Yaw angular velocity correction method, device, vehicle, equipment and medium

Abstract

The present invention provides a yaw rate correction method, apparatus, vehicle, device, and medium. These methods improve yaw rate correction accuracy without increasing hardware or communication costs, thereby better meeting the accuracy requirements of the vehicle's autonomous driving system for the input yaw rate. The yaw rate correction method includes: obtaining the vehicle's steering wheel angle, vehicle speed, and the actual yaw rate output during the current sampling period; predicting the upper and lower limits of the yaw rate change rate in real time based on the vehicle's steering wheel angle and speed; and correcting the actual yaw rate based on the upper and lower limits.

Description

Technical Field

[0001] The present invention relates to the field of vehicle driving parameter control, and in particular to a yaw rate correction method, device, vehicle, equipment and medium. Background Art

[0002] In vehicle dynamics control, the vehicle's heading, sideslip, and yaw angles are fundamental attitude parameters, and their accuracy is crucial for establishing various vehicle dynamics models. In ADAS systems, the vehicle's yaw rate serves as a fundamental attitude parameter input, enabling functions such as environmental perception, vehicle positioning, trajectory prediction for the vehicle and surrounding vehicles, behavioral decision-making, motion planning, and motion control. Yaw rate is fundamental to the implementation of automated parking, AEB, FCW, and LDW in autonomous driving, and its accuracy significantly impacts the safety of these functions.

[0003] The solution, published with publication number CN102621570A, features a vehicle dynamics parameter correction method based on dual global positioning and inertial correction. It discloses a yaw angle correction and optimization method. By installing two global positioning modules and an inertial correction module on the vehicle body, these modules jointly correct the vehicle's sideslip angle β, the lateral acceleration ay1 caused by steering, the yaw angle ψ, the roll angle, the lateral acceleration ay1 at the center of mass of the vehicle, the longitudinal acceleration aX at the center of mass, the yaw angular velocity r at the center of mass, and the roll angular velocity p at the center of mass. Combining the IMU with GPS for correction leverages GPS's all-weather, error-free, and rapid attitude measurement capabilities. The GPS signal simultaneously provides real-time feedback to the IMU, continuously correcting IMU-calibrated drift. This method increases the GPS system's accuracy in correcting vehicle yaw angles, but requires high system hardware and communication costs.

[0004] The YawRate (Chinese: yaw angular velocity) of L2 autonomous driving models basically comes from the ESP system, and the ESP system calculates YAWRATE based on the vehicle's lateral acceleration (ay). When the vehicle encounters road impacts, such as speed bumps, manhole covers, potholes and other abnormal road conditions, the lateral acceleration ay provided by the acceleration sensor in the ESP system will be mismeasured, resulting in a very large deviation in the YAWARTE calculated by the ESP system. Figure 5 Point A indicates a sudden spike in yawrate. The autonomous vehicle's ADAS controller responds by violently steering the steering wheel in reverse, causing the yawrate to oscillate back to point B. The autonomous vehicle then responds violently to point C, causing the steering control to become unstable and oscillate, leading to passenger complaints. Summary of the Invention

[0005] The present invention provides a yaw rate correction method, device, vehicle, equipment and medium, which improve the yaw rate correction accuracy without increasing hardware or communication costs, thereby better meeting the vehicle automatic driving system's requirements for the accuracy of the input vehicle yaw rate.

[0006] The technical solution of the present invention is:

[0007] The present invention provides a yaw angular velocity correction method, comprising:

[0008] Obtain the vehicle's steering wheel angle, vehicle speed, and actual yaw rate output during the current sampling period;

[0009] According to the vehicle's steering wheel angle and speed, the upper and lower limits of the yaw rate change rate are predicted in real time;

[0010] The actual yaw rate is corrected based on the yaw rate change rate upper limit and the yaw rate change rate lower limit.

[0011] Preferably, the step of predicting the upper limit value and the lower limit value of the yaw rate change rate in real time based on the steering wheel angle and the vehicle speed includes:

[0012] Inputting the vehicle's steering wheel angle and vehicle speed into a pre-established yaw rate change rate theoretical value model to obtain a yaw rate change rate theoretical value;

[0013] Inputting the theoretical values ​​of the yaw rate change rate into the pre-established yaw rate change rate upper limit value model respectively to obtain the yaw rate change rate upper limit value;

[0014] The yaw rate change rate theoretical values ​​are input into the pre-established yaw rate change rate lower limit value model to obtain the yaw rate change rate lower limit value.

[0015] Preferably, the step of inputting the theoretical values ​​of the yaw rate change rate into a pre-established yaw rate change rate upper limit value model to obtain the yaw rate change rate upper limit value comprises:

[0016] The product of the theoretical value of the yaw rate change rate and the first correction coefficient is determined as the upper limit value of the yaw rate change rate;

[0017] The value of the first correction coefficient is negatively correlated with the road curvature C and the vehicle speed V.

[0018] Preferably, the step of inputting the theoretical values ​​of the yaw rate change rate into a pre-established yaw rate change rate lower limit model to obtain the yaw rate change rate lower limit includes:

[0019] The product of the theoretical value of the yaw rate change rate and the second correction coefficient is determined as the lower limit value of the yaw rate change rate;

[0020] The value of the second correction coefficient is negatively correlated with the road curvature C and the vehicle speed V, and the second correction coefficient is smaller than the first correction coefficient.

[0021] Preferably, the step of correcting the actual yaw rate according to the yaw rate change rate upper limit and the yaw rate change rate lower limit includes:

[0022] determining an actual yaw rate change rate according to the actual yaw rate;

[0023] The actual yaw rate is corrected based on the relative magnitude relationship between the yaw rate change rate upper limit value, the yaw rate change rate lower limit value and the actual yaw rate change rate.

[0024] Preferably, the step of correcting the actual yaw rate according to the relative magnitude relationship between the yaw rate change rate upper limit value, the yaw rate change rate lower limit value and the actual yaw rate change rate includes:

[0025] If the actual yaw rate change rate is greater than the yaw rate change rate upper limit, the actual yaw rate is corrected according to the actual yaw rate output in the previous sampling period and the yaw rate change rate upper limit;

[0026] If the actual yaw rate change rate is less than the upper limit of the yaw rate change rate, the actual yaw rate is corrected according to the actual yaw rate output in the previous sampling period and the lower limit of the yaw rate change rate;

[0027] If the yaw rate change rate lower limit ≤ the actual yaw rate change rate ≤ the yaw rate change rate upper limit, the actual yaw rate output in the current sampling period is directly used as the corrected actual yaw rate.

[0028] Preferably, the step of correcting the actual yaw rate according to the actual yaw rate and the upper limit of the yaw rate change rate output in the previous sampling period includes:

[0029] First, multiply the upper limit of the yaw rate change rate by the length of a sampling period, and then add the resulting product to the actual yaw rate output in the previous sampling period to obtain the corrected actual yaw rate.

[0030] Preferably, the step of correcting the actual yaw rate according to the actual yaw rate and the lower limit of the yaw rate change rate output in the previous sampling period includes:

[0031] First, multiply the lower limit of the yaw rate change rate by the length of a sampling period, and then add the resulting product to the actual yaw rate output in the previous sampling period to obtain the corrected actual yaw rate.

[0032] Preferably, the acquired actual yaw angular velocity is output by the vehicle's electronic stability system ESP or inertial measurement unit IMU.

[0033] Preferably, the acquired steering wheel angle of the vehicle is an actually measured real-time steering wheel angle or a predicted steering wheel angle predicted by a predetermined steering wheel angle prediction model;

[0034] The acquired vehicle speed is the actual measured real-time vehicle speed or the predicted vehicle speed predicted by a predetermined vehicle speed prediction model.

[0035] The present invention also provides a yaw angular velocity correction device, comprising:

[0036] The vehicle parameter acquisition module is used to obtain the vehicle's steering wheel angle, vehicle speed, and actual yaw rate output in the current sampling period;

[0037] A yaw rate change rate upper and lower limit prediction module is used to predict the yaw rate change rate upper limit and the yaw rate change rate lower limit in real time based on the vehicle's steering wheel angle and vehicle speed;

[0038] The actual yaw rate correction module is used to correct the actual yaw rate according to the yaw rate change rate upper limit value and the yaw rate change rate lower limit value.

[0039] Preferably, the yaw rate change rate upper and lower limit prediction module includes:

[0040] a yaw rate change rate theoretical value prediction unit, configured to input the vehicle's steering wheel angle and vehicle speed into a pre-established yaw rate change rate theoretical value model to obtain a yaw rate change rate theoretical value;

[0041] a yaw rate change rate upper limit value prediction unit, configured to input the yaw rate change rate theoretical values ​​into a pre-established yaw rate change rate upper limit value model to obtain the yaw rate change rate upper limit value;

[0042] The yaw rate change rate lower limit value prediction unit is used to input the yaw rate change rate theoretical values ​​into the pre-established yaw rate change rate lower limit value model to obtain the yaw rate change rate lower limit value.

[0043] Preferably, the actual yaw rate correction module includes:

[0044] an actual yaw rate change rate determining unit, configured to determine an actual yaw rate change rate according to the actual yaw rate;

[0045] The actual yaw rate correction unit is used to correct the actual yaw rate according to the relative magnitude relationship between the yaw rate change rate upper limit value, the yaw rate change rate lower limit value and the actual yaw rate change rate.

[0046] Preferably, the actual yaw rate correction unit includes:

[0047] a first actual yaw rate correction subunit, configured to correct the actual yaw rate according to the actual yaw rate output in the previous sampling period and the yaw rate change upper limit value if the actual yaw rate change rate is greater than the yaw rate change upper limit value;

[0048] a second actual yaw rate correction subunit, configured to correct the actual yaw rate according to the actual yaw rate output in the previous sampling period and the yaw rate change lower limit value if the actual yaw rate change rate is less than the yaw rate change upper limit value;

[0049] The third actual yaw rate correction subunit is configured to directly use the actual yaw rate output in the current sampling period as the corrected actual yaw rate if the yaw rate change rate lower limit is ≤ the actual yaw rate change rate ≤ the yaw rate change rate upper limit.

[0050] The present invention also provides a vehicle comprising the above-mentioned yaw angular velocity correction device.

[0051] The present invention also provides a control device, including a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the yaw angular velocity correction method as described above.

[0052] The present invention also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the yaw angular velocity correction method as described above are implemented.

[0053] The beneficial effects of the present invention are:

[0054] 1) By constructing a theoretical value model of the yaw rate change rate affected by the steering system, the influence of errors from specific sensors (such as accelerometers) on the yaw rate measurement is eliminated. A yaw rate filtering process is constructed by combining the yaw rate determined by the vehicle's own parameters with road condition parameter calibration. This allows for real-time filtering of the yaw rate measured by the ESP system or IMU, thus avoiding large errors caused by the ESP system's accelerometers under specific road conditions.

[0055] 2) This method can automatically adjust the yaw rate YawRate measured in the current state. The filtering process responds promptly and automatically adapts to the current road conditions, avoiding the parameter solidification and time delay problems of ordinary filters, and avoiding erroneous operations of the autonomous driving system triggered by time delay.

[0056] 3) During the dynamic determination of the upper and lower limits for the yaw rate change, redundancy is incorporated into the normal effects of normal road conditions, such as cornering, drainage, road construction, road subsidence, and slippery roads, on the measured yaw rate. Only the effects of abnormal road conditions on the yaw rate YawRate are filtered out, enhancing the robustness of the filtering system.

[0057] 4) This method does not require high computing power and can run in real time on an MCU with a high functional safety level, meeting the high functional safety requirements of intelligent driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 Schematic diagram of the flow of the yaw rate correction method in this embodiment;

[0059] Figure 2 FIG. 1 is a diagram of a correction filter architecture for the vehicle yaw rate in this embodiment;

[0060] Figure 3 Schematic diagram of the calculation process of the upper and lower limits of the yaw rate change rate in this embodiment;

[0061] Figure 4 Schematic diagram of the yaw rate filter process in this embodiment;

[0062] Figure 5 Schematic diagram of measuring yaw angular velocity in the prior art;

[0063] Figure 6 This is a measurement analysis diagram of the yaw angular velocity in the prior art;

[0064] Figure 7 This is a comparison diagram of the effects of the implementation case in this embodiment and the prior art;

[0065] Figure 8 FIG1 is a diagram of a correction filter architecture for a vehicle yaw rate according to another embodiment of the present invention;

[0066] Figure 9 This is a structural block diagram of the yaw angular velocity correction device in this embodiment. DETAILED DESCRIPTION

[0067] The following describes the embodiments of the present invention with reference to the accompanying drawings and preferred embodiments. Those skilled in the art will readily appreciate the other advantages and benefits of the present invention from the disclosure herein. The present invention may also be implemented or applied through various other specific embodiments, and the various details in this specification may be modified or altered based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are intended only to illustrate the present invention and are not intended to limit the scope of protection of the present invention.

[0068] It should be noted that the illustrations provided in the following embodiments are merely schematic illustrations of the basic concept of the present invention. Therefore, the illustrations only show components related to the present invention and are not drawn according to the number, shape, and size of components in actual implementation. In actual implementation, the type, quantity, and proportion of each component may be changed arbitrarily, and the component layout may also be more complex.

[0069] As Figure 5 As shown in the figure, during autonomous driving, if a pothole-like road surface is encountered, the lateral acceleration mismeasurement by the traditional lateral acceleration detector in the ESP system causes YAWRATE to spike at value A. Furthermore, the autonomous driving system's extreme response and correction can cause YAWRATE to oscillate at peaks B and C, resulting in vehicle oscillation. Therefore, a YAWRATE measurement filter model is needed to filter out YAWRATE oscillations caused by lateral acceleration sensor measurement errors in scenarios like potholes.

[0070] Based on the above background, the present invention provides a real-time dynamic correction method for the yaw rate of an autonomous vehicle. This real-time dynamic correction method calculates the theoretical yaw rate in real time using a theoretical yaw rate change rate model constructed based on the steering wheel angle and vehicle speed. Furthermore, considering the actual operating conditions in actual applications, the possible upper and lower limits of the yaw rate are obtained. These upper and lower limits are used to dynamically correct large deviations and fluctuations in the yaw rate measured by the ESP system or IMU under abnormal conditions.

[0071] Combine Figure 1 、 Figure 2 and Figure 8 In this embodiment, the yaw rate correction method includes:

[0072] Step S101 , obtaining the vehicle's steering wheel angle, vehicle speed, and actual yaw rate output during the current sampling period.

[0073] In this embodiment, the obtained vehicle steering wheel angle is the actual measured real-time steering wheel angle or the predicted steering wheel angle predicted using a predetermined steering wheel angle prediction model. The obtained vehicle speed is the actual measured real-time speed or the predicted speed predicted using a predetermined speed prediction model.

[0074] When the vehicle's steering wheel angle is the actual measured real-time steering wheel angle and the vehicle's speed is the actual measured real-time speed, the vehicle's steering wheel angle is obtained from the vehicle's electronic stability system ESP or the steering wheel angle sensor, and the vehicle's speed is obtained via the driven wheel speed sensor. Figure 2 The architecture in .

[0075] When the steering wheel angle of the vehicle is the predicted steering wheel angle predicted by the predetermined steering wheel angle prediction model and the vehicle speed is the predicted vehicle speed predicted by the predetermined vehicle speed prediction model, the predetermined steering wheel angle prediction model and the predetermined vehicle speed prediction model can be implemented using algorithms such as Kalman filtering or ion filtering. At this time, the method in this embodiment executes Figure 8 The architecture in .

[0076] The actual yaw rate output in the current sampling period is the actual measurement value obtained by the ESP system or the IMU system.

[0077] Step S102 : Predicting the upper limit value and the lower limit value of the yaw rate change rate in real time based on the steering wheel angle and vehicle speed of the vehicle.

[0078] In this embodiment, step S102 specifically includes:

[0079] Inputting the vehicle's steering wheel angle and vehicle speed into a pre-established yaw rate change rate theoretical value model to obtain a yaw rate change rate theoretical value;

[0080] Inputting the theoretical values ​​of the yaw rate change rate into the pre-established yaw rate change rate upper limit value model respectively to obtain the yaw rate change rate upper limit value;

[0081] The yaw rate change rate theoretical values ​​are input into the pre-established yaw rate change rate lower limit value model to obtain the yaw rate change rate lower limit value.

[0082] In order to construct the above-mentioned yaw rate change rate theoretical value model, yaw rate change rate upper limit value model and yaw rate change rate lower limit value model, it is necessary to rely on the Yawrate filter. Figure 2 and Figure 8 In this embodiment, the Yawrate filter includes a YawRate change rate limit calculation module and a YawRate filter assignment module.

[0083] Specifically, the YawRate change rate limit calculation module includes a YawRate change rate theoretical value model 4, a YawRate change rate upper limit calculation module 5 and a YawRate change rate lower limit calculation module 6. The YawRate change rate theoretical value model 4 establishes a yaw rate change rate theoretical value model whose input factors are less affected by abnormal road conditions, and inputs the calculated yaw rate change rate theoretical value into the Yawate change rate upper limit calculation module 5 and the Yawrate change rate lower limit calculation module 6 respectively; the yaw rate change rate upper limit model in the Yawrate change rate upper limit calculation module 5 takes into account the normal fluctuations of the model input factors caused by normal road conditions such as cross slopes, and establishes an allowable yaw rate change rate upper limit. The yaw rate change lower limit value model in the yaw rate change lower limit value calculation module 6 takes into account the normal fluctuation of the model input factor due to normal road conditions such as slippery road surface, and establishes the allowable yaw rate change lower limit value. By taking into account the upper limit of the yaw rate change rate affected by all normal road conditions that affect the driving trajectory, Yaw angular rate change lower limit Stored to YawRate assignment module 9.

[0084] After the theoretical value model of the yaw rate change rate is established, the model function algorithm is integrated into the intelligent driving motion controller system (that is, the theoretical value model of the yaw rate change rate is embedded).

[0085] The steering wheel angle θ is obtained by turning the steering wheel, the vehicle speed V is obtained by a mature wheel speed sensor (or other mature vehicle speed sensors), and the yaw rate change rate theoretical value model theoretical value system filters out the influence of abnormal road lateral acceleration on the yaw rate calculation, and has strong robustness.

[0086] In this embodiment, the YawRate change rate upper limit value calculation module 5 obtains the yaw rate change rate theoretical value from the YawRate change rate theoretical value model 4. The upper limit value of the yaw rate change rate is established according to the upper limit value model of the yaw rate change rate.

[0087] The calculation of the upper limit of the yaw rate change rate involves the establishment theory of the upper limit correction coefficient value (ie, the first correction coefficient).

[0088] In order to obtain the first correction coefficient mentioned above, it is necessary to first determine the first predetermined correction coefficient. According to the design specifications for curved sections of highways, a cross slope value is designed to improve the vehicle's cornering performance and drainage requirements. The standard stipulates that the cross slope value shall not be greater than 5%. When a vehicle is driving on a road with a cross slope, the vehicle will turn even if the steering wheel angle is 0. Therefore, the cross slope will cause the actual yaw rate of change to be higher than the theoretical value. The first predetermined correction coefficient A is 1.1 times the value of the first predetermined correction coefficient A, and considering the road construction error and road settlement, the first predetermined correction coefficient A is amplified to 1.2 in engineering applications. Taking into account the road construction error and road settlement, the first predetermined correction coefficient is calibrated to 1.15-1.2.

[0089] Furthermore, the first correction coefficient is determined by: first correction coefficient = first predetermined correction coefficient * dynamic correction coefficient.

[0090] The above-mentioned dynamic correction coefficient is evaluated from the dynamic model. Since the vehicle is not a perfect rigid body and has understeer, the dynamic correction coefficient in this embodiment = 1 - understeer dynamic correction coefficient. The understeer dynamic correction coefficient is associated with the dynamic model of each vehicle and is related to the real-time road curvature C (provided by a camera or map) and the vehicle speed V. It is generally calibrated at a dynamic test site. An example of a MAP table of the calibrated understeer dynamic correction coefficient is shown in Table 1 below:

[0091]

[0092] Table 1

[0093] The above lower limit of the yaw rate change rate The determination of yawrate takes into account the redundant impact of normal road conditions such as cornering, drainage, road construction or settlement on YawRate, avoiding accidental damage caused by abnormal road conditions.

[0094] The YawRate change rate lower limit calculation module 6 obtains the yaw rate change rate theoretical value from the YawRate change rate theoretical value model 4 The lower limit value of the yaw rate change rate is established according to the lower limit value model of the yaw rate change rate

[0095] The calculation of the lower limit value of the yaw rate change rate involves the establishment of a lower limit correction coefficient value (ie, the second correction coefficient).

[0096] In order to obtain the second correction coefficient, it is necessary to first establish the second predetermined correction coefficient. The vehicle system is not a perfect rigid body, and considering the slippery road conditions in rainy days, the lateral acceleration of the vehicle will cause understeer. The maximum understeer is measured at the test site. Under extreme working conditions: 130 kilometers and 500m turning radius, the actual yaw rate of change is higher than the theoretical value. It is expected to be reduced to 0.87 times. The lower limit takes into account the engineering application of YawRate due to slippery road conditions. This normal situation is allowed to exist to avoid false filtering. In engineering applications, the second predetermined correction coefficient B value is reduced to 0.8-0.87.

[0097] Furthermore, the required second correction coefficient is determined by second correction coefficient = second predetermined correction coefficient * dynamic correction coefficient.

[0098] The solution method of the above dynamic correction coefficient is the same as the determination method in Table 1 above.

[0099] While distinguishing between abnormal roads such as speed bumps, manhole covers, and potholes, the system also allows for the existence of normal influences such as large-curvature cross-slope roads, slippery roads, and vehicle stiffness dispersion, enabling the autonomous driving system to obtain a more accurate yawrate for the vehicle and accurately execute the target trajectory.

[0100] In step S103 , the actual yaw rate is corrected according to the yaw rate change rate upper limit and the yaw rate change rate lower limit.

[0101] This step S103 includes:

[0102] determining an actual yaw rate change rate according to the actual yaw rate;

[0103] According to the upper limit of the yaw rate change rate and the lower limit of the yaw rate change rate The actual yaw rate is corrected based on the relative magnitude relationship with the actual yaw rate change rate.

[0104] Specifically, if According to the actual yaw rate YawRate output in the previous sampling period T-1 and the upper limit of the yaw rate change rate The actual yaw rate is corrected; that is, the upper limit of the yaw rate change rate is first multiplied by the length of one sampling period, and then the obtained product is added to the actual yaw rate output in the previous sampling period to obtain the corrected actual yaw rate.

[0105] like According to the actual yaw rate YawRate output in the previous sampling period T-1 and the lower limit of the yaw rate change rate The actual yaw rate is corrected; that is, the lower limit of the yaw rate change rate is first multiplied by the length of one sampling period, and then the obtained product is added to the actual yaw rate output in the previous sampling period to obtain the corrected actual yaw rate.

[0106] like The actual yaw rate YawRate output in the current sampling period is directly used as the corrected actual yaw rate.

[0107] In this embodiment, the length of one sampling period is 20 ms.

[0108] like Figure 2 and 8 The YawRate filter assignment module includes a YawRate measurement acquisition module 7, a YawRate filtering module 8, and a YawRate assignment module 9. The YawRate measurement acquisition module 7 obtains the actual detected yaw rate change rate YawRate from the ESP system or IMU and sends this detected value to the YawRate filtering module 8. The YawRate filtering module 8 filters the actual detected yaw rate value according to a pre-set filtering principle and in combination with the dynamically updated upper and lower limits of the yaw rate change rate obtained from the YawRate assignment module 9. This fully considers filtering out abnormal road conditions such as speed bumps, manhole covers, and potholes, while allowing the filter to take into account the impact of slippery road surfaces, high-speed turns, and other normal road conditions, thereby achieving real-time filtering of YawRate abnormal values. The YawRate assignment module 9 reassigns the YawRate value under different conditions based on the filtering results.

[0109] The YawRate filtering module 8 updates the latest calculated yaw rate in the local storage according to the filtering standard and transmits it to the automatic driving function module 6.

[0110] like Figure 5 In this embodiment, a 60 km / h straight road pothole scenario is used. When the vehicle passes through the pothole, the Yawrate measurement value is affected for about 0.8 seconds, with a positive error of +0.6° / s and a negative error of -1.4° / s. During this period, the steering control system corrects the steering wheel angle in real time by approximately -2° and +5°, causing the steering wheel of the autonomous vehicle to swing abnormally left and right.

[0111] like Figure 6 In the same scenario, when the vehicle passes through a pothole, the actual yaw rate is also affected, with the positive error reaching -1.4° / s and the negative error reaching +0.6° / s. After adding the filtering correction process in this embodiment, point B enters CASE 1: the actual measured yaw rate change rate > the yaw rate change rate upper limit, YawRate = YawRate T-1The positive error of + yaw rate change upper limit × T period (i.e., the length of a single sampling period) is greatly suppressed, and points A and C enter CASE 2: yaw rate change lower limit ≤ actually measured yaw rate change ≤ yaw rate change upper limit, YawRate = actually measured YawRate, the corrected yaw angle is approximately 0° / s, the steering control system corrects the steering wheel angle to approximately 0° in real time, and the autonomous vehicle's steering wheel is stable.

[0112] like Figure 7 In a scenario with a 500-meter turning radius, the yaw rate becomes stable after conventional filtering, but a delay of approximately 120ms occurs, resulting in delayed correction. This increases the autonomous vehicle's trajectory execution error and causes the vehicle to be off-center during cornering. Comparing the filtering correction effect of this embodiment, it can be seen that the yaw rate becomes stable with almost no delay, effectively ensuring the autonomous vehicle's trajectory execution error.

[0113] like Figure 9 , an embodiment of the present invention further provides a yaw angular velocity correction device, comprising:

[0114] The vehicle parameter acquisition module 201 is used to obtain the vehicle's steering wheel angle, vehicle speed, and actual yaw rate output during the current sampling period;

[0115] The yaw rate change rate upper and lower limit prediction module 202 is used to predict the yaw rate change rate upper limit and the yaw rate change rate lower limit in real time based on the vehicle's steering wheel angle and vehicle speed;

[0116] The actual yaw rate correction module 203 is configured to correct the actual yaw rate according to the yaw rate change rate upper limit and the yaw rate change rate lower limit.

[0117] Preferably, the yaw rate change rate upper and lower limit prediction module 202 includes:

[0118] The yaw rate change rate theoretical value prediction unit 2021 is used to input the vehicle's steering wheel angle and vehicle speed into a pre-established yaw rate change rate theoretical value model to obtain a yaw rate change rate theoretical value;

[0119] The yaw rate change rate upper limit value prediction unit 2022 is used to input the yaw rate change rate theoretical value into a pre-established yaw rate change rate upper limit value model to obtain the yaw rate change rate upper limit value;

[0120] The yaw rate change rate lower limit value prediction unit 2023 is configured to input the yaw rate change rate theoretical values ​​into a pre-established yaw rate change rate lower limit value model to obtain the yaw rate change rate lower limit value.

[0121] Preferably, the actual yaw rate correction module 203 includes:

[0122] an actual yaw rate change rate determining unit 2031, configured to determine an actual yaw rate change rate according to the actual yaw rate;

[0123] The actual yaw rate correction unit 2032 is configured to correct the actual yaw rate according to a relative magnitude relationship between the yaw rate change rate upper limit value, the yaw rate change rate lower limit value, and the actual yaw rate change rate.

[0124] Preferably, the actual yaw rate correction unit 2032 includes:

[0125] A first actual yaw rate correction subunit 20321 is configured to correct the actual yaw rate according to the actual yaw rate output in the previous sampling period and the yaw rate change upper limit value if the actual yaw rate change rate is greater than the yaw rate change upper limit value;

[0126] a second actual yaw rate correction subunit 20322 configured to correct the actual yaw rate according to the actual yaw rate output in the previous sampling period and the yaw rate change rate lower limit if the actual yaw rate change rate is less than the yaw rate change rate upper limit;

[0127] The third actual yaw rate correction subunit 20323 is configured to directly use the actual yaw rate output in the current sampling period as the corrected actual yaw rate if the yaw rate change rate lower limit ≤ the actual yaw rate change rate ≤ the yaw rate change rate upper limit.

[0128] The specific implementation method of the above-mentioned device in this embodiment can borrow the specific implementation means of the above-mentioned method, which has the same technical effect as the above-mentioned method.

[0129] The present invention also provides a vehicle comprising the above-mentioned yaw angular velocity correction device.

[0130] The present invention also provides a control device, including a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the yaw angular velocity correction method as described above.

[0131] The present invention also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the yaw angular velocity correction method as described above are implemented.

[0132] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A yaw rate correction method, characterized in that: include: Obtain the vehicle's steering wheel angle, vehicle speed, and actual yaw rate output during the current sampling period; Based on the vehicle's steering wheel angle and speed, the upper and lower limits of the yaw rate change rate are predicted in real time. Specifically, the following are included: Inputting the vehicle's steering wheel angle and vehicle speed into a pre-established yaw rate change rate theoretical value model to obtain a yaw rate change rate theoretical value, thereby determining an upper limit value and a lower limit value of the yaw rate change rate; Correcting the actual yaw rate according to the yaw rate change rate upper limit and the yaw rate change rate lower limit; specifically, determining the actual yaw rate change rate according to the actual yaw rate; If the actual yaw rate change rate is greater than the yaw rate change rate upper limit, the actual yaw rate is corrected according to the actual yaw rate output in the previous sampling period and the yaw rate change rate upper limit; If the actual yaw rate change rate is less than the yaw rate change rate lower limit, the actual yaw rate is corrected according to the actual yaw rate output in the previous sampling period and the yaw rate change rate lower limit; If the yaw rate change rate lower limit ≤ the actual yaw rate change rate ≤ the yaw rate change rate upper limit, the actual yaw rate output in the current sampling period is directly used as the corrected actual yaw rate.

2. The yaw rate correction method according to claim 1, characterized in that: The step of predicting the upper limit value and the lower limit value of the yaw rate change rate in real time based on the steering wheel angle and the vehicle speed further includes: Inputting the theoretical values ​​of the yaw rate change rate into the pre-established yaw rate change rate upper limit value model respectively to obtain the yaw rate change rate upper limit value; The yaw rate change rate theoretical values ​​are input into the pre-established yaw rate change rate lower limit value model to obtain the yaw rate change rate lower limit value.

3. The yaw rate correction method according to claim 2, characterized in that: Inputting the theoretical values ​​of the yaw rate change rate into the pre-established yaw rate change rate upper limit value model to obtain the yaw rate change rate upper limit value comprises the following steps: The product of the theoretical value of the yaw rate change rate and the first correction coefficient is determined as the upper limit value of the yaw rate change rate; The value of the first correction coefficient is negatively correlated with the road curvature C and the vehicle speed V.

4. The yaw rate correction method according to claim 3, characterized in that: Inputting the theoretical values ​​of the yaw rate change rate into the pre-established yaw rate change rate lower limit model to obtain the yaw rate change rate lower limit includes the following steps: The product of the theoretical value of the yaw rate change rate and the second correction coefficient is determined as the lower limit value of the yaw rate change rate; The value of the second correction coefficient is negatively correlated with the road curvature C and the vehicle speed V, and the second correction coefficient is smaller than the first correction coefficient.

5. The yaw rate correction method according to claim 1, characterized in that: The steps of correcting the actual yaw rate according to the actual yaw rate and the upper limit of the yaw rate change rate outputted in the previous sampling period include: First, multiply the upper limit of the yaw rate change rate by the length of a sampling period, and then add the resulting product to the actual yaw rate output in the previous sampling period to obtain the corrected actual yaw rate.

6. The yaw rate correction method according to claim 1 or 5, characterized in that: The steps of correcting the actual yaw rate according to the actual yaw rate and the lower limit of the yaw rate change rate outputted in the previous sampling period include: First, multiply the lower limit of the yaw rate change rate by the length of a sampling period, and then add the resulting product to the actual yaw rate output in the previous sampling period to obtain the corrected actual yaw rate.

7. The yaw rate correction method according to claim 1, characterized in that: The actual yaw rate is obtained by the vehicle's electronic stability system ESP or inertial measurement unit IMU output.

8. The yaw rate correction method according to claim 1, characterized in that: The obtained vehicle steering wheel angle is an actually measured real-time steering wheel angle or a predicted steering wheel angle predicted by a predetermined steering wheel angle prediction model; The acquired vehicle speed is the actual measured real-time vehicle speed or the predicted vehicle speed predicted by a predetermined vehicle speed prediction model.

9. A yaw rate correction device, characterized in that: include: The vehicle parameter acquisition module is used to obtain the vehicle's steering wheel angle, vehicle speed, and actual yaw rate output in the current sampling period; A yaw rate change rate upper and lower limit prediction module is used to predict the yaw rate change rate upper limit and the yaw rate change rate lower limit in real time based on the vehicle's steering wheel angle and vehicle speed; An actual yaw rate correction module is used to correct the actual yaw rate according to an upper limit value and a lower limit value of the yaw rate change rate; The yaw rate change rate upper and lower limit prediction module includes: a yaw rate change rate theoretical value prediction unit, configured to input the vehicle's steering wheel angle and vehicle speed into a pre-established yaw rate change rate theoretical value model to obtain a yaw rate change rate theoretical value, thereby determining an upper limit value and a lower limit value of the yaw rate change rate; The actual yaw rate correction module includes: an actual yaw rate change rate determining unit, configured to determine an actual yaw rate change rate according to the actual yaw rate; The actual yaw rate correction unit specifically includes: a first actual yaw rate correction subunit, configured to correct the actual yaw rate according to the actual yaw rate output in the previous sampling period and the upper limit of the yaw rate change rate if the actual yaw rate change rate is greater than the upper limit of the yaw rate change rate; a second actual yaw rate correction subunit, configured to correct the actual yaw rate according to the actual yaw rate output in the previous sampling period and the lower limit of the yaw rate change rate if the actual yaw rate change rate is less than the upper limit of the yaw rate change rate; and a third actual yaw rate correction subunit, configured to directly use the actual yaw rate output in the current sampling period as the corrected actual yaw rate if the lower limit of the yaw rate change rate is less than or equal to the actual yaw rate change rate or less than or equal to the upper limit of the yaw rate change rate.

10. The yaw rate correction device according to claim 9, characterized in that: The yaw rate change rate upper and lower limit prediction module also includes: a yaw rate change rate upper limit value prediction unit, configured to input the yaw rate change rate theoretical values ​​into a pre-established yaw rate change rate upper limit value model to obtain the yaw rate change rate upper limit value; The yaw rate change rate lower limit value prediction unit is used to input the yaw rate change rate theoretical values ​​into the pre-established yaw rate change rate lower limit value model to obtain the yaw rate change rate lower limit value.

11. A vehicle, characterized in that: Including the yaw angular velocity correction device as described in claim 9 or 10.

12. A control device, characterized in that: The invention comprises a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the yaw angular rate correction method according to any one of claims 1 to 8.

13. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the yaw angular rate correction method according to any one of claims 1 to 8 are implemented.

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