A safety protection method and device in vehicle platoon longitudinal control

Abstract

The present application relates to the technical field of vehicle platoon longitudinal control, and relates to a safety protection method and device in vehicle platoon longitudinal control. For each following vehicle in the vehicle platoon except the lead vehicle, a longitudinal dynamics model, a desired distance model, a longitudinal speed error model and a longitudinal position error model of the following vehicle are constructed. A corresponding upper-layer distributed platoon cooperative controller and a lower-layer predictive safety filter of the following vehicle are determined. The upper-layer distributed platoon cooperative controller and the lower-layer predictive safety filter of the following vehicle are run to determine the desired acceleration of the following vehicle. The desired acceleration of the following vehicle is input into an execution unit in the following vehicle, and the execution unit adjusts the speed of the following vehicle and the distance between the following vehicle and the preceding vehicle according to the desired acceleration. The safety constraint distance between each vehicle and the preceding vehicle in the vehicle platoon can be guaranteed, and the safety and stability of platoon driving are improved.

Description

Technical Field

[0001] This specification relates to the field of vehicle platoon longitudinal control technology, and in particular to a safety protection method and device for vehicle platoon longitudinal control. Background Technology

[0002] With the widespread adoption of automobiles and the rapid development of vehicle-to-everything (V2X) technology, intelligent platooning control has become a crucial application in intelligent transportation systems, effectively improving traffic safety, increasing efficiency, and reducing energy consumption. Leveraging vehicle-to-vehicle communication technology, vehicles can share information such as speed and location in real time, enabling collaborative control and thus alleviating traffic congestion and reducing accident rates. Furthermore, by optimizing overall routes and speeds, platooning can further reduce energy consumption, especially in electric vehicle applications, helping to extend their driving range. Simultaneously, platooning reduces frequent braking and acceleration, thereby lowering energy consumption.

[0003] However, due to the complexity of traffic environments and the nonlinear characteristics of vehicle dynamics systems, current research on cooperative tracking and performance optimization in vehicle platoon longitudinal control still has certain limitations. In actual operation, except for the lead vehicle, it is difficult to precisely maintain the safe distance between each vehicle in the platoon and the vehicle in front. This not only affects the safety of platoon driving but may even lead to collision risks. This problem, to some extent, limits the widespread application of vehicle platoon longitudinal control technology, weakens the stability of platoon driving, and makes it difficult to adapt to complex and changing driving environments.

[0004] Therefore, this specification provides a safety protection method and device for longitudinal control of vehicle platoons. Summary of the Invention

[0005] This specification provides a safety protection method and device for longitudinal control of vehicle platooning, in order to partially solve the aforementioned problems existing in the prior art.

[0006] The following technical solution is adopted in this specification:

[0007] This manual provides a safety protection method for longitudinal control of vehicle platoons, including:

[0008] S1: For each following vehicle in the vehicle queue, excluding the lead vehicle, construct a longitudinal dynamics model for that following vehicle i; where i represents the i-th following vehicle in the vehicle queue, and i is a positive integer;

[0009] S2: Based on the preset first following distance and second following distance, construct the expected distance model between the following vehicle i and the vehicle in front of the following vehicle i;

[0010] S3: Construct the longitudinal velocity error model of the following vehicle i; and determine the longitudinal position error model of the following vehicle i based on the desired spacing model;

[0011] S4: Based on the longitudinal position error model and longitudinal speed error model of the following vehicle i, construct the longitudinal tracking error state space model, longitudinal tracking error state and upper-level distributed queue cooperative controller corresponding to the following vehicle i;

[0012] S5: Based on the upper-layer distributed queue cooperative controller and longitudinal dynamics model corresponding to the following vehicle i, construct the lower-layer predictive safety filter corresponding to the following vehicle i;

[0013] S6: Run the upper-layer distributed queue cooperative controller and the lower-layer predictive safety filter corresponding to the following vehicle i to determine the expected acceleration of the following vehicle i;

[0014] S7: Input the desired acceleration of the following vehicle i into the execution unit in the following vehicle i. The execution unit adjusts the speed of the following vehicle i according to the desired acceleration, so as to adjust the distance between the following vehicle i and the vehicle in front of the following vehicle i.

[0015] Based on the aforementioned technical means, this solution can ensure coordinated tracking and performance optimization in vehicle platoon longitudinal control while considering the safe constraint distance that each vehicle in the platoon, excluding the lead vehicle, must maintain with respect to the vehicle in front. This improves the safety and stability of platoon driving and reduces the risk of vehicle collisions. It is applicable to various vehicle platoon longitudinal control methods based on sliding mode control, feedback control, backstepping control, and reinforcement learning, and exhibits generalization capabilities. Furthermore, by constructing a lower-level predictive safety filter and adding it to the lower layer of the upper-level distributed platoon cooperative controller, unsafe control actions of the upper-level distributed platoon cooperative controller can be corrected, thereby improving the safety of the vehicle platoon longitudinal control method.

[0016] Furthermore, the expression for the longitudinal dynamics model of the following vehicle i is:

[0017]

[0018]

[0019] Where, p i (t),v i (t),a i (t),u i (t) represents the longitudinal vehicle position, longitudinal velocity, longitudinal acceleration, and desired acceleration of the following vehicle i at time t, respectively. i The time delay is the longitudinal actuator delay of the following vehicle i.

[0020] Furthermore, the expression for the desired spacing model is:

[0021] D i (t)=l+h i v i (t)

[0022] Among them, D i (t) represents the expected distance between the following vehicle i and the vehicle preceding it at time t; l is the preset first following distance; h i The second following distance for the vehicle i is preset; v i (t) represents the longitudinal velocity of the following vehicle i at time t.

[0023] Furthermore, the expression for the longitudinal velocity error model of the following vehicle i is:

[0024] e vi (t)=v i-1 (t)-v i (t)

[0025] Among them, e vi (t) represents the longitudinal velocity error of the following vehicle i at time t; v i-1 (t) represents the longitudinal velocity of the vehicle preceding vehicle i at time t; v i (t) represents the longitudinal velocity of the following vehicle i at time t.

[0026] Furthermore, the expression for the longitudinal position error model of the following vehicle i is:

[0027] e pi (t)=p i-1 (t)-p i (t)-D i (t)

[0028] Among them, e pi (t) represents the longitudinal vehicle position error of the following vehicle i at time t; p i-1 (t) represents the longitudinal position of the vehicle preceding the following vehicle i at time t; p i (t) represents the longitudinal position of the following vehicle i at time t.

[0029] Furthermore, the longitudinal tracking error state space model and the longitudinal tracking error state corresponding to the following vehicle i are as follows:

[0030]

[0031] x i (t)=[e pi (t)e vi (t)a i(t)a i-1 (t)] T

[0032]

[0033] in, Let x be the state-space model of the longitudinal tracking error corresponding to the following vehicle i. i (t) represents the longitudinal tracking error state corresponding to the following vehicle i.

[0034] Furthermore, the expression for the upper-level distributed queue cooperative controller corresponding to the following vehicle i is:

[0035] u i (t)=-k pi e pi (t)-k vi e vi (t)

[0036] Among them, u i (t) represents the expected acceleration of the following vehicle i at time t, calculated by the upper-level distributed queue cooperative controller corresponding to the following vehicle i; k pi and k vi All of these are preset gain constants for the following vehicle i.

[0037] Furthermore, the expression for the cost function of the lower-level predictive safety filter corresponding to the following vehicle i is:

[0038]

[0039] Among them, u i_s (s|t) represents a set of expected acceleration sequences predicted by the lower-level predictive safety filter corresponding to the following vehicle i at time t. (s|t) is equivalent to (s+t), and the length of the expected acceleration sequence is s; u i_s (0|t) is the first expected acceleration in the expected acceleration sequence.

[0040] Furthermore, the expression for the constraint corresponding to the lower-level predictive security filter is:

[0041] x i (0|t)=x i (t)

[0042]

[0043] x min =[min(u i ),min(e pi ),min(e vi ),min(a i)] T

[0044] x max =[max(u i ),max(e pi ),max(e vi ),max(a i )] T

[0045] Where, x i (s|t) is the longitudinal tracking error state sequence of the following vehicle i, (s|t) is equivalent to (s+t), and the length of the longitudinal tracking error state sequence is s; x i (0|t) represents the longitudinal tracking error state when s is 0 in the longitudinal tracking error state sequence; min(u i ),min(e pi ),min(e vi ),min(s i ) represent the preset minimum expected acceleration, minimum position error, minimum velocity error, and minimum longitudinal acceleration, respectively; max(u i ),max(e pi ),max(e vi ),max(a i These are the preset maximum expected acceleration, maximum position error, maximum velocity error, and maximum longitudinal acceleration, respectively. To solve for the set of terminals in the model predictive control involved in the lower-level predictive security filter, N p N represents the prediction time domain length in model predictive control. p Equal to s; I n It is an n*n identity matrix.

[0046] Furthermore, the method further includes step S8:

[0047] Repeat steps S4-S7 until the longitudinal control of the vehicle platoon ends.

[0048] The above-mentioned technical solutions adopted in this specification can achieve the following beneficial effects:

[0049] The safety protection method for longitudinal control of vehicle platoons provided in this specification can ensure coordinated tracking and performance optimization while taking into account the safe constraint distance that each vehicle in the platoon (excluding the lead vehicle) must maintain with respect to the vehicle in front. This improves the safety and stability of platoon driving and reduces the risk of vehicle collisions. It is applicable to various longitudinal control methods for vehicle platoons, including sliding mode control, feedback control, backstepping control, and reinforcement learning, and has generalization capabilities. Furthermore, by constructing a lower-level predictive safety filter and adding it to the lower layer of the upper-level distributed platoon cooperative controller, unsafe control actions of the upper-level distributed platoon cooperative controller can be corrected, thereby improving the safety of the longitudinal control method for vehicle platoons. Attached Figure Description

[0050] The accompanying drawings, which are included to provide a further understanding of this specification and form part of this specification, illustrate exemplary embodiments and are used to explain this specification, but do not constitute an undue limitation thereof. In the drawings:

[0051] Figure 1 A flowchart illustrating a safety protection method in longitudinal control of a vehicle queue, provided as an embodiment of this specification;

[0052] Figure 2 This is a schematic diagram illustrating the effect of a safety protection method in longitudinal control of vehicle platooning provided in this specification;

[0053] Figure 3 A schematic diagram of a safety protection device in longitudinal control of a vehicle platoon, provided for the purposes of this specification;

[0054] Figure 4 This specification provides a corresponding Figure 1 A schematic diagram of the structure of an electronic device. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this specification will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without creative effort are within the scope of protection of this application.

[0056] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0057] The technical solutions provided in the various embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0058] Figure 1 A flowchart illustrating a safety protection method in longitudinal control of a vehicle platoon, provided as an embodiment of this specification, includes the following steps:

[0059] S1: For each following vehicle in the vehicle queue, excluding the lead vehicle, construct a longitudinal dynamics model for that following vehicle i; where i represents the i-th following vehicle in the vehicle queue, and i is a positive integer.

[0060] This specification describes the process of vehicle distance control in the longitudinal control of vehicle platooning. In the embodiments described herein, this process can be executed by a computing unit. However, this specification does not limit the type of device or platform used to perform the vehicle distance control process in the longitudinal control of vehicle platooning; for example, a personal computer, mobile terminal, vehicle infotainment system, or onboard electronic control unit (ECU) can also be used. For ease of description, the following description uses a computing unit capable of data processing on the vehicle as the execution entity.

[0061] In one or more embodiments of this specification, in the longitudinal control of the vehicle platoon, the entire vehicle platoon may contain N+1 vehicles. The vehicles in the platoon are sequentially numbered from 0 to N according to their longitudinal arrangement from front to back. The 0th vehicle is the lead vehicle of the platoon, and the remaining vehicles, numbered 1 to N, are following vehicles.

[0062] Each vehicle in the platoon is equipped with communication equipment, positioning equipment, a computing unit, and an execution unit. The communication equipment obtains vehicle information (such as longitudinal vehicle position, longitudinal speed, and longitudinal acceleration) from the vehicle's CAN bus and transmits it to surrounding vehicles in the platoon (including the vehicle preceding or following it) via vehicle-to-vehicle (V2V) communication. It can also receive vehicle information from surrounding vehicles, forming a vehicle platoon communication topology and exchanging information. The positioning equipment obtains the vehicle's current longitudinal position, longitudinal speed, and longitudinal acceleration through devices such as the Global Positioning System (GPS) and transmits it to the CAN bus. The computing unit obtains its own vehicle information and information from surrounding vehicles via the CAN bus. Through subsequent calculations, it obtains the desired acceleration from the upper-layer distributed platoon cooperative controller and the lower-layer predictive safety filter, and transmits it to the execution unit via the CAN bus. The execution unit adjusts the vehicle's speed according to the desired acceleration to maintain the desired platoon structure.

[0063] In one or more embodiments of this specification, the computing unit can construct a longitudinal dynamics model for each following vehicle in the vehicle queue, excluding the lead vehicle. Taking the vehicles in the queue as sequentially numbered from 0 to N as an example, vehicles numbered from 1 to N are the following vehicles after the 0th vehicle (i.e., the lead vehicle). Therefore, the number of this following vehicle can be set as i, where i is a positive integer in the range of 1 to N.

[0064] The computing unit can obtain the longitudinal vehicle position, longitudinal velocity, and longitudinal acceleration of the following vehicle i via the CAN bus, as well as the preset longitudinal actuator delay, which refers to the time between pressing the accelerator pedal twice. Based on this, a longitudinal dynamics model of the following vehicle i containing the desired acceleration is constructed. It is worth noting that, in this specification, "longitudinal" refers to the length direction of the vehicle from the front to the rear.

[0065] Of course, for each vehicle in the convoy, its longitudinal position, longitudinal velocity, or longitudinal acceleration may change over time as the convoy moves. Therefore, considering time t, the expression for the longitudinal dynamics model of the following vehicle i can be:

[0066]

[0067] Where, p i (t),v i (t),a i (t),u i(t) represents the longitudinal vehicle position, longitudinal velocity, longitudinal acceleration, and desired acceleration of the following vehicle i at time t, respectively. i The longitudinal actuator time delay is preset for the following vehicle i. It is worth noting that the longitudinal vehicle position of the following vehicle i means the longitudinal displacement of the following vehicle i.

[0068] S2: Based on the preset first following distance and second following distance, construct the expected distance model between the following vehicle i and the vehicle preceding the following vehicle i.

[0069] In one or more embodiments of this specification, the computing unit can construct a model of the expected distance between the following vehicle i and the preceding vehicle (i-1) of the following vehicle i based on a preset first following distance and a second following distance.

[0070] The expression for the expected spacing model is:

[0071] D i (t)=l+h i v i (t)

[0072] Among them, D i (t) represents the expected distance between the following vehicle i and the vehicle (i-1) preceding it at time t. l is the preset first following distance. h i This is the preset second following distance for the following vehicle i. i (t) represents the longitudinal velocity of the following vehicle i at time t. Of course, l and h... i The appropriate selection should be made based on the operating speed and conditions of the vehicle platoon to meet the requirements for platoon stability and performance.

[0073] S3: Construct a longitudinal speed error model for the following vehicle i; and determine a longitudinal position error model for the following vehicle i based on the desired spacing model.

[0074] In one or more embodiments of this specification, since the computing unit can obtain information about the vehicle itself and surrounding vehicles from the CAN bus, the computing unit can construct a longitudinal speed error model between the following vehicle i and the preceding vehicle (i-1) at time t. The computing unit also constructs a longitudinal position error model between the following vehicle i and the preceding vehicle (i-1) at time t based on the desired spacing model.

[0075] The expression for the longitudinal velocity error model of the following vehicle i is:

[0076] e vi (t)=v i-1 (t)-v i (t)

[0077] Among them, e vi (t) represents the longitudinal velocity error of the following vehicle i at time t. i-1 (t) represents the longitudinal velocity of the vehicle preceding the following vehicle (i-1) at time t. i (t) represents the longitudinal velocity of the following vehicle i at time t.

[0078] The expression for the longitudinal position error model of the following vehicle i is:

[0079] e pi (t)=p i-1 (t)-p i (t)-D i (t)

[0080] Among them, e pi (t) represents the longitudinal vehicle position error of the following vehicle i at time t. i-1 (t) represents the longitudinal position of the vehicle preceding the following vehicle (i-1) at time t. i (t) represents the longitudinal position of the following vehicle i at time t.

[0081] S4: Based on the longitudinal position error model and longitudinal speed error model of the following vehicle i, construct the longitudinal tracking error state space model, longitudinal tracking error state, and upper-level distributed queue cooperative controller corresponding to the following vehicle i.

[0082] In one or more embodiments of this specification, the computing unit can determine the longitudinal tracking error state space model, longitudinal tracking error state, and upper-layer distributed queue cooperative controller corresponding to the following vehicle i based on the longitudinal position error model and longitudinal speed error model of the following vehicle i.

[0083] The longitudinal tracking error state space model and the longitudinal tracking error state corresponding to the following vehicle i are as follows:

[0084]

[0085] x i (t)=[e pi (t)e vi (t)a i (t)a i-1 (t)] T

[0086]

[0087] in, Let x be the state-space model of the longitudinal tracking error corresponding to the following vehicle i. i (t) represents the longitudinal tracking error state corresponding to the following vehicle i. i-1(t) and a i-1 (t) represents the expected acceleration and longitudinal acceleration of the (i-1)th following vehicle, respectively.

[0088] The expression for the upper-level distributed queue cooperative controller corresponding to the following vehicle i is:

[0089] u i (t)=-k pi e pi (t)-k vi e vi (t)

[0090] Among them, u i (t) represents the expected acceleration of the following vehicle i at time t, calculated by the upper-level distributed queue cooperative controller corresponding to the following vehicle i. pi and k vi All of these are preset gain constants for the following vehicle i. Of course, the gain constant can be selected according to the following rules, k pi <0,k vi >0,k vi >-δ i k pi This is to meet the requirements for vehicle platoon stability and tracking performance.

[0091] S5: Based on the upper-layer distributed queue cooperative controller and longitudinal dynamics model corresponding to the following vehicle i, construct the lower-layer predictive safety filter corresponding to the following vehicle i.

[0092] In one or more embodiments of this specification, the computing unit may determine the lower-level predictive safety filter corresponding to the following vehicle i based on the upper-level distributed queue cooperative controller and the longitudinal dynamics model corresponding to the following vehicle i.

[0093] It is worth noting that the lower-level predictive security filter constructed here is a security verification module or system used to verify the u calculated by the upper-level distributed queue collaborative controller. i (t) is modified to satisfy the security constraints of the lower-level predictive security filter (hereinafter referred to as constraints). The cost function is a mathematical expression used by the lower-level predictive security filter to measure whether the expected acceleration calculated by the upper-level distributed queue cooperative controller satisfies the constraints. The expected acceleration that satisfies the constraints is selected by the cost function.

[0094] Therefore, the expression for the cost function of the lower-level predictive safety filter corresponding to the following vehicle i is:

[0095]

[0096] Among them, u i_s(s|t) represents a set of expected acceleration sequences predicted by the lower-level predictive safety filter corresponding to the following vehicle i at time t. (s|t) is equivalent to (s+t), and the length of the expected acceleration sequence is s, where s = 0, 1, 2…N. p N p The explanation can be found in the following constraint N. p Explanation. u i_s (0|t) represents the first expected acceleration in the expected acceleration sequence.

[0097] The expression for the constraint corresponding to the lower-level predictive security filter is:

[0098] x i (0|t)=x i (t)

[0099]

[0100] x min =[min(u i ),min(e pi ),min(e vi ),min(a i )] T

[0101] x max =[max(u i ),max(e pi ),max(e vi ),max(a i )] T

[0102] Where, x i (s|t) is the longitudinal tracking error state sequence of the following vehicle i, (s|t) is equivalent to (s+t), and the length of the longitudinal tracking error state sequence is s. i (0|t) represents the longitudinal tracking error state when s is 0 in the longitudinal tracking error state sequence. min(u i ),min(e pi ),min(e vi ),min(a i ) represent the preset minimum expected acceleration, minimum position error, minimum velocity error, and minimum longitudinal acceleration, respectively; max(u i ),max(e pi ),max(e vi ),max(a i These are the preset maximum expected acceleration, maximum position error, maximum velocity error, and maximum longitudinal acceleration, respectively. To solve for the set of terminals in the model predictive control involved in the lower-level predictive security filter, N p n represents the prediction time domain length in model predictive control. p Equal to s. I n It is an n*n identity matrix. It is worth noting that the expected minimum acceleration, minimum position error, minimum velocity error, minimum longitudinal acceleration, maximum expected acceleration, maximum position error, maximum velocity error, and maximum longitudinal acceleration are all preset constants. Among them, the expected minimum acceleration can be the same as the minimum longitudinal acceleration, and the expected maximum acceleration can be the same as the maximum longitudinal acceleration.

[0103] S6: Run the upper-layer distributed queue cooperative controller and the lower-layer predictive safety filter corresponding to the following vehicle i to determine the expected acceleration of the following vehicle i.

[0104] S7: Input the desired acceleration of the following vehicle i into the execution unit in the following vehicle i. The execution unit adjusts the speed of the following vehicle i according to the desired acceleration, so as to adjust the distance between the following vehicle i and the vehicle in front of the following vehicle i.

[0105] In one or more embodiments of this specification, the computing unit can run the upper-layer distributed queue cooperative controller and the lower-layer predictive safety filter corresponding to the following vehicle i to determine the expected acceleration of the following vehicle i. Then, the computing unit inputs the expected acceleration of the following vehicle i into the execution unit within the following vehicle i, and the execution unit can adjust the speed of the following vehicle i according to the expected acceleration to adjust the distance between the following vehicle and the vehicle in front of it, thereby achieving safety protection among the vehicles in the vehicle queue.

[0106] Furthermore, step S8 is included, whereby the calculation unit can repeat steps S4-S7 to continue calculating the expected acceleration of the following vehicle i at time t+1 and thereafter, until the longitudinal control of the vehicle platoon ends.

[0107] Figure 2 This is a schematic diagram illustrating the effect of a safety protection method in the longitudinal control of vehicle platoons. As shown in the figure... Figure 2 The two vehicles on the left, one in front and one behind, which pose a collision risk, are protected by this plan, and after the vehicle distance is controlled, a [collision] is formed. Figure 2 The right side has no risk of collision.

[0108] based on Figure 1The method described herein, for longitudinal control of vehicle platoons, ensures coordinated tracking and performance optimization while considering the necessary safety constraints between each vehicle (excluding the lead vehicle) and the vehicle in front. This enhances the safety and stability of platooning and reduces the risk of collisions. It is applicable to various longitudinal control methods for vehicle platoons, including sliding mode control, feedback control, backstepping control, and reinforcement learning, and exhibits generalization capabilities. Furthermore, by constructing a lower-level predictive safety filter and adding it to the lower layer of the upper-level distributed platooning cooperative controller, unsafe control actions of the upper-level distributed platooning cooperative controller can be corrected, thereby improving the safety of the longitudinal control method for vehicle platoons.

[0109] The above describes a safety protection method for longitudinal control of vehicle platoons, provided by one or more embodiments of this specification. Based on the same idea, this specification also provides a corresponding safety protection device for longitudinal control of vehicle platoons, such as... Figure 3 As shown.

[0110] Figure 3 This specification provides a schematic diagram of a safety protection device for longitudinal control of vehicle platooning, specifically including:

[0111] The first construction module 300 is used to construct a longitudinal dynamics model for each following vehicle i in the vehicle queue, excluding the lead vehicle; where i represents the i-th following vehicle in the vehicle queue and i is a positive integer.

[0112] The second construction module 302 is used to construct the expected distance model between the following vehicle i and the vehicle in front of the following vehicle i based on the preset first following distance and second following distance;

[0113] The third construction module 304 is used to construct the longitudinal speed error model of the following vehicle i; and to determine the longitudinal position error model of the following vehicle i based on the expected spacing model.

[0114] The fourth construction module 306 is used to construct the longitudinal tracking error state space model, longitudinal tracking error state, and upper-layer distributed queue cooperative controller corresponding to the following vehicle i based on the longitudinal position error model and longitudinal speed error model of the following vehicle i.

[0115] The fifth construction module 308 is used to construct the lower-level predictive safety filter corresponding to the following vehicle i based on the upper-level distributed queue cooperative controller and longitudinal dynamics model corresponding to the following vehicle i.

[0116] The determination module 310 is used to run the upper-layer distributed queue cooperative controller and the lower-layer predictive safety filter corresponding to the following vehicle i to determine the expected acceleration of the following vehicle i.

[0117] The execution module 312 is used to input the desired acceleration of the following vehicle i into the execution unit in the following vehicle i. The execution unit adjusts the speed of the following vehicle i according to the desired acceleration, so as to adjust the distance between the following vehicle i and the vehicle in front of the following vehicle i.

[0118] This specification also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 A safety protection method is provided for longitudinal control of vehicle queuing.

[0119] This instruction manual also provides Figure 4 The diagram shows a schematic structural representation of the electronic device. Figure 4 As shown, at the hardware level, this electronic device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to achieve the above. Figure 1 The aforementioned safety protection method in longitudinal control of vehicle platooning.

[0120] Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of hardware and software. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0121] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0122] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0123] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0124] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware components.

[0125] Those skilled in the art will understand that embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0126] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0127] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0128] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0129] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0130] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0131] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0132] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0133] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0134] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0135] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0136] The above description is merely an embodiment of this specification and is not intended to limit this specification. Various modifications and variations can be made to this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims of this specification.

Claims

1. A safety protection method in a vehicle platoon longitudinal control, characterized by, include: S1: For each following vehicle in the vehicle queue, excluding the lead vehicle, construct a longitudinal dynamics model for that following vehicle i; where i represents the i-th following vehicle in the vehicle queue, and i is a positive integer; S2: Based on the preset first following distance and second following distance, construct the expected distance model between the following vehicle i and the vehicle in front of the following vehicle i; S3: Construct the longitudinal velocity error model of the following vehicle i; and determine the longitudinal position error model of the following vehicle i based on the desired spacing model; S4: Based on the longitudinal position error model and longitudinal speed error model of the following vehicle i, construct the longitudinal tracking error state space model, longitudinal tracking error state and upper-level distributed queue cooperative controller corresponding to the following vehicle i; S5: Based on the upper-layer distributed queue cooperative controller and longitudinal dynamics model corresponding to the following vehicle i, construct the lower-layer predictive safety filter corresponding to the following vehicle i; S6: Run the upper-layer distributed queue cooperative controller and the lower-layer predictive safety filter corresponding to the following vehicle i to determine the expected acceleration of the following vehicle i; S7: Input the desired acceleration of the following vehicle i into the execution unit in the following vehicle i. The execution unit adjusts the speed of the following vehicle i according to the desired acceleration, so as to adjust the distance between the following vehicle i and the vehicle in front of the following vehicle i. The expression for the constraint corresponding to the lower-layer predictive security filter is as follows: In the formula, This is the longitudinal tracking error state sequence of the following vehicle i. Equivalent to The length of the longitudinal tracking error state sequence is s. For time t, there is a set of expected acceleration sequences predicted by the lower-level predictive safety filter corresponding to the following vehicle i. This represents the longitudinal tracking error state corresponding to the following vehicle i. This represents the longitudinal tracking error state when s is 0 in the longitudinal tracking error state sequence. These are the preset minimum expected acceleration, minimum position error, minimum velocity error, and minimum longitudinal acceleration, respectively. These are the preset maximum expected acceleration, maximum position error, maximum velocity error, and maximum longitudinal acceleration, respectively. To solve for the set of terminals involved in the model predictive control when solving for the lower-level predictive security filter, The prediction time domain length in model predictive control. Equal to s; It is an n*n identity matrix.

2. The safety protection method in longitudinal control of vehicle platooning as described in claim 1, characterized in that, The expression for the longitudinal dynamics model of the following vehicle i is: in, Let be the longitudinal vehicle position, longitudinal velocity, longitudinal acceleration, and desired acceleration of the following vehicle i at time t, respectively. The time delay is the longitudinal actuator delay of the following vehicle i.

3. The safety protection method in longitudinal control of vehicle platooning as described in claim 2, characterized in that, The expression for the desired spacing model is: in, Let t be the expected distance between the following vehicle i and the vehicle preceding it at time t; The preset first following distance; This is the preset second following distance for the following vehicle i; Let t be the longitudinal velocity of the following vehicle i.

4. The safety protection method in longitudinal control of vehicle platooning as described in claim 3, characterized in that, The expression for the longitudinal velocity error model of the following vehicle i is: in, Let be the longitudinal velocity error of the following vehicle i at time t; Let t be the longitudinal velocity of the vehicle preceding vehicle i that is following vehicle i; Let t be the longitudinal velocity of the following vehicle i.

5. The safety protection method in longitudinal control of vehicle platooning as described in claim 4, characterized in that, The expression for the longitudinal position error model of the following vehicle i is: in, Let be the longitudinal vehicle position error of the following vehicle i at time t; Let t be the longitudinal vehicle position of the vehicle preceding vehicle i. Let t be the longitudinal vehicle position of the following vehicle i at time t.

6. The safety protection method in longitudinal control of vehicle platooning as described in claim 5, characterized in that, The longitudinal tracking error state space model and the longitudinal tracking error state corresponding to the following vehicle i are as follows: in, This is the state-space model of the longitudinal tracking error corresponding to the following vehicle i. This represents the longitudinal tracking error state corresponding to the following vehicle i.

7. The safety protection method in longitudinal control of vehicle platooning as described in claim 6, characterized in that, The expression for the upper-level distributed queue cooperative controller corresponding to the following vehicle i is: in, The expected acceleration of the following vehicle i at time t is calculated by the upper-level distributed queue cooperative controller corresponding to the following vehicle i. and All of these are preset gain constants for the following vehicle i.

8. The safety protection method in longitudinal control of vehicle platooning as described in claim 7, characterized in that, The expression for the cost function of the lower-level predictive safety filter corresponding to the following vehicle i is: in, Let be a set of expected acceleration sequences predicted by the lower-level predictive safety filter corresponding to the following vehicle i at time t. Equivalent to The length of the desired acceleration sequence is s; This is the first expected acceleration in the expected acceleration sequence.

9. A safety protection method for longitudinal control of vehicle platoons as described in claim 1, characterized in that, The method further includes step S8: Repeat steps S4-S7 until the longitudinal control of the vehicle platoon ends.

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