Multi-vehicle cooperative control method, electronic device, storage medium and program product

Abstract

The invention provides a multi-vehicle cooperative control method, electronic equipment, a storage medium and a program product, and relates to the technical field of motorcade control, and the method comprises the steps: obtaining the motion state parameters of a first vehicle and a second vehicle which are adjacent in a multi-motorcade; generating a driving time distance parameter between the first vehicle and the second vehicle based on the motion state parameter; determining a safe driving distance between the first vehicle and the second vehicle based on the driving time distance parameter; and performing cooperative control on the multiple vehicle queues based on the safe driving distance. By adopting the method and the device, the problem that a traditional spacing strategy cannot keep the motorcade stable when the speed of a certain vehicle in the motorcade changes rapidly can be solved, so that the stability of motorcade operation is improved.

Description

Technical Field

[0001] This application relates to the field of fleet control technology, and in particular to a multi-vehicle cooperative control method, electronic equipment, storage medium, and program product. Background Technology

[0002] In the field of multi-vehicle group cooperative control technology, since the vehicles in a platoon do not operate in isolation but rather exhibit significant kinematic interactions, fully considering and resolving these kinematic interactions is a crucial prerequisite for improving the overall performance of the platoon control system. Establishing an effective spacing / interval strategy is one of the core challenges, as this strategy is directly related to traffic safety and road capacity improvement, and is a vital support for the implementation of multi-vehicle group cooperative control technology. However, common spacing strategies in related technologies still cannot promptly adjust vehicle spacing when the speed of a vehicle in the platoon changes rapidly, leading to problems such as platoon oscillation and unstable following, resulting in poor platoon operational stability. Summary of the Invention

[0003] The main purpose of this application is to propose a multi-vehicle cooperative control method, electronic equipment, storage medium, and program product, which aims to solve the problems associated with traditional spacing strategies and thereby improve the stability of fleet operation.

[0004] To achieve the above objectives, the first aspect of this application proposes a multi-vehicle cooperative control method, the method comprising: Obtain the motion state parameters of the first and second adjacent vehicles in a multi-vehicle queue; Based on the motion state parameters, the travel time and distance parameters between the first vehicle and the second vehicle are generated; The safe driving distance between the first vehicle and the second vehicle is determined based on the driving time and distance parameters. The multi-vehicle queue is controlled collaboratively based on the safe driving distance.

[0005] In some embodiments, the motion state parameters include: a first speed and a first acceleration of a first vehicle, and a second speed and a second acceleration of a second vehicle; the first vehicle is the vehicle in front of the second vehicle; The step of generating the travel time and distance parameters between the first vehicle and the second vehicle based on the motion state parameters includes: Divide the speed difference between the first speed and the second speed by the second speed to obtain the speed deviation parameter between the first vehicle and the second vehicle. The acceleration difference between the first acceleration and the second acceleration is normalized based on the second speed to obtain the acceleration matching parameters between the first vehicle and the second vehicle; The speed deviation parameter and the acceleration matching parameter are fused to obtain the travel time and distance parameter between the first vehicle and the second vehicle.

[0006] In some embodiments, the method further includes: Obtain the spacing control coefficient for coordinated control of the multi-vehicle queue; The process of fusing the velocity deviation parameter and the acceleration matching parameter includes: The velocity deviation parameter and the acceleration matching parameter are fused based on the spacing control coefficient.

[0007] In some embodiments, obtaining the spacing control coefficient for coordinated control of the multi-vehicle queue includes: Obtain the range of control coefficients corresponding to the preset multi-input variable time interval strategy; the multi-input variable time interval strategy is used to indicate the processing of the motion state parameters of the first and second adjacent vehicles in the multi-vehicle queue, so as to obtain the safe driving distance between the first vehicle and the second vehicle. Within the range of the selected control coefficients, the spacing control coefficients for coordinated control of the multi-vehicle queue are determined.

[0008] In some embodiments, the range of control coefficient selection includes the target range of spacing control coefficients for cooperative adaptive cruise vehicles, and the cooperative adaptive cruise vehicles include vehicles in the multi-vehicle platoon. The method further includes: The control speed parameters of the cooperative adaptive cruise vehicle are determined based on the multi-input variable time interval strategy. Based on the control speed parameters and the speed disturbance transfer function of the cooperative adaptive cruise vehicle, the stability conditions of the cooperative adaptive cruise vehicle are determined. The target range of the spacing control coefficient for the cooperative adaptive cruise vehicle is calculated based on the stability conditions.

[0009] In some embodiments, the second vehicle is a vehicle following the first vehicle; Determining the safe driving distance between the first vehicle and the second vehicle based on the driving time and distance parameters includes: Multiply the travel time distance parameter by the second speed of the second vehicle in the motion state parameters to obtain the product of the travel time distance parameter and the second speed; The expected static distance is added to the product to obtain the safe driving distance between the first vehicle and the second vehicle.

[0010] In some embodiments, the second vehicle is a vehicle following the first vehicle; The coordinated control of the multi-vehicle platoon based on the safe driving distance includes at least one of the following: Based on the safe driving distance, a target control speed parameter for the second vehicle is generated, and the second vehicle is controlled to drive in the multi-vehicle queue according to the target control speed parameter; Based on the safe driving distance and the control speed parameters of the third vehicle in the multi-vehicle queue, the target control speed parameters of the second vehicle are generated, and the second vehicle is controlled to drive in the multi-vehicle queue according to the target control speed parameters; the third vehicle is the vehicle behind the second vehicle.

[0011] To achieve the above objectives, a second aspect of this application provides a multi-vehicle cooperative control device, the device comprising: The acquisition module is used to acquire the motion state parameters of the first and second adjacent vehicles in a multi-vehicle queue. A variable time-distance module is used to generate travel time-distance parameters between the first vehicle and the second vehicle based on the motion state parameters; A variable spacing module is used to determine a safe driving distance between the first vehicle and the second vehicle based on the driving time and distance parameters. The collaborative control module is used to perform collaborative control of the multi-vehicle queue based on the safe driving distance.

[0012] To achieve the above objectives, a third aspect of this application provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the multi-vehicle cooperative control method described in the first aspect.

[0013] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the multi-vehicle cooperative control method described in the first aspect.

[0014] To achieve the above objectives, the fifth aspect of this application provides a computer program product comprising a computer program that, when executed by a processor, implements the multi-vehicle cooperative control method provided in the first aspect above.

[0015] The multi-vehicle cooperative control method, device, electronic device, computer-readable storage medium, and computer program product proposed in this application acquire motion state parameters of adjacent first and second vehicles in a multi-vehicle queue; generate travel time and distance parameters between the first and second vehicles based on the motion state parameters; determine a safe travel distance between the first and second vehicles based on the travel time and distance parameters; and perform cooperative control of the multi-vehicle queue based on the safe travel distance.

[0016] Compared to traditional platooning control methods using spacing strategies, this application obtains the motion state parameters of adjacent first and second vehicles in a multi-vehicle platoon. First, it generates a travel time distance parameter between the first and second vehicles based on these motion state parameters. Then, it further determines a safe travel distance between the first and second vehicles based on this travel time distance parameter, and performs collaborative control of the multi-vehicle platoon based on this safe travel distance. Thus, this application implements a variable time interval strategy based on the motion state parameters of adjacent vehicles in a multi-vehicle platoon. Even when the speed of a vehicle in the platoon changes rapidly, a safe travel distance can be determined based on the motion state parameters of that vehicle and its adjacent vehicles. This effectively avoids the problems of platooning oscillation and unstable following caused by the inability of traditional spacing strategies to adjust vehicle spacing in such situations, thereby improving the stability of platoon operation. Attached Figure Description

[0017] Figure 1 A flowchart illustrating the steps of the multi-vehicle cooperative control method provided in this application in some embodiments; Figure 2 for Figure 1 A detailed flowchart of step S102; Figure 3 A flowchart illustrating the steps of the multi-vehicle cooperative control method provided in this application in some other embodiments; Figure 4 for Figure 3 A detailed flowchart of step S301; Figure 5 A flowchart illustrating the steps of the multi-vehicle cooperative control method provided in this application in some other embodiments; Figure 6 The control phase diagram of the spacing control coefficients involved in some embodiments of the multi-vehicle cooperative control method provided in this application; Figure 7 for Figure 1 A detailed flowchart of step S103; Figure 8 for Figure 1 A detailed flowchart of step S104; Figure 9 A schematic diagram of the multi-vehicle cooperative control device provided in this application; Figure 10 A schematic diagram of the hardware structure of the electronic device provided in this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] It should be noted that although functional modules are divided in the device / system schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device / system or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used herein is for descriptive purposes only and is not intended to limit the scope of this application.

[0021] First, the overall concept of the multi-vehicle cooperative control method provided in this application will be explained.

[0022] Currently, artificial intelligence and intelligent transportation technologies are constantly innovating, and intelligent vehicles are a hot topic in the development of these technologies. However, many problems remain unresolved in single-vehicle intelligent driving, such as: inaccurate readings from individual sensors, limited detection range of onboard sensors, blind spots of onboard sensors, high cost of onboard computing processors, and a lack of predictive mechanisms for the behavior of other vehicles.

[0023] In response, multi-vehicle collaborative control technology based on intelligent connectivity has gradually become the mainstream of industry development. This technology can achieve blind spot compensation, all-round information perception, make up for the lack of on-board computing power, and solve the shortcomings of single-vehicle intelligence.

[0024] The core value of multi-vehicle group cooperative control technology lies in improving traffic efficiency and ensuring traffic safety through the cooperation between vehicles. On the one hand, it can increase urban traffic flow, alleviate traffic congestion, and improve traffic efficiency; on the other hand, it can reduce fuel consumption and improve driving stability.

[0025] However, facing issues such as communication delays and external interference, the difficulty and complexity of controlling intelligent vehicle fleets based on multi-vehicle group cooperative control technology also increase, thus bringing new challenges to multi-vehicle cooperative control. Specifically, inherent vehicle spacing strategies and external interference lead to an increase in the cumulative spacing error of intelligent connected vehicle fleets, making it difficult for the fleet to maintain small vehicle spacing and speed consistency.

[0026] Since vehicles within a platoon do not operate in isolation but rather exhibit significant kinematic interactions, ignoring these interactions can lead to inconsistencies between vehicle behavior and traffic flow theory. Therefore, fully considering and addressing these kinematic interactions is a crucial prerequisite for improving the overall performance of platoon control systems. Establishing an effective spacing strategy is one of the core challenges, directly related to traffic safety and road capacity improvement, and is a vital support for the implementation of multi-vehicle group cooperative control technology.

[0027] The study of spacing strategies is crucial for the longitudinal control of a platoon, as it determines the safe following gap between vehicles. Optimizing controller design based on appropriate spacing strategies is key to ensuring high platoon stability. Common spacing strategies include Constant Spacing Policy (CSP), Variable Spacing Policy (VSP), Constant Time Headway Policy (CTHP), and Variable Time Headway Policy (VTHP).

[0028] The fixed spacing strategy is the most commonly used, and the expression is as follows: , For convoy spacing, It represents a constant, expected spacing. However, fixed-spacing strategies also have some limitations and challenges, including low road utilization and difficulty adapting to complex driving conditions. The expression for a variable-spacing strategy is as follows: , This is the expected static distance. Let be the speed of the i-th car in the convoy. It refers to the travel time and distance between vehicles. When the time interval is a fixed constant, the strategy is an equal time interval strategy, i.e., an equal time interval variable spacing strategy. However, when... When the variable is constant, the strategy is a variable time-distance strategy, i.e., a variable time-distance-variable spacing strategy. An investigation of the constant time-distance-variable spacing strategy in truck platoon control revealed that excessive spacing at low speeds reduced road utilization. Furthermore, the constant time-distance-variable spacing strategy performed poorly when the lead vehicle frequently accelerated or decelerated. Adopting a variable time-distance-variable spacing strategy can meet the requirements of information feedback, communication reliability, and real-time performance in platoon control scenarios under fixed distance conditions.

[0029] However, when the acceleration of the lead vehicle changes significantly, leading to rapid changes in vehicle speed, the performance of these traditional strategies often deteriorates. For example, the inability to adjust vehicle spacing in a timely manner may cause platoon swaying, unstable following, and other problems, resulting in poor platoon stability. Therefore, there is still a need to develop more robust and adaptable spacing strategies to effectively handle complex driving conditions and adapt to changes in acceleration.

[0030] To address the aforementioned issues, this application proposes a multi-vehicle cooperative control method, device, electronic equipment, computer-readable storage medium, and computer program product. The aim is to introduce changes in the acceleration and speed of the preceding vehicle during cooperative control of a convoy in mixed traffic flow, based on a multi-input variable time interval strategy. This addresses the instability caused by rapid speed changes in a vehicle within the convoy, thereby improving the stability of convoy operation.

[0031] The multi-vehicle cooperative control method, device, electronic device, computer-readable storage medium, and computer program product proposed in this application acquire motion state parameters of adjacent first and second vehicles in a multi-vehicle queue; generate travel time and distance parameters between the first and second vehicles based on the motion state parameters; determine a safe travel distance between the first and second vehicles based on the travel time and distance parameters; and perform cooperative control of the multi-vehicle queue based on the safe travel distance.

[0032] Compared to traditional platooning control methods using spacing strategies, this application obtains the motion state parameters of adjacent first and second vehicles in a multi-vehicle platoon. First, it generates a travel time distance parameter between the first and second vehicles based on these motion state parameters. Then, it further determines a safe travel distance between the first and second vehicles based on this travel time distance parameter, and performs collaborative control of the multi-vehicle platoon based on this safe travel distance. Thus, this application implements a variable time interval strategy based on the motion state parameters of adjacent vehicles in a multi-vehicle platoon. Even when the speed of a vehicle in the platoon changes rapidly, a safe travel distance can be determined based on the motion state parameters of that vehicle and its adjacent vehicles. This effectively avoids the problems of platooning oscillation and unstable following caused by the inability of traditional spacing strategies to adjust vehicle spacing in such situations, thereby improving the stability of platoon operation.

[0033] Next, the multi-vehicle cooperative control method, device, electronic device, computer-readable storage medium, and computer program product provided in this application will be specifically described through the following embodiments, and firstly, the various detailed embodiments of the multi-vehicle cooperative control method provided in this application will be described in detail.

[0034] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent will be obtained first. Furthermore, the collection, use, and processing of this data will comply with relevant laws, regulations, and standards. In addition, when this application needs to obtain sensitive personal information of users, separate permission or consent from the user will be obtained through pop-ups or redirects to confirmation pages. Only after obtaining the user's separate permission or consent will the necessary user-related data for the normal operation of this application be obtained.

[0035] It should be noted that the multi-vehicle cooperative control method provided in this application relates to the field of fleet control technology. The multi-vehicle cooperative control method provided in this application can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be an in-vehicle terminal, or an electronic device such as a smartphone, tablet, laptop, or desktop computer that is associated with a vehicle and can communicate and interact with the vehicle via a network. The server can be a backend server terminal device of the terminal, which can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms. The software can be an application implementing the multi-vehicle cooperative control method, a computer program, and a storage medium carrying the computer program. It should be understood that, based on different design needs of practical applications, the terminals, servers, and software of the multi-vehicle cooperative control method provided in this application may also be other forms not listed here, and the multi-vehicle cooperative control method provided in this application does not specifically limit these.

[0036] Furthermore, this application can also be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: vehicle terminals, personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, personal computers (PCs), minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via communication networks. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0037] For ease of understanding and explanation, the following text will use the application of the multi-vehicle cooperative control method provided in this application to a terminal device as an example to describe the various specific embodiments of this application in detail. The terminal device can use the multi-vehicle cooperative control method provided in this application to perform closed-loop simulation testing of the vehicle autonomous driving planning algorithm. In some descriptions, the terminal device may be simply referred to as the terminal. The implementation of the multi-vehicle cooperative control method provided in this application by any of the aforementioned entities can refer to the process of applying the multi-vehicle cooperative control method to a terminal device as described below.

[0038] Please refer to Figure 1 , Figure 1 The flowchart illustrates the steps of the multi-vehicle cooperative control method provided in this application in some embodiments. It should be understood that, although... Figure 1 The flowcharts illustrating subsequent steps show the execution order of some method steps. However, based on different design requirements in practical applications, the multi-vehicle cooperative control method provided in this application can, of course, employ a different execution order of method steps than shown in the figures. That is, Figure 1 The order of the steps shown does not constitute a limitation on the execution logic order of the multi-vehicle cooperative control method provided in this application. Any other method based on... Figure 1 Reasonable changes to the sequence of steps shown should be included within the protection scope of the multi-vehicle cooperative control method provided in this application.

[0039] like Figure 1 As shown, in some embodiments, the multi-vehicle cooperative control method provided in this application may include steps S101 to S104 as shown below.

[0040] Step S101: Obtain the motion state parameters of the first and second adjacent vehicles in the multi-vehicle queue.

[0041] It should be noted that motion state parameters can include at least velocity and acceleration.

[0042] When performing a task of coordinated control of a multi-vehicle queue, the terminal device can continuously collect motion state parameters of the first vehicle and the second vehicle that are adjacent to each other in the queue.

[0043] In some embodiments, the terminal device can control each vehicle in a multi-vehicle convoy to autonomously collect its motion state parameters using onboard sensors. For example, the terminal device controls each vehicle to independently collect its speed and acceleration using its own onboard sensors, and then reports the real-time collected speed and acceleration as its own motion state parameters to the terminal device for convoy cooperative control.

[0044] In other embodiments, the terminal device can also collect data through vehicle-to-vehicle, vehicle-to-infrastructure, and vehicle-to-cloud (V2X) communication technologies, and interact with each vehicle in the multi-vehicle queue in real time to obtain the motion state parameters of the adjacent first and second vehicles.

[0045] In other embodiments, the terminal device can also integrate the motion state parameters autonomously collected and reported by each vehicle using onboard sensors and / or acquired through vehicle-to-everything (V2X) collaborative communication via a fusion algorithm to obtain higher accuracy and reliability speed / acceleration information. For example, the terminal device can perform hierarchical fusion processing on the single-vehicle data collected and reported by each vehicle using sensors and the data from neighboring vehicles to obtain the fused motion state parameters for each vehicle. Alternatively, the terminal device can employ deep learning fusion (such as CNN-LSTM) to input the motion state parameters collected and reported by each vehicle using sensors and / or acquired through V2X collaborative communication into a deep learning model pre-trained based on historical data. This deep learning model then adaptively corrects any abnormal data in the input motion state data.

[0046] Step S102: Generate travel time and distance parameters between the first vehicle and the second vehicle based on the motion state parameters.

[0047] After obtaining the motion state parameters of the first vehicle and the second vehicle, the terminal device further generates the travel time and distance parameters between the first vehicle and the second vehicle based on the motion state parameters according to the pre-built multi-input variable time interval strategy.

[0048] In some embodiments, a multi-input variable time interval strategy can be constructed by incorporating the vehicle's acceleration and velocity, in which the travel time distance between vehicles is calculated. The expression is as follows: .

[0049] in, , and It is the spacing control coefficient. Let be the speed of the i-th car in the convoy. Let i be the speed of the (i-1)th car in the convoy. Let be the acceleration of the (i-1)th car in the convoy. Let be the acceleration of the i-th car in the convoy.

[0050] Based on this, the terminal device substitutes the acceleration and velocity of the first vehicle and the acceleration and velocity of the second vehicle into the calculation. The expression can be used to calculate the travel time and distance parameters between the first and second vehicles.

[0051] Step S103: Determine the safe driving distance between the first vehicle and the second vehicle based on the driving time and distance parameters.

[0052] After calculating the travel time and distance parameters between the first vehicle and the second vehicle, the terminal device further determines the safe driving distance between the first vehicle and the second vehicle based on the travel time and distance parameters according to the multi-input variable time interval strategy.

[0053] In some embodiments, the multi-input variable time interval strategy can employ an expression. Calculate the distance between vehicles That is, the terminal device uses the travel time and distance parameters between the first vehicle and the second vehicle. Substituting this expression further... This allows us to calculate the safe driving distance between the first and second vehicles. .

[0054] In some embodiments, the terminal device can perform the above calculations. Expressions and direct substitution Thus, the expression for the multi-input variable time interval strategy is obtained as follows: .

[0055] Based on this, after obtaining the motion state parameters of the first and second vehicles, the terminal device can, according to the multi-input variable time interval strategy, first calculate the speed difference Δv between the first and second vehicles based on their respective speeds in the motion state parameters, and calculate the acceleration difference Δa between the first and second vehicles based on their respective accelerations in the motion state parameters. Then, it can combine this with the expected static distance. The speed of the second vehicle and spacing control coefficient , and The safe driving distance between the first vehicle and the second vehicle is calculated. .

[0056] Step S104: Perform coordinated control of the multi-vehicle queue based on the safe driving distance.

[0057] After determining the safe driving distance between the first vehicle and the second vehicle, the terminal device further controls the driving speed of the second vehicle based on the safe driving distance, thereby realizing coordinated control of the entire multi-vehicle platoon.

[0058] In some embodiments, when using a car-following model to perform cooperative control of a multi-vehicle queue, the terminal device can substitute the safe driving distance between the first vehicle and the second vehicle into the car-following model to calculate the target control speed parameter of the second vehicle, so as to control the second vehicle to drive in the multi-vehicle queue according to the target control speed parameter.

[0059] It should be noted that vehicle following models can include Intelligent Driver Model (IDM), Adaptive Cruise Control (ACC) model, and Cooperative Adaptive Cruise Control (CACC) model. Among them: The expression for the Intelligent Driver Model (IDM) is as follows: .

[0060] in, , Let x and y represent the acceleration and velocity of vehicle n at time t, respectively. Vehicle at time t and vehicles Speed ​​difference; Let n be the distance between the front ends of vehicle n at time t. Minimum safe parking distance; Decelerate for comfort; This refers to the vehicle's maximum acceleration parameter. For automatic flow / driver's desired speed; For safe headway; For the train commander.

[0061] The expression for the Adaptive Cruise Control (ACC) model is as follows: .

[0062] in, , These are the control coefficients for vehicle spacing error and speed difference, respectively. This refers to the expected inter-vehicle time distance parameter for ACC vehicles.

[0063] The expression for the Cooperative Adaptive Cruise Control (CACC) model is as follows: .

[0064] in, For system control step size; For vehicles exist The speed of time; , They represent Time vehicle The difference between the actual and expected vehicle spacing, and the time factor of this difference. The differential term; , These represent the control coefficients for the vehicle spacing error and its differential term, respectively. This represents the desired workshop time interval.

[0065] It should be understood that, based on different design needs in practical applications, in different feasible implementations, the terminal device may of course adopt other vehicle following models not listed here to control the driving speed of the second vehicle based on the safe driving distance between the first and second vehicles, thereby realizing the coordinated control of the entire multi-vehicle queue. The multi-vehicle coordinated control method provided in this application does not limit the specific types of vehicle following models that can be used.

[0066] In this embodiment, when the terminal device performs the task of coordinated control of a multi-vehicle queue, it continuously collects the motion state parameters of adjacent first and second vehicles in the queue. Then, according to a pre-built multi-input variable time interval strategy, the terminal device first generates a travel time distance parameter between the first and second vehicles based on these motion state parameters, and then determines a safe driving distance between them based on this parameter. Finally, the terminal device controls the speed of the second vehicle based on this safe driving distance, thereby achieving coordinated control of the entire multi-vehicle queue.

[0067] Compared to traditional platooning control methods using spacing strategies, this application obtains the motion state parameters of adjacent first and second vehicles in a multi-vehicle platoon. First, it generates a travel time distance parameter between the first and second vehicles based on these motion state parameters. Then, it further determines a safe travel distance between the first and second vehicles based on this travel time distance parameter, and performs collaborative control of the multi-vehicle platoon based on this safe travel distance. Thus, this application implements a variable time interval strategy based on the motion state parameters of adjacent vehicles in a multi-vehicle platoon. Even when the speed of a vehicle in the platoon changes rapidly, a safe travel distance can be determined based on the motion state parameters of that vehicle and its adjacent vehicles. This effectively avoids the problems of platooning oscillation and unstable following caused by the inability of traditional spacing strategies to adjust vehicle spacing in such situations, thereby improving the stability of platoon operation.

[0068] In some embodiments, the motion state parameters include: a first speed and a first acceleration of a first vehicle, and a second speed and a second acceleration of a second vehicle; the first vehicle is the vehicle in front of the second vehicle.

[0069] Please refer to Figure 2 , Figure 2 for Figure 1 A detailed flowchart of step S102.

[0070] like Figure 2 As shown, in some embodiments, step S102 above: generating the travel time and distance parameters between the first vehicle and the second vehicle based on the motion state parameters may include steps S201 to S203 as shown below.

[0071] Step S201: Divide the speed difference between the first speed and the second speed by the second speed to obtain the speed deviation parameter between the first vehicle and the second vehicle.

[0072] When the terminal device generates the travel time distance parameters between the first vehicle and the second vehicle based on the acquired motion state parameters, if the motion state parameters of the first vehicle are its first speed and first acceleration, and the motion state parameters of the second vehicle following the first vehicle are its second speed and second acceleration, the terminal device can first calculate the speed difference between the first speed and the second speed, and then divide this speed difference by the second speed to calculate the speed deviation parameter between the first vehicle and the second vehicle. For example, the terminal device can use the formula: , will the first speed With the second speed The speed difference between the two divided by the second speed The speed deviation parameters between the first vehicle and the second vehicle are obtained.

[0073] Step S202: Normalize the acceleration difference between the first acceleration and the second acceleration based on the second speed to obtain the acceleration matching parameters between the first vehicle and the second vehicle.

[0074] When the terminal device generates the travel time distance parameters between the first vehicle and the second vehicle based on the acquired motion state parameters, if the motion state parameters include the first speed and first acceleration of the first vehicle, and the second speed and second acceleration of the second vehicle, and the first vehicle is the vehicle in front of the second vehicle, the terminal device can also calculate the acceleration difference between the first acceleration and the second acceleration while calculating the speed deviation parameter between the first vehicle and the second vehicle, and normalize the acceleration difference based on the second speed to obtain the acceleration matching parameters between the first vehicle and the second vehicle. For example, the terminal device can use the formula: ( Based on the second speed For the first acceleration With the second acceleration The acceleration difference between the two vehicles is normalized to obtain the acceleration matching parameters between the first vehicle and the second vehicle.

[0075] Step S203: The speed deviation parameter and the acceleration matching parameter are fused to obtain the travel time and distance parameter between the first vehicle and the second vehicle.

[0076] After calculating the speed deviation parameter between the first vehicle and the second vehicle, as well as the acceleration matching parameter between the first vehicle and the second vehicle, the terminal device performs fusion processing on the speed deviation parameter and the acceleration matching parameter according to a pre-built multi-input variable time interval strategy, thereby calculating the travel time distance parameter between the first vehicle and the second vehicle.

[0077] Please refer to Figure 3 , Figure 3 The flowcharts of the multi-vehicle cooperative control method provided in this application are shown in some other embodiments.

[0078] like Figure 3 As shown, in some embodiments, the multi-vehicle cooperative control method provided in this application may further include step S301 as shown below.

[0079] Step S301: Obtain the spacing control coefficient for coordinated control of the multi-vehicle queue.

[0080] When the terminal device uses any of the above-mentioned car-following models to perform cooperative control of a multi-vehicle queue, it obtains the spacing control coefficients for cooperative control of the multi-vehicle queue from the fused expression of the car-following model and the multi-input variable time interval strategy. For example, the terminal device can substitute the expression of the multi-input variable time interval strategy into the expression of the CACC model to obtain the fused expression: .

[0081] in, The target output acceleration at time t Vehicle spacing control parameters; The vehicle length is uniformly set at 5 meters. This is the expected static distance. This refers to the expected inter-vehicle time distance parameters for CACC vehicles. Speed ​​difference control parameters; Acceleration feedback parameters; Δv is the velocity difference between vehicle n and n-1; Δa is the acceleration difference between vehicle n and n-1.

[0082] In this way, the terminal device can obtain at least the spacing control coefficient for coordinated control of multiple vehicle queues from the fused expression. , and .

[0083] In this case, the step of "fusing the velocity deviation parameter and the acceleration matching parameter" in step S203 above can include the following steps: The velocity deviation parameter and the acceleration matching parameter are fused based on the spacing control coefficient.

[0084] When the terminal device performs fusion processing on the velocity deviation parameter and acceleration matching parameter according to the multi-input variable time interval strategy, it can perform fusion processing on the velocity deviation parameter and acceleration matching parameter based on the spacing control coefficient, provided that the spacing control coefficient is obtained. For example, the terminal device can use the following formula to further fuse the velocity deviation parameter and acceleration matching parameter based on the spacing control coefficient. , and The speed deviation parameters and acceleration matching parameters between the first vehicle and the second vehicle are fused to calculate the travel time and distance parameters between the first vehicle and the second vehicle. : .

[0085] in, , and It is the spacing control coefficient. The second speed, The fastest in the team, For the first acceleration, For the second acceleration, Indicates the speed deviation parameter, ( This represents the acceleration matching parameters.

[0086] Please refer to Figure 4 , Figure 4for Figure 3 A detailed flowchart of step S301.

[0087] like Figure 4 As shown, in some embodiments, step S301 above: obtaining the spacing control coefficient for coordinated control of the multi-vehicle queue may include steps S401 and S402 as shown below.

[0088] Step S401: Obtain the range of control coefficients corresponding to the preset multi-input variable time interval strategy; the multi-input variable time interval strategy is used to indicate the processing of the motion state parameters of the first and second adjacent vehicles in the multi-vehicle queue to obtain the safe driving distance between the first vehicle and the second vehicle.

[0089] When the terminal device obtains the spacing control coefficients for coordinated control of multiple vehicle queues, it can also first obtain the range of control coefficients corresponding to the multi-input variable time interval strategy mentioned above.

[0090] It should be noted that the multi-input variable time interval strategy is a strategy in which the aforementioned instruction terminal device first calculates the travel time and distance parameters based on the motion state parameters of the first vehicle and the second vehicle, and then further calculates the safe travel distance based on the travel time and distance parameters. The expression of the multi-input variable time interval strategy is as follows: .

[0091] in, , and These are the spacing control coefficients. The terminal device can perform a stability analysis of the spacing strategy beforehand using this multi-input variable time interval strategy, thereby determining the selection range of each of these spacing control coefficients, i.e., the control coefficient selection range. For example, the spacing control coefficients determined by the terminal device after performing a stability analysis of the multi-input variable time interval strategy. , and Their respective value ranges can be , ≥0.6、 >3.24.

[0092] Step S402: Determine the spacing control coefficient for coordinated control of the multi-vehicle queue within the range of the selected control coefficient.

[0093] After obtaining the control coefficient selection range corresponding to the multi-input variable time interval strategy, the terminal device can select the spacing control coefficient for coordinated control of the multi-vehicle queue within this range. Where there are multiple spacing control coefficients, the terminal device selects multiple spacing control coefficients that meet the corresponding value range conditions, based on the value range of each spacing control coefficient within the control coefficient selection range. For example, in the spacing control coefficient... , and Their respective value ranges are , ≥0.6、 When the value is greater than 3.24, the terminal device can select the spacing control coefficient. =0.6、 =3.25 and =1.

[0094] In some embodiments, the range of control coefficients includes the target range of spacing control coefficients for cooperative adaptive cruise vehicles.

[0095] When performing stability analysis on the multi-input variable time interval strategy, the terminal device can use a vehicle following model to control any cooperative adaptive cruise control vehicle equipped with the Cooperative Adaptive Cruise Control (CACC). Based on the multi-input variable time interval strategy, it can calculate the safe driving distance between the cooperative adaptive cruise vehicle and the vehicle in front, thereby analyzing the conditions that the cooperative adaptive cruise vehicle needs to meet to achieve stability. This allows for the calculation of the target range of the distance control coefficient for the cooperative adaptive cruise vehicle, and the target range is used as the selection range of the control coefficient corresponding to the multi-input variable time interval strategy.

[0096] In some embodiments, the cooperative adaptive cruise vehicle includes vehicles in the multi-vehicle convoy.

[0097] When performing stability analysis on the multi-input variable time interval strategy, the terminal equipment can also use a vehicle following model to control any vehicle equipped with the Cooperative Adaptive Cruise Control (CACC) system in the multi-vehicle queue, thereby analyzing the conditions required for the vehicle to achieve stability and calculating the target range of the vehicle's spacing control coefficient.

[0098] Please refer to Figure 5 , Figure 5 The flowcharts of the multi-vehicle cooperative control method provided in this application are shown in some other embodiments.

[0099] like Figure 5As shown, in some embodiments, the multi-vehicle cooperative control method provided in this application may further include steps S501 and S503 as shown below.

[0100] Step S501: Determine the control speed parameters of the cooperative adaptive cruise vehicle based on the multi-input variable time interval strategy.

[0101] It should be noted that the control speed parameter of the vehicle in cooperative adaptive cruise can be the target output acceleration of the vehicle at time t.

[0102] When performing stability analysis on a multi-input variable time interval strategy, the terminal device determines the control speed parameters of the cooperative adaptive cruise vehicle based on this strategy during the control process using a vehicle car-following model. That is, the terminal device can calculate the control speed parameters of the cooperative adaptive cruise vehicle in a multi-vehicle queue based on the fused expression, after combining the expressions of the vehicle car-following model and the multi-input variable time interval strategy. For example, the control speed parameters of the cooperative adaptive cruise vehicle... The result can be calculated using the fusion formula obtained by substituting the expression of the multi-input variable time interval strategy into the expression of the vehicle car-following model CACC.

[0103] .

[0104] Step S502: Determine the stability conditions of the cooperative adaptive cruise vehicle based on the control speed parameters and the speed disturbance transfer function of the cooperative adaptive cruise vehicle.

[0105] It should be noted that the stability conditions for a vehicle in cooperative adaptive cruise control can be the conditions that the vehicle must meet to achieve stability.

[0106] When performing stability analysis on the multi-input variable time interval strategy, the terminal device, after determining the control speed parameters of the cooperative adaptive cruise vehicle based on the multi-input variable time interval strategy, further combines the control speed parameters and the speed disturbance transfer function of the cooperative adaptive cruise vehicle to analyze the stability conditions of the cooperative adaptive cruise vehicle.

[0107] In some embodiments, when analyzing the stability conditions of the cooperative adaptive cruise vehicle by combining the control speed parameters and the speed disturbance transfer function of the cooperative adaptive cruise vehicle, the terminal device can first perform differential calculations on the expression for calculating the control speed parameters to obtain the following parameters: .

[0108] in, Indicates acceleration right Sensitivity Indicates acceleration Sensitivity to workshop time intervals Indicates acceleration right Sensitivity.

[0109] Then, the terminal device combines the parameters obtained from differential calculations with the speed disturbance transfer function of the cooperative adaptive cruise vehicle to analyze the stability conditions of the cooperative adaptive cruise vehicle.

[0110] In some embodiments, the speed disturbance transfer function of the cooperative adaptive cruise vehicle is represented during propagation as a continuous product of the speed disturbance transfer functions of each vehicle in the multi-vehicle queue. For example, assuming the total number of vehicles in the traffic flow (multi-vehicle queue) is N, then the speed disturbance transfer function of the entire vehicle queue is... This refers to the cumulative effect of the velocity perturbation transfer function of these individuals. For example: .

[0111] In this case, the terminal device can incorporate the velocity disturbance transfer function. The following criteria are used to determine the stability of traffic flow for cooperative adaptive cruise vehicles, based on the continuous product of the factors, i.e., to analyze the stability conditions of the cooperative adaptive cruise vehicle.

[0112] .

[0113] in, The Laplace transform form of G(s), that is, the frequency domain obtained by performing a Laplace transform on the transfer function, is obtained through... In the frequency domain, the maximum amplitude of the transfer function is expressed as follows: express.

[0114] If the equality sign in the above criteria holds, then the multi-vehicle platoon system can be considered to have reached a critical stable state. Furthermore, when the control parameters of all vehicles in the platoon are consistent, the corresponding formula can be further derived as follows: .

[0115] By further simplifying the above formula, we can obtain: .

[0116] Thus, the conditions required for a vehicle to achieve stability in cooperative adaptive cruise control can be obtained by substituting the parameters obtained from the differential calculations above into the simplified formula: .

[0117] According to the formula characterizing the stability condition of cooperative adaptive cruise vehicles, the terminal equipment needs to know the control parameters to calculate the stability of traffic flow for cooperative adaptive cruise vehicles. , , , and Among them, control parameters and Confirmed.

[0118] Step S503: Calculate the target range of the spacing control coefficient of the cooperative adaptive cruise vehicle based on the stability conditions.

[0119] After determining the stability conditions of the cooperative adaptive cruise vehicle, the terminal device further calculates the target range of the spacing control coefficient of the cooperative adaptive cruise vehicle based on the stability conditions.

[0120] Please refer to Figure 6 , Figure 6 The control phase diagram of the spacing control coefficients involved in some embodiments of the multi-vehicle cooperative control method provided in this application.

[0121] In some embodiments, the terminal device can plot the stability of the vehicle traffic flow in the cooperative adaptive cruise system with respect to... , and The control phase diagram for these three spacing control coefficients is as follows: Figure 6 As shown. From the formula characterizing the stability condition of a vehicle in cooperative adaptive cruise control, it can be determined that when the vehicle in cooperative adaptive cruise control is in a stable state... The range of values ​​is ,exist Figure 6 middle, and The value range is the stable region, and the hyperbola represents the critical value. The stable regions on the left and right represent the range in which the vehicle is in a stable state during cooperative adaptive cruise control; while the region in the middle indicates that the vehicle is in an unstable state.

[0122] Furthermore, according to the capacity analysis of the spacing control strategy, the maximum capacity of heterogeneous traffic flow always increases with... It gradually increases with the increase, and with The decrease in the value makes it more significant; therefore, the terminal device can select... The minimum value is 0.6, then The value should be greater than 3.24. That is, ≥0.6、 >3.24.

[0123] In this embodiment, the travel time distance between vehicles is introduced by incorporating the acceleration and speed changes of the vehicle in front of the terminal device, thereby constructing a multi-input variable time interval strategy for coordinated control of a multi-vehicle platoon. This strategy is then substituted into a vehicle car-following model for spacing strategy stability analysis to determine the appropriate range for spacing control coefficients. Thus, when performing coordinated control of a multi-vehicle platoon, the terminal device can select spacing control coefficients based on this range. These coefficients are then used to fuse speed deviation parameters and acceleration matching parameters between adjacent vehicles in the platoon to obtain travel time distance parameters. These parameters are then used to determine a safe travel distance for coordinated platoon control. Furthermore, by substituting the multi-input variable time interval strategy into the vehicle car-following model for spacing strategy stability analysis to determine the appropriate range for spacing control coefficients, the generalization performance of the multi-input variable time interval strategy can be improved.

[0124] In some embodiments, the second vehicle is a vehicle following the first vehicle.

[0125] Please refer to Figure 7 , Figure 7 for Figure 1 A detailed flowchart of step S103.

[0126] like Figure 7 As shown, in some embodiments, step S103 above: determining the safe driving distance between the first vehicle and the second vehicle based on the driving time and distance parameters may include steps S701 and S702 as shown below.

[0127] Step S701: Multiply the travel time distance parameter by the second speed of the second vehicle in the motion state parameters to obtain the product of the travel time distance parameter and the second speed.

[0128] Step S702: Add the expected static distance to the product to obtain the safe driving distance between the first vehicle and the second vehicle.

[0129] When determining the safe driving distance between the first and second vehicles based on the travel time-distance parameter between the first and second vehicles according to the multi-input variable time interval strategy, the terminal device can first multiply the travel time-distance parameter by the second speed of the second vehicle from the pre-acquired motion state parameters to obtain the product of the travel time-distance parameter and the second speed. Then, the terminal device further adds the expected static distance under the multi-input variable time interval strategy to the calculated product of the travel time-distance parameter and the second speed to obtain the safe driving distance between the first and second vehicles.

[0130] For example, when the terminal device determines the safe driving distance between the first vehicle and the second vehicle based on the driving time distance parameter between the first vehicle and the second vehicle according to the multi-input variable time interval strategy, it can use the expression of the VSP control strategy. First, set the travel time and distance parameters between the first and second vehicles. The second speed of the second vehicle Multiply, and then add the expected static distance to the calculated product. This allows for the calculation of the safe driving distance between the first and second vehicles. .

[0131] Please refer to Figure 8 , Figure 8 for Figure 1 A detailed flowchart of step S104.

[0132] like Figure 8 As shown, in some embodiments, when the second vehicle is the vehicle behind the first vehicle, the above step S104: performing coordinated control of the multi-vehicle queue based on the safe driving distance may include at least one of the following steps S801 and S802.

[0133] Step S801: Generate the target control speed parameters of the second vehicle based on the safe driving distance, and control the second vehicle to drive in the multi-vehicle queue according to the target control speed parameters.

[0134] When the terminal device controls the speed of the second vehicle based on the safe driving distance between the first and second vehicles, if the second vehicle is the last vehicle in a multi-vehicle queue, the terminal device can directly generate the target control speed parameters of the second vehicle based on the safe driving distance, and then control the second vehicle to drive in the multi-vehicle queue according to the target control speed parameters, thereby achieving stable collaborative control of the entire multi-vehicle queue including the second vehicle.

[0135] In some embodiments, the terminal device may employ the above-described fused expression: The target control speed parameters of the second vehicle are calculated. And control the second vehicle according to the instructions. Driving.

[0136] Step S802: Based on the safe driving distance and the control speed parameters of the third vehicle in the multi-vehicle queue, generate the target control speed parameters of the second vehicle, and control the second vehicle to drive in the multi-vehicle queue according to the target control speed parameters; the third vehicle is the vehicle behind the second vehicle.

[0137] When the terminal device controls the speed of the second vehicle based on the safe driving distance between the first and second vehicles, if the second vehicle is not the last vehicle in the multi-vehicle queue, that is, if there is a third vehicle behind the second vehicle, the terminal device can introduce the control speed parameter of the third vehicle as the speed feedback of the following vehicle. By combining the safe driving distance and the control speed parameter of the third vehicle, the target control speed parameter of the second vehicle can be calculated. Then, the second vehicle is controlled to drive in the multi-vehicle queue according to the target control speed parameter, thereby achieving stable collaborative control of the entire multi-vehicle queue.

[0138] In this embodiment, the target control speed parameters of the second vehicle are calculated using different methods depending on whether the second vehicle is the last vehicle in a multi-vehicle platoon, through the terminal device. This avoids situations where following vehicles need to frequently adjust their speeds due to sudden acceleration / deceleration of non-last vehicles during the coordinated control of a multi-vehicle platoon, thereby further reducing instability such as fluctuations in the multi-vehicle platoon.

[0139] Please refer to Figure 9 This application also provides a multi-vehicle cooperative control device, which can realize the above-mentioned multi-vehicle cooperative control method.

[0140] like Figure 9 As shown, the multi-vehicle cooperative control device provided in this application may include: The acquisition module is used to acquire the motion state parameters of the first and second adjacent vehicles in a multi-vehicle queue. A variable time-distance module is used to generate travel time-distance parameters between the first vehicle and the second vehicle based on the motion state parameters; A variable spacing module is used to determine a safe driving distance between the first vehicle and the second vehicle based on the driving time and distance parameters. The collaborative control module is used to perform collaborative control of the multi-vehicle queue based on the safe driving distance.

[0141] In some embodiments, the motion state parameters include: a first speed and a first acceleration of a first vehicle, and a second speed and a second acceleration of a second vehicle; the first vehicle is the vehicle in front of the second vehicle; The variable time-distance module is further configured to divide the speed difference between the first speed and the second speed by the second speed to obtain a speed deviation parameter between the first vehicle and the second vehicle; normalize the acceleration difference between the first acceleration and the second acceleration based on the second speed to obtain an acceleration matching parameter between the first vehicle and the second vehicle; and fuse the speed deviation parameter and the acceleration matching parameter to obtain a travel time-distance parameter between the first vehicle and the second vehicle.

[0142] In some embodiments, the acquisition module is further configured to acquire the spacing control coefficient for coordinated control of the multi-vehicle queue; The variable time-distance module is also used to perform fusion processing on the velocity deviation parameter and the acceleration matching parameter based on the spacing control coefficient.

[0143] In some embodiments, the acquisition module is further configured to acquire the range of control coefficients corresponding to a preset multi-input variable time interval strategy; the multi-input variable time interval strategy is configured to instruct the processing of the motion state parameters of adjacent first and second vehicles in a multi-vehicle queue to obtain a safe driving distance between the first vehicle and the second vehicle; and to determine the spacing control coefficient for coordinated control of the multi-vehicle queue within the range of the control coefficients.

[0144] In some embodiments, the range of control coefficient selection includes the target range of spacing control coefficients for cooperative adaptive cruise vehicles, and the cooperative adaptive cruise vehicles include vehicles in the multi-vehicle platoon. The multi-vehicle cooperative control device provided in this application may further include: The strategy stability analysis module is used to determine the control speed parameters of the cooperative adaptive cruise vehicle based on the multi-input variable time interval strategy; determine the stability conditions of the cooperative adaptive cruise vehicle based on the control speed parameters and the speed disturbance transfer function of the cooperative adaptive cruise vehicle; and calculate the target range of the spacing control coefficient of the cooperative adaptive cruise vehicle based on the stability conditions.

[0145] In some embodiments, the second vehicle is a vehicle following the first vehicle; The variable spacing module is further configured to multiply the travel time distance parameter by the second speed of the second vehicle in the motion state parameters to obtain the product of the travel time distance parameter and the second speed; and to add the expected static distance to the product to obtain the safe travel distance between the first vehicle and the second vehicle.

[0146] In some embodiments, the second vehicle is a vehicle following the first vehicle; The collaborative control module is further configured to generate target control speed parameters for the second vehicle based on the safe driving distance, and control the second vehicle to drive in the multi-vehicle queue according to the target control speed parameters; and to generate target control speed parameters for the second vehicle based on the safe driving distance and the control speed parameters of the third vehicle in the multi-vehicle queue, and control the second vehicle to drive in the multi-vehicle queue according to the target control speed parameters; wherein the third vehicle is the vehicle behind the second vehicle.

[0147] It should be noted that the specific implementation of the multi-vehicle cooperative control device provided in this application is basically the same as the specific implementation of the multi-vehicle cooperative control method described above, and will not be repeated here.

[0148] Please see Figure 10 This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-mentioned multi-vehicle cooperative control method.

[0149] In some embodiments, the electronic device may be any smart terminal such as an in-vehicle terminal, an in-vehicle hardware platform (e.g., an in-vehicle computer), a tablet computer, a smartphone, or a wearable device; or, the electronic device may be a vehicle including a memory and a processor.

[0150] like Figure 10 As shown, the electronic device provided in this application may include: The processor 1001 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to achieve the technical solution provided in this application. The memory 1002 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 1002 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1002 and is called and executed by the processor 1001 to execute the multi-vehicle cooperative control method of this application. Input / output interface 1003 is used to implement information input and output; The communication interface 1004 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 1005 transmits information between various components of the device (e.g., processor 1001, memory 1002, input / output interface 1003, and communication interface 1004); The processor 1001, memory 1002, input / output interface 1003 and communication interface 1004 are connected to each other within the device via bus 1005.

[0151] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described multi-vehicle cooperative control method.

[0152] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0153] This application also provides a computer program product, including a computer program, the steps of which are implemented when the computer program is executed by a processor, and are basically the same as the specific embodiments of the multi-vehicle cooperative control method described above, and will not be repeated here.

[0154] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of this application, and do not constitute a limitation on the technical solutions provided in this application. Those skilled in the art will know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0155] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0156] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0157] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0158] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0159] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0160] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0161] The units described above 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 network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0162] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0163] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple 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 of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0164] The preferred embodiments of this application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and spirit of this application shall be within the scope of the claims.

Claims

1. A multi-vehicle cooperative control method, characterized in that, The method includes: Obtain the motion state parameters of the first and second adjacent vehicles in a multi-vehicle queue; Based on the motion state parameters, the travel time and distance parameters between the first vehicle and the second vehicle are generated; The safe driving distance between the first vehicle and the second vehicle is determined based on the driving time and distance parameters. The multi-vehicle queue is controlled collaboratively based on the safe driving distance.

2. The method according to claim 1, characterized in that, The motion state parameters include: the first speed and first acceleration of the first vehicle, and the second speed and second acceleration of the second vehicle; the first vehicle is the vehicle in front of the second vehicle; The step of generating the travel time and distance parameters between the first vehicle and the second vehicle based on the motion state parameters includes: Divide the speed difference between the first speed and the second speed by the second speed to obtain the speed deviation parameter between the first vehicle and the second vehicle. The acceleration difference between the first acceleration and the second acceleration is normalized based on the second speed to obtain the acceleration matching parameters between the first vehicle and the second vehicle; The speed deviation parameter and the acceleration matching parameter are fused to obtain the travel time and distance parameter between the first vehicle and the second vehicle.

3. The method according to claim 2, characterized in that, The method further includes: Obtain the spacing control coefficient for coordinated control of the multi-vehicle queue; The process of fusing the velocity deviation parameter and the acceleration matching parameter includes: The velocity deviation parameter and the acceleration matching parameter are fused based on the spacing control coefficient.

4. The method according to claim 3, characterized in that, The step of obtaining the spacing control coefficient for coordinated control of the multi-vehicle queue includes: Obtain the range of control coefficients corresponding to the preset multi-input variable time interval strategy; the multi-input variable time interval strategy is used to indicate the processing of the motion state parameters of the first and second adjacent vehicles in the multi-vehicle queue, so as to obtain the safe driving distance between the first vehicle and the second vehicle. Within the range of the selected control coefficients, the spacing control coefficients for coordinated control of the multi-vehicle queue are determined.

5. The method according to claim 4, characterized in that, The range of control coefficients includes the target range of spacing control coefficients for the cooperative adaptive cruise vehicles, and the cooperative adaptive cruise vehicles include the vehicles in the multi-vehicle platoon. The method further includes: The control speed parameters of the cooperative adaptive cruise vehicle are determined based on the multi-input variable time interval strategy. Based on the control speed parameters and the speed disturbance transfer function of the cooperative adaptive cruise vehicle, the stability conditions of the cooperative adaptive cruise vehicle are determined. The target range of the spacing control coefficient for the cooperative adaptive cruise vehicle is calculated based on the stability conditions.

6. The method according to claim 1, characterized in that, The second vehicle is the vehicle behind the first vehicle; Determining the safe driving distance between the first vehicle and the second vehicle based on the driving time and distance parameters includes: Multiply the travel time distance parameter by the second speed of the second vehicle in the motion state parameters to obtain the product of the travel time distance parameter and the second speed; The expected static distance is added to the product to obtain the safe driving distance between the first vehicle and the second vehicle.

7. The method according to any one of claims 1 to 6, characterized in that, The second vehicle is the vehicle behind the first vehicle; The coordinated control of the multi-vehicle platoon based on the safe driving distance includes at least one of the following: Based on the safe driving distance, a target control speed parameter for the second vehicle is generated, and the second vehicle is controlled to drive in the multi-vehicle queue according to the target control speed parameter; Based on the safe driving distance and the control speed parameters of the third vehicle in the multi-vehicle queue, the target control speed parameters of the second vehicle are generated, and the second vehicle is controlled to drive in the multi-vehicle queue according to the target control speed parameters; the third vehicle is the vehicle behind the second vehicle.

8. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the multi-vehicle cooperative control method according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the multi-vehicle cooperative control method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the multi-vehicle cooperative control method as described in any one of claims 1 to 7.

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