A vehicle platoon following control method and device for mixed traffic

Abstract

The application discloses a kind of vehicle queue follow car control method and device for mixed traffic, technical solution main point is that controlled vehicle obtains vehicle real-time state information by information collection device;Based on formation control device, vehicle queue including control vehicle is formed;In mode control device, the kinematics constraint of controlled vehicle is obtained, and the working mode and optimal control input of controlled vehicle are planned in SMPC controller;In robust control device, queue stability robust control algorithm is used to realize the stable control of queue system.The vehicle queue follow car control method and device are better to realize mixed traffic environment vehicle queue stability control under the interference influence of adjacent lane random behavior of manned car, system parameter uncertainty, nonlinear fluctuation of front car and external environment, give full play to the traffic efficiency advantage of vehicle queue, improve the efficiency and safety of car driving under mixed traffic environment.

Description

Technical Field

[0001] This application belongs to the field of intelligent transportation system control, specifically relating to vehicle queuing control technology, and particularly to a vehicle queuing following control method and device for mixed traffic. Background Technology

[0002] With the rapid development of technologies in communication, sensing, and control, transportation systems are increasingly moving towards intelligentization. As a crucial component of intelligent transportation systems, intelligent connected vehicles (ICVs) hold significant research importance for realizing intelligent transportation. Based on the substantial advantages of ICVs in road safety, traffic efficiency, energy conservation, and emission reduction, more and more ICVs will be on the road in the future, and their market share will continue to rise. However, due to constraints in economic, technological, and legal development, a fully realized road traffic system composed entirely of ICVs is still a long way off. A mixed traffic environment where ICVs and human-driven vehicles share the same roads will inevitably emerge. Therefore, addressing the impact of the random behavior of human-driven vehicles on ICVs is extremely important.

[0003] Based on considerations of road safety, traffic efficiency, and energy conservation and emission reduction, researchers have developed various advanced vehicle motion modes and control methods for intelligent connected vehicles, including vehicle platooning technology. Through real-time vehicle-to-vehicle information exchange and advanced vehicle autonomous control, vehicles in a platoon can easily achieve beyond-line-of-sight environmental perception and form a stable and compact vehicle spacing, thereby reducing wind resistance, achieving energy conservation and emission reduction, greatly improving traffic efficiency, and ensuring vehicle driving safety.

[0004] In mixed traffic environments, both intelligent connected vehicles (ICVs) and human-driven vehicles (HDVs) exist. Intelligent connected vehicles are defined as ICVs, and human-driven vehicles as HDVs. In mixed traffic environments, vehicle queuing systems are inevitably affected by the random behavior of human-driven vehicles. Researchers have focused on this issue and proposed various methods for controlling vehicle queuing stability under the influence of unknown disturbances.

[0005] However, current vehicle platoon stability control methods for mixed traffic environments only consider the impact of speed fluctuations of vehicles in the same lane of the platoon, while ignoring the impact of random behaviors such as overtaking, lane changing, and cutting in from adjacent lanes on the driving stability and platoon structure of the vehicle platoon.

[0006] Therefore, there is an urgent need for a vehicle platooning control method and device for mixed traffic, which is of great significance for ensuring the stability of vehicle platoons in mixed traffic environments and the driving safety of intelligent connected vehicles. Summary of the Invention

[0007] The purpose of this invention is to address the aforementioned technical problems by providing a vehicle queuing and following control method and apparatus for mixed traffic.

[0008] The technical solution of this invention: This invention discloses a vehicle platooning following control method for mixed traffic, comprising the following steps: when the controlled vehicle is within a safe distance from the vehicle in front, does not exceed the maximum driving speed, and the front bumper of the adjacent HDV vehicle is behind the front bumper of the controlled vehicle or in front of the rear bumper of the vehicle in front, a mixed vehicle platooning stability robust control algorithm is run:

[0009] Under conditions of system parameter uncertainty, unexpected traffic environmental disturbances, nonlinear fluctuations of vehicles ahead, crosswinds, and road slope, a hybrid traffic closed-loop system with dynamic output feedback is established, based on H... ∞ Robust control methods are used to construct robust controllers for hybrid vehicle platoon stability.

[0010] The stability criterion for the vehicle queue in a mixed traffic environment is obtained based on the stability controller, and the vehicle queue is stabilized and controlled according to the stability criterion.

[0011] Furthermore, the method includes the following steps:

[0012] Step 1: Select the ICV vehicle as the controlled vehicle, and at any time, obtain the real-time status information of the vehicle itself, the lead vehicle, and adjacent vehicles through the information collection device.

[0013] Step 2: Establish a vehicle queue that includes control vehicles;

[0014] Step 3: Set the vehicle operating mode including stable following, emergency braking, hazard warning, transition and lane changing. Obtain the kinematic constraints of the controlled vehicle in the mode control device. Based on the information received by the information acquisition device and the discrete hybrid traffic queuing system, plan the operating mode and optimal control input of the controlled vehicle in the SMPC controller. Send the current operating mode of the controlled vehicle to the mode selector and send the optimal control input to the execution unit.

[0015] Step 4: When the controlled vehicle is in a stable following mode, determine the queue type of the controlled vehicle, and based on the determination, use the queue stability robust control algorithm in the robust control device to achieve stable control of the queue system.

[0016] Furthermore, the robust controller for hybrid vehicle platoon stability is designed as follows:

[0017] When the controlled vehicle is in a mixed vehicle platoon consisting of ICVs and HDVs in a mixed traffic environment, the dynamic model of the mixed traffic system based on disturbances and model parameter uncertainties, and the dynamic expression of the designed dynamic output feedback controller, the closed-loop system of the mixed traffic system with dynamic output feedback is as follows:

[0018]

[0019]

[0020] in,

[0021] w(t) represents the disturbance quantity of the queuing system, including nonlinear fluctuations from vehicles ahead, crosswinds, road slope, and other disturbances; x(t) = [x1(t),…,x n (t)] T Let x be the state variable of the queue system. k (t) represents the controller state variable;

[0022] A, B, B w C, C z and D z Let A be the coefficient matrix of the queue system. k B k and C k The coefficient matrix for the dynamic output feedback controller;

[0023] Define A = A N +ΔA, where A N =[a ij ] is the nominal matrix, a ij =(a ij,max +a ij,min ) / 2, a ij,max and a ij,min Let A be the maximum and minimum values ​​of all values ​​in the i-th row and j-th column of A;

[0024] ΔA is the model uncertainty parameter matrix, ΔA=LFR, where L and R are given matrices, and F satisfies F T F≤I;

[0025] The expression for the robust controller for the stability of the hybrid vehicle platoon is:

[0026]

[0027] in,

[0028]

[0029] In the formula, F1 represents the expression containing X and A. N B The linear terms, F2, contain Y and A. N B linear terms, X, Y, M, and N are parameter matrices of appropriate dimensions, and η1, η2, and η3 are positive scalars.

[0030] Furthermore, the vehicle queuing stability criterion in the mixed traffic environment is as follows:

[0031] For a mixed vehicle queue with non-zero disturbance w(t) ∈ L2[0,∞), given matrices L and R, if there exist any appropriate dimension matrices X, Y, M, and N, and positive scalars η1, η2, and η3 satisfying max||z(t)||2 / ||w(t)||2<γ and Π1>0, Π2<0, i.e., when Π1>0 and Π2<0 have feasible solutions, then the controller coefficient matrix A can be obtained. k B k and C k Ensure that the hybrid vehicle queuing system is asymptotically stable under w(t)∈L2[0,∞); and that the hybrid vehicle queuing system is completely L2-average stable when there are feasible solutions for Π1>0 and Π2<0 under the condition 0<γ<1.

[0032] Furthermore, the mode selector identifies the working mode vector represented in binary encoding.

[0033] ε i =[ε F,i ε B,i ε D,i ε T,i ε C,i ] T

[0034] Where, ε F,i ε B,i ε D,i ε T,i and ε C,i These represent the activation status of the stable following mode, emergency braking mode, hazard warning mode, transition mode, and lane change mode, respectively. A value of 1 indicates that the mode is active, and a value of 0 indicates that the mode is frozen. |ε i |=1;

[0035] The establishment of the discrete hybrid traffic queuing system is as follows:

[0036] x i (k+1)=(I+t s A i )xi (k)+t s B i u i (k)+t s C i v i-1 (k)

[0037] Where, x i (k) is the state vector of the controlled vehicle i at time k, t s For the sampling time of the controlled vehicle i, u i v is the control input for the controlled vehicle i. i-1 (k) represents the speed of vehicle i-1 at time k, A i B i and C i Let I be the system matrix of the controlled vehicle i, and let I be the identity matrix;

[0038] The established cost function is:

[0039]

[0040] In the formula, R i Q is a positive definite matrix. i For weighted matrices, Let c be the probability cost weight. B,i c represents the emergency braking cost weight. x,ij and c v,ij Let l represent the cost weights for the expected distance difference and speed difference between vehicle i and vehicle j, respectively. g Let g be the length of the vehicle.

[0041] The defined optimization problem is:

[0042]

[0043] The SMPC control solves for the operating mode of the controlled vehicle i at time k. and optimal control input And Send to the mode selector to select the appropriate mode; input the optimal control value as the first value. Send to the execution unit to adjust the control input of the controlled vehicle.

[0044] Furthermore, obtaining the kinematic constraints of the controlled vehicle includes obtaining the acceleration range α of the controlled vehicle based on vehicle state information and passenger comfort requirements. i ∈[a i,min ,a i,max and control limits

[0045] Based on the current speed limits of the roads, the speed limit range v for the controlled vehicles is set. i ∈[0,v max ];

[0046] Based on collision avoidance considerations, a distance limit d is set between the controlled vehicle and the vehicle in front. i ≥d min ;

[0047] Based on the current vehicle spacing strategy adopted in the vehicle platoon, the expected value of the spacing limit between the controlled vehicle and the lead vehicle is calculated in real time.

[0048] Based on the vehicle information transmission status in the queue, obtain the communication topology of the queue.

[0049] Furthermore, the vehicle convoy is a convoy consisting of an ICV as the lead vehicle and ICVs and / or HDVs as follower vehicles, wherein the ICVs are all ahead of the HDVs in the vehicle convoy.

[0050] Furthermore, the emergency braking mode includes: when the controlled vehicle i detects its distance d relative to the preceding vehicle i-1. i Below the minimum safe distance d min At time, or vehicle speed v i Exceeding the maximum driving speed v max When the SMPC controller obtains status information from the information acquisition device, it switches the operating mode to emergency braking mode by calculating the command mode selector, and commands vehicle i to brake at maximum braking deceleration to prevent a collision; until the distance between vehicles and the vehicle speed return to within the safe threshold, the mode selector switches back to the previous operating mode.

[0051] The hazard warning mode includes: when the controlled vehicle i detects that an HDV in an adjacent lane is overtaking it (i.e., the front bumper of the HDV is beyond the front bumper of the controlled vehicle i) and there is a possibility that the HDV will change lanes and insert itself between the controlled vehicle i and the vehicle in front of it (i-1), the SMPC controller obtains status information from the information acquisition device, switches the operating mode to hazard warning mode through the command mode selector, obtains the vehicle status information of the HDV through the information acquisition device, and calculates the probability P of the HDV changing lanes and inserting itself in front of the controlled vehicle in real time through the lane change probability prediction method. i If the HDV lane-changing insertion probability P i Reaching or exceeding the predetermined value When this happens, the SMPC controller command mode selector immediately switches to transition mode; if the HDV lane change insertion probability P i Less than the predetermined value Furthermore, when the front bumper position passes the rear bumper position of vehicle i-1, the SMPC controller commands the mode selector to terminate the hazard warning mode and switch back to the stable following mode.

[0052] The transition mode includes: when the probability P of the HDV changing lanes and cutting in front of the controlled vehicle is determined, i Reaching or exceeding the predetermined value When the HDV is considered the new leading vehicle of the controlled vehicle i, the SMPC controller adjusts the distance between the controlled vehicle and the HDV based on the relative status of the controlled vehicle and the HDV obtained by the information acquisition device and the following strategy. When the HDV crosses the lane line and enters the front of the controlled vehicle, the SMPC controller obtains the status information from the information acquisition device, maintains the active state of the hazard mode by calculating the command mode selector, and starts the lane change mode when appropriate. When the HDV does not cross the lane line and its rear bumper position exceeds the rear bumper position of vehicle i-1, the controlled vehicle is adjusted to follow the original vehicle i-1, the SMPC controller command mode selector terminates the transition mode and switches back to the stable following mode.

[0053] The lane-changing mode includes: after the HDV lane-changing vehicle inserts in front of the controlled vehicle, the controlled vehicle cannot achieve the expected distance from the original following vehicle i-1 in the queue, and no longer reflects the technical advantages of the controlled vehicle in the queue in terms of good road throughput and energy utilization; at this time, the SMPC controller commands the mode selector to switch to the lane-changing mode, and after the lane change is successful, it returns to step two.

[0054] To ensure collision-free lane changing, the controlled vehicle should consider the HDV in the target lane; for example, if the controlled vehicle decides to change lanes to an adjacent lane, it should consider the position and speed of the HDV behind it in the adjacent lane to avoid possible collisions; when there are no vehicles in the target lane behind the controlled vehicle, or when the controlled vehicle can maintain the minimum safe distance from the HDV during the lane change, the SMPC controller obtains status information from the information acquisition device, terminates the transition mode by calculating the command mode selector, and activates the lane changing mode.

[0055] Stable following mode: When the controlled vehicle does not meet the conditions of the other four working modes, the SMPC controller commands the mode selector to remain in stable following mode and proceed to step four for stable following control.

[0056] Furthermore, the operating mode priority is set as follows: emergency braking mode has the highest priority, and stable following mode has the lowest priority.

[0057] The present invention also discloses a vehicle platooning and following control device for mixed traffic, including an information acquisition device, a platooning control device, a robust control device, and a mode control device; the mode control device includes an SMPC controller, a mode selector, and an execution unit.

[0058] The SMPC controller is used to calculate the operating mode and optimal control input of the controlled vehicle and send them to the mode selector and the execution unit; the SMPC controller stores at least one instruction, which is loaded and executed by the data processing module to realize the above-mentioned vehicle platooning and following control method for mixed traffic.

[0059] The mode selector includes the aforementioned operating modes and identifies the operating mode vector represented in binary code.

[0060] The beneficial effects of this application are as follows:

[0061] (1) In order to solve the impact of random behavior of human-driven vehicles in adjacent lanes on the driving stability and queue structure of vehicle queues, this application proposes a SMPC control method based on the planning working mode of discrete hybrid traffic queue system. Under the premise of fully considering the actual traffic conditions and the existing technology level, it realizes the stability control of vehicle queues in mixed traffic environments affected by random behavior of human-driven vehicles in adjacent lanes, uncertainty of queue system parameters, nonlinear fluctuations of vehicles in front and external environment, so as to give full play to the traffic efficiency advantage of vehicle queues and improve the efficiency and safety of vehicle driving in mixed traffic environments.

[0062] (2) In order to adapt to different behaviors of manned vehicles, this application proposes a mode control device with five working modes. In order to ensure that the working modes are easy to identify and receive SMPC controller planning information, a mode selector that identifies binary codes is proposed.

[0063] (3) To address the problem of mixed vehicle queuing stability control under mixed traffic environments affected by queuing system uncertainties and external disturbances, this application proposes a method based on H ∞ Dynamic output feedback control method based on robust control theory;

[0064] (4) This application considers the uncertainties of the mixed traffic environment queuing system, the nonlinear fluctuations of the vehicles ahead and the interference of the external environment. The nonlinear fluctuations of the vehicles and the interference of the external environment are added to the vehicle acceleration disturbance signal to characterize the uncertainty of the queuing system, thereby optimizing the queuing system model in the mixed traffic environment and reducing the impact of uncertainty and interference. Attached Figure Description

[0065] Figure 1 This is a flowchart of the method described in this application;

[0066] Figure 2 This is a connection diagram of the device described in this application;

[0067] Figure 3 This is a schematic diagram of vehicle queue types in a specific embodiment of this application;

[0068] in, Figure 3 (a) is a vehicle platoon consisting entirely of ICVs. Figure 3 (b) is a vehicle convoy consisting of ICVs as lead vehicles, ICVs and HDVs as follower vehicles, with all ICVs preceding the HDVs. Figure 3 (c) is a vehicle platoon consisting of ICVs as lead vehicles and HDVs as follower vehicles;

[0069] Figure 4 This is a schematic diagram of the vehicle queue constructed in a specific embodiment of this application in a real road scenario;

[0070] Figure 5 These are schematic diagrams illustrating different working modes in specific embodiments of this application;

[0071] in, Figure 5 (a) is the critical state for activating the danger warning mode. Figure 5 (b) is the process state under the hazard warning mode. Figure 5 (c) is the frozen critical state of the danger warning mode. Figure 5 (d) represents the process state of the transition mode. Figure 5 (e) represents the process state of lane-changing mode. Detailed Implementation

[0072] The technical solution of this application will be described in detail below with reference to the accompanying drawings.

[0073] Figure 1 This is a general block diagram of a vehicle platooning and following control method and device for mixed traffic. The system used in the vehicle platooning and following control method for mixed traffic provided in this application includes any controlled vehicle in the lane, which is a smart connected vehicle, and its state is completely observable and controllable. Furthermore, each controlled vehicle is equipped with an information acquisition device, a platooning control device, a mode control device, and a robust control device. The connection method of the devices is as follows... Figure 2 As shown.

[0074] Considering existing vehicle platoon stability control technologies, and addressing the issue of how the random behavior of adjacent lanes' driven vehicles affects the driving stability and platoon structure of vehicle platoons under current technological conditions, this application aims to provide a vehicle platoon following control method and device for mixed traffic. This method achieves stability control of vehicle platoons in mixed traffic environments affected by random behavior of adjacent lanes' driven vehicles, uncertainties in platoon system parameters, nonlinear fluctuations of vehicles ahead, and external environmental disturbances. The goal is to fully leverage the traffic efficiency advantages of vehicle platoons and improve the efficiency and safety of vehicle driving in mixed traffic environments.

[0075] In a mixed traffic environment, there are intelligent connected vehicles and manned vehicles. Intelligent connected vehicles are defined as ICVs, and manned vehicles as HDVs. In this application, all controlled vehicles are ICVs, and the platooning control device, mode control device, and robust control device described in the application exist only within ICVs.

[0076] Example:

[0077] Due to the shortcomings of existing technologies, such as Figure 1 As shown, this application discloses a vehicle platooning and following control method and apparatus for mixed traffic, comprising:

[0078] Step 1: Select the ICV vehicle as the controlled vehicle, and at any time, obtain the real-time status information of the vehicle itself, the lead vehicle, and adjacent vehicles through the information collection device.

[0079] The information acquisition device in step one includes wireless communication equipment and vehicle sensors. The wireless communication equipment includes a vehicle-to-vehicle communication module (DSRC) based on dedicated short-range communication technology and a wireless information transmission module (WiFi). The vehicle sensors include GPS, INS, wheel speed encoders, radar, and cameras, etc.

[0080] Both ICVs and HDVs can obtain their own position, speed, and acceleration information through GPS, INS, and wheel speed encoders, and obtain status data such as relative position and relative speed with the vehicle in front through radar and cameras;

[0081] ICVs can obtain status information such as the position and speed of other vehicles in the vehicle queue through wireless communication devices, transmit the status data of themselves and other vehicles they have acquired through wireless communication devices, and obtain the current road traffic status and speed limit information through WiFi and cameras.

[0082] HDV can only transmit the status data of itself and other vehicles it has acquired to the surrounding ICVs via wireless communication devices.

[0083] Step 2: Establish a vehicle queue including the controlled vehicle. The controlled vehicle determines whether it is in the vehicle queue in the queue control device. If it is, proceed to Step 3. Otherwise, perform vehicle queue control and then proceed to Step 3.

[0084] Considering the significant technological advantages of ICVs over HDVs in terms of road throughput and energy efficiency, regulations stipulate that only the following are permitted: Figure 3 (a) shows a vehicle convoy consisting entirely of ICVs; as shown in the image. Figure 3 (b) shows a convoy of vehicles with ICVs as the lead vehicle, ICVs and HDVs as follower vehicles, and all ICVs are ahead of the HDVs; and as shown in Figure 1. Figure 3(c) shows a vehicle convoy consisting of ICVs as lead vehicles and HDVs as follower vehicles.

[0085] Step two, vehicle platooning control, enables the controlled vehicle to form platoons with other ICVs, such as... Figure 3 (a) or Figure 3 (b) shows the vehicle queue. The vehicle queuing control of the vehicle queue is an existing control method (such as application number: 202210009545.3, invention title: a multi-vehicle cooperative control method and device to ensure stable rapid vehicle queuing), which will not be described in detail here.

[0086] like Figure 3 and Figure 4 In a vehicle convoy with an ICV as the lead vehicle and ICVs and / or HDVs as follower vehicles, assume the convoy containing the controlled vehicle consists of N vehicles, including ICVs and HDVs; define the lead vehicle as number 1, and the follower vehicles as numbered 2 to N. Assume the controlled vehicle is numbered i (1≤i≤n), where n is the number of ICVs in the convoy (1≤n≤N).

[0087] Step 3: Set vehicle operating modes including stable following, emergency braking, hazard warning, transition, and lane changing in the mode control device, acquire the kinematic constraints of the controlled vehicle, and plan the operating mode and optimal control input of the controlled vehicle in the SMPC controller based on the information received by the information acquisition device and the discrete hybrid traffic queuing system. Send the current operating mode of the controlled vehicle to the mode selector and send the optimal control input to the execution unit. The execution unit controls the front wheel steering angle, brake hydraulic cylinder oil pressure, and drive motor current of the controlled vehicle according to the optimal control input.

[0088] Step three involves obtaining the kinematic constraints of the controlled vehicle as follows: Based on the vehicle state information and passenger comfort requirements, the acceleration range 'a' of the controlled vehicle is obtained. i ∈[a i,min ,a i,max and control limits

[0089] Based on the current speed limits of the roads, the speed limit range v for the controlled vehicles is set. i ∈[0,v max ];

[0090] Based on collision avoidance considerations, a distance limit d is set between the controlled vehicle and the vehicle in front. i ≥d min ;

[0091] Based on the current vehicle spacing strategy adopted in the vehicle platoon, such as fixed spacing strategy, fixed time spacing strategy, and variable spacing strategy based on energy optimization, the expected value of the spacing limit between the controlled vehicle and the lead vehicle is calculated in real time.

[0092] Based on the vehicle information transmission status in the queue, obtain the communication topology of the queue.

[0093] Among them, a i a is the acceleration of the controlled vehicle; i,min a is the maximum braking deceleration of the controlled vehicle, which is a negative value; i,max The maximum forward acceleration of the controlled vehicle; The control input for the controlled vehicle i; u i,min and u i,max To control the upper and lower bounds of the input quantity; v i The current speed of the controlled vehicle; v max The maximum driving speed based on road speed limits and safety considerations; d i The real-time distance between the controlled vehicle and the vehicle in front is represented as follows: Figure 4 As shown; d min This refers to the minimum distance between vehicles based on collision avoidance considerations.

[0094] In step three, the information collected by the information acquisition device includes vehicle information in the lane where the controlled vehicle is located and vehicle information in adjacent lanes. The lane where the controlled vehicle is located is the lane where the vehicle platoon is located, denoted as lane 1, and the adjacent lane is denoted as lane 2, such as... Figure 5 As shown.

[0095] The operating modes of the controlled vehicle in step three include: stable following mode, emergency braking mode, hazard warning mode, transition mode, and lane changing mode.

[0096] The following is a detailed explanation of these five working modes:

[0097] Emergency braking mode: When the controlled vehicle i detects its distance d relative to the preceding vehicle i-1. i Below the minimum safe distance d min At time, or vehicle speed v i Exceeding the maximum driving speed v max At this time, the SMPC controller obtains status information from the information acquisition device, calculates the command mode selector, switches the operating mode to emergency braking mode, and commands vehicle i to brake at maximum braking deceleration to prevent a collision. The mode selector switches back to the previous operating mode until the distance between vehicles and the vehicle speed return to within the safe threshold.

[0098] Hazard Warning Mode: When the controlled vehicle i detects that an HDV in adjacent lane 2 is overtaking it (i.e., the front bumper of the HDV is beyond the front bumper of the controlled vehicle i), its actual behavior is as follows: Figure 5 As shown in (b), Figure 5(a) shows the critical position) and when there is a possibility of changing lanes and inserting between the controlled vehicle i and its preceding vehicle i-1, the SMPC controller obtains status information from the information acquisition device, switches the operating mode to the danger warning mode by calculating the command mode selector, obtains the vehicle status information of this HDV through the information acquisition device, and calculates in real time the probability P of the HDV changing lanes and inserting in front of the controlled vehicle using the lane change probability prediction method. i If the HDV lane-changing insertion probability P i Reaching or exceeding the predetermined value When this happens, the SMPC controller command mode selector immediately switches to transition mode; if the HDV lane change insertion probability P i Less than the predetermined value Furthermore, its front bumper extends beyond the rear bumper of vehicle i-1. Figure 5 When (c) is at its critical position, the SMPC controller commands the mode selector to terminate the hazard warning mode and switch back to the stable following mode.

[0099] The lane-changing probability prediction method is an existing technology, such as the application number: 202110151796.0, the invention title: Prediction method of motor vehicle lane-changing behavior, which will not be elaborated here.

[0100] Transition mode: When determining the probability P of HDV changing lanes and cutting in front of the controlled vehicle. i Reaching or exceeding the predetermined value At any given time, this HDV is considered the new preceding vehicle of the controlled vehicle i. Based on the relative status between the controlled vehicle and this HDV obtained by the information collection device, and in conjunction with the following strategy, the distance between the controlled vehicle and the HDV is adjusted. When the HDV crosses the lane line and enters in front of the controlled vehicle (e.g., ... Figure 5 When (d) is in effect, the SMPC controller obtains status information from the information acquisition device, maintains the hazard mode active state through the calculation command mode selector, and initiates the lane change mode when appropriate; when the HDV has not crossed the lane line and its rear bumper position exceeds the rear bumper position of vehicle i-1 (e.g., Figure 5 When (c) is shown, the controlled vehicle is adjusted to follow the original vehicle i-1, the SMPC controller command mode selector terminates the transition mode and switches back to the stable following mode.

[0101] Lane-changing mode: After the HDV changes lanes and inserts in front of the controlled vehicle, the controlled vehicle can no longer achieve the expected distance from the original following vehicle i-1 in the queue, thus no longer demonstrating the technical advantages of the controlled vehicle's good road throughput and energy utilization in the queue. At this time, the SMPC controller commands the mode selector to switch to lane-changing mode. After a successful lane change, it returns to step two.

[0102] To ensure a collision-free lane change, the controlled vehicle should take into account the HDV in the target lane.

[0103] For example, in Figure 5 In (e), if the controlled vehicle decides to change lanes to lane 2, the position and speed of the HDV behind it in lane 2 should be taken into account in order to avoid a possible collision.

[0104] When there are no vehicles in the target lane behind the controlled vehicle, or when the controlled vehicle can maintain the minimum safe distance from the HDV during the lane change process, the SMPC controller obtains status information from the information acquisition device, terminates the transition mode by calculating the command mode selector, and activates the lane change mode.

[0105] Stable following mode: When the controlled vehicle does not meet the conditions of the other four working modes, the SMPC controller commands the mode selector to remain in stable following mode and proceed to step four for stable following control.

[0106] For driving safety considerations, the operating mode priority is set as follows: emergency braking mode has the highest priority, and stable following mode has the lowest priority.

[0107] The mode selector identifies the working mode vector represented in binary code.

[0108] ε i =[ε F,i ε B,i ε D,i ε T,i ε C,i ] T

[0109] Where, ε F,i ε B,i ε D,i ε T,i and ε C,i These represent the activation status of the stable following mode, emergency braking mode, hazard warning mode, transition mode, and lane change mode, respectively. A value of 1 indicates that the mode is active, and a value of 0 indicates that the mode is frozen. ||ε i ||2=1.

[0110] In step three, the SMPC control method is to establish the cost function and optimization problem of the optimal control problem in the finite prediction time domain at time k, and solve for the current operating mode and optimal control input of the controlled vehicle.

[0111] The discrete hybrid traffic queuing system is established as follows:

[0112] x i (k+1)=(I+t s A i )x i (k)+t s B i ui (k)+t s C i v i-1 (k)

[0113] Where, x i (k) is the state vector of the controlled vehicle i at time k, t s For the sampling time of the controlled vehicle i, u i v is the control input for the controlled vehicle i. i-1 (k) represents the speed of vehicle i-1 at time k, A i B i and C i Let I be the system matrix of the controlled vehicle i, and let I be the identity matrix.

[0114] The established cost function is:

[0115]

[0116] Among them, R i Q is a positive definite matrix. i For weighted matrices, Let c be the probability cost weight. B,i c represents the emergency braking cost weight. x,ij and c v,ij Let l represent the cost weights for the expected distance difference and speed difference between vehicle i and vehicle j, respectively. g Let g be the length of the vehicle.

[0117] The defined optimization problem is:

[0118]

[0119] The SMPC control solves for the operating mode of the controlled vehicle i at time k. and optimal control input And Send to the mode selector to select the appropriate mode; input the optimal control value as the first value. Send to the execution unit to adjust the control input of the controlled vehicle.

[0120] Step 4: When the controlled vehicle is in a stable following mode, determine the queue type of the controlled vehicle, and based on the determination, use the queue stability robust control algorithm in the robust control device to achieve stable control of the queue system.

[0121] When the controlled vehicle is in such a situation Figure 3(a) When the vehicle queue is composed entirely of ICVs, a robust stability control algorithm for a pure intelligent connected vehicle queue is run. The algorithm is an existing technology (e.g., application number: 202211036806.7, invention title: A heterogeneous vehicle queue stability control method for random vehicle-to-vehicle communication links), and will not be described in detail here.

[0122] When the controlled vehicle is in stable following mode, the vehicle convoy consists of an ICV as the lead vehicle and ICVs and HDVs as follower vehicles, such as... Figure 3 (b) and Figure 3 As shown in (c), a robust control algorithm for mixed vehicle queue stability is run for mixed traffic environments.

[0123] The robust control algorithm for mixed vehicle platoon stability in mixed traffic environments is based on H. ∞ The dynamic output feedback control algorithm based on robust control theory is designed as follows:

[0124] The controlled vehicle may be subject to unexpected disturbances in mixed traffic flow under uncertain system parameters, nonlinear fluctuations from vehicles ahead, crosswinds, road gradients, and other interferences.

[0125] Based on the dynamic model of the hybrid traffic system and the uncertainty of model parameters, and the dynamic expression of the designed dynamic output feedback controller, the closed-loop system of the hybrid traffic system with dynamic output feedback is as follows:

[0126]

[0127]

[0128] in,

[0129] w(t) represents the disturbance quantity of the queuing system, including nonlinear fluctuations from vehicles ahead, crosswinds, road slope, and other disturbances; x(t) = [x1(t),…,x n (t)] T Let x be the state variable of the queue system. k (t) represents the controller state variable;

[0130] A, B, B w C, C z and D z Let A be the coefficient matrix of the queue system. k B k and C k The coefficient matrix for the dynamic output feedback controller;

[0131] Considering the parameter uncertainties in the dynamic model of the mixed traffic system, we define A = A N +ΔA, where AN =[a ij ] is the nominal matrix, a ij =(a ij,max +a ij,min ) / 2, a ij,max and a ij,min Let A be the maximum and minimum values ​​of all values ​​in the i-th row and j-th column of A;

[0132] ΔA is the model uncertainty parameter matrix, ΔA=LFR, where L and R are given matrices, and F satisfies F T F≤I;

[0133] Based on H ∞ Based on robust control theory, a dynamic output feedback control system is designed to provide a robust stability controller for hybrid vehicle platooning under various disturbances, including system parameter uncertainties, unexpected traffic disturbances, nonlinear fluctuations of vehicles ahead, crosswinds, and road gradients. This robust stability controller is expressed as follows:

[0134]

[0135] in,

[0136] F1 contains X and A N B The linear terms, F2, contain Y and A. N B linear terms, X, Y, M, and N are parameter matrices of appropriate dimensions, and η1, η2, and η3 are positive scalars;

[0137] The stability criterion for vehicle queues in a mixed traffic environment is obtained based on the stability robust controller, and the vehicle queue is stabilized and controlled according to the stability criterion.

[0138] Specifically, the stability criterion is:

[0139] For a mixed vehicle queue with non-zero disturbance w(t) ∈ L2[0,∞), given matrices L and R, if there exist any appropriate dimension matrices X, Y, M, and N, and positive scalars η1, η2, and η3 satisfying max‖z(t)||2 / ||w(t)||2<γ and Π1>0, Π2<0, i.e., when Π1>0 and Π2<0 have feasible solutions, then the controller coefficient matrix A can be obtained. k B k and C kEnsure that the hybrid vehicle queuing system is asymptotically stable under w(t)∈L2[0,∞); and that the hybrid vehicle queuing system is completely L2-average stable when there are feasible solutions for Π1>0 and Π2<0 under the condition 0<γ<1.

[0140] Based on the dynamic output feedback control system obtained from the above solution, the control input u(t) = C is calculated. k x k (t), and transmits it to the execution unit. The execution unit controls the brake hydraulic cylinder oil pressure and drive motor current of the controlled vehicle according to the control input.

[0141] The architecture of this embodiment enables vehicle queuing stability control in mixed traffic environments affected by random behavior of manned vehicles in adjacent lanes, uncertainty of queuing system parameters, nonlinear fluctuations of vehicles ahead, and external environmental disturbances. This avoids the random behavior of manned vehicles from disrupting the stability and structure of the vehicle queuing, which is of great significance for ensuring the driving safety and efficiency of intelligent connected vehicles in mixed traffic environments.

[0142] Those skilled in the art will understand that, unless otherwise defined, all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0143] In this application, "and / or" means either the individual existence of each element or the simultaneous existence of both elements.

[0144] In this application, "connection" can mean either a direct connection between components or an indirect connection between components through other components.

[0145] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A vehicle queuing and following control method for mixed traffic, characterized in that, When the controlled vehicle is within a safe distance from the vehicle in front, does not exceed the maximum speed, and the front bumper of the HDV vehicle in the adjacent lane is behind the front bumper of the controlled vehicle or in front of the rear bumper of the vehicle in front of the controlled vehicle, the robust control algorithm for mixed vehicle platoon stability is run: Under conditions of system parameter uncertainty, unexpected traffic environmental disturbances, nonlinear fluctuations of vehicles ahead, crosswinds, and road slope, a hybrid traffic closed-loop system with dynamic output feedback is established, based on H... ∞ Robust control methods are used to construct robust controllers for hybrid vehicle platoon stability. The stability criterion for the vehicle queue in a mixed traffic environment is obtained based on the stability controller, and the vehicle queue is stabilized and controlled according to the stability criterion. The robust controller for the stability of the hybrid vehicle platoon is designed as follows: When the controlled vehicle is in a mixed vehicle platoon consisting of ICVs and HDVs in a mixed traffic environment, the dynamic model of the mixed traffic system based on disturbances and model parameter uncertainties, and the dynamic expression of the designed dynamic output feedback controller, the closed-loop system of the mixed traffic system with dynamic output feedback is as follows: ； in, , , , ; The disturbance amount in the queuing system includes nonlinear fluctuations from vehicles ahead, crosswinds, road slopes, and other disturbances. For queue system state variables, For controller state variables; A , B , , C , and Here is the coefficient matrix of the queue system. , and The coefficient matrix for the dynamic output feedback controller; definition ,in For the nominal matrix, , and for A The i Line and number j The maximum and minimum values ​​of all values ​​in the column; For the model's uncertain parameter matrix, In the formula, L and R Given a matrix, F satisfy ; The expression for the robust controller for the stability of the hybrid vehicle platoon is: ， ； in, , , ， In the formula, For containing X , , B , linear terms, For containing Y , , B , linear terms, , , X , Y , M and N For a parameter matrix of appropriate dimensions, , and It is a positive scalar; The stability criterion for vehicle platooning in the mixed traffic environment is as follows: For nonzero interference A mixed vehicle queue, for a given matrix L and R If any appropriate dimension matrix exists X , Y , M and N and positive scalar , and and satisfy and , At that time, that is and When a feasible solution exists, the controller coefficient matrix can be obtained. , and Ensure that the hybrid vehicle queuing system is in The asymptotic stability of the following; and when and exist When a feasible solution exists under certain conditions, the hybrid vehicle queuing system is completely... L 2. Average stable.

2. A vehicle queuing and following control method for mixed traffic, characterized in that, The method includes the following steps: Step 1: Select the ICV vehicle as the controlled vehicle, and at any time, obtain the real-time status information of the vehicle itself, the lead vehicle, and adjacent vehicles through the information collection device. Step 2: Establish a vehicle queue that includes control vehicles; Step 3: Set up a stable following mode, emergency braking mode, hazard warning mode, transition mode and lane changing mode. Obtain the kinematic constraints of the controlled vehicle in the mode control device. Based on the information received by the information acquisition device and the discrete hybrid traffic queuing system, plan the working mode and optimal control input of the controlled vehicle in the SMPC controller. Send the current working mode of the controlled vehicle to the mode selector and send the optimal control input to the execution unit. The mode selector identifies a working mode vector represented in binary code. ； in, , , , and These represent the activation status of the following modes: stable following mode, emergency braking mode, hazard warning mode, transition mode, and lane change mode. A value of 1 indicates that the mode is active, and a value of 0 indicates that the mode is inactive. ; The discrete hybrid traffic queuing system is established as follows: ； in, for k Vehicles under constant control i The state vector, For the controlled vehicle i Sampling time, For the controlled vehicle i The control input quantity, for k Time vehicle i -1 driving speed, , and For the controlled vehicle i The system matrix, I It is the identity matrix; The established cost function is: ； In the formula, It is a positive definite matrix. For weighted matrices, For probability cost weights, The emergency braking cost weight, and Representing vehicles i and vehicles j The cost weights of the expected distance difference and speed difference between them. For vehicles g The length of the vehicle; The defined optimization problem is: ; SMPC control in k The controlled vehicle is obtained by solving the problem in real time. i working mode and optimal control input and will Send to the mode selector to select the appropriate mode; input the optimal control value as the first value. Send to the execution unit to adjust the control input of the controlled vehicle. ; The danger warning mode is as follows: when an adjacent lane HDV is overtaking a controlled vehicle and there is a possibility that it will change lanes and insert itself between the controlled vehicle and the vehicle in front of it, the vehicle status information of the HDV is obtained through the information collection device, and the probability of the HDV changing lanes and inserting itself in front of the controlled vehicle is calculated in real time through the lane change probability prediction method. The transition mode is as follows: when the probability of the HDV changing lanes and inserting in front of the controlled vehicle reaches or exceeds a predetermined value, the HDV is used as the new leading vehicle of the controlled vehicle, and the distance between the controlled vehicle and the HDV is adjusted according to the relative state between the controlled vehicle and the HDV, combined with the following strategy. Step 4: When the controlled vehicle is in a stable following mode, determine the queue type of the controlled vehicle, and based on the determination, use the queue stability robust control algorithm in the robust control device to achieve stable control of the queue system.

3. The vehicle queuing and following control method for mixed traffic according to claim 2, characterized in that, The process of obtaining the kinematic constraints of the controlled vehicle includes obtaining the acceleration range of the controlled vehicle based on vehicle state information and passenger comfort requirements. and control input limits ; Based on the current speed limits of the roads, the speed limit range for the controlled vehicles is set. ; Based on collision avoidance considerations, a distance limit is set between the controlled vehicle and the vehicle in front. ; Based on the current vehicle spacing strategy adopted in the vehicle platoon, the expected distance between the controlled vehicle and the lead vehicle is calculated in real time. ; Based on the vehicle information transmission status in the queue, obtain the communication topology of the queue.

4. The vehicle queuing and following control method for mixed traffic as described in any one of claims 1-3, characterized in that: The vehicle convoy is a convoy consisting of an ICV as the lead vehicle and ICVs and / or HDVs as follower vehicles, with the ICVs always preceding the HDVs in the convoy.

5. The vehicle queuing and following control method for mixed traffic as described in claim 2, characterized in that: The emergency braking mode includes: when the controlled vehicle... i It was detected relative to the vehicle in front. i -1 spacing Below the minimum safe distance At time, or vehicle speed Exceeding the maximum driving speed At this time, the SMPC controller obtains status information from the information acquisition device, switches the operating mode to emergency braking mode through the command mode selector, and commands the vehicle to... i Braking is performed at maximum deceleration to prevent a collision; the mode selector switches back to the previous operating mode once the distance between vehicles and the vehicle speed return to within the safe threshold. The danger warning mode includes: when the controlled vehicle i An HDV was detected overtaking it in an adjacent lane (i.e., the HDV's front bumper was beyond the controlled vehicle's position). i (Front bumper position) and there is a lane change and insertion into the controlled vehicle. i With the car in front i When the probability is between -1, the SMPC controller obtains status information from the information acquisition device, switches the operating mode to hazard warning mode through the command mode selector, obtains the vehicle status information of this HDV through the information acquisition device, and calculates in real time the probability of the HDV changing lanes and inserting in front of the controlled vehicle using the lane change probability prediction method. If the HDV lane-changing insertion probability Reaching or exceeding the predetermined value When this occurs, the SMPC controller command mode selector immediately switches to transition mode; if the HDV lane change insertion probability... Less than the predetermined value And its front bumper extends beyond the vehicle. i When the rear bumper is at position -1, the SMPC controller commands the mode selector to terminate the hazard warning mode and switch back to the stable following mode. The transition mode includes: when determining the probability that the HDV lane changer will cut in front of the controlled vehicle. Reaching or exceeding the predetermined value At that time, this HDV was considered the controlled vehicle. i The new leading vehicle, based on the relative status of the controlled vehicle and the HDV obtained by the information acquisition device, and in conjunction with the following strategy, adjusts the distance between the controlled vehicle and the HDV; when the HDV crosses the lane line and enters in front of the controlled vehicle, the SMPC controller obtains status information from the information acquisition device, calculates the command mode selector to maintain the hazard mode active state, and initiates the lane-changing mode when appropriate; when the HDV has not crossed the lane line and its rear bumper is beyond the vehicle... i- When the rear bumper of vehicle 1 is in position, the vehicle being followed by the controlled vehicle will be restored to the original vehicle in front. i -1, The SMPC controller command mode selector terminates the transition mode and switches back to stable following mode; The lane-changing mode includes: after the HDV changes lanes and inserts in front of the controlled vehicle, the controlled vehicle cannot reach the original vehicle in front. i The expected spacing of -1 no longer reflects the technical advantages of the controlled vehicle in the vehicle queue in terms of good road throughput and energy utilization. At this time, the SMPC controller command mode selector switches to lane-changing mode. After the lane change is successful, return to step two. To ensure collision-free lane changing, the controlled vehicle should consider the HDV in the target lane; for example, if the controlled vehicle decides to change lanes to an adjacent lane, it should consider the position and speed of the HDV behind it in the adjacent lane to avoid possible collisions; when there are no vehicles in the target lane behind the controlled vehicle, or when the controlled vehicle can maintain the minimum safe distance from the HDV during the lane change, the SMPC controller obtains status information from the information acquisition device, terminates the transition mode by calculating the command mode selector, and activates the lane changing mode. Stable following mode: When the controlled vehicle does not meet the conditions of the other four working modes, the SMPC controller commands the mode selector to remain in stable following mode and proceed to step four for stable following control.

6. The vehicle queuing and following control method for mixed traffic as described in claim 5, characterized in that: The operating mode priority is set as follows: emergency braking mode has the highest priority, and stable following mode has the lowest priority.

7. A vehicle queuing and following control device for mixed traffic, characterized in that: It includes an information acquisition device, a formation control device, a robust control device, and a mode control device; the mode control device includes an SMPC controller, a mode selector, and an execution unit; The information acquisition device is used to obtain real-time status information of the controlled vehicle itself, the lead vehicle, and adjacent vehicles. The formation control device is used to form a vehicle platoon that includes the controlled vehicles; The SMPC controller is used to plan the operating mode and optimal control input of the controlled vehicle based on the real-time status information acquired by the information acquisition device, the kinematic constraints of the controlled vehicle, and the discrete hybrid traffic queuing system, and sends the operating mode to the mode selector and the optimal control input to the execution unit. The mode selector is equipped with a stable following mode, an emergency braking mode, a hazard warning mode, a transition mode, and a lane changing mode, and is used to identify the working mode vector represented by binary code and select the corresponding working mode according to the working mode vector. The execution unit is used to adjust the control input amount of the controlled vehicle according to the optimal control input; The robust control device is used to determine the type of vehicle queue in which the controlled vehicle is located when the controlled vehicle is in a stable following mode, and to achieve stable control of the vehicle queue system by using a queue stability robust control algorithm based on the type of vehicle queue.

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