Vehicle lateral and longitudinal coupling control methods, devices, equipment and storage media

Abstract

This application provides a vehicle lateral and longitudinal coupling control method, apparatus, device, and storage medium, comprising: determining a preview point on the lane line based on lane line information of the road where the vehicle is currently located; calculating the vehicle's steering angular velocity according to the LQR control algorithm based on the lateral distance between the vehicle and the preview point, the vehicle's current heading error, the vehicle's steering angle, and the vehicle's current longitudinal speed; calculating the desired steering angle of the vehicle's steering wheel based on the steering angular velocity and adjusting accordingly; determining the desired longitudinal speed of the vehicle based on the lane line information; using the difference between the vehicle's current longitudinal speed and the desired longitudinal speed as the input of a proportional-integral (PI) control algorithm; the output of the PI algorithm is the desired longitudinal acceleration of the vehicle; and calculating the desired engine torque based on the desired longitudinal acceleration of the vehicle and adjusting accordingly. By applying the LQR algorithm and the PI control algorithm, the computational complexity is low while maintaining high lateral and longitudinal control accuracy.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and in particular to a vehicle lateral and longitudinal coupling control method, device, equipment and storage medium. Background Technology

[0002] As commercial vehicles become increasingly intelligent, lateral and longitudinal coupling control is becoming more and more important. Lateral control mainly involves vehicle steering and path tracking, while longitudinal control involves speed and acceleration management. In practical vehicle control systems, lateral and longitudinal control are inseparable because they jointly affect vehicle stability and safety. Effective lateral and longitudinal coupling control can improve vehicle handling performance, comfort, and fuel economy.

[0003] In existing technologies, model predictive control (MPC), dynamic programming, and reinforcement learning are commonly used for vehicle lateral and longitudinal control. These methods can handle multi-input multi-output systems, nonlinear dynamics, and complex constraints.

[0004] However, the existing methods mentioned above have high computational complexity and require high computing power, making it difficult to control the vehicle when there is insufficient computing power during vehicle operation. Summary of the Invention

[0005] This application provides a vehicle lateral and longitudinal coupling control method, device, equipment, and storage medium to solve the problems that existing methods have high computational complexity, high computing power requirements, and difficulty in controlling the vehicle when faced with insufficient computing power during vehicle operation.

[0006] In a first aspect, this application provides a vehicle lateral and longitudinal coupling control method, the method comprising:

[0007] Obtain the lane line information of the road where the target vehicle is located and the current longitudinal speed value of the target vehicle;

[0008] The target aiming time of the target vehicle is obtained, and the position information of the aiming point on the lane line is determined based on the lane line information, the longitudinal vehicle speed value and the target aiming time.

[0009] Based on the lane line information and the position information, the lateral distance between the target vehicle and the aiming point and the heading error of the target vehicle are determined. The heading error is used to indicate the difference between the current heading angle of the target vehicle and the heading angle of the lane line at the aiming point.

[0010] Based on the lateral distance, the heading error, the longitudinal speed value, and the current steering angle of the target vehicle, the desired steering angular velocity of the target vehicle is calculated using a linear quadratic regulator control algorithm.

[0011] Based on the desired steering angular velocity, calculate the desired steering wheel angle of the target vehicle, and adjust the steering wheel angle of the target vehicle to the desired steering wheel angle;

[0012] Based on the lane line information, determine the desired longitudinal speed of the target vehicle;

[0013] The difference between the longitudinal vehicle speed value and the desired longitudinal speed is used as the input of the proportional-integral control algorithm, and the output of the proportional-integral algorithm is the desired longitudinal acceleration of the target vehicle.

[0014] Based on the desired longitudinal acceleration of the target vehicle, the desired torque of the engine of the target vehicle is calculated, and the torque of the engine is adjusted to the desired torque.

[0015] In one possible design, determining the position information of the aiming point on the lane line based on the lane line information of the road where the target vehicle is located, the longitudinal vehicle speed value, and the target aiming time includes:

[0016] Calculate the aiming distance based on the longitudinal vehicle speed value and the target aiming time;

[0017] The position information is determined based on the pre-aiming distance and the lane line information.

[0018] In one possible design, obtaining the target pre-aiming time includes:

[0019] Obtain the slope information of the road in front of the target vehicle;

[0020] The target aiming time is determined based on the longitudinal vehicle speed value and the slope information. The greater the slope of the road in front of the target vehicle, the shorter the target aiming time.

[0021] In one possible design, determining the desired longitudinal speed of the target vehicle based on the lane line information includes:

[0022] Based on the lane line information, obtain the curvature information of the lane lines on the road in front of the target vehicle;

[0023] The system obtains the road speed limit of the road ahead of the target vehicle, and obtains the road condition information of the road ahead of the target vehicle, and determines the maximum permissible lateral acceleration of the road ahead of the target vehicle based on the road condition information.

[0024] The safe speed value of the target vehicle on the road ahead is calculated based on the improved Levison model formula, which is:

[0025]

[0026] Among them, v safe Let a be the safe vehicle speed value. max Let c be the maximum permissible lateral acceleration, c be the curvature of the lane line in front of the target vehicle, and v be the maximum permissible lateral acceleration. limit The speed limit for the road ahead of the target vehicle;

[0027] The speed of the vehicle in front of the target vehicle and the relative distance between the vehicle in front and the target vehicle are obtained.

[0028] Calculate the safe following speed based on the speed of the vehicle in front and the relative distance;

[0029] The minimum of the safe vehicle speed value and the expected following speed is determined as the expected longitudinal speed.

[0030] In one possible design, determining the maximum permissible lateral acceleration of the road ahead of the target vehicle based on the road condition information includes:

[0031] Based on the road condition information, determine the road surface type of the road ahead of the target vehicle;

[0032] Based on the road surface type, determine the road surface adhesion coefficient of the road ahead of the target vehicle;

[0033] The maximum permissible lateral acceleration is calculated based on the product of the road surface adhesion coefficient and the gravitational acceleration.

[0034] In one possible design, calculating the desired torque of the engine of the target vehicle based on the desired longitudinal acceleration of the target vehicle includes:

[0035] Based on the desired longitudinal acceleration of the target vehicle, the desired torque is calculated using the torque calculation formula, which is:

[0036]

[0037] Among them, T n The desired torque; i g i is the final drive ratio of the target vehicle; i0 is the gear ratio of the transmission of the target vehicle; η Tdenoted as , where is the transmission efficiency of the target vehicle's power system; r is the wheel rolling radius of the target vehicle; m is the total mass of the target vehicle; g is the acceleration due to gravity; α is the slope of the road ahead of the target vehicle; f is the rolling resistance of the target vehicle; C D λ is the drag coefficient of the target vehicle; A is the frontal area of ​​the target vehicle; v is the longitudinal speed; λ is the rotational mass conversion factor of the target vehicle. Let be the desired longitudinal acceleration.

[0038] In one possible design, the step of calculating the desired steering angular velocity of the target vehicle using a linear quadratic regulator control algorithm based on the lateral distance, the heading error, the longitudinal speed value, and the current steering angle of the target vehicle includes:

[0039] Based on the control law of the linear quadratic regulator control algorithm, multiple candidate steering angular velocities are calculated. The control law is as follows:

[0040] u = -kx

[0041] Where u is the candidate steering angular velocity,

[0042] k = R -1 B T P

[0043] A T P+PA+Q-PBR -1 B T P=0

[0044] Where A is the state transition matrix, A T B is the transpose of the state transition matrix, which includes the longitudinal vehicle speed value and the wheelbase between the front and rear axles of the target vehicle; B is the control matrix. T Let Q be the transpose of the control matrix, Q be the state cost weight matrix, and R be the control cost weight matrix. -1 Let R be the inverse matrix, and P be the symmetric positive definite matrix to be solved.

[0045]

[0046] Where d is the lateral distance, θ * -θ is the heading error, θ * Let θ be the orientation angle of the lane line at the aiming point, θ be the current orientation angle of the target vehicle, and δ be the current steering angle of the target vehicle;

[0047] The cost function J is calculated based on the cost function and the candidate steering angular velocity.

[0048]

[0049] Where u T Let be the transpose of u;

[0050] The candidate steering angular velocity corresponding to the lowest cost function value is determined as the desired steering angular velocity.

[0051] Secondly, this application provides a vehicle lateral and longitudinal coupling control device, the device comprising:

[0052] The acquisition module is used to: acquire lane line information of the road where the target vehicle is located and the current longitudinal speed value of the target vehicle;

[0053] The aiming module is used for:

[0054] The target aiming time of the target vehicle is obtained, and the position information of the aiming point on the lane line is determined based on the lane line information, the longitudinal vehicle speed value and the target aiming time.

[0055] The lateral control module is used for:

[0056] Based on the lane line information and the position information, the lateral distance between the target vehicle and the aiming point and the heading error of the target vehicle are determined. The heading error is used to indicate the difference between the current heading angle of the target vehicle and the heading angle of the lane line at the aiming point.

[0057] Based on the lateral distance, the heading error, the longitudinal speed value, and the current steering angle of the target vehicle, the desired steering angular velocity of the target vehicle is calculated using a linear quadratic regulator control algorithm.

[0058] Based on the desired steering angular velocity, calculate the desired steering wheel angle of the target vehicle, and adjust the steering wheel angle of the target vehicle to the desired steering wheel angle;

[0059] The longitudinal control module is used for:

[0060] Based on the lane line information, determine the desired longitudinal speed of the target vehicle;

[0061] The difference between the longitudinal vehicle speed value and the desired longitudinal speed is used as the input of the proportional-integral control algorithm, and the output of the proportional-integral algorithm is the desired longitudinal acceleration of the target vehicle.

[0062] Based on the desired longitudinal acceleration of the target vehicle, the desired torque of the engine of the target vehicle is calculated, and the torque of the engine is adjusted to the desired torque.

[0063] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0064] The memory stores computer-executed instructions;

[0065] The processor executes computer execution instructions stored in the memory to implement the vehicle lateral and longitudinal coupling control method as described in the first aspect.

[0066] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the vehicle lateral and longitudinal coupling control method as described in the first aspect.

[0067] The vehicle lateral and longitudinal coupling control method, apparatus, device, and storage medium provided in this application have the following technical effects:

[0068] 1. In this method, the LQR (Linear Quadratic Regulator) and proportional-integral control algorithms require less computation compared to more complex methods such as model predictive control (MPC) and dynamic programming, enabling real-time control with limited computational resources. The LQR control algorithm utilizes a feedback mechanism to adjust the vehicle's steering angular velocity based on the vehicle's real-time state, ensuring the vehicle accurately tracks the target path and improving driving safety and comfort. By determining the vehicle's desired longitudinal speed based on lane line information and adjusting the vehicle's acceleration using the proportional-integral control algorithm, this method achieves precise control of the vehicle's longitudinal speed.

[0069] 2. By acquiring lane information of the road where the vehicle is currently located and determining the aiming point based on this information, this method can predict the vehicle's driving path in advance. This aiming control method can improve the vehicle's path tracking accuracy and stability, reduce lateral deviation and heading error, thereby improving the vehicle's handling performance and safety. The introduction of aiming control allows the vehicle to better adapt to changes in road curvature, especially when driving on curves, by adjusting the steering angle in advance, reducing unnecessary steering adjustments and energy consumption. Attached Figure Description

[0070] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0071] Figure 1 Flowchart of the vehicle lateral and longitudinal coupling control method provided in the embodiments of this application Figure 1 ;

[0072] Figure 2 This is a schematic diagram of the aiming control provided in an embodiment of this application;

[0073] Figure 3 Flowchart of the vehicle lateral and longitudinal coupling control method provided in the embodiments of this application Figure 2 ;

[0074] Figure 4 A schematic diagram of the vehicle lateral and longitudinal coupling control device provided in this application;

[0075] Figure 5 A schematic diagram of the structure of the electronic device provided in this application.

[0076] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0077] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0078] To address the problem that existing technologies have high computational complexity, require significant computing power, and struggle to effectively control vehicles when insufficient computing power is available during operation, the technical concept of this application is:

[0079] Based on the lane markings of the road where the vehicle is currently located, a target point is determined on the lane markings. Using the lateral distance between the vehicle and the target point, the vehicle's current heading error, the vehicle's steering angle, and its current longitudinal speed, the LQR control algorithm calculates the vehicle's steering angular velocity. Based on the steering angular velocity, the desired steering angle of the vehicle's steering wheel is calculated and adjusted accordingly. The desired longitudinal speed of the vehicle is determined based on the lane markings. The difference between the current longitudinal speed and the desired longitudinal speed is used as the input to the proportional-integral (PI) control algorithm. The output of the PI algorithm is the desired longitudinal acceleration of the vehicle. Based on the desired longitudinal acceleration, the desired engine torque is calculated and adjusted accordingly.

[0080] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0081] Example 1

[0082] This application provides a vehicle lateral and longitudinal coupling control method, which can be applied to the vehicle's control unit. Figure 1 Flowchart of the vehicle lateral and longitudinal coupling control method provided in the embodiments of this application Figure 1 ,like Figure 1 As shown, the method includes:

[0083] S101. Obtain the lane line information of the road where the target vehicle is located and the current longitudinal speed value of the target vehicle;

[0084] Specifically, since lane lines serve as the fundamental reference frame for vehicle lateral control, it is necessary to acquire lane line geometric features using environmental perception devices. This step can be achieved in the following ways: for example, by using a binocular camera to acquire road images and extracting lane line feature points using a convolutional neural network; or by using LiDAR point cloud data combined with the RANSAC algorithm to fit a cubic spline curve. Lane line information should at least include lateral offset, curvature, and orientation angle parameters. Current lane line information could be, for example:

[0085] y = c0 + c1x + c2x 2 +c3x 3

[0086] in,

[0087] c0: The lateral offset distance of the target vehicle relative to the lane line at the longitudinal x=0;

[0088] tan -1 (c1): The lane line orientation angle θ at the longitudinal x = 0;

[0089] 2c2: The curvature k of the lane line at the longitudinal x = 0. r ;

[0090] 6c3: The rate of change of curvature k′ of the lane line at the longitudinal x = 0. r ;

[0091] x: Longitudinal distance of a point on the lane line in the vehicle coordinate system;

[0092] y: In the vehicle coordinate system, at point x, the lateral distance of the lane line.

[0093] S102. Obtain the target aiming time of the target vehicle, and determine the position information of the aiming point on the lane line based on the lane line information, the longitudinal vehicle speed value and the target aiming time;

[0094] This step improves the system's forward-looking capability by introducing anticipatory control. Because vehicle motion has inertial characteristics, it is necessary to predict the trajectory tracking requirements at future moments.

[0095] Determining the location information of the aiming point can include:

[0096] Calculate the aiming distance based on the longitudinal vehicle speed and the target aiming time;

[0097] The location information is determined based on the pre-aiming distance and lane line information.

[0098] Specifically, this step can calculate the preview distance based on a kinematic model: the longitudinal position of the preview point = longitudinal vehicle speed × preview time, while the lateral position is determined by the value of the lane line curvature function at the preview distance. For example, a polynomial fitting of the lane line equation can be used, and the longitudinal displacement can be substituted into the equation to calculate the lateral coordinates.

[0099] S103. Based on lane line information and position information, determine the lateral distance between the target vehicle and the pre-aiming point, and the heading error of the target vehicle;

[0100] Figure 2 This is a schematic diagram of the aiming control provided in the embodiments of this application, such as... Figure 2 As shown, the heading error is used to indicate the difference between the target vehicle's current heading angle and the lane line's heading angle at the aiming point, where θ * Let θ be the azimuth angle of the lane line at the aiming point, i.e., the tangential direction angle of the lane line at the aiming point, and θ be the current azimuth angle of the target vehicle. Then the heading error is θ. * -θ. The heading error can be calculated by differentiating the lane line equation to obtain the tangent direction angle at the aiming point, and then subtracting it from the target vehicle's current heading angle measured by the target vehicle's IMU.

[0101] The lateral distance d between the target vehicle and the pre-aiming point can be:

[0102] d = sin(θ) * -θ)(xx * )-cos(θ * -θ)(yy * )

[0103] In the above formula, θ * The lane line's orientation angle at the aiming point;

[0104] (x,y) are the coordinates of the centroid of the target vehicle in the vehicle coordinate system, such as the coordinates of the center point of the rear axle of the target vehicle.

[0105] (x - ,y - ) represents the coordinates of the aiming point in the vehicle coordinate system.

[0106] S104. Based on the lateral distance, heading error, longitudinal speed value and the target vehicle's current steering angle, calculate the target vehicle's desired steering angular velocity using a linear quadratic regulator control algorithm.

[0107] The linear quadratic regulator control algorithm is also known as the LQR control algorithm. Due to the strong coupling characteristics of vehicle lateral dynamics, the LQR algorithm can optimize energy consumption while ensuring control accuracy. In its implementation, a three-state system model including lateral position error, heading error, and steering angle is first established. Then, a quadratic performance index function is designed, and the optimal feedback gain matrix is ​​obtained by solving the Riccati equation. Specifically, this step is implemented as follows:

[0108] First, define the state space vector as:

[0109]

[0110] Where d is the lateral distance, θ * -θ is the heading error, such as Figure 2 As shown, δ is the current steering angle of the target vehicle.

[0111] Taking the derivative of the above equation, we can obtain:

[0112]

[0113] Among them, such as Figure 2 As shown, v is the current longitudinal speed of the target vehicle, and L is the wheelbase between the front and rear axles of the target vehicle. Assume θ * Since -θ and δ are small quantities, the linear equation can be obtained as follows:

[0114]

[0115] Wherein, the state transition matrix A and the control matrix B are respectively:

[0116]

[0117] The control variable u is:

[0118]

[0119] In practical applications, based on the control law of the linear quadratic regulator control algorithm, multiple candidate steering angular velocities u are calculated, and the control law is as follows:

[0120] u = -kx

[0121] Here, k is the optimal feedback gain matrix, obtained by solving the Ricati equation, which is:

[0122] k = R -1 BT P

[0123] A T P+PA+Q-PBR -1 B T P=0

[0124] Where A is the state transition matrix, A T B is the transpose of the state transition matrix, which contains the longitudinal vehicle speed and the wheelbase between the front and rear axles of the target vehicle; B is the control matrix. T Let R be the transpose of the control matrix, Q be the state cost weight matrix, and R be the control cost weight matrix. -1 Let R be the inverse matrix, and P be the symmetric positive definite matrix to be solved. It should be noted that in practical applications, Q and R need to be set according to the control objective, and then, based on A and B, numerical methods such as iterative methods or direct solutions are used to solve the Ricati equations to obtain matrix P.

[0125] Then, the cost function value is calculated based on the cost function and the candidate steering angular velocity. The cost function J is:

[0126]

[0127] Where u T Let be the transpose of u;

[0128] The candidate steering angular velocity corresponding to the lowest cost function value is determined as the desired steering angular velocity. LQR control designs an optimal feedback controller by solving the Riccati equation, enabling the system to effectively track the target path while minimizing the cost function. By adjusting the weight matrices Q and R, a balance can be found between response speed and control energy, thus achieving precise and efficient lateral control.

[0129] S105. Calculate the desired steering wheel angle of the target vehicle based on the desired steering angular velocity, and adjust the steering wheel angle of the target vehicle to the desired steering wheel angle.

[0130] This step translates control commands into actuator actions. Due to the transmission ratio and response delay in the steering system, this conversion requires a dynamic model. This step can be calculated using the steering system transmission ratio formula: Steering wheel angle = Steering angular velocity × Transmission ratio × Control cycle. For example, for an EPS system with a transmission ratio of 16:1, if the desired steering angular velocity is 0.1 rad / s, then the steering wheel angle needs to be adjusted by 0.16 degrees every 0.1 seconds.

[0131] S106. Determine the desired longitudinal speed of the target vehicle based on the lane line information;

[0132] This step enables proactive safety speed adjustment. For example, since road curvature affects vehicle stability margin, dynamic speed adjustment is necessary. This step can determine a baseline speed based on the current lane curvature by querying a preset curvature-speed mapping table. For instance, when the lane curvature radius is detected to be less than 200m, the desired speed is set to min(current speed limit, sqrt(lateral acceleration threshold × curvature radius)). Slope information from the navigation map can also be integrated for speed compensation.

[0133] S107. The difference between the longitudinal vehicle speed and the desired longitudinal speed is used as the input of the proportional-integral control algorithm, and the output of the proportional-integral algorithm is the desired longitudinal acceleration of the target vehicle.

[0134] Because of the nonlinear characteristics of engine response, a PI controller can be used to balance response speed and stability. The desired longitudinal acceleration can be calculated using the following formula:

[0135]

[0136] in,

[0137] k p k I These are the proportional coefficient and the integral coefficient, respectively.

[0138] v represents the current longitudinal speed of the target vehicle;

[0139] V ref The desired longitudinal velocity;

[0140] The desired longitudinal acceleration.

[0141] In practice, for example, a scaling factor k can be set. p =0.3, integral coefficient k I =0.05, sampling period 100ms. The integral term can be set with anti-saturation limit to prevent sudden changes in control quantity caused by long-term error accumulation.

[0142] S108. Based on the target vehicle's desired longitudinal acceleration, calculate the target vehicle's engine's desired torque and adjust the engine's torque to the desired torque.

[0143] This step completes the final execution of the longitudinal dynamics control commands. Since there is a non-linear relationship between vehicle rolling resistance and acceleration, the required torque needs to be calculated using an inverse dynamics model. This step can be performed using the formula: Required Torque = (Vehicle Mass × Acceleration + Rolling Resistance + Air Resistance) × Tire Rolling Radius / Total Drivetrain Efficiency. For example, for a 2000kg vehicle, when the required acceleration is 1 m / s²... 2Considering the typical drag coefficient, it is calculated that the engine needs to output approximately 350 Nm of torque, and the torque command is sent to the ECM for execution via the CAN bus.

[0144] The technical effects of this embodiment are as follows:

[0145] 1. In this method, the LQR (Linear Quadratic Regulator) and proportional-integral control algorithms require less computation compared to more complex methods such as model predictive control (MPC) and dynamic programming, enabling real-time control with limited computational resources. The LQR control algorithm utilizes a feedback mechanism to adjust the vehicle's steering angular velocity based on the vehicle's real-time state, ensuring the vehicle accurately tracks the target path and improving driving safety and comfort. By determining the vehicle's desired longitudinal speed based on lane line information and adjusting the vehicle's acceleration using the proportional-integral control algorithm, this method achieves precise control of the vehicle's longitudinal speed.

[0146] 2. By acquiring lane information of the road where the vehicle is currently located and determining the aiming point based on this information, this method can predict the vehicle's driving path in advance. This aiming control method can improve the vehicle's path tracking accuracy and stability, reduce lateral deviation and heading error, thereby improving the vehicle's handling performance and safety. The introduction of aiming control allows the vehicle to better adapt to changes in road curvature, especially when driving on curves, by adjusting the steering angle in advance, reducing unnecessary steering adjustments and energy consumption.

[0147] Example 2

[0148] Figure 3 Flowchart of the vehicle lateral and longitudinal coupling control method provided in the embodiments of this application Figure 2 ,like Figure 3 As shown, the method includes:

[0149] S301. Obtain the lane line information of the road where the target vehicle is located and the current longitudinal speed value of the target vehicle;

[0150] S302, Obtain the slope information of the road ahead of the target vehicle;

[0151] In this step, considering the impact of slope changes on vehicle dynamics, an inertial measurement unit (IMU) or a high-precision map navigation system can be used to obtain the slope angle of the road ahead (for example, multi-sensor data can be fused using a Kalman filter algorithm). Specifically, a slope-distance correspondence table can be established, or continuous slope curves can be obtained through real-time terrain scanning.

[0152] S303. Based on the longitudinal vehicle speed value and the gradient information, determine the target aiming time. The greater the gradient of the road in front of the target vehicle, the shorter the target aiming time.

[0153] Specifically, a lookup table method can be used to pre-define a three-dimensional mapping table of vehicle speed, gradient, and anticipation time. In practice, for example, when a 5% increase in uphill gradient is detected, the anticipation time can be shortened by 0.3 seconds, thereby improving system response speed while ensuring control stability and avoiding control lag caused by sudden changes in gradient. Alternatively, a coupling model between longitudinal vehicle speed and gradient can be established to dynamically adjust the anticipation time. In practice, the longitudinal vehicle speed value is used as the core input parameter; for example, an anticipation time calculation function can be used.

[0154]

[0155] Where T is the target aiming time, v is the current longitudinal speed of the target vehicle, and k t The adjustment coefficient is α, where α is the slope angle of the road ahead. max This represents the maximum permissible lateral acceleration on the current road. As vehicle speed increases, the preview time needs to be extended accordingly to ensure that the preview distance matches the vehicle's dynamic response capability. Conversely, as the gradient increases, the preview time is shortened by the cosα term to offset the changes in acceleration components caused by the gradient. For example, in a high-speed scenario (v = 30 m / s) and on a flat road (α = 0°), the preview time can be set to 2.5 seconds, while at the same vehicle speed encountering a 10° uphill slope, the preview time is shortened to 2.2 seconds.

[0156] By considering the gradient factor in determining the target preview time, the problem of acceleration calculation error caused by neglecting the gradient factor in traditional control is solved. By taking into account the target vehicle's current longitudinal speed, the preview time is dynamically adapted to the vehicle's actual motion state, thereby balancing the foresight and real-time performance of the control system under complex road conditions and avoiding steering oscillations or path tracking lag caused by a fixed preview time.

[0157] S304. Determine the position information of the aiming point on the lane line based on the lane line information, longitudinal vehicle speed value, and target aiming time;

[0158] S305. Based on lane line information and position information, determine the lateral distance between the target vehicle and the pre-aiming point, and the heading error of the target vehicle;

[0159] S306. Based on the lateral distance, heading error, longitudinal speed value and the target vehicle's current steering angle, calculate the target vehicle's desired steering angular velocity using a linear quadratic regulator control algorithm.

[0160] S307. Calculate the desired steering wheel angle of the target vehicle based on the desired steering angular velocity, and adjust the steering wheel angle of the target vehicle to the desired steering wheel angle;

[0161] S308. Based on lane line information, obtain the curvature information of the lane lines on the road ahead of the target vehicle;

[0162] In this step, a cubic spline curve fitting algorithm can be used to process the lane line coordinate points (for example, the curvature radius R value can be updated every 0.1 seconds) to establish a curvature-distance mapping relationship in order to obtain the curvature information of the lane line.

[0163] S309. Obtain the road speed limit of the road ahead of the target vehicle, and obtain the road condition information of the road ahead of the target vehicle, and determine the maximum permissible lateral acceleration of the road ahead of the target vehicle based on the road condition information.

[0164] In this step, speed limit signs can be obtained through V2X communication or visual recognition (e.g., using the YOLOv5 algorithm to detect speed limit signs).

[0165] Optionally, determine the maximum permissible lateral acceleration of the road ahead of the target vehicle based on road condition information, including:

[0166] Based on road condition information, determine the road surface type ahead of the target vehicle;

[0167] Determine the road surface adhesion coefficient in front of the target vehicle based on the road surface type;

[0168] The maximum permissible lateral acceleration is calculated by multiplying the road surface adhesion coefficient by the gravitational acceleration.

[0169] Specifically, vehicle-mounted sensor fusion can be used to determine road surface type, such as tire-road noise spectrum analysis (using microphone signals) or infrared sensors to detect road surface reflectivity. V2X communication can also be used to receive real-time road surface conditions (such as marking it as slippery in rainy weather) provided by cloud or roadside units.

[0170] A road surface type-road surface adhesion coefficient correspondence table can be pre-stored in the vehicle's storage unit. For example, the road surface adhesion coefficient corresponding to dry asphalt road surface is 0.85, the road surface adhesion coefficient corresponding to wet and slippery cement road surface is 0.55, and the road surface adhesion coefficient corresponding to icy road surface is 0.15.

[0171] Maximum permissible lateral acceleration a max The calculation formula can be:

[0172] a max =μ·g

[0173] Where μ is the road adhesion coefficient and g is the acceleration due to gravity. The maximum permissible lateral acceleration of the vehicle is dynamically calculated based on road condition information. Its core function is to provide a safety boundary constraint for the lateral control of the vehicle and avoid the risk of sideslip caused by the lateral force of the tires exceeding the road adhesion limit.

[0174] S310. Calculate the safe speed value of the road ahead of the target vehicle based on the improved Levison model formula;

[0175] Specifically, the improved Levison model formula is as follows:

[0176]

[0177] Among them, v safe For a safe speed value, a max The maximum permissible lateral acceleration is given by c, where c is the curvature of the lane line in front of the target vehicle, and v is the maximum permissible lateral acceleration. limit The speed limit for the road ahead of the target vehicle.

[0178] In this step, the critical speed of the target vehicle without skidding or rollover is calculated by considering road curvature and the maximum permissible lateral acceleration. Furthermore, the improved Levison model has lower computational complexity, making it suitable for applications in scenarios with limited computing power.

[0179] S311. Obtain the speed of the vehicle in front of the target vehicle, and the relative distance between the vehicle in front and the target vehicle;

[0180] Specifically, this step can utilize millimeter-wave radar or lidar for target detection to obtain the speed of the vehicle in front and the relative distance between the vehicle in front and the target vehicle.

[0181] S312. Calculate the safe following speed based on the speed of the vehicle in front and the relative distance.

[0182] Specifically, it can be calculated using the following formula:

[0183]

[0184] Among them, v follow For safe following speed, v lead Let d be the speed of the vehicle in front. actual d represents the relative distance between the vehicle in front and the target vehicle. safe The minimum safe distance is denoted by m, which is an adjustment coefficient (for example, it can be the reciprocal of the safe time distance, which is usually 1.5 seconds).

[0185] S313. The minimum of the safe speed value and the expected following speed shall be determined as the expected longitudinal speed.

[0186] Specifically, by comparing safe speed values ​​and expected following speed values, the system can dynamically adjust the expected longitudinal speed of the target vehicle based on the traffic and road conditions, thereby ensuring the driving safety of the target vehicle.

[0187] S314. The difference between the longitudinal vehicle speed and the desired longitudinal speed is used as the input of the proportional-integral control algorithm, and the output of the proportional-integral algorithm is the desired longitudinal acceleration of the target vehicle.

[0188] S315. Based on the target vehicle's desired longitudinal acceleration, calculate the target vehicle's engine's desired torque and adjust the engine's torque to the desired torque.

[0189] Optionally, based on the target vehicle's desired longitudinal acceleration, the desired torque of the target vehicle's engine is calculated, including:

[0190] Based on the target vehicle's desired longitudinal acceleration, the desired torque is calculated using the torque calculation formula:

[0191]

[0192] Among them, T n i represents the desired torque; g i is the final drive ratio of the target vehicle; i0 is the gear ratio of the target vehicle's transmission; η T denoted by , where is the transmission efficiency of the target vehicle's powertrain; is the rolling radius of the target vehicle's wheels; is the total mass of the target vehicle; is the acceleration due to gravity; is the gradient of the road ahead of the target vehicle; is the rolling resistance of the target vehicle; and C is the total mass of the target vehicle. D λ is the drag coefficient of the target vehicle; A is the frontal area of ​​the target vehicle; v is the longitudinal speed; λ is the rotational mass conversion factor of the target vehicle. The desired longitudinal acceleration.

[0193] It should be noted that in this embodiment, S301, S304, S305, S306, S307, and S314 can be referred to in Embodiment 1, and will not be repeated here.

[0194] Figure 4 This is a schematic diagram of the vehicle lateral and longitudinal coupling control device provided in this application, as shown below. Figure 4 As shown, the vehicle lateral and longitudinal coupling control device 40 provided in this embodiment includes:

[0195] The acquisition module 401 is used to: acquire lane line information of the road where the target vehicle is located and the current longitudinal speed value of the target vehicle;

[0196] Pre-aiming module 402 is used for:

[0197] Obtain the target aiming time of the target vehicle, and determine the position information of the aiming point on the lane line based on lane line information, longitudinal vehicle speed value and target aiming time;

[0198] Lateral control module 403 is used for:

[0199] Based on lane line information and position information, determine the lateral distance between the target vehicle and the aiming point, and the heading error of the target vehicle. The heading error is used to indicate the difference between the target vehicle's current heading angle and the lane line's heading angle at the aiming point.

[0200] Based on the lateral distance, heading error, longitudinal speed, and the target vehicle's current steering angle, the desired steering angular velocity of the target vehicle is calculated using a linear quadratic regulator control algorithm.

[0201] Based on the desired steering angular velocity, calculate the desired steering wheel angle of the target vehicle, and adjust the steering wheel angle of the target vehicle to the desired steering wheel angle;

[0202] Longitudinal control module 404 is used for:

[0203] Based on lane marking information, determine the target vehicle's desired longitudinal speed;

[0204] The difference between the longitudinal vehicle speed and the desired longitudinal speed is used as the input to the proportional-integral control algorithm, and the output of the proportional-integral algorithm is the desired longitudinal acceleration of the target vehicle.

[0205] Based on the target vehicle's desired longitudinal acceleration, calculate the target vehicle's engine's desired torque and adjust the engine's torque to the desired torque.

[0206] The vehicle lateral and longitudinal coupling control device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0207] Figure 5 A schematic diagram of the structure of the electronic device provided in this application. Figure 5 As shown, the electronic device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus 504.

[0208] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0209] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0210] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0211] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0212] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0213] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0214] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0215] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0216] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0217] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0218] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0219] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0220] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0221] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0222] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A vehicle lateral and longitudinal coupling control method, characterized in that, The method includes: Obtain the lane line information of the road where the target vehicle is located and the current longitudinal speed value of the target vehicle; The target aiming time of the target vehicle is obtained, and the position information of the aiming point on the lane line is determined based on the lane line information, the longitudinal vehicle speed value and the target aiming time. Based on the lane line information and the position information, the lateral distance between the target vehicle and the aiming point and the heading error of the target vehicle are determined. The heading error is used to indicate the difference between the current heading angle of the target vehicle and the heading angle of the lane line at the aiming point. Based on the lateral distance, the heading error, the longitudinal speed value, and the current steering angle of the target vehicle, the desired steering angular velocity of the target vehicle is calculated using a linear quadratic regulator control algorithm. Based on the desired steering angular velocity, calculate the desired steering wheel angle of the target vehicle, and adjust the steering wheel angle of the target vehicle to the desired steering wheel angle; Based on the lane line information, determine the desired longitudinal speed of the target vehicle; The difference between the longitudinal vehicle speed value and the desired longitudinal speed is used as the input of the proportional-integral control algorithm, and the output of the proportional-integral algorithm is the desired longitudinal acceleration of the target vehicle. Based on the desired longitudinal acceleration of the target vehicle, the desired torque of the engine of the target vehicle is calculated, and the torque of the engine is adjusted to the desired torque.

2. The method according to claim 1, characterized in that, The step of determining the position information of the aiming point on the lane line based on the lane line information of the road where the target vehicle is located, the longitudinal speed value, and the target aiming time includes: Calculate the aiming distance based on the longitudinal vehicle speed value and the target aiming time; The position information is determined based on the pre-aiming distance and the lane line information.

3. The method according to claim 2, characterized in that, The acquisition of target pre-aiming time includes: Obtain the slope information of the road in front of the target vehicle; The target aiming time is determined based on the longitudinal vehicle speed value and the slope information. The greater the slope of the road in front of the target vehicle, the shorter the target aiming time.

4. The method according to claim 1, characterized in that, Determining the desired longitudinal speed of the target vehicle based on the lane line information includes: Based on the lane line information, obtain the curvature information of the lane lines on the road in front of the target vehicle; The system obtains the road speed limit of the road ahead of the target vehicle, and obtains the road condition information of the road ahead of the target vehicle, and determines the maximum permissible lateral acceleration of the road ahead of the target vehicle based on the road condition information. The safe speed value of the target vehicle on the road ahead is calculated based on the improved Levison model formula, which is: Among them, v safe Let a be the safe vehicle speed value. max Let c be the maximum permissible lateral acceleration, c be the curvature of the lane line in front of the target vehicle, and v be the maximum permissible lateral acceleration. limit The speed limit for the road ahead of the target vehicle; The speed of the vehicle in front of the target vehicle and the relative distance between the vehicle in front and the target vehicle are obtained. Calculate the safe following speed based on the speed of the vehicle in front and the relative distance; The minimum of the safe vehicle speed value and the expected following speed is determined as the expected longitudinal speed.

5. The method according to claim 4, characterized in that, Determining the maximum permissible lateral acceleration of the road ahead of the target vehicle based on the road condition information includes: Based on the road condition information, determine the road surface type of the road ahead of the target vehicle; Based on the road surface type, determine the road surface adhesion coefficient of the road ahead of the target vehicle; The maximum permissible lateral acceleration is calculated based on the product of the road surface adhesion coefficient and the gravitational acceleration.

6. The method according to claim 3, characterized in that, The step of calculating the desired torque of the engine of the target vehicle based on the desired longitudinal acceleration of the target vehicle includes: Based on the desired longitudinal acceleration of the target vehicle, the desired torque is calculated using the torque calculation formula, which is: Among them, T n The desired torque; i g i is the final drive ratio of the target vehicle; i0 is the gear ratio of the transmission of the target vehicle; η T denoted as , where is the transmission efficiency of the target vehicle's power system; r is the wheel rolling radius of the target vehicle; m is the total mass of the target vehicle; g is the acceleration due to gravity; α is the slope of the road ahead of the target vehicle; f is the rolling resistance of the target vehicle; C D λ is the drag coefficient of the target vehicle; A is the frontal area of ​​the target vehicle; v is the longitudinal speed; λ is the rotational mass conversion factor of the target vehicle. Let be the desired longitudinal acceleration.

7. The method according to any one of claims 1-6, characterized in that, The step of calculating the desired steering angular velocity of the target vehicle using a linear quadratic regulator control algorithm based on the lateral distance, the heading error, the longitudinal speed value, and the current steering angle of the target vehicle includes: Based on the control law of the linear quadratic regulator control algorithm, multiple candidate steering angular velocities are calculated. The control law is as follows: u = -kx Where u is the candidate steering angular velocity, k=R -1 B T P A T P+PA+Q-PBR -1 B T P=0 Where A is the state transition matrix, A T B is the transpose of the state transition matrix, which includes the longitudinal vehicle speed value and the wheelbase between the front and rear axles of the target vehicle; B is the control matrix. T Let Q be the transpose of the control matrix, Q be the state cost weight matrix, and R be the control cost weight matrix. -1 Let R be the inverse matrix, and P be the symmetric positive definite matrix to be solved. Where d is the lateral distance, θ*-θ is the heading error, θ* is the orientation angle of the lane line at the aiming point, θ is the current orientation angle of the target vehicle, and δ is the current steering angle of the target vehicle; The cost function J is calculated based on the cost function and the candidate steering angular velocity. J=∫0 ∞ (x T Qx+u T Ru)dt Where u T Let be the transpose of u; The candidate steering angular velocity corresponding to the lowest cost function value is determined as the desired steering angular velocity.

8. A vehicle lateral and longitudinal coupling control device, characterized in that, The device includes: The acquisition module is used to: acquire lane line information of the road where the target vehicle is located and the current longitudinal speed value of the target vehicle; The aiming module is used for: The target aiming time of the target vehicle is obtained, and the position information of the aiming point on the lane line is determined based on the lane line information, the longitudinal vehicle speed value and the target aiming time. The lateral control module is used for: Based on the lane line information and the position information, the lateral distance between the target vehicle and the aiming point and the heading error of the target vehicle are determined. The heading error is used to indicate the difference between the current heading angle of the target vehicle and the heading angle of the lane line at the aiming point. Based on the lateral distance, the heading error, the longitudinal speed value, and the current steering angle of the target vehicle, the desired steering angular velocity of the target vehicle is calculated using a linear quadratic regulator control algorithm. Based on the desired steering angular velocity, calculate the desired steering wheel angle of the target vehicle, and adjust the steering wheel angle of the target vehicle to the desired steering wheel angle; The longitudinal control module is used for: Based on the lane line information, determine the desired longitudinal speed of the target vehicle; The difference between the longitudinal vehicle speed value and the desired longitudinal speed is used as the input of the proportional-integral control algorithm, and the output of the proportional-integral algorithm is the desired longitudinal acceleration of the target vehicle. Based on the desired longitudinal acceleration of the target vehicle, the desired torque of the engine of the target vehicle is calculated, and the torque of the engine is adjusted to the desired torque.

9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the vehicle lateral and longitudinal coupling control method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the vehicle lateral and longitudinal coupling control method as described in any one of claims 1 to 7.

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