Course angular velocity anomaly detection method and device, electronic equipment and storage medium

Abstract

The invention provides a course angular velocity anomaly detection method and device, electronic equipment and a storage medium. The course angular velocity anomaly detection method comprises the following steps: firstly, obtaining turning parameters of a vehicle; then, based on the turning parameters, the first course angular velocity of the vehicle is obtained through calculation; and performing anomaly detection on the second course angular velocity by using the first course angular velocity to obtain a first anomaly detection result. And then calculating a zero offset value of the second course angular velocity, and performing anomaly detection on the second course angular velocity by using the zero offset value to obtain a second anomaly detection result. And finally, combining the first anomaly detection result and the second anomaly detection result to determine whether the second course angular velocity is abnormal or not. Therefore, by utilizing the method provided by the invention, whether the course angular velocity output by the IMU is abnormal or not can be timely and effectively judged, the accuracy and the stability of attitude estimation in dead reckoning of the automatic driving vehicle are improved, and the safe and stable operation of the vehicle is ensured.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and in particular to a heading angular velocity anomaly detection method, device, electronic device and storage medium. Background Art

[0002] For autonomous vehicles, when sensors such as lidar and cameras malfunction or fail, or when the satellite signal is blocked in tunnels, underground parking lots, mountainous areas and other environments, the inertial measurement unit (IMU) can provide higher-frequency, high-precision signals and provide vehicle angular velocity and acceleration information in real time, which can be used for high-precision dead reckoning.

[0003] However, in some cases, the IMU's heading angular velocity measurement results may also deviate, and the existing technology is unable to promptly detect abnormalities in the IMU's heading angular velocity measurement results. When the deviations continue to accumulate, they will affect the dead reckoning attitude estimation, easily leading to a decrease in vehicle positioning accuracy or abnormalities, and even causing the vehicle to lose control and cause a vehicle safety accident. Summary of the invention

[0004] In view of this, the present application provides a heading angular velocity anomaly detection method, device, electronic device and storage medium to solve the problem that the prior art cannot promptly detect abnormalities in the heading angular velocity measurement results of the IMU.

[0005] To achieve the above objectives, this application provides the following technical solutions:

[0006] The first aspect of the present application discloses a method for detecting abnormal heading angular velocity, comprising:

[0007] Obtaining turning parameters of the vehicle; wherein the turning parameters include inner wheel angular velocity, outer wheel angular velocity, turning radius, inner and outer wheel distance and vehicle turning angle;

[0008] Based on the turning parameter, a first heading angular velocity of the vehicle is calculated;

[0009] Using the first heading angular velocity to perform an abnormality detection on the second heading angular velocity to obtain a first abnormality detection result; wherein the second heading angular velocity is a heading angular velocity measured by an inertial measurement unit;

[0010] Calculating a zero bias value of the second heading angular velocity, and performing an abnormality detection on the second heading angular velocity using the zero bias value to obtain a second abnormality detection result;

[0011] In combination with the first abnormality detection result and the second abnormality detection result, it is determined whether the second heading angular velocity is abnormal.

[0012] Optionally, in the above method, the calculating the first heading angular velocity of the vehicle based on the turning parameter includes:

[0013] multiplying the difference between the inner wheel angular velocity and the outer wheel angular velocity by the turning radius to obtain a first product;

[0014] Multiplying the inner and outer wheel distances by the cosine value of the vehicle turning angle to obtain a second product;

[0015] The first product is divided by the second product to obtain the first heading angular velocity.

[0016] Optionally, in the above method, the step of performing abnormality detection on the second heading angular velocity using the first heading angular velocity to obtain a first abnormality detection result includes:

[0017] Detecting whether the wheel speed state of each wheel of the vehicle is normal;

[0018] If it is detected that the wheel speed states of the wheels are all normal, a set of differences between the first heading angular velocity and the second heading angular velocity within a first preset time period is generated;

[0019] Comparing each difference value in the set with a preset first threshold value, and determining the number of difference values ​​greater than the first threshold value;

[0020] Comparing the number of differences with a preset second threshold;

[0021] If the number of the differences is less than the second threshold, the first abnormality detection result is that the second heading angular velocity is normal;

[0022] If the number of differences is not less than a second threshold, the first abnormality detection result is that the second heading angular velocity is abnormal.

[0023] Optionally, in the above method, the calculating the zero bias value of the second heading angular velocity includes:

[0024] When the vehicle is in a static state, an average value of each of the second heading angular velocities within a second preset time period is calculated, and the average value is used as the zero bias value.

[0025] Optionally, in the above method, the calculating the zero bias value of the second heading angular velocity includes:

[0026] When the vehicle is in dynamic state, the heading angular velocity is estimated through Kalman filtering to obtain the estimated heading angular velocity;

[0027] A difference between the estimated heading angular velocity and the second heading angular velocity is calculated and used as the zero bias value.

[0028] Optionally, the above method, after combining the first abnormality detection result and the second abnormality detection result to determine whether the second heading angular velocity is abnormal, further includes:

[0029] If it is determined that the second heading angular velocity is abnormal, the vehicle speed is controlled according to a preset scheme, and the inertial measurement unit is switched to a backup inertial measurement unit.

[0030] The second aspect of the present application discloses a device for detecting abnormal heading angular velocity, comprising:

[0031] An acquisition unit, used for acquiring turning parameters of the vehicle; wherein the turning parameters include an inner wheel angular velocity, an outer wheel angular velocity, a turning radius, a distance between the inner and outer wheels, and a vehicle turning angle;

[0032] A calculation unit, configured to calculate a first heading angular velocity of the vehicle based on the turning parameter;

[0033] a first detection unit, configured to perform an abnormality detection on a second heading angular velocity using the first heading angular velocity to obtain a first abnormality detection result; wherein the second heading angular velocity is a heading angular velocity measured by an inertial measurement unit;

[0034] a second detection unit, configured to calculate a zero bias value of the second heading angular velocity, and perform an abnormality detection on the second heading angular velocity using the zero bias value to obtain a second abnormality detection result;

[0035] A determination unit is used to determine whether the second heading angular velocity is abnormal in combination with the first abnormality detection result and the second abnormality detection result.

[0036] Optionally, in the above-mentioned device, the computing unit includes:

[0037] a first calculation subunit, configured to multiply the difference between the inner wheel angular velocity and the outer wheel angular velocity by the turning radius to obtain a first product;

[0038] A second calculation subunit is used to multiply the inner and outer wheel distances by the cosine value of the vehicle turning angle to obtain a second product;

[0039] The third calculation subunit is used to divide the first product by the second product to obtain the first heading angular velocity.

[0040] Optionally, in the above device, the first detection unit includes:

[0041] A detection subunit, used for detecting whether the wheel speed state of each wheel of the vehicle is normal;

[0042] a set generating subunit, configured to generate a set of differences between the first heading angular velocity and the second heading angular velocity within a first preset time period if it is detected that the wheel speed states of the respective wheels are normal;

[0043] A first comparison subunit, used to compare each difference in the set with a preset first threshold, and determine the number of differences greater than the first threshold;

[0044] A second comparison subunit, used to compare the number of differences with a preset second threshold;

[0045] a first determining subunit, configured to determine that the first abnormality detection result is that the second heading angular velocity is normal if the number of the difference values ​​is less than the second threshold value;

[0046] The second determining subunit is configured to determine that, if the number of the differences is not less than a second threshold value, the first abnormality detection result is that the second heading angular velocity is abnormal.

[0047] Optionally, in the above device, the second detection unit 304 includes:

[0048] The first generating subunit is used to calculate an average value of each of the second heading angular velocities within a second preset time period when the vehicle is in a static state, and use the average value as the zero bias value.

[0049] Optionally, in the above device, the second detection unit 304 includes:

[0050] The estimation subunit is used to estimate the heading angular velocity through Kalman filtering when the vehicle is in a dynamic state to obtain an estimated heading angular velocity;

[0051] The fourth calculation subunit is used to calculate the difference between the estimated heading angular velocity and the second heading angular velocity, and use the difference as the zero bias value.

[0052] Optionally, the above device further includes:

[0053] A switching unit is used to control the vehicle speed according to a preset scheme and switch the inertial measurement unit to a spare inertial measurement unit if it is determined that the second heading angular velocity is abnormal.

[0054] The third aspect of the present application discloses an electronic device, comprising:

[0055] one or more processors;

[0056] a storage device having one or more programs stored thereon;

[0057] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of the first aspects of the present application.

[0058] A fourth aspect of the present application discloses a computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method described in any one of the first aspects of the present application is implemented.

[0059] It can be seen from the above technical scheme that in a method for detecting abnormal heading angular velocity provided by the present application, the turning parameters of the vehicle are first obtained. Then, based on the turning parameters, the first heading angular velocity of the vehicle is calculated. The second heading angular velocity is detected for abnormality using the first heading angular velocity to obtain a first abnormality detection result; wherein, the second heading angular velocity is the heading angular velocity measured by the inertial measurement unit. Then, the zero bias value of the second heading angular velocity is calculated, and the second heading angular velocity is detected for abnormality using the zero bias value to obtain a second abnormality detection result. Finally, it is determined whether the second heading angular velocity is abnormal by combining the first abnormality detection result and the second abnormality detection result. It can be seen that, using the method of the present application, the second heading angular velocity output by the IMU is detected for abnormality by the zero bias values ​​of the first heading angular velocity and the second heading angular velocity, respectively, so that it can be timely and effectively judged whether the heading angular velocity output by the IMU is abnormal, thereby improving the accuracy and stability of attitude estimation in the dead reckoning of the autonomous driving vehicle, and ensuring the safe and stable operation of the vehicle. The problem that the abnormality of the heading angular velocity measurement result of the IMU cannot be detected in time in the prior art is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0061] Figure 1 A flowchart of a method for detecting abnormal heading angular velocity disclosed in an embodiment of the present application;

[0062] Figure 2 This is a flowchart of an implementation of step S103 disclosed in another embodiment of the present application;

[0063] Figure 3 A schematic diagram of a device for detecting abnormal heading angular velocity disclosed in another embodiment of the present application;

[0064] Figure 4 A schematic diagram of an electronic device disclosed in another embodiment of the present application. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0066] In this application, the terms "comprises", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.

[0067] Furthermore, in this document, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0068] The present application provides a method for detecting abnormal heading angular velocity. Figure 1 As shown, including:

[0069] S101. Obtain turning parameters of the vehicle; wherein the turning parameters include an inner wheel angular velocity, an outer wheel angular velocity, a turning radius, a distance between the inner and outer wheels, and a vehicle turning angle.

[0070] It should be noted that, ideally, the vehicle's angular velocity is equal to the ratio of the linear velocity at the center of mass of the vehicle to the curvature of the vehicle's driving track. The linear velocity of the vehicle and the curvature of the vehicle's driving track are not easy to measure directly, but can be indirectly calculated through the speed difference between the inner and outer wheels of the vehicle, the turning angle information, etc. Therefore, the turning parameters of the vehicle are first obtained; among them, the turning parameters include the angular velocity of the inner wheel , outer wheel angular velocity , turning radius R, inner and outer wheel distance L and vehicle turning angle , these parameters are calculated by sensors on the vehicle. When the vehicle turns left, the left wheel is the inner wheel and the right wheel is the outer wheel; when the vehicle turns right, the right wheel is the inner wheel and the left wheel is the outer wheel.

[0071] S102: Calculate a first heading angular velocity of the vehicle based on the turning parameter.

[0072] It should be noted that after obtaining turning parameters such as the inner wheel angular velocity, the outer wheel angular velocity, the turning radius, the inner and outer wheel distance and the vehicle turning angle, the first heading angular velocity of the vehicle is calculated by a preset formula based on the obtained turning parameters.

[0073] Optionally, in another embodiment of the present application, an implementation of step S102 may include:

[0074] The first product is obtained by multiplying the difference between the angular velocity of the inner wheel and the angular velocity of the outer wheel by the turning radius.

[0075] Multiply the distance between the inner and outer wheels by the cosine of the vehicle's turning angle to obtain the second product.

[0076] Divide the first product by the second product to obtain the first heading angular velocity.

[0077] It should be noted that the parameters such as the inner wheel angular velocity, the outer wheel angular velocity, the turning radius, the inner and outer wheel distance and the vehicle turning angle are substituted into the preset vehicle heading angle calculation formula to calculate the first heading angular velocity of the vehicle, and the formula is as follows:

[0078]

[0079] in, is the angular velocity of the inner wheel of the vehicle, is the angular velocity of the outer wheel of the vehicle, is the vehicle turning radius, is the distance between the inner and outer wheels of the vehicle, is the wheel angle.

[0080] S103. Perform an abnormality detection on the second heading angular velocity using the first heading angular velocity to obtain a first abnormality detection result, wherein the second heading angular velocity is the heading angular velocity measured by an inertial measurement unit IMU; wherein the second heading angular velocity is the heading angular velocity measured by the inertial measurement unit IMU.

[0081] It should be noted that after the first heading angular velocity is calculated according to the turning parameters, the second heading angular velocity output by the inertial measurement unit is obtained, and then the first heading angular velocity is compared with the second heading angular velocity to detect whether the second heading angular velocity output by the inertial measurement unit is abnormal, and a first abnormality detection result is obtained.

[0082] Optionally, in another embodiment of the present application, an implementation of step S103 is as follows: Figure 2 As shown, this may include:

[0083] S201, detecting whether the wheel speed status of each wheel of the vehicle is normal.

[0084] It should be noted that the wheel speed state measured by the wheel speed sensor is first diagnosed to detect whether the wheel speed state of each wheel of the vehicle is normal. The detection items include: 1. Determine whether the values ​​of each wheel speed are updated normally and whether there are any stuck frames; 2. Determine whether each wheel speed has a large abnormal value; 3. Determine whether the speed difference between the coaxial left and right wheels exceeds the coaxial wheel speed difference threshold; whether the speed difference between different circumferences on the same side exceeds the speed difference threshold on the same side. If the above detection results are all no, it is determined that the wheel speed state of each wheel is normal; otherwise, it is determined that the wheel speed state of one or some wheels is abnormal.

[0085] S202: If it is detected that the wheel speed states of all wheels are normal, a set of differences between the first heading angular velocity and the second heading angular velocity within a first preset time period is generated.

[0086] It should be noted that if it is detected that the wheel speed states of the above-mentioned wheels are all normal, the first heading angular velocity and the second heading angular velocity within a first preset time period are obtained, and the preset time period can be set according to actual conditions, for example, 5 minutes, wherein the first heading angular velocity and the second heading angular velocity are re-obtained every 30 seconds. Then, the difference between each group of the first heading angular velocity and the second heading angular velocity within the preset time period is calculated, and a set of all the differences is generated.

[0087] S203: Compare each difference in the set with a preset first threshold, and determine the number of differences that are greater than the first threshold.

[0088] It should be noted that each difference in the set is compared with a preset first threshold to determine the number of differences greater than the first threshold. The first threshold can be set according to actual conditions, for example, 20.

[0089] S204: Compare the number of differences with a preset second threshold.

[0090] It should be noted that the number of differences is compared with a preset second threshold, and the second threshold can be set according to actual conditions, for example, 2.

[0091] S205: If the number of differences is less than the second threshold, the first abnormality detection result is that the second heading angular velocity is normal.

[0092] S206: If the number of differences is not less than the second threshold, the first abnormality detection result is that the second heading angular velocity is abnormal.

[0093] S104, calculating a zero bias value of the second heading angular velocity, and using the zero bias value to perform an abnormality detection on the second heading angular velocity to obtain a second abnormality detection result.

[0094] It should be noted that the zero bias of the heading angular velocity is the static deviation of the heading angle, which refers to the deviation between the output measurement value and the true value without the action of external force or angular velocity. The existence of zero bias will cause deviations in the measurement results, affect the accuracy of attitude estimation, and cause the error to gradually increase. In addition, the zero bias will also be affected by environmental factors such as temperature and vibration. Therefore, the zero bias value of the second heading angular velocity is calculated, and the zero bias value is used to perform abnormal detection on the second heading angular velocity. When the zero bias value of the heading angular velocity exceeds the zero bias threshold set by the inertial measurement unit IMU, or the zero bias change calculated twice exceeds 0.02, it is judged that there is an abnormality in the IMU measurement of the heading angular velocity, otherwise it is judged that there is no abnormality in the IMU measurement of the heading angular velocity, and a second abnormality detection result is generated.

[0095] Optionally, in another embodiment of the present application, an implementation of calculating the zero bias value of the second heading angular velocity in the above step S104 may include:

[0096] When the vehicle is in a static state, the average value of each second heading angular velocity within the second preset time period is calculated, and the average value is used as the zero bias value.

[0097] It should be noted that when the vehicle is stationary and there is no load change, the heading angular velocity should be 0, but due to the existence of zero bias, the heading angular velocity still has a value. At this time, the value of the heading angular velocity is not a constant value, but is in a small fluctuation state. Therefore, the average value of each second heading angular velocity in the second preset time period is calculated, and the average value is used as the zero bias value. The second preset time period can be set according to actual conditions, for example, 5 minutes.

[0098] Optionally, in another embodiment of the present application, an implementation of calculating the zero bias value of the second heading angular velocity in the above step S104 may include:

[0099] When the vehicle is in dynamic state, the heading angular velocity is estimated through Kalman filtering to obtain the estimated heading angular velocity.

[0100] The difference between the estimated heading angular velocity and the second heading angular velocity is calculated and used as the zero bias value.

[0101] It should be noted that when the vehicle is in a non-stationary dynamic state, the heading angular velocity is estimated through Kalman filtering to obtain the estimated heading angular velocity. Kalman filtering is an algorithm that uses the linear system state equation and the system input and output observation data to optimally estimate the system state. Here, the heading angular velocity is used as the state quantity, and the state quantity is estimated through other observation information to obtain the estimated heading angular velocity. The difference between the estimated heading angular velocity and the second heading angular velocity is calculated, and the difference is used as the zero bias value.

[0102] Optionally, in another embodiment of the present application, the heading angular velocity is estimated through Kalman filtering to obtain an estimated heading angular velocity, and then the ratio of the estimated heading angular velocity and the second heading angular velocity is calculated to obtain a proportional factor error of the heading angular velocity. The proportional factor of the inertial measurement unit IMU is corrected according to the proportional factor error, and the proportional factor refers to the proportional relationship between the IMU heading angular velocity and the true value.

[0103] S105. Determine whether the second heading angular velocity is abnormal by combining the first abnormality detection result and the second abnormality detection result.

[0104] It should be noted that if both the first abnormal detection result and the second abnormal detection result show that the second heading angular velocity is normal, it is determined that there is no abnormality in the second heading angular velocity; if the first abnormal detection result and / or the second abnormal detection result show that the second heading angular velocity is abnormal, it is determined that there is an abnormality in the second heading angular velocity.

[0105] In a method for detecting anomalies in angular velocity of heading provided by an embodiment of the present application, firstly, a turning parameter of the vehicle is obtained. Then, based on the turning parameter, a first angular velocity of heading of the vehicle is calculated. The first angular velocity of heading is used to detect anomalies in the second angular velocity of heading, and a first anomaly detection result is obtained; wherein, the second angular velocity of heading is the angular velocity of heading measured by the inertial measurement unit. Then, the zero bias value of the second angular velocity of heading is calculated, and the zero bias value is used to detect anomalies in the second angular velocity of heading, and a second anomaly detection result is obtained. Finally, the first anomaly detection result and the second anomaly detection result are combined to determine whether the second angular velocity of heading is abnormal. It can be seen that, by using the method of the present application, the second angular velocity of heading output by the IMU is detected for anomalies by the zero bias values ​​of the first angular velocity of heading and the second angular velocity of heading respectively, so that it can be timely and effectively judged whether the angular velocity of heading output by the IMU is abnormal, and the accuracy and stability of attitude estimation in the dead reckoning of the autonomous driving vehicle are improved, and the safe and stable operation of the vehicle is ensured. The problem that the angular velocity measurement result of the IMU cannot be detected in time in the prior art is solved.

[0106] Optionally, in another embodiment of the present application, after executing step S105, the following may also be included:

[0107] If it is determined that the second heading angular velocity is abnormal, the vehicle speed is controlled according to a preset scheme, and the inertial measurement unit is switched to a backup inertial measurement unit.

[0108] It should be noted that if it is determined that the second heading angular velocity is abnormal, the vehicle speed is controlled according to a preset scheme, such as deceleration or parking. Then the inertial measurement unit is switched to a backup inertial measurement unit, for example, the inertial measurement unit configured in the electronic stability control system of the vehicle is used as a backup inertial measurement unit, and the heading angular velocity is measured by the backup inertial measurement unit to perform dead reckoning to ensure the accuracy and stability of the vehicle attitude estimation. If there is no abnormality in the second heading angular velocity, the heading angular velocity is directly measured by the inertial measurement unit to perform vehicle attitude estimation.

[0109] Another embodiment of the present application also provides a device for detecting abnormal heading angular velocity, such as Figure 3 As shown, specifically including:

[0110] The acquisition unit 301 is used to acquire turning parameters of the vehicle; wherein the turning parameters include the inner wheel angular velocity, the outer wheel angular velocity, the turning radius, the inner and outer wheel distance and the vehicle turning angle.

[0111] The calculation unit 302 is used to calculate a first heading angular velocity of the vehicle based on the turning parameter.

[0112] The first detection unit 303 is used to perform an abnormality detection on the second heading angular velocity by using the first heading angular velocity to obtain a first abnormality detection result; wherein the second heading angular velocity is the heading angular velocity measured by the inertial measurement unit.

[0113] The second detection unit 304 is used to calculate the zero bias value of the second heading angular velocity, and perform anomaly detection on the second heading angular velocity using the zero bias value to obtain a second anomaly detection result.

[0114] The determination unit 305 is configured to determine whether the second heading angular velocity is abnormal by combining the first abnormality detection result and the second abnormality detection result.

[0115] In this embodiment, the specific execution process of the acquisition unit 301, the calculation unit 302, the first detection unit 303, the second detection unit 304 and the determination unit 305 can be referred to the corresponding Figure 1 The content of the method embodiment will not be repeated here.

[0116] In a device for detecting anomaly of angular heading velocity provided by an embodiment of the present application, first, an acquisition unit 301 acquires a turning parameter of a vehicle. Then, a calculation unit 302 calculates a first angular heading velocity of the vehicle based on the turning parameter. The first detection unit 303 uses the first angular heading velocity to perform anomaly detection on the second angular heading velocity to obtain a first anomaly detection result; wherein, the second angular heading velocity is the angular heading velocity measured by the inertial measurement unit. Then, the second detection unit 304 calculates the zero bias value of the second angular heading velocity, and uses the zero bias value to perform anomaly detection on the second angular heading velocity to obtain a second anomaly detection result. Finally, the determination unit 305 determines whether there is an anomaly in the second angular heading velocity in combination with the first anomaly detection result and the second anomaly detection result. It can be seen that, by using the method of the present application, the second angular heading velocity output by the IMU is respectively detected for anomaly by the zero bias values ​​of the first angular heading velocity and the second angular heading velocity, so as to timely and effectively determine whether there is an anomaly in the angular heading velocity output by the IMU, thereby improving the accuracy and stability of attitude estimation in the dead reckoning of the autonomous driving vehicle, and ensuring the safe and stable operation of the vehicle. The problem that the IMU's heading angular velocity measurement results are abnormal and cannot be detected in time in the prior art is solved.

[0117] Optionally, in another embodiment of the present application, an implementation of the calculation unit 302 includes:

[0118] The first calculation subunit is used to multiply the difference between the inner wheel angular velocity and the outer wheel angular velocity by the turning radius to obtain a first product.

[0119] The second calculation subunit is used to multiply the distance between the inner and outer wheels by the cosine value of the vehicle turning angle to obtain a second product.

[0120] The third calculation subunit is used to divide the first product by the second product to obtain a first heading angular velocity.

[0121] In this embodiment, the specific execution process of the first computing subunit, the second computing subunit, and the third computing subunit can be found in the corresponding method embodiments described above, and will not be repeated here.

[0122] Optionally, in another embodiment of the present application, an implementation of the first detection unit 303 includes:

[0123] The detection subunit is used to detect whether the wheel speed status of each wheel of the vehicle is normal.

[0124] The set generating subunit is used to generate a set of differences between the first heading angular velocity and the second heading angular velocity within a first preset time period if it is detected that the wheel speed states of each wheel are normal.

[0125] The first comparison subunit is used to compare each difference in the set with a preset first threshold value, and determine the number of differences greater than the first threshold value.

[0126] The second comparison subunit is used to compare the number of differences with a preset second threshold.

[0127] The first determination subunit is configured to determine that, if the number of differences is less than a second threshold, the first abnormality detection result is that the second heading angular velocity is normal.

[0128] The second determining subunit is used to determine that if the number of differences is not less than a second threshold value, the first abnormality detection result is a second heading angular velocity abnormality.

[0129] In this embodiment, the specific execution process of the detection subunit, the set generation subunit, the first comparison subunit, the second comparison subunit, the first determination subunit and the second determination subunit can be referred to in the corresponding Figure 2 The content of the method embodiment will not be repeated here.

[0130] Optionally, in another embodiment of the present application, an implementation of the second detection unit 304 includes:

[0131] The first generating subunit is used to calculate the average value of each second heading angular velocity within a second preset time period when the vehicle is in a static state, and use the average value as the zero bias value.

[0132] In this embodiment, the specific execution process of the first generating subunit can be found in the corresponding method embodiment described above, and will not be repeated here.

[0133] Optionally, in another embodiment of the present application, an implementation of the second detection unit 304 includes:

[0134] The estimation subunit is used to estimate the heading angular velocity through Kalman filtering when the vehicle is in a dynamic state to obtain an estimated heading angular velocity;

[0135] The fourth calculation subunit is used to calculate the difference between the estimated heading angular velocity and the second heading angular velocity, and use the difference as the zero bias value.

[0136] In this embodiment, the specific execution process of the estimation subunit and the fourth calculation subunit can be found in the corresponding method embodiment described above, which will not be repeated here.

[0137] Optionally, in another embodiment of the present application, the above-mentioned device for detecting abnormal heading angular velocity may further include:

[0138] The switching unit is used to control the vehicle speed according to a preset scheme and switch the inertial measurement unit to a spare inertial measurement unit if it is determined that the second heading angular velocity is abnormal.

[0139] In this embodiment, the specific execution process of the switching unit can refer to the corresponding method embodiment content above, which will not be repeated here.

[0140] Another embodiment of the application also provides an electronic device, such as Figure 4 As shown, specifically including:

[0141] One or more processors 401 .

[0142] The storage device 402 stores one or more programs.

[0143] When one or more programs are executed by one or more processors 401 , the one or more processors 401 implement any one of the methods in the above embodiments.

[0144] Another embodiment of the present application further provides a computer storage medium on which a computer program is stored, wherein when the computer program is executed by a processor, any one of the methods in the above embodiments is implemented.

[0145] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0146] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

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

Claims

1. A method for detecting abnormal heading angular velocity, characterized in that: include: Obtaining turning parameters of the vehicle; wherein the turning parameters include inner wheel angular velocity, outer wheel angular velocity, turning radius, inner and outer wheel distance and vehicle turning angle; Based on the turning parameter, a first heading angular velocity of the vehicle is calculated; Using the first heading angular velocity to perform an abnormality detection on the second heading angular velocity to obtain a first abnormality detection result; wherein the second heading angular velocity is a heading angular velocity measured by an inertial measurement unit; Calculating a zero bias value of the second heading angular velocity, and performing an abnormality detection on the second heading angular velocity using the zero bias value to obtain a second abnormality detection result; In combination with the first abnormality detection result and the second abnormality detection result, it is determined whether the second heading angular velocity is abnormal.

2. The method according to claim 1, characterized in that The calculating, based on the turning parameter, a first heading angular velocity of the vehicle comprises: multiplying the difference between the inner wheel angular velocity and the outer wheel angular velocity by the turning radius to obtain a first product; Multiplying the inner and outer wheel distances by the cosine value of the vehicle turning angle to obtain a second product; The first product is divided by the second product to obtain the first heading angular velocity.

3. The method according to claim 1, characterized in that The using the first heading angular velocity to perform abnormality detection on the second heading angular velocity to obtain a first abnormality detection result includes: Detecting whether the wheel speed state of each wheel of the vehicle is normal; If it is detected that the wheel speed states of the wheels are all normal, a set of differences between the first heading angular velocity and the second heading angular velocity within a first preset time period is generated; Comparing each difference value in the set with a preset first threshold value, and determining the number of difference values ​​greater than the first threshold value; Comparing the number of differences with a preset second threshold; If the number of the differences is less than the second threshold, the first abnormality detection result is that the second heading angular velocity is normal; If the number of differences is not less than a second threshold, the first abnormality detection result is that the second heading angular velocity is abnormal.

4. The method according to claim 1, characterized in that: The calculating the zero bias value of the second heading angular velocity comprises: When the vehicle is in a static state, an average value of each of the second heading angular velocities within a second preset time period is calculated, and the average value is used as the zero bias value.

5. The method according to claim 1, characterized in that The calculating the zero bias value of the second heading angular velocity comprises: When the vehicle is in dynamic state, the heading angular velocity is estimated through Kalman filtering to obtain the estimated heading angular velocity; A difference between the estimated heading angular velocity and the second heading angular velocity is calculated and used as the zero bias value.

6. The method according to claim 1, characterized in that After combining the first abnormality detection result and the second abnormality detection result to determine whether the second heading angular velocity is abnormal, the method further includes: If it is determined that the second heading angular velocity is abnormal, the vehicle speed is controlled according to a preset scheme, and the inertial measurement unit is switched to a backup inertial measurement unit.

7. A device for detecting abnormal heading angular velocity, characterized in that: include: An acquisition unit, used for acquiring turning parameters of the vehicle; wherein the turning parameters include an inner wheel angular velocity, an outer wheel angular velocity, a turning radius, a distance between the inner and outer wheels, and a vehicle turning angle; A calculation unit, configured to calculate a first heading angular velocity of the vehicle based on the turning parameter; a first detection unit, configured to perform an abnormality detection on a second heading angular velocity using the first heading angular velocity to obtain a first abnormality detection result; wherein the second heading angular velocity is a heading angular velocity measured by an inertial measurement unit; a second detection unit, configured to calculate a zero bias value of the second heading angular velocity, and perform an abnormality detection on the second heading angular velocity using the zero bias value to obtain a second abnormality detection result; A determination unit is used to determine whether the second heading angular velocity is abnormal in combination with the first abnormality detection result and the second abnormality detection result.

8. The device according to claim 7, characterized in that The computing unit comprises: a first calculation subunit, configured to multiply the difference between the inner wheel angular velocity and the outer wheel angular velocity by the turning radius to obtain a first product; A second calculation subunit is used to multiply the inner and outer wheel distances by the cosine value of the vehicle turning angle to obtain a second product; The third calculation subunit is used to divide the first product by the second product to obtain the first heading angular velocity.

9. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method according to any one of claims 1 to 6.

10. A computer storage medium, characterized in that: A computer program is stored thereon, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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