Control method, apparatus, device, and product

Abstract

This invention provides a control method, device, equipment, and product. The method includes: determining whether an inertial measurement unit (IMU) is malfunctioning based on vehicle attitude information; and disabling the vehicle's driver assistance functions if the IMU is malfunctioning. This method uses data collected by the IMU to determine if it is malfunctioning, and disables driver assistance functions if an malfunction is found, thus preventing safety risks due to IMU failure and effectively protecting the safety of drivers and passengers.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and in particular to a control method, device, equipment, and product. Background Technology

[0002] Advanced autonomous driving is a crucial step in the development of intelligent electric vehicles. High-precision positioning is indispensable for advanced autonomous driving, and the current mainstream approach to high-precision positioning utilizes Inertial Navigation System (INS) algorithms. INS algorithms involve the fusion of multiple sensors, including GNSS Real-Time Kinematic (GNSS-RTK), Inertial Measurement Unit (IMU), wheel speed, gear position, and other vehicle information. Even in areas with weak satellite signals, dead reckoning (DR) can still provide vehicle pose information. DR calculations primarily rely on the vehicle's own information. The mainstream approach is to integrate chassis information and IMU data. Due to cost and size limitations of onboard sensors, onboard IMUs typically employ gyroscopes and accelerometers based on Micro-Electro-Mechanical Systems (MEMS).

[0003] IMUs using MEMS structures have advantages such as small size, low cost, and low power consumption, and can achieve high accuracy through professional calibration. However, MEMS IMUs must withstand the complex environment of a vehicle, such as vibration, shock, and radiation. These factors can alter the characteristics of MEMS devices. Such situations can lead to data anomalies in the IMU, such as data failure with no output or hardware zero-position anomalies. Zero-position anomalies have a significant impact on the vehicle. If the vehicle's IMU zero-position deviation is large, it can cause INS divergence, affecting the output vehicle pose information and thus impacting vehicle assistance and navigation functions to varying degrees. Especially in driver assistance, if the vehicle's pose exhibits unusual anomalies, issues such as abnormal steering or false triggering of the Autonomous Emergency Braking (AEB) system can occur, endangering the safety of vehicle occupants. Summary of the Invention

[0004] This invention provides a control method, device, equipment, and product that enables early prediction of whether an inertial measurement unit (IMU) will malfunction, effectively avoiding safety issues such as navigation and assisted driving malfunctions caused by IMU malfunctions leading to vehicle posture abnormalities.

[0005] Firstly, this embodiment provides a control method, the method comprising:

[0006] Based on the vehicle attitude information, determine whether there is any abnormality in the inertial measurement unit;

[0007] If the inertial measurement unit malfunctions, the vehicle's driver assistance functions will be disabled.

[0008] Secondly, this embodiment provides a control device, the device comprising:

[0009] The anomaly detection module is used to determine whether there is an anomaly in the inertial measurement unit based on the vehicle attitude information.

[0010] The function disable module is used to disable the vehicle's driver assistance functions if the inertial measurement unit malfunctions.

[0011] Thirdly, this embodiment provides an electronic device, including:

[0012] At least one processor; and

[0013] A memory communicatively connected to the at least one processor; wherein,

[0014] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the control method described in any embodiment of the present invention.

[0015] Fourthly, this embodiment provides a computer-readable storage medium, wherein the computer program is executed by the at least one processor to enable the at least one processor to perform the control method described in any embodiment of the present invention.

[0016] Fifthly, embodiments of the present invention also provide a computer program product, the computer program product including a computer program, which, when executed by a processor, implements the control method as described in any embodiment of the present invention.

[0017] This invention provides a control method, apparatus, and device. The method includes: firstly, determining whether an inertial measurement unit (IMU) exhibits zero-bias over-limit anomaly based on vehicle attitude information; then, if the IMU exhibits a zero-bias over-limit anomaly, disabling the vehicle's driver assistance functions. This technical solution determines whether the IMU has an anomaly based on data collected by the IMU, and disables the driver assistance functions if an anomaly is found. By adding judgment logic through algorithmic processing without adding any sensors, it effectively avoids safety and user experience issues such as navigation and driver assistance anomalies caused by IMU anomalies leading to vehicle posture abnormalities.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the principle of a gyroscope and accelerometer based on a microelectromechanical system;

[0021] Figure 2 This is a flowchart illustrating a control method provided in Embodiment 1 of the present invention;

[0022] Figure 3 This is a flowchart illustrating another control method provided in Embodiment 2 of the present invention;

[0023] Figure 4 This is a flowchart illustrating the execution of a control method in a specific application scenario, as provided in Embodiment 2 of the present invention.

[0024] Figure 5 This is a schematic diagram of the structure of a control device provided in Embodiment 3 of the present invention;

[0025] Figure 6 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] In recent years, with the continuous development of electric vehicles, automotive intelligence has gradually moved towards intelligentization, following the rise of the electronics industry. Among these advancements, the continuously improving advanced autonomous driving has become a crucial step in the development of electric vehicle intelligence. Advanced autonomous driving relies heavily on high-precision positioning, and the current mainstream approach to high-precision positioning is through the Inertial Navigation System (INS) algorithm. Unlike traditional GNSS positioning, which is heavily dependent on satellite signals, the INS algorithm is a multi-sensor fusion approach, incorporating vehicle information such as GNSS-RTK, IMU, wheel speed, and gear position. Even in areas with weak satellite signals, it can still rely on DR (Depth Measurement) to calculate and provide vehicle pose information (the accuracy of DR varies depending on the algorithm and sensor precision, but all accumulate errors over time).

[0029] When performing calculations, DR primarily relies on information from the vehicle itself. The mainstream approach is to integrate chassis information (including wheel speed and gear position) with IMU data. Due to limitations in cost and size of onboard sensors, onboard IMUs typically employ MEMS-based gyroscopes and accelerometers. Figure 1 This is a schematic diagram of the principle of a gyroscope and accelerometer based on a microelectromechanical system. Simply put, by amplifying and converting the capacitance changes generated between a fixed substrate and a movable substrate, the motion quantities in different directions can be obtained, and thus the angular velocity and acceleration in different directions can be mapped.

[0030] IMUs using MEMS structures have advantages such as small size, low cost, and low power consumption, and can achieve high accuracy through professional calibration. However, MEMS IMUs must withstand the complex environment of a vehicle, including vibration, shock, and radiation. These factors can alter the characteristics of MEMS devices. Such situations can lead to data anomalies in the IMU, such as data loss, no output, or hardware zero-point anomalies. Zero-point anomalies have a significant impact on the vehicle. If the vehicle's IMU zero-point deviation is large, it can cause INS divergence, affecting the output vehicle pose information and impacting functions such as driver assistance and navigation to varying degrees. Especially in driver assistance, abnormal vehicle pose can lead to issues such as abnormal steering or false triggering of AEB (Autonomous Emergency Braking), endangering the safety of vehicle occupants.

[0031] Example 1

[0032] Figure 2 This is a flowchart illustrating a control method provided in Embodiment 1 of the present invention. This method is applicable to vehicle control based on anomaly detection of an inertial measurement unit. The method can be executed by a control device, which can be implemented in hardware and / or software and is generally integrated into an electronic device.

[0033] like Figure 2 As shown in the first embodiment, a control method is provided, in which an inertial measurement unit is installed in the vehicle. The method includes:

[0034] S101. Based on the vehicle attitude information, determine whether there is any abnormality in the inertial measurement unit.

[0035] While existing solutions for intelligent vehicles widely utilize MEMS-based inertial measurement units (IMUs), they lack adequate safety verification and control measures for IMUs experiencing performance failures under bias anomalies. This leads to issues such as navigation malfunctions and driver assistance function (ADAS) abnormalities caused by IMU bias anomalies in intelligent vehicles, with ADAS anomalies potentially posing safety risks. This embodiment addresses this by pre-determining whether the IMU bias is abnormal and reporting the fault via fault diagnosis information. This informs the downstream application layer and disables ADAS-related functions, minimizing the safety risks associated with ADAS anomalies caused by IMU bias anomalies.

[0036] The application scenario of this embodiment can be described as follows: based on existing vehicle information, sensor data, etc., without adding any other components, the system pre-determines whether the inertial measurement unit has zero bias exceeding the limit, and then controls the vehicle based on the determination result to avoid safety issues such as navigation abnormalities and assisted driving abnormalities caused by abnormal vehicle posture due to abnormal inertial measurement unit.

[0037] In this embodiment, scene judgment, logical judgment, and historical memory functions are used to determine whether the inertial measurement unit (IMU) has a zero-bias over-limit anomaly. For scene judgment, it is necessary to first determine whether the vehicle is currently stationary. The vehicle's stationary state means that the vehicle is stationary relative to the ground. It can be considered that the vehicle's current stationary state is a prerequisite for further judging whether to perform zero-bias over-limit anomaly on the IMU.

[0038] In this embodiment, vehicle attitude information can be collected by the inertial measurement unit (IMU) over a period of time, and the presence of zero bias exceeding the limit can be determined based on this information. Vehicle attitude information may include angular velocity measured by the onboard MEMS gyroscope and vehicle acceleration collected by the accelerometer. For example, by collecting gyroscope data over a period of time and observing the percentage of stationary gyroscope data exceeding a threshold, if the percentage exceeds the threshold, it is recorded that the IMU is unavailable, indicating a zero bias exceeding the limit issue. This determination is only valid within the current power-on cycle.

[0039] Specifically, the steps for determining whether the inertial measurement unit (IMU) has a zero-bias over-limit anomaly based on vehicle attitude information can be described as follows: obtain the angular velocities measured by the IMU within a set time period; determine the proportion of angular velocities greater than a set angular velocity threshold to the total number of angular velocities; if the proportion is greater than a set percentage threshold, then the IMU has a zero-bias over-limit anomaly; if the proportion is less than or equal to the set percentage threshold, then the IMU does not have a zero-bias over-limit anomaly.

[0040] S102. If the inertial measurement unit has an out-of-range zero bias, then the vehicle's driver assistance functions will be disabled.

[0041] In this embodiment, if the inertial measurement unit (IMU) exhibits a zero-bias over-limit anomaly, a Diagnostic Trouble Code (DTC) is generated. This DTC indicates that the IMU has experienced a zero-bias over-limit anomaly. The DTC is then sent to the downstream application layer, which disables the vehicle's driver assistance functions. This approach avoids the safety risks associated with driver assistance function malfunctions caused by IMU zero-bias anomalies. These driver assistance functions may include autonomous driving, lane keeping assist, emergency avoidance, active safety features, and other functions that utilize the IMU or its generated data.

[0042] It should be noted that if the inertial measurement unit (IMU) does not exhibit any zero-bias over-limit anomalies within a power-on cycle, monitoring of the IMU will continue. Conversely, if the IMU exhibits a zero-bias over-limit anomaly within a power-on cycle, the vehicle's driver assistance functions will be disabled for the remainder of that cycle.

[0043] Understandably, in response to the problems existing in the inertial measurement units of the current automotive MEMS structure, the judgment logic of the existing sensor data source is adopted. The algorithm calculates and judges whether there is an abnormality in the inertial measurement unit, and then reports the fault diagnosis information to the whole vehicle in a positive way. This avoids the safety risks caused by the failure of the inertial measurement unit and prevents some abnormal problems from occurring, thus effectively protecting the safety of the occupants.

[0044] This invention provides a control method that uses data collected by an inertial measurement unit (IMU) to determine if the IMU is malfunctioning. If an malfunction is detected, the assisted driving function is disabled. Without adding any sensors, an algorithmic processing method is used to add judgment logic to determine if the IMU has zero-bias over-limit anomalies. This effectively avoids safety and user experience issues such as navigation malfunctions and assisted driving malfunctions caused by IMU malfunctions leading to abnormal vehicle posture.

[0045] As an optional embodiment of the present invention, the method can be further optimized based on the above embodiments by including:

[0046] a1) Determine the current status of the vehicle.

[0047] In this embodiment, scene judgment, logical judgment, and historical memory functions are used to determine whether the inertial measurement unit (IMU) has zero bias exceeding the limit anomaly. For scene judgment, it is necessary to first determine whether the vehicle is currently stationary. This can be done by using the vehicle's chassis information as a basic indicator; further, it can be done by combining information collected by the sensors in the IMU; or, more specifically, by using vehicle information collected by GNSS to further determine whether the vehicle is stationary, thus avoiding the vehicle being in a state of forced movement. Based on the above description, it is possible to determine whether the vehicle is stationary.

[0048] Considering that the vehicle is not stationary, its angular velocity and acceleration are not at absolute zero. If the vehicle's inertial measurement unit is already malfunctioning, it is inaccurate to characterize whether there is an abnormality based on the data from the inertial measurement unit. It is necessary to perform anomaly detection on the inertial measurement unit when the vehicle is stationary.

[0049] As a specific implementation method, the steps for determining the current state of the vehicle can be optimized, including:

[0050] a11) Obtain vehicle chassis information, inertial measurement unit variance information, and global navigation satellite system characterization status information.

[0051] The vehicle's chassis information includes wheel speeds and gear position; the inertial measurement unit's variance information includes the variance of angular velocity measured by the gyroscope and the variance of acceleration measured by the accelerometer; and the Global Navigation Satellite System's characterization status information includes the horizontal velocity measured by GNSS corresponding to the GNSS fixed solution. This step is used to obtain the above information to determine whether the vehicle is stationary.

[0052] a12) Determine whether the chassis information meets the first set condition, whether the variance information meets the second set condition, and whether the characterization state information meets the third set condition.

[0053] Specifically, it determines whether the vehicle's wheel speed and gear position meet the first set condition, whether the angular velocity variance measured by the gyroscope and the acceleration variance measured by the accelerometer in the inertial measurement unit meet the second set condition, and whether the GNSS fixed solution and the horizontal velocity measured by the GNSS meet the third set condition.

[0054] As a specific implementation method, determining whether the chassis information meets the first set condition, whether the variance information meets the second set condition, and whether the characterization state information meets the third set condition includes:

[0055] a121) If the current wheel speed in the chassis information is less than the set wheel speed threshold and the current gear is the parking gear, then the chassis information is determined to meet the first set condition.

[0056] The wheel speed threshold can be set according to actual conditions. Specifically, the current wheel speed of the vehicle in the chassis information is compared with the set wheel speed threshold, and it is determined whether the current gear is park (P). This information can be considered the most basic information for determining whether the vehicle is stationary. If the current wheel speed is less than the set wheel speed threshold and the current gear is park, then the chassis information is determined to meet the first set condition.

[0057] a122) If the current wheel speed in the chassis information is greater than or equal to the set wheel speed threshold or the current gear is not the parking gear, then the chassis information does not meet the first set condition.

[0058] Specifically, if the current wheel speed is greater than or equal to the set wheel speed threshold or the current gear is not a parking gear, it is determined that the chassis information does not meet the first set condition, and at this time it can be determined that the vehicle is in a non-stationary state.

[0059] a123) If the current angular velocity variance in the variance information is less than the set angular velocity variance threshold and the current acceleration variance is less than the set acceleration variance threshold, then the variance information is determined to meet the second set condition.

[0060] The threshold values ​​for angular velocity variance and acceleration variance can be set according to actual conditions. Specifically, the current angular velocity variance of the vehicle in the variance information is compared with the set angular velocity variance threshold, and the current acceleration variance of the vehicle is compared with the set acceleration variance threshold. If the current angular velocity variance in the variance information is less than the set angular velocity variance threshold and the current acceleration variance is less than the set acceleration variance threshold, then the variance information is determined to meet the second set condition.

[0061] a124) If the current angular velocity variance in the variance information is greater than or equal to the set angular velocity variance threshold or the current acceleration variance is greater than or equal to the set acceleration variance threshold, then it is determined that the variance information does not meet the second set condition.

[0062] Specifically, if the current angular velocity variance in the variance information is greater than or equal to the set angular velocity variance threshold or the current acceleration variance is greater than or equal to the set acceleration variance threshold, then it is determined that the variance information does not meet the second set condition, and at this time it can be determined that the vehicle is in a non-stationary state.

[0063] a125) If the horizontal velocity corresponding to the fixed solution in the characterization state information is less than the set horizontal velocity threshold, then the characterization state information is determined to satisfy the third set condition.

[0064] The horizontal velocity threshold can be set according to the actual situation. The horizontal velocity corresponding to the fixed solution refers to the horizontal velocity with high accuracy. Specifically, the horizontal velocity corresponding to the fixed solution in the characterization state information is compared with the set horizontal velocity threshold. If the horizontal velocity corresponding to the fixed solution in the characterization state information is less than the set horizontal velocity threshold, then the characterization state information is determined to meet the third set condition.

[0065] It's important to note that a vehicle being in a "hijacked motion" state typically refers to a situation where the vehicle is forced into involuntary movement due to some external force, such as a vehicle placed on a ship and moving with it. When a vehicle is in a hijacked motion state, its wheel speed is zero and the gear is in Park (P), but the vehicle is still moving relative to the ground. The inertial measurement unit (IMU) will detect this as motion. Combining this with GNSS state information can determine whether the vehicle is truly stationary or in a hijacked motion state. For vehicles in a hijacked motion state, using the IMU to detect zero-bias anomalies is inaccurate; the vehicle must be truly stationary before any anomaly detection is made. Using GNSS state information to further determine whether the vehicle is stationary avoids misjudgments caused by a hijacked motion state. This effectively avoids misjudgments in special scenarios (such as trailers and ferries in hijacked motion) while ensuring the accuracy of the reported data and the robustness of the algorithm.

[0066] a126) If the horizontal velocity corresponding to the fixed solution in the characterization state information is greater than or equal to the set horizontal velocity threshold, then it is determined that the characterization state information does not meet the third set condition.

[0067] Specifically, if the horizontal velocity corresponding to the fixed solution in the characterization state information is greater than or equal to the set horizontal velocity threshold, then it is determined that the characterization state information does not meet the third set condition, and at this time it can be determined that the vehicle is in a non-stationary state.

[0068] The above details the steps for determining whether the chassis information meets the first set condition, whether the variance information meets the second set condition, and whether the characterization state information meets the third set condition.

[0069] a13) If all the set conditions are met and the duration exceeds the set time threshold, then the current state of the vehicle is determined to be stationary.

[0070] The time threshold can be set according to actual conditions, and no specific restrictions are imposed here. In this embodiment, the vehicle's stationary state is determined by combining the performance of each set condition over a period of time. In this embodiment, if the vehicle's current state meets all set conditions and the duration of this satisfaction exceeds the set time threshold, then the vehicle's current state is confirmed as stationary. It should be noted that combining the performance of the vehicle over a period of time with each set condition improves the stability of the logic. Furthermore, due to the diversity of conditions, the probability of misjudgment can be greatly reduced, improving the accuracy of the judgment.

[0071] a14) Otherwise, the current state of the vehicle is determined to be non-stationary.

[0072] In this embodiment, if the current state of the vehicle does not meet the set conditions, or meets the set conditions but the duration does not reach the set time threshold, then the current state of the vehicle is determined to be a non-stationary state.

[0073] The above technical solution specifies the steps for determining the current state of the vehicle, providing a prerequisite for subsequent judgment on whether to perform zero-bias over-limit anomaly of the inertial measurement unit, and making the detection results more accurate.

[0074] b1) If the vehicle is currently stationary, acquire the vehicle attitude information collected by the inertial measurement unit within a set time period.

[0075] Specifically, if the vehicle is currently stationary, the system further determines whether the inertial measurement unit (IMU) has an excessive zero bias based on existing sensor data. This step involves acquiring vehicle attitude information collected by the IMU over a set time period. This vehicle attitude information may include angular velocity measured by the onboard MEMS gyroscope, vehicle acceleration collected by the accelerometer, etc. In this embodiment, the system can determine whether the IMU has an excessive zero bias based on vehicle attitude information collected over a period of time.

[0076] The above technical solution specifies the limiting conditions and methods for acquiring vehicle attitude information, and enables scenario judgment for abnormalities in the inertial measurement unit.

[0077] As an optional embodiment of the present invention, based on the above embodiments, after determining whether the inertial measurement unit is abnormal, the method may further include:

[0078] a2) If the inertial measurement unit is abnormal, record the flag as unavailable and write the flag into memory.

[0079] In this embodiment, if the inertial measurement unit has a zero bias over-limit anomaly, then after the vehicle has completed driving in the current power-on cycle, a flag indicating that the inertial measurement unit is unavailable is recorded and written into memory before the vehicle is powered off in the current ignition cycle.

[0080] b2) If there is no abnormality in the inertial measurement unit, record the flag as available and write the flag into memory.

[0081] In this embodiment, if the inertial measurement unit does not have a zero bias over-limit anomaly, then after the vehicle has completed driving in this power-on cycle, the available flag bit of the inertial measurement unit is recorded once and written into memory before the vehicle is powered off in this ignition cycle.

[0082] Furthermore, based on the above optional embodiments, the method can be optimized to include the following when the vehicle is powered on:

[0083] a3) Access memory to obtain the status of the flag bit set in the previous power-on cycle.

[0084] The specific number of power-on cycles is not limited and can be set according to actual conditions; for example, the first set of power-on cycles could be the first three power-on cycles. In this embodiment, each time the vehicle is powered on, the flag bits stored in memory are checked, and the status of the flag bits for the first set of power-on cycles is retrieved from the memory. In the first set of power-on cycles, each power-on cycle corresponds to a flag bit status, and the status of each flag bit may be either that the inertial measurement unit is unavailable or that the inertial measurement unit is available.

[0085] b3) If the status of the flag bits in the memory is "inertial measurement unit unavailable" in the first set power-on cycles, then the vehicle's driver assistance functions will be disabled.

[0086] Specifically, if this flag indicates that the inertial measurement unit (IMU) has been unavailable for several consecutive cycles in the past, the vehicle's driver assistance functions will be disabled directly upon power-on, and the user will be notified that the IMU is faulty. This fault will be reported via fault diagnosis information, informing the downstream application layer to disable driver assistance functions and suggesting repair. Additionally, a recoverable logic is included, allowing the user to restore the system with a single click.

[0087] c3) Otherwise, use the vehicle's driver assistance functions normally and perform the abnormal detection procedure for the inertial measurement unit.

[0088] Specifically, if the inertial measurement unit (IMU) is available in the flag position of the previous set cycle, the vehicle's driver assistance functions will not be disabled, and the anomaly detection steps for the IMU will continue. For example, if the user has memorized the normal flag position for the past three ignition cycles, no user functions will be disabled.

[0089] The above technical solution adds the function of historical memory judgment. By using the judgment of the flag bit in advance for a set power-on cycle, it can avoid the possible misjudgment of a single ignition cycle, effectively avoid the safety risks caused by the failure of the inertial measurement unit and some abnormal problems, and protect the safety of the occupants.

[0090] Example 2

[0091] Figure 3 This is a flowchart illustrating another control method provided in Embodiment 2 of the present invention. This embodiment is a further optimization of the above embodiment. In this embodiment, the limitation on "determining whether there is an abnormality in the inertial measurement unit based on the vehicle attitude information" is further optimized.

[0092] like Figure 3 As shown, this embodiment two provides a control method, which specifically includes the following steps:

[0093] S201. Obtain the angular velocity measured by the inertial measurement unit within a set time period.

[0094] The set time can be adjusted according to actual conditions. Vehicle attitude information includes angular velocity measured by the onboard MEMS gyroscope and vehicle acceleration collected by the accelerometer. This step primarily uses the angular velocity measured by the onboard MEMS gyroscope as the judgment criterion, recording it as the angular velocity measured by the inertial measurement unit. The angular velocity measured by the inertial measurement unit within the set time is then obtained.

[0095] S202. Determine the proportion of the number of angular velocities greater than the set angular velocity threshold to the total number of angular velocities.

[0096] Specifically, the angular velocities acquired within a set time period are compared with a set angular velocity threshold, and the proportion of angular velocities greater than the set angular velocity threshold to the total number of angular velocities is further determined.

[0097] S203. If the ratio is greater than the set percentage threshold, it is determined that the inertial measurement unit has an out-of-limit zero bias anomaly.

[0098] Specifically, if the proportion is greater than the set percentage threshold, it is determined that the inertial measurement unit has an out-of-range zero bias anomaly.

[0099] S204. If the ratio is less than or equal to the set ratio threshold, then it is determined that the inertial measurement unit does not have a zero bias over-limit anomaly.

[0100] Specifically, if the percentage is less than or equal to a set percentage threshold, it is determined that the inertial measurement unit (IMU) does not have a zero-bias over-limit anomaly. For example, by collecting gyroscope data over a period of time and observing the percentage of gyroscope data exceeding a threshold in the total data volume when stationary, if the percentage is greater than the percentage threshold, it is recorded that the IMU is unavailable, that is, it is determined that the IMU has a zero-bias over-limit problem at this time, and this is only valid within the current power-on cycle.

[0101] S205. If the inertial measurement unit has an out-of-limit zero bias anomaly, the vehicle's driver assistance functions shall be disabled.

[0102] The aforementioned technical solution specifies the steps for determining whether the inertial measurement unit (IMU) has an abnormal zero-bias deviation. Without adding any sensors, it incorporates algorithmic processing to enhance the judgment logic and determine if the zero-bias of the onboard MEMS gyroscope is abnormal, demonstrating strong robustness. By reporting fault diagnosis information, it informs the downstream application layer and disables related driver assistance functions, minimizing the safety risks associated with driver assistance function malfunctions caused by IMU zero-bias deviation. It effectively avoids safety and user experience issues such as navigation and driver assistance malfunctions caused by abnormal vehicle posture due to IMU anomalies.

[0103] To more clearly illustrate the control method provided by this embodiment of the invention, an example of vehicle control based on anomaly detection using an inertial measurement unit in a practical application scenario will be used. For example, Figure 4 This is a flowchart illustrating the execution of a control method in a specific application scenario provided in Embodiment 2 of the present invention. Figure 4 As shown, the execution steps of the control method specifically include:

[0104] S1. When the vehicle is powered on, access the memory to obtain the status of the flag bits in the first three power-on cycles. If the status of the flag bits in the memory in the first three power-on cycles is that the inertial measurement unit is unavailable, then execute step 10; otherwise, execute step S2.

[0105] S2. Obtain vehicle chassis information, inertial measurement unit variance information, and global navigation satellite system characterization status information.

[0106] S3. Determine whether the chassis information meets the first set condition, the variance information meets the second set condition, and the characterization state information meets the third set condition, and whether all set conditions are met and the duration exceeds the set time threshold. If not, proceed to step S4; if yes, proceed to step S5.

[0107] S4. Determine that the vehicle's current state is non-stationary.

[0108] S5. Determine that the current state of the vehicle is stationary.

[0109] S6. If the vehicle is currently stationary, acquire the vehicle attitude information collected by the inertial measurement unit within a set time period.

[0110] S7. Obtain the angular velocity measured by the inertial measurement unit within a set time period.

[0111] S8. Determine the proportion of the number of angular velocities greater than the set angular velocity threshold to the total number of angular velocities.

[0112] S9. If the ratio is greater than the set ratio threshold, it is determined that the inertial measurement unit has an out-of-limit zero bias anomaly.

[0113] S10. If the inertial measurement unit has a zero bias over-limit anomaly, generate diagnostic fault information and send it to the downstream application layer to disable the vehicle's driver assistance functions.

[0114] S11. If the inertial measurement unit has a zero bias over-limit anomaly, record the flag as unavailable and write the flag into memory.

[0115] S12. If the ratio is less than or equal to the set ratio threshold, it is determined that the inertial measurement unit does not have a zero bias over-limit anomaly.

[0116] S13. If the inertial measurement unit does not have a zero bias over-limit anomaly, record the flag as available for the inertial measurement unit and write the flag into memory.

[0117] Example 3

[0118] Figure 5 This is a schematic diagram of a control device provided in Embodiment 3 of the present invention. This device is applicable to vehicle control based on inertial measurement unit (IMU) anomaly detection. An IMU is installed in the vehicle. This control device can be implemented in hardware and / or software and is generally integrated into an electronic device. For example... Figure 5 As shown, the device includes: an anomaly detection module 31 and a function disabling module 32, wherein,

[0119] The anomaly detection module 32 is used to determine whether there is an anomaly in the inertial measurement unit based on the vehicle attitude information;

[0120] The function disable module 33 is used to disable the vehicle's driver assistance functions if the inertial measurement unit has an out-of-limit zero bias anomaly.

[0121] The above technical solution uses data collected by the inertial measurement unit (IMU) to determine if there are any anomalies in the IMU. If an anomaly is found, the assisted driving function is disabled. Without adding any sensors, an algorithmic processing method is used to add judgment logic to determine if the IMU has any zero-bias over-limit anomalies. This effectively avoids safety and user experience issues such as navigation malfunctions and assisted driving anomalies caused by IMU anomalies leading to abnormal vehicle posture.

[0122] Optionally, the device further includes an information acquisition module, which includes:

[0123] The state determination unit determines the current state of the vehicle;

[0124] The information acquisition unit is used to acquire vehicle attitude information collected by the inertial measurement unit within a set time if the vehicle is currently stationary.

[0125] Optionally, the state determination unit includes:

[0126] The information acquisition subunit is used to acquire chassis information of the vehicle, variance information of the inertial measurement unit, and characterization status information of the global navigation satellite system.

[0127] The condition judgment subunit is used to determine whether the chassis information meets the first set condition, whether the variance information meets the second set condition, and whether the characterization state information meets the third set condition.

[0128] The stationary determination subunit is used to determine that the current state of the vehicle is stationary if all set conditions are met and the duration exceeds a set time threshold.

[0129] The non-stationary determination sub-unit is used to determine that the current state of the vehicle is non-stationary otherwise.

[0130] Optionally, the conditional judgment subunit is specifically used for:

[0131] If the current wheel speed in the chassis information is less than the set wheel speed threshold and the current gear is the parking gear, then the chassis information is determined to meet the first set condition.

[0132] If the current wheel speed is greater than or equal to the set wheel speed threshold or the current gear is not the parking gear, then the chassis information does not meet the first set condition.

[0133] If the current angular velocity variance in the variance information is less than the set angular velocity variance threshold and the current acceleration variance is less than the set acceleration variance threshold, then the variance information is determined to meet the second set condition.

[0134] If the current angular velocity variance in the variance information is greater than or equal to the set angular velocity variance threshold or the current acceleration variance is greater than or equal to the set acceleration variance threshold, then it is determined that the variance information does not meet the second set condition.

[0135] If the horizontal velocity corresponding to the fixed solution in the characterization state information is less than the set horizontal velocity threshold, then the characterization state information is determined to meet the third set condition.

[0136] If the horizontal velocity corresponding to the fixed solution in the characterization state information is greater than or equal to the set horizontal velocity threshold, then it is determined that the characterization state information does not meet the third set condition.

[0137] Optionally, the exception detection module 31 is specifically used for:

[0138] Obtain the angular velocity measured by the inertial measurement unit within a set time period;

[0139] Determine the proportion of angular velocities exceeding a set angular velocity threshold out of the total number of angular velocities;

[0140] If the proportion is greater than the set proportion threshold, it is determined that the inertial measurement unit has an out-of-limit zero bias anomaly.

[0141] If the proportion is less than or equal to the set proportion threshold, it is determined that the inertial measurement unit does not have a zero bias over-limit anomaly.

[0142] Optionally, the device further includes a flag recording module, which, after determining whether the inertial measurement unit has an out-of-limit zero bias anomaly, is used to:

[0143] If the inertial measurement unit is faulty, record the flag as unavailable and write the flag into memory;

[0144] If the inertial measurement unit is not faulty, the flag is recorded as available and written into memory.

[0145] Optionally, the device also includes a flag determination module, which, when the vehicle is powered on, is specifically used for:

[0146] Access memory to obtain the status of the flag bit set in the previous power-on cycles;

[0147] If the status of the flag bits in memory is "inertial measurement unit unavailable" in the previous set power-on cycles, then the vehicle's driver assistance functions will be disabled.

[0148] Otherwise, use the vehicle's driver assistance functions normally and perform the abnormality detection procedure for the inertial measurement unit.

[0149] The control device provided in the embodiments of the present invention can execute the control method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0150] Example 4

[0151] Figure 6 This is a schematic diagram of an electronic device according to Embodiment 4 of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0152] like Figure 6 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 or a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded into the RAM 43 from storage unit 48. The RAM 43 may also store various programs and data required for the operation of the electronic device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0153] Multiple components in electronic device 40 are connected to I / O interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0154] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as control methods.

[0155] In some embodiments, the control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the control method described above may be performed. Alternatively, in other embodiments, processor 41 may be configured to execute the control method by any other suitable means (e.g., by means of firmware).

[0156] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0157] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0158] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0159] To provide interaction with the user, the systems and technologies described herein can be implemented in a vehicle having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the vehicle. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0160] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0161] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0162] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the control method provided in any embodiment of this invention.

[0163] In implementing a computer program product, computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include, but are not limited to, object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0164] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0165] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A control method characterized by, include: Based on the vehicle attitude information, determine whether there is any abnormality in the inertial measurement unit; If the inertial measurement unit malfunctions, the vehicle's driver assistance functions will be disabled.

2. The method of claim 1, wherein, Before determining whether the inertial measurement unit is abnormal based on the vehicle attitude information, the method further includes: Determine the current state of the vehicle; If the vehicle is currently stationary, the vehicle attitude information collected by the inertial measurement unit within a set time period is obtained.

3. The method according to any one of claims 1-2, characterized in that, Determining the current state of the vehicle includes: Obtain the chassis information of the vehicle, the variance information of the inertial measurement unit, and the characterization status information of the global navigation satellite system; Determine whether the chassis information meets the first set condition, whether the variance information meets the second set condition, and whether the characterization state information meets the third set condition. If all the set conditions are met and the duration exceeds the set time threshold, then the current state of the vehicle is determined to be a stationary state. Otherwise, the current state of the vehicle is determined to be non-stationary.

4. The method of claim 3, wherein, The determination of whether the chassis information meets the first set condition, whether the variance information meets the second set condition, and whether the characterization state information meets the third set condition includes: If the current wheel speed in the chassis information is less than the set wheel speed threshold and the current gear is the parking gear, then the chassis information is determined to meet the first set condition. If the current wheel speed in the chassis information is greater than or equal to the set wheel speed threshold or the current gear is not the parking gear, then it is determined that the chassis information does not meet the first set condition. If the current angular velocity variance in the variance information is less than a set angular velocity variance threshold and the current acceleration variance is less than a set acceleration variance threshold, then the variance information is determined to satisfy the second set condition. If the current angular velocity variance in the variance information is greater than or equal to a set angular velocity variance threshold or the current acceleration variance is greater than or equal to a set acceleration variance threshold, then it is determined that the variance information does not meet the second set condition. If the horizontal velocity corresponding to the fixed solution in the characterization state information is less than the set horizontal velocity threshold, then the characterization state information is determined to satisfy the third set condition. If the horizontal velocity corresponding to the fixed solution in the characterization state information is greater than or equal to the set horizontal velocity threshold, then it is determined that the characterization state information does not meet the third set condition.

5. The method according to any one of claims 1 to 4, characterized in that, The step of determining whether there is an anomaly in the inertial measurement unit based on the vehicle attitude information includes: Obtain the angular velocity measured by the inertial measurement unit within a set time period; Determine the proportion of the number of angular velocities greater than a set angular velocity threshold to the total number of angular velocities; If the ratio is greater than the set ratio threshold, it is determined that the inertial measurement unit has a zero bias over-limit anomaly. If the ratio is less than or equal to the set percentage threshold, then it is determined that the inertial measurement unit does not have a zero bias over-limit anomaly.

6. The method according to any one of claims 1 to 5, characterized in that, After determining whether there is an anomaly in the inertial measurement unit, the process also includes: If the inertial measurement unit is faulty, a flag is recorded indicating that the inertial measurement unit is unavailable and the flag is written into memory. If the inertial measurement unit is not malfunctioning, the record flag is set to indicate that the inertial measurement unit is available and the flag is written into memory.

7. The method of claim 6, wherein, When the vehicle is powered on, it also includes: Access the memory to obtain the status of the flag bit in the previous set number of power-on cycles; If the status of the flag bits in the memory is unavailable for the inertial measurement unit in the previous set power-on cycles, then the vehicle's driver assistance function is disabled. Otherwise, the vehicle's driver assistance functions are used normally, and anomaly detection steps for the inertial measurement unit are performed.

8. A control device characterized by comprising: include: The anomaly detection module is used to determine whether there is an anomaly in the inertial measurement unit based on the vehicle attitude information. The function disable module is used to disable the vehicle's driver assistance functions if the inertial measurement unit malfunctions.

9. An electronic device, comprising: include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the control method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the control method as described in any one of claims 1-7.

11. A computer program product, characterised in that, The computer program product includes a computer program that, when executed by a processor, implements the control method as described in any one of claims 1-7.

Images