Vehicle zero offset updating method, device and equipment and storage medium

Abstract

The invention discloses a vehicle zero offset updating method and device, equipment and a storage medium. Comprising the steps of obtaining vehicle error data when an automatic driving vehicle meets a specified driving condition; determining a vehicle driving condition according to the vehicle error data; when the vehicle driving condition is stable linear driving, vehicle zero offset updating results are determined according to the vehicle error data, and the vehicle zero offset updating results comprise a course angle zero offset updating result and a steering wheel zero offset updating result. The vehicle driving condition is determined through the vehicle error data, the vehicle zero offset updating result is further determined through the vehicle error data when the vehicle is stably driven, the vehicle error data comprises a transverse error, a steering wheel turning angle error and a course angle error, and the vehicle zero offset updating result is further determined according to different steering wheels and course angles when different vehicles leave factories. According to the method, automatic deviation correction can be carried out in the vehicle running process according to the vehicle condition of each vehicle, the deviation correction effect is automatically verified, compensation is automatically carried out, and it is guaranteed that the automatic driving function of the vehicle is not damaged due to zero deviation increase of a steering wheel or a course angle.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent vehicle driving, and particularly to a vehicle zero-offset update method, device, equipment and storage medium. Background Art

[0002] An intelligent driving vehicle automatically drives according to instructions issued by an automatic driving system. The zero-offset of important actuators or sensors directly affects the safe driving of the vehicle. Due to the error of factory calibration and the deviation caused by long-term mechanical wear of the vehicle, there may be a zero-offset in the steering wheel angle or the heading angle. For example, in a sanitation cleaning vehicle, a zero-offset in the steering wheel or the heading angle will cause the vehicle to deviate to one side, being too close to the roadside edge and hitting the roadside or being too far from the roadside edge and unable to clean the roadside edge. For example, in a vehicle driving at high speed, a zero-offset in the steering wheel or the heading angle will cause the vehicle to deviate to one side, possibly being too close to the adjacent lane or invading other lanes, affecting the safe driving of the vehicle.

[0003] The existing calculation methods for the zero-offset of the steering wheel are too complex, with insufficient practical operability, stability and reliability. And in the existing technology, it is impossible to achieve simultaneous correction when there is an interaction between the heading angle and the steering wheel angle. Summary of the Invention

[0004] The present invention provides a vehicle zero-offset update method, device, equipment and storage medium, which can automatically correct the deviation during the vehicle driving process according to the vehicle condition, automatically verify the correction effect, and can automatically compensate as the zero-offset of the steering wheel or the heading angle changes during the vehicle operation, ensuring that the automatic driving function of the vehicle is not damaged due to the increase of the zero-offset of the steering wheel or the heading angle.

[0005] According to one aspect of the present invention, a vehicle zero-offset update method is provided, and the method includes:

[0006] When an autonomous driving vehicle meets the specified driving conditions, obtain vehicle error data, where the vehicle error data includes lateral error, steering wheel angle error and heading angle error;

[0007] Determine the vehicle driving situation according to the vehicle error data;

[0008] When the vehicle driving situation is stable straight driving, determine the vehicle zero-offset update result according to the vehicle error data, where the vehicle zero-offset update result includes a heading angle zero-offset update result and a steering wheel zero-offset update result.

[0009] Optionally, the method further includes: obtaining the vehicle speed and the lane line curvature corresponding to the vehicle driving road; when the lane line curvature is less than a preset curvature threshold and the vehicle speed is within a specified speed range, determine that the vehicle meets the specified driving conditions.

[0010] Optionally, obtain vehicle error data, including: obtaining error statistical data of the vehicle according to a preset period, where the error statistical data includes each lateral error acquisition value, each steering wheel angle error acquisition value, and each heading angle error acquisition value; determining the driving time of the vehicle under specified driving conditions and the data volume corresponding to the error statistical data; when the driving time is greater than the preset driving time and the data volume is greater than the preset data volume, taking the average value of each lateral error acquisition value as the lateral error, taking the average value of each steering wheel angle error acquisition value as the steering wheel angle error, and taking the average value of each heading angle error acquisition value as the heading angle error.

[0011] Optionally, determine the vehicle driving condition according to the vehicle error data, including: determining the variance of the lateral error corresponding to the lateral error; determining whether the variance of the lateral error is less than a preset variance threshold, and if so, determining that the vehicle driving condition is stable straight driving; otherwise, determining that the vehicle driving condition is non-stable straight driving.

[0012] Optionally, determine the vehicle zero bias update result according to the vehicle error data, including: determining whether the heading angle error is greater than a preset heading angle error threshold, and if so, taking the heading angle error as the heading angle zero bias update result and determining the steering wheel zero bias update result according to the steering wheel error; otherwise, determining that the vehicle zero bias update result is not updated.

[0013] Optionally, determine the steering wheel zero bias update result according to the steering wheel error, including: determining whether the steering wheel error is greater than the steering wheel error threshold, and if so, taking the steering wheel error as the steering wheel zero bias update result; otherwise, determining that the vehicle zero bias update result is not updated.

[0014] Optionally, after determining the vehicle zero bias update result according to the vehicle error data, the method further includes: obtaining the updated heading angle error and the updated lateral error based on the steering wheel zero bias update result and the heading angle zero bias update result; when both the updated heading angle error and the updated lateral error are less than the matched preset update thresholds, writing the steering wheel zero bias update result and the heading angle zero bias update result to a specified address.

[0015] According to another aspect of the present invention, there is provided a vehicle zero bias update device, which includes:

[0016] A vehicle error data acquisition module, configured to obtain vehicle error data when an autonomous vehicle meets specified driving conditions, where the vehicle error data includes a lateral error, a steering wheel angle error, and a heading angle error;

[0017] A vehicle driving condition determination module, configured to determine the vehicle driving condition according to the vehicle error data;

[0018] A vehicle zero-offset update result determination module is configured to determine a vehicle zero-offset update result according to vehicle error data when the vehicle driving condition is stable straight driving, where the vehicle zero-offset update result includes a heading angle zero-offset update result and a steering wheel zero-offset update result.

[0019] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0020] At least one processor; and

[0021] A memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a vehicle zero-offset update method according to any embodiment of the present invention.

[0023] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement a vehicle zero-offset update method according to any embodiment of the present invention when executed.

[0024] The technical solution of the embodiment of the present invention determines the vehicle driving condition through vehicle error data, and further determines the vehicle zero-offset update result through vehicle error data when the vehicle driving is stable. The vehicle error data includes lateral error, steering wheel angle error and heading angle error. For different steering wheels and heading angles of different vehicles when leaving the factory, it can automatically correct the deviation during vehicle driving according to the vehicle condition of each vehicle, automatically verify the deviation correction effect, and automatically perform compensation to ensure that the vehicle's automatic driving function is not damaged due to the increase of the zero-offset of the steering wheel or heading angle.

[0025] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0027] Figure 1 is a flowchart of a vehicle zero-offset update method provided according to Embodiment 1 of the present invention;

[0028] Figure 2 It is a flowchart of another vehicle zero-offset update method provided by Embodiment 1 of the present invention;

[0029] Figure 3 It is a flowchart of another vehicle zero-offset update method provided by Embodiment 2 of the present invention;

[0030] Figure 4 It is a schematic structural diagram of a vehicle zero-offset update device provided by Embodiment 3 of the present invention;

[0031] Figure 5 It is a schematic structural diagram of an electronic device for implementing the vehicle zero-offset update method of the embodiments of the present invention. Detailed implementation manners

[0032] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0033] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0034] Embodiment 1

[0035] Figure 1 A flowchart of a vehicle zero-offset update method is provided for Embodiment 1 of the present invention. This embodiment is applicable to the situation of correcting the heading angle and steering wheel of a vehicle. This method can be executed by a vehicle zero-offset update device, which can be implemented in the form of hardware and / or software, and the vehicle zero-offset update device can be configured in a vehicle controller. As Figure 1 shown, the method includes:

[0036] S110. When the autonomous vehicle meets the specified driving conditions, obtain the vehicle error data, where the vehicle error data includes lateral error, steering wheel angle error, and heading angle error.

[0037] Among them, the driving conditions refer to the environment and state of the vehicle during driving, including factors such as road conditions, weather conditions, traffic flow, and driver state. The specified driving conditions in this embodiment specifically refer to that the vehicle speed and lane line curvature meet the set conditions. In addition, in this solution, after the vehicle enters the autonomous driving mode, the controller will run the software to perform data statistics, and then achieve automatic correction. The technical solution of the embodiment of the present invention is to obtain the vehicle error data and determine the driving situation of the vehicle and the zero-offset update result based on these data. When the autonomous vehicle meets the specified driving conditions, the method will obtain the vehicle error data, including lateral error, steering wheel angle error, and heading angle error. Then, based on these error data, determine the driving situation of the vehicle, such as whether it is stable straight driving. When the driving situation of the vehicle is stable straight driving, the method will determine the vehicle zero-offset update result based on the vehicle error data, including the heading angle zero-offset update result and the steering wheel zero-offset update result. These zero-offset update results can help the vehicle control system better understand the attitude and motion state of the vehicle, thereby improving the control accuracy and stability of the vehicle.

[0038] Further, the lateral error refers to the deviation between the actual driving direction and the expected driving direction of the vehicle during driving. The lateral error can be expressed in terms of angle or distance, usually in terms of angle. In the vehicle control system, the lateral error is usually measured by sensors, such as inertial navigation systems, lidar, cameras, etc. The lateral error can be used for the lateral control of the vehicle, such as steering control, lane keeping, etc. The steering wheel angle error refers to the deviation between the actual steering wheel angle of the vehicle and the expected steering wheel angle. The steering wheel angle error can be expressed in terms of angle or radian, usually in terms of angle. The heading angle error refers to the deviation between the actual heading angle of the vehicle and the expected heading angle. The heading angle error can be expressed in terms of angle or radian, usually in terms of angle. The heading angle error is usually measured by sensors, such as inertial navigation systems, global positioning systems (GPS), etc. The vehicle error data is an important indicator of the driving stability and control accuracy of the vehicle. The smaller the vehicle error, the more stable the vehicle driving and the higher the control accuracy.

[0039] Optionally, the method further includes: obtaining the vehicle speed and the lane line curvature corresponding to the vehicle driving road; when the lane line curvature is less than the preset curvature threshold and the vehicle speed is within the specified speed range, determine that the vehicle meets the specified driving conditions.

[0040] Among them, the lane line curvature refers to the degree of bending of the lane line on the road, usually expressed by the radius of curvature. The radius of curvature refers to the bending radius of the lane line on the road, that is, the distance from the center of curvature of the lane line on the road to the lane line. The smaller the radius of curvature, the greater the degree of bending of the lane line, and a larger steering angle and a smaller speed are required for the vehicle to maintain stability when driving. When the lane line curvature is less than the preset curvature threshold and the vehicle speed is within the specified speed range, it can be determined that the vehicle meets the specified driving conditions, and at this time, the statistical error mode can be entered.

[0041] Optionally, obtain vehicle error data, including: obtaining the error statistical data of the vehicle according to a preset period, where the error statistical data includes each lateral error acquisition value, each steering wheel angle error acquisition value, and each heading angle error acquisition value; determining the driving time of the vehicle under the specified driving conditions and the data volume corresponding to the error statistical data; when the driving time is greater than the preset driving time and the data volume is greater than the preset data volume, taking the average value of each lateral error acquisition value as the lateral error, taking the average value of each steering wheel angle error acquisition value as the steering wheel angle error, and taking the average value of each heading angle error acquisition value as the heading angle error.

[0042] Specifically, in the statistical error mode, each lateral error acquisition value, each steering wheel angle error acquisition value, and each heading angle error acquisition value can be obtained through a preset period, and the driving time of the vehicle under the specified driving conditions and the data volume corresponding to the error statistical data are determined. Determining the data volume is to ensure that the statistical sample size is greater than the minimum required sample size. When the driving time is greater than the preset driving time and the data volume is greater than the preset data volume, taking the average value of each lateral error acquisition value as the lateral error, taking the average value of each steering wheel angle error acquisition value as the steering wheel angle error, and taking the average value of each heading angle error acquisition value as the heading angle error. These error data can be used for the lateral control of the vehicle, such as steering control, lane keeping, etc., so as to improve the stability and control accuracy of vehicle driving. It should be noted that the user can set parameters such as the preset period, preset driving time, and preset data volume according to the actual situation to ensure the accuracy and reliability of the system. At the same time, the sensor needs to be calibrated and maintained regularly to ensure the accuracy and stability of the sensor.

[0043] S120. Determine the driving situation of the vehicle according to the vehicle error data.

[0044] It should be noted that different lateral control software algorithms are used in the Advanced Driving Assistance System (ADAS) controller, but the steering wheel angle command value obtained by relying on the feedback of the lateral error and the heading angle error can be simplified into the following formula (1) for representation:

[0045]

[0046] Among them, represents the steering wheel angle command, x represents the lateral error, and θ represents the heading angle error. It is assumed that the directions defined by the three are the same. When it is positive, the steering wheel turns to the left. When x is positive, the vehicle's center of mass position is to the left. When θ is positive, the vehicle's heading angle is to the left. a and b represent calibration values determined according to vehicle information such as vehicle speed and vehicle load. At a fixed vehicle speed and a fixed vehicle mass, a and b are constants.

[0047] Among them, a must be a negative value, that is, when the heading angle error remains unchanged, the more the vehicle's center of mass position is to the left, the more the feedback steering angle command turns to the right. b must be a negative value, that is, when the lateral error remains unchanged, the more the vehicle's heading angle is to the left, the more the feedback steering angle command turns to the right. That is, the negative feedback mechanism of the heading angle deviation and the lateral error on the steering wheel angle command.

[0048] Furthermore, according to vehicle kinematics, the relationship between the lateral error and the heading angle error is obtained: The reference points for the vehicle's lateral error and the heading angle error are at the vehicle's center of mass. Assume the lateral error: x unit: m; the heading angle error (true value): θ, unit: rad; the vehicle speed: v, unit: m / s; the time: t, unit: s; dx / dt = v * sinθ. When θ is relatively small, sinθ ≈ θ. Therefore: dx / dt = v * θ. When the steering wheel has a zero offset, that is, when a 0 command is sent, the front wheel angle of the vehicle is not correct and is either to the left or to the right. Assume the vehicle is driving at a constant speed on a straight road, and there is a steady-state error c in the angle sensor and a zero offset f of the steering wheel. According to the geometric relationship between the steering wheel angle and the vehicle yaw rate, the following formula (2) is obtained:

[0049]

[0050] Among them, ω r represents the vehicle yaw angular velocity, represents the steering wheel angle command, e represents the proportional relationship between the front wheel angle and the steering wheel angle, K represents the stability factor, L represents the wheelbase of the vehicle's front and rear wheels, v represents the vehicle's longitudinal speed, d = 180 / π is the unit conversion from rad to °C, and the above formula is converted into the following formula (3):

[0051]

[0052] Among them, ω r represents the vehicle yaw angular velocity, represents the steering wheel angle command, e represents the proportional relationship between the front wheel angle and the steering wheel angle, K represents the stability factor, L represents the wheelbase of the vehicle's front and rear wheels, v represents the vehicle's longitudinal speed, d = 180 / π is the unit conversion from rad to °C. According to It can be written as Substituting dx / dt = x' = v*θ into the above equation gives (4):

[0053]

[0054] where x is the lateral error, x' is the first derivative of the lateral error, x'' is the second derivative of the lateral error, e represents the proportional relationship between the front wheel angle and the steering wheel angle, K represents the stability factor, L represents the wheelbase of the vehicle's front and rear wheels, v represents the vehicle's longitudinal speed, a and b are calibration quantities, c represents the steady-state error, and f represents the steering wheel zero offset. Let m3 = -a, m4 = f - bc, then it can be simplified to (5):

[0055] m1*x'' + m2*x + m3*x = m4 (5)

[0056] where x is the lateral error, x' is the first derivative of the lateral error, x'' is the second derivative of the lateral error. According to the positive and negative signs of each parameter, it can be obtained that: m1 is a positive number, m2 is a positive number, m3 is a positive number. This is a second-order ordinary differential equation. Solving the ordinary differential equation:

[0057]

[0058] where c1 and c2 represent the steady-state error, t represents time, e represents the proportional relationship between the front wheel angle and the steering wheel angle, x is the lateral error, and the exponential terms are all negative. Therefore, when the time t increases, the lateral error approaches That is Taking the derivative of (6) gives the following formula (7):

[0059]

[0060] where x' is the first derivative of the lateral error, c1 and c2 represent the steady-state error, t represents time, e represents the proportional relationship between the front wheel angle and the steering wheel angle, and f represents the steering wheel zero offset. The exponential terms in formula (7) are all negative. Therefore, when the time t increases, x' approaches 0, that is, the heading angle error approaches 0 when the time t increases.

[0061] Furthermore, based on the above derivation, when driving at a constant speed on a straight road in the autopilot mode:

[0062] 1) When there is a steady-state measurement deviation of the heading angle but no steering wheel angle deviation, the true value of the steady-state error of the heading angle is 0, the measured value of the heading angle error is not 0, and the lateral steady-state error is not 0. At this time, the mean value of the measured values of the heading angle error statistically obtained is the steady-state measurement deviation of the heading angle.

[0063] 2) When there is no steady-state measurement deviation of the heading angle but there is a steering wheel angle deviation, the true value and the measured value of the steady-state error of the heading angle are 0, and the lateral steady-state error is not 0. At this time, the average value of the steering wheel angle statistically obtained is the zero bias of the steering wheel angle.

[0064] 3) When there is a steady-state measurement deviation of the heading angle and there is a steering wheel angle deviation, the true value of the steady-state error of the heading angle is 0, the measured value of the heading angle error is not 0, and whether the lateral steady-state error is 0 depends on whether f-bc is 0. At this time, the average value of the steering wheel angle statistically obtained is the zero bias of the steering wheel angle.

[0065] Optionally, determining the vehicle driving condition according to the vehicle error data includes: determining the variance of the lateral error corresponding to the lateral error; judging whether the variance of the lateral error is less than a preset variance threshold. If so, determining that the vehicle driving condition is stable straight driving; otherwise, determining that the vehicle driving condition is non-stable straight driving.

[0066] Specifically, when the variance of the vehicle lateral error is less than the preset variance threshold, it indicates that the vehicle is driving stably. If the variance is less than the preset variance threshold, it means that the lateral error during the vehicle driving process is small, and the vehicle driving condition is stable straight driving. If the variance is greater than or equal to the preset variance threshold, it means that the lateral error during the vehicle driving process is large, and the vehicle driving condition is non-stable straight driving.

[0067] S130. When the vehicle driving condition is stable straight driving, determining the vehicle zero bias update result according to the vehicle error data, where the vehicle zero bias update result includes the heading angle zero bias update result and the steering wheel zero bias update result.

[0068] Figure 2 The flowchart of a vehicle zero bias update method provided in Embodiment 1 of the present invention, step S130 mainly includes the following steps S131 to S135:

[0069] S131. When the vehicle driving condition is stable straight driving, judging whether the heading angle error is greater than a preset heading angle error threshold. If so, execute S132 - S133; otherwise, execute S135.

[0070] S132. Taking the heading angle error as the heading angle zero bias update result.

[0071] Specifically, the preset heading angle error threshold is preset according to factors such as the type of vehicle and the driving environment, usually 1 degree or 2 degrees. If the heading angle error is greater than the preset heading angle error threshold, it indicates that there is a large error in the vehicle's heading angle and needs to be updated. The heading angle error is used as the heading angle zero bias update result, that is, the vehicle's heading angle zero bias is updated to improve the vehicle's positioning accuracy. If the heading angle error is not greater than the preset heading angle error threshold, it is determined that the vehicle zero bias update result is not to update, that is, if the heading angle error is not greater than the preset heading angle error threshold, it indicates that the vehicle's heading angle error is small and does not need to be updated.

[0072] S133. Determine whether the steering wheel error is greater than the steering wheel error threshold. If so, execute S134; otherwise, execute S135.

[0073] S134. Use the steering wheel error as the steering wheel zero bias update result.

[0074] S135. Determine that the vehicle zero bias update result is not to update.

[0075] Specifically, if the steering wheel error is greater than the steering wheel error threshold, use the steering wheel error as the steering wheel zero bias update result. If the steering wheel error is not greater than the steering wheel error threshold, determine that the vehicle zero bias update result is not to update.

[0076] The technical solution of the embodiment of the present invention determines the vehicle driving situation through vehicle error data, and further determines the vehicle zero bias update result through vehicle error data when the vehicle is driving stably. The vehicle error data includes lateral error, steering wheel angle error, and heading angle error. For different steering wheels and heading angles of different vehicles when leaving the factory, it can automatically correct the deviation during the vehicle driving process according to the vehicle condition of each vehicle, automatically verify the correction effect, and automatically perform compensation to ensure that the vehicle's autonomous driving function is not damaged due to the increase of the zero bias of the steering wheel or heading angle.

[0077] Embodiment 2

[0078] Figure 3 It is a flowchart of a vehicle zero bias update method provided by Embodiment 2 of the present invention. This embodiment adds a process of verifying vehicle zero bias update on the basis of Embodiment 1 above. As Figure 3 shown, the method includes:

[0079] S210. When the autonomous vehicle meets the specified driving conditions, obtain vehicle error data, where the vehicle error data includes lateral error, steering wheel angle error, and heading angle error.

[0080] Optionally, the method further includes: obtaining the vehicle speed and the lane curvature of the road on which the vehicle is driving; when the lane curvature is less than a preset curvature threshold and the vehicle speed is within a specified speed range, determining that the vehicle meets the specified driving conditions.

[0081] Optionally, obtaining vehicle error data includes: obtaining the error statistical data of the vehicle according to a preset period, where the error statistical data includes each lateral error acquisition value, each steering wheel angle error acquisition value, and each heading angle error acquisition value; determining the driving time of the vehicle under the specified driving conditions and the data volume corresponding to the error statistical data; when the driving time is greater than a preset driving time and the data volume is greater than a preset data volume, taking the average value of each lateral error acquisition value as the lateral error, taking the average value of each steering wheel angle error acquisition value as the steering wheel angle error, and taking the average value of each heading angle error acquisition value as the heading angle error.

[0082] S220. Determine the driving situation of the vehicle according to the vehicle error data.

[0083] Optionally, determining the driving situation of the vehicle according to the vehicle error data includes: determining the variance of the lateral error corresponding to the lateral error; determining whether the variance of the lateral error is less than a preset variance threshold, and if so, determining that the driving situation of the vehicle is stable straight driving; otherwise, determining that the driving situation of the vehicle is non-stable straight driving.

[0084] S230. When the driving situation of the vehicle is stable straight driving, determine the vehicle zero bias update result according to the vehicle error data, where the vehicle zero bias update result includes the heading angle zero bias update result and the steering wheel zero bias update result.

[0085] Optionally, determining the vehicle zero bias update result according to the vehicle error data includes: determining whether the heading angle error is greater than a preset heading angle error threshold, and if so, taking the heading angle error as the heading angle zero bias update result and determining the steering wheel zero bias update result according to the steering wheel error; otherwise, determining that the vehicle zero bias update result is not updated.

[0086] Optionally, determining the steering wheel zero bias update result according to the steering wheel error includes: determining whether the steering wheel error is greater than the steering wheel error threshold, and if so, taking the steering wheel error as the steering wheel zero bias update result; otherwise, determining that the vehicle zero bias update result is not updated.

[0087] S240. Obtain the updated heading angle error and the updated lateral error based on the steering wheel zero bias update result and the heading angle zero bias update result.

[0088] Specifically, after adding the zero offset, continue to detect the lateral error, heading angle error, and the average value of the steering wheel commands. When the planned path is a straight line, obtain the updated heading angle error and the updated lateral error. It should be noted that the updated heading angle error and the updated lateral error obtained at this time are the average values of the errors.

[0089] S250. When both the updated heading angle error and the updated lateral error are less than the matched preset update threshold, write the steering wheel zero offset update result and the heading angle zero offset update result to the specified address.

[0090] Specifically, after continuous statistics for a certain period of time, if both the updated heading angle error and the updated lateral error are less than the matched preset update threshold, write the steering wheel zero offset update result and the heading angle zero offset update result to the specified address of the electronic control unit. The specified address can be a non-volatile memory (NVM). After each subsequent vehicle power-on, the heading angle zero offset and the steering wheel angle zero offset can be read from the NVM and applied to run in the software, providing a method that combines the online correction verification of the steering wheel zero offset with the NVM storage and memory. It can memorize and update the steering wheel zero offset according to the vehicle condition of each vehicle. It can be read each time when powered on, memorize the zero offset of the vehicle according to the vehicle condition of each vehicle, run when powered on, and continuously update. When the vehicle is off the production line, there is no need for manual calibration. When the vehicle is mass-produced and put on the market, it can always automatically correct the deviation, ensuring that the steering wheel or heading angle zero offset does not affect the autonomous driving function, improving the product competitiveness, and reducing the after-sales maintenance cost.

[0091] The technical solution of the embodiment of the present invention determines the vehicle driving situation through vehicle error data, and further determines the vehicle zero offset update result through the vehicle error data when the vehicle driving is stable. The vehicle error data includes lateral error, steering wheel angle error, and heading angle error. For different steering wheels and heading angles of different vehicles when leaving the factory, it can automatically correct the deviation during the vehicle driving process according to the vehicle condition of each vehicle, automatically verify the correction effect, and automatically perform compensation to ensure that the autonomous driving function of the vehicle is not damaged due to the increase of the zero offset of the steering wheel or the heading angle.

[0092] Embodiment III

[0093] Figure 4 is a schematic structural diagram of a vehicle zero offset update device provided by Embodiment III of the present invention. As Figure 4 shown, the device includes: a vehicle error data acquisition module 310, configured to acquire vehicle error data when the autonomous vehicle meets the specified driving conditions, where the vehicle error data includes lateral error, steering wheel angle error, and heading angle error;

[0094] a vehicle driving situation determination module 320, configured to determine the vehicle driving situation according to the vehicle error data;

[0095] The vehicle zero-offset update result determination module 330 is configured to determine the vehicle zero-offset update result according to the vehicle error data when the vehicle driving condition is stable straight driving, where the vehicle zero-offset update result includes the heading angle zero-offset update result and the steering wheel zero-offset update result.

[0096] Optionally, the device further includes: a driving condition verification module, configured to: obtain the vehicle speed and the lane line curvature corresponding to the vehicle driving road; when the lane line curvature is less than a preset curvature threshold and the vehicle speed is within a specified speed range, determine that the vehicle meets the specified driving condition.

[0097] Optionally, the vehicle error data acquisition module 310 specifically includes: a vehicle error data acquisition unit, configured to: obtain the error statistical data of the vehicle according to a preset period, where the error statistical data includes each lateral error acquisition value, each steering wheel angle error acquisition value, and each heading angle error acquisition value; determine the driving time of the vehicle under the specified driving condition and the data volume corresponding to the error statistical data; when the driving time is greater than a preset driving time and the data volume is greater than a preset data volume, use the average value of each lateral error acquisition value as the lateral error, use the average value of each steering wheel angle error acquisition value as the steering wheel angle error, and use the average value of each heading angle error acquisition value as the heading angle error.

[0098] Optionally, the vehicle driving condition determination module 320 is specifically configured to: determine the lateral error variance corresponding to the lateral error; determine whether the lateral error variance is less than a preset variance threshold, and if so, determine that the vehicle driving condition is stable straight driving; otherwise, determine that the vehicle driving condition is non-stable straight driving.

[0099] Optionally, the vehicle zero-offset update result determination module 330 is specifically configured to: determine whether the heading angle error is greater than a preset heading angle error threshold, and if so, use the heading angle error as the heading angle zero-offset update result and determine the steering wheel zero-offset update result according to the steering wheel error; otherwise, determine that the vehicle zero-offset update result is not updated.

[0100] Optionally, the vehicle zero-offset update result determination module 330 specifically includes: a steering wheel zero-offset update result determination unit, configured to: determine whether the steering wheel error is greater than the steering wheel error threshold, and if so, use the steering wheel error as the steering wheel zero-offset update result; otherwise, determine that the vehicle zero-offset update result is not updated.

[0101] Optionally, the device further includes: a zero-offset update result verification module, configured to: after determining the vehicle zero-offset update result according to the vehicle error data, obtain an updated heading angle error and an updated lateral error based on the steering wheel zero-offset update result and the heading angle zero-offset update result; when both the updated heading angle error and the updated lateral error are less than the matched preset update threshold, write the steering wheel zero-offset update result and the heading angle zero-offset update result to the specified address.

[0102] The technical solution of the embodiment of the present invention determines the vehicle driving condition through vehicle error data, and further determines the vehicle zero-offset update result through the vehicle error data when the vehicle is driving stably. The vehicle error data includes lateral error, steering wheel angle error, and heading angle error. For different steering wheels and heading angles of different vehicles when leaving the factory, it can automatically correct the deviation during vehicle driving according to the vehicle condition of each vehicle, automatically verify the deviation correction effect, and automatically perform compensation to ensure that the vehicle's autonomous driving function is not damaged due to the increase of the zero-offset of the steering wheel or the heading angle.

[0103] A vehicle zero-offset update device provided by an embodiment of the present invention can execute a vehicle zero-offset update method provided by any embodiment of the present invention, and has function modules and beneficial effects corresponding to the execution of the method.

[0104] Embodiment 4

[0105] Figure 5 FIG. shows a schematic structural diagram of an electronic device 10 that can be used to implement an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as, for example, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, for example, a personal digital processor, a cellular phone, a smart phone, a wearable device (such as a helmet, glasses, a watch, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0106] As Figure 5As shown, the electronic device 10 includes at least one processor 11 and a memory communicatively connected to the at least one processor 11, such as read-only memory (ROM) 12, random access memory (RAM) 13, etc. Among them, the memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, ROM 12, and RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0107] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0108] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a vehicle zero-offset update method. That is: when the autonomous vehicle meets the specified driving conditions, vehicle error data is acquired, where the vehicle error data includes lateral error, steering wheel angle error, and heading angle error; the vehicle driving situation is determined according to the vehicle error data; when the vehicle driving situation is stable straight driving, the vehicle zero-offset update result is determined according to the vehicle error data, where the vehicle zero-offset update result includes the heading angle zero-offset update result and the steering wheel zero-offset update result.

[0109] In some embodiments, a vehicle zero-bias update method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the vehicle zero-bias update method described above may be executed. Alternatively, in other embodiments, the processor 11 may be configured to execute a vehicle zero-bias update method by any other suitable means (e.g., by means of firmware).

[0110] Various embodiments of the systems and techniques described above in this document may be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on a chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs executable and / or interpretable on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor, receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0111] The computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs may be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine, or entirely on the remote machine or server.

[0112] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0113] In order to provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0114] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0115] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The client-server relationship is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0116] It should be understood that various forms of processes shown above can be used, with steps reordered, added or deleted. For example, the steps described in the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is imposed herein.

[0117] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A vehicle zero-offset update method, characterized in that, Including: When the autonomous vehicle meets the specified driving conditions, obtaining vehicle error data, where the vehicle error data includes lateral error, steering wheel angle error, and heading angle error; Determining the vehicle driving situation according to the vehicle error data; When the vehicle driving situation is stable straight driving, determining a vehicle zero bias update result according to the vehicle error data, where the vehicle zero bias update result includes a heading angle zero bias update result and a steering wheel zero bias update result.

2. The method according to claim 1, characterized in that, The method further includes: Obtaining the vehicle speed and the lane line curvature corresponding to the vehicle driving road; When the lane line curvature is less than a preset curvature threshold and the vehicle speed is within a specified speed range, determining that the vehicle meets the specified driving conditions.

3. The method according to claim 1, characterized in that, The obtaining of the vehicle error data includes: Obtaining vehicle error statistical data according to a preset period, where the error statistical data includes each lateral error acquisition value, each steering wheel angle error acquisition value, and each heading angle error acquisition value; Determining the driving time of the vehicle under the specified driving conditions and the data volume corresponding to the error statistical data; When the driving time is greater than a preset driving time and the data volume is greater than a preset data volume, taking the average value of each lateral error acquisition value as the lateral error, taking the average value of each steering wheel angle error acquisition value as the steering wheel angle error, and taking the average value of each heading angle error acquisition value as the heading angle error.

4. The method according to claim 1, characterized in that, The determining of the vehicle driving situation according to the vehicle error data includes: Determining the lateral error variance corresponding to the lateral error; Judging whether the lateral error variance is less than a preset variance threshold, if so, determining that the vehicle driving situation is stable straight driving; Otherwise, determining that the vehicle driving situation is non-stable straight driving.

5. The method according to claim 1, characterized in that, The determining of the vehicle zero bias update result according to the vehicle error data includes: Judging whether the heading angle error is greater than a preset heading angle error threshold, if so, taking the heading angle error as the heading angle zero bias update result, and determining the steering wheel zero bias update result according to the steering wheel error; Otherwise, determining that the vehicle zero bias update result is not to be updated.

6. The method according to claim 5, characterized in that, The determining of the steering wheel zero bias update result according to the steering wheel error includes: Judging whether the steering wheel error is greater than the steering wheel error threshold, if so, taking the steering wheel error as the steering wheel zero bias update result; Otherwise, determining that the vehicle zero bias update result is not to be updated.

7. The method according to claim 6, characterized in that, After determining the vehicle zero bias update result according to the vehicle error data, the method further includes: Obtaining an updated heading angle error and an updated lateral error based on the steering wheel zero bias update result and the heading angle zero bias update result; When both the updated heading angle error and the updated lateral error are less than the matching preset update thresholds, writing the steering wheel zero bias update result and the heading angle zero bias update result to a specified address.

8. A vehicle zero-offset update device, characterized in that, Including: A vehicle error data acquisition module, configured to obtain vehicle error data when the autonomous vehicle meets the specified driving conditions, where the vehicle error data includes lateral error, steering wheel angle error, and heading angle error; A vehicle driving condition determination module, configured to determine a vehicle driving condition according to the vehicle error data; A vehicle zero-offset update result determination module, configured to determine a vehicle zero-offset update result according to the vehicle error data when the vehicle driving condition is stable straight driving, wherein the vehicle zero-offset update result includes a heading angle zero-offset update result and a steering wheel zero-offset update result.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-7.

10. A computer storage medium, characterized in that The computer storage medium stores computer instructions for causing a processor to execute the method according to any one of claims 1-7 when executed.

Images