Trajectory tracking control method, device, equipment, medium and product

Abstract

The invention discloses a trajectory tracking control method, device and equipment, a medium and a product. The method comprises the steps that a vehicle transverse track planning function is constructed according to vehicle starting point displacement and vehicle lane changing time, and vehicle transverse displacement is determined based on pre-constructed lane changing track constraint conditions according to the vehicle transverse track planning function; according to vehicle driving information observed by different types of sensors, road adhesion coefficient estimation is carried out based on a vehicle dynamics model, and a road adhesion coefficient is obtained; constructing a trajectory tracking control target constraint condition, and constructing a trajectory tracking control target function; according to the transverse position of the vehicle, under the condition that the trajectory tracking control target constraint condition is met, the function value of the trajectory tracking control target function is controlled to meet the vehicle stability and trajectory tracking accuracy conditions. According to the technical scheme, accurate track tracking control in a vehicle driving environment is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle trajectory planning, and in particular to a trajectory tracking control method, device, equipment, medium and product. Background Art

[0002] At present, the research on lane changing strategies and trajectory tracking control of intelligent vehicles under conventional working conditions has been relatively mature. However, there are still deficiencies in the research on lane changing strategies under extreme conditions such as low-adhesion roads or high-speed driving. The road adhesion conditions in high-speed scenarios directly determine the stress conditions of the tires. Identifying the road adhesion conditions of the vehicle's current driving environment is of great significance to improving control performance. Summary of the invention

[0003] The present invention provides a trajectory tracking control method, device, equipment, medium and product to achieve precise tracking control of the trajectory in a vehicle driving environment.

[0004] According to one aspect of the present invention, a trajectory tracking control method is provided, the method comprising:

[0005] Constructing a vehicle lateral trajectory planning function according to the vehicle starting point displacement and the vehicle lane changing time, and determining the vehicle lateral displacement according to the vehicle lateral trajectory planning function and based on the pre-constructed lane changing trajectory constraint condition;

[0006] According to the vehicle driving information observed by different types of sensors, the road adhesion coefficient is estimated based on the vehicle dynamics model to obtain the road adhesion coefficient;

[0007] Constructing trajectory tracking control target constraints and constructing trajectory tracking control target functions;

[0008] According to the lateral position of the vehicle, and under the condition that the trajectory tracking control target constraint condition is satisfied, the function value of the trajectory tracking control target function is controlled to satisfy vehicle stability and trajectory tracking accuracy conditions.

[0009] According to another aspect of the present invention, a trajectory tracking control device is provided, the device comprising:

[0010] A vehicle lateral displacement determination module, used to construct a vehicle lateral trajectory planning function according to the vehicle starting point displacement and the vehicle lane change time, and determine the vehicle lateral displacement according to the vehicle lateral trajectory planning function and based on the pre-constructed lane change trajectory constraint conditions;

[0011] An adhesion coefficient determination module is used to estimate the road adhesion coefficient based on the vehicle dynamics model according to the vehicle driving information observed by different types of sensors to obtain the road adhesion coefficient;

[0012] Function construction module, used to construct trajectory tracking control target constraints and trajectory tracking control target functions;

[0013] The numerical optimization module is used to control the function value of the trajectory tracking control objective function to meet the vehicle stability and trajectory tracking accuracy conditions according to the lateral position of the vehicle and under the condition that the trajectory tracking control objective constraint is met.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the trajectory tracking control method described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the trajectory tracking control method described in any embodiment of the present invention when executed.

[0019] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the trajectory tracking control method according to any embodiment of the present invention is implemented.

[0020] The technical solution of the embodiment of the present invention estimates the road adhesion coefficient. The road adhesion coefficient greatly affects the lateral and longitudinal force characteristics of the tire. This parameter also greatly affects the control performance during the vehicle control process. Accurately estimating the road adhesion coefficient effectively improves the control effect. Design a model to predict the lateral trajectory tracking controller to improve the stability, accuracy, rapidity, safety and stability of the vehicle's lateral trajectory tracking.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 is a flow chart of a trajectory tracking control method provided according to Embodiment 1 of the present invention;

[0024] Figure 2 is a structural schematic diagram of a trajectory tracking control device provided according to Embodiment 2 of the present invention;

[0025] Figure 3 It is a structural schematic diagram of an electronic device for implementing the trajectory tracking control method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] Embodiment 1

[0029] Figure 1A flow chart of a trajectory tracking control method provided in Embodiment 1 of the present invention. This embodiment can be applied to situations where trajectory tracking control is performed by comprehensively considering the important influence of the road adhesion coefficient on driving stability and safety during high-speed driving. The method can be executed by a trajectory tracking control device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device.

[0030] It should be noted that, considering the accuracy and practical efficiency of vehicle trajectory planning, this embodiment adopts the fifth-order polynomial method for trajectory planning. In addition, considering the important influence of the road adhesion coefficient on driving stability and safety during high-speed driving, this embodiment estimates the road adhesion coefficient. Finally, considering that the vehicle is subject to various constraints in the actual driving process, which affects the precise control, the model predictive controller is designed to perform trajectory tracking control. Ultimately, the effect of improving the rapidity, accuracy, stability and safety of vehicle lane change trajectory tracking is achieved.

[0031] like Figure 1 As shown, the method includes:

[0032] S110, constructing a vehicle lateral trajectory planning function according to the vehicle starting point displacement and the vehicle lane changing time, and determining the vehicle lateral displacement according to the vehicle lateral trajectory planning function and based on the pre-constructed lane changing trajectory constraint condition.

[0033] S120 , estimating the road adhesion coefficient based on the vehicle dynamics model according to the vehicle driving information observed by different types of sensors to obtain the road adhesion coefficient.

[0034] S130, constructing trajectory tracking control target constraint conditions and constructing trajectory tracking control target function.

[0035] S140. According to the lateral position of the vehicle, and under the condition that the trajectory tracking control target constraint condition is satisfied, the function value of the trajectory tracking control target function is controlled to satisfy the vehicle stability and trajectory tracking accuracy conditions.

[0036] Trajectory planning determines the safety, stability and comfort of the vehicle's active lane-changing process, and is the basis for achieving good motion control of intelligent vehicles. The first, second and third derivatives of the quintic polynomial are all differentiable, which can ensure smooth and continuous lateral acceleration during the lane-changing process, design the active lane-changing trajectory under high-speed conditions, and ignore the longitudinal speed change of the vehicle during the lane-changing process.

[0037] In an optional embodiment, a vehicle lateral trajectory planning function is constructed according to the vehicle starting point displacement and the vehicle lane changing time, and the vehicle lateral displacement is determined based on the vehicle lateral trajectory planning function and the pre-constructed lane changing trajectory constraint condition, including:

[0038] Step a1: construct a quintic polynomial objective function of the lateral lane-changing trajectory, and generate a lateral speed objective function and a lateral velocity objective function according to the quintic polynomial objective function of the lateral lane-changing trajectory.

[0039] Among them, the expression of the quintic polynomial objective function of the lateral lane change trajectory is as follows:

[0040] y(t)=a0+a1t+a2t 2 +a3t 3 +a4t 4 +a5t 5 ;

[0041] Where y(t) represents the lateral displacement of the vehicle, a i (i=0,1,…5) represents the polynomial coefficients of the vehicle lateral trajectory.

[0042] The first-order and second-order derivatives of the lateral lane-changing trajectory y(t) are used to obtain the lateral velocity objective function: and lateral acceleration objective function As shown below:

[0043]

[0044] Step a2: determine the polynomial coefficients according to the vehicle starting point displacement and the vehicle lane changing time, based on the quintic polynomial objective function of the lateral lane changing trajectory, the lateral speed objective function and the lateral speed objective function.

[0045] The displacement y(0) at the starting point of the vehicle lane change is 0, the vehicle lane change time is set to T, and the lateral speed of the vehicle at the starting and ending points of the lane change is Lateral acceleration are all 0, the lateral displacement of the lane change end point is y(T), set to h, then we can get:

[0046]

[0047] From this, we can see that the polynomial coefficients a0~a5 are:

[0048]

[0049] Step a3: construct a vehicle lateral trajectory planning function based on the polynomial coefficients.

[0050] The vehicle lateral trajectory planning function includes the vehicle lateral displacement, lateral velocity and lateral acceleration, and the corresponding expressions are as follows:

[0051]

[0052] Where y(t) represents the lateral displacement of the vehicle; Represents the lateral speed of the vehicle; Represents the lateral acceleration of the vehicle.

[0053] Step a4: According to the vehicle lateral trajectory planning function, based on the pre-constructed lane-changing trajectory constraint conditions, determine the lateral displacement of the vehicle.

[0054] According to the above vehicle lateral trajectory planning function, based on the driving time t in the current driving cycle of the vehicle and the lane-changing time T of the vehicle, the lateral displacement Y(y(t)), lateral speed Lateral acceleration

[0055] Furthermore, in order to meet safety, the dynamic constraints of the vehicle, and the comfort during the lane-changing process, the following several constraints are specifically added to the lane-changing trajectory: The lane-changing trajectory constraint conditions include at least one of lateral displacement constraint, driving speed constraint, lateral acceleration constraint, minimum lane-changing time constraint, and collision constraint.

[0056] (1) Lateral displacement Y(y(t)) constraint: 0.5w < y(t) < 1.5w, where w represents the road width.

[0057] (2) Lateral driving speed Constraint: 0 < v < v max v max represents the maximum speed limit of the road.

[0058] (3) Lateral acceleration Constraint: |a y | < a y,max a y,max represents the maximum lateral acceleration.

[0059] (4) Minimum lane-changing time t min Constraint: The minimum lane-changing time when the vehicle does not lose control obtained by combining the road surface adhesion coefficient and the vehicle speed.

[0060] (5) Collision constraint: No collision occurs during the lane-changing process.

[0061] The above-mentioned quintic polynomial can provide continuous and smooth position, speed, and acceleration curves. It avoids sudden changes in speed or acceleration, reduces mechanical shock and wear, and improves the stability and reliability of the system. Secondly, the quintic polynomial has sufficient degrees of freedom to set constraint conditions such as the positions, speeds, and accelerations of the starting point and the ending point, so as to obtain a trajectory that meets the requirements.

[0062] According to the vehicle driving information observed by different types of sensors, the road adhesion coefficient is estimated based on the vehicle dynamics model to obtain the road adhesion coefficient. Adhesion coefficient estimation is a very critical link in the design of stability control systems. The adhesion conditions between tires and roads have a great influence on the robustness of the controller. The observation system is based on a 7-DOF vehicle dynamics model and a UniTire simplified model, and uses an unscented Kalman filter algorithm to estimate the road adhesion coefficient. Compared with other improved Kalman filters, it has higher accuracy.

[0063] In an optional embodiment, according to the vehicle driving information observed by different types of sensors, the road adhesion coefficient is estimated based on the vehicle dynamics model to obtain the road adhesion coefficient, including:

[0064] Step b1, obtaining vehicle driving information based on different types of sensors; the vehicle driving information includes vehicle lateral acceleration, vehicle longitudinal acceleration and yaw angular velocity.

[0065] Step b2, constructing a vehicle dynamics model; the vehicle dynamics model includes a vehicle longitudinal motion model, a vehicle lateral motion model and a vehicle yaw motion model.

[0066] The expression of the 7-DOF vehicle dynamics model is:

[0067] Vehicle longitudinal motion model:

[0068]

[0069] Vehicle lateral motion model:

[0070]

[0071] Vehicle yaw motion model:

[0072]

[0073] In the above formula, m represents the vehicle mass, v x 、v y Represent the longitudinal and lateral speeds of the vehicle, respectively. represents the vehicle yaw rate, F xi 、F yi Represent the longitudinal force and lateral force of the tire respectively, the subscripts i = fl, fr, rl, rr represent the left front, right front, left rear, and right rear wheels respectively, δ represents the front wheel turning angle, I z is the moment of inertia, a and b are the distances from the center of mass of the vehicle to the front and rear axles respectively, and c is the wheelbase of the vehicle.

[0074] Step b3: construct the lateral force function of the vehicle tire and the longitudinal force function of the vehicle tire.

[0075] The lateral force function and longitudinal force function of the vehicle tire can be expressed as follows after being improved by the UniTire simplified model including the dynamic friction coefficient:

[0076]

[0077] is the normalized force, and its expressions are:

[0078]

[0079] Where C μx , C μy Represent the coefficients related to the vertical load respectively.

[0080] Step b4: according to the vehicle dynamics model, based on the lateral force function of the vehicle tire and the longitudinal force function of the vehicle tire, generate the vehicle lateral acceleration expression function, the vehicle longitudinal acceleration expression function and the vehicle yaw angular velocity change rate expression function.

[0081] By combining the above 7-DOF vehicle dynamics model with the improved tire longitudinal and lateral force expressions, the vehicle lateral acceleration expression function a can be obtained: x 、Vehicle longitudinal acceleration expression function a y And the vehicle yaw rate change rate expression function

[0082]

[0083] Among them, a x 、a y is the longitudinal and lateral acceleration of the vehicle, which can be observed by sensors. is the rate of change of yaw angular velocity, which can be obtained by taking the discrete derivative of the yaw angular velocity observed by the sensor, μ fl , μ fr , μ rl and μ rr Represent the road adhesion coefficients of the four wheels of the vehicle.

[0084] Step b5: construct an observation system, and use the road adhesion coefficient as the observation state quantity of the observation system, and use the vehicle lateral acceleration, vehicle longitudinal acceleration and yaw angular velocity as the observation output quantities of the observation system.

[0085] Construct an observation system and use the road adhesion coefficient as the observation state quantity of the observation system. The observation state quantity of the road adhesion coefficient is x μ =[μ fl ,μ fr ,μ rl ,μ rr ] T, the front wheel steering angle is used as the control variable u = δ, and the output is Assuming that the road adhesion coefficient changes slowly, the discrete state equation of the observation system can be expressed as follows:

[0086] x μ,k+1 =f2(x μ,k ,u k ,w k )

[0087] In the formula, w k is the system process noise.

[0088] Step b6: Determine the observation coefficient according to the vehicle lateral acceleration, the vehicle longitudinal acceleration and the yaw rate, based on the vehicle lateral acceleration expression function, the vehicle longitudinal acceleration expression function and the vehicle yaw rate change rate expression function.

[0089] The discrete output equation of the observation system can be expressed as:

[0090]

[0091] in,

[0092]

[0093] In the formula, v k Assume that w is the observation noise. k and v k are mutually independent zero-mean white noise.

[0094] Step b7: Determine the road adhesion coefficient based on the observation system according to the observation coefficient and the observation output.

[0095] Based on the above observation system, the road adhesion coefficient is solved.

[0096] When the vehicle is driving on different road conditions, the observation system can adjust the parameters of the steering assist and suspension system according to the adhesion coefficient to improve the steering response and stability of the vehicle. At the same time, it provides important parameter information for trajectory tracking control, so that the controller can adjust the vehicle's acceleration, speed and steering angle according to different road adhesion conditions to better track the predetermined trajectory.

[0097] Constructing trajectory tracking control target constraints and trajectory tracking control objective functions; according to the lateral position of the vehicle, and under the conditions of satisfying the trajectory tracking control target constraints, controlling the function value of the trajectory tracking control objective function to satisfy vehicle stability and trajectory tracking accuracy conditions.

[0098] In order to ensure that the vehicle accurately tracks the reference trajectory and the vehicle stability, an MPC (Model Predictive Control) lateral trajectory tracking controller is designed. The 7-DOF vehicle dynamics model is used as the prediction model, and the following expression is obtained:

[0099]

[0100] Where, ΔM z is the additional yaw moment,

[0101] Select lateral velocity, longitudinal velocity, yaw angle, yaw angular velocity, lateral displacement, and longitudinal displacement as the state variables of the controller:

[0102]

[0103] The control variables are defined as the front wheel steering angle and the additional yaw moment:

[0104] u=[δΔM z ] T ;

[0105] Introduce a tire slip angle constraint and set the controller output variable to:

[0106] y=[y c y s ] T ;

[0107] The control output is The soft constraint output is y s =[α fl α fr α rl α rr ] T α i Represents the tire slip angle, and the subscripts i=fl, fr, rl, rr represent left front, left rear, right front, and right rear respectively.

[0108] The trajectory tracking control objective function is defined as follows:

[0109]

[0110] Where N p is the prediction time domain, N c is the control time domain, η(t+i|t) is the predicted output, η ref(t+i|t) is the target output, Δu(t+i|t) is the control quantity, Q and R represent the system weight matrix and the control quantity increment weight matrix respectively, ρ is the relaxation weight coefficient, and ε is the relaxation factor. Among them, the value of J is used to evaluate the accuracy of vehicle tracking reference trajectory and vehicle stability.

[0111] In order to ensure the safety and stability of the vehicle during lane changing, trajectory tracking control target constraints are introduced.

[0112] Among them, the trajectory tracking control target constraints include constraints on the control amount, control increment and output amount, and yaw rate constraints; wherein the yaw rate constraints are generated based on the road adhesion coefficient.

[0113] First, the control quantity, control quantity increment, and output quantity are constrained to be between the upper and lower limit values:

[0114] u min (k+i)≤u(k+i)≤u max (k+i),i=1,2,…,N c -1

[0115] Δu min (k+i)≤Δu(k+i)≤Δu max (k+i),i=1,2,…,N c -1;

[0116] η min (k+i)<<η(k+i)<<η max (k+i),i=1,2,…,N p

[0117] The second is the constraint on the yaw rate. In order to ensure the maneuverability of the vehicle, the yaw rate is constrained within a certain range:

[0118]

[0119] Among them, μ is the road adhesion coefficient; g is the gravitational acceleration; v x That is, the lateral speed of the vehicle.

[0120] By establishing an accurate prediction model and providing reliable parameters, the constructed MPC model has the characteristics of real-time update, rolling optimization, and feedback correction, and continuously adjusts the prediction input at the next moment to make the control effect more accurate. In addition, MPC can handle constrained problems to ensure stable and safe vehicle control.

[0121] The technical solution of the embodiment of the present invention estimates the road adhesion coefficient. The road adhesion coefficient greatly affects the lateral and longitudinal force characteristics of the tire. This parameter also greatly affects the control performance during the vehicle control process. Accurately estimating the road adhesion coefficient effectively improves the control effect. Design a model to predict the lateral trajectory tracking controller to improve the stability, accuracy, rapidity, safety and stability of the vehicle's lateral trajectory tracking.

[0122] Embodiment 2

[0123] Figure 2 The structure diagram of a trajectory tracking control device provided in the second embodiment of the present invention. The trajectory tracking control device provided in the embodiment of the present invention can be applied to the situation where the trajectory tracking control is performed by comprehensively considering the important influence of the road adhesion coefficient on the driving stability and safety during high-speed driving. The trajectory tracking control device can be implemented in the form of hardware and / or software, such as Figure 2 As shown, the trajectory tracking control device can be configured in an electronic device, and specifically includes: a vehicle lateral displacement determination module 201, an adhesion coefficient determination module 202, a function construction module 203 and a numerical optimization module 204. Among them,

[0124] The vehicle lateral displacement determination module 201 is used to construct a vehicle lateral trajectory planning function according to the vehicle starting point displacement and the vehicle lane changing time, and determine the vehicle lateral displacement according to the vehicle lateral trajectory planning function and based on the pre-constructed lane changing trajectory constraint conditions;

[0125] The adhesion coefficient determination module 202 is used to estimate the road adhesion coefficient based on the vehicle dynamics model according to the vehicle driving information observed by different types of sensors to obtain the road adhesion coefficient;

[0126] Function construction module 203, used to construct trajectory tracking control target constraint conditions and construct trajectory tracking control target function;

[0127] The numerical optimization module 204 is used to control the function value of the trajectory tracking control objective function to meet the vehicle stability and trajectory tracking accuracy conditions according to the lateral position of the vehicle and under the condition that the trajectory tracking control objective constraint condition is met.

[0128] The technical solution of the embodiment of the present invention estimates the road adhesion coefficient. The road adhesion coefficient greatly affects the lateral and longitudinal force characteristics of the tire. This parameter also greatly affects the control performance during the vehicle control process. Accurately estimating the road adhesion coefficient effectively improves the control effect. Design a model to predict the lateral trajectory tracking controller to improve the stability, accuracy, rapidity, safety and stability of the vehicle's lateral trajectory tracking.

[0129] Optionally, the lane changing trajectory constraint condition includes at least one of a lateral displacement constraint, a driving speed constraint, a lateral acceleration constraint, a minimum lane changing time constraint and a collision constraint.

[0130] Optionally, the vehicle lateral displacement determination module 201 includes:

[0131] an objective function generating unit, configured to construct a quintic polynomial objective function of a lateral lane-changing trajectory, and to generate a lateral velocity objective function and a lateral speed objective function according to the quintic polynomial objective function of the lateral lane-changing trajectory;

[0132] a coefficient determination unit, for determining polynomial coefficients based on a quintic polynomial objective function of a lateral lane-changing trajectory, a lateral velocity objective function, and a lateral speed objective function according to a vehicle starting point displacement and a vehicle lane-changing time;

[0133] A planning function construction unit, used for constructing a vehicle lateral trajectory planning function according to polynomial coefficients;

[0134] The lateral displacement determination unit is used to determine the lateral displacement of the vehicle according to the vehicle lateral trajectory planning function and based on the pre-constructed lane change trajectory constraint conditions.

[0135] Optionally, the adhesion coefficient determination module 202 includes:

[0136] A driving information acquisition unit, used to acquire vehicle driving information obtained based on different types of sensors; the vehicle driving information includes vehicle lateral acceleration, vehicle longitudinal acceleration and yaw angular velocity;

[0137] A model building unit, used to build a vehicle dynamics model; the vehicle dynamics model includes a vehicle longitudinal motion model, a vehicle lateral motion model and a vehicle yaw transport model;

[0138] A force function construction unit, used for constructing a lateral force function of a vehicle tire and a longitudinal force function of a vehicle tire;

[0139] A speed function generating unit, configured to generate a vehicle lateral acceleration expression function, a vehicle longitudinal acceleration expression function and a vehicle yaw rate change rate expression function based on the vehicle dynamics model and the lateral force function of the vehicle tire and the vehicle tire longitudinal force function;

[0140] An observation system construction unit, used to construct an observation system, and use the road adhesion coefficient as an observation state quantity of the observation system, and use the vehicle lateral acceleration, vehicle longitudinal acceleration and yaw angular velocity as observation output quantities of the observation system;

[0141] an observation coefficient generating unit, configured to determine an observation coefficient according to the vehicle lateral acceleration, the vehicle longitudinal acceleration and the yaw rate, based on the vehicle lateral acceleration expression function, the vehicle longitudinal acceleration expression function and the vehicle yaw rate change rate expression function;

[0142] The adhesion coefficient generating unit is used to determine the road adhesion coefficient based on the observation system according to the observation coefficient and the observation output.

[0143] Optionally, the trajectory tracking control target constraints include constraints on control quantity, control increment and output quantity, and yaw rate constraints; wherein the yaw rate constraints are generated based on the road adhesion coefficient.

[0144] The trajectory tracking control device provided in the embodiment of the present invention can execute the trajectory tracking control method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0145] Embodiment 2

[0146] Figure 2 A schematic diagram of the structure of an electronic device 20 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0147] like Figure 2 As shown, the electronic device 20 includes at least one processor 21, and a memory connected to the at least one processor 21, such as a read-only memory (ROM) 22, a random access memory (RAM) 23, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 21 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 22 or the computer program loaded from the storage unit 28 to the random access memory (RAM) 23. In the RAM 23, various programs and data required for the operation of the electronic device 20 can also be stored. The processor 21, ROM 22 and RAM 23 are connected to each other through a bus 24. An input / output (I / O) interface 25 is also connected to the bus 24.

[0148] A number of components in the electronic device 20 are connected to the I / O interface 25, including: an input unit 26, such as a keyboard, a mouse, etc.; an output unit 27, such as various types of displays, speakers, etc.; a storage unit 28, such as a disk, an optical disk, etc.; and a communication unit 29, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 29 allows the electronic device 20 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0149] The processor 21 may be a variety of general and / or dedicated processing components with processing and computing capabilities. Some examples of the processor 21 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 21 executes the various methods and processes described above, such as a trajectory tracking control method.

[0150] In some embodiments, the trajectory tracking control method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 28. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 20 via the ROM 22 and / or the communication unit 29. When the computer program is loaded into the RAM 23 and executed by the processor 21, one or more steps of the trajectory tracking control method described above may be performed. Alternatively, in other embodiments, the processor 21 may be configured to perform the trajectory tracking control method in any other appropriate manner (e.g., by means of firmware).

[0151] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0152] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0153] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0154] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0155] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0156] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0157] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0158] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A trajectory tracking control method, characterized in that: include: Constructing a vehicle lateral trajectory planning function according to the vehicle starting point displacement and the vehicle lane changing time, and determining the vehicle lateral displacement according to the vehicle lateral trajectory planning function and based on the pre-constructed lane changing trajectory constraint condition; According to the vehicle driving information observed by different types of sensors, the road adhesion coefficient is estimated based on the vehicle dynamics model to obtain the road adhesion coefficient; Constructing trajectory tracking control target constraints and constructing trajectory tracking control target functions; According to the lateral position of the vehicle, and under the condition that the trajectory tracking control target constraint condition is satisfied, the function value of the trajectory tracking control target function is controlled to satisfy vehicle stability and trajectory tracking accuracy conditions.

2. The method according to claim 1, characterized in that The lane-changing trajectory constraint condition includes at least one of a lateral displacement constraint, a driving speed constraint, a lateral acceleration constraint, a minimum lane-changing time constraint, and a collision constraint.

3. The method according to claim 1, characterized in that The step of constructing a vehicle lateral trajectory planning function according to the vehicle starting point displacement and the vehicle lane changing time, and determining the vehicle lateral displacement according to the vehicle lateral trajectory planning function and based on a pre-constructed lane changing trajectory constraint condition, includes: constructing a quintic polynomial objective function of a lateral lane-changing trajectory, and generating a lateral velocity objective function and a lateral speed objective function according to the quintic polynomial objective function of the lateral lane-changing trajectory; Determine polynomial coefficients based on a quintic polynomial objective function of a lateral lane-changing trajectory, a lateral velocity objective function, and a lateral speed objective function according to the vehicle starting point displacement and the vehicle lane-changing time; According to the polynomial coefficients, a vehicle lateral trajectory planning function is constructed; According to the vehicle lateral trajectory planning function, based on pre-constructed lane change trajectory constraints, the vehicle lateral displacement is determined.

4. The method according to claim 1, characterized in that: The method of estimating the road adhesion coefficient based on the vehicle driving information observed by different types of sensors and the vehicle dynamics model to obtain the road adhesion coefficient includes: Acquiring vehicle driving information obtained based on different types of sensors; the vehicle driving information includes vehicle lateral acceleration, vehicle longitudinal acceleration and yaw angular velocity; Constructing a vehicle dynamics model; the vehicle dynamics model includes a vehicle longitudinal motion model, a vehicle lateral motion model and a vehicle yaw transport model; Constructing a lateral force function of a vehicle tire and a longitudinal force function of a vehicle tire; According to the vehicle dynamics model, based on the lateral force function of the vehicle tire and the longitudinal force function of the vehicle tire, a vehicle lateral acceleration expression function, a vehicle longitudinal acceleration expression function and a vehicle yaw rate change rate expression function are generated; An observation system is constructed, and a road adhesion coefficient is used as an observation state quantity of the observation system, and a lateral acceleration, a longitudinal acceleration and a yaw angular velocity of the vehicle are used as observation output quantities of the observation system; Determining an observation coefficient according to the vehicle lateral acceleration, the vehicle longitudinal acceleration and the yaw rate, based on the vehicle lateral acceleration expression function, the vehicle longitudinal acceleration expression function and the vehicle yaw rate change rate expression function; According to the observation coefficient and the observation output, a road adhesion coefficient is determined based on the observation system.

5. The method according to claim 1, characterized in that The trajectory tracking control target constraint conditions include control quantity, control increment and output quantity constraint conditions, and yaw rate constraint conditions; wherein the yaw rate constraint conditions are generated based on the road adhesion coefficient.

6. A trajectory tracking control device, characterized in that: include: A vehicle lateral displacement determination module, used to construct a vehicle lateral trajectory planning function according to the vehicle starting point displacement and the vehicle lane change time, and determine the vehicle lateral displacement according to the vehicle lateral trajectory planning function and based on the pre-constructed lane change trajectory constraint conditions; An adhesion coefficient determination module is used to estimate the road adhesion coefficient based on the vehicle dynamics model according to the vehicle driving information observed by different types of sensors to obtain the road adhesion coefficient; Function construction module, used to construct trajectory tracking control target constraints and trajectory tracking control target functions; The numerical optimization module is used to control the function value of the trajectory tracking control objective function to meet the vehicle stability and trajectory tracking accuracy conditions according to the lateral position of the vehicle and under the condition that the trajectory tracking control objective constraint is met.

7. The device according to claim 6, characterized in that The lane-changing trajectory constraint condition includes at least one of a lateral displacement constraint, a driving speed constraint, a lateral acceleration constraint, a minimum lane-changing time constraint, and a collision constraint.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the trajectory tracking control method according to any one of claims 1 to 5.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the trajectory tracking control method according to any one of claims 1 to 5 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the trajectory tracking control method according to any one of claims 1 to 5 is implemented.

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