1 approaches 0, so under the premise of ensuring the stability of the observation error of the extended state observer, the following Lyapunov equation is established:

[0085]

[0086] Its derivative is: in From the established extended state observer, we can obtain: Established, bringing it into the style Get Established, Order:

[0087]

[0088] This is the virtual control quantity, which is determined by designing α. 11 =-k 11 z 11 The derivative of the Lyapunov equation above can be written in the following form:

[0089]

[0090] By Young's inequality, the following relationship holds:

[0091] The derivatives of the Lyapunov equations hold the following relationship:

[0092]

[0093] in Δ2 = diag(0, 1, 0, 0). Similarly, the goal of queue control is to make the value approach 0, as shown in the previous analysis: The following Lyapunov equations are established: Its derivative is: Based on the preceding analysis and the established extended state observer, we can conclude that: make Where α 12 It is the established virtual control quantity, through design in then Mode The derivative of the Lyapunov equation can be written in the following form:

[0094]

[0095] in Δ1 = diag(1,0,0,0), so the control objective of the queue is transformed into making z 31 As the integers approach 0, the following formula holds true based on the preceding analysis: The following Lyapunov equations are established: Its derivative is: And for Based on the preceding analysis and the established extended state observer, the following formula holds true: in This is an estimate of the total external disturbances experienced by the system. From the above formula, we can see the system's control input υ1. Therefore, we design u1 as follows: Attached The derivative of the established Lyapunov equation yields the following formula:

[0096]

[0097] in Δ1 = diag(1,0,0,0), so by reasonably selecting the parameters in the above formula, the control objective of the first vehicle can be achieved.

[0098] Similarly, under the premise of ensuring queue stability and stable observation error of the extended state observer, the above derivation process is extended to other vehicles in the queue, resulting in the following controller design process:

[0099] z 11 =p1-p0+l0+d1

[0100]

[0101]

[0102]

[0103] z 12 =p2-(q+1)p1=qp0-q(l0+d1)+(l1+d2)

[0104]

[0105]

[0106] α 12 =-k 12 z 12

[0107]

[0108]

[0109] z 1i =p i -(q+1)p i-1 =qp i-2 -q(l i-2 +d i-1 )+(l i-1 +d i )

[0110]

[0111]

[0112] α 1i =-k 1i z 1i

[0113]

[0114]

[0115] Where i > 2

[0116] Example 2

[0117] According to an embodiment of the present invention, a vehicle queue control device is also provided. This device can execute a vehicle queue control method provided in Embodiment 1 above. The specific implementation method and preferred application scenario are the same as those in Embodiment 1 above, and will not be repeated here.

[0118] Figure 6 This is a schematic diagram of a vehicle queue control device according to an embodiment of the present invention, such as... Figure 6 As shown, the device includes:

[0119] The first control module 602 is used to respond to receiving a control command to control the vehicle queue, and to control the controller in the vehicle queue to obtain the target driving state parameters of the first vehicle and the initial driving state parameters of the second vehicle. The control command is used to control multiple vehicles in the vehicle queue to drive according to a preset interval strategy.

[0120] The second control module 604 is used to control the controller to control the second vehicle according to the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy, so as to obtain the target position of the second vehicle.

[0121] The estimation module 606 is used to control the extended state observer of the second vehicle to estimate the target driving state parameters of the second vehicle based on the target position. The target driving state parameters are applied in a scenario where multiple vehicles in a vehicle queue are controlled.

[0122] Optionally, the second control module includes: a first control unit, used to control the controller to obtain control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and a preset interval strategy; and a second control unit, used to control the second vehicle based on the control parameters and then obtain the target position of the second vehicle.

[0123] Optionally, the first control unit includes: a first control parameter obtaining unit, configured to obtain control parameters based on target driving state parameters of the first vehicle, initial driving state parameters of the second vehicle, and a preset interval strategy in response to the first vehicle being the lead vehicle in a vehicle convoy; and a second control parameter obtaining unit, configured to obtain control parameters based on target driving state parameters of the first vehicle, initial driving state parameters of the second vehicle, target driving state parameters of the third vehicle, and a preset interval strategy in response to the first vehicle not being the lead vehicle in a vehicle convoy, wherein the first vehicle is a vehicle between the second and third vehicles.

[0124] Optionally, the first control parameter obtaining unit includes: a preset driving state parameter determining unit, used to determine the target driving state parameter of the first vehicle as the preset driving state parameter, wherein the preset driving state parameter is the driving state parameter output based on the first vehicle driving according to the preset curve, and the preset curve is used to represent the correspondence between the vehicle's driving speed and driving time.

[0125] Optionally, the estimation module includes: a decomposition unit for decomposing the extended state observer into multiple sub-models using a backstepping design method; a third control unit for controlling the multiple sub-models to a stable state based on a target control quantity and / or an objective function and a target position, wherein the target control quantity is the control quantity used to control the multiple sub-models to a stable state, and the objective function is the equation used to control the multiple sub-models to a stable state; and an assembling unit for assembling the multiple sub-models in a stable state to obtain target driving state parameters.

[0126] Example 3

[0127] According to an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, the above-described vehicle queue control method is executed in the processor of the device.

[0128] Example 4

[0129] According to an embodiment of the present invention, a vehicle is also provided, comprising: one or more processors; a storage device for storing one or more programs; and, when the one or more programs are executed by the one or more processors, causing the one or more processors to execute the above-described vehicle queue control method.

[0130] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0131] In the above embodiments of the present invention, 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.

[0132] In the several 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.

[0133] 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.

[0134] Furthermore, the functional units in the various embodiments of the present invention 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.

[0135] 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 the present invention, 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 the present invention. 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.

[0136] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for controlling a vehicle queue, characterized in that, include: In response to receiving a control command to control the vehicle queue, the controller in the vehicle queue is controlled to obtain the target driving state parameters of the first vehicle and the initial driving state parameters of the second vehicle. The control command is used to control multiple vehicles in the vehicle queue to drive according to a preset interval strategy. The target driving state parameters include: the current speed, current acceleration and current position of the first vehicle, and the second vehicle in the vehicle queue is located behind the first vehicle. The controller controls the second vehicle based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy to obtain the target position of the second vehicle. The extended state observer controlling the second vehicle estimates the target driving state parameters of the second vehicle based on the target position, wherein the target driving state parameters are applied in a scenario where multiple vehicles in the vehicle queue are controlled; The extended state observer controlling the second vehicle estimates the target driving state parameters of the second vehicle based on the target position, including: decomposing the extended state observer into multiple sub-models using a backstepping design method; controlling the multiple sub-models to a stable state based on a target control quantity and / or objective function and the target position, wherein the target control quantity is a control quantity used to control the multiple sub-models to be in the stable state, and the objective function is an equation used to control the multiple sub-models to be in the stable state, and the objective function is a Lyapunov equation; and aggregating the multiple sub-models in the stable state to obtain the target driving state parameters.

2. The vehicle queuing control method according to claim 1, characterized in that, The controller controls the second vehicle based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy to obtain the target position of the second vehicle, including: The controller obtains control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy. After controlling the second vehicle based on the control parameters, the controller obtains the target position of the second vehicle.

3. The vehicle queuing control method according to claim 2, characterized in that, The controller obtains control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy, including: In response to the first vehicle being the lead vehicle in the vehicle convoy, the controller is controlled to obtain the control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy. In response to the first vehicle not being the lead vehicle in the vehicle platoon, the controller is controlled to obtain the control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, the target driving state parameters of the third vehicle, and the preset interval strategy, wherein the first vehicle is a vehicle between the second vehicle and the third vehicle.

4. The vehicle queuing control method according to claim 1, characterized in that, In response to the first vehicle being the lead vehicle, the target driving state parameters of the first vehicle are determined to be preset driving state parameters. The preset driving state parameters are driving state parameters output based on the first vehicle driving according to a preset curve. The preset curve is used to represent the correspondence between the vehicle's driving speed and driving time.

5. The vehicle queuing control method according to claim 1, characterized in that, The extended state observer is constructed based on the system disturbance state parameters and a third-order nonlinear dynamic model, which is constructed based on the vehicle's position state parameters, velocity state parameters, and acceleration state parameters.

6. A control device for a vehicle platoon, characterized in that, include: The first control module is configured to respond to a control command received for controlling the vehicle queue, and to control the controller in the vehicle queue to obtain the target driving state parameters of the first vehicle and the initial driving state parameters of the second vehicle. The control command is configured to control multiple vehicles in the vehicle queue to drive according to a preset interval strategy. The target driving state parameters include: the current speed, current acceleration and current position of the first vehicle, and the second vehicle in the vehicle queue is positioned behind the first vehicle. The second control module is used to control the controller to control the second vehicle according to the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy, so as to obtain the target position of the second vehicle. An estimation module is used to control the extended state observer of the second vehicle to estimate the target driving state parameters of the second vehicle based on the target position, wherein the target driving state parameters are applied in a scenario where multiple vehicles in the vehicle queue are controlled. The estimation module is further configured to decompose the extended state observer into multiple sub-models using a backstepping design method; control the multiple sub-models to a stable state based on a target control quantity and / or an objective function and the target position, wherein the target control quantity is a control quantity used to control the multiple sub-models to a stable state, and the objective function is an equation used to control the multiple sub-models to a stable state, wherein the objective function is a Lyapunov equation; and aggregate the multiple sub-models in the stable state to obtain the target driving state parameters.

7. The vehicle queuing control device according to claim 6, characterized in that, The second control module includes: The first control unit is used to control the controller to obtain control parameters based on the target driving state parameters of the first vehicle, the initial driving state parameters of the second vehicle, and the preset interval strategy. The second control unit is used to control the controller to control the second vehicle based on the control parameters and then obtain the target position of the second vehicle.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the execution of the vehicle queuing control method of any one of claims 1 to 5 in the processor of the device.

9. A vehicle, characterized in that, include: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors perform the vehicle queue control method according to any one of claims 1 to 5.

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