Vehicle control method and device and vehicle

Abstract

The invention discloses a vehicle control method and device and a vehicle. The method comprises the steps that the road curve radius of a road on which the vehicle runs is obtained; according to the road curve radius and the motion state of the vehicle, target correction parameters are obtained, the motion state of the vehicle comprises the roll angle of the vehicle, the centering error of the vehicle, the hand torque of a steering wheel of the vehicle and the chassis element deformation quantity of the vehicle, and the target correction parameters are used for correcting control parameters of the vehicle in the cross slope scene; the vehicle can run in the middle of the road; determining a control parameter of the vehicle based on the target correction parameter; and vehicle driving is controlled based on the control parameters, so that the accuracy of vehicle centering driving control is improved.

Description

Technical Field

[0001] The present application relates to the field of automobile intelligent driving technology, and more specifically, to a vehicle control method, device and vehicle. Background Art

[0002] With the development of science and technology, the functions of vehicle driving automatic control are becoming more and more diverse. The centering assist function is a comfort assist driving function designed to assist the driver to keep the car in the center of the lane during driving; it helps the vehicle stay in the center of the lane by automatically applying steering force to ensure driving safety. At present, there are situations where vehicles are driving on sloped roads. Based on this, there is a challenge in related technologies to improve the accuracy of the vehicle centering assist function in sloped scenarios. Summary of the invention

[0003] In view of this, the embodiments of the present application propose a vehicle control method, device and vehicle to improve the above-mentioned problems.

[0004] In a first aspect, an embodiment of the present application provides a vehicle control method, the method comprising: obtaining a road curve radius of a road on which a vehicle is traveling; obtaining target correction parameters based on the road curve radius and the motion state of the vehicle, wherein the motion state of the vehicle includes the roll angle of the vehicle, the centering error of the vehicle, the steering wheel torque of the vehicle, and the deformation of the chassis elements of the vehicle, and the target correction parameters are used to correct the control parameters of the vehicle in a cross slope scenario so that the vehicle travels in the center of the road; determining the control parameters of the vehicle based on the target correction parameters; and controlling the driving of the vehicle based on the control parameters.

[0005] In the second aspect, the embodiment of the present application provides a vehicle control device, the device comprising: a road curve radius acquisition module, a target correction parameter acquisition module, a control parameter determination module and a vehicle control module. The road curve radius acquisition module is used to acquire the road curve radius of the road on which the vehicle is traveling; the target correction parameter acquisition module is used to acquire the target correction parameters according to the road curve radius and the motion state of the vehicle, wherein the motion state of the vehicle includes the roll angle of the vehicle, the centering error of the vehicle, the steering wheel hand torque of the vehicle and the deformation of the chassis element of the vehicle, and the target correction parameters are used to correct the control parameters of the vehicle in a cross slope scenario so that the vehicle is centered on the road; the control parameter determination module is used to determine the control parameters of the vehicle based on the target correction parameters; the vehicle control module is used to control the vehicle driving based on the control parameters.

[0006] In a third aspect, an embodiment of the present application provides a vehicle, comprising a memory and a processor, wherein the memory is coupled to the processor, the memory stores instructions, and when the instructions are executed by the processor, the processor executes the above method.

[0007] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a program code is stored, and the program code can be called by a processor to execute the above method.

[0008] In the scheme of the present application, when the road on which the vehicle is traveling is a transverse slope, correction parameters for vehicle control are obtained based on the vehicle's roll angle, centering error, road curve radius of the road, steering wheel hand torque, and chassis component deformation, and the vehicle's control parameters are dynamically adjusted based on the correction parameters. The vehicle driving is controlled based on the control parameters, thereby optimizing the accuracy of the vehicle's centering driving control in the transverse slope scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0010] Figure 1 A schematic diagram of a vehicle control method according to an embodiment of the present application is shown;

[0011] Figure 2 A schematic diagram showing a first mapping relationship provided by an embodiment of the present application is shown;

[0012] Figure 3 A schematic diagram showing a second mapping relationship provided by an embodiment of the present application is shown;

[0013] Figure 4 A schematic diagram showing a third mapping relationship provided by an embodiment of the present application is shown;

[0014] Figure 5 A schematic diagram showing a fourth mapping relationship provided by an embodiment of the present application is shown;

[0015] Figure 6 A schematic diagram showing a fifth mapping relationship provided by an embodiment of the present application is shown;

[0016] Figure 7 A schematic diagram of a vehicle control method according to an embodiment of the present application is shown;

[0017] Figure 8A schematic diagram of a vehicle control method according to an embodiment of the present application is shown;

[0018] Fig. 9 A module block diagram of a vehicle control device provided by an embodiment of the present application is shown;

[0019] Fig.10 A block diagram of a vehicle according to an embodiment of the present application for executing a vehicle control method according to an embodiment of the present application is shown;

[0020] Fig.11 A storage unit for storing or carrying program codes for implementing a vehicle control method according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0022] With the development of vehicle driving automatic control technology, the functions of vehicle assisted driving are becoming more and more diverse. In the process of vehicle assisted driving, the vehicle can assist the driver in driving through automatic vehicle control within a certain period of time; and controlling the vehicle to drive along the center line of the lane is an important part of this technology. Ensuring that the vehicle drives along the center line of the lane can effectively reduce the driver's labor intensity and improve driving safety.

[0023] However, in the related art, the Advanced Driving Assistance System (ADAS) using a single radar and a single camera is unable to detect the cross-slope scene, and the lack of samples in the cross-slope scene during performance calibration will lead to unreasonable vehicle centering control parameters in the cross-slope scene, causing the vehicle to not drive in the center. In addition, in the related art, there is also a solution that calculates the cross-slope angle by the vehicle's yaw angular velocity and the vehicle's speed, and controls the vehicle according to the cross-slope angle. However, in the scenes of large curvature curves, vehicle lane changes, detours, etc., there is an inaccurate cross-slope angle detection result, resulting in low accuracy of vehicle centering control.

[0024] Therefore, in the related art, when the lane centering assist function is activated, when the vehicle is traveling on a road with a horizontal slope, the control ability of the vehicle's centering assist system is poor, which will cause the vehicle to tilt to the side of the road, causing the vehicle to not travel in the center.

[0025] In view of the above problems, the inventors have found through long-term research that they have proposed the vehicle control method, device and vehicle provided in the embodiments of the present application. When the road on which the vehicle is traveling is a transverse slope, the correction parameters of the vehicle control are dynamically adjusted according to the vehicle's roll angle, centering error, road curve radius of the road on which the vehicle is traveling, steering wheel hand torque and chassis element deformation, and the control parameters of the vehicle are determined according to the correction parameters, and the vehicle driving is controlled based on the control parameters, thereby improving the accuracy and safety of driving control in the center of the lane in the transverse slope scenario. Among them, the specific vehicle control method is described in detail in the subsequent embodiments.

[0026] In order to better understand the solutions of the embodiments of the present application, the technical terms used in the embodiments of the present application are explained below.

[0027] LCC, Lane Centering Control, also known as Lane Centering Assist, is a comfort-assisted driving function that assists the driver to keep the car in the middle of the lane during driving.

[0028] NOA, Navigate on Autopilot, navigation assisted driving, also known as advanced assisted driving, is a technology that deeply integrates navigation and assisted driving functions.

[0029] ADAS, Advanced Driving Assistance System, uses a variety of sensors installed on the car (millimeter wave radar, lidar, monocular / binocular cameras and satellite navigation) to sense the surrounding environment at any time during driving, collect data, identify, detect and track static and dynamic objects, and combine navigation map data to perform systematic calculations and analysis, so as to make the driver aware of possible dangers in advance, effectively increasing the comfort and safety of car driving.

[0030] PID, Proportional Integral Derivative, control system, is a control system that controls by comparing the information collected by real-time data of the controlled object with the given value, based on the proportion, integration and differentiation of the error generated.

[0031] MPC, Model Predictive Control, is a special type of control. Its current control action is obtained by solving a finite-time open-loop optimal control problem at each sampling moment. The current state of the process is used as the initial state of the optimal control problem, and the solved optimal control sequence only implements the first control action.

[0032] LQR, Linear Quadratic Regulator, can obtain the optimal control law of state linear feedback, and it is easy to form closed-loop optimal control. LQR optimal control can make the original system achieve better performance indicators at a low cost (in fact, it can also adjust unstable systems), and the method is simple and easy to implement. At the same time, it is easy to simulate the system using the powerful function system of Matlab.

[0033] EPS, Electrical Power Steering, electronic power steering system, uses the power generated by the electric motor to assist the driver in power steering.

[0034] ICA, Integrated Cruise Assist, lane cruise assist, works through the forward-looking camera and front millimeter-wave radar, and is used to reduce the driver's workload in monotonous driving environments or traffic congestion.

[0035] NDA, Navigated Driving Assist, is a navigation driving assistance system that can autonomously overtake, change lanes, enter and exit ramps, pass through ramps, merge into the main road, etc. according to the guidance of the navigation route or the surrounding traffic environment.

[0036] The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0037] See also Figure 1 , Figure 1 FIG. 1 is a flow chart of a vehicle control method provided by an embodiment of the present application. In a specific embodiment, the vehicle control method can be applied to Fig. 9 The vehicle control device 200 and the vehicle 100 equipped with the vehicle control device 200 are shown. Fig.10 ). The following will take a vehicle as an example to illustrate the specific process of this embodiment. Of course, it is understandable that the vehicle used in this embodiment may include desktop computers, laptops, vehicle terminals, large screens, cameras, millimeter wave radars and other devices, which are not limited here. Figure 1 The process shown is described in detail, and the vehicle control method may specifically include the following steps:

[0038] Step S110: Acquire the curve radius of the road on which the vehicle is traveling.

[0039] As an implementable manner, the vehicle may receive a control instruction input by a user, wherein the control instruction may be used to instruct the vehicle to activate a lane centering function (such as a lane centering function, a highway pilot driving assistance function, etc.). Accordingly, the vehicle may respond to the control instruction and activate the lane centering function, thereby controlling the vehicle to drive in the center.

[0040] As another feasible method, the vehicle can obtain the road curve radius of the road on which the vehicle is traveling when the road on which the vehicle is traveling is a transverse slope. The transverse slope refers to the transverse slope of each component of the road width and roadside strip, and refers to the transverse inclination of the road surface, dividing strip, sidewalk, green belt, etc.

[0041] As another feasible manner, the vehicle may obtain in real time the curve radius of the road on which the vehicle is traveling.

[0042] The vehicle may be provided with a camera, and accordingly, the vehicle may obtain data collected by the camera, and may obtain the road curve radius of the road on which the vehicle is traveling based on the data. The vehicle may obtain the roll angle, yaw angle, pitch angle, heading angle, etc. of the vehicle through the data collected by the camera; and may determine the lane lines on both sides of the road on which the vehicle is traveling based on the data, and may determine the center lines of the lane lines on both sides as the lane line center lines, and may determine the lateral distance between the center of the vehicle's rear axle and the lane center line as the centering error.

[0043] The vehicle can determine the lane line of the road the vehicle is traveling on based on the data collected by the camera: Y = A0 + A1 X + (A2 / 2) X 2 . Wherein, X can represent the longitudinal distance of the vehicle, A0 can represent the centering error of the vehicle, A1 can represent the heading angle of the vehicle, and A2 can represent the curvature of the road on which the vehicle is traveling, wherein the curvature can be the inverse of the curve radius of the road on which the vehicle is traveling. Accordingly, the vehicle can determine the curve radius of the vehicle's road according to the equation and the data collected by the camera.

[0044] Step S120: Obtain target correction parameters based on the road curve radius and the motion state of the vehicle, wherein the motion state of the vehicle includes the roll angle of the vehicle, the centering error of the vehicle, the steering wheel torque of the vehicle, and the deformation of the chassis elements of the vehicle, and the target correction parameters are used to correct the control parameters of the vehicle in a cross slope scenario so that the vehicle can travel in the center of the road.

[0045] In some embodiments, after obtaining the road radius of the road on which the vehicle is traveling, the vehicle may obtain a target correction parameter according to the road curve radius and the motion state of the vehicle. The motion state of the vehicle may include the roll angle of the vehicle, the centering error of the vehicle, the steering wheel hand torque of the vehicle, the deformation of the chassis element of the vehicle, the yaw angle of the vehicle, the pitch angle of the vehicle, the heading angle of the vehicle, etc. The target correction parameter may be used to correct the control parameters of the vehicle in a cross slope scenario so that the vehicle can travel in the center of the road.

[0046] Among them, a camera can be provided on the vehicle, and accordingly, the vehicle can obtain data collected by the camera provided on the vehicle to obtain the vehicle's roll angle, yaw angle, pitch angle, heading angle, etc.; and the double-side lane lines of the road on which the vehicle is traveling can be determined based on the data collected by the camera, and the center line of the double-side lane lines can be determined as the lane line center line, and the lateral distance between the center of the vehicle's rear axle and the lane center line can be determined as the centering error.

[0047] Among them, the steering wheel hand torque can represent the degree of human intervention of the driver on the steering wheel in the vehicle, and can be measured by the EPS end torque sensor in the vehicle.

[0048] The deformation of the chassis element of the vehicle can be understood as the spring offset on the vehicle. Optionally, a displacement sensor can be provided on the spring bracket of the chassis element of the vehicle; accordingly, the vehicle can obtain the movement of the spring through the displacement sensor, and obtain the deformation of the chassis element of the vehicle according to the movement.

[0049] In some embodiments, the first mapping relationship, the second mapping relationship, the third mapping relationship, the fourth mapping relationship and the fifth mapping relationship may be pre-set in the vehicle; the vehicle may also obtain the first mapping relationship, the second mapping relationship, the third mapping relationship, the fourth mapping relationship and the fifth mapping relationship from an associated cloud or electronic device through wireless communication technology (such as Bluetooth, WiFi, zigbee and other wireless communication technologies), or obtain the first mapping relationship, the second mapping relationship, the third mapping relationship, the fourth mapping relationship and the fifth mapping relationship from an associated electronic device through a serial communication interface (such as a serial bus, a serial peripheral interface, etc.).

[0050] Optionally, the first mapping relationship may include a correspondence between a roll angle and a first correction factor, wherein different roll angles may correspond to different first correction factors or the same first correction factor. Accordingly, after the vehicle obtains the roll angle of the vehicle, the first correction factor corresponding to the roll angle may be determined from the first mapping relationship. Optionally, the second mapping relationship may include a correspondence between a centering error and a second correction factor, wherein different centering errors may correspond to different second correction factors or the same second correction factor. Accordingly, after the vehicle obtains the centering error of the vehicle, the second correction factor corresponding to the centering error may be determined from the second mapping relationship. Optionally, the third mapping relationship may include a correspondence between a steering wheel hand torque and a third correction factor, wherein different steering wheel hand torques may correspond to different third correction factors or the same third correction factor. Accordingly, after the vehicle obtains the steering wheel hand torque of the vehicle, the third correction factor corresponding to the steering wheel hand torque may be determined from the third mapping relationship. Optionally, the fourth mapping relationship may include a correspondence between a chassis component change and a fourth correction factor, wherein different chassis component changes correspond to different fourth correction factors, or may correspond to the same fourth correction factor. Accordingly, after the vehicle obtains the chassis component change of the vehicle, the fourth correction factor corresponding to the chassis component change may be determined from the fourth mapping relationship. Optionally, the fifth mapping relationship may include a correspondence between a road curve radius and a fifth correction factor, wherein different road curve radii correspond to different fifth correction factors, or may correspond to the same fifth correction factor. Accordingly, after the vehicle obtains the road curve radius of the vehicle, the fifth correction factor corresponding to the road curve radius may be determined from the fifth mapping relationship.

[0051] It is understandable that in order to ensure that the dynamic and static characteristics of the sensor are within the design range under different use environments, it is necessary to conduct a comprehensive test of its technical performance; wherein, the method of sensor calibration can be to input a known measured quantity into the sensor to be calibrated, obtain the output of the sensor, and obtain a series of calibration curves characterizing the corresponding relationship between the two by processing and comparing the input and output, and then obtain the actual measurement results of the sensor performance indicators. In addition, considering that a set of parameters with vehicle yaw angle, pitch angle, and roll angle will be obtained through sensor calibration when the whole vehicle is off the assembly line, according to the calibration scenario, the parameters of vehicle yaw angle, pitch angle, and roll angle are infinitely close to 0 in an ideal situation. Based on this, the electronic device can obtain the matching relationship between the quantitatively obtained vehicle roll angle and the road slope when the vehicle is traveling on a road with different known lateral inclinations, and obtain the corresponding vehicle control correction parameters when the vehicle is traveling on a road with different known lateral inclinations, so that the slope of the vehicle's driving road surface can be determined according to the matching relationship, and the vehicle control correction parameters (first correction factor) corresponding to different roll angles can be obtained, thereby obtaining the first mapping relationship. Accordingly, the vehicle can obtain the first mapping relationship from the electronic device.

[0052] For example, see Figure 2 , which shows a schematic diagram of a first mapping relationship provided by an embodiment of the present application. The first mapping relationship may include a correspondence between multiple roll angles α and multiple first correction factors K_α, and may also include a correspondence between multiple road surfaces with multiple lateral inclinations and multiple first correction factors K_α.

[0053] In some embodiments, referring to national standards, ordinary lanes, and passenger car sizes, it can be estimated that the lane width is generally 3.75m, and the width of the vehicle can be 1.9m; ​​based on this, the centering error can be between [-1, 1]m, where the vehicle can be set to + when it is left relative to the vehicle centerline, and - when it is right relative to the vehicle centerline. Based on this, the electronic device obtains the vehicle control correction parameters (second correction factors) corresponding to the vehicle under different known centering errors, thereby obtaining a second mapping relationship. Accordingly, the vehicle can obtain the second mapping relationship from the electronic device.

[0054] For example, see Figure 3 , which shows a schematic diagram of a second mapping relationship provided by an embodiment of the present application. The second mapping relationship may include a correspondence relationship between a plurality of centering errors β and a plurality of second correction factors K_β.

[0055] In some embodiments, considering that the centering error of the vehicle will change in a cross-slope scenario, and the vehicle will deviate to one side for a long time, in this scenario, the driver usually takes over the vehicle by hand and slightly pulls the vehicle back to the center of the lane; based on this, in this embodiment, the steering wheel hand torque and the cross-slope scenario can be associated. Among them, the electronic device can obtain the vehicle control correction parameter (third correction factor) corresponding to the vehicle under different known steering wheel hand torques, thereby obtaining a third mapping relationship. Accordingly, the vehicle can obtain the third mapping relationship from the electronic device.

[0056] For example, see Figure 4 , which shows a schematic diagram of a third mapping relationship provided by an embodiment of the present application. The third mapping relationship may include a correspondence relationship between multiple steering wheel hand torques θ and multiple third correction factors K_θ.

[0057] In some embodiments, considering that the vehicle is on a horizontal road and the load is evenly distributed, the weight of the left and right wheels is symmetrical, so that the deformation of the left and right chassis spring elements in an ideal state can be obtained; however, when the vehicle is traveling on a transverse slope road, due to the inclination of one side of the road, the center of gravity of the vehicle will be shifted to the side with lower terrain, resulting in a large compression of the elastic element of the vehicle on the side with lower terrain. Based on this, in this embodiment, the electronic device can obtain the deformation of the elastic elements of the left and right wheels when the vehicle is traveling on different known transverse slope inclinations, and can calculate the mean of the deformation of the left and right elastic elements and the difference between the mean of the deformation of the left and right sides, and can obtain the vehicle control correction parameter (fourth correction factor) corresponding to the vehicle under different known mean of the deformation of the left and right elastic elements and the difference between the mean of the deformation of the left and right sides, so as to obtain the fourth mapping relationship. Accordingly, the vehicle can obtain the fourth mapping relationship from the electronic device.

[0058] For example, see Figure 5 , which shows a schematic diagram of a fourth mapping relationship provided by an embodiment of the present application. The fourth mapping relationship may include a correspondence between a plurality of left and right elastic element deformation differences and a plurality of fourth correction factors Σ, and may also include a correspondence between a plurality of cross slope inclinations and a plurality of fourth correction factors Σ.

[0059] In some implementations, considering that the radius of a road curve has an impact on the vehicle's centering driving control, for example, the accuracy of the vehicle's centering driving control is different when the road is a straight road and when the road is a curve. Based on this, in this embodiment, the electronic device can obtain the vehicle control correction parameter (fifth correction factor) corresponding to the vehicle traveling on different road curve radii, thereby obtaining the fifth mapping relationship. Accordingly, the vehicle can obtain the fifth mapping relationship from the electronic device.

[0060] For example, see Figure 6 , which shows a schematic diagram of a fifth mapping relationship provided by an embodiment of the present application. The fifth mapping relationship may include a correspondence relationship between multiple road curve radii and multiple fifth correction factors γ.

[0061] As an implementable manner, the vehicle may obtain the target correction parameter according to the first correction factor, the second correction factor, the third correction factor, the fourth correction factor and the fifth correction factor.

[0062] As an implementable manner, the vehicle may determine the minimum value, maximum value, average value, median value, mode, arithmetic mean value, etc. of the first correction factor, the second correction factor, the third correction factor, the fourth correction factor, and the fifth correction factor as the target correction parameter.

[0063] Optionally, the vehicle may be pre-set with weight parameters corresponding to the first correction factor, the second correction factor, the third correction factor, the fourth correction factor, and the fifth correction factor; accordingly, the vehicle may obtain the target correction parameter according to the weight parameters corresponding to the first correction factor, the second correction factor, the third correction factor, the fourth correction factor, and the fifth correction factor, and the first correction factor, the second correction factor, the third correction factor, the fourth correction factor, and the fifth correction factor. Exemplarily, the first correction factor is α, the second correction factor is β, the third correction factor is θ, the fourth correction factor is Σ, and the fifth correction factor is γ, the weight parameter corresponding to the first correction factor is a, the weight parameter corresponding to the second correction factor is b, the weight parameter corresponding to the third correction factor is c, the weight parameter corresponding to the fourth correction factor is d, and the weight parameter corresponding to the fifth correction factor is e.

[0064] Among them, a, b, c, d, and e can respectively represent the accuracy of the sensor side deviation error, centering error, steering wheel hand torque, chassis deformation, and road curve radius corresponding to the roll angle in reflecting the cross slope scene, and the values ​​can all be [0, 1]. In some embodiments, considering that the sensor side deviation error accurately feedbacks the road inclination, the chassis deformation is easily affected by the load, and the evaluation effect of the cross slope accuracy is attenuated, based on this, in this embodiment, a>b≈c≈e>d can be set.

[0065] Optionally, the vehicle may obtain the target correction parameter K according to a first calculation formula, wherein the first calculation formula is: K = a×α+b×β+c×θ+d×∑+e×γ. Optionally, the vehicle may also obtain the target correction parameter K according to a second calculation formula, wherein the second calculation formula is: K = (a×α+b×β+c×θ+d×∑)×γ.

[0066] In some embodiments, after the vehicle obtains the target correction parameter based on the curve radius of the road on which the vehicle is traveling and the motion state of the vehicle, the target correction parameter can be normalized to obtain a normalized target correction parameter between [0, 1].

[0067] In some implementations, considering that when the vehicle crosses the lane line, the centering error is too large and the centering keeping function is abnormal; based on this, in this embodiment, if the vehicle determines that the vehicle crosses the lane line according to the motion state, the vehicle can be controlled to exit the centering keeping function. The vehicle can also output information for prompting the vehicle to exit the centering keeping function to improve the user experience.

[0068] Step S130: Determine the control parameters of the vehicle based on the target correction parameters.

[0069] In some embodiments, after the vehicle obtains the target correction parameter, the control parameter of the vehicle can be determined based on the target correction parameter. The control parameter may include a steering wheel angle, a steering wheel torque, a brake deceleration, etc. Exemplarily, a centered driving control model may be pre-set in the vehicle, and the control model corresponds to the original control parameter; accordingly, after the vehicle obtains the target correction parameter, the product of the original control parameter and the target correction parameter may be used as the control parameter, and the steering wheel angle, steering wheel torque, brake deceleration, etc. output by the control model may be obtained based on the control parameter acting on the control model.

[0070] Step S140: Controlling the vehicle driving based on the control parameters.

[0071] In some embodiments, after the vehicle obtains the control parameter, the control parameter can be input into the actuator of the vehicle to control the vehicle to travel based on the control parameter. For example, the vehicle can input the control parameter into the EPS execution system of the vehicle to control the vehicle to travel.

[0072] It can be understood that in this embodiment, the vehicle can decompose the characteristics of the cross slope into detailed parameters that can be used for vehicle control (such as the vehicle's roll angle, the vehicle's centering error, the road curve radius of the road on which the vehicle is traveling, the vehicle's steering wheel torque, the vehicle's chassis component deformation, etc.), and can obtain target correction parameters for the cross slope for vehicle control by analyzing the relationship between the parameters and the vehicle's centering driving control, thereby optimizing the vehicle's ability to center in cross slope scenarios and improving the accuracy and safety of lane centering driving control.

[0073] A vehicle control method provided in an embodiment of the present application obtains correction parameters for vehicle control based on the vehicle's roll angle, centering error, road curve radius of the road, steering wheel torque, and chassis component deformation when the road on which the vehicle is traveling is a transverse slope, dynamically adjusts the vehicle's control parameters based on the correction parameters, and controls vehicle driving based on the control parameters, thereby optimizing the accuracy of vehicle centering driving control during the activation of the lane centering assist function in a transverse slope scenario.

[0074] See also Figure 7 , Figure 7 The flow chart of the vehicle control method provided by an embodiment of the present application is shown in FIG. Figure 7 The process shown is described in detail, and the vehicle control method may specifically include the following steps:

[0075] Step S210: Obtain the curve radius of the road on which the vehicle is traveling.

[0076] For the specific description of step S210, please refer to the above description of step S110, which will not be repeated here.

[0077] Step S220: determining a first correction factor according to the roll angle and a first mapping relationship, wherein the first mapping relationship includes a correspondence between the roll angle and the first correction factor, and different roll angles correspond to different first correction factors.

[0078] In some embodiments, the vehicle may determine the first correction factor according to the roll angle of the vehicle and the first mapping relationship. The first mapping relationship may include a correspondence between the roll angle and the first correction factor, and different roll angles correspond to different first correction factors. The first mapping relationship may be pre-set in the vehicle.

[0079] In some embodiments, the vehicle may obtain the current position, target position, and motion state of the vehicle before obtaining the target correction parameters based on the road curve radius and motion state of the road. If it is determined that the deviation between the current position and the target position is greater than a deviation threshold, it may be determined whether the road on which the vehicle is traveling is a horizontal slope based on the motion state of the vehicle and the road curve radius of the road. If it is determined that the road on which the vehicle is traveling is a horizontal slope, the target correction parameters may be obtained based on the road curve radius and motion state of the road.

[0080] The target position of the vehicle can be determined based on the lane line of the road on which the vehicle is traveling; the target position can correspond to the current position of the vehicle, which is the position that the vehicle is expected to reach at the next moment. Optionally, the target position of the vehicle can be a position on the center line of the lane lines on both sides of the road on which the vehicle is traveling (lane center line). Optionally, the target position can be determined based on the navigation path of the vehicle, and can include but is not limited to the position determined based on the navigation path to control the vehicle to travel from the current position to the position approaching the navigation path. A deviation threshold can be pre-set in the vehicle, and the deviation threshold can be set by the user independently, or obtained through third-party experimental data.

[0081] Optionally, the vehicle can obtain the current position of the vehicle and the target position of the vehicle through the navigation and positioning system, and can obtain the deviation between the current position of the vehicle and the target position of the vehicle, and can compare the deviation with the deviation threshold, and can determine whether to detect whether the vehicle is in a horizontal slope scene according to the comparison result. Exemplarily, if it is determined that the deviation between the current position and the target position is greater than the deviation threshold, it can be determined whether the road on which the vehicle is traveling is a horizontal slope according to the movement state of the vehicle.

[0082] Among them, the vehicle can detect the vehicle's motion state and the road curve radius of the road on which the vehicle is traveling in real time through cameras, millimeter radar waves, torque sensors and other equipment; among them, the vehicle's motion state can include the vehicle's roll angle, centering error, steering wheel hand torque, chassis component deformation, yaw angle, pitch angle, heading angle, etc.

[0083] As an implementable manner, the vehicle may determine whether the road on which the vehicle is traveling is a transverse slope according to the roll angle of the vehicle. For example, a first threshold may be pre-set in the vehicle; wherein, if the vehicle determines that the roll angle is greater than the first threshold, it may be determined that the road on which the vehicle is traveling is a transverse slope.

[0084] As another practicable manner, the vehicle may determine whether the road on which the vehicle is traveling is a transverse slope based on the centering error of the vehicle. For example, a first time duration and a second threshold value may be pre-set in the vehicle; wherein, if the vehicle determines that the centering error is continuously greater than the second threshold value within the first time duration, it may be determined that the road on which the vehicle is traveling is a transverse slope.

[0085] Optionally, a first range may also be pre-set in the vehicle. Accordingly, if the vehicle also detects that the centering error continues within the first range for a first time period, it can be determined that the road on which the vehicle is traveling is a transverse slope. Among them, considering the case where the vehicle's lateral cruise assist function is activated and controlled (such as ICA, NDA, etc.), the centering error in the scenario of non-large curvature curves (within 300m) is generally distributed within [-0.2m, 0.2m]; in addition, due to the poor centering phenomenon of large curvature curves themselves, the coupling with the poor centering caused by the transverse slope is relatively large, and the scene characteristics are difficult to accurately distinguish. Based on this, in this embodiment, the first range can be within [-0.2m, 0.2m], so as to optimize the vehicle's centering driving control for small curvature transverse slope scenarios.

[0086] As another practicable manner, the vehicle may determine whether the road on which the vehicle is traveling is a transverse slope according to the curvature corresponding to the road curve radius of the vehicle. The curvature corresponding to the road curve radius is the inverse of the road curve radius. Exemplarily, a third threshold may be pre-set in the vehicle; if the vehicle determines that the curvature corresponding to the road curve radius of the vehicle is greater than the third threshold, it may be determined that the road on which the vehicle is traveling is a transverse slope.

[0087] As another feasible method, the vehicle can judge whether the road the vehicle is traveling on is a transverse slope according to the direction of the steering wheel hand torque and the direction of the centering error. Among them, considering the characteristic that the driver subjectively wants to correct the direction in the scenario of poor centering, based on this, in this embodiment, if the vehicle determines that the direction of the steering wheel hand torque of the vehicle is opposite to the direction of the centering error of the vehicle, it can be determined that the road the vehicle is traveling on is a transverse slope, so that when the direction of the steering wheel hand torque is opposite to the direction of the centering error, it is determined that the vehicle has entered a transverse slope scenario, and when the direction of the steering wheel hand torque is the same as the direction of the centering error, the target control parameter of the vehicle can be determined to be 1, so that the vehicle centering control is optimized for the opposite direction of the steering wheel hand torque and the centering error, thereby improving the effectiveness of the optimized control and reducing the power consumption of the optimized control.

[0088] As another practicable manner, the vehicle may determine whether the road on which the vehicle is traveling is a transverse slope according to the deformation amount of the chassis element of the vehicle. For example, a fourth threshold value may be pre-set in the vehicle; wherein, if it is determined that the deformation amount of the chassis element of the vehicle is greater than the fourth threshold value, it may be determined that the road on which the vehicle is traveling is a transverse slope.

[0089] In some embodiments, the chassis component deformation amount of the vehicle may include the left chassis component deformation amount of the vehicle and the right chassis component deformation amount of the vehicle. In the process of judging whether the road on which the vehicle is traveling is a transverse slope according to the chassis component deformation amount of the vehicle, the difference between the left chassis component deformation amount of the vehicle and the right chassis component deformation amount of the vehicle may be obtained, and whether the road on which the vehicle is traveling is a transverse slope may be determined according to the difference. Exemplarily, a fifth threshold value may be pre-set in the vehicle; in the case where it is determined that the difference between the left chassis component deformation amount of the vehicle and the right chassis component deformation amount of the vehicle is greater than the fifth threshold value, it may be determined that the road on which the vehicle is traveling is a transverse slope.

[0090] Optionally, a sixth threshold may be pre-set in the vehicle; wherein the vehicle may also obtain the maximum value of the deformation of the left chassis component of the vehicle and the deformation of the right chassis component of the vehicle. If it is determined that the maximum value is greater than the sixth threshold, it can be determined that the road on which the vehicle is traveling is a horizontal slope.

[0091] As an implementable method, if it is determined that the vehicle's roll angle is greater than a first threshold, the vehicle's centering error is continuously greater than a second threshold within a first time period, the curvature corresponding to the vehicle's road curve radius is greater than a third threshold, the direction of the vehicle's steering wheel torque is opposite to the direction of the vehicle's centering error, and the vehicle's chassis element deformation is greater than a fourth threshold, then it can be determined that the road the vehicle is traveling on is a cross slope, thereby determining whether the road the vehicle is traveling on is a cross slope based on the vehicle's motion state, thereby improving the accuracy of cross slope scenario determination and the accuracy of vehicle centering control optimization in cross slope scenarios.

[0092] Optionally, when the vehicle determines that the road it is traveling on is a transverse slope, the vehicle may determine the first correction factor according to the roll angle in the motion state of the vehicle and the first mapping relationship. The vehicle may obtain the first correction factor corresponding to the roll angle of the vehicle from the first mapping relationship as the first correction factor.

[0093] Step S230: determining a second correction factor according to the centering error and a second mapping relationship, wherein the second mapping relationship includes a correspondence between the centering error and the second correction factor, and different centering errors correspond to different second correction factors.

[0094] In some embodiments, the vehicle may determine the second correction factor according to the centering error in the motion state of the vehicle and the second mapping relationship. The vehicle may be pre-set with the second mapping relationship, wherein the second mapping relationship may include a correspondence between the centering error and the second correction factor, and different centering errors correspond to different second correction factors. The vehicle may obtain the correction factor corresponding to the centering error of the vehicle from the second mapping relationship as the second correction factor.

[0095] Step S240: Determine a third correction factor according to the steering wheel hand torque and a third mapping relationship, wherein the third mapping relationship includes a correspondence between the steering wheel hand torque and the third correction factor, and different steering wheel hand torques correspond to different third correction factors.

[0096] In some embodiments, the vehicle may determine the third correction factor according to the steering wheel hand torque in the motion state of the vehicle and the third mapping relationship. The vehicle may be pre-set with a third mapping relationship, wherein the third mapping relationship may include a correspondence between the steering wheel hand torque and the third correction factor, and different steering wheel hand torques correspond to different third correction factors. The vehicle may obtain a correction factor corresponding to the steering wheel hand torque of the vehicle from the third mapping relationship as the third correction factor.

[0097] Step S250: determining a fourth correction factor according to the chassis component variation and a fourth mapping relationship, wherein the fourth mapping relationship includes a correspondence between the chassis component variation and the fourth correction factor, and different chassis component variations correspond to different fourth correction factors.

[0098] In some embodiments, the vehicle may determine the fourth correction factor according to the change amount of the chassis component in the motion state of the vehicle and the fourth mapping relationship. The fourth mapping relationship may be pre-set in the vehicle, wherein the fourth mapping relationship may include a correspondence between the change amount of the chassis component and the fourth correction factor, and different changes in chassis components correspond to different fourth correction factors. The vehicle may obtain the correction factor corresponding to the change amount of the chassis component of the vehicle from the fourth mapping relationship as the fourth correction factor.

[0099] Step S260: Obtain the target correction parameter according to the road curve radius, the first correction factor, the second correction factor, the third correction factor and the fourth correction factor.

[0100] In some embodiments, the vehicle may obtain a target correction parameter based on a road curve radius of the vehicle, a first correction factor corresponding to the vehicle, a second correction factor corresponding to the vehicle, a third correction factor corresponding to the vehicle, and a fourth correction factor corresponding to the vehicle.

[0101] In some embodiments, considering that the large curvature curve itself has a poor centering phenomenon, and the coupling with the poor centering caused by the cross slope is relatively large, the scene features are difficult to accurately distinguish. Based on this, in this embodiment, the vehicle can optimize the centering control for the small curvature curve; wherein, a first radius threshold can be pre-set in the vehicle, and the first radius threshold can be used as a basis for judging whether the road the vehicle is traveling on is a small curvature curve; it can be set by the user independently, or obtained through third-party experimental data, and illustratively, the first radius threshold is 300m.

[0102] In some embodiments, considering that the driver has a stronger sense of security about lateral deviation in a straight road scenario than in a curve, the driver also has a certain probability of intervention in a large lateral deviation error scenario, so the correction factor of the vehicle mainly depends on the sensor deviation error, centering error, driver's hand torque and chassis component deformation. Based on this, in this embodiment, a second radius threshold can be pre-set in the vehicle, and the second radius threshold can be used as a basis for judging whether the road the vehicle is traveling on is a straight road; wherein the second radius threshold can be greater than the first radius threshold, and can be set by the user independently, or obtained through third-party experimental data, and illustratively, the second radius threshold is 3000m.

[0103] As an implementable method, if the vehicle determines that the radius of the vehicle's road curve is less than the first radius threshold, the target correction parameter can be determined as 1, thereby optimizing the centering control for small curvature curves and avoiding optimizing the vehicle's centering performance in large curvature slope scenarios, thereby reducing the power consumption of the vehicle's centering performance optimization and improving the accuracy of the vehicle's centering performance optimization.

[0104] If it is determined that the vehicle's road curve radius is greater than or equal to the first radius threshold, and the road curve radius is less than the second radius threshold, it can be determined that the vehicle is traveling on a small curvature curve; accordingly, the vehicle can determine the correction factor of the vehicle's centering driving control based on the sensor deviation error, centering error, driver's hand torque, and chassis component deformation. In addition, considering that during the vehicle's driving, the probability of driver intervention is low in the small lateral deviation error scenario, and the probability of driver intervention in the large lateral deviation error scenario is high; wherein, in the case of driver intervention, the correction factor mainly depends on the sensor deviation error, centering error, driver's hand torque, and chassis component deformation; wherein, in the case of driver non-intervention, the correction factor mainly depends on the sensor deviation error and centering error. Based on this, the vehicle can be pre-set with a first error and a second error, wherein the first error is less than the second error; the first error and the second error can be used as a basis for judging whether the vehicle's driving scenario is a large lateral deviation error scenario or a small lateral deviation error scenario; it can be set by the user independently, or obtained through third-party experimental data, and for example, the first error is 0.1m and the second error is 0.2m. Among them, the situation where the vehicle's centering error is greater than the second error can be determined as a large lateral deviation error scenario, the situation where the centering error is less than or equal to the second error and greater than or equal to the first error can be determined as a small lateral deviation error scenario; the situation where the centering error is less than the first error can be determined as a scenario where no centering driving adjustment is required.

[0105] Among them, if the curve radius of the road on which the vehicle is determined to be traveling is greater than or equal to a first radius threshold, and the curve radius of the road is less than a second radius threshold, then a first relationship between the centering error corresponding to the vehicle and the first error and the second error can be obtained; and the target correction parameter can be obtained based on the first relationship, the first correction factor corresponding to the vehicle, the second correction factor corresponding to the vehicle, the third correction factor corresponding to the vehicle, and the fourth correction factor corresponding to the vehicle.

[0106] As an implementable embodiment, if the vehicle determines that the curve radius of the road it is traveling on is greater than or equal to a first radius threshold, and the curve radius of the road is less than a second radius threshold, and the centering error corresponding to the vehicle is greater than or equal to the first error, and less than or equal to the second error, then the target correction parameter can be obtained based on the first correction factor and the second correction factor.

[0107] As another possible implementation, if the vehicle determines that the curve radius of the road it is traveling on is greater than or equal to a first radius threshold, and the curve radius of the road is less than a second radius threshold, and the centering error is greater than the second error, then the target correction parameter is obtained based on the first correction factor, the second correction factor, the third correction factor and the fourth correction factor.

[0108] As another possible implementation, if the vehicle determines that the curve radius of the road it is traveling on is greater than or equal to a first radius threshold, and the curve radius of the road is less than a second radius threshold, and it is determined that the centering error of the vehicle is less than the first error, then the target correction parameter can be determined to be 1.

[0109] In some embodiments, a third radius threshold may be pre-set in the vehicle, and the third radius threshold may also be used as a basis for judging whether the road on which the vehicle is traveling is a straight road; wherein the third radius threshold may be the same as the second radius threshold, or may be different, and may be set by the user independently, or may be obtained through third-party experimental data, and exemplarily, the third radius threshold is 3000m. wherein a third error and a fourth error may be pre-set in the vehicle, and the third error and the fourth error may be used as a basis for judging whether the driving scene of the vehicle is a large lateral deviation error scene or a small lateral deviation error scene, and may be set by the user independently, or may be obtained through third-party experimental data, and exemplarily, the third error may be 0.1m, and the fourth error may be 0.3m. wherein a road with a turning radius between the first radius threshold and the second radius threshold may be determined as a curve, and considering that the correction factor for the vehicle's centering mainly depends on the sensor error, the centering error, the driver's hand torque, the chassis type variable, etc., the driver's sense of security for the centering deviation in the curve is weaker than that in the straight road, so the centering error calibration amount should be set smaller. based on this, in this embodiment, the third error may be smaller than the fourth error. Exemplarily, a scenario in which the vehicle's road curve radius is greater than or equal to the second radius threshold can be determined as a straight road scenario, a scenario in which the centering error is greater than or equal to the fourth error can be determined as a large lateral deviation error scenario, and a scenario in which the centering error is less than or equal to the fourth error and greater than or equal to the third error can be determined as a small lateral deviation error scenario.

[0110] Among them, if the road curve radius of the road on which the vehicle is determined to be traveling is greater than the third radius threshold, the second relationship between the centering error corresponding to the vehicle and the third error and the fourth error can be obtained, and the target correction parameter can be obtained based on the second relationship, the first correction factor corresponding to the vehicle, the second correction factor corresponding to the vehicle, the third correction factor corresponding to the vehicle, and the fourth correction factor corresponding to the vehicle.

[0111] As an implementable method, if it is determined that the road curve radius of the vehicle is greater than or equal to a third radius threshold, the centering error corresponding to the vehicle is greater than or equal to the third error, and less than or equal to the fourth error, the target correction parameter can be obtained based on the first correction factor and the second correction factor; or, if it is determined that the road curve radius of the vehicle is greater than or equal to the third radius threshold, and the centering error corresponding to the vehicle is greater than the fourth error, the target correction parameter can be obtained based on the first correction factor, the second correction factor, the third correction factor and the fourth correction factor; or, if it is determined that the road curve radius of the vehicle is greater than or equal to the third radius threshold, and the centering error corresponding to the vehicle is less than the third error, the target correction parameter can be determined to be 1.

[0112] In some embodiments, in the process of the vehicle obtaining the target correction parameter based on the first correction factor, the second correction factor, the third correction factor and the fourth correction factor, the product of the first correction factor and the first weight can be determined as the first correction parameter, the product of the second correction factor and the second weight can be determined as the second correction parameter, the product of the third correction factor and the third weight can be determined as the third correction parameter, the product of the fourth correction factor and the fourth weight can be determined as the fourth correction parameter, and the sum of the first correction parameter, the second correction parameter, the third correction parameter and the fourth correction parameter can be determined as the target correction parameter.

[0113] Among them, considering that the sensor side deviation error accurately feedbacks the road inclination, the chassis deformation is easily affected by the load, and the evaluation effect of the cross slope accuracy is attenuated; based on this, in this embodiment, the second weight can be less than the first weight; the second weight can be less than the first weight; the third weight can be less than the first weight; the fourth weight can be less than the first weight, and less than the second weight, and less than the third weight.

[0114] In some embodiments, considering that the centering error of the vehicle is too large, such as when the vehicle presses the center line, in this case, the user can clearly perceive that the vehicle is not driving in the center, based on which the user will manually intervene in the control of the vehicle driving. In this case, the auxiliary centering function of the vehicle will automatically exit, so there is no need to superimpose control parameters to control the centering of the vehicle. Based on this, a fifth error can be pre-set in the vehicle, and the fifth error can be greater than the fourth error, and the fifth error can be greater than the second error. Exemplarily, the fifth error can be 0.8m; accordingly, the vehicle can obtain the target correction parameters when the centering error is less than or equal to the fifth error, thereby improving the effectiveness and rationality of the centering control of the vehicle.

[0115] Exemplarily, the vehicle determines that the road on which the vehicle is traveling is a transverse slope, and determines, according to the vehicle's motion state, that the first correction factor of the vehicle is α, the second correction factor is β, the third correction factor is θ, the fourth correction factor is Σ, the road curve radius is R, and the centering error is H. Among them, the vehicle may be pre-set with a first weight of a, a second weight of b, a third weight of c, a fourth weight of d, a first radius threshold of 300m, a second radius threshold of 3000m, a third radius threshold of 3000m, a first error of 0.1m, a second error of 0.2m, a third error of 0.1m, a fourth error of 0.3m, and a fourth error of 0.8m.

[0116] If the road turning radius R ≥ 3000m, the vehicle can determine the target correction parameter K based on the first formula. The first formula is:

[0117]

[0118] If the road turning radius is 300m≤R<3000m, the vehicle can determine the target correction parameter K based on the second formula. The second formula is:

[0119]

[0120] Among them, the first weight is a, the second weight is b, the third weight is c, and the fourth weight is d, which can respectively reflect the accuracy of the cross slope scene by the sensor side deviation error, the centering error, the steering wheel hand torque, and the chassis deformation, and the values ​​are all [0, 1]; among them, the sensor side deviation error accurately feedbacks the road inclination, and the chassis deformation is easily affected by the load, and the evaluation effect of the cross slope accuracy is attenuated. Based on this, in this embodiment, a>b≈c>d. Among them, after the vehicle obtains the target correction parameter, K can be normalized to obtain a target correction parameter between [0, 1].

[0121] For example, see Figure 8, which shows a flow chart of a method for vehicle control provided by an embodiment of the present application. Wherein, the vehicle may include a vehicle execution system (such as EPS, etc.) and a vehicle control system. Wherein, when the vehicle's lateral cruise assist function (such as lane centering LCC, high-speed pilot driving assistance NOA, etc.) is activated, the vehicle can detect the actual position (current position) of the vehicle, the road curve radius and motion state of the road being traveled by the vehicle-mounted sensors (such as front smart camera, millimeter wave radar, displacement and steering wheel torque sensors) in real time, and can obtain the target position of the vehicle. Wherein, the vehicle can calculate the difference between the actual position and the target position through the ADAS controller, and when it is determined that the difference is greater than the deviation threshold, the steering wheel angle required for the vehicle to reach the target position is calculated by the control algorithm (such as PID, MPC, LQR, etc.) combined with feedforward or feedback and output to the execution system such as EPS, so as to control the vehicle to travel along the expected trajectory.

[0122] Among them, the vehicle can obtain the target correction parameter K of the vehicle in the cross slope scenario through the road curve radius of the road on which the vehicle is traveling and the motion state of the vehicle, and can use K as a correction factor for feedforward control or feedback control to directly act on the parameters of the vehicle motion control algorithm, thereby decomposing the typical characteristics of the cross slope to the sensor level, and calculating the dynamic vehicle control correction coefficient in the vehicle driving environment in real time through the sensor's perception data, and feeding it back to the intelligent assisted driving system controller to optimize the centering performance in the cross slope scenario, thereby improving the centering ability of the vehicle's lane centering keeping function or high-speed pilot driving assistance function in the cross slope scenario.

[0123] Step S270: Determine the control parameters of the vehicle based on the target correction parameters.

[0124] Step S280: Controlling the vehicle driving based on the control parameters.

[0125] For the detailed description of step S270 to step S280, please refer to the above description of step S130 to step S140, which will not be repeated here.

[0126] Compared with the vehicle control method provided in one embodiment of the present application, Figure 1The vehicle control method shown in the embodiment can also determine a first correction factor according to the roll angle and the first mapping relationship, wherein the first mapping relationship includes a corresponding relationship between the roll angle and the first correction factor, and different roll angles correspond to different first correction factors; determine a second correction factor according to the centering error and the second mapping relationship, wherein the second mapping relationship includes a corresponding relationship between the centering error and the second correction factor, and different centering errors correspond to different second correction factors; determine a third correction factor according to the steering wheel hand torque and the third mapping relationship, wherein the third mapping relationship includes a corresponding relationship between the steering wheel hand torque and the third correction factor, and different The steering wheel hand torque corresponds to different third correction factors; the fourth correction factor is determined according to the chassis component change and the fourth mapping relationship, wherein the fourth mapping relationship includes the correspondence between the chassis component change and the fourth correction factor, and different chassis component changes correspond to different fourth correction factors; the target correction parameter is obtained according to the road curve radius, the first correction factor, the second correction factor, the third correction factor and the fourth correction factor, so as to decompose the typical characteristics of the cross slope to the sensor level, and calculate the dynamic vehicle control correction coefficient in the vehicle driving environment in real time through the sensor perception data, thereby improving the accuracy of vehicle centering control.

[0127] See also Fig. 9 , Fig. 9 The module block diagram of the vehicle control device provided by an embodiment of the present application is shown. The vehicle control device 200 is applied to the above-mentioned vehicle. Fig. 9 The process shown in the figure is described in detail, the vehicle control device 200 includes: a road curve radius acquisition module 210, a target correction parameter acquisition module 220, a control parameter determination module 230 and a vehicle control module 240, wherein:

[0128] The road curve radius acquisition module 210 is used to acquire the road curve radius of the road on which the vehicle is traveling.

[0129] The target correction parameter acquisition module 220 is used to obtain the target correction parameters according to the road curve radius and the motion state of the vehicle, wherein the motion state of the vehicle includes the roll angle of the vehicle, the centering error of the vehicle, the steering wheel torque of the vehicle and the deformation of the chassis elements of the vehicle, and the target correction parameters are used to correct the control parameters of the vehicle in a cross slope scenario so that the vehicle can drive in the center of the road.

[0130] The control parameter determination module 230 is used to determine the control parameters of the vehicle based on the target correction parameters.

[0131] The vehicle control module 240 is used to control the driving of the vehicle based on the control parameters.

[0132] Further, the target correction parameter acquisition module 220 may include: a first correction factor determination unit, a second correction factor determination unit, a third correction factor determination unit, a fourth correction factor determination unit and a target correction parameter acquisition subunit, wherein:

[0133] The first correction factor determination unit is used to determine the first correction factor according to the roll angle and a first mapping relationship, wherein the first mapping relationship includes a correspondence between the roll angle and the first correction factor, and different roll angles correspond to different first correction factors.

[0134] The second correction factor determination unit is used to determine the second correction factor according to the centering error and a second mapping relationship, wherein the second mapping relationship includes a correspondence between the centering error and the second correction factor, and different centering errors correspond to different second correction factors.

[0135] The third correction factor determination unit is used to determine the third correction factor according to the steering wheel hand torque and the third mapping relationship, wherein the third mapping relationship includes the correspondence between the steering wheel hand torque and the third correction factor, and different steering wheel hand torques correspond to different third correction factors.

[0136] The fourth correction factor determination unit is used to determine the fourth correction factor according to the chassis component change amount and a fourth mapping relationship, wherein the fourth mapping relationship includes a correspondence between the chassis component change amount and the fourth correction factor, and different chassis component changes correspond to different fourth correction factors.

[0137] The target correction parameter obtaining subunit is used to obtain the target correction parameter according to the road curve radius, the first correction factor, the second correction factor, the third correction factor and the fourth correction factor.

[0138] Further, the target correction parameter obtaining subunit may include: a first relationship obtaining unit and a target correction parameter obtaining first unit, wherein:

[0139] The first relationship acquisition unit is used to acquire a first relationship between the centering error and the first error and the second error if the road curve radius is greater than or equal to a first radius threshold and the road curve radius is less than a second radius threshold, wherein the first error is less than the second error.

[0140] The target correction parameter obtaining first unit is used to obtain the target correction parameter according to the first relationship, the first correction factor, the second correction factor, the third correction factor and the fourth correction factor.

[0141] Further, the target correction parameter obtaining first unit may include: a target correction parameter obtaining second unit, a target correction parameter obtaining third unit and a target correction parameter obtaining fourth unit, wherein:

[0142] The target correction parameter obtaining second unit is used to obtain the target correction parameter according to the first correction factor and the second correction factor if the centering error is greater than or equal to the first error and less than or equal to the second error.

[0143] The target correction parameter obtaining third unit is used to obtain the target correction parameter according to the first correction factor, the second correction factor, the third correction factor and the fourth correction factor if the centering error is greater than the second error.

[0144] The target correction parameter obtaining fourth unit is used to determine that the target correction parameter is 1 if the centering error is less than the first error.

[0145] Further, the target correction parameter obtaining subunit may include: a second relationship obtaining unit and a target correction parameter obtaining fifth unit, wherein:

[0146] The second relationship acquisition unit is used to acquire a second relationship between the centering error and the third error and the fourth error if the road curve radius is greater than a third radius threshold, wherein the third error is smaller than the fourth error.

[0147] The target correction parameter obtaining fifth unit is used to obtain the target correction parameter according to the second relationship, the first correction factor, the second correction factor, the third correction factor and the fourth correction factor.

[0148] Further, the target correction parameter obtaining fifth unit may include: a target correction parameter obtaining sixth unit, a target correction parameter obtaining seventh unit and a target correction parameter obtaining eighth unit, wherein:

[0149] The sixth unit for obtaining a target correction parameter is configured to obtain the target correction parameter according to the first correction factor and the second correction factor if the centering error is greater than or equal to the third error and less than or equal to the fourth error.

[0150] The seventh unit for obtaining a target correction parameter is configured to obtain the target correction parameter according to the first correction factor, the second correction factor, the third correction factor and the fourth correction factor if the centering error is greater than the fourth error.

[0151] The target correction parameter obtaining eighth unit is used to determine that the target correction parameter is 1 if the centering error is less than the third error.

[0152] Further, the target correction parameter obtaining third unit or the target correction parameter obtaining seventh unit may include: a first correction parameter determining unit, a second correction parameter determining unit, a third correction parameter determining unit, a fourth correction parameter determining unit and a target correction parameter obtaining first subunit, wherein:

[0153] The first correction parameter determining unit is used to determine the product of the first correction factor and the first weight as a first correction parameter.

[0154] The second correction parameter determination unit is used to determine the product of the second correction factor and a second weight as a second correction parameter, wherein the second weight is smaller than the first weight.

[0155] The third correction parameter determination unit is used to determine the product of the third correction factor and a third weight as a third correction parameter, wherein the third weight is smaller than the first weight.

[0156] A fourth correction parameter determination unit is used to determine the product of the fourth correction factor and a fourth weight as a fourth correction parameter, wherein the fourth weight is smaller than the first weight, smaller than the second weight, and smaller than the third weight.

[0157] The target correction parameter obtaining first subunit is used to determine the sum of the first correction parameter, the second correction parameter, the third correction parameter and the fourth correction parameter as the target correction parameter.

[0158] Furthermore, before obtaining the target correction parameter according to the road curve radius and the motion state of the vehicle, the vehicle control device 200 may further include: a motion state acquisition unit and a cross slope judgment unit, wherein:

[0159] A motion state acquisition unit is used to acquire the current position of the vehicle, the target position and the motion state of the vehicle, wherein the target position is determined according to the lane line of the road on which the vehicle is traveling.

[0160] The transverse slope judgment unit is used to judge whether the road on which the vehicle is traveling is a transverse slope according to the movement state of the vehicle and the radius of the road curve if the deviation between the current position and the target position is greater than a deviation threshold.

[0161] Further, the transverse slope judgment unit may include: a first transverse slope judgment unit, a second transverse slope judgment unit, a third transverse slope judgment unit, a fourth transverse slope judgment unit and a fifth transverse slope judgment unit, wherein:

[0162] The first transverse slope judgment unit is used to determine that the road on which the vehicle is traveling is a transverse slope if the roll angle is greater than a first threshold value.

[0163] The second transverse slope judgment unit is used to determine that the road on which the vehicle is traveling is a transverse slope if the centering error of the vehicle is continuously greater than a second threshold value within a first time period.

[0164] The third transverse slope judgment unit is used to determine that the road on which the vehicle is traveling is a transverse slope if the curvature corresponding to the road curve radius is greater than a third threshold, wherein the curvature corresponding to the road curve radius is the inverse of the road curve radius.

[0165] The fourth transverse slope judgment unit is used to determine that the road on which the vehicle is traveling is a transverse slope if the direction of the steering wheel hand torque is opposite to the direction of the centering error.

[0166] The fifth transverse slope judgment unit is used to determine that the road on which the vehicle is traveling is a transverse slope if the deformation amount of the chassis element is greater than a fourth threshold value.

[0167] Further, the chassis element deformation amount includes the left chassis element deformation amount of the vehicle and the right chassis element deformation amount of the vehicle, and the cross slope fifth judgment unit may include: a cross slope fifth judgment subunit, wherein:

[0168] The fifth transverse slope judgment subunit is used to determine that the road on which the vehicle is traveling is a transverse slope if the difference between the deformation amount of the left chassis element and the deformation amount of the right chassis element is greater than a fifth threshold.

[0169] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0170] In several embodiments provided in the present application, the coupling between modules may be electrical, mechanical or other forms of coupling.

[0171] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated modules can be implemented in the form of hardware or software functional modules.

[0172] See also Fig.10, which shows a structural block diagram of a vehicle provided in an embodiment of the present application. The vehicle 100 may be an electric vehicle, a tricycle, a gasoline vehicle, a two-wheel vehicle, or other vehicle with processing capabilities. The vehicle 100 in the present application may include one or more of the following components: a processor 110, a memory 120, and one or more applications, wherein one or more applications may be stored in the memory 120 and configured to be executed by one or more processors 110, and one or more programs are configured to execute the method as described in the aforementioned method embodiment.

[0173] Among them, the processor 110 may include one or more processing cores. The processor 110 uses various interfaces and lines to connect various parts of the entire vehicle 100, and executes various functions and processes data of the vehicle 100 by running or executing instructions, programs, code sets or instruction sets stored in the memory 120, and calling data stored in the memory 120. Optionally, the processor 110 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 110 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed; and the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 110, but may be implemented separately through a communication chip.

[0174] The memory 120 may include a random access memory (RAM) or a read-only memory (ROM). The memory 120 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the following various method embodiments, etc. The data storage area may also store data created by the vehicle 100 during use (such as a phone book, audio and video data, chat record data), etc.

[0175] See also Fig.11, which shows a structural block diagram of a computer-readable storage medium provided in an embodiment of the present application. The computer-readable medium 300 stores program codes, which can be called by a processor to execute the method described in the above method embodiment.

[0176] The computer readable storage medium 300 can be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk or a ROM. Optionally, the computer readable storage medium 300 includes a non-transitory computer-readable storage medium. The computer readable storage medium 300 has storage space for program code 310 that performs any method steps in the above method. These program codes can be read from or written to one or more computer program products. The program code 310 can be compressed, for example, in an appropriate form.

[0177] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A vehicle control method, characterized in that: The method comprises: Obtaining the road curve radius of the road on which the vehicle is traveling; According to the road curve radius and the motion state of the vehicle, a target correction parameter is obtained, wherein the motion state of the vehicle includes the roll angle of the vehicle, the centering error of the vehicle, the steering wheel hand torque of the vehicle, and the deformation of the chassis element of the vehicle, and the target correction parameter is used to correct the control parameter of the vehicle in a cross slope scenario so that the vehicle drives in the center of the road; determining a control parameter of the vehicle based on the target correction parameter; The vehicle is controlled to travel based on the control parameter.

2. The method according to claim 1, characterized in that The obtaining of a target correction parameter according to the road curve radius and the motion state of the vehicle includes: Determining a first correction factor according to the roll angle and a first mapping relationship, wherein the first mapping relationship includes a correspondence between the roll angle and the first correction factor, and different roll angles correspond to different first correction factors; Determine a second correction factor according to the centering error and a second mapping relationship, wherein the second mapping relationship includes a correspondence between the centering error and the second correction factor, and different centering errors correspond to different second correction factors; determining a third correction factor according to the steering wheel hand torque and a third mapping relationship, wherein the third mapping relationship includes a correspondence between the steering wheel hand torque and the third correction factor, and different steering wheel hand torques correspond to different third correction factors; Determining a fourth correction factor according to the chassis component change amount and a fourth mapping relationship, wherein the fourth mapping relationship includes a correspondence between the chassis component change amount and the fourth correction factor, and different chassis component change amounts correspond to different fourth correction factors; The target correction parameter is obtained according to the road curve radius, the first correction factor, the second correction factor, the third correction factor and the fourth correction factor.

3. The method according to claim 2, characterized in that The obtaining the target correction parameter according to the road curve radius, the first correction factor, the second correction factor, the third correction factor and the fourth correction factor includes: If the road curve radius is greater than or equal to a first radius threshold, and the road curve radius is less than a second radius threshold, obtaining a first relationship between the centering error and the first error and the second error, wherein the first error is less than the second error; The target correction parameter is obtained according to the first relationship, the first correction factor, the second correction factor, the third correction factor, and the fourth correction factor.

4. The method according to claim 3, characterized in that The obtaining the target correction parameter according to the first relationship, the first correction factor, the second correction factor, the third correction factor and the fourth correction factor comprises: If the centering error is greater than or equal to the first error and less than or equal to the second error, obtaining the target correction parameter according to the first correction factor and the second correction factor; or If the centering error is greater than the second error, obtaining the target correction parameter according to the first correction factor, the second correction factor, the third correction factor and the fourth correction factor; or If the centering error is less than the first error, the target correction parameter is determined to be 1.

5. The method according to claim 2, characterized in that: The obtaining the target correction parameter according to the road curve radius, the first correction factor, the second correction factor, the third correction factor and the fourth correction factor includes: If the road curve radius is greater than a third radius threshold, obtaining a second relationship between the centering error and the third error and the fourth error, wherein the third error is smaller than the fourth error; The target correction parameter is obtained according to the second relationship, the first correction factor, the second correction factor, the third correction factor, and the fourth correction factor.

6. The method according to claim 5, characterized in that The obtaining the target correction parameter according to the second relationship, the first correction factor, the second correction factor, the third correction factor and the fourth correction factor comprises: If the centering error is greater than or equal to the third error and less than or equal to the fourth error, obtaining the target correction parameter according to the first correction factor and the second correction factor; or If the centering error is greater than the fourth error, obtaining the target correction parameter according to the first correction factor, the second correction factor, the third correction factor and the fourth correction factor; or If the centering error is less than the third error, the target correction parameter is determined to be 1.

7. The method according to claim 4 or 6, characterized in that: The obtaining the target correction parameter according to the first correction factor, the second correction factor, the third correction factor and the fourth correction factor comprises: Determine the product of the first correction factor and the first weight as a first correction parameter; Determine a product of the second correction factor and a second weight as a second correction parameter, wherein the second weight is less than the first weight; Determine a third correction parameter by multiplying the third correction factor by a third weight, wherein the third weight is less than the first weight; Determine a product of the fourth correction factor and a fourth weight as a fourth correction parameter, wherein the fourth weight is smaller than the first weight, smaller than the second weight, and smaller than the third weight; A sum of the first correction parameter, the second correction parameter, the third correction parameter, and the fourth correction parameter is determined as the target correction parameter.

8. The method according to claim 1, characterized in that Before obtaining the target correction parameter according to the road curve radius and the motion state of the vehicle, the method further includes: Acquiring the current position, target position and motion state of the vehicle, wherein the target position is determined according to the lane line of the road on which the vehicle is traveling; If the deviation between the current position and the target position is greater than a deviation threshold, it is determined whether the road on which the vehicle is traveling is a transverse slope according to the motion state of the vehicle and the radius of the road curve.

9. The method according to claim 7, characterized in that: The determining, based on the motion state of the vehicle and the road curve radius, whether the road on which the vehicle is traveling is a horizontal slope comprises: If the roll angle is greater than a first threshold, determining that the road on which the vehicle is traveling is a transverse slope; and / or If the centering error of the vehicle continues to be greater than a second threshold value within a first time period, determining that the road on which the vehicle is traveling is a transverse slope; and / or If the curvature corresponding to the road curve radius is greater than a third threshold, it is determined that the road on which the vehicle is traveling is a transverse slope, wherein the curvature corresponding to the road curve radius is the inverse of the road curve radius; and / or If the direction of the steering wheel hand torque is opposite to the direction of the centering error, it is determined that the road on which the vehicle is traveling is a transverse slope; and / or If the deformation amount of the chassis element is greater than a fourth threshold, it is determined that the road on which the vehicle is traveling is a transverse slope.

10. The method according to claim 9, characterized in that The chassis element deformation amount includes a left chassis element deformation amount of the vehicle and a right chassis element deformation amount of the vehicle, and if the chassis element deformation amount is greater than a fourth threshold, determining that the road on which the vehicle is traveling is a transverse slope comprises: If the difference between the deformation amount of the left chassis element and the deformation amount of the right chassis element is greater than a fifth threshold, it is determined that the road on which the vehicle is traveling is a transverse slope.

11. A vehicle control device, characterized in that: The device comprises: A road curve radius acquisition module is used to acquire the road curve radius of the road on which the vehicle is traveling; a target correction parameter acquisition module, for obtaining target correction parameters according to the road curve radius and the motion state of the vehicle, wherein the motion state of the vehicle includes the roll angle of the vehicle, the centering error of the vehicle, the steering wheel hand torque of the vehicle, and the deformation of the chassis element of the vehicle, and the target correction parameters are used to correct the control parameters of the vehicle in a cross slope scenario so that the vehicle can drive in the center of the road; a control parameter determination module, configured to determine a control parameter of the vehicle based on the target correction parameter; A vehicle control module is used to control the driving of the vehicle based on the control parameters.

12. A vehicle, characterized in that: include: one or more processors; Memory; One or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs are configured to execute the method according to any one of claims 1-10.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program codes, which can be called by a processor to execute the method according to any one of claims 1 to 10.

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