Heterogeneous traffic flow stability control method and system considering electronic throttle feedback

Abstract

The present invention proposes a traffic flow stability control method and system considering electronic throttle feedback control, including: establishing a basic heterogeneous traffic flow following model; constructing an electronic throttle feedback control item through the coupling relationship between the throttle angles of two adjacent vehicles; improving the basic heterogeneous traffic flow following model based on the control item, and establishing a heterogeneous non-equilibrium traffic flow macro model; introducing traffic flow density and speed disturbances into the macro model, calculating a function containing disturbances and further calculating a neutral stability condition of the traffic flow; using the stability condition to judge the stability of the macro model, and improving the stability of the macro traffic flow system by adjusting control parameters.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent transportation technology, and in particular relates to a heterogeneous traffic flow stability control method and system considering electronic throttle valve feedback. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] At present, the contradiction between the rapid growth of traffic demand and the relative shortage of traffic supply has led to increasingly serious road traffic problems such as high incidence of traffic accidents and urban road congestion. In order to explore the formation mechanism of a series of traffic problems, the model and method of the evolution law of traffic flow density wave with time and space are analyzed, and then the basic method of controlling traffic flow changes is sought, and a theoretical basis is provided for traffic planning and management departments, and finally a reasonable control of traffic flow is achieved.

[0004] At present, many scholars have constructed many models and explored the dynamic characteristics of traffic flow. However, each model has certain limitations. For example, Bando's optimal speed model will produce stop-and-go phenomena, Treiber's intelligent driver model will produce following differences, and most of the existing following models do not consider the situation that the initial state of vehicles on the road is non-balanced and the vehicle is single. These limitations will make the model unable to more accurately reflect the evolution of traffic flow, resulting in unstable traffic flow and increasing the probability of congestion.

[0005] In addition, the control effect of the electronic throttle in existing research schemes usually acts on the micro level, that is, the following behavior of the two vehicles. However, its control effect is not reflected in the evolution of the non-equilibrium heterogeneous traffic flow density wave at the macro level. Summary of the invention

[0006] In order to overcome the shortcomings of the above-mentioned prior art, the present invention provides a heterogeneous traffic flow stability control method considering electronic throttle valve feedback, designs a more reasonable traffic flow model, and accurately simulates the evolution of non-equilibrium heterogeneous traffic flow density waves under actual conditions from a macro perspective, so as to improve traffic flow stability and reduce the occurrence of traffic congestion.

[0007] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0008] In a first aspect, a heterogeneous traffic flow stability control method considering electronic throttle valve feedback is disclosed, comprising:

[0009] Establish a basic heterogeneous traffic flow following model based on driving behavior that changes with real-time following distance;

[0010] The electronic throttle valve feedback control item is constructed through the coupling relationship between the throttle angles of two adjacent vehicles;

[0011] Based on the control items, the basic heterogeneous traffic flow following model is improved to establish a macroscopic model of heterogeneous non-equilibrium traffic flow.

[0012] Traffic flow density and speed disturbances are introduced into the macro model, the function containing disturbances is calculated and the neutral stability conditions of traffic flow are further calculated;

[0013] The stability of the macro model is judged by the stability condition, and the stability of the macro traffic flow system is improved by adjusting the control parameters.

[0014] As a further technical solution, a following interaction item is constructed through the relationship between the following distance and the driving behavior habits. Specifically, the driver will change his driving behavior in real time according to the following distance to the vehicle in front, and the difference in the optimal speed proportion of different driving behaviors is used as the following interaction item of the traffic flow.

[0015] As a further technical solution, an electronic throttle valve feedback control item is constructed through the coupling relationship between the throttle angles of two adjacent vehicles. Specifically, when the vehicles are driving on the road, the difference in the electronic throttle valve angles of the two adjacent vehicles is used as the electronic throttle valve feedback control item of the traffic flow.

[0016] As a further technical solution, the basic heterogeneous traffic flow following model is an improved full speed difference model.

[0017] As a further technical solution, when establishing a macro model of heterogeneous non-equilibrium traffic flow, the basic heterogeneous traffic flow following model is improved based on the control item to obtain a heterogeneous traffic flow following model;

[0018] Combined with the characteristics of heterogeneous traffic flow in non-equilibrium environment, the car-following model of heterogeneous traffic flow is improved by utilizing the characteristics of macro-micro transformation relationship, and a macroscopic model of heterogeneous non-equilibrium traffic flow is obtained.

[0019] As a further technical solution, the traffic flow density and speed disturbances are introduced into the heterogeneous non-equilibrium traffic flow macro model, the function containing the disturbance is calculated, and the neutral stability condition of the traffic flow is further calculated, specifically:

[0020] The disturbance of traffic flow density and speed is introduced into the heterogeneous non-equilibrium traffic flow macro model, Taylor second-order expansion is performed and high-order terms are ignored to obtain the traffic flow function model with disturbance.

[0021] The traffic flow function model with disturbance and Treat it as an unknown number and express it in the form of an equation matrix;

[0022] Calculate the coefficient determinant of the function expressed in matrix form and get the coefficients of σ k The expression of a quadratic equation of one variable;

[0023] About σ k Expand the expression of the quadratic equation of one variable into a quadratic function, ignore the higher-order terms and calculate ik and (ik) 2 The coefficient value of is expressed as;

[0024] When the traffic flow is stable, z2>0, ignoring the influence of interference, the conditional expression of neutral stability of traffic flow is obtained.

[0025] As a further technical solution, in the expression of the neutral stability condition of traffic flow, when a>0, it means that the non-equilibrium heterogeneous traffic flow system is in a stable state, otherwise, the system is in an unstable state.

[0026] As a further technical solution, when the system is in an unstable state, a neutral stability curve is drawn to further judge the stability of the traffic flow system. By adjusting the relevant parameters and the strength of the control items, the impact of various factors on the stability of the traffic flow is observed, which is reflected in the neutral stability curve as the change in the area of ​​the stability area and the instability area. When the stability curve moves downward, the area of ​​the traffic flow stability area increases, that is, the traffic flow stability increases. Conversely, the traffic flow stability decreases.

[0027] In a second aspect, a traffic flow stability control system considering electronic throttle feedback control is disclosed, comprising:

[0028] The basic model building module is configured to: build a basic heterogeneous traffic flow following model through time-varying driving behavior;

[0029] The control item establishment module is configured to: establish an electronic throttle valve feedback control item through a coupling relationship between throttle angles of two adjacent vehicles;

[0030] The macro model building module is configured to: improve the basic heterogeneous traffic flow following model based on the control item to establish a heterogeneous non-equilibrium traffic flow macro model;

[0031] The macro model judgment module is configured to: introduce traffic flow density and speed disturbances into the macro model, calculate the function containing the disturbances and further calculate the neutral stability conditions of the traffic flow;

[0032] The stability of the macro model is judged by the stability condition, and the stability of the macro traffic flow system is improved by adjusting the control parameters.

[0033] One or more of the above technical solutions have the following beneficial effects:

[0034] The technical solution of the present invention introduces a feedback control item based on the throttle angle difference between two adjacent vehicles, and a driving behavior that changes according to the real-time following distance, to construct a non-equilibrium heterogeneous traffic flow macro model under the current traffic scenario, which can further truly reflect the traffic characteristics; by comparing the role of the control item in the traffic system, and observing the changes in the neutral stability curve of the traffic flow, the results show that by selecting a suitable feedback gain coefficient, the stability of the traffic flow system is significantly enhanced, and the instability of the heterogeneous traffic flow caused by small disturbances is significantly weakened; the present invention can also obtain the impact of the proportion of networked autonomous driving vehicles on the stability of traffic flow, and at the same time provide a theoretical basis for the decision-making of traffic control and traffic management departments, thereby effectively alleviating problems such as traffic congestion.

[0035] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0037] Figure 1 A flow chart for implementing an example of the present invention;

[0038] Figure 2 This is a diagram of the following situation of different types of vehicles in a non-equilibrium heterogeneous environment;

[0039] Figure 3 The traffic flow stability area change diagram corresponding to different proportions of connected autonomous vehicles in the traffic flow;

[0040] Figure 4 It is the traffic flow stability area change diagram corresponding to different feedback control intensity coefficients;

[0041] Figure 5 The traffic flow density wave evolution diagram corresponding to different penetration rates of connected autonomous vehicles. DETAILED DESCRIPTION

[0042] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0043] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0044] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0045] Embodiment 1

[0046] This embodiment discloses a method for controlling the stability of heterogeneous traffic flow considering feedback control of an electronic throttle valve. The flow chart is as follows: Figure 1 As shown, the following steps are included:

[0047] Step 1: Establish a basic micro-following model and obtain relevant following information;

[0048] This embodiment is described by taking a certain heterogeneous traffic scene as an example. Figure 2 As shown in Figure 1, there are two types of vehicles on the road, namely manually driven vehicles and connected autonomous vehicles. The following characteristics of different types of vehicles are shown in Table 1. The proportion of connected autonomous vehicles is changed to obtain the stability of traffic flow under different probabilities of following situations.

[0049] This embodiment uses the full speed difference model as the basic homogeneous traffic flow following model, and the expression of the above step (1) is:

[0050]

[0051] In the formula, v n (t) represents the speed of the nth vehicle at time t, λ and a are sensitivity coefficients, Δx n (t) and Δv n (t) represents the headway distance and speed difference between two adjacent vehicles.

[0052] Table 1 Proportions of different following modes

[0053]

[0054]

[0055] Based on the time-varying driving behavior, a basic heterogeneous traffic flow following model is established, which is expressed by the formula:

[0056]

[0057] In the formula, p a-t is the proportion of different driving behaviors, p a-t ≥0.5 is aggressive driving, p a-t <0.5 is timid driving, α1 and α2 are coefficients, and It represents the average headway distance of the mixed flow and the speed difference between two adjacent vehicles.

[0058]

[0059] Step 2: Build control items to improve the basic heterogeneous car-following model and establish a macro model of heterogeneous traffic flow under non-equilibrium conditions;

[0060] The above step (2) specifically includes: the relationship between the electronic throttle angle and the maximum acceleration and speed of the vehicle is expressed by the formula:

[0061]

[0062] In the formula, θ n (t) and v n (t) respectively represent the electronic throttle angle and speed of the nth vehicle at time t, θ e and v e They represent the optimal throttle opening angle and optimal speed of the vehicle, respectively. max represents the maximum acceleration of the vehicle, b and c are coefficients;

[0063] The difference in the electronic throttle angles of two adjacent vehicles is used as a feedback control item, which is expressed by the formula:

[0064]

[0065] The basic car-following model is improved based on the control term to obtain the heterogeneous traffic flow car-following model, which is expressed as:

[0066]

[0067]

[0068]

[0069] In the formula, represents the optimal headway distance between two adjacent vehicles, A n and B n+1 Respectively represent the maximum braking deceleration of the nth and n+1th vehicles, τ n is the reaction time, l n+1 is the vehicle length, p c is the penetration rate of connected autonomous vehicles, and β is the sensitivity coefficient.

[0070] Traffic macro models include equilibrium continuity models and non-equilibrium models. This example uses the Aw-Rascle-Zhang (ARZ) model as the basis for the non-equilibrium traffic flow model, which is expressed as follows:

[0071] (CE)ρ t +(ρv) x =0

[0072]

[0073] Where h(ρ) is the hesitation function, which is an increasing function of density.

[0074] Combined with the characteristics of heterogeneous traffic flow in non-equilibrium environment, the car-following model is improved by using the characteristics of macro-micro transformation relationship, and the macro model of non-equilibrium heterogeneous traffic flow is obtained, which is expressed as:

[0075]

[0076] It should be noted that the micro-following model mainly reflects the interaction between vehicles. The macro model describes the overall operating status and characteristics, but ignores the behavior of individual vehicles and explores the operating status of the entire road due to the existence of disturbances in the traffic system, which is beyond the reach of the micro model.

[0077] Step 3: Introduce small disturbances in traffic flow, obtain the non-equilibrium heterogeneous traffic flow function under the disturbance state, and obtain the neutral stability condition based on the function.

[0078] In this step, the neutral stability condition is used to judge the stability of traffic flow in the current heterogeneous and non-equilibrium mixed traffic environment, a neutral stability curve is drawn, relevant parameters are adjusted, and the impact of various factors on traffic flow stability is intuitively observed. Then, the purpose of improving stability is achieved by adjusting the parameters.

[0079] The above step (3) specifically includes:

[0080] Introducing a small disturbance related to traffic flow density and speed, the expression is:

[0081]

[0082] Where ρ0 and v0 are the initial density and speed of the traffic flow system, respectively, and k is the amplitude of the delay disturbance.

[0083] By bringing the disturbances of density and speed into the non-equilibrium heterogeneous traffic flow macro model, performing Taylor second-order expansion and ignoring high-order terms, we can obtain the traffic flow function model containing disturbances, namely:

[0084]

[0085] The state equation of non-equilibrium heterogeneous traffic flow under disturbance is and Considered as unknowns, the matrix form of the equation is used, namely:

[0086]

[0087] In the formula,

[0088] Calculate the coefficient determinant of the function and get the coefficients about σk The quadratic equation of one variable is expressed as:

[0089]

[0090] σ k Expanded into a quadratic function σ k =z1(ik)+z1(ik) 2 +…, ignoring higher-order terms and calculating ik and (ik) 2 The coefficient value is expressed as:

[0091]

[0092] Here, the parameter is expanded into two parts, the real part and the imaginary part, as the criterion for stability. If the root of the real part is greater than zero, it means that the upstream small disturbance is gradually compressed in the process of transmission to the downstream vehicles, and the traffic flow is in a stable state.

[0093] If the root of the real part is less than zero, it means that the small disturbance upstream is amplified in the process of transmission to the downstream vehicles, and the traffic flow is unstable.

[0094] When the traffic flow is stable, z2>0, the influence of interference can be ignored, and the conditional expression of traffic flow neutral stability is obtained as follows:

[0095]

[0096] In the formula, is the initial density of the mixed flow, and V is the optimal velocity under the initial conditions of the mixed flow.

[0097] Step 4: Use the neutral stability condition to determine the stability of the traffic system under the current non-equilibrium heterogeneous traffic environment;

[0098] The above step 4 specifically includes: when a>0, it indicates that the non-equilibrium heterogeneous traffic flow system is in a stable state, otherwise, the system is in an unstable state. The neutral stability curve is drawn to further judge the stability of the traffic flow system. By adjusting the relevant parameters and the strength of the control items, the influence of various factors on the stability of the traffic flow is observed, which is reflected in the neutral stability curve as the change in the area of ​​the stability area and the instability area. When the stability curve moves down, the area of ​​the traffic flow stability area increases, that is, the traffic flow stability increases, otherwise, the traffic flow stability decreases.

[0099] Based on the neutral stability condition of traffic flow, a stability curve of "traffic flow density-sensitivity coefficient" is drawn. By setting the optimal speed function, traffic flow density, maximum acceleration and a series of sensitivity coefficients, a stability curve with density as the horizontal axis and a step size of 0.001 and the vertical axis as the sensitivity coefficient is drawn.

[0100] The sub-technical scheme of this embodiment, based on the non-equilibrium traffic flow model, constructs feedback control items through the angle difference of the electronic throttles of the front and rear vehicles, as well as the penetration rate and time-varying driving behavior of networked autonomous driving vehicles in specific traffic scenarios, and introduces them into the non-equilibrium traffic flow macro model, introduces small disturbances into the traffic flow system, improves the stability of traffic flow, verifies the control effect, and analyzes the impact of different factors on traffic flow stability.

[0101] The traffic flow stability control scheme considering electronic throttle feedback control in the embodiment of the present invention can more realistically respond to the evolution of traffic flow density waves in the intelligent networked heterogeneous and non-equilibrium traffic environment, model and analyze the stability of macroscopic traffic flow characteristics, and improve traffic flow stability by using control parameters to control heterogeneous traffic flow congestion.

[0102] In this implementation example, the control parameters are the penetration rate of connected autonomous vehicles and the weight of the electronic throttle feedback item. In the neutral stability expression, other parameters are constants or functions, and only density, the penetration rate of connected autonomous vehicles, and the throttle weight are variables, and density exists as an independent variable. Therefore, the control parameters are determined by the neutral stability expression. When the throttle feedback item parameter is greater than 0 and less than 1, it indicates positive feedback, and the control item begins to work. The larger the parameter, the stronger the control effect.

[0103] When controlling parameters, the impact on stability is observed by adjusting the penetration rate of connected autonomous vehicles and the electronic throttle weight coefficient.

[0104] In order to quantitatively analyze the impact of the penetration rate of connected autonomous vehicles on traffic flow stability, it is assumed that the penetration rate of connected autonomous vehicles is 0.2, 0.4, 0.6, and 0.8. The penetration rate of connected autonomous vehicles is respectively substituted into the neutral stability condition expression, and the neutral stability curve of traffic flow under different penetration rates is plotted. The changing trend of the curve is further observed, such as Figure 3 As shown in the figure, the area below the curve is unstable, and vice versa, it is a stable area. As the penetration rate of connected autonomous vehicles increases from 0.2 to 0.8 at intervals of 0.2, the unstable area under the neutral stability curve decreases, that is, the stable area becomes larger. This phenomenon reflects that the emergence of connected autonomous vehicles is beneficial to the stability of traffic flow. Based on this, the analysis results of the stability of heterogeneous traffic flow systems under non-equilibrium environments can be obtained, see Appendix Figure 5 shown.

[0105] In addition, if Figure 4 As shown, when the electronic throttle control item takes effect, the stronger the throttle control item is, the less stable the traffic flow area is, that is, the traffic flow system is gradually stabilized.

[0106] Through the above technical scheme, the present invention provides a heterogeneous traffic flow stability control method considering electronic throttle feedback control. On the basis of the non-equilibrium traffic flow model, the feedback control item is constructed through the angle difference of the electronic throttles of the front and rear vehicles, as well as the penetration rate and time-varying driving behavior of networked autonomous driving vehicles under specific traffic scenarios, and it is introduced into the non-equilibrium traffic flow macro model, and small disturbances are introduced into the traffic flow system. From a macro perspective, the present invention expands the non-equilibrium macro traffic flow model based on electronic throttle control, which can more realistically reflect heterogeneous traffic scenarios, improve the stability of traffic flow, verify the control effect, and analyze the influence of different factors on traffic flow stability.

[0107] It should be noted that the above technical solution of the present application more realistically reflects the evolution of the stability of the mixed traffic system and the density wave from a macroscopic level. It not only considers the penetration rate of networked autonomous driving vehicles, but also considers the non-equilibrium traffic flow state in the modeling process. The influence of the electronic throttle valve in the prior art on the stability of traffic flow only stays between two adjacent vehicles, and the effect of the throttle opening is mainly reflected at the microscopic level, that is, in the following behavior between two adjacent vehicles, the feedback control affects the speed, acceleration and head-to-head distance of the following vehicle. However, the influence of the control effect on the entire traffic system is ignored.

[0108] Different from the micro-car-following model which studies the speed change, acceleration change and headway change of the following vehicle through feedback items, the sub-scheme of this embodiment focuses on the impact of feedback items on the stability of the macro traffic flow system and the evolution of traffic flow density waves.

[0109] In the specific implementation, it is necessary to collect the speed, headway, acceleration, length and headway time of vehicles on the same lane; based on the data set, a reasonable parameter value range is set, and the genetic algorithm is used to calibrate the parameters of the proposed model to output the optimal parameter values, and control the stability of traffic flow through factors such as the penetration rate of different connected autonomous driving vehicles.

[0110] Embodiment 2

[0111] The purpose of this embodiment is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the program.

[0112] Embodiment 3

[0113] The purpose of this embodiment is to provide a computer-readable storage medium.

[0114] A computer-readable storage medium stores a computer program, which executes the steps of the above method when executed by a processor.

[0115] Embodiment 4

[0116] The purpose of this embodiment is to provide a traffic flow stability control system considering electronic throttle valve feedback control, comprising:

[0117] The basic model building module is configured to: build a basic heterogeneous traffic flow following model;

[0118] The control item establishment module is configured to: establish an electronic throttle valve feedback control item through a coupling relationship between throttle angles of two adjacent vehicles;

[0119] The macro model building module is configured to: improve the basic heterogeneous traffic flow following model based on the control item to establish a heterogeneous non-equilibrium traffic flow macro model;

[0120] The macro model judgment module is configured to: introduce traffic flow density and speed disturbances into the macro model, calculate the function containing the disturbances and further calculate the neutral stability conditions of the traffic flow;

[0121] The stability of the macro model is judged by the stability condition, and the stability of the macro traffic flow system is improved by adjusting the control parameters.

[0122] The steps involved in the apparatuses of the above embodiments 2, 3 and 4 correspond to the method embodiment 1, and the specific implementation methods can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0123] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0124] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A heterogeneous traffic flow stability control method considering electronic throttle valve feedback, characterized in that: include: Establish a basic heterogeneous traffic flow following model; The electronic throttle valve feedback control item is constructed through the coupling relationship between the throttle angles of two adjacent vehicles; Based on the control items, the basic heterogeneous traffic flow following model is improved to establish a macro model of heterogeneous non-equilibrium traffic flow. The following modes include CAV-CAV, CAV-HDV, HDV-CAV and HDV-HDV. The ratio of CAV-CAV is , the headway distance is ; The ratio of CAV-HDV is , the headway distance is ; The ratio of HDV-CAV is , the headway distance is , the ratio of HDV-HDV is , the headway distance is ; The penetration rate of connected autonomous vehicles; Based on the time-varying driving behavior, the basic heterogeneous traffic flow following model is established and expressed by the formula: In the formula, is the proportion of different driving behaviors, For aggressive driving, For timid driving, and is the coefficient, and It represents the average headway distance of the mixed flow and the speed difference between two adjacent vehicles; The basic car-following model is improved based on the control term to obtain the heterogeneous traffic flow car-following model, which is expressed as: In the formula, represents the optimal headway distance between two adjacent vehicles, and Respectively represent and The maximum braking deceleration of the vehicle, is the reaction time, For the car commander, is the penetration rate of connected autonomous vehicles, is the sensitivity coefficient; The non-equilibrium traffic flow model based on the Aw-Rascle-Zhang model is expressed as: In the formula, The hesitation function is an increasing function of density; Traffic flow density and speed disturbances are introduced into the macro model, the function containing disturbances is calculated and the neutral stability conditions of traffic flow are further calculated; The stability of the macro model is judged by the stability condition, and the stability of the macro traffic flow system is improved by adjusting the control parameters.

2. The method for controlling the stability of heterogeneous traffic flow considering electronic throttle valve feedback as claimed in claim 1, characterized in that: An electronic throttle valve feedback control item is constructed through the coupling relationship between the throttle valve angles of two adjacent vehicles. Specifically, when the vehicles are driving on the road, the difference in the electronic throttle valve angles of the two adjacent vehicles is used as the electronic throttle valve feedback control item of the traffic flow.

3. The method for controlling the stability of heterogeneous traffic flow considering electronic throttle valve feedback as claimed in claim 1, characterized in that: The basic heterogeneous traffic flow following model is a full speed difference model.

4. The method for controlling the stability of heterogeneous traffic flow considering electronic throttle valve feedback as claimed in claim 1, characterized in that: When establishing a heterogeneous non-equilibrium traffic flow macro model, the basic heterogeneous traffic flow following model is improved based on the control term to obtain a heterogeneous traffic flow following model. Combined with the characteristics of heterogeneous traffic flow in non-equilibrium environment, the heterogeneous traffic flow following model is improved by using the characteristics of macro-micro transformation relationship, and a macroscopic model of heterogeneous non-equilibrium traffic flow is obtained.

5. The method for controlling the stability of heterogeneous traffic flow considering electronic throttle valve feedback as claimed in claim 1, characterized in that: Traffic flow density and speed disturbances are introduced into the heterogeneous non-equilibrium traffic flow macro model, and the function containing disturbances is calculated and the neutral stability conditions of traffic flow are further calculated, which are as follows: The disturbance of traffic flow density and speed is introduced into the heterogeneous non-equilibrium traffic flow macro model, Taylor second-order expansion is performed and high-order terms are ignored to obtain the traffic flow function model with disturbance. The traffic flow function model with disturbance and Treat it as an unknown number and express it in the form of an equation matrix; Calculate the coefficient determinant of the function expressed in matrix form and get the coefficients of The expression of a quadratic equation of one variable; About The expression of the quadratic equation of one variable is expanded into a quadratic function, ignoring the higher-order terms and calculating and The coefficient value of is expressed as; When the traffic flow is stable, , ignoring the influence of interference, the conditional expression of neutral stability of traffic flow is obtained.

6. The method for controlling the stability of heterogeneous traffic flow considering electronic throttle valve feedback as claimed in claim 1, characterized in that: In the traffic flow neutral stability condition expression, when When , it indicates that the non-equilibrium heterogeneous traffic flow system is in a stable state, otherwise, the system is in an unstable state.

7. The method for controlling the stability of heterogeneous traffic flow considering electronic throttle valve feedback as claimed in claim 1, characterized in that: When the system is in an unstable state, a neutral stability curve is drawn to further judge the stability of the traffic flow system. By adjusting relevant parameters and control item strengths, the impact of various factors on traffic flow stability is observed, which is reflected in the neutral stability curve as the change in the area of ​​the stability area and the instability area. When the stability curve moves downward, the area of ​​the traffic flow stability area increases, that is, the traffic flow stability increases. Conversely, the traffic flow stability decreases. The relevant parameters include the penetration rate of networked autonomous driving vehicles and the electronic throttle weight coefficient.

8. A traffic flow stability control system considering electronic throttle valve feedback control, characterized in that: include: The basic model building module is configured to: build a basic heterogeneous traffic flow following model; The control item establishment module is configured to: establish an electronic throttle valve feedback control item through a coupling relationship between throttle angles of two adjacent vehicles; The macro model building module is configured to: improve the basic heterogeneous traffic flow following model based on the control item to establish a heterogeneous non-equilibrium traffic flow macro model; The following modes include CAV-CAV, CAV-HDV, HDV-CAV and HDV-HDV. The ratio of CAV-CAV is , the headway distance is ; The ratio of CAV-HDV is , the headway distance is ; The ratio of HDV-CAV is , the headway distance is , the ratio of HDV-HDV is , the headway distance is ; The penetration rate of connected autonomous vehicles; Based on the time-varying driving behavior, the basic heterogeneous traffic flow following model is established and expressed by the formula: In the formula, is the proportion of different driving behaviors, For aggressive driving, For timid driving, and is the coefficient, and It represents the average headway distance of the mixed flow and the speed difference between two adjacent vehicles; The basic car-following model is improved based on the control term to obtain the heterogeneous traffic flow car-following model, which is expressed as: In the formula, represents the optimal headway distance between two adjacent vehicles, and Respectively represent and The maximum braking deceleration of the vehicle, is the reaction time, For the car commander, is the penetration rate of connected autonomous vehicles, is the sensitivity coefficient; The non-equilibrium traffic flow model based on the Aw-Rascle-Zhang model is expressed as: In the formula, The hesitation function is an increasing function of density; The macro model judgment module is configured to: introduce traffic flow density and speed disturbances into the macro model, calculate the function containing the disturbances and further calculate the neutral stability conditions of the traffic flow; The stability of the macro model is judged by the stability condition, and the stability of the macro traffic flow system is improved by adjusting the control parameters.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 7 are performed.

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