Zero offset calibration method and device for vehicle steering wheel, vehicle, equipment and medium

Abstract

The invention relates to a zero offset calibration method and device for a vehicle steering wheel, a vehicle, equipment and a medium, in particular to the technical field of power systems. The method includes: controlling a vehicle to run in a preset vehicle speed range along a calibration map according to an expected turning angle; lateral deviation and actual turning angles of the vehicle at different vehicle speeds in a preset vehicle speed range are collected; according to the actual rotation angle and the expected rotation angle, zero deflection angle measurement values at different vehicle speeds are calculated; based on a preset vehicle speed range, the lateral deviation and a zero-deflection angle estimated value, establishing a correlation among the vehicle speed, the lateral deviation and the zero-deflection angle, the zero-deflection angle estimated value being calculated based on the lateral deviation and the route length of the calibration map; determining a target zero deflection angle estimated value corresponding to the actual vehicle speed and the actual transverse deviation of the vehicle according to the correlation; and filtering and fusing the target zero-deflection angle estimated value and the zero-deflection angle measured value to obtain a zero-deflection angle calibration value, so that the zero-deflection angle calibration value is automatically compensated to the issuing turning angle to control the steering of wheels.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving in mines, and in particular to a method, device, vehicle, equipment and medium for zero bias calibration of a vehicle steering wheel. Background Art

[0002] Mining scenes are complex and roads are unstructured, which poses a great challenge to the implementation of autonomous driving in mines. In addition, the installation of actuators for mining transport trucks lacks standardization. There are differences in zero offset after the steering wheel is installed, and most of them use direct control of the front wheel steering. The actuator problem is more serious than that of passenger cars. During autonomous driving, a slight zero offset of the steering wheel may cause the vehicle to deviate from the reference line, increasing driving risks.

[0003] At present, the control methods for adaptive calibration of zero bias angle are mostly based on vehicle models under simple road scenes, and are mainly used for zero bias calibration of steering wheels of passenger cars and small mining vehicles. There is little research on zero bias calibration of front wheel steering of large-tonnage mining trucks. At the same time, due to the lack of straight-line driving sections in mining scenes and the influence of poor signals on positioning, conventional self-calibration algorithms are difficult to apply in mines, and conventional zero bias angle calibration methods cannot adapt to mining trucks with large tonnage and complex road conditions.

[0004] Stable and accurate tracking of the planned path is a key indicator for autonomous driving in mines. However, the zero deflection angle of mining trucks is large and different for each vehicle, resulting in a fixed direction deviation in the lateral high-precision tracking control, which cannot be completely corrected by the existing lateral control algorithm. The method of manually measuring the zero deflection angle and compensating for it is not only costly, but also affected by external factors, and the results are inaccurate. Therefore, there is an urgent need for a method and system that can adaptively calibrate the zero deflection angle of mining trucks. Summary of the invention

[0005] In order to solve the above technical problems or at least partially solve the above technical problems, the present application provides a method, device, vehicle, equipment and medium for zero offset calibration of vehicle steering wheels, which can solve the problems of complex mining scenes, large differences in zero offset of steering wheels of mining trucks, difficulty in adapting existing zero offset angle calibration methods, inaccurate and costly manual measurement compensation, and inability to meet the high-precision lateral control requirements of mining trucks, thereby realizing adaptive calibration of the vehicle's zero offset angle.

[0006] In order to achieve the above purpose, the technical solutions provided by the embodiments of the present application are as follows:

[0007] In a first aspect, the present application provides a method for zero bias calibration of a vehicle steering wheel, the method comprising: controlling the vehicle to travel along a calibration map according to an expected turning angle within a preset speed range; collecting the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range; calculating the zero bias angle measurement values ​​at different speeds according to the actual turning angle and the expected turning angle; establishing a correlation between the vehicle speed, the lateral deviation and the zero bias angle based on the preset speed range, the lateral deviation and the zero bias angle estimation value, the zero bias angle estimation value being calculated based on the lateral deviation and the route length of the calibration map; determining a target zero bias angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation relationship; filtering and fusing the target zero bias angle estimation value and the zero bias angle measurement value to obtain a zero bias angle calibration value, so as to automatically compensate the zero bias angle calibration value to the issued turning angle to control the wheel steering.

[0008] As an optional implementation provided in an embodiment of the present application, a correlation between vehicle speed, lateral deviation and zero deviation angle is established based on a preset vehicle speed range, lateral deviation and zero deviation angle estimation value, including: using the lateral deviation corresponding to each vehicle speed within the preset vehicle speed range as a row index and each vehicle speed as a column index, to establish a two-dimensional calibration table between vehicle speed, lateral deviation and zero deviation angle.

[0009] As an optional implementation provided in an embodiment of the present application, a target zero deviation angle estimate corresponding to the actual vehicle speed and the actual lateral deviation is determined according to a correlation, including: obtaining the target zero deviation angle estimate corresponding to the actual vehicle speed and the actual lateral deviation from a two-dimensional calibration table.

[0010] As an optional implementation provided in an embodiment of the present application, the method further includes: if the actual vehicle speed and / or the actual lateral deviation does not exist in the two-dimensional calibration table, estimating the target zero deviation angle estimate by linear interpolation.

[0011] As an optional implementation provided in an embodiment of the present application, the method also includes: determining whether the zero deflection angle calibration value is greater than or equal to a first threshold and less than or equal to a second threshold; if the zero deflection angle calibration value is less than the first threshold, using the first threshold as the new zero deflection angle calibration value; if the zero deflection angle calibration value is greater than the second threshold, using the second threshold as the new zero deflection angle calibration value.

[0012] As an optional implementation manner provided in an embodiment of the present application, the lateral deviation and actual turning angle of the vehicle at different speeds within a preset speed range are collected, including: collecting multiple lateral deviations and multiple actual turning angles of the vehicle at each speed within the preset speed range; taking the average value of the multiple lateral deviations as the lateral deviation corresponding to each speed, and taking the average value of the multiple actual turning angles as the actual turning angle corresponding to each speed.

[0013] In a second aspect, the present application provides a zero bias calibration device for a vehicle steering wheel, the device comprising:

[0014] A control module, used to control the vehicle to travel according to a desired turning angle along a calibrated map within a preset speed range;

[0015] An information collection module is used to collect the lateral deviation and actual turning angle of the vehicle at different speeds within a preset speed range;

[0016] The data processing module is used to calculate the zero deviation angle measurement value under different vehicle speeds according to the actual turning angle and the expected turning angle; establish the correlation between the vehicle speed, lateral deviation and zero deviation angle based on the preset vehicle speed range, lateral deviation and zero deviation angle estimation value, and the zero deviation angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; determine the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation relationship; filter and fuse the target zero deviation angle estimation value and the zero deviation angle measurement value to obtain the zero deviation angle calibration value, so as to automatically compensate the zero deviation angle calibration value to the issued turning angle to control the wheel steering.

[0017] In a third aspect, the present application provides an electronic device comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the method for zero bias calibration of a vehicle steering wheel as described in the first aspect or any one of its optional embodiments is implemented.

[0018] In a fourth aspect, the present application provides an autonomous driving vehicle for use in a mining scenario, comprising:

[0019] A travel mechanism, configured to drive the vehicle on a mine road;

[0020] A steering actuator configured to control the steering of the wheels;

[0021] The data collection device is configured to collect the lateral deviation and actual turning angle of the vehicle at different vehicle speeds within a preset vehicle speed range;

[0022] The control unit is configured to: control the vehicle to travel along the calibration map according to the expected turning angle within a preset speed range; calculate the zero deviation angle measurement value at different vehicle speeds based on the actual turning angle and the expected turning angle; establish a correlation between the vehicle speed, the lateral deviation and the zero deviation angle based on the preset speed range, the lateral deviation and the zero deviation angle estimation value, the zero deviation angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; determine the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation according to the correlation relationship; filter and fuse the target zero deviation angle estimation value and the zero deviation angle measurement value to obtain the zero deviation angle calibration value, so as to automatically compensate the zero deviation angle calibration value to the issued turning angle and control the steering actuator.

[0023] In a fifth aspect, the present application provides a computer-readable storage medium, comprising: a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the zero bias calibration method of the vehicle steering wheel is implemented as described in the first aspect or any one of its optional embodiments.

[0024] In the sixth aspect, the present application provides a computer program product, including: the computer program product includes a computer program, when the computer program is run on a computer, the computer implements the zero bias calibration method of the vehicle steering wheel as described in the first aspect or any one of its optional embodiments.

[0025] Compared with the prior art, the technical solution provided by the embodiments of the present application has the following advantages:

[0026] The embodiment of the present application provides a method, device, vehicle, equipment and medium for zero bias calibration of a vehicle steering wheel, wherein the method first controls the vehicle to travel according to the expected turning angle along a calibration map within a preset speed range; collects the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range; calculates the zero bias angle measurement values ​​at different speeds according to the actual turning angle and the expected turning angle; based on the preset speed range, lateral deviation and zero bias angle estimation value, the zero bias angle estimation value is calculated based on the lateral deviation and the route length of the calibration map to establish a correlation between the vehicle speed, lateral deviation and zero bias angle; determines the target zero bias angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation; filters and fuses the target zero bias angle estimation value and the zero bias angle measurement value to obtain a zero bias angle calibration value, so as to automatically compensate the zero bias angle calibration value to the issued turning angle to control the wheel steering. In this way, the present application can comprehensively consider the impact of different vehicle speeds on the zero deviation angle by controlling the vehicle to travel within a preset speed range; collect lateral deviations and actual turning angles at different vehicle speeds, and the calculated zero deviation angle measurement value is more in line with the actual situation, and can accurately capture the difference in zero deviation angle at different vehicle speeds; establish a correlation between vehicle speed, lateral deviation and zero deviation angle, determine the target zero deviation angle estimate from multiple dimensions, and then filter and fuse the estimate and measurement values, which greatly improves the accuracy of zero deviation angle calibration; realizes automatic calibration of zero deviation angle, without the need for manual measurement and manual compensation one by one, which greatly reduces labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0029] Figure 1 A schematic flow chart of a method for zero bias calibration of a vehicle steering wheel provided in an embodiment of the present application;

[0030] Figure 2 A flowchart of the zero deflection calibration value processing logic is provided for the embodiment of the present application;

[0031] Figure 3 A schematic structural diagram of a zero bias calibration device for a vehicle steering wheel provided in an embodiment of the present application;

[0032] Figure 4 A schematic diagram of the structure of an electronic device described in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the technical terms required to be used in the embodiments or the description of the prior art are briefly introduced below.

[0034] In vehicle design and theory, when the steering system of a mining truck is in perfect calibration, that is, when the zero deflection angle is zero, the turning angle of the vehicle is achieved according to the designed steering geometry and control logic. For example, according to the Ackerman steering principle, when the vehicle turns, the turning angles of the inner and outer wheels will conform to a certain geometric relationship to ensure that all wheels can roll purely around a common instantaneous steering center, achieve smooth steering, and reduce tire wear and steering resistance.

[0035] If the front wheels have zero deflection, it means that the front wheels have a certain deflection angle when the driver does not actively operate the steering. When the driver operates the steering system to give a turning angle command, the actual front wheel turning angle is the superposition of the commanded turning angle and the zero deflection angle. For example, if the zero deflection angle is positive 5°, and the driver commands the front wheels to turn left 10°, the actual front wheel turning angle is 15° left. This will cause the actual steering trajectory of the vehicle to be inconsistent with expectations, which may cause the vehicle to turn early or late when turning, affecting the turning radius and path accuracy.

[0036] For mining trucks with four-wheel steering, the rear wheels also have zero deflection. The zero deflection of the rear wheels will change the degree and timing of the rear wheel's participation in the steering process. Under normal circumstances, the rear wheel steering angle is determined according to a certain control strategy based on factors such as the vehicle's driving state and the front wheel steering angle. However, if the rear wheels have zero deflection, the actual steering angle of the rear wheels is also a combination of the control command steering angle and the zero deflection angle. For example, when turning at low speed, the rear wheels should be deflected in the opposite direction of the front wheels by a certain angle to reduce the turning radius. If the rear wheels have zero deflection, the rear wheel deflection angle may be inaccurate, making the vehicle's steering posture unstable, and even causing tailswinging.

[0037] The zero bias angles of the front and rear wheels combined will cause the vehicle's steering center to shift and the turning radius to change. The vehicle may not be able to follow the expected path and may deviate from the lane when driving on a curve, increasing the risk of collision with other objects.

[0038] In the field of mine autonomous driving, the unstructured roads and complex driving scenarios in mine scenes pose huge challenges to the implementation of mine autonomous driving. At the same time, considering that the installation of the actuators of mining transport trucks cannot be effectively standardized like passenger cars, and even most mining truck manufacturers do not support four-wheel alignment, there will inevitably be certain errors after the steering wheel is installed, which makes the steering wheels of different mining trucks show individual zero bias differences. In particular, the lateral control of mining transport trucks for autonomous driving is mostly to directly control the front wheels for steering, rather than steering control through the steering wheel. Therefore, the dead zone, zero bias, response delay and other problems exposed by its actuators are also greater than those of passenger cars. In the case of manual driving, the driver corrects the steering wheel by observing the actual driving trajectory of the vehicle to offset the impact of zero bias, etc., but in the case of autonomous driving, in complex road scenes such as mines, if the trajectory is tracked at medium and high speeds, even a small zero bias of the steering wheel will cause the vehicle to deviate from the center reference line of the driving trajectory, increasing the driving risk of autonomous driving.

[0039] At present, the control methods for adaptive calibration of zero bias angle are mostly based on vehicle kinematic and dynamic models, and the vehicle's driving road scenes are relatively regular and simple, which makes it easy to obtain long straight road scenes for self-calibration. In addition, this method is mostly used for the calibration of steering wheel zero bias of passenger cars and small mining vehicles, and less for the zero bias calibration of large-tonnage mining trucks that only rely on the front wheels to control the steering. In addition, many online self-calibration methods cannot be well adapted to mining vehicles. The main reason is that mining scenes cannot have many simple straight driving scenes like passenger cars, and it is impossible to guarantee whether the vehicle can meet the self-calibration conditions by driving on a straight road for a long time. Secondly, we are also limited by the interference factors caused by inaccurate positioning due to poor signals in mining scenes. It is impossible to determine whether the vehicle's driving process deviates from one side of the reference line due to inaccurate positioning or zero bias angle problems. Therefore, conventional self-calibration algorithms cannot reproduce mining scenes well. Considering the irregular and complex driving road scenes and low driving speed characteristics of mining trucks, many manufacturers often use some non-model-based control schemes to reduce the complexity of the vehicle control algorithm while also having good control effects. Therefore, the conventional zero bias angle calibration control method cannot be well adapted to the zero bias calibration of mining trucks under large tonnage and complex road scene conditions.

[0040] For autonomous driving in mines, whether the planned path can be stably and accurately tracked to reach the designated destination is a very important control performance indicator. At present, since the zero deviation angle of mining transport trucks is larger than that of passenger cars, and the size and direction of the zero deviation angle of each vehicle are different, the problem of fixed-direction lateral deviation will be brought about to achieve its lateral high-precision tracking control, and the fixed-direction lateral deviation caused by this defect cannot be completely corrected by the lateral control algorithm of the vehicle. At the same time, considering that only relying on manual measurement of the zero deviation angle of each vehicle and manually compensating it to the issued turning angle of lateral control in the form of configuration parameters can only roughly solve the problems caused by the zero deviation angle. This method will not only consume a large labor cost, but also the results measured by this method are affected by external objective factors, resulting in the results not necessarily being accurate. Therefore, how to provide a control method and system for adaptively calibrating the zero deviation angle of mining trucks, and automatically compensating it to the issued turning angle to eliminate the problem caused by zero deviation is a major issue that algorithm engineers in this field urgently need to solve.

[0041] In order to more clearly understand the above-mentioned purposes, features and advantages of the present application, the scheme of the present application will be further described below. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0042] In the following description, many specific details are set forth to facilitate a full understanding of the present application, but the present application may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only part of the embodiments of the present application, rather than all of the embodiments.

[0043] In order to solve some or all of the technical problems existing in the related art, the embodiment of the present application provides a zero bias calibration method, device, vehicle, equipment and medium for a vehicle steering wheel, wherein the method first controls the vehicle to travel along the calibration map according to the expected turning angle within a preset speed range; collects the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range; calculates the zero bias angle measurement value at different speeds according to the actual turning angle and the expected turning angle; based on the preset speed range, lateral deviation and zero bias angle estimation value, the zero bias angle estimation value is calculated based on the lateral deviation and the route length of the calibration map to establish a correlation between the vehicle speed, lateral deviation and zero bias angle; determines the target zero bias angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation; filters and fuses the target zero bias angle estimation value and the zero bias angle measurement value to obtain the zero bias angle calibration value, so as to automatically compensate the zero bias angle calibration value to the issued turning angle to control the wheel steering. In this way, the present application can comprehensively consider the influence of different vehicle speeds on the zero bias angle by controlling the vehicle to travel within the preset speed range. The lateral deviation and actual turning angle are collected at different vehicle speeds, and the calculated zero deviation angle measurement value is more in line with the actual situation, which can accurately capture the difference in zero deviation angle at different vehicle speeds. The correlation between vehicle speed, lateral deviation and zero deviation angle is established, and the target zero deviation angle estimation value is determined from multiple dimensions. Then, the estimation value and the measurement value are filtered and fused, which greatly improves the accuracy of zero deviation angle calibration. Automatic calibration of zero deviation angle is achieved, without manual measurement and manual compensation, which greatly reduces labor costs.

[0044] A zero bias calibration method for a vehicle steering wheel provided in an embodiment of the present application can be implemented by a zero bias calibration device or an electronic device of a vehicle steering wheel, and the electronic device includes but is not limited to a personal computer, a laptop computer, a tablet computer, a smart phone, etc. The operating system of the electronic device may include an Android (Android), a mobile operating system (iOS) developed by Apple, an operating system (Windows) developed by Microsoft Corporation of the United States, etc., and the embodiment of the present application does not limit this. The electronic device can be run alone to implement the present application, or it can be connected to a network and implement the present application through interactive operations with other computer devices in the network. Wherein, the network in which the electronic device is located includes but is not limited to the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (Virtual Private Network, VPN) network, etc.

[0045] It should be noted that the protection scope of the zero bias calibration method for a vehicle steering wheel described in an embodiment of the present application is not limited to the execution order of the steps listed in this embodiment, and all solutions implemented by adding, reducing or replacing steps in the prior art based on the principles of the present application are included in the protection scope of the present application.

[0046] like Figure 1 As shown, Figure 1 The present invention is a flowchart of a method for zero bias calibration of a vehicle steering wheel according to an embodiment of the present invention. The method can be performed by a zero bias calibration device for a vehicle steering wheel, wherein the device can be implemented by software and / or hardware and can generally be integrated in an electronic device. The method mainly includes the following steps S101 to S106:

[0047] S101, controlling the vehicle to travel along a calibrated map at a desired turning angle within a preset speed range.

[0048] In some embodiments, before executing step S101, a straight line path of a preset length is first collected to generate a calibration map. The preset length may be 100 meters, and the straight line path is not limited to a road type.

[0049] The vehicle is controlled to drive automatically along the calibrated map according to the expected turning angle, and the expected turning angle may be 0. In the automatic driving mode, the preset vehicle speed range may be 5 to 30 km / h. For example, the vehicle is controlled to enter the starting point of the straight path, and the vehicle is driven automatically along the calibrated map at a speed of 5 km / h according to the expected turning angle throughout the journey to complete the tracking of the 100-meter straight path.

[0050] S102: Collecting lateral deviation and actual turning angle of the vehicle at different speeds within a preset speed range.

[0051] The lateral deviation and the actual turning angle at different vehicle speeds within the preset vehicle speed range are collected. For example, the lateral deviation and the actual turning angle at 5km / h, 10km / h, 15km / h, 20km / h, 25km / h and 30km / h are collected.

[0052] In some embodiments, multiple lateral deviations and multiple actual turning angles of the vehicle at each vehicle speed within a preset vehicle speed range are collected, and then the average value of the multiple lateral deviations is used as the lateral deviation corresponding to each vehicle speed, and the average value of the multiple actual turning angles is used as the actual turning angle corresponding to each vehicle speed.

[0053] For example, to ensure data validity, three lateral deviations are collected at each vehicle speed, and the average of the three lateral deviations is used as the lateral deviation corresponding to the vehicle speed. Three actual turning angles are collected at each vehicle speed, and the average of the three actual turning angles is used as the actual turning angle corresponding to the vehicle speed. Then, the actual turning angle is subtracted from the expected turning angle to obtain the zero deviation angle measurement value.

[0054] S103: Calculate zero-angle measurement values ​​at different vehicle speeds according to the actual turning angle and the expected turning angle.

[0055] Optionally, after executing step S102, three actual turning angles are collected at each vehicle speed. Then, the zero deflection angle measurement value is obtained by subtracting the actual turning angle from the expected turning angle. The average of the three zero deflection angle measurement values ​​at each vehicle speed is used as the zero deflection angle measurement value actually corresponding to the vehicle speed.

[0056] S104. Establishing a correlation between the vehicle speed, the lateral deviation and the zero deviation angle based on a preset vehicle speed range, the lateral deviation and the zero deviation angle estimation value, wherein the zero deviation angle estimation value is calculated based on the lateral deviation and the route length of the calibration map.

[0057] The estimated value of zero deflection angle θ is calculated according to Calculated, where lat_err represents the lateral deviation of the vehicle along the calibration map to the end point; dis represents the route length of the calibration map, for example, 100m. Driving along the calibration map at different speeds will produce different lateral deviations, that is, different zero deviation angle estimates can be obtained.

[0058] According to different vehicle speeds within the preset vehicle speed range, and the lateral deviation and zero deviation angle estimation values ​​corresponding to each vehicle speed, a correlation between the vehicle speed, the lateral deviation and the zero deviation angle is established. In some embodiments, a two-dimensional calibration table between the vehicle speed, the lateral deviation and the zero deviation angle is established with the lateral deviation corresponding to each vehicle speed within the preset vehicle speed range as a row index and each vehicle speed as a column index.

[0059] Exemplarily, the correlation can be represented by a two-dimensional calibration table, where the behavioral lateral deviation lat_error_list

[21] = [-2.0, -1.8, -1.6, -1.4, -1.2, -1.0, -0.8, -0.6, -0.4, -0.2, 0.0, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0], unit: m, and the column is vehicle speed speed_list[7] = [0, 5, 10, 15, 20, 25, 30], unit: km / h.

[0060] The two-dimensional calibration table is shown in Table 1 below:

[0061] Table 1

[0062]

[0063]

[0064] S105, determining a target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation relationship;

[0065] In some embodiments, based on the row and column indexes of the two-dimensional calibration table, a target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle is obtained by querying.

[0066] In some other embodiments, when the actual vehicle speed and the actual lateral deviation corresponding to the vehicle do not exist in the two-dimensional calibration table, the target zero deviation angle estimation value is estimated by linear interpolation. Linear interpolation is a method of estimating unknown data points by using known data points.

[0067] Optionally, estimating the target zero bias angle estimate by linear interpolation includes: determining an interpolation interval of the actual vehicle speed and / or the actual lateral deviation; calculating a vehicle speed interpolation weight and / or a lateral deviation interpolation weight based on the actual vehicle speed and / or the actual lateral deviation and the distance from the corresponding interpolation interval endpoint; obtaining a target zero bias angle estimate corresponding to the interpolation interval endpoint from a two-dimensional calibration table; and calculating a target zero bias angle estimate corresponding to the actual vehicle speed and the actual lateral deviation based on the target zero bias angle estimate corresponding to the interpolation interval endpoint, as well as the vehicle speed interpolation weight and / or the lateral deviation interpolation weight.

[0068] Using the previous example, we will explain the specific process of using linear interpolation to calculate the target zero deflection angle estimate:

[0069] Step 201: Determine the interpolation interval of vehicle speed and lateral deviation.

[0070] Find two adjacent speed values ​​v1 and v2 in the speed list speed_list, such that v1≤v≤v2. For example, if the actual speed v of the vehicle is 12km / h, then in speed_list v1=10km / h, v2=15km / h.

[0071] Find two adjacent lateral error values ​​lat1 and lat2 in the lateral error list lat_error_list, such that lat1≤lat≤lat2. For example, if the actual lateral error lat is 0.3m, then lat1=0.2m, lat2=0.4m.

[0072] Step 202: Calculate the interpolation weights of vehicle speed and lateral deviation.

[0073] The weight is calculated based on the distance between the vehicle speed and the end point of the interpolation interval. Let w1 be the weight of v relative to v1, and w2 be the weight of v relative to v2, then w2 = (vv1) / (v2v1), w1 = 1w2. For v = 12km / h, v1 = 10km / h, v2 = 15km / h, we can get w2 = (1210) / (1510) = 0.4, w1 = 10.4 = 0.6.

[0074] Similarly, let u1 be the weight of lat relative to lat1, and u2 be the weight of lat relative to lat2, then u2 = (latlat1) / (lat2lat1), u1 = 1u2. For lat = 0.3m, lat1 = 0.2m, lat2 = 0.4m, we can get u2 = (0.30.2) / (0.40.2) = 0.5, u1 = 10.5 = 0.5.

[0075] Step 203: Obtain the corresponding zero deflection angle estimate.

[0076] According to the interpolation interval of the found vehicle speed and lateral deviation, determine the zero offset angle estimation values ​​corresponding to the four corner points. Let so11 be the zero offset angle estimation value corresponding to v1 and lat1, so12 be the zero offset angle estimation value corresponding to v1 and lat2, so21 be the zero offset angle estimation value corresponding to v2 and lat1, and so22 be the zero offset angle estimation value corresponding to v2 and lat2. For example, in the zero offset angle list steer_offset_list, v1=10km / h, lat1=0.2m corresponds to so11=0.128 degrees; v1=10km / h, lat2=0.4m corresponds to so12=0.267 degrees; v2=15km / h, lat1=0.2m corresponds to so21=0.129 degrees; v2=15km / h, lat2=0.4m corresponds to so22=0.374 degrees.

[0077] Step 204: Perform bilinear interpolation calculation.

[0078] First, when the lateral deviation is lat1, so11 and so21 are interpolated according to the vehicle speed interpolation weight to obtain so_lat1 = w1so11 + w2so21; when the lateral deviation is lat2, so12 and so22 are interpolated to obtain so_lat2 = w1so12 + w2so22. For the above example, so_lat1 = 0.60.128 + 0.40.129 = 0.1284 degrees, so_lat2 = 0.60.267 + 0.40.374 = 0.3134 degrees.

[0079] Finally, so_lat1 and so_lat2 are interpolated according to the lateral deviation interpolation weight to obtain the final target zero deflection angle estimation value so = u1so_lat1 + u2so_lat2, that is, so = 0.50.1284 + 0.50.3134 = 0.2209 degrees.

[0080] In other embodiments, when the actual vehicle speed and the actual lateral deviation corresponding to the vehicle do not exist in the two-dimensional calibration table, polynomial interpolation, spline interpolation, radial basis function interpolation, inverse distance weighted interpolation, etc. can be used to estimate the target zero deviation angle estimate. This application does not specifically limit this.

[0081] S106, filtering and fusing the target zero deflection angle estimation value and the zero deflection angle measurement value to obtain a zero deflection angle calibration value, so as to automatically compensate the zero deflection angle calibration value to the issued steering angle to control the wheel steering.

[0082] Optionally, the target zero deflection angle estimation value and the zero deflection angle measurement value are fused through a Kalman filter to obtain a zero deflection angle calibration value. The autonomous driving system then calculates and issues a steering angle instruction to the steering wheel based on the planned path and the zero deflection angle calibration value, increasing or decreasing an angle value corresponding to the zero deflection angle calibration value. In this way, the actual steering wheel rotation angle will be adjusted due to this compensation value, thereby offsetting the influence of the zero deflection angle on the driving path, allowing the vehicle to accurately drive along the planned path.

[0083] The calculation formula of the Kalman filter involves the prediction stage and the correction stage. The prediction stage includes the state estimation value prediction and the covariance prediction, as shown in formula (1)(2); the correction stage includes the Kalman gain calculation, the state optimal estimation value correction and the covariance correction, as shown in formula (3)(4)(5):

[0084]

[0085] P - k =A×P - k-1 ×A T +Q(2)

[0086]

[0087] P k =(IK k ×H)×P - k (5)

[0088] In formula (1), is the estimated value of the zero deflection angle at the current time k, is the zero deflection estimate of the previous moment k-1, and A is the state transfer matrix. and the state transfer matrix A to predict the zero deflection angle estimate at the current time k

[0089] In formula (2), P - kis the covariance between the zero deflection measurement and the zero deflection estimate at the current time k, P - k-1 is the covariance between the zero deflection measurement value and the zero deflection estimate at the previous moment k-1, Q is the process noise matrix, which represents the influence of certain uncertain factors on the covariance. - k-1 and the state transfer matrix A and the transpose of A T To calculate the covariance P at the current moment - k , plus the process noise matrix Q.

[0090] In formula (3), K k is the Kalman gain, which represents the weight of the zero deflection angle measurement value and the zero deflection angle estimation value in the state optimal estimation process. H is the measurement matrix, and R is the measurement noise matrix. Kalman gain K k Comprehensively consider the covariance P obtained in the prediction stage - k , measurement matrix H and measurement noise matrix R. The purpose is to determine the weight of the zero deflection angle measurement value and the zero deflection angle estimation value in the final state optimal estimation. If the measurement noise is relatively small, that is, the zero deflection angle measurement value is more accurate, then the weight of the zero deflection angle measurement value will be larger; conversely, if the zero deflection angle estimation value is more reliable, the weight of the zero deflection angle estimation value will be larger.

[0091] In formula (4), we already have the predicted zero deflection angle estimate Now we have a zero declination measurement z k (obtained through a two-dimensional linear lookup table), through the Kalman gain K k To combine the zero deflection angle estimate with the zero deflection angle measurement, we can get the optimal zero deflection angle estimate. is the zero deflection angle measurement value calculated based on the zero deflection angle estimate, It is the error between the zero deflection angle measurement and the zero deflection angle estimate. This error is multiplied by the Kalman gain K k , plus the zero skew estimate A more accurate estimate of the optimal zero deflection angle is obtained.

[0092] In formula (5), I is the identity matrix. According to the Kalman gain K k , measurement matrix H and prediction covariance P - k To calculate the covariance P between the zero deflection measurement and the optimal zero deflection estimate k Subtract K from the identity matrix I k ×H and then multiply by P - k, is to update the covariance so that it can more accurately reflect the current estimation error.

[0093] In some embodiments, after executing step S106, it can also be determined whether the zero deflection angle calibration value is greater than or equal to a first threshold and less than or equal to a second threshold; if the zero deflection angle calibration value is less than the first threshold, the first threshold is used as the new zero deflection angle calibration value; if the zero deflection angle calibration value is greater than the second threshold, the second threshold is used as the new zero deflection angle calibration value.

[0094] like Figure 2 As shown, Figure 2 This is a flowchart of the processing logic of the zero steer angle calibration value (steer_offset). The main steps are as follows:

[0095] Step 1. Input the zero-angle calibration value steer_offset after filtering and fusion;

[0096] Step 2: Determine whether the zero deviation angle calibration value steer_offset exceeds the set threshold range [steer_offset_limit, steer_offset_limit]. The threshold range is defined by a first threshold steer_offset_limit and a second threshold steer_offset_limit.

[0097] If "steer_offset" is less than steer_offset_limit, that is, it exceeds the left boundary, the process points to the left and outputs steer_offset_limit.

[0098] If "steer_offset" is within the range of [steer_offset_limit,steer_offset_limit], directly output "steer_offset" itself.

[0099] When "steer_offset" is greater than steer_offset_limit, that is, it exceeds the right boundary, the process points to the right and outputs steer_offset_limit.

[0100] This is done to avoid abnormalities in the zero bias angle calibration value obtained by fusion filtering, which leads to unreasonable zero bias calibration results, thereby causing adverse effects on the mining truck during automatic driving, and further affecting the tracking accuracy and safety of the entire vehicle. This embodiment limits the zero bias angle calibration value obtained by fusion filtering to a specific threshold range to avoid its value being too large or too small.

[0101] In summary, the embodiment of the present application provides a method for zero bias calibration of a vehicle steering wheel, which first controls the vehicle to travel according to the expected turning angle along the calibration map within a preset speed range; collects the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range; calculates the zero bias angle measurement values ​​at different speeds according to the actual turning angle and the expected turning angle; based on the preset speed range, lateral deviation and zero bias angle estimation value, the zero bias angle estimation value is calculated based on the lateral deviation and the route length of the calibration map to establish a correlation between the vehicle speed, lateral deviation and zero bias angle; determines the target zero bias angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation; filters and fuses the target zero bias angle estimation value and the zero bias angle measurement value to obtain a zero bias angle calibration value, so as to automatically compensate the zero bias angle calibration value to the issued turning angle to control the wheel steering.

[0102] In this way, this application can comprehensively consider the impact of different vehicle speeds on the zero deviation angle by controlling the vehicle to travel within a preset speed range. Traditional methods are mostly based on fixed models and do not fully consider changes in vehicle speed. This application collects lateral deviations and actual turning angles at different vehicle speeds, and the calculated zero deviation angle measurement value is more in line with the actual situation. For example, in mine transportation, the vehicle speed often varies due to different road conditions. This application can accurately capture the difference in zero deviation angle at different vehicle speeds.

[0103] This application establishes the correlation between vehicle speed, lateral deviation and zero deflection angle, determines the target zero deflection angle estimation value from multiple dimensions, and then filters and fuses the estimation value and the measured value, which greatly improves the accuracy of zero deflection angle calibration. Compared with determining the zero deflection angle by a single method, this method combines multiple factors and can effectively reduce the risk of vehicle deviation from the trajectory due to inaccurate zero deflection angle, ensuring more stable driving of autonomous driving vehicles in mines.

[0104] Mine roads are complex, and traditional self-calibration methods rely on simple regular road scenes, which are difficult to apply in mines. This application operates within a preset speed range and can adapt to the variable speed of mine vehicles. Even under complex road conditions, it can complete the zero deviation angle calibration according to different vehicle speeds.

[0105] This application does not need to rely on long straight road scenes for self-calibration, and is not affected by inaccurate positioning caused by poor signals in mines. Because it focuses on determining the zero deflection angle through its own driving data such as vehicle speed and lateral deviation, rather than relying solely on positioning data, it can better adapt to the complex environment of mines and achieve effective calibration of the zero deflection angle.

[0106] In the past, the method of manually measuring the zero deflection angle of each vehicle and manually compensating it to the issued turning angle consumed a lot of manpower and the results were inaccurate due to external factors. This application realizes automatic calibration of the zero deflection angle, without the need for manual measurement and manual compensation, which greatly reduces labor costs.

[0107] This application automatically compensates for the issued turning angle, avoiding possible errors caused by manual operation, ensuring the consistency and accuracy of zero deviation angle compensation for each vehicle, and improving the overall operating efficiency and reliability of the mine's automatic driving system.

[0108] like Figure 3 As shown, Figure 3 A schematic diagram of the structure of a zero bias calibration device for a vehicle steering wheel provided in an embodiment of the present application, the device comprising:

[0109] The control module 301 is used to control the vehicle to travel along the calibrated map according to the desired turning angle within a preset speed range;

[0110] The information collection module 302 is used to collect the lateral deviation and actual turning angle of the vehicle at different speeds within a preset speed range;

[0111] The data processing module 303 is used to calculate the zero deviation angle measurement value under different vehicle speeds based on the actual turning angle and the expected turning angle; establish the correlation between the vehicle speed, the lateral deviation and the zero deviation angle based on the preset vehicle speed range, the lateral deviation and the zero deviation angle estimation value, and the zero deviation angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; determine the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation relationship; filter and fuse the target zero deviation angle estimation value and the zero deviation angle measurement value to obtain the zero deviation angle calibration value, so as to automatically compensate the zero deviation angle calibration value to the issued turning angle to control the wheel steering.

[0112] As an optional implementation provided in an embodiment of the present application, the data processing module 303 establishes a correlation between the vehicle speed, lateral deviation and zero deviation angle based on a preset vehicle speed range, lateral deviation and zero deviation angle estimation value, and is specifically used to: use the lateral deviation corresponding to each vehicle speed within the preset vehicle speed range as a row index and each vehicle speed as a column index to establish a two-dimensional calibration table between the vehicle speed, lateral deviation and zero deviation angle.

[0113] As an optional implementation provided in an embodiment of the present application, the data processing module 303 determines the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation relationship, and is specifically used to: obtain the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation from a two-dimensional calibration table.

[0114] As an optional implementation provided in an embodiment of the present application, the data processing module 303 is also used to: if the actual vehicle speed and / or the actual lateral deviation does not exist in the two-dimensional calibration table, estimate the target zero deviation angle estimate by linear interpolation.

[0115] As an optional implementation provided in an embodiment of the present application, the device also includes a verification module for determining whether the zero deflection angle calibration value is greater than or equal to a first threshold and less than or equal to a second threshold; if the zero deflection angle calibration value is less than the first threshold, the first threshold is used as the new zero deflection angle calibration value; if the zero deflection angle calibration value is greater than the second threshold, the second threshold is used as the new zero deflection angle calibration value.

[0116] As an optional implementation provided in an embodiment of the present application, the information collection module 302 is specifically used to: collect multiple lateral deviations and multiple actual turning angles of the vehicle at each vehicle speed within a preset speed range; take the average value of the multiple lateral deviations as the lateral deviation corresponding to each vehicle speed, and take the average value of the multiple actual turning angles as the actual turning angle corresponding to each vehicle speed.

[0117] For the specific definition of the zero bias calibration device for the vehicle steering wheel, please refer to the definition of the zero bias calibration method for the vehicle steering wheel in the above text, which will not be repeated here. Each module in the above-mentioned zero bias calibration device for the vehicle steering wheel can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0118] In one embodiment, the present application provides an electronic device, which may be a terminal, and its internal structure diagram may be as follows: Figure 4 As shown. The electronic device includes a processor, a memory, a communication interface, a display screen and an input device connected by a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the electronic device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, an operator network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a method for detecting a jam is implemented. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device can be a touch layer covered on the display screen, or a button, a trackball or a touchpad provided on the housing of the electronic device, or an external keyboard, touchpad or mouse, etc.

[0119] Those skilled in the art will understand that Figure 4The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0120] In one embodiment, the zero offset calibration device for the vehicle steering wheel provided in the present application can be implemented in the form of a computer program. The computer program can be Figure 4 The memory of the electronic device may store various program modules constituting the zero bias calibration device of the vehicle steering wheel, for example, Figure 3 The control module 301, information acquisition module 302 and data processing module 303 are shown. The computer program composed of various program modules enables the processor to execute the steps of the zero bias calibration method of the vehicle steering wheel in various embodiments of the present application described in this specification.

[0121] For example, Figure 4 The electronic device shown can be Figure 3 The control module 301 in the zero bias calibration device of the vehicle steering wheel shown controls the vehicle to travel according to the expected turning angle along the calibration map within the preset speed range; the electronic device can collect the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range through the information collection module 302; the electronic device can calculate the zero bias angle measurement value at different speeds according to the actual turning angle and the expected turning angle through the data processing module 303; based on the preset speed range, the lateral deviation and the zero bias angle estimation value, establish a correlation between the vehicle speed, the lateral deviation and the zero bias angle, and the zero bias angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; determine the target zero bias angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation relationship; filter and fuse the target zero bias angle estimation value and the zero bias angle measurement value to obtain the zero bias angle calibration value, so as to automatically compensate the zero bias angle calibration value to the issued turning angle to control the wheel steering.

[0122] In one embodiment, the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0123] The vehicle is controlled to travel along the calibration map at the expected turning angle within the preset speed range; the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range are collected; the zero deviation angle measurement values ​​at different speeds are calculated according to the actual turning angle and the expected turning angle; based on the preset speed range, the lateral deviation and the zero deviation angle estimation value, a correlation between the vehicle speed, the lateral deviation and the zero deviation angle is established, and the zero deviation angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle is determined according to the correlation relationship; the target zero deviation angle estimation value and the zero deviation angle measurement value are filtered and fused to obtain a zero deviation angle calibration value, so as to automatically compensate the zero deviation angle calibration value to the issued turning angle to control the wheel steering.

[0124] In one embodiment, when the processor executes the computer program, the following steps are also implemented: based on a preset vehicle speed range, lateral deviation and zero deviation angle estimation value, a correlation between the vehicle speed, lateral deviation and zero deviation angle is established, including: using the lateral deviation corresponding to each vehicle speed within the preset vehicle speed range as a row index and each vehicle speed as a column index to establish a two-dimensional calibration table between the vehicle speed, lateral deviation and zero deviation angle.

[0125] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle based on the correlation relationship, including: obtaining the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation from a two-dimensional calibration table.

[0126] In one embodiment, the processor further implements the following steps when executing the computer program: The method also includes: if the actual vehicle speed and / or the actual lateral deviation does not exist in the two-dimensional calibration table, estimating the target zero deviation angle estimate value by linear interpolation.

[0127] In one embodiment, the processor also implements the following steps when executing the computer program: the method also includes: determining whether the zero deflection angle calibration value is greater than or equal to a first threshold and less than or equal to a second threshold; if the zero deflection angle calibration value is less than the first threshold, using the first threshold as the new zero deflection angle calibration value; if the zero deflection angle calibration value is greater than the second threshold, using the second threshold as the new zero deflection angle calibration value.

[0128] In one embodiment, when the processor executes the computer program, it also implements the following steps: collecting the lateral deviation and actual turning angle of the vehicle at different speeds within a preset speed range, including: collecting multiple lateral deviations and multiple actual turning angles of the vehicle at each speed within the preset speed range; taking the average value of the multiple lateral deviations as the lateral deviation corresponding to each speed, and taking the average value of the multiple actual turning angles as the actual turning angle corresponding to each speed.

[0129] When the processor in the electronic device provided by the present application executes a computer program, the vehicle is first controlled to travel along the calibration map according to the expected turning angle within the preset speed range; the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range are collected; the zero deviation angle measurement value at different speeds is calculated according to the actual turning angle and the expected turning angle; based on the preset speed range, the lateral deviation and the zero deviation angle estimation value, the correlation between the vehicle speed, the lateral deviation and the zero deviation angle is established, and the zero deviation angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle is determined according to the correlation; the target zero deviation angle estimation value and the zero deviation angle measurement value are filtered and fused to obtain the zero deviation angle calibration value, so as to automatically compensate the zero deviation angle calibration value to the issued turning angle to control the wheel steering. In this way, the present application can comprehensively consider the influence of different vehicle speeds on the zero deviation angle by controlling the vehicle to travel within the preset speed range. The lateral deviation and the actual turning angle are collected at different vehicle speeds, and the calculated zero deviation angle measurement value is more in line with the actual situation, and the difference of the zero deviation angle at different vehicle speeds can be accurately captured. The correlation between vehicle speed, lateral deviation and zero deflection angle is established, the target zero deflection angle estimation value is determined from multiple dimensions, and then the estimation value and the measured value are filtered and fused, which greatly improves the accuracy of zero deflection angle calibration. Automatic calibration of zero deflection angle is achieved, without manual measurement and manual compensation, which greatly reduces labor costs.

[0130] The present application provides an autonomous driving vehicle for use in a mine scenario, comprising:

[0131] A travel mechanism, configured to drive the vehicle on a mine road;

[0132] A steering actuator configured to control the steering of the wheels;

[0133] The data collection device is configured to collect the lateral deviation and actual turning angle of the vehicle at different vehicle speeds within a preset vehicle speed range;

[0134] The control unit is configured to: control the vehicle to travel along the calibration map according to the expected turning angle within a preset speed range; calculate the zero deviation angle measurement value at different vehicle speeds based on the actual turning angle and the expected turning angle; establish a correlation between the vehicle speed, the lateral deviation and the zero deviation angle based on the preset speed range, the lateral deviation and the zero deviation angle estimation value, the zero deviation angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; determine the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation according to the correlation relationship; filter and fuse the target zero deviation angle estimation value and the zero deviation angle measurement value to obtain the zero deviation angle calibration value, so as to automatically compensate the zero deviation angle calibration value to the issued turning angle and control the steering actuator.

[0135] In one embodiment, the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the following steps when the computer program is executed:

[0136] The vehicle is controlled to travel along the calibration map at the expected turning angle within the preset speed range; the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range are collected; the zero deviation angle measurement values ​​at different speeds are calculated according to the actual turning angle and the expected turning angle; based on the preset speed range, the lateral deviation and the zero deviation angle estimation value, a correlation between the vehicle speed, the lateral deviation and the zero deviation angle is established, and the zero deviation angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle is determined according to the correlation relationship; the target zero deviation angle estimation value and the zero deviation angle measurement value are filtered and fused to obtain a zero deviation angle calibration value, so as to automatically compensate the zero deviation angle calibration value to the issued turning angle to control the wheel steering.

[0137] In one embodiment, when the computer program executes the computer program, the following steps are also implemented: based on a preset vehicle speed range, lateral deviation and zero deviation angle estimation value, a correlation between the vehicle speed, lateral deviation and zero deviation angle is established, including: using the lateral deviation corresponding to each vehicle speed within the preset vehicle speed range as a row index and each vehicle speed as a column index to establish a two-dimensional calibration table between the vehicle speed, lateral deviation and zero deviation angle.

[0138] In one embodiment, when the computer program is executed, the following steps are also implemented: determining the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle based on the correlation relationship, including: obtaining the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation by querying from a two-dimensional calibration table.

[0139] In one embodiment, the computer program further implements the following steps when executing the computer program: The method also includes: if the actual vehicle speed and / or the actual lateral deviation does not exist in the two-dimensional calibration table, estimating the target zero deviation angle estimate by linear interpolation.

[0140] In one embodiment, the computer program further implements the following steps when executing the computer program: the method also includes: determining whether the zero deflection angle calibration value is greater than or equal to a first threshold and less than or equal to a second threshold; if the zero deflection angle calibration value is less than the first threshold, using the first threshold as the new zero deflection angle calibration value; if the zero deflection angle calibration value is greater than the second threshold, using the second threshold as the new zero deflection angle calibration value.

[0141] In one embodiment, when the computer program executes the computer program, the following steps are also implemented: collecting the lateral deviation and actual turning angle of the vehicle at different speeds within a preset speed range, including: collecting multiple lateral deviations and multiple actual turning angles of the vehicle at each speed within the preset speed range; taking the average value of the multiple lateral deviations as the lateral deviation corresponding to each speed, and taking the average value of the multiple actual turning angles as the actual turning angle corresponding to each speed.

[0142] When the computer program in the computer-readable storage medium provided by the present application executes the computer program, the vehicle is first controlled to travel along the calibration map according to the expected turning angle within the preset speed range; the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range are collected; the zero deviation angle measurement value at different speeds is calculated according to the actual turning angle and the expected turning angle; based on the preset speed range, the lateral deviation and the zero deviation angle estimation value, the correlation between the speed, the lateral deviation and the zero deviation angle is established, and the zero deviation angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; the target zero deviation angle estimation value corresponding to the actual speed and the actual lateral deviation of the vehicle is determined according to the correlation; the zero deviation angle estimation value and the zero deviation angle measurement value are filtered and fused to obtain the zero deviation angle calibration value, so as to automatically compensate the zero deviation angle calibration value to the issued turning angle to control the wheel steering. In this way, the present application can comprehensively consider the influence of different vehicle speeds on the zero deviation angle by controlling the vehicle to travel within the preset speed range. The lateral deviation and the actual turning angle are collected at different vehicle speeds, and the calculated zero deviation angle measurement value is more in line with the actual situation, and the difference of the zero deviation angle at different vehicle speeds can be accurately captured. The correlation between vehicle speed, lateral deviation and zero deflection angle is established, the target zero deflection angle estimation value is determined from multiple dimensions, and then the estimation value and the measured value are filtered and fused, which greatly improves the accuracy of zero deflection angle calibration. Automatic calibration of zero deflection angle is achieved, without manual measurement and manual compensation, which greatly reduces labor costs.

[0143] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media that include computer-usable program code.

[0144] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0145] In the present application, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0146] In this application, memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0147] In this application, computer-readable media includes permanent and non-permanent, removable and non-removable storage media. Storage media can be implemented by any method or technology to store information, and the information can be computer-readable instructions, data structures, modules of programs or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. According to the definition in this article, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0148] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0149] The above is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A zero bias calibration method for a vehicle steering wheel, characterized in that: include: Control the vehicle to travel along the calibrated map at the desired turning angle within a preset speed range; Collecting the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range; Calculating zero-angle measurement values ​​at different vehicle speeds according to the actual turning angle and the expected turning angle; Establishing a correlation between the vehicle speed, the lateral deviation and the zero deflection angle based on the preset vehicle speed range, the lateral deviation and the zero deflection angle estimation value, wherein the zero deflection angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; Determine a target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation; The target zero deflection angle estimation value and the zero deflection angle measurement value are filtered and fused to obtain a zero deflection angle calibration value, so as to automatically compensate the zero deflection angle calibration value to the issued steering angle to control the wheel steering.

2. The method according to claim 1, characterized in that The establishing of a correlation between the vehicle speed, the lateral deviation and the zero slip angle based on the preset vehicle speed range, the lateral deviation and the zero slip angle estimation value comprises: A two-dimensional calibration table between vehicle speed, lateral deviation and zero deflection angle is established by taking the lateral deviation corresponding to each vehicle speed within the preset vehicle speed range as a row index and each vehicle speed as a column index.

3. The method according to claim 2, characterized in that The step of determining a target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation relationship includes: The target zero deflection angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation is obtained by querying the two-dimensional calibration table.

4. The method according to claim 3, characterized in that: The method further comprises: If the actual vehicle speed and / or the actual lateral deviation does not exist in the two-dimensional calibration table, the target zero deviation angle estimation value is estimated by linear interpolation.

5. The method according to claim 1, characterized in that The method further comprises: Determine whether the zero deflection angle calibration value is greater than or equal to a first threshold and less than or equal to a second threshold; If the zero deflection angle calibration value is less than the first threshold value, taking the first threshold value as a new zero deflection angle calibration value; If the zero deflection angle calibration value is greater than the second threshold, the second threshold is used as a new zero deflection angle calibration value.

6. The method according to claim 1, characterized in that The collecting of the lateral deviation and the actual turning angle of the vehicle at different vehicle speeds within the preset vehicle speed range includes: Collecting a plurality of lateral deviations and a plurality of actual turning angles of the vehicle at each vehicle speed within the preset vehicle speed range; An average value of the plurality of lateral deviations is used as the lateral deviation corresponding to each vehicle speed, and an average value of the plurality of actual turning angles is used as the actual turning angle corresponding to each vehicle speed.

7. A zero bias calibration device for a vehicle steering wheel, characterized in that: include: A control module, used to control the vehicle to travel according to a desired turning angle along a calibrated map within a preset speed range; An information collection module is used to collect the lateral deviation and actual turning angle of the vehicle at different speeds within the preset speed range; The data processing module is used to calculate the zero deviation angle measurement value under different vehicle speeds according to the actual turning angle and the expected turning angle; establish the correlation between the vehicle speed, the lateral deviation and the zero deviation angle based on the preset vehicle speed range, the lateral deviation and the zero deviation angle estimation value, wherein the zero deviation angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; determine the target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation of the vehicle according to the correlation; filter and fuse the target zero deviation angle estimation value and the zero deviation angle measurement value to obtain a zero deviation angle calibration value, so as to automatically compensate the zero deviation angle calibration value to the issued turning angle to control the wheel steering.

8. An autonomous driving vehicle for use in mining scenarios, characterized in that: include: A travel mechanism, configured to drive the vehicle on a mine road; A steering actuator configured to control the steering of the wheels; The data collection device is configured to collect the lateral deviation and actual turning angle of the vehicle at different vehicle speeds within a preset vehicle speed range; A control unit, the control unit being configured to: Controlling the vehicle to travel along the calibrated map at a desired turning angle within the preset vehicle speed range; Calculating zero-angle measurement values ​​at different vehicle speeds according to the actual turning angle and the expected turning angle; Establishing a correlation between the vehicle speed, the lateral deviation and the zero deflection angle based on the preset vehicle speed range, the lateral deviation and the zero deflection angle estimation value, wherein the zero deflection angle estimation value is calculated based on the lateral deviation and the route length of the calibration map; Determine a target zero deviation angle estimation value corresponding to the actual vehicle speed and the actual lateral deviation according to the correlation; The target zero deflection angle estimation value and the zero deflection angle measurement value are filtered and fused to obtain a zero deflection angle calibration value, so as to automatically compensate the zero deflection angle calibration value to the issued steering angle and control the steering actuator.

9. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the zero bias calibration method for a vehicle steering wheel as claimed in any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium, characterized in that: include: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the zero bias calibration method for a vehicle steering wheel is implemented as claimed in any one of claims 1 to 6.

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