Vehicle yaw angle compensation calibration method, device, equipment and storage medium

Abstract

The present invention discloses a vehicle yaw angle compensation calibration method, device, equipment and storage medium, and belongs to the field of autonomous driving planning and control. The present invention performs static calibration of the yaw angle when the target vehicle is powered on and meets the first calibration condition to obtain a static calibration value; determines a single static calibration value according to the static calibration value, the offline calibration memory value and the second calibration condition; performs dynamic calibration of the yaw angle on the target vehicle when the target vehicle does not meet the first calibration condition but meets the third calibration condition to obtain a dynamic calibration value; determines a fusion calibration value according to the single static calibration value and the dynamic calibration value, and performs yaw angle compensation calibration of the target vehicle according to the fusion calibration value. In this way, the two methods of combining online dynamic calibration and offline static calibration for mutual verification are realized, which can adapt to more complex driving environments and solve the influence caused by temperature and sensor zero drift.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving planning and control, and in particular to a vehicle yaw angle compensation calibration method, device, equipment and storage medium. Background Art

[0002] As a key parameter for lateral control in autonomous driving, vehicle yaw rate can be used to plan the vehicle's trajectory, curvature, and speed in real time based on the vehicle's yaw rate during operation, ensuring centering control in various scenarios. Traditional yaw angle calibration only involves a single static sensor calibration when the vehicle rolls off the production line. However, after delivery to the user, irreversible stability errors can occur as mileage, driving environment, and driving conditions change. This can cause the autonomous vehicle's lateral control to become uncentered or even lead to a swerve. Therefore, adaptive yaw angle compensation tailored to the vehicle's driving state is a pressing technical challenge.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the present invention is to provide a vehicle yaw angle compensation calibration method, device, equipment and storage medium, aiming to solve the technical problem of how to perform adaptive yaw angle compensation according to the vehicle driving state in the prior art.

[0005] To achieve the above object, the present invention provides a vehicle yaw angle compensation calibration method, the vehicle yaw angle compensation calibration method comprising the following steps:

[0006] When the target vehicle is powered on and meets a first calibration condition, a yaw angle static calibration is performed to obtain a static calibration value;

[0007] determining a single static calibration value according to the static calibration value, the offline calibration memory value, and the second calibration condition;

[0008] When the target vehicle does not meet the first calibration condition but meets the third calibration condition, performing a yaw angle dynamic calibration on the target vehicle to obtain a dynamic calibration value;

[0009] A fusion calibration value is determined according to the single static calibration value and the dynamic calibration value, and yaw angle compensation calibration of the target vehicle is performed according to the fusion calibration value.

[0010] Optionally, performing static calibration of the yaw angle when the target vehicle is powered on and satisfies a first calibration condition to obtain a static calibration value includes:

[0011] Determining an operating state of the target vehicle after the target vehicle is powered on, and determining whether a first calibration condition is satisfied based on the operating state;

[0012] When the target vehicle meets a first calibration condition, a static calibration of the yaw angle of the target vehicle is performed to obtain a static calibration value.

[0013] Optionally, determining a single static calibration value according to the static calibration value, the offline calibration memory value, and the second calibration condition includes:

[0014] Obtaining an offline calibration memory value of the target vehicle;

[0015] Comparing the static calibration value with the offline calibration memory value to obtain a calibration difference;

[0016] A single static calibration value is determined based on the calibration difference and the second calibration condition.

[0017] Optionally, determining a single static calibration value according to the calibration difference and the second calibration condition includes:

[0018] comparing the calibration difference to a target error range for a second calibration condition;

[0019] When the comparison result shows that the calibration difference exceeds the target error range, determining that the comparison result does not meet the second calibration condition, prompting the user to perform manual calibration, and obtaining the manual calibration result as the single static calibration value;

[0020] When the comparison result shows that the calibration difference does not exceed the target error range, it is determined that the comparison result meets the second calibration condition, and the static calibration value is used as the single static calibration value.

[0021] Optionally, the performing dynamic calibration on the target vehicle to obtain a dynamic calibration value includes:

[0022] Acquiring yaw rate sensor data of the target vehicle traveling in a straight line;

[0023] Performing a histogram optimization on the yaw rate sensor data to obtain an optimal yaw angle value corresponding to each vehicle speed;

[0024] A dynamic calibration value is determined according to the optimal yaw angle value.

[0025] Optionally, performing histogram optimization on the yaw rate sensor data to obtain the optimal yaw angle value corresponding to each vehicle speed includes:

[0026] constructing a histogram based on the yaw rate sensor data;

[0027] Obtaining a corrected feedforward value of the yaw angle according to the histogram;

[0028] The corrected feedforward value is corrected according to the lane line lateral deviation and the steering wheel angle frequency to obtain an optimal yaw angle value.

[0029] Optionally, determining the fused calibration value according to the single static calibration value and the dynamic calibration value includes:

[0030] Get the fusion ratio and preset fusion algorithm;

[0031] A fusion calibration value is obtained by calculating the fusion ratio, the preset fusion algorithm, the single static calibration value, and the dynamic calibration value.

[0032] In addition, to achieve the above-mentioned purpose, the present invention further proposes a vehicle yaw angle compensation calibration device, the vehicle yaw angle compensation calibration device comprising:

[0033] A static calibration module, configured to perform static calibration of the yaw angle when the target vehicle is powered on and satisfies a first calibration condition, and obtain a static calibration value;

[0034] A static calibration value determination module, configured to determine a single static calibration value according to the static calibration value, an offline calibration memory value, and a second calibration condition;

[0035] a dynamic calibration module, configured to perform dynamic calibration of the yaw angle of the target vehicle to obtain a dynamic calibration value when the target vehicle does not meet the first calibration condition but meets the third calibration condition;

[0036] A fusion calibration module is used to determine a fusion calibration value according to the single static calibration value and the dynamic calibration value, and perform yaw angle compensation calibration of the target vehicle according to the fusion calibration value.

[0037] In addition, to achieve the above-mentioned purpose, the present invention also proposes a vehicle yaw angle compensation calibration device, which includes: a memory, a processor, and a vehicle yaw angle compensation calibration program stored on the memory and running on the processor, and the vehicle yaw angle compensation calibration program is configured to implement the vehicle yaw angle compensation calibration method described above.

[0038] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a vehicle yaw angle compensation calibration program is stored. When the vehicle yaw angle compensation calibration program is executed by a processor, the vehicle yaw angle compensation calibration method as described above is implemented.

[0039] The present invention performs static yaw angle calibration on a target vehicle when it is powered on and meets a first calibration condition, obtaining a static calibration value. A single static calibration value is determined based on the static calibration value, an offline calibration memory value, and a second calibration condition. When the target vehicle fails to meet the first calibration condition but meets a third calibration condition, dynamic yaw angle calibration is performed on the target vehicle to obtain a dynamic calibration value. A fused calibration value is determined based on the single static calibration value and the dynamic calibration value, and yaw angle compensation calibration of the target vehicle is performed based on the fused calibration value. This method achieves a combined verification between online dynamic calibration and offline static calibration, adapting to more complex driving environments and addressing the effects of temperature and sensor drift. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 Schematic diagram of the structure of a vehicle yaw angle compensation calibration device in a hardware operating environment according to an embodiment of the present invention;

[0041] Figure 2 This is a flow chart of a first embodiment of a vehicle yaw angle compensation calibration method according to the present invention;

[0042] Figure 3 Schematic diagram of a storage device in an embodiment of a vehicle yaw angle compensation calibration method of the present invention;

[0043] Figure 4 This is a flow chart of a second embodiment of a vehicle yaw angle compensation calibration method according to the present invention;

[0044] Figure 5 Schematic diagram of a histogram in an embodiment of a vehicle yaw angle compensation calibration method of the present invention;

[0045] Figure 6 This is a structural block diagram of the first embodiment of the vehicle yaw angle compensation calibration device of the present invention.

[0046] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0047] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0048] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a vehicle yaw angle compensation calibration device in the hardware operating environment involved in an embodiment of the present invention.

[0049] like Figure 1As shown, the vehicle yaw angle compensation calibration device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the user interface 1003 may optionally include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (RAM) memory, or a stable non-volatile memory (NVM), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0050] Those skilled in the art will understand that Figure 1 The structure shown in does not constitute a limitation on the vehicle yaw angle compensation calibration device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0051] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a vehicle yaw angle compensation calibration program.

[0052] exist Figure 1 In the vehicle yaw angle compensation calibration device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the vehicle yaw angle compensation calibration device of the present invention can be set in the vehicle yaw angle compensation calibration device, and the vehicle yaw angle compensation calibration device calls the vehicle yaw angle compensation calibration program stored in the memory 1005 through the processor 1001, and executes the vehicle yaw angle compensation calibration method provided by the embodiment of the present invention.

[0053] The embodiment of the present invention provides a vehicle yaw angle compensation calibration method, referring to Figure 2 , Figure 2 FIG1 is a flow chart of a first embodiment of a vehicle yaw angle compensation calibration method according to the present invention.

[0054] In this embodiment, the vehicle yaw angle compensation calibration method includes the following steps:

[0055] Step S10: When the target vehicle is powered on and satisfies a first calibration condition, a static calibration of the yaw angle is performed to obtain a static calibration value.

[0056] In this embodiment, the execution subject may be the vehicle yaw compensation calibration device, which has functions such as data processing, data communication, and program execution. The vehicle yaw compensation calibration device may be any intelligent terminal such as a computer or smartphone. Of course, other devices with similar functions may also be used, and this implementation condition does not impose any restrictions. For ease of explanation, this embodiment uses the vehicle yaw compensation calibration device as an example.

[0057] It should be noted that the vehicle's yaw rate, as a key parameter for lateral control in autonomous driving, can be used to plan the vehicle's driving trajectory, driving curvature, and driving speed in real time based on the vehicle's yaw rate during operation, meeting the vehicle's centering control requirements in different scenarios. Traditional yaw angle calibration only performs a static sensor calibration once when the vehicle rolls off the production line. However, after delivery to the user, irreversible stability errors will occur as information such as mileage, driving environment, and driving conditions change, resulting in problems such as the autonomous vehicle's lateral control being out of center or the vehicle being in a dragon shape. Therefore, how to adaptively compensate for the yaw angle based on the vehicle's driving state is a technical problem that urgently needs to be solved. The solution of this embodiment can not only reduce the calibration accuracy requirements for the sensor when the vehicle rolls off the production line, but also compensate for the sensor zero drift error caused by the driving environment through online self-learning, solving the problem of unqualified yaw angle (Yawrate) off-line calibration accuracy and yaw angle zero drift in long-mileage vehicles.

[0058] It should be understood that the first calibration condition refers to the vehicle being stationary, all four doors and hood closed, and the steering wheel angle velocity being zero. Once the target vehicle is powered on and meets the first calibration condition, static yaw angle calibration is performed, and the resulting calibration value is used as the static calibration value.

[0059] Furthermore, in order to accurately determine whether the first verification condition is met, step S10 includes: determining the working status of the target vehicle after the target vehicle is powered on, and determining whether the first calibration condition is met based on the working status; when the target vehicle meets the first calibration condition, performing static calibration of the yaw angle of the target vehicle to obtain a static calibration value.

[0060] It should be noted that the working state includes the vehicle speed, the state of the doors, the state of the hood and the trunk, and the steering wheel angular velocity, so that the first calibration condition can be determined.

[0061] Step S20: determining a single static calibration value according to the static calibration value, the offline calibration memory value and the second calibration condition.

[0062] It should be understood that after the static calibration value is determined, the static calibration value is compared with the offline calibration memory value to determine a single static calibration value.

[0063] Furthermore, in order to determine a single static calibration value, step S20 includes: obtaining an off-line calibration memory value of the target vehicle; comparing the static calibration value with the off-line calibration memory value to obtain a calibration difference; and determining a single static calibration value based on the calibration difference and a second calibration condition.

[0064] In a specific implementation, the static calibration value is compared with the vehicle production line calibration memory value to obtain a calibration difference, and then the value of the single static calibration value is determined according to the value range of the calibration difference.

[0065] Furthermore, in order to determine a single static calibration value, the step of determining a single static calibration value based on the calibration difference includes: comparing the calibration difference with a target error range of a second calibration condition; when the comparison result is that the calibration difference exceeds the target error range, determining that the comparison result does not meet the second calibration condition, prompting the user to perform manual calibration, and obtaining the manual calibration result as a single static calibration value; when the comparison result is that the calibration difference does not exceed the target error range, determining that the comparison result meets the second calibration condition, and using the static calibration value as the single static calibration value.

[0066] It should be noted that the target error range in the second calibration condition is less than 0.4deg / s. If the comparison result shows that the calibration difference does not exceed the target error range, calibration value 1 is recorded as the single static calibration value for yaw angle compensation. If the comparison result shows that the calibration difference exceeds the target error range, the user is prompted to perform manual calibration (the central control screen's intelligent driving menu page has an online calibration button, which can prompt the user to calibrate or the user can actively perform calibration). The value after the user's manual calibration directly updates the offline calibration memory value and is stored as the new calibration value. The updated offline calibration memory value is then used as the single static calibration value.

[0067] It should be understood that the user manual calibration method: the vehicle is on a flat road, with all four doors and two hoods closed, the four tire pressure errors are less than 0.1 bar, and there are no passengers other than the driver. After the conditions are met, the driver manually clicks to start calibration. After the vehicle is stationary for 10 seconds, the steering wheel is released and the vehicle accelerates steadily to 5m / s in a straight line, then decelerates steadily to a standstill in a straight line. The driver is required to perform a total of three calibrations on a flat road. The average of the three calibration errors is taken as the manual calibration value and recorded in Map_Calibration.

[0068] In the specific implementation, the static calibration method is as follows: within 6 seconds after the vehicle is unlocked and powered on, the original Yawrate sensor value of the vehicle in the static state is recorded. After filtering, the average Yawrate value is taken as the calibration value 1 and recorded in V_standstill.

[0069] Step S30: When the target vehicle does not meet the first calibration condition but meets the third calibration condition, a yaw angle dynamic calibration is performed on the target vehicle to obtain a dynamic calibration value.

[0070] It should be noted that the third calibration condition is that the vehicle speed is >15km / h, the vehicle is driving in a straight line, the steering wheel angle change is <0.2deg, and the slope is less than 3°.

[0071] It should be understood that when it is determined that the target vehicle does not satisfy the first calibration condition but satisfies the third calibration condition, a yaw angle dynamic calibration is performed on the target vehicle.

[0072] Step S40: determining a fusion calibration value according to the single static calibration value and the dynamic calibration value, and performing yaw angle compensation calibration of the target vehicle according to the fusion calibration value.

[0073] It should be noted that after determining the single static calibration value and the dynamic calibration value, the two calibration values ​​need to be fused to obtain a fused calibration value, so as to achieve accurate compensation calibration of the vehicle yaw angle.

[0074] In a specific implementation, if the third calibration condition is not satisfied, the single static calibration value is directly taken as the calibration value for the final compensation calibration of the yaw angle of the target vehicle.

[0075] Furthermore, in order to accurately obtain the fusion calibration value, step S40 includes: obtaining a fusion ratio and a preset fusion algorithm; and calculating the fusion calibration value according to the fusion ratio, the preset fusion algorithm, the single static calibration value, and the dynamic calibration value.

[0076] It should be understood that the dynamic calibration value Map_Spd is fused with the single static calibration value V_standstill. The fusion method fuses the static result and the dynamic calibration value in proportion based on the vehicle speed. At different vehicle speeds, the fused calibration value = Map_Spd*X+V_standstill*Y, where V_standstill is the calibration value during static calibration, and Map_Spd is a correction value obtained by looking up the following Table 1 at different speeds. X and Y respectively represent reference proportions of the fused calibration related to speed.

[0077] Table 1

[0078]

[0079] It should be understood that if Figure 3 As shown, the solution of this embodiment also includes a storage device, which includes data storage, data updating, and data reading. The data calibration program is calculated by the SOC module. The stored value is located in a fixed memory area in the SOC module. The memory value in the fixed memory area is read after initial power-up. When the vehicle is locked and powered off, the learning value of the current cycle is stored in the fixed memory area to update the memory value of the previous cycle. At the same time, other MCU modules can read the memory value in the SOC module through the communication protocol for use. The stored value X = {Map_Spd, V_standstill, Map_Calibration}, where Map_Spd represents the yaw angle compensation value corrected according to speed, V_standstill represents the static calibration result, and Map_Calibration represents the offline calibration value or manual calibration value.

[0080] This embodiment performs static yaw angle calibration on the target vehicle when it is powered on and meets a first calibration condition, obtaining a static calibration value. A single static calibration value is determined based on the static calibration value, the offline calibration memory value, and the second calibration condition. When the target vehicle does not meet the first calibration condition but meets a third calibration condition, dynamic yaw angle calibration is performed on the target vehicle to obtain a dynamic calibration value. A fused calibration value is determined based on the single static calibration value and the dynamic calibration value, and yaw angle compensation calibration of the target vehicle is performed based on the fused calibration value. This method achieves a combined verification between online dynamic calibration and offline static calibration, adapting to more complex driving environments and addressing the effects of temperature and sensor drift.

[0081] refer to Figure 4 , Figure 4 FIG2 is a flow chart of a second embodiment of a vehicle yaw angle compensation calibration method according to the present invention.

[0082] Based on the first embodiment described above, the vehicle yaw angle compensation calibration method of this embodiment includes, in step S30:

[0083] Step S301: Acquire yaw rate sensor data of the target vehicle traveling in a straight line.

[0084] It should be noted that dynamic optimization is to use closed-loop correction to find the optimal sensor offset value based on the sensor detection value when the vehicle is moving in a straight line. First, the Yawrate value output by the sensor at different driving speeds is statistically analyzed to search for the optimal offset value at different speeds.

[0085] Step S302: performing histogram optimization on the yaw rate sensor data to obtain the optimal yaw angle value corresponding to each vehicle speed.

[0086] It should be understood that the histogram optimization method is mainly to use the mean value and standard deviation method of the histogram to determine, and then the optimal yaw angle corresponding to different vehicle speeds can be obtained.

[0087] Furthermore, in order to accurately determine the optimal yaw angle value, step S302 includes: constructing a histogram based on the yaw rate sensor data; obtaining a corrected feedforward value of the yaw angle based on the histogram; and correcting the corrected feedforward value based on the lateral deviation of the lane line and the steering wheel angle frequency to obtain the optimal yaw angle value.

[0088] In the specific implementation, the mean value and standard deviation method of the histogram is used to determine the value. The schematic diagram of the histogram is as follows: Figure 5 This value is used as the feedforward value for yaw angle correction. Secondly, if the feedforward-compensated value used in the lateral control algorithm causes the vehicle to be off-center or drifting within the lane, feedback correction is performed using the lane line lateral deviation and steering wheel angle frequency during straight driving. The optimal yaw angle value when the vehicle is centered after correction is recorded. Finally, the offset adaptive compensation data for all straight driving conditions is recorded. Dynamic calibration values ​​are output based on different driving speed ranges and recorded in the Map_Spd table. The default compensation value is 0 and can be updated based on later dynamic learning values.

[0089] It should be noted that the criteria for straight-line driving are: vehicle steering wheel angle < 0.2 degrees, angle change rate < 0.5 degrees / s, lane curvature < 0.01 degrees, curvature change rate < 0.00001 degrees, and vehicle lateral acceleration < 0.05. The criteria for centered driving are: vehicle guide line lateral deviation < ±10 cm, steering wheel angle < 0.1 degrees, and angle change rate < 0.3 degrees / s.

[0090] It should be understood that due to the sensor's location within the vehicle's steering wheel airbag, significant temperature fluctuations only occur during the initial static calibration upon power-up. During driving, the air conditioning maintains a relatively static temperature. Therefore, temperature correction is only used during static calibration; dynamic calibration does not incorporate temperature correction. The Map_Calibration offline calibration temperature is 26°C, with a default value of 0. Later, static calibration values ​​at different temperatures are recorded and updated when the vehicle is unlocked and powered up, and during manual calibration by the user.

[0091] Step S303: determining a dynamic calibration value according to the optimal yaw angle value.

[0092] In the specific implementation, the optimal yaw angle value when the vehicle is centered after correction is recorded; finally, the adaptive compensation data of the offset on all straight roads during driving is recorded, and the dynamic calibration value is output according to different driving speed segments and recorded in the Map_Spd table. The default compensation value is 0, which can be updated according to the later dynamic learning value to obtain the dynamic calibration value.

[0093] This embodiment obtains yaw rate sensor data from the target vehicle traveling in a straight line; performs a histogram optimization on this yaw rate sensor data to determine the optimal yaw angle value for each vehicle speed; and determines a dynamic calibration value based on this optimal yaw angle value. This approach utilizes high-precision detection units with online self-learning compensation to avoid redundancy, effectively reducing costs.

[0094] In addition, an embodiment of the present invention further proposes a storage medium, on which a vehicle yaw angle compensation calibration program is stored. When the vehicle yaw angle compensation calibration program is executed by a processor, the steps of the vehicle yaw angle compensation calibration method described above are implemented.

[0095] Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0096] Reference Figure 6 , Figure 6 This is a structural block diagram of the first embodiment of the vehicle yaw angle compensation calibration device of the present invention.

[0097] like Figure 6 As shown, the vehicle yaw angle compensation calibration device proposed in the embodiment of the present invention includes:

[0098] The static calibration module 10 is configured to perform static calibration of the yaw angle when the target vehicle is powered on and satisfies a first calibration condition, and obtain a static calibration value.

[0099] The static calibration value determination module 20 is configured to determine a single static calibration value according to the static calibration value, the offline calibration memory value and the second calibration condition.

[0100] The dynamic calibration module 30 is configured to perform dynamic calibration of the yaw angle of the target vehicle to obtain a dynamic calibration value when the target vehicle does not meet the first calibration condition but meets the third calibration condition.

[0101] The fusion calibration module 40 is configured to determine a fusion calibration value according to the single static calibration value and the dynamic calibration value, and perform yaw angle compensation calibration of the target vehicle according to the fusion calibration value.

[0102] This embodiment performs static yaw angle calibration on the target vehicle when it is powered on and meets the first calibration condition, obtaining a static calibration value. A single static calibration value is determined based on the static calibration value, the offline calibration memory value, and the second calibration condition. If the target vehicle does not meet the first calibration condition but meets the third calibration condition, dynamic yaw angle calibration is performed on the target vehicle to obtain a dynamic calibration value. A fused calibration value is determined based on the single static calibration value and the dynamic calibration value, and yaw angle compensation calibration of the target vehicle is performed based on the fused calibration value. This method combines online dynamic calibration with offline static calibration for mutual verification, adapting to more complex driving environments and addressing the effects of temperature and sensor drift.

[0103] In one embodiment, the static calibration module 10 is further used to determine the operating status of the target vehicle after the target vehicle is powered on, and determine whether a first calibration condition is met based on the operating status; when the target vehicle meets the first calibration condition, static calibration of the yaw angle of the target vehicle is performed to obtain a static calibration value.

[0104] In one embodiment, the static calibration value determination module 20 is further used to obtain the offline calibration memory value of the target vehicle; compare the static calibration value with the offline calibration memory value to obtain a calibration difference; and determine a single static calibration value based on the calibration difference and a second calibration condition.

[0105] In one embodiment, the static calibration value determination module 20 is further used to compare the calibration difference with the target error range of the second calibration condition; when the comparison result is that the calibration difference exceeds the target error range, it is determined that the comparison result does not meet the second calibration condition, the user is prompted to perform manual calibration, and the manual calibration result is obtained as a single static calibration value; when the comparison result is that the calibration difference does not exceed the target error range, it is determined that the comparison result meets the second calibration condition, and the static calibration value is used as the single static calibration value.

[0106] In one embodiment, the dynamic calibration module 30 is further configured to obtain yaw rate sensor data of the target vehicle traveling in a straight line; perform histogram optimization on the yaw rate sensor data to obtain optimal yaw angle values ​​corresponding to various vehicle speeds; and determine a dynamic calibration value based on the optimal yaw angle values.

[0107] In one embodiment, the dynamic calibration module 30 is further configured to construct a histogram based on the yaw rate sensor data; obtain a corrected feedforward value of the yaw angle based on the histogram; and correct the corrected feedforward value based on the lateral deviation of the lane line and the steering wheel angle frequency to obtain an optimal yaw angle value.

[0108] In one embodiment, the fusion calibration module 40 is further configured to obtain a fusion ratio and a preset fusion algorithm; and calculate a fusion calibration value based on the fusion ratio, the preset fusion algorithm, the single static calibration value, and the dynamic calibration value.

[0109] It should be understood that the above is only an example and does not constitute any limitation to the technical solution of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any limitation on this.

[0110] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of it according to actual needs to achieve the purpose of the embodiment scheme, and no limitation is made here.

[0111] In addition, for technical details not fully described in this embodiment, reference can be made to the vehicle yaw angle compensation calibration method provided in any embodiment of the present invention, and will not be repeated here.

[0112] In addition, it should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0113] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0114] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, or of course by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0115] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A vehicle yaw angle compensation calibration method, characterized in that: The vehicle yaw angle compensation calibration method comprises: When the target vehicle is powered on and meets a first calibration condition, a yaw angle static calibration is performed to obtain a static calibration value, wherein the first calibration condition refers to that the vehicle is stationary, the doors, the front hood and the rear hood are not opened, and the steering wheel angle speed is zero; Determine a single static calibration value according to the static calibration value, the offline calibration memory value and the second calibration condition, wherein the second calibration condition is that the calibration difference obtained by comparing the static calibration value with the offline calibration memory value does not exceed a target error range, wherein the target error range is an interval range of less than 0.4 deg / s; Determining a single static calibration value according to the static calibration value, the offline calibration memory value and the second calibration condition comprises: Obtaining an off-line calibration memory value of the target vehicle; Comparing the static calibration value with the offline calibration memory value to obtain a calibration difference; comparing the calibration difference to a target error range for a second calibration condition; When the comparison result shows that the calibration difference exceeds the target error range, it is determined that the comparison result does not meet the second calibration condition, the user is prompted to perform manual calibration, and the manual calibration result is obtained as a single static calibration value; When the comparison result shows that the calibration difference does not exceed the target error range, it is determined that the comparison result satisfies the second calibration condition, and the static calibration value is used as a single static calibration value; When the target vehicle does not meet the first calibration condition but meets the third calibration condition, obtaining the yaw rate sensor data of the target vehicle traveling in a straight line, wherein the third calibration condition is that the vehicle speed is greater than 15 km / h, the vehicle is traveling in a straight line and the steering wheel angle change is less than 0.2 degrees, and the slope is less than 3; constructing a histogram according to the yaw rate sensor data; Obtaining a corrected feedforward value of the yaw angle according to the histogram; The corrected feedforward value is corrected according to the lane line lateral deviation and the steering wheel angle frequency to obtain an optimal yaw angle value; determining a dynamic calibration value according to the optimal yaw angle value; A fusion calibration value is determined according to the single static calibration value and the dynamic calibration value, and a yaw angle compensation calibration of the target vehicle is performed according to the fusion calibration value.

2. The vehicle yaw angle compensation calibration method according to claim 1, characterized in that: The step of performing static calibration of the yaw angle when the target vehicle is powered on and satisfies the first calibration condition to obtain a static calibration value includes: Determining an operating state of the target vehicle after the target vehicle is powered on, and determining whether a first calibration condition is satisfied according to the operating state; When the target vehicle meets the first calibration condition, a static calibration of the yaw angle of the target vehicle is performed to obtain a static calibration value.

3. The vehicle yaw angle compensation calibration method according to claim 1, characterized in that: The determining of the fused calibration value according to the single static calibration value and the dynamic calibration value comprises: Get the fusion ratio and preset fusion algorithm; A fusion calibration value is calculated according to the fusion ratio, the preset fusion algorithm, the single static calibration value and the dynamic calibration value.

4. A vehicle yaw angle compensation calibration device, characterized in that: The vehicle yaw angle compensation calibration device comprises: A static calibration module, configured to perform static calibration of the yaw angle when the target vehicle is powered on and satisfies a first calibration condition to obtain a static calibration value, wherein the first calibration condition refers to that the vehicle is stationary, the doors, the front hood and the rear hood are not opened, and the steering wheel angle speed is zero; a static calibration value determination module, configured to determine a single static calibration value according to the static calibration value, an offline calibration memory value, and a second calibration condition, wherein the second calibration condition is that a calibration difference obtained by comparing the static calibration value with the offline calibration memory value does not exceed a target error range, wherein the target error range is an interval range of less than 0.4 deg / s; The static calibration value determination module is further used to obtain the offline calibration memory value of the target vehicle; compare the static calibration value with the offline calibration memory value to obtain a calibration difference; compare the calibration difference with a target error range of a second calibration condition; when the comparison result is that the calibration difference exceeds the target error range, determine that the comparison result does not meet the second calibration condition, prompt the user to perform manual calibration, and obtain the manual calibration result as a single static calibration value; when the comparison result is that the calibration difference does not exceed the target error range, determine that the comparison result meets the second calibration condition, and use the static calibration value as a single static calibration value; A dynamic calibration module is used to obtain yaw rate sensor data of the target vehicle traveling in a straight line when the target vehicle does not meet the first calibration condition but meets the third calibration condition, wherein the third calibration condition is that the vehicle speed is greater than 15 km / h, the vehicle is traveling in a straight line and the steering wheel angle change is less than 0.2 deg, and the slope is less than 3; construct a histogram according to the yaw rate sensor data; obtain a corrected feedforward value of the yaw angle according to the histogram; correct the corrected feedforward value according to the lane line lateral deviation and the steering wheel angle frequency to obtain an optimal yaw angle value; and determine a dynamic calibration value according to the optimal yaw angle value; A fusion calibration module is used to determine a fusion calibration value according to the single static calibration value and the dynamic calibration value, and perform yaw angle compensation calibration of the target vehicle according to the fusion calibration value.

5. A vehicle yaw angle compensation calibration device, characterized in that: The vehicle yaw angle compensation calibration device includes: a memory, a processor, and a vehicle yaw angle compensation calibration program stored in the memory and running on the processor, wherein the vehicle yaw angle compensation calibration program is configured to implement the vehicle yaw angle compensation calibration method as described in any one of claims 1 to 3.

6. A storage medium, characterized in that: The storage medium stores a vehicle yaw angle compensation calibration program, and when the vehicle yaw angle compensation calibration program is executed by the processor, the vehicle yaw angle compensation calibration method according to any one of claims 1 to 3 is implemented.

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