A surround view online calibration method and device for truck and truck

Abstract

The application belongs to the field of vehicle calibration, and specifically discloses a surround view online calibration method and device for a truck, a truck, and the like. The vertical direction offset, the vertical direction pitch angle, the horizontal direction offset angle, and the horizontal direction offset of each camera are calculated according to vehicle information. The angle change in the horizontal direction of the vehicle is calculated. The vertical angle correction matrix, the horizontal angle correction matrix, the vertical direction offset correction matrix, and the horizontal direction offset correction matrix are constructed through the above parameters. The vertical angle correction matrix, the horizontal angle correction matrix, and the current rotation matrix are multiplied to obtain a correction rotation matrix. The vertical direction offset correction matrix, the horizontal direction offset correction matrix, and the current translation matrix are multiplied to obtain a correction translation matrix. The correction rotation matrix and the correction translation matrix constitute new surround view external calibration parameters. The application automatically recalculates the calibration parameters according to the vehicle information when the vehicle state changes, and improves the surround view accuracy of the vehicle under different conditions.

Description

Technical Field

[0001] This invention belongs to the field of vehicle calibration, specifically relating to a method and device for online surround-view calibration of trucks, and a truck. Background Technology

[0002] 360° surround view, as an emerging technology, uses surround-view cameras placed around the vehicle to stitch together images of the vehicle's surroundings onto the central control screen, allowing the driver to understand the surrounding environment and ensure driving safety. Due to differences in vehicle model and camera installation location, 360° surround view requires calibration before use to ensure image display accuracy. Compared to passenger cars, trucks are subject to more factors affecting 360° surround view calibration accuracy due to their different uses. For example, drivers adjust vehicle height under different loads, affecting surround view accuracy; turning or driving on rough roads causes changes in yaw angle and tire slip angle, also impacting accuracy. Therefore, a specialized online surround view calibration system and method for trucks is needed to improve their surround view accuracy.

[0003] Currently, the main methods for surround view calibration include manual calibration and automatic system calibration. Manual calibration involves manually selecting specific calibration points at a designated calibration site. This method is easily affected by human subjectivity and has poor accuracy. Automatic system calibration, on the other hand, involves automatically selecting specific points at a designated calibration site. This method is more objective and has improved accuracy compared to manual calibration. However, for trucks, different loads and driving conditions can cause inaccuracies in the offline calibration parameters, thus affecting surround view accuracy. Automatic system calibration can only be performed offline, not online, and cannot quickly respond to real-time situations, further impacting surround view accuracy. Summary of the Invention

[0004] To address the aforementioned issues, this invention provides a method and apparatus for online surround view calibration of trucks, and a truck that automatically recalculates calibration parameters based on vehicle information when the vehicle's status changes, thereby improving surround view accuracy under different vehicle conditions.

[0005] In a first aspect, the technical solution of the present invention provides a method for online calibration of a truck's surround view system. The vehicle includes three axles: a front axle, a first rear axle, and a second rear axle. A 360° surround view camera is installed on each of the vehicle's left, right, front, and rear sides. When the vehicle is taken off the calibration line, initial surround view external calibration parameters are stored. These initial surround view external calibration parameters include an initial rotation matrix and an initial translation matrix for transforming the camera coordinate system to the world coordinate system. The method includes the following steps:

[0006] Obtain the height of the airbags on each axle of the vehicle, calculate the vertical offset of the vehicle based on the changes in the height of the airbags on each axle, and calculate the vertical offset of each camera based on the vertical offset of the vehicle.

[0007] Obtain the first and second rear axle loads of the vehicle, calculate the vehicle pitch angle based on the first and second rear axle loads, and determine the vertical pitch angle of each camera based on the vehicle pitch angle.

[0008] Obtain the vehicle's lateral acceleration, calculate the slip angle of each tire based on the vehicle's lateral acceleration, and calculate the horizontal offset angle of each camera based on the slip angle of each tire.

[0009] Calculate the left and right offset of each tire based on the side slip angle of each tire, and calculate the horizontal offset of each camera based on the left and right offset of each tire.

[0010] Obtain the vehicle's yaw angle and yaw angle, and calculate the change in the vehicle's horizontal angle based on the vehicle's yaw angle and yaw angle;

[0011] The vertical pitch angle and horizontal offset angle of each camera are multiplied by the vehicle's horizontal angle change, vertical offset, and horizontal offset to construct the vertical angle correction matrix, horizontal angle correction matrix, vertical offset correction matrix, and horizontal offset correction matrix, respectively.

[0012] Multiply the vertical angle correction matrix, horizontal angle correction matrix, and current rotation matrix to obtain the corrected rotation matrix. Multiply the vertical offset correction matrix, horizontal offset correction matrix, and current translation matrix to obtain the corrected translation matrix. The corrected rotation matrix and corrected translation matrix constitute the new surround view external calibration parameters.

[0013] In one optional implementation, the height of the airbags on each axle of the vehicle is obtained, the vertical offset of the vehicle is calculated based on the changes in the height of the airbags on each axle, and the vertical offset of each camera is calculated based on the vertical offset of the vehicle, specifically including:

[0014] Obtain the airbag height of each axis in the current sampling period and the previous sampling period;

[0015] The height variation of each airbag on each axis is calculated using the following formula.

[0016] △H1=H1'-H1

[0017] △H2=H2'-H2

[0018] △H3=H3'-H3

[0019] Where H1, H2, and H3 are the airbag heights of the front axis, the first rear axis, and the second rear axis in the previous sampling period, respectively; H1', ​​H2', and H3' are the airbag heights of the front axis, the first rear axis, and the second rear axis in the current sampling period, respectively; and △H1, △H2, and △H3 are the changes in airbag heights of the front axis, the first rear axis, and the second rear axis, respectively.

[0020] Calculate the average of △H1, △H2, and △H3 as the vertical offset of the vehicle;

[0021] The vertical offset of the front camera of the vehicle is the vertical offset of the vehicle.

[0022] The vertical offset of the cameras on the left and right sides of the vehicle = the vertical offset of the vehicle + the front overhang length × tan (the vertical tilt angle of the camera).

[0023] The vertical offset of the rear camera of the vehicle = the vertical offset of the vehicle + the length of the front of the vehicle × tan (vertical tilt angle of the camera).

[0024] In one optional implementation, the first and second rear axle loads of the vehicle are obtained, the vehicle pitch angle is calculated based on the first and second rear axle loads, and the vertical pitch angle of each camera is determined based on the vehicle pitch angle, specifically including:

[0025] Obtain the first rear axle loads M2 and m2 of the current sampling period and the previous sampling period, and calculate the first rear axle load difference Δm2 = M2 - m2;

[0026] Obtain the second rear axle loads M3 and m3 of the current sampling period and the previous sampling period, and calculate the second rear axle load difference Δm3 = M3 - m3;

[0027] Calculate the front axle weight difference Δm1, including:

[0028] (1) When the vehicle drive configuration is 6×2 with rear lift, ;

[0029] (2) When the vehicle drive configuration is 6×2 (rear lift, front lift), ;

[0030] (3) When the vehicle drive mode is 6×2 with lifting, ;

[0031] (4) When the vehicle drive configuration is 6×2 with lifting before lifting, ;

[0032] Where L is the distance from the vehicle's center of gravity to the middle of the two rear axles, L1 is the wheelbase of the main vehicle, and L2 is the distance between the first and second rear axles.

[0033] The vehicle pitch angle is calculated using the following formula. ,

[0034] ;

[0035] The vertical pitch angle of each camera is determined as the vehicle pitch angle. .

[0036] In one optional implementation, the lateral acceleration of the vehicle is acquired, the slip angle of each tire is calculated based on the lateral acceleration, and the horizontal offset angle of each camera is calculated based on the slip angle of each tire. Specifically, this includes:

[0037] The slip angle of each tire is calculated using the following formula. ,

[0038] ;

[0039] in, , ;

[0040] In the formula, For vehicle load capacity, For the lateral acceleration of the vehicle, This refers to the tire pressure adjustment factor. For nominal lateral stiffness, , , The calibration coefficient is the experimental coefficient. This refers to the number of tires;

[0041] The horizontal offset angle of the camera on the right side of the vehicle is the average of the sideslip angles of each tire on the right side;

[0042] The horizontal offset angle of the camera on the left side of the vehicle is the average of the sideslip angles of each tire on the left side;

[0043] The horizontal offset angle of the front and rear cameras of the vehicle is the average of the slip angles of all tires.

[0044] In one optional implementation, the lateral offset of each tire is calculated based on the tire slip angle, and the horizontal offset of each camera is calculated based on the lateral offset of each tire, specifically including:

[0045] The left and right offset y of each tire is calculated using the following formula.

[0046] y = v × t × tan(δ);

[0047] In the formula, v is the vehicle speed and t is the vehicle travel time;

[0048] The horizontal offset of the camera on the right side of the vehicle is the average of the left and right offsets of each tire on the right side.

[0049] The horizontal offset of the camera on the left side of the vehicle is the average of the left and right offsets of each tire on the left side.

[0050] The horizontal offset of the front and rear cameras of the vehicle is the average of the left and right offsets of all tires.

[0051] In an optional implementation, the change in the vehicle's horizontal angle is calculated based on the vehicle's yaw angle and yaw angle, specifically by calculating the change in the vehicle's horizontal angle using the following formula. :

[0052]

[0053] in, For the vehicle's yaw angle, This refers to the vehicle's yaw angle.

[0054] In an optional implementation, the method further includes the following steps:

[0055] When the vehicle vertical offset, vehicle pitch angle, tire slip angle, and tire lateral offset are less than the corresponding preset threshold, the corresponding changes will not be used as correction values ​​for the correction of the surround view external calibration parameters.

[0056] After obtaining the vertical angle correction matrix, horizontal angle correction matrix, vertical offset correction matrix, and horizontal offset correction matrix, if the time since the last update of the calibration parameters is greater than the update time threshold, and the number of updates within a certain period is less than the update number threshold, then the external calibration parameters for the surrounding view are updated.

[0057] In an optional implementation, the method further includes the following steps:

[0058] Configure the weighted values ​​of each influencing factor, which includes vertical pitch angle, horizontal offset angle, vertical offset, and horizontal offset.

[0059] The recommended values ​​for each influencing factor are calculated using the following formula. ,

[0060]

[0061] in, The weighted values ​​of the influencing factors. These are the values ​​of the influencing factors for each statistical analysis. This represents the number of times the count has been recorded.

[0062] Manually calibrate the values ​​based on the recommended values ​​for each influencing factor.

[0063] Secondly, the technical solution of the present invention provides a truck surround view online calibration device, including a main controller, which is electrically connected to an air suspension controller, an EBS / ABS controller, and a steering wheel controller respectively. The main controller obtains the airbag height of each axle of the vehicle from the air suspension controller, obtains the vehicle yaw angle and vehicle lateral acceleration from the EBS / ABS controller, and obtains the vehicle yaw angle from the steering wheel controller. The main controller executes the truck surround view online calibration method described above and feeds back the new surround view external calibration parameters to the surround view system.

[0064] Thirdly, the technical solution of the present invention provides a truck equipped with the above-mentioned device.

[0065] This invention provides a truck surround-view online calibration method and device, and a truck, which, compared to existing technologies, have the following advantages: It acquires parameters such as vehicle airbag height, axle load, and lateral acceleration; calculates the vertical and horizontal changes of the camera based on these vehicle parameters; and then corrects the camera's surround-view external calibration parameters based on these changes. When vehicle load or driving conditions change, this invention automatically recalculates calibration parameters using information such as vehicle airbag height, vehicle yaw angle, vehicle axle load, and tire slip angle, thereby improving surround-view accuracy under different conditions. Furthermore, the collected automatic calibration parameters are calculated to derive recommended points for manual calibration by the driver, thereby improving the accuracy of manual calibration parameters. Attached Figure Description

[0066] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0067] Figure 1 This is a schematic diagram of the architecture of a truck surround-view online calibration device provided in an embodiment of the present invention.

[0068] Figure 2 This is a schematic diagram of a truck surround view online calibration method provided in an embodiment of the present invention. Detailed Implementation

[0069] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the specific embodiments. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this patent application.

[0070] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0071] Figure 1 This is a schematic diagram of the architecture of a truck surround-view online calibration device provided in an embodiment of the present invention, including a main controller, which is electrically connected to an air suspension controller, an EBS / ABS controller, and a steering wheel controller.

[0072] The air suspension controller collects the airbag height data for each axle and transmits it to the main controller. The EBS / ABS controller collects the vehicle yaw angle and lateral acceleration data and transmits them to the main controller. The steering wheel controller collects the vehicle yaw angle data and transmits it to the main controller. Based on this information, the main controller executes an online calibration method for truck surround view, obtains new external calibration parameters, and feeds them back to the surround view system for recalibration. Specific steps of the online calibration method for truck surround view will be detailed in subsequent embodiments. Simultaneously, the main controller receives images of the vehicle's surroundings collected by a 360° surround view camera, providing calibration data for manual calibration and the first automatic calibration. The 360° surround view camera consists of four cameras installed at the front, left, right, and rear of the vehicle. Furthermore, the truck in this embodiment is a three-axle vehicle including a front axle, a first rear axle, and a second rear axle.

[0073] This embodiment performs a truck surround-view online calibration method during vehicle operation, enabling the calibration parameters to be more accurate according to changes in vehicle status. Manual calibration is performed before the vehicle is put into use, and automatic calibration is performed upon vehicle removal from service.

[0074] The first manual calibration of default parameters is required before the surround view system is installed to ensure the accuracy of automatic calibration. This is to load the system with default parameters (including the position / angle parameters of each camera, distortion correction coefficient, perspective transformation parameters, and stitching parameters). These default parameters are calibrated by relevant personnel at a specific site, and vehicles of the same model share these default parameters.

[0075] Automatic calibration is performed when the vehicle rolls off the production line. After the installation and debugging of the surround view system are completed and the rest of the parts are adjusted, automatic calibration is required at a specific site (which is exactly the same as the manual calibration site) to correct the default parameters. The correction process includes obtaining the coordinates of the automatic calibration parameters, comparing the coordinates of the automatic calibration parameters with the coordinates of the manual calibration parameters, obtaining the offset angles of the X-axis and Y-axis, correcting the manual calibration parameters by the offset angles, and stitching the new image obtained according to the corrected parameters.

[0076] The manual and automatic calibrations described above are performed immediately after the vehicle rolls off the production line. However, for trucks, at this point, the vehicle is neither equipped with a trailer nor carries any load. Once a trailer is added and a load is carried, the vehicle's height and axle loads change, and the vehicle's posture also changes under different road conditions. These factors affect the vehicle's yaw angle, pitch angle, vertical offset, lateral offset, and tire slip angle. Changes in these factors alter the position of the surround-view camera relative to its installation and calibration, leading to reduced surround-view accuracy or misalignment at the splicing points. Therefore, this embodiment uses the vehicle's CAN bus to send the relevant information collected by the controller to the main controller. The main controller then uses this information to recalculate the calibration parameters using the truck's online surround-view calibration method.

[0077] Figure 2 This is a schematic flowchart of an online calibration method for surround view systems used in trucks, provided by an embodiment of the present invention. Figure 2 As shown, the method includes the following steps. The order of the steps in this flowchart can be changed depending on different requirements.

[0078] S1, obtain the height of the airbags on each axle of the vehicle, calculate the vertical offset of the vehicle based on the change in the height of the airbags on each axle, and calculate the vertical offset of each camera based on the vertical offset of the vehicle.

[0079] S2, obtain the first and second rear axle loads of the vehicle, calculate the vehicle pitch angle based on the first and second rear axle loads, and determine the vertical pitch angle of each camera based on the vehicle pitch angle.

[0080] S3, acquire the vehicle's lateral acceleration, calculate the slip angle of each tire based on the vehicle's lateral acceleration, and calculate the horizontal offset angle of each camera based on the slip angle of each tire.

[0081] S4 calculates the left and right offset of each tire based on the side slip angle of each tire, and calculates the horizontal offset of each camera based on the left and right offset of each tire.

[0082] S5, obtain the vehicle yaw angle and vehicle roll angle, and calculate the change in the vehicle's horizontal angle based on the vehicle yaw angle and vehicle roll angle.

[0083] S6. Multiply the vertical pitch angle and horizontal offset angle of each camera by the vehicle's horizontal angle change, vertical offset, and horizontal offset to construct vertical angle correction matrix, horizontal angle correction matrix, vertical offset correction matrix, and horizontal offset correction matrix, respectively.

[0084] S7, multiply the vertical angle correction matrix, the horizontal angle correction matrix, and the current rotation matrix to obtain the corrected rotation matrix, multiply the vertical offset correction matrix, the horizontal offset correction matrix, and the current translation matrix to obtain the corrected translation matrix, and the corrected rotation matrix and the corrected translation matrix constitute the new surround view external calibration parameters.

[0085] When the vehicle is calibrated after production, initial vehicle parameter information is stored, including the vehicle's total height, axle load, and surround-view calibration parameters. These surround-view calibration parameters include internal and external parameters. Internal parameters refer to equipment parameters such as focal length, optical center, and lens distortion. External parameters are the rotation and translation matrices used to transform the camera coordinate system to the world coordinate system. In this embodiment, the calibration parameter correction refers to the correction of the rotation and translation matrices. Steps S1 and S2 calculate the camera's vertical correction value; steps S3-S5 calculate the camera's horizontal correction value and the vehicle's horizontal angle change; step S6 constructs a correction matrix based on the camera's vertical and horizontal correction values ​​and the vehicle's horizontal angle change; and step S7 updates the surround-view external calibration parameters based on the correction matrix. The following provides a detailed explanation of these steps.

[0086] (1) Camera vertical correction value

[0087] When a trailer is added or a heavy load is applied to the vehicle, the air suspension controller sends the collected airbag height information, as well as the first and second rear axle load information, to the main controller via the CAN bus. The main controller calculates the first front axle load after the heavy load is applied based on the first and second rear axle loads, thus obtaining the difference in the first front axle load before and after the load, and further obtaining the difference in the load of each axle before and after the load. The vertical offset of the vehicle is calculated based on the change in airbag height, and the vehicle pitch angle is calculated based on the difference in the load of each axle and the vertical offset.

[0088] Step 1: Calculate the vertical offset of the vehicle based on the height changes of the airbags on each axle, and then calculate the vertical offset of each camera based on the vertical offset of the vehicle.

[0089] Step 1.1: Obtain the height of each airbag on each axis in the current sampling period and the previous sampling period.

[0090] Step 1.2: Calculate the height change of each airbag using the following formula.

[0091] △H1=H1'-H1

[0092] △H2=H2'-H2

[0093] △H3=H3'-H3

[0094] Wherein, H1, H2, and H3 are the airbag heights of the front axis, first rear axis, and second rear axis in the previous sampling period, respectively; H1', ​​H2', and H3' are the airbag heights of the front axis, first rear axis, and second rear axis in the current sampling period, respectively; and ΔH1, ΔH2, and ΔH3 are the changes in airbag heights of the front axis, first rear axis, and second rear axis, respectively.

[0095] Step 1.3: Calculate the average value of △H1, △H2, and △H3 as the vertical offset of the vehicle.

[0096] Step 1.4: The vertical offset of the front camera is equal to the vertical offset of the vehicle; the vertical offset of the left and right cameras is equal to the vertical offset of the vehicle plus the front overhang length × tan (vertical pitch angle of the camera); the vertical offset of the rear camera is equal to the vertical offset of the vehicle plus the length of the front of the vehicle × tan (vertical pitch angle of the camera).

[0097] Specifically, the vertical offset of each axis is calculated using the airbag height data collected on the CAN bus. The first front axis height offset △H1, the first rear axis airbag height offset △H2, and the second rear axis airbag height offset △H3 are defined. The heights before loading are: first front axis H1, first rear axis H2, and second rear axis H3; after loading are: first front axis H1', ​​first rear axis H2', and second rear axis H3'. The height offsets of each axis are calculated using the formulas described above. The vertical pitch angle of the camera is calculated using step 2.

[0098] Step 2: Obtain the first and second rear axle loads of the vehicle, calculate the vehicle pitch angle based on the first and second rear axle loads, and determine the vertical pitch angle of each camera based on the vehicle pitch angle.

[0099] Step 2.1: Obtain the first rear axle weights M2 and m2 of the current sampling period and the previous sampling period, and calculate the first rear axle weight difference Δm2 = M2 - m2.

[0100] Step 2.2: Obtain the second rear axle weights M3 and m3 of the current sampling period and the previous sampling period, and calculate the second rear axle weight difference Δm3 = M3 - m3.

[0101] Step 2.3, calculate the front axle weight difference Δm1, including:

[0102] 1) When the vehicle drive configuration is 6×2 with rear lift, ;

[0103] 2) When the vehicle drive configuration is 6×2 (rear lift, front lift), ;

[0104] 3) When the vehicle drive configuration is 6×2 with a lift, ;

[0105] 4) When the vehicle drive configuration is 6×2 with lifting before lifting, ;

[0106] Where L is the distance from the vehicle's center of gravity to the middle of the two rear axles, L1 is the wheelbase of the main vehicle, and L2 is the distance between the first and second rear axles.

[0107] Step 2.4, calculate the vehicle pitch angle using the following formula. ,

[0108] .

[0109] Step 2.5: Determine the vertical pitch angle of each camera as the vehicle pitch angle. .

[0110] It should be noted that the calculation method for front axle weight after loading differs depending on the drive type. The specific calculation method described above should be selected according to the vehicle's drive type. In an optional implementation, the vertical attitude change of the vehicle is obtained based on the above calculations, and the vertical external calibration correction value is obtained. When the above changes are less than a preset threshold, the changes are not used as correction values; otherwise, the above values ​​are used as vertical correction values ​​for the external calibration parameters.

[0111] (2) Camera horizontal correction value

[0112] When a loaded vehicle is driving on the road, in addition to continuing to collect relevant information from the air suspension controller, the steering wheel controller sends the vehicle's yaw angle to the main controller via the CAN bus, and the EBS / ABS controller sends the vehicle's yaw angle and lateral acceleration to the main controller via the CAN bus. The yaw angle and yaw angle allow for the calculation of the vehicle's horizontal angular change. Simultaneously, the tire slip angle is calculated using the vehicle's lateral acceleration, tire pressure changes, and tire type, and the lateral offset of the vehicle is then calculated based on the tire slip angle.

[0113] Step 1: Calculate the slip angle of each tire based on the vehicle's lateral acceleration, and then calculate the horizontal offset angle of each camera based on the slip angle of each tire.

[0114] Step 1.1: Calculate the slip angle of each tire using the following formula. ,

[0115] ;

[0116] in, , .

[0117] In the formula, For vehicle load capacity, For the lateral acceleration of the vehicle, This refers to the tire pressure adjustment factor. For nominal lateral stiffness, , , The calibration coefficient is the experimental coefficient. This refers to the number of tires.

[0118] Step 1.2: The horizontal offset angle of the right-side camera is the average of the slip angles of all tires on the right side; the horizontal offset angle of the left-side camera is the average of the slip angles of all tires on the left side; the horizontal offset angles of the front and rear cameras are the average of the slip angles of all tires.

[0119] Tire slip angle is the angle between the tire's direction of motion and its actual rolling direction. The slip angle is typically calculated based on the tire's mechanical model and is mainly related to the following factors: vehicle load, tire pressure, tire type, and lateral force on the tire. First, vehicle load directly affects the tire's vertical load. The higher the vertical load, the larger the tire's contact patch, resulting in increased lateral stiffness. The formula for calculating the vertical load is as follows: Secondly, tire pressure P determines tire rigidity. Insufficient pressure reduces lateral stiffness, leading to a larger slip angle. The tire pressure adjustment coefficient Kp can be obtained through testing and calibrated to adjust the slip angle under different tire pressures. Furthermore, different tires have different lateral stiffnesses. .

[0120] The slip angle is related to the lateral force of the tire and satisfies the following relationship: ;in The tire slip angle is the product of the vehicle load and the vehicle's lateral acceleration, which can be obtained from the EBS / ABS sensor on the CAN bus. Therefore, the formula for calculating the tire slip angle is: Among them, lateral stiffness The calculation formula is: . for The load effect function is typically fitted using a quadratic function: .

[0121] Step 2: Calculate the left and right offset of each tire based on the side slip angle of each tire, and calculate the horizontal offset of each camera based on the left and right offset of each tire.

[0122] Step 2.1, calculate the left and right offset y of each tire using the following formula.

[0123] y = v × t × tan(δ);

[0124] In the formula, v is the vehicle speed and t is the vehicle travel time.

[0125] Lateral offset is mainly affected by the following factors: Side slip angle: the lateral angle caused by tire slippage; Vehicle speed: the higher the speed, the greater the offset; Travel time: the longer the travel time, the more significant the lateral offset.

[0126] Step 2.2: The horizontal offset of the right-side camera is the average of the left and right offsets of all the tires on the right side; the horizontal offset of the left-side camera is the average of the left and right offsets of all the tires on the left side; the horizontal offsets of the front and rear cameras are the average of the left and right offsets of all the tires.

[0127] Step 3: Calculate the change in the vehicle's horizontal angle based on the vehicle's yaw angle and yaw angle.

[0128] Specifically, the angular change of the vehicle in the horizontal direction is calculated using the following formula. :

[0129]

[0130] in, For the vehicle's yaw angle, This refers to the vehicle's yaw angle.

[0131] In an optional implementation, horizontal external calibration correction values ​​are obtained based on the vehicle's attitude changes in the horizontal direction calculated above. When each of the above changes is less than a preset threshold, the change is not used as a correction value; otherwise, the above values ​​are used as horizontal correction values ​​for the external calibration parameters.

[0132] (3) Update external calibration parameters

[0133] Set a threshold for the number of updates within a certain period and a threshold for the update time. After calculating the horizontal and vertical correction values ​​of the external calibration parameters, if the time since the last parameter update is greater than the update time threshold and the number of updates within a certain period is less than the set threshold for the number of updates within a certain period, then update the lookaround external calibration parameters.

[0134] The update method involves obtaining correction matrices by comparing the horizontal and vertical correction values ​​with the initial parameters. These correction matrices are then multiplied by the initial rotation and translation matrices to obtain correction matrix B'. The camera coordinates are then corrected based on these correction matrices. First, the vertical pitch angle and horizontal offset angle of each camera are multiplied by the vehicle's horizontal angle change, vertical offset, and horizontal offset to construct vertical angle correction matrices, horizontal angle correction matrices, vertical offset correction matrices, and horizontal offset correction matrices, respectively. Next, the vertical angle correction matrix, horizontal angle correction matrix, and current rotation matrix are multiplied to obtain the corrected rotation matrix. The vertical offset correction matrix, horizontal offset correction matrix, and current translation matrix are multiplied to obtain the corrected translation matrix. The corrected rotation matrix and corrected translation matrix constitute the new surround-view external calibration parameters.

[0135] Specifically, the surrounding external calibration parameter B consists of a 4×4 rotation matrix R and a 4×1 translation matrix t:

[0136] B = [R|t]

[0137] A correction matrix is ​​constructed based on the vertical pitch angle, vertical offset, horizontal offset angle (including the horizontal angle change β and tire slip angle) of each camera, and the horizontal offset. The vertical angle correction matrix is ​​as follows: The horizontal angle correction matrix is The vertical offset correction matrix is The horizontal offset correction matrix is All of the above matrices are 4×4 matrices. Multiply the angle correction matrix by the rotation matrix R to obtain the correction matrix R', and multiply the translation correction matrix by the translation matrix t to obtain the correction matrix t'. Based on R' and t', obtain the new correction matrix B', and then calculate the correction parameters for each camera based on B'.

[0138] (4) Manually calibrate recommended values

[0139] In an optional implementation, the recalculated surround-view external calibration parameters are categorized and stored in the main controller according to vehicle drive type, vehicle load, vertical pitch angle, vertical offset, horizontal offset angle, and horizontal offset, and recommended values ​​are calculated.

[0140] Step 1: Configure the weighting values ​​of each influencing factor, which includes vertical pitch angle, horizontal offset angle, vertical offset, and horizontal offset.

[0141] Specifically, weighted values ​​are set for four main influencing factors—vertical pitch angle, vertical offset, horizontal offset angle, and horizontal offset—based on different drive types and different loads.

[0142] Step 2: Calculate the recommended values ​​for each influencing factor using the following formula. ,

[0143]

[0144] in, The weighted values ​​of the influencing factors. These are the values ​​of the influencing factors for each statistical analysis. This represents the number of times the count has been recorded.

[0145] Step 3: Manually calibrate the recommendations based on the recommended values ​​for each influencing factor.

[0146] When the driver needs to perform manual calibration, recommended calibration points are displayed on the surround view system based on vehicle information to improve the accuracy of manual calibration.

[0147] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A truck surround view online calibration method, the vehicle comprising three axles, a front axle, a first rear axle and a second rear axle, a 360 surround view camera is arranged on the left, right, front and rear of the vehicle respectively, and initial surround view external calibration parameters are stored when the vehicle is calibrated offline, the initial surround view external calibration parameters comprising an initial rotation matrix and an initial translation matrix for transforming the camera coordinate system to the world coordinate system, characterized in that, The method includes the following steps: Obtain the height of the airbags on each axle of the vehicle, calculate the vertical offset of the vehicle based on the changes in the height of the airbags on each axle, and calculate the vertical offset of each camera based on the vertical offset of the vehicle. Obtain the first and second rear axle loads of the vehicle, calculate the vehicle pitch angle based on the first and second rear axle loads, and determine the vertical pitch angle of each camera based on the vehicle pitch angle. Obtain the vehicle's lateral acceleration, calculate the slip angle of each tire based on the vehicle's lateral acceleration, and calculate the horizontal offset angle of each camera based on the slip angle of each tire. Calculate the left and right offset of each tire based on the side slip angle of each tire, and calculate the horizontal offset of each camera based on the left and right offset of each tire. Obtain the vehicle's yaw angle and yaw angle, and calculate the change in the vehicle's horizontal angle based on the vehicle's yaw angle and yaw angle; The vertical pitch angle and horizontal offset angle of each camera are multiplied by the vehicle's horizontal angle change, vertical offset, and horizontal offset to construct the vertical angle correction matrix, horizontal angle correction matrix, vertical offset correction matrix, and horizontal offset correction matrix, respectively. Multiply the vertical angle correction matrix, horizontal angle correction matrix, and current rotation matrix to obtain the corrected rotation matrix; multiply the vertical offset correction matrix, horizontal offset correction matrix, and current translation matrix to obtain the corrected translation matrix; the corrected rotation matrix and corrected translation matrix constitute the new surround view external calibration parameters; Obtain the first and second rear axle loads of the vehicle, calculate the vehicle pitch angle based on the first and second rear axle loads, and determine the vertical pitch angle of each camera based on the vehicle pitch angle. Specifically, this includes: Obtain the first rear axle loads M2 and m2 of the current sampling period and the previous sampling period, and calculate the first rear axle load difference Δm2 = M2 - m2; Obtain the second rear axle loads M3 and m3 of the current sampling period and the previous sampling period, and calculate the second rear axle load difference Δm3 = M3 - m3; Calculate the front axle weight difference Δm1, including: (1) when the vehicle driving form is 6x2 after lifting the rear, ; (2) when the vehicle driving form is 6x2, the front is lifted after lifting, ; (3) when the vehicle drive form is 6x2 with lift lift rear, ; (4) when the vehicle drive form is 6x2 with lift lift front, ; Where L is the distance from the vehicle's center of gravity to the middle of the two rear axles, L1 is the wheelbase of the main vehicle, and L2 is the distance between the first and second rear axles. The vehicle pitch angle is calculated by the following equation , ； determining a vertical pitch angle of each camera as a vehicle pitch angle .

2. The surround view online calibration method for truck according to claim 1, characterized in that, The system obtains the height of the airbags on each axle of the vehicle, calculates the vertical offset of the vehicle based on the changes in the airbag heights on each axle, and then calculates the vertical offset of each camera based on the vertical offset. Specifically, this includes: Obtain the airbag height of each axis in the current sampling period and the previous sampling period; The height variation of each airbag on each axis is calculated using the following formula. △H1=H1'-H1 △H2=H2'-H2 △H3=H3'-H3 Where H1, H2, and H3 are the airbag heights of the front axis, the first rear axis, and the second rear axis in the previous sampling period, respectively; H1', ​​H2', and H3' are the airbag heights of the front axis, the first rear axis, and the second rear axis in the current sampling period, respectively; and △H1, △H2, and △H3 are the changes in airbag heights of the front axis, the first rear axis, and the second rear axis, respectively. Calculate the average of △H1, △H2, and △H3 as the vertical offset of the vehicle; The vertical offset of the front camera of the vehicle is the vertical offset of the vehicle. The vertical offset of the cameras on the left and right sides of the vehicle = the vertical offset of the vehicle + the front overhang length × tan (the vertical tilt angle of the camera). The vertical offset of the rear camera of the vehicle = the vertical offset of the vehicle + the length of the front of the vehicle × tan (vertical tilt angle of the camera).

3. The surround view online calibration method for truck according to claim 1, characterized in that, Obtain the vehicle's lateral acceleration, calculate the slip angle of each tire based on the lateral acceleration, and calculate the horizontal offset angle of each camera based on the slip angle of each tire. Specifically, this includes: The tire side slip angle of each tire is calculated by the following equation , ； wherein , ; wherein is the vehicle load, is the vehicle lateral acceleration, is the tire air pressure adjustment coefficient, is the nominal cornering stiffness, , , is the test calibration coefficient, is the number of tires; The horizontal offset angle of the camera on the right side of the vehicle is the average of the sideslip angles of each tire on the right side; The horizontal offset angle of the camera on the left side of the vehicle is the average of the sideslip angles of each tire on the left side; The horizontal offset angle of the front and rear cameras of the vehicle is the average of the slip angles of all tires.

4. The surround view online calibration method for truck according to claim 3, characterized in that, Calculate the lateral offset of each tire based on its side slip angle, and then calculate the horizontal offset of each camera based on the lateral offset of each tire. Specifically, this includes: The left and right offset y of each tire is calculated using the following formula. y = v × t × tan(δ); In the formula, v is the vehicle speed and t is the vehicle travel time; The horizontal offset of the camera on the right side of the vehicle is the average of the left and right offsets of each tire on the right side. The horizontal offset of the camera on the left side of the vehicle is the average of the left and right offsets of each tire on the left side. The horizontal offset of the front and rear cameras of the vehicle is the average of the left and right offsets of all tires.

5. The surround view online calibration method for truck according to claim 4, characterized in that, The angle change in the vehicle horizontal direction is calculated from the vehicle yaw angle and the vehicle roll angle, specifically including calculating the angle change in the vehicle horizontal direction by the following formula : wherein, is the vehicle yaw angle, is the vehicle roll angle.

6. The truck surround view online calibration method of any one of claims 1-5, wherein, The method also includes the following steps: When the vehicle vertical offset, vehicle pitch angle, tire slip angle, and tire lateral offset are less than the corresponding preset threshold, the corresponding changes will not be used as correction values ​​for the correction of the surround view external calibration parameters. After obtaining the vertical angle correction matrix, horizontal angle correction matrix, vertical offset correction matrix, and horizontal offset correction matrix, if the time since the last update of the calibration parameters is greater than the update time threshold, and the number of updates within a certain period is less than the update number threshold, then the external calibration parameters for the surrounding view are updated.

7. The surround view online calibration method for trucks according to any one of claims 1-5, wherein, The method also includes the following steps: Configure the weighted values ​​of each influencing factor, which includes vertical pitch angle, horizontal offset angle, vertical offset, and horizontal offset. The recommended value of each influencing factor is calculated by the following equation , wherein, a weighted value of the influencing factor, an influencing factor value for each statistics, a number of statistics; Manually calibrate the values ​​based on the recommended values ​​for each influencing factor.

8. A surround view online calibration apparatus for a truck, characterized by, The system includes a main controller, which is electrically connected to an air suspension controller, an EBS / ABS controller, and a steering wheel controller. The main controller obtains the airbag height of each axle of the vehicle from the air suspension controller, the vehicle yaw angle and lateral acceleration from the EBS / ABS controller, and the vehicle yaw angle from the steering wheel controller. The main controller executes the truck surround view online calibration method according to any one of claims 1-7 and feeds back the new surround view external calibration parameters to the surround view system.

9. A truck characterized in that It is equipped with the device as described in claim 8.

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