CN113788018A - Longitudinal queue associated vehicle system under influence of communication time delay and fuzzy control method thereof - Google Patents
Longitudinal queue associated vehicle system under influence of communication time delay and fuzzy control method thereof Download PDFInfo
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Abstract
The invention provides a longitudinal queue associated vehicle system under the influence of communication time delay and a fuzzy control method thereof.A speed, an acceleration, position information, errors between associated vehicles and an error change rate of the vehicles are obtained by acquiring signals and calculating, and a longitudinal queue control problem with a CACC function is described into a discrete associated system under the influence of communication time delay from the characteristic of one-way strong coupling to construct an associated system model; secondly, acquiring a communication delay upper bound ensuring the stable condition of the queue association system by using a partial decomposition method and a Lyapunov function method, neglecting vehicle state information exceeding the communication delay upper bound, and only adopting the vehicle state information within a communication delay range; and finally, designing a longitudinal queue cruise control strategy by combining the inter-vehicle distance and the upper limit of communication delay by using a fuzzy PID control algorithm. The invention can reasonably respond to the acceleration or deceleration behavior of the front vehicle under the proposed control strategy, achieve the expected CACC control performance and effectively compensate the influence of communication time delay.
Description
Technical Field
The invention relates to the technical field of vehicle cruise control, in particular to a longitudinal cooperative adaptive cruise control technology, and specifically relates to a longitudinal queue associated vehicle system under the influence of communication time delay and a fuzzy control method thereof.
Background
It should be understood at the outset that the statements in this section merely provide a background information related to the present patent application and may not necessarily constitute prior art.
Cooperative Adaptive Cruise Control (CACC) under vehicle-to-vehicle communication is a typical representative of the modern fleet vehicle Cooperative Control technology. The CACC technology is a method of vehicle-vehicle cooperative control, which realizes cooperative queue control, and on the basis of ensuring safety, can keep the following distance of vehicles smaller than that of an adaptive cruise control system, reduce the fluctuation of the speed of vehicles in a queue, better improve traffic safety, reduce traffic energy consumption, improve traffic efficiency, and have stronger inhibition capability on external interference, thus being concerned.
In the research of the cooperative adaptive cruise control system, the research is mainly carried out on the cooperative control aspect of multiple vehicles, and under the action of a cooperative control rule, different vehicles exchange information with each other to finally realize the aim of stable operation of a queue.
In an actual workshop communication network environment, communication time delay in a large-scale queue vehicle control system is inevitable, system control of vehicles is obviously influenced, and meanwhile, for the large-scale fleet control system, the relevance between queues is important, such as the relevance between an autonomous vehicle and all vehicles in front.
Disclosure of Invention
According to the two characteristics, the communication time delay and the correlation characteristics among vehicles are considered in a control target, a longitudinal queue correlation vehicle system under the influence of the communication time delay is established, meanwhile, nonlinear intelligent control is realized by applying fuzzy control, the robustness and flexibility are good, and the precision and the control effect of queue cooperative control are improved.
The invention is realized by the following technical scheme that firstly, a longitudinal queue associated vehicle system under the influence of communication time delay is provided, which comprises a workshop communication module, an information acquisition module, a cooperative decision module and a motion control module, wherein the workshop communication module is communicated with a vehicle-to-vehicle (V2V) through a Global Positioning System (GPS) to receive and send state information between the vehicles; the information acquisition module is used for acquiring information including speed, position and acceleration of the autonomous vehicle and the queue vehicle, and calculating the actual distance between the front vehicle and the autonomous vehicle, the relative speed between the front vehicle and the autonomous vehicle, the relative acceleration between the front vehicle and the autonomous vehicle and the error change rate through the acquired information; the cooperative decision-making module is used for taking the relative inter-vehicle distance between the front vehicle and the autonomous vehicle and the inter-vehicle distance error as input, ignoring the vehicle state information beyond the upper bound of the communication time delay according to the expected inter-vehicle distance and the actual inter-vehicle distance error and by combining a workshop kinematics model, and adopting the available vehicle state information within the communication time delay range for ensuring the stability of the queue; the motion control module comprises a control decision module, a fuzzy controller and a PID controller and is used for controlling the autonomous vehicle to drive along with the front vehicle at a desired speed and keeping a safe distance between vehicles; the control decision module determines the acceleration and deceleration behaviors of the autonomous vehicle according to the expected inter-vehicle distance and the inter-vehicle distance error; the fuzzy controller dynamically outputs three PID parameters according to the expected inter-vehicle distance error and the change rate of the expected inter-vehicle distance error; and the PID controller controls the autonomous vehicle according to the PID parameters output by the fuzzy controller in a motion control mode determined by the control decision layer.
As a possible implementation manner, the safe distance model designs a control target to be a vehicle distance error and a speed error according to the relative speed, the communication delay and the associated system characteristics of the front vehicle and the autonomous vehicle, which are provided by the vehicle state acquisition module.
As a possible implementation mode, the workshop kinematics model is sent from a one-way strong coupling characteristic, a longitudinal queue control problem with a CACC function is described as a discrete state space equation under the influence of communication time delay, and a queue vehicle CACC correlation system under the influence of communication time delay is constructed.
As a possible implementation manner, the fuzzy controller obtains fuzzy input quantity by fuzzy quantization of the deviation between the expected inter-vehicle distance and the actual inter-vehicle distance and the error change rate of the inter-vehicle distance by using a membership function based on a workshop kinematics model, and outputs the coefficient value of the PID controller.
The invention also provides a fuzzy control method of the vehicle system related to the longitudinal queue under the influence of the communication time delay, which is applied to the vehicle system related to the longitudinal queue under the influence of the communication time delay and comprises the following steps:
a. acquiring motion state information of front vehicles and autonomous vehicles in a queue, acquiring position, speed and acceleration information in the driving and braking processes of the vehicles by using a sensor and a wireless communication technology, and calculating to obtain speed errors, acceleration errors and error change rates of other vehicles;
b. designing a control target, and designing the communication delay, the association characteristic fusion and the inter-vehicle distance error as the control target through the acquired information including the position, the vehicle speed and the acceleration;
c. acquiring an upper communication delay bound;
d. designing a PID controller.
As a possible implementation manner, the step c of obtaining the upper limit of the communication delay includes the following sub-steps,
c-1, establishing a longitudinal queue associated vehicle system model under the influence of communication time delay, describing a longitudinal queue control problem with a CACC function into a discrete association system under the influence of communication time delay from the characteristic of one-way strong coupling, and establishing the longitudinal queue associated vehicle system model under the influence of communication time delay;
and c-2, performing stability analysis on the longitudinal queue associated vehicle system model established in the step c-1 by using a partial decomposition method and a Lyapunov function method, and obtaining a communication delay upper bound for ensuring the stability of the associated queue.
As a possible implementation manner, the design of the PID controller in step d is specifically as follows,
designing input quantity of the fuzzy controller: and carrying out fuzzy quantization on the obtained vehicle distance error and the vehicle distance error change rate by utilizing a membership function to obtain four corresponding fuzzy input quantities, wherein the fuzzy language values of the vehicle distance error and the vehicle distance error change rate are L, M, S and ZO, L represents large, M represents moderate, S represents small, ZO represents zero, a fuzzy controller carries out fuzzy reasoning according to a designed fuzzy control rule and obtains a fuzzy output quantity, the input quantity adopts a Gaussian membership function, and the output quantity adopts a triangular membership function.
The stability of the whole CACC queue is controlled by combining the inter-vehicle distance control and the communication time delay, and a PID controller u is designed as follows:
u(k)＝KP*e(k)+KI*∑e(k)+KD(e (K +1) -e (K)), wherein KPIs a proportionality coefficient, KIIs the integral coefficient, KDIs a differential coefficient.
As a possible implementation manner, the fuzzy control rule includes that when the inter-vehicle distance error is too large, the response speed of the rear vehicle is increased, and meanwhile, the out-of-range control effect caused when the CACC queue system starts is avoided; when the error of the distance between the vehicles is too small, the proportional coefficient and the integral coefficient are adjusted, so that the CACC queue association system has good steady-state performance, and meanwhile, the differential coefficient is adjusted, so that the system is prevented from vibrating at a balance point; when the vehicle-to-vehicle distance error is in a medium size, the response overshoot of the CACC queue association system is slightly reduced, and meanwhile, the response speed of the CACC queue system is ensured.
Compared with the prior art, the invention has the beneficial effects that:
1. the method comprises the steps of establishing a longitudinal queue associated vehicle system model under the influence of communication time delay by considering the associated characteristics of the communication time delay and queue vehicles into control targets, namely inter-vehicle distance errors and speed errors and considering the association between queue vehicle systems from the perspective of one-way strong coupling characteristics, and performing stability analysis on the associated vehicle system model by a partial decomposition method and a Lyapunov function method, thereby obtaining an upper communication time delay bound for ensuring the stability of the associated vehicle system model, and finally effectively reducing the influence of the communication time delay on the cooperation of the queue vehicles.
2. The controller is designed by combining the upper limit of communication delay for ensuring the stability of the longitudinal queue associated vehicle system with a control target, and the inter-vehicle distance error change rate are used as control input, so that the fuzzy rule of the fuzzy PID control strategy is designed, the acceleration or deceleration behavior of the front vehicle is effectively responded, the expected CACC control performance can be achieved, and the influence of the communication delay is effectively compensated.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a block diagram of a longitudinal queue associated vehicle system under the influence of communication latency provided by the present invention;
FIG. 2 is a schematic diagram of a longitudinal queue associated vehicle system under the influence of communication latency provided by the present invention;
FIG. 3 is a structural diagram of fuzzy PID control of vehicles associated with a longitudinal queue under the influence of communication delay provided by the present invention;
fig. 4 is a schematic flow chart illustrating steps of a fuzzy control method for a longitudinal queue associated vehicle system under the influence of communication delay according to the present invention.
Detailed Description
In order to clearly illustrate the technical features of the present invention, the present invention is further illustrated by the following detailed description with reference to the accompanying drawings.
As shown in fig. 1 to 3, a longitudinal queue association vehicle system under the influence of communication time delay is provided, which includes a vehicle-to-vehicle communication module, an information acquisition module, a cooperative decision module, and a motion control module, wherein the vehicle-to-vehicle communication module receives and sends state information between vehicles through a Global Positioning System (GPS) and vehicle-to-vehicle (V2V); the information acquisition module is used for acquiring information including speed, position and acceleration of the autonomous vehicles and the queue vehicles, and calculating the actual distance between the front vehicle and the autonomous vehicles, the relative speed between the front vehicle and the autonomous vehicles, the relative acceleration between the front vehicle and the autonomous vehicles and the error change rate through the acquired information; the cooperative decision-making module is used for taking the relative inter-vehicle distance between the front vehicle and the autonomous vehicle and the inter-vehicle distance error as input, ignoring the vehicle state information beyond the upper bound of the communication time delay according to the expected inter-vehicle distance and the actual inter-vehicle distance error and by combining a inter-vehicle kinematic model, and adopting the available vehicle state information within the communication time delay range for ensuring the stability of the queue; the motion control module comprises a control decision module, a fuzzy controller and a PID (proportion integration differentiation) controller and is used for controlling the autonomous vehicle to drive along with the front vehicle at an expected speed and keeping a safe distance between vehicles; the control decision module determines the acceleration and deceleration behaviors of the autonomous vehicle according to the expected inter-vehicle distance and the inter-vehicle distance error; the fuzzy controller dynamically outputs three PID parameters according to the expected inter-vehicle distance error and the expected inter-vehicle distance error change rate; and the PID controller controls the autonomous vehicle according to the PID parameters output by the fuzzy controller in a motion control mode determined by the control decision layer.
In this embodiment, the safe distance model designs a control target to be a vehicle distance error and a speed error according to the relative speed, the communication delay and the associated system characteristics of the preceding vehicle and the autonomous vehicle provided by the vehicle state acquisition module.
Furthermore, the workshop kinematics model is based on a one-way strong coupling characteristic, describes a longitudinal queue control problem with a CACC function into a discrete state space equation under the influence of communication delay, and constructs a longitudinal queue associated vehicle system under the influence of the communication delay.
Further, the fuzzy controller obtains fuzzy input quantity by fuzzy quantization of deviation between the expected vehicle distance and the actual vehicle distance and the vehicle distance error change rate by using a membership function based on a vehicle kinematics model and outputs a coefficient value of the PID controller.
Based on the longitudinal correlation system based on the fuzzy control strategy provided in the foregoing embodiment, as shown in fig. 4, a fuzzy control method for the longitudinal correlation system under the influence of communication delay is also provided for the foregoing embodiment, and is applied to the foregoing longitudinal queue correlation vehicle system under the influence of communication delay, and includes the following steps:
a. acquiring motion state information of front vehicles and autonomous vehicles in a queue, acquiring position, speed and acceleration information in the driving and braking processes of the vehicles by using a sensor and a wireless communication technology, and calculating to obtain speed errors, acceleration errors and error change rates of other vehicles;
b. designing a control target, and designing the communication delay, the association characteristic fusion and the inter-vehicle distance error as the control target through the acquired information including the position, the vehicle speed and the acceleration;
the desired speed and the desired inter-vehicle distance of the autonomous vehicle are dependent on the length of the queue and the driving status of the other vehicles in the queue. Thus, the desired speed in the queue can be expressed as:
wherein w is an influence weight representing the length of the queue, related to the relative position of the vehicle in the queue, and
the desired inter-vehicle distance in the queue may be expressed as:
wherein d is0iRepresenting the minimum safe distance for the ith vehicle.
From the configuration in the queue, the speed error is:
the vehicle spacing error is:
c. acquiring an upper communication delay bound, wherein the acquiring of the upper communication delay bound in step c comprises the following sub-steps,
c-1, establishing a longitudinal queue associated vehicle system model under the influence of communication time delay, describing a longitudinal queue control problem with a CACC function into a discrete association system under the influence of communication time delay from the characteristic of one-way strong coupling, and constructing a longitudinal queue associated vehicle system under the influence of communication time delay;
in the vehicle system related to the longitudinal queue under the influence of the communication time delay, information is transmitted between adjacent vehicles through a physical sensor, and the communication time delay is avoided; and the self-vehicle and other vehicles carry out information transmission through wireless equipment, and communication time delay exists when the state information such as speed, acceleration and the like sampled by the ith vehicle at the kth moment is sent to other vehicles. Meanwhile, the driving state of the vehicle is directly influenced by the front vehicle, the influence is larger when the distance is shorter, and the influence of the rear vehicle along with the front vehicle is small, so that the vehicles have one-way strong coupling characteristic.
Based on the one-way strong coupling characteristic between vehicles, the longitudinal queues can be represented according to the aggregated vectors as:
wherein the content of the first and second substances,
the system state vector of the ith vehicle in the vehicle fleet is obtained;
Aija constant matrix with proper dimension represents that the ith vehicle and the jth vehicle have a one-way strong coupling relation; tau is the time lag of communication disturbance between vehicles, tau>0；BiA matrix of appropriate dimensions; u. ofiIs a controller; k denotes the kth sample point.
c-2, performing stability analysis on the longitudinal correlation system model established in the step c-1 by using a partial decomposition method and a Lyapunov function method to obtain a communication delay upper bound for ensuring the stability of the correlation queue;
in the longitudinal queue-associated vehicle system (5) under the influence of the communication time delay, let tau be 0, and the longitudinal queue-associated vehicle system is decomposed into N subsystems with single decoupling
Formula (6) is represented by x (k +1) ═ asx (k), wherein,
x＝[x1 x2 … xN]T，
the system is asymptotically stable. Therefore, there is a matrix equation that uniquely satisfies the discrete type Lyapunov
Wherein
By expanding the matrix equation (7), N (N +1)/2 matrix equations can be obtained.
Selecting an orthodefinite quadratic form
v(x(k))＝xT(k)Px(k) (8)
And (3) associating the Lyapunov function of the vehicle system model (5) candidate for the longitudinal queue under the influence of the communication time delay. Solution sequence for associating vehicle system models (5) along a longitudinal queue under the influence of communication time delay
to obtain
It can be known that Δ v (x (k)) > cells do not count(1)Is negative. Therefore, the longitudinal queue associated vehicle system (5) is gradually stable under the influence of the communication time delay.
When the stability of the step c-2 is analyzed,
and decomposing the vehicle system (5) associated with the longitudinal queue under the influence of the communication time delay according to a partial decomposition method to obtain a formula (6). With respect to equation (6), the solution sequence of the correlation system (5) can be found as:
selecting v (x (k) ═ xT(k) Px (k) is used as a Lyapunov function of the correlation system model, the difference of the longitudinal queue correlation vehicle system is calculated, a matrix M containing the communication time delay tau can be obtained, and as long as the communication time delay tau is ensured to meet the condition that the matrix M is positive, the stable upper bound of the communication time delay tau of the longitudinal queue correlation vehicle system under the influence of the communication time delay can be obtained.
d. The PID controller is designed, as will be described in detail below,
and designing input quantity of a fuzzy controller, and carrying out fuzzy quantization on the obtained inter-vehicle distance error and the change rate of the inter-vehicle distance error by utilizing a membership function to obtain two corresponding fuzzy input quantities.
The fuzzy linguistic values for the inter-vehicle distance error and the rate of change of the inter-vehicle distance error are L, M, S and ZO, where L represents large, M represents medium, S represents small, and ZO represents zero.
The input quantity adopts a Gaussian membership function, and the output quantity adopts a triangular membership function.
In the running process of the queue vehicle, because the structure of the controlled vehicle is complex and the environment change of the vehicle at any moment is abnormal, in order to obtain good control effect and ensure safety, the parameter values of the PID regulator need to be adjusted according to the current state at each moment. Therefore, three parameters of the PID regulator are regulated on line by the Fuzzy, and real-time feedback can be carried out according to the running condition of the system. For example, the front vehicle suddenly reduces the speed, and the autonomous vehicle should make adjustments in time to avoid a collision. And carrying out fuzzy reasoning on the four obtained fuzzy input quantities according to a fuzzy rule so as to obtain corresponding fuzzy output quantities. Wherein the fuzzy control rules comprise, for each of the fuzzy control rules,
when the error of the distance between the vehicles is overlarge, the response speed of the rear vehicle is accelerated, and the over-range control effect caused when the CACC queue system starts is avoided;
when the error of the distance between the vehicles is too small, the proportional coefficient and the integral coefficient are adjusted, so that the CACC queue association system has good steady-state performance, and meanwhile, the differential coefficient is adjusted, so that the system is prevented from vibrating at a balance point;
when the distance error is in a medium size, the response overshoot of the CACC queue association system is slightly reduced, and the response speed of the CACC queue system is ensured.
Fuzzy input quantity E based on inter-vehicle distance error E, fuzzy input quantity EC of inter-vehicle distance change rate EC and parameter adjustment KPThe fuzzy rule table is shown in table 1.
TABLE 1
Fuzzy input quantity E based on inter-vehicle distance error E, fuzzy input quantity EC of inter-vehicle distance change rate EC and parameter adjustment KIThe fuzzy rule table is shown in table 2.
TABLE 2
Fuzzy input quantity E based on inter-vehicle distance error E, fuzzy input quantity EC of inter-vehicle distance change rate EC and parameter adjustment KDThe fuzzy rule table is shown in table 3.
TABLE 3
According to the actual situation of the longitudinal queue associated vehicle system under the influence of communication time delay, the design of the controller is divided into two parts based on a longitudinal queue associated vehicle system model (5) under the influence of communication time delay. Firstly, the relative distance control is carried out, and the aim is to keep a small safety distance between each vehicle in the queue and the vehicle in front of the vehicle; and the other is communication delay control, which aims to ensure that vehicles beyond the communication range are ignored in the queue so as to maintain the stability of the queue. In order to overcome the traditional fuzzy controller and meet the control requirement of the queue, the stability of the whole CACC queue is controlled by combining the inter-vehicle distance control and the communication time delay by using a fuzzy PID control algorithm.
Finally, it should be further noted that the above examples and descriptions are not limited to the above embodiments, and technical features of the present invention that are not described may be implemented by or using the prior art, and are not described herein again; the above embodiments and drawings are only for illustrating the technical solutions of the present invention and not for limiting the present invention, and the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that changes, modifications, additions or substitutions within the spirit and scope of the present invention may be made by those skilled in the art without departing from the spirit of the present invention, and shall also fall within the scope of the claims of the present invention.
Claims (9)
1. A longitudinal queue associated vehicle system under the influence of communication time delay is characterized by comprising a workshop communication module, an information acquisition module, a cooperative decision module and a motion control module, wherein,
an inter-vehicle communication module for receiving and transmitting status information between vehicles through a Global Positioning System (GPS) and vehicle-to-vehicle (V2V) communication;
the information acquisition module is used for acquiring information including speed, position and acceleration of the autonomous vehicles and the queue vehicles, and calculating the actual distance between the front vehicle and the autonomous vehicles, the relative speed between the front vehicle and the autonomous vehicles, the relative acceleration between the front vehicle and the autonomous vehicles and the error change rate according to the acquired information;
the cooperative decision-making module is used for taking the relative inter-vehicle distance between the front vehicle and the autonomous vehicle and the inter-vehicle distance error as input, ignoring the vehicle state information beyond the upper bound of the communication time delay according to the expected inter-vehicle distance and the actual inter-vehicle distance error and by combining a workshop kinematics model, and adopting the available vehicle state information within the communication time delay range for ensuring the stability of the queue;
the motion control module comprises a control decision module, a fuzzy controller and a PID (proportion integration differentiation) controller and is used for controlling the autonomous vehicle to drive along with the front vehicle at a desired speed and keeping a safe distance between vehicles;
the control decision module determines the acceleration and deceleration behaviors of the autonomous vehicle according to the expected inter-vehicle distance and the inter-vehicle distance error;
the fuzzy controller dynamically outputs three PID parameters according to the expected inter-vehicle distance error and the change rate of the expected inter-vehicle distance error;
and the PID controller controls the autonomous vehicle according to the PID parameters output by the fuzzy controller in a motion control mode determined by the control decision layer.
2. The longitudinal queue associated vehicle system under the influence of communication delay of claim 1, wherein the safe distance model designs the control target to be inter-vehicle distance error and speed error according to the relative speed of the preceding vehicle and the autonomous vehicle, the communication delay and the associated system characteristics provided by the vehicle state acquisition module.
3. The longitudinal queue-related vehicle system under the influence of the communication delay of claim 1, wherein the workshop kinematics model is based on a one-way strong coupling characteristic, describes a longitudinal queue control problem with a CACC function into a discrete state space equation under the influence of the communication delay, and constructs the longitudinal queue-related vehicle system under the influence of the communication delay.
4. The longitudinal queue-associated vehicle system under the influence of communication delay according to claim 1, wherein the fuzzy controller performs fuzzy quantization on the deviation between the expected inter-vehicle distance and the actual inter-vehicle distance and the error change rate of the inter-vehicle distance by using a membership function based on a vehicle kinematics model to obtain a fuzzy input quantity and output a coefficient value of the PID controller.
5. A fuzzy control method of a longitudinal queue correlation vehicle system under the influence of communication time delay is applied to the longitudinal correlation system under the influence of communication time delay as claimed in claim 1, and is characterized by comprising the following steps:
a. acquiring motion state information of front vehicles and autonomous vehicles in a queue, acquiring position, speed and acceleration information in the driving and braking processes of the vehicles by using a sensor and a wireless communication technology, and calculating to obtain speed errors, acceleration errors and error change rates of other vehicles;
b. designing a control target, and designing the communication delay, the association characteristic fusion and the inter-vehicle distance error as the control target through the acquired information including the position, the vehicle speed and the acceleration;
c. acquiring an upper communication delay bound;
d. designing a PID controller.
6. The fuzzy control method of the longitudinal queue-related vehicle system under the influence of the communication delay according to claim 5, wherein the step c of obtaining the upper limit of the communication delay comprises the following sub-steps,
c-1, establishing a longitudinal queue correlation system model under the influence of communication time delay, describing a longitudinal queue control problem with a CACC function into a discrete correlation system under the influence of communication time delay from the characteristic of one-way strong coupling, and constructing a CACC correlation system model of the queue vehicle under the influence of communication time delay;
and c-2, performing stability analysis on the longitudinal correlation system model established in the step c-1 by using a partial decomposition method and a Lyapunov function method to obtain an upper communication delay bound for ensuring the stability of the correlation queue.
7. The fuzzy control method of the vehicle system related to the longitudinal queue under the influence of the communication time delay as claimed in claim 5, wherein the design of the PID controller in the step d is as follows,
designing input quantity of the fuzzy controller: fuzzy quantizing the obtained inter-vehicle distance error and the inter-vehicle distance error change rate by utilizing a membership function to obtain two corresponding fuzzy input quantities, wherein the fuzzy language values of the inter-vehicle distance error and the inter-vehicle distance error change rate are L, M, S and ZO, wherein L represents large, M represents moderate, S represents small, ZO represents zero, and a fuzzy controller conducts fuzzy reasoning according to a designed fuzzy control rule and obtains a fuzzy output quantity;
the stability of the whole CACC queue is controlled by combining the inter-vehicle distance control and the communication time delay, and a PID controller u is designed as follows:
u(k)＝KP*e(k)+KI*∑e(k)+KD(e (K +1) -e (K)), wherein KPIs a proportionality coefficient, KIIs the integral coefficient, KDIs a differential coefficient.
8. The method of claim 7, wherein a Gaussian membership function is used for input variables and a triangular membership function is used for output variables.
9. The fuzzy control method of the longitudinal queue-associated vehicle system under the influence of the communication delay of claim 7, wherein the fuzzy control rule comprises,
when the error of the distance between the vehicles is overlarge, the response speed of the rear vehicle is accelerated, and the over-range control effect caused when the CACC queue system starts is avoided;
when the error of the distance between the vehicles is too small, the proportional coefficient and the integral coefficient are adjusted, so that the CACC queue association system has good steady-state performance, and meanwhile, the differential coefficient is adjusted, so that the system is prevented from vibrating at a balance point;
when the distance error is in a medium size, the response overshoot of the CACC queue association system is slightly reduced, and the response speed of the CACC queue system is ensured.
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