CN110979309A - Vehicle following model stability control method considering driver perception error - Google Patents

Vehicle following model stability control method considering driver perception error Download PDF

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CN110979309A
CN110979309A CN201911338200.7A CN201911338200A CN110979309A CN 110979309 A CN110979309 A CN 110979309A CN 201911338200 A CN201911338200 A CN 201911338200A CN 110979309 A CN110979309 A CN 110979309A
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张俊杰
于海洋
任毅龙
杨灿
冀浩杰
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Beihang University
Hefei Innovation Research Institute of Beihang University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/02—Control of vehicle driving stability
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/14—Adaptive cruise control
    • B60W30/16—Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
    • B60W30/165—Automatically following the path of a preceding lead vehicle, e.g. "electronic tow-bar"

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Abstract

The invention discloses a stability control method of a vehicle following model considering a driver perception error, which is used for solving the influence of the driver random perception error on the stability of a traffic flow. The method is characterized in that under the condition that information perception errors exist in the moving state of a front vehicle in the vehicle following process of a driver, vehicle head distance and front vehicle speed confidence level parameters are introduced, a vehicle following model considering the perception errors of the driver is established, and on the basis, a feedback control method is designed to enhance the stability of the model. Compared with a model without considering a feedback control method, the feedback control method can effectively improve the stability of the queue and provide technical support for the queue stability control method in the fields of traffic management and control, intelligent vehicle control and the like.

Description

Vehicle following model stability control method considering driver perception error
Technical Field
The invention relates to the field of traffic control methods, in particular to a method for controlling stability of a vehicle following model by considering a perception error of a driver.
Background
The problem of traffic congestion in the current society becomes the focus of people's attention increasingly, and a traffic flow model is used as a mathematical model capable of effectively describing traffic flow, and a vehicle following model can further reveal the mechanism of traffic congestion and describe the driving behavior characteristics of a single vehicle. Therefore, in recent years, researchers have proposed various car-following models to analyze the influence of driving behavior characteristics on traffic flow stability.
In 1953, pipe proposed a pioneering car-following model. Subsequently, Chandler et al proposed a first linear vehicle-following model with only relative velocity as the response stimulus, based on the stimulus-response conceptual model. In response to the deficiencies of the vehicle-following model proposed by Chandler et al, Gazis et al propose a GHR model that assumes that the state of motion of the rear vehicle is determined by the speed, relative speed and headway of two consecutive vehicles. In 1995, Bando et al constructed an optimal speed (OV) model with a driver's intention to maintain an optimal speed in a traffic flow as an assumption. Helbin and Tilch proposed a Generalized force model (GF), which, while avoiding the drawbacks of the optimal velocity model, still presents impractical accelerations. Thus, in 2001, Jiang et al proposed a Full speed differential control (FVD) model, which not only retained the advantages of the OV model, but also overcome the drawbacks of the GF model. Lu et al elucidates the driver's following behavior by defining the driver's perceived risk level as a Safety Margin, and proposes a Desired Safety Margin (DSM) model. Subsequently, Wang et al investigated the effect of driving behavior characteristic parameters on traffic flow through a DSM model. Through the search of the prior art documents, the influence of driving behaviors on the stability of traffic flow is researched based on OV, FVD, GF, GHR, DSM and an expansion model thereof which are widely proposed. With the development of the traffic flow theory, a plurality of new car following models are established on the basis of theoretical modeling or experimental modeling to explain the oscillation, capacity reduction, car following behavior characteristics and the like of the traffic flow. And the characteristic of the behavior of a driver during the process of following the vehicle and how to further improve the stability of the traffic flow are still the current hot problems.
Recently, Konishi et al have adopted a delayed feedback control method to improve the stability of traffic flow based on an improved coupled map trellis model (CM). Chen proposes a two-lane Optimal Velocity Feedback Control (OVFC) model to dampen velocity oscillations. Ge et al propose a modified CM model considering two consecutive headway time intervals and further propose a feedback control-based two-lane following model considering lane change behavior. Xie et al propose an Internet vehicle driver assistance strategy based on distributed feedback control to improve traffic flow stability and traffic efficiency. Although learners consider physiological and psychological characteristics and traffic environments of different drivers, establish corresponding vehicle-following models and design corresponding feedback control methods to enhance stability of the models, the prior art does not provide a method which considers perception errors of the drivers, constructs the vehicle-following models based on confidence degrees of perceived vehicle speed and vehicle-head distance and designs corresponding feedback control methods to enhance stability of the models in relevant document retrieval processes.
Disclosure of Invention
Aiming at the defects of the technology, the invention provides a method for controlling the stability of a car-following model by considering the perception error of a driver. Because the driver can cause traffic flow oscillation to the vehicle speed and the random perception error of the distance between the vehicle heads in the vehicle following process, the feedback control method designed based on the invention can effectively improve the stability of the traffic flow.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a method for controlling stability of a vehicle following model by considering a perception error of a driver is characterized by comprising the following steps: the method comprises the following steps:
(1) based on vehicle parameters and driver information in a traffic scene, a vehicle-following model FVD considering the reaction time of a driver is established, and the motion equations of the model are shown in formulas (1) and (2):
Figure BDA0002331539820000021
U(Δxn)＝v0[tanhc1(Δxn-hc)+c2](2)，
in the formulas (1) and (2), k and lambda are response sensitivity coefficients of the driver, tau is response time of the driver, and vn(t) is the speed of the vehicle n at time t, Δ xn(t) is the headway distance between vehicle n and vehicle n-1 at time t, U (-) the optimal velocity function, v0，c1，c2And hcIs a constant parameter;
(2) the method comprises the following steps of (1) introducing the confidence level of the speed of a front vehicle and the distance between the front vehicles into the vehicle following model established in the step (1) in consideration of the perception error of a driver, and establishing the vehicle following model in consideration of the perception error of the driver, wherein the motion equation of the vehicle following model is shown as a formula (3):
Figure BDA0002331539820000031
in the formula (3), α represents confidence levels, ζ (v) of the preceding vehicle speed and the vehicle-head distance, respectivelyn-1) And
Figure BDA0002331539820000033
respectively representing the standard deviation phi of the sensing errors of the speed and the distance between the two heads of the front vehicle-1(. cndot.) represents the inverse function of a standard normal distribution;
(3) and establishing a feedback control term as shown in formula (4):
Cn(t)＝γ(Δxn(t-τ*)-Δxn(t)) (4)，
in the formula (4), Cn(t) is a feedback control item of the vehicle n at the time t, gamma is an adjustable gain parameter of a sliding film controller, and tau*Is the response delay time lag of the feedback controller;
(4) introducing the feedback control item established in the step (3) into the vehicle-following model which is established in the step (2) and takes the driver perception error into consideration, and obtaining the vehicle-following model which has feedback control and takes the driver perception error into consideration, wherein the vehicle-following model is shown in a formula (5):
Figure BDA0002331539820000032
(5) and controlling the car-following stability in the traffic scene based on the car-following model obtained in the step (4).
The method for controlling the stability of the vehicle following model by considering the perception error of the driver is characterized in that confidence levels α of the speed and the distance between the front vehicles in the steps (2) to (4) are uniformly distributed.
The method for controlling stability of the vehicle following model by considering the perception error of the driver is characterized by comprising the following steps of: in the step (3), a linear stability condition of the vehicle following model considering the perception error of the driver is obtained through a linear stability analysis method, a boundary line of a model stability area and an instability area of the model at confidence levels of different front vehicle speeds and head distances is drawn on a two-dimensional phase plane of (k, tau), a feedback control item is constructed based on the principle, and the feedback control item is introduced into the vehicle following model considering the perception error of the driver, which is established in the step (2), so that the stability of the model is improved.
The method for controlling stability of the vehicle following model by considering the perception error of the driver is characterized by comprising the following steps of: in the car-following model with feedback control and considering the perception error of the driver obtained in the step (4), the speeds and positions of all the vehicles are updated according to the following rules, and the updating formulas are shown in formulas (6) and (7):
vn(t)＝vn(t-Δt)+a(t-Δt)×Δt,n＝1,2,…N (6)，
Figure BDA0002331539820000041
in equations (6) and (7), Δ t is the acceleration adjustment time.
The method for controlling stability of the vehicle following model by considering the perception error of the driver is characterized by comprising the following steps of: and (5) dynamically controlling the car following stability in the traffic scene based on the updating formula.
Compared with a vehicle following model considering the perception error of a driver, the motion equation of the vehicle following motion acceleration control method adds a feedback control term (namely, a third term of the motion equation). Because a driver perceives errors of the motion state information of a front vehicle in the actual vehicle following process, the confidence level of the speed and the distance between the front vehicle is introduced to represent the random errors of the perception information of the driver, a vehicle following model considering the perception errors of the driver is further constructed, meanwhile, the evolution law of the traffic flow under the condition of a feedback control strategy is contrastively analyzed to find, the feedback control method provided by the inventor can effectively enable the traffic flow to be more uniform, and the traffic jam phenomena of 'stop when the vehicle is stopped' and the like are prevented. The invention can help to promote the random disturbance to be gradually dissipated when the external factors interfere with the ACC or the vehicle queue control sensor so as to ensure the stability and the safety of the vehicle queue.
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Fig. 1 is a schematic diagram of vehicle queue follow-up motion in an embodiment of the invention.
FIG. 2 is a technical flow chart for constructing a stability control method of a vehicle-following model with driver perception errors taken into consideration.
Fig. 3 is a diagram of a stability comparison of a car-following model considering a driver perception error using the proposed method with feedback control and a car-following model considering a driver perception error, in which fig. 3(a) is a diagram of a box line of a vehicle headway (a car-following model considering a driver perception error) of a queue vehicle, considering that confidence of a front vehicle speed and a headway obeys a uniform distribution; fig. 3(b) is a spatiotemporal evolution diagram of velocity (vehicle-following model with feedback control method taking into account driver perception error).
Detailed Description
The invention is further illustrated with reference to the following figures and examples.
As shown in figure 1 and figure2, the invention sets the traffic situation to be simulated by the controllable guiding vehicle, and selects the value of the parameter according to the set traffic situation, including the response time tau of the driver, the acceleration sensitivity coefficient k, lambda, the confidence level of the front vehicle speed and the distance between the two heads of the driver are α and β respectively, and the perception error standard deviation of the front vehicle speed and the distance between the two heads of the driver are zeta (v is the standard deviation of the perception error of the front vehicle speed and the distance between the two heads of the drivern-1) And
Figure BDA0002331539820000042
adjustable gain parameter gamma of feedback controller, response delay time lag tau of feedback controller*。
The invention first acquires the initial states of all vehicles. And simulating the motion state of the vehicle queue when t is greater than 0, assuming that the leading vehicle moves according to a pre-specified scheme, and the following vehicle fleet operates according to a vehicle following model considering the perception error of the driver, and inspecting the motion states of all vehicles when t is greater than 0 by comparing the vehicle following model, which is introduced into a feedback control strategy and considers the perception error of the driver.
The invention discloses a method for introducing confidence levels of the speed and the distance between two front vehicles based on an FVD model under the condition of considering the existence of a driver perception error, and designing a feedback control strategy to enhance the stability of a queue, which comprises the following specific steps:
(1) establishing an FVD vehicle following model considering the reaction time of a driver:
Figure BDA0002331539820000051
U(Δxn)＝v0[tanhc1(Δxn-hc)+c2],
where k, λ are the reaction sensitivity coefficient of the driver, vn(t) is the speed of the vehicle n at time t, Δ xn(t) is the headway distance between vehicle n and vehicle n-1 at time t, U (-) the optimal velocity function, v0，c1，c2And hcIs a constant parameter.
(2) Establishing a vehicle following model considering the perception error of a driver:
Figure BDA0002331539820000052
wherein α represents confidence levels, ζ (v) of the preceding vehicle speed and the distance between the two vehiclesn-1) And
Figure BDA0002331539820000054
respectively representing the standard deviation phi of the sensing errors of the speed and the distance between the two heads of the front vehicle-1(. cndot.) represents the inverse function of a standard normal distribution.
(3) Designing a feedback control strategy:
Cn(t)＝γ(Δxn(t-τ*)-Δxn(t)).
in the formula, Cn(t) is a feedback control item of the vehicle n at the time t, gamma is an adjustable gain parameter of a sliding film controller, and tau*Is the response delay time lag of the feedback controller.
(4) Vehicle-following model with feedback control method taking into account driver perception error:
Figure BDA0002331539820000053
and deducing a linear stability condition of the car following model considering the perception error of the driver, and drawing a boundary line of the model stability area and the instability area of the model under the confidence levels of different front car speeds and head distances on a two-dimensional phase plane of (k, tau).
(5) The set traffic scene comprises N50 vehicles which are uniformly distributed on the same lane with the vehicle head distance L of 25 m. The number of the first vehicle is 1, and other vehicles are numbered in sequence according to the driving direction.
(6) The speed and position of the vehicle initial state are as follows:
Figure BDA0002331539820000061
in the formula (I), the compound is shown in the specification,
Figure BDA0002331539820000062
is a head vehicle
Figure BDA0002331539820000063
At a moment of small acceleration disturbance, subject to a 5 × 10 disturbance-2XU (-1, 1).
(7) The method comprises the following steps of (1) vehicle following model parameter value taking of a driver perception error into consideration with a feedback control method:
confidence coefficient α of the vehicle speed and the distance between the front vehicles is α -U0.3, 07;
adjustable gain parameter γ of the feedback controller: 1.5s-2；
Response delay time lag tau of feedback controller*：0.5s；
Front vehicle speed perception error standard deviation zeta (v)n-1)：0.5m/s；
Known error standard deviation of distance between heads
Figure BDA0002331539820000064
4m，
Acceleration sensitivity coefficient k: 5s-1；
Acceleration sensitivity coefficient λ: 0.1s-1，
Driver reaction time τ: 0.3 s;
other usual parameters: v. of0＝16.8m/s，c1＝0.0860m-1,c2＝0.913，hc＝25m。
Fig. 3 is a box diagram of the distance between the vehicle heads in the queue under the condition that the disturbance that the confidence coefficients of the vehicle speed and the distance between the vehicle heads obey uniform distribution, namely α -U [0.3,07] of the front vehicle is considered, and the situation that the distance between the vehicle heads of all the vehicles fluctuates greatly due to the perception error of the driver on the vehicle information under the condition that a feedback control strategy is not provided can be seen from fig. 3(a), and when a vehicle following model considering the perception error of the driver is added into the feedback control strategy, the fluctuation of the distance between the vehicle heads of all the vehicles is very small, as shown in fig. 3 (b).
The embodiments of the present invention are described only for the preferred embodiments of the present invention, and not for the limitation of the concept and scope of the present invention, and various modifications and improvements made to the technical solution of the present invention by those skilled in the art without departing from the design concept of the present invention shall fall into the protection scope of the present invention, and the technical content of the present invention which is claimed is fully set forth in the claims.

Claims (5)

1. A method for controlling stability of a vehicle following model by considering a perception error of a driver is characterized by comprising the following steps: the method comprises the following steps:
(1) based on vehicle parameters and driver information in a traffic scene, a vehicle-following model FVD considering the reaction time of a driver is established, and the motion equations of the model are shown in formulas (1) and (2):
Figure FDA0002331539810000011
U(Δxn)＝v0[tanhc1(Δxn-hc)+c2](2)，
in the formulas (1) and (2), k and lambda are response sensitivity coefficients of the driver, tau is response time of the driver, and vn(t) is the speed of the vehicle n at time t, Δ xn(t) is the headway distance between vehicle n and vehicle n-1 at time t, U (-) the optimal velocity function, v0，c1，c2And hcIs a constant parameter;
(2) the method comprises the following steps of (1) introducing the confidence level of the speed of a front vehicle and the distance between the front vehicles into the vehicle following model established in the step (1) in consideration of the perception error of a driver, and establishing the vehicle following model in consideration of the perception error of the driver, wherein the motion equation of the vehicle following model is shown as a formula (3):
Figure FDA0002331539810000012
in the formula (3), α represents confidence levels, ζ (v) of the preceding vehicle speed and the vehicle-head distance, respectivelyn-1) And
Figure FDA0002331539810000014
respectively representing the standard deviation phi of the sensing errors of the speed and the distance between the two heads of the front vehicle-1(. cndot.) represents the inverse function of a standard normal distribution;
(3) and establishing a feedback control term as shown in formula (4):
Cn(t)＝γ(Δxn(t-τ*)-Δxn(t)) (4)，
in the formula (4), Cn(t) is a feedback control item of the vehicle n at the time t, gamma is an adjustable gain parameter of a sliding film controller, and tau*Is the response delay time lag of the feedback controller;
(4) introducing the feedback control item established in the step (3) into the vehicle-following model which is established in the step (2) and takes the driver perception error into consideration, and obtaining the vehicle-following model which has feedback control and takes the driver perception error into consideration, wherein the vehicle-following model is shown in a formula (5):
Figure FDA0002331539810000013
(5) and controlling the car-following stability in the traffic scene based on the car-following model obtained in the step (4).
2. The method for controlling stability of the vehicle-following model by considering the perception error of the driver is characterized in that confidence levels α of the speed and the distance between the front vehicles in the steps (2) to (4) are subjected to uniform distribution.
3. The method for controlling stability of a vehicle-following model considering driver perception errors according to claim 1, wherein the method comprises the following steps: in the step (3), a linear stability condition of the vehicle following model considering the perception error of the driver is obtained through a linear stability analysis method, a boundary line of a model stability area and an instability area of the model at confidence levels of different front vehicle speeds and head distances is drawn on a two-dimensional phase plane of (k, tau), a feedback control item is constructed based on the principle, and the feedback control item is introduced into the vehicle following model considering the perception error of the driver, which is established in the step (2), so that the stability of the model is improved.
4. The method for controlling stability of a vehicle-following model considering driver perception errors according to claim 1, wherein the method comprises the following steps: in the car-following model with feedback control and considering the perception error of the driver obtained in the step (4), the speeds and positions of all the vehicles are updated according to the following rules, and the updating formulas are shown in formulas (6) and (7):
vn(t)＝vn(t-Δt)+a(t-Δt)×Δt,n＝1,2,…N (6)，
Figure FDA0002331539810000021
in equations (6) and (7), Δ t is the acceleration adjustment time.
5. The method for controlling stability of the vehicle-following model considering the perception error of the driver according to claim 4, wherein the method comprises the following steps: and (5) dynamically controlling the car following stability in the traffic scene based on the updating formula.
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