Method for optimizing acceleration and transmission data of a platooning fleet for fuel economy

Abstract

The application relates to the technical field of connected vehicle platoon control, and provides a connected vehicle platoon acceleration and transmission data optimization method for guaranteeing fuel economy, and the specific steps comprise the following steps: inputting initial states, respectively initial acceleration a i (0), initial speed v i (0), and initial position s i (0); a follow-up control unit of a follow-up vehicle controls the acceleration of the follow-up vehicle by using a control protocol a j (t) and tracks the states of a head vehicle and a front vehicle; vehicle platoon speed information v i (t) is obtained from a vehicle kinematics equation; optimal acceleration control is obtained from a vehicle platoon fuel consumption minimization target; the distance between a platoon vehicle and infrastructure is calculated; and the data transmission amount of time t is obtained from a communication reliability maximization target. The method of the application jointly optimizes the acceleration and transmission data on the basis of guaranteeing fuel economy.

Description

Technical Field

[0001] This application relates to the field of connected vehicle platoon control technology, and in particular to a method for optimizing the acceleration and data transmission of connected vehicle platoons to ensure fuel economy. Background Technology

[0002] The statements in this section are merely background information related to this application and do not necessarily constitute prior art.

[0003] Vehicle-to-everything (VICS) systems are key enablers of Intelligent Transportation Systems (ITS), smart cities, and the Internet of Things (IoT). To realize the significant benefits of VICS, vehicles must be equipped with sensors, data storage, and the ability to communicate with other vehicles and roadside infrastructure. By using vehicle-to-everything (V2X) communication, the safety of connected vehicles can be improved, and headway can be reduced.

[0004] However, with the rapid development of autonomous driving technology, many computationally intensive in-vehicle tasks, such as infotainment, video streaming, traffic condition updates, high-definition map downloads, and traffic management applications, will generate an explosive growth in data, posing new challenges to VICS (Vehicle Information Systems). As vehicle computing tasks flourish, providing high computing power becomes increasingly critical for VICS, and all these tasks should be computed efficiently and reliably. Given the complexity of vehicle control and the existence of unreliable vehicle-to-vehicle wireless communication, the safety of autonomous driving technology faces significant challenges. Against this backdrop, cloud computing and mobile edge computing technologies have emerged, offering the advantage of expanding vehicle computing power by allocating resources from a shared pool and serving data-driven applications.

[0005] Furthermore, vehicle platooning is one use case for autonomous driving technology, representing a highly efficient collaborative operation mode for connected vehicles. By incorporating advanced technologies such as V2X communication, perception, and control, connected vehicles can travel with smaller headrooms, and cooperation within a vehicle platoon is crucial for interference management and enhanced communication reliability. Therefore, vehicle platooning has the potential to increase traffic capacity, ensure safety, and reduce fuel consumption. V2X and collaborative computing are key technologies supporting the implementation of vehicle platooning applications, enabling dynamic interaction of real-time information across all aspects, transforming passive safety into active safety, and promoting collaborative traffic management at the system level. Consequently, connected vehicle platooning has attracted increasing research interest.

[0006] In recent years, the steadily growing automotive industry has boosted economic development and made our daily lives more convenient, but transportation systems are facing increasing challenges. Most countries are struggling with traffic congestion, increased fuel consumption, air pollution, and serious accidents. Especially against the backdrop of the energy crisis, reducing vehicle fuel consumption has become a major challenge.

[0007] To ensure fuel economy and the safety of platooning, it is necessary to jointly optimize the acceleration and data transmission of connected vehicle platoons. Summary of the Invention

[0008] To address the aforementioned issues, this application proposes a method for optimizing the acceleration and transmission data of connected vehicle fleets while ensuring fuel economy. This method jointly optimizes the acceleration and transmission data of the fleet while maintaining fuel economy.

[0009] This application provides a method for optimizing the acceleration and data transmission of connected vehicle fleets to ensure fuel economy. Based on an optimization system consisting of a V2V communication unit, a computing unit, a V2I communication unit, a following control unit, and infrastructure, the specific method includes the following steps:

[0010] Step S1: Each vehicle in the connected vehicle platoon system inputs its initial state, which is the initial acceleration a. i (0), initial velocity v i (0), Initial position s i (0), i = 1, 2, ..., N, where N is the number of vehicles in the connected vehicle queue;

[0011] Step S2: All vehicles in the connected vehicle platoon communicate via V2V communication units, exchanging speed and location information. The following vehicle's control unit uses control protocol a. j (t) controls its own acceleration and thereby tracks the states of the lead vehicle and the vehicle in front, where a j (t)=-(β1(s j (t)-s j-1 (t)+l0)+β2(v j (t)-v j-1 (t))-(β1(s j (t)-s1(t)+(j-1)×l0)+β2(v j (t)-v1(t))), j=2、3、...、N, β1、β2 are adjustable parameters, l0 is the desired vehicle spacing;

[0012] Step S3: The computing units of all vehicles in the connected vehicle queue communicate via control protocol and vehicle kinematic equations v i (t+1)=v i (t)+τa i (t) calculates its own velocity information, where τ is the unit time length;

[0013] Step S4: The computing unit of the lead vehicle in the connected vehicle queue aims to minimize fuel consumption.

[0014]

[0015] and acceleration constraints The optimal acceleration control is then obtained. In the formula, k1, k2, k3, and k4 are parameters related to fuel consumption. These are the lower and upper limits of acceleration for the lead vehicle, respectively.

[0016] Step S5: Optimal acceleration control of the lead vehicle by all following control units in the connected vehicle platoon. Tracking is performed, and all the computing units following the vehicle are based on optimal acceleration control. Find the optimal acceleration control for yourself

[0017] From the vehicle kinematic equations

[0018] v i (t+1)=v i (t)+τa i (t), s i (t+1)=s i (t)+τv i (t)+τ 2 a i (t) / 2 yields the optimal speed for all vehicles in the queue. and optimal position information;

[0019] The location of the roadside infrastructure is fixed at s0, and the distance between it and the centerline of the road where the connected vehicle queue is located is L. The computing units of all vehicles in the connected vehicle queue calculate the distance between each vehicle and the infrastructure.

[0020] Step S6: Communication between all vehicles in the connected vehicle queue and the roadside infrastructure is provided by a cellular network, with a channel capacity of [missing information].

[0021] The probability of successful data transmission between a single vehicle and roadside infrastructure at time t is:

[0022]

[0023] The probability of successful data transmission between the connected vehicle platoon and roadside infrastructure at time t is:

[0024]

[0025] The probability of successful data transmission between connected vehicle platoons and roadside infrastructure over the entire time span is

[0026]

[0027] The computing units of all vehicles in the connected vehicle platoon aim to maximize the reliability of V2I communication.

[0028]

[0029] and constraints The optimal data transmission scheme is obtained by dividing the transmitted data volume D into its components.

[0030] To To solve this problem, the augmented Lagrange multiplier method is used, introducing an auxiliary Lagrange function.

[0031] And KKT conditions,

[0032] get

[0033] In the formula, B is the available bandwidth, N is the number of vehicles in the connected vehicle queue, M is the number of other vehicles competing with the vehicle queue for the V2I channel, and P... T Where N is the data transmission power, N0 is the data transmission noise, and d i (t) represents the vehicle data transmission scheme. Let λ be the channel gain, δ be the path loss constant, T be the total time length, D be the amount of data transmitted, and λ be the path loss constant. t ω represents the multiplier.

[0034] Preferably, in step S2, the adjustable parameters β1 and β2 satisfy β1+β2=1, β1∈[0,0.7);

[0035] The desired vehicle spacing l0 is 3 to 10 meters.

[0036] Preferably, in step S3, the unit time length τ is 0.005 to 0.015 s.

[0037] Preferably, in step S4, the parameters k1, k2, k3, and k4 related to fuel consumption are set fixed values, k1 = 0.007, k2 = 0.0052, k3 = 1.09, and k4 = 8;

[0038] Lower and upper limits of acceleration of the lead car Values ​​range from -5 to -2 m / s 2 , Values ​​range from 3 to 5 m / s 2 .

[0039] Preferably, in step S5, the location s0 of the roadside infrastructure is any value, and the distance L between the roadside infrastructure and the centerline of the road where the connected queue is located is 5 to 100m.

[0040] Preferably, in step S6, the number of vehicles N in the connected vehicle queue is 3 to 8, the number of other vehicles M competing with the vehicle queue for the V2I channel is 0 to 100, and the data transmission power P... T The data transmission noise N0 is a fixed value of 33dBm, the path loss constant δ is a fixed value of -95dBm, and the path loss constant δ is a fixed value of 2.75.

[0041] The total time duration T ranges from 10 to 50 seconds, D ranges from 10 to 100 Mbit, and the auxiliary function multiplier λ... t ω satisfies λ t ≤0, ω∈R.

[0042] Compared with the prior art, the beneficial effects of this application are as follows:

[0043] (1) This application makes the connected vehicle platoon more stable based on the vehicle following control protocol, thereby improving safety. At the same time, it quantifies the vehicle's fuel consumption as a function of the vehicle's speed, which can ensure fuel economy during the connected vehicle platooning process.

[0044] (2) Based on vehicle speed control, this application solves the data transmission partitioning solution, thereby clarifying the amount of data transmitted by each connected vehicle in each unit time, so as to ensure high-performance communication between connected vehicles and roadside infrastructure. While ensuring vehicle fuel economy, it realizes the joint optimization of connected vehicle platoon acceleration and data transmission. Attached Figure Description

[0045] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application.

[0046] Figure 1 This is a schematic diagram illustrating an application scenario of one embodiment of this application.

[0047] Figure 2 This is a schematic diagram of the system composition and information transmission route according to one embodiment of this application.

[0048] Figure 3 This is a schematic diagram of a method flow according to one embodiment of this application.

[0049] Figure 4 This is a schematic diagram of the optimal acceleration control curve according to one embodiment of this application.

[0050] Figure 5 This is a schematic diagram of the optimal transmission data partitioning curve according to an embodiment of this application.

[0051] In the picture:

[0052] 1. V2V communication unit, 2. Computing unit, 3. V2I communication unit, 4. Vehicle following control unit, 5. Infrastructure. Detailed implementation method:

[0053] The present application will be further described below with reference to the accompanying drawings and embodiments.

[0054] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0055] In this disclosure, terms such as "upper," "lower," "left," "right," "front," "back," "vertical," "horizontal," "side," and "bottom" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are merely relational terms determined for the convenience of describing the structural relationship of the various components or elements in this disclosure, and do not specifically refer to any component or element in this disclosure, nor should they be construed as limiting this disclosure.

[0056] like Figures 1 to 5 As shown, this application provides a connected vehicle fleet acceleration and data transmission optimization system to ensure fuel economy, which consists of a V2V communication unit 1, a computing unit 2, a V2I communication unit 3, a following control unit 4, and infrastructure 5.

[0057] like Figure 1 As shown, the application scenario of this application is an urban road scenario under a vehicle-road cooperative system. The connected vehicles in the system can travel in a straight line along urban roads, have V2V communication, V2I communication, data storage and computing capabilities, and can travel in the form of vehicle platoons. Considering the abundant roadside infrastructure resources in the vehicle-road cooperative system, platooned vehicles within the communication range of the roadside infrastructure can transmit their computing tasks to the infrastructure through V2I communication, and the infrastructure 5 will assist in completing the computing tasks. In other words, connected vehicles within the coverage area of ​​the roadside infrastructure 5 can establish a single-hop link to the roadside infrastructure to access data services and have the ability to form platoons.

[0058] V2V communication refers to communication between vehicles, while V2I communication refers to communication between vehicles and infrastructure.

[0059] like Figure 2The system composition and information transmission route shown are as follows: the lead vehicle and the following vehicles in the connected vehicle platoon are equipped with V2V communication unit 1, computing unit 2, and V2I communication unit 3. The following vehicles are also equipped with a following control unit 4. The infrastructure 5 of the vehicle-road cooperative system is set up by the roadside. The lead vehicle and the following vehicles in the connected vehicle platoon exchange vehicle status information in real time through their onboard V2V communication units 1. The following control unit 4 of the following vehicles uses a control protocol to track the lead vehicle and the vehicle in front of it to obtain its own acceleration. The computing unit 2 of the lead vehicle obtains the optimal acceleration control based on the speed information of each connected vehicle under the goal of minimizing fuel consumption. After obtaining the optimal acceleration control that ensures fuel economy, the computing units 2 of all vehicles in the connected vehicle platoon calculate the optimal data transmission division and transmit it to the infrastructure 5 by the V2I communication unit 3. The infrastructure 5 assists in completing the calculation task.

[0060] like Figure 3 As shown, this application also provides a method for optimizing the acceleration and transmission data of a connected fleet based on the above system to ensure fuel economy, specifically including the following steps:

[0061] Step S1: Each vehicle in the connected vehicle platoon system inputs its initial state, which is the initial acceleration a. i (0), initial velocity v i (0), Initial position s i (0), i = 1, 2, ..., N, where N is the number of vehicles in the connected vehicle queue;

[0062] Step S2: All vehicles in the connected vehicle platoon communicate through V2V communication unit 1 to exchange speed and location information. The following control unit 4 of the following vehicle adopts control protocol a. j (t) controls its own acceleration and thereby tracks the states of the lead vehicle and the vehicle in front, where a j (t)=-(β1(s j (t)-s j-1 (t)+l0)+β2(v j (t)-v j-1 (t))-(β1(s j (t)-s1(t)+(j-1)×l0)+β2(v j (t)-v1(t))), j=2、3、...、N, β1、β2 are adjustable parameters, l0 is the desired vehicle spacing;

[0063] Step S3: The computing unit 2 of all vehicles in the connected vehicle queue uses the control protocol and vehicle kinematic equations v i (t+1)=v i (t)+τa i (t) calculates its own velocity information, where τ is the unit time length;

[0064] Step S4: The computing unit 2 of the lead vehicle in the connected vehicle queue aims to minimize fuel consumption.

[0065]

[0066] and acceleration constraints The optimal acceleration control is then obtained. In the formula, k1, k2, k3, and k4 are parameters related to fuel consumption. These are the lower and upper limits of acceleration for the lead vehicle, respectively.

[0067] Step S5: Optimal acceleration control of the lead vehicle by the vehicle-following control unit 4 for all vehicles in the connected vehicle platoon. Tracking is performed, and all the following vehicle's computing units 2 are based on optimal acceleration control. Find the optimal acceleration control for yourself

[0068] From the vehicle kinematic equations

[0069] v i (t+1)=v i (t)+τa i (t), s i (t+1)=s i (t)+τv i (t)+τ 2 a i (t) / 2 yields the optimal speed for all vehicles in the queue. and optimal position information:

[0070] The location of roadside infrastructure 5 is fixed at s0, and the distance between it and the centerline of the road where the connected vehicle queue is located is L. The computing unit 2 of all vehicles in the connected vehicle queue calculates the distance between each vehicle and infrastructure 5.

[0071] Step S6: Communication between all vehicles in the connected vehicle queue and the roadside infrastructure 5 is provided by a cellular network, with a channel capacity of [missing information].

[0072] The probability of successful data transmission between a single vehicle and roadside infrastructure 5 at time t is:

[0073]

[0074] The probability of successful data transmission between the connected vehicle platoon and roadside infrastructure 5 at time t is:

[0075]

[0076] The probability of successful data transmission between the connected vehicle platoon and roadside infrastructure 5 over the entire time range is:

[0077]

[0078] The computing unit 2 of all vehicles in the connected vehicle platoon aims to maximize the reliability of V2I communication.

[0079]

[0080] and constraints d i When (t)≥0, the data volume D to be transmitted is divided to obtain the optimal data transmission scheme.

[0081] To To solve this problem, the augmented Lagrange multiplier method is used, introducing an auxiliary Lagrange function.

[0082] And KKT (Karush-Kuhn-Tucker) conditions,

[0083] get

[0084] In the formula, B is the available bandwidth, N is the number of vehicles in the connected vehicle queue, M is the number of other vehicles competing with the vehicle queue for the V2I channel, and P... T Where N is the data transmission power, N0 is the data transmission noise, and d i (t) represents the V2I data transmission scheme for the fleet vehicles. Let λ be the channel gain, δ be the path loss constant, T be the total time length, D be the amount of data transmitted, and λ be the path loss constant. t ω represents the multiplier.

[0085] In step S4, the formula The meaning is to find the value of a1(t) that minimizes the subsequent expression. After finding a1t, verify whether it meets the constraints. If it does not, adjust a1(t).

[0086] In the same step S6 The meaning is to seek d i The value of (t) makes the subsequent expression obtain the maximum value.

[0087] Furthermore, in step S2, the adjustable parameters β1 and β2 satisfy β1+β2=1, β1∈[0,0.7); in practical application scenarios, the desired vehicle spacing l0 is 3~10m.

[0088] Furthermore, in step S3, the unit time length τ is taken as 0.005 to 0.015 s.

[0089] Furthermore, in step S4, the parameters k1, k2, k3, and k4 related to fuel consumption are set as fixed values: k1 = 0.007, k2 = 0.0052, k3 = 1.09, and k4 = 8.

[0090] Furthermore, the lower and upper limits of the acceleration of the lead car. Values ​​range from -5 to -2 m / s 2 , Values ​​range from 3 to 5 m / s 2 .

[0091] Furthermore, in step S5, the location s0 of the roadside infrastructure 5 is arbitrary, and the distance L between the roadside infrastructure 5 and the centerline of the road where the connected queue is located takes the value of 5 to 100m.

[0092] Furthermore, in step S6, the available bandwidth B can be determined by the actual application scenario, the number of vehicles N in the connected vehicle queue is 3 to 8, the number of other vehicles M competing with the vehicle queue for the V2I channel is 0 to 100, and the data transmission power P... T The data transmission noise N0 is a fixed value of 33dBm, the path loss constant δ is a fixed value of -95dBm, and the path loss constant δ is a fixed value of 2.75.

[0093] The total time duration T ranges from 10 to 50 seconds, D ranges from 10 to 100 Mbit, and the auxiliary function multiplier λ... t ω satisfies λ t ≤0, ω∈R.

[0094] Figure 4 , Figure 5 Specific embodiments of this application are shown. Figure 4 This is a schematic diagram of the optimal acceleration control curve for an embodiment. Figure 5 This is a schematic diagram of the optimal data partitioning curve for an embodiment. In this embodiment, the adjustable parameters β1 and β2 are set to values ​​of 0.3 and 0.7, respectively; the desired vehicle spacing l0 is set to 8m; the unit time length τ is set to 0.1s; and the lower and upper limits of the acceleration of the lead vehicle are also specified. The values ​​are taken as -2m / s² and 3m / s² respectively; the location of the roadside infrastructure s0 is taken as 300m, and the distance L between the roadside infrastructure and the centerline of the road where the connected vehicle queue is located is taken as 10m; the available bandwidth B is taken as 10MHz, the number of vehicles N in the connected vehicle queue is taken as 5, and the number of other vehicles M competing with the vehicle queue for the V2I channel is taken as 40; the total time range T is taken as 30s, and the total amount of transmitted data D is taken as 30Mbit; the auxiliary function multiplier λ tω satisfies λ t ≤0, ω∈R; Initial acceleration a of the vehicles in the convoy i (1) = 0, initial velocity is v i (1) = 20 m / s, initial position is s i (1) = 100 - (i-1) × 10m.

[0095] like Figure 4 , Figure 5 As shown, the method of this application, based on the vehicle following control protocol, makes the connected vehicle platoon more stable, thereby improving safety. At the same time, it quantifies the vehicle's fuel consumption as a function of the vehicle's speed, which can ensure fuel economy during the platooning of connected vehicles. Based on the vehicle speed control, the data transmission partitioning solution is obtained, thereby clarifying the amount of data transmitted by each connected vehicle per unit time, so as to ensure high-performance communication between connected vehicles and roadside infrastructure. While ensuring vehicle fuel economy, the method achieves joint optimization of connected vehicle platoon acceleration and data transmission.

[0096] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0097] While the specific embodiments of this application have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this application. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this application are still within the scope of protection of this application.

Claims

1. A method for optimizing acceleration and data transmission in a connected vehicle fleet to ensure fuel economy, characterized in that: Based on the optimization system consisting of a V2V communication unit (1), a computing unit (2), a V2I communication unit (3), a vehicle following control unit (4), and infrastructure (5), the specific method includes the following steps: Step S1: Each vehicle in the connected vehicle platoon system inputs its initial state, which is the initial acceleration a. i (0), initial velocity v i (0), Initial position s i (0), i = 1, 2, ..., N, where N is the number of vehicles in the connected vehicle queue; Step S2: All vehicles in the connected vehicle queue communicate through the V2V communication unit (1) to exchange speed and location information. The following vehicle's control unit (4) uses control protocol a. j (t) controls its own acceleration and thereby tracks the states of the lead vehicle and the vehicle in front, where a j (t)=-(β1(s j (t)-s j-1 (t)+l0)+β2(v j (t)-v j-1 (t))-(β1(s j (t)-s1(t)+(j-1)×l0)+β2(v j (t)-v1(t))), j=2、3、...、N, β1、β2 are adjustable parameters, l0 is the desired vehicle spacing; Step S3, the computing unit (2) of all vehicles in the connected vehicle queue uses the control protocol and vehicle kinematic equations v i (t+1)=v i (t)+τa i (t) calculates its own velocity information, where τ is the unit time length; Step S4, the calculation unit (2) of the lead vehicle in the connected vehicle queue aims to minimize fuel consumption. and acceleration constraints The optimal acceleration control is then obtained. In the formula, k1, k2, k3, and k4 are parameters related to fuel consumption. These are the lower and upper limits of acceleration for the lead vehicle, respectively. Step S5: The following control units (4) of all vehicles in the connected vehicle platoon perform optimal acceleration control on the lead vehicle. Tracking is performed, and all the computing units (2) following the vehicle are based on optimal acceleration control. Find the optimal acceleration control for yourself From the vehicle kinematic equations v i (t+1)=v i (t)+τa i (t), s i (t+1)=s i (t)+τv i (t)+τ 2 a i (t) / 2 yields the optimal speed for all vehicles in the queue. and optimal position information; The location of the roadside infrastructure (5) is fixed at s0, and the distance between it and the centerline of the road where the connected vehicle queue is located is L. The computing unit (2) of all vehicles in the connected vehicle queue calculates the distance between each vehicle and the infrastructure (5). Step S6: Communication between all vehicles in the connected vehicle queue and the roadside infrastructure (5) is provided by the cellular network, with a channel capacity of [missing information]. The probability of successful data transmission between a single vehicle and roadside infrastructure (5) at time t is: The probability of successful data transmission between the connected vehicle platoon and roadside infrastructure (5) at time t is: The probability of successful data transmission between connected vehicle platoons and roadside infrastructure (5) over the entire time range is The computing units (2) of all vehicles in the connected vehicle queue aim to maximize the reliability of V2I communication. and constraints d i When (t)≥0, the data volume D to be transmitted is divided to obtain the optimal data transmission scheme. To To solve this problem, the augmented Lagrange multiplier method is used, introducing an auxiliary Lagrange function. And KKT conditions, get In the formula, B is the available bandwidth, N is the number of vehicles in the connected vehicle queue, M is the number of other vehicles competing with the vehicle queue for the V2I channel, PT is the data transmission power, N0 is the data transmission noise, and d i (t) represents the vehicle data transmission scheme. Let λ be the channel gain, δ be the path loss constant, T be the total time length, D be the amount of data transmitted, and λ be the path loss constant. t ω represents the multiplier.

2. The method for optimizing acceleration and transmission data of a connected vehicle fleet to ensure fuel economy according to claim 1, characterized in that: In step S2, the adjustable parameters β1 and β2 satisfy β1+β2=1, β1∈[0,0.7); The desired vehicle spacing l0 is 3 to 10 meters.

3. The method for optimizing acceleration and transmission data of a connected vehicle fleet to ensure fuel economy according to claim 1, characterized in that: In step S3, the unit time length τ is 0.005 to 0.015 s.

4. The method for optimizing acceleration and transmission data of a connected vehicle fleet to ensure fuel economy according to claim 1, characterized in that: In step S4, the parameters k1, k2, k3, and k4 related to fuel consumption are set as fixed values: k1 = 0.007, k2 = 0.0052, k3 = 1.09, and k4 = 8. Lower and upper limits of acceleration of the lead car Values ​​range from -5 to -2 m / s 2 , Values ​​range from 3 to 5 m / s 2 .

5. The method for optimizing acceleration and transmission data of a connected vehicle fleet to ensure fuel economy according to claim 1, characterized in that: In step S5, the location s0 of the roadside infrastructure (5) is arbitrary, and the distance L between the roadside infrastructure (5) and the centerline of the road where the network queue is located is 5 to 100m.

6. The method for optimizing acceleration and transmission data of a connected vehicle fleet to ensure fuel economy according to claim 1, characterized in that: In step S6, the number of vehicles N in the connected vehicle queue ranges from 3 to 8, the number of other vehicles M competing with the vehicle queue for the V2I channel ranges from 0 to 100, and the data transmission power P... T The data transmission noise N0 is a fixed value of 33dBm, the path loss constant δ is a fixed value of -95dBm, and the path loss constant δ is a fixed value of 2.

75. The total time duration T ranges from 10 to 50 seconds, D ranges from 10 to 100 Mbit, and the auxiliary function multiplier λ... t ω satisfies λ t ≤0, ω∈R.

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