Vehicle acceleration anomaly processing method and apparatus, storage medium, and vehicle

Abstract

The present invention relates to the technical field of autonomous driving, and disclosed are a vehicle acceleration anomaly processing method and apparatus, a storage medium, and a vehicle. The method comprises: acquiring a real-time acceleration command signal and an actual acceleration signal of a vehicle, wherein the acceleration command signal is used for representing a calculated desired acceleration to be achieved of the vehicle, and the actual acceleration signal is used for representing a measured actual achieved acceleration of the vehicle; on the basis of the acceleration command signal and the actual acceleration signal, performing acceleration anomaly detection on the vehicle to obtain a detection result; and in response to the detection result that an acceleration anomaly is present in the vehicle, adjusting an autonomous driving acceleration behavior of the vehicle on the basis of a target processing strategy, wherein the target processing strategy is determined on the basis of an anomaly category of the acceleration anomaly. The present invention solves the technical problem of low autonomous driving safety caused by high difficulty and low precision of the detection of acceleration anomalies in existing autonomous driving functions.

Description

Vehicle acceleration abnormality processing method, device, storage medium and vehicle Technical Field

[0001] The present invention relates to the field of autonomous driving technology, and in particular to a method, device, storage medium and vehicle for handling vehicle acceleration anomalies. Background Art

[0002] Driven by the growing trend toward intelligent, electrified, and connected vehicles, autonomous driving technology has become a key research area. Compared to L1 and L2 autonomous driving, L3 and above require the autonomous driving system to perform all driving operations and possess a fail-operation feature. This means that if a hardware failure or systemic failure occurs during autonomous driving, safety measures must be implemented to achieve a safe state (such as a safe stop) to ensure the safety of all road users.

[0003] The longitudinal electronic control part of the autonomous driving system usually includes a longitudinal control module, a driving and parking execution module, and a drive module. When an abnormality occurs in the drive module that slightly affects the torque execution accuracy (such as high temperature aging, mechanical vibration, calibration error, etc.), it may cause a slow acceleration execution deviation in the L3 level autonomous driving function. This slow acceleration execution deviation is difficult to detect through the drive module self-test, so it is very likely to cause the vehicle to accelerate slowly to the point of causing danger. The difficulty in detecting acceleration anomalies in the autonomous driving function and the low accuracy lead to low safety of autonomous driving, which has become one of the important technical issues in the relevant technical field.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far.

[0005] Summary of the Invention

[0006] Embodiments of the present invention provide a vehicle acceleration anomaly processing method, device, storage medium and vehicle to at least solve the technical problem that the detection of acceleration anomalies in existing autonomous driving functions is difficult and has low accuracy, resulting in low safety of autonomous driving.

[0007] According to one aspect of an embodiment of the present invention, a method for handling vehicle acceleration anomalies is provided, comprising: obtaining a real-time acceleration command signal and an actual acceleration signal of the vehicle, wherein the acceleration command signal is used to represent an expected acceleration to be executed calculated by the vehicle, and the actual acceleration signal is used to represent an actual executed acceleration measured by the vehicle; based on the acceleration command signal and the actual acceleration signal, performing acceleration anomaly detection on the vehicle to obtain a detection result; and in response to the detection result indicating that the vehicle has an acceleration anomaly, adjusting the vehicle's automatic driving acceleration behavior according to a target processing strategy, wherein the target processing strategy is determined by the anomaly category of the acceleration anomaly.

[0008] Optionally, based on the acceleration command signal and the actual acceleration signal, the vehicle is detected for acceleration anomaly, and the detection results obtained include: in response to the activation of the automatic driving function, determining the actual acceleration data from the actual acceleration signal, and determining the acceleration command data from the acceleration command signal; performing acceleration anomaly detection on the actual acceleration data and the acceleration command data to determine the detection results.

[0009] Optionally, determining the actual acceleration data from the actual acceleration signal and determining the acceleration command data from the acceleration command signal includes: based on multiple sampling moments, sampling from the actual acceleration signal to obtain multiple acceleration actual values ​​in the actual acceleration data; based on multiple sampling moments and the acceleration response time of the vehicle, sampling from the acceleration command signal to obtain multiple acceleration command values ​​in the acceleration command data.

[0010] Optionally, acceleration anomaly detection includes: acceleration deviation detection, performing acceleration anomaly detection on actual acceleration data and acceleration instruction data, and determining the detection result includes: performing acceleration deviation detection on actual acceleration data and acceleration instruction data, and in response to the actual acceleration deviation of the vehicle being greater than a first threshold, determining that the detection result is that the vehicle has a first acceleration anomaly, wherein the actual acceleration deviation is determined by the difference between the actual acceleration data and the acceleration instruction data, and the first threshold is the acceleration deviation threshold obtained from the safety metric analysis of the vehicle in an abnormal acceleration scenario.

[0011] Optionally, acceleration anomaly detection includes: acceleration deviation integral detection and unexpected acceleration duration detection, and acceleration anomaly detection is performed on the actual acceleration data and the acceleration instruction data. Determining the detection result also includes: when the actual acceleration deviation of the vehicle is less than or equal to the first threshold, acceleration deviation integral detection and unexpected acceleration duration detection are performed on the actual acceleration data and the acceleration instruction data; in response to the acceleration deviation integral of the vehicle being greater than the second threshold and the acceleration duration of the vehicle exceeding the third threshold, determining that the detection result is that the vehicle has a first acceleration anomaly; and in response to the acceleration deviation integral of the vehicle being greater than the second threshold and the acceleration duration of the vehicle not exceeding the third threshold, determining that the detection result is that the vehicle has a second acceleration anomaly; wherein, the acceleration deviation integral is the integral result of the actual acceleration deviation within the acceleration duration, the second threshold is the unexpected speed increment threshold obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario, and the third threshold is the fault tolerance duration threshold of unexpected acceleration obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario.

[0012] Optionally, the vehicle acceleration abnormality handling method also includes: in response to the detection result that the vehicle has a first acceleration abnormality, determining the target processing strategy includes: sending a clear torque request to the vehicle's automatic driving execution end, and sending a fault report to the vehicle's automatic driving control end; in response to the detection result that the vehicle has a second acceleration abnormality, determining the target processing strategy includes: adjusting the signal parameters in the acceleration command signal according to the actual acceleration deviation and the first threshold.

[0013] Optionally, adjusting the signal parameters in the acceleration command signal according to the actual acceleration deviation and the first threshold includes: performing acceleration correction adjustment on the signal parameters in the acceleration command signal based on the actual acceleration deviation, so that the actual acceleration deviation recalculated based on the adjusted acceleration command signal is less than or equal to the first threshold.

[0014] According to another aspect of an embodiment of the present invention, a vehicle acceleration anomaly processing device is also provided, including: an acquisition module, configured to obtain a real-time acceleration command signal and an actual acceleration signal of the vehicle, wherein the acceleration command signal is used to represent the expected acceleration to be executed calculated by the vehicle, and the actual acceleration signal is used to represent the actual execution acceleration measured by the vehicle; a detection module, configured to perform acceleration anomaly detection on the vehicle based on the acceleration command signal and the actual acceleration signal to obtain a detection result; a processing module, configured to adjust the automatic driving acceleration behavior of the vehicle according to a target processing strategy in response to the detection result that the vehicle has an acceleration anomaly, wherein the target processing strategy is determined by the anomaly category of the acceleration anomaly.

[0015] Optionally, the above-mentioned detection module is also configured to: in response to activation of the automatic driving function, determine the actual acceleration data from the actual acceleration signal, and determine the acceleration command data from the acceleration command signal; perform acceleration anomaly detection on the actual acceleration data and the acceleration command data, and determine the detection result.

[0016] Optionally, the above-mentioned detection module is also configured to: based on multiple sampling moments, sample from the actual acceleration signal to obtain multiple acceleration actual values ​​in the acceleration actual data; based on multiple sampling moments and the acceleration response time of the vehicle, sample from the acceleration command signal to obtain multiple acceleration command values ​​in the acceleration command data.

[0017] Optionally, acceleration anomaly detection includes: acceleration deviation detection, and the above-mentioned detection module is further configured to: perform acceleration deviation detection on the actual acceleration data and the acceleration instruction data, and in response to the actual acceleration deviation of the vehicle being greater than a first threshold, determine that the detection result is that the vehicle has a first acceleration anomaly, wherein the actual acceleration deviation is determined by the difference between the actual acceleration data and the acceleration instruction data, and the first threshold is the acceleration deviation threshold obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario.

[0018] Optionally, acceleration anomaly detection includes: acceleration deviation integral detection and unexpected acceleration duration detection, and the above-mentioned detection module is further configured to: when the actual acceleration deviation of the vehicle is less than or equal to a first threshold, perform acceleration deviation integral detection and unexpected acceleration duration detection on the actual acceleration data and the acceleration instruction data; in response to the acceleration deviation integral of the vehicle being greater than a second threshold and the acceleration duration of the vehicle exceeding a third threshold, determine that the detection result is that the vehicle has a first acceleration anomaly; and in response to the acceleration deviation integral of the vehicle being greater than the second threshold and the acceleration duration of the vehicle not exceeding the third threshold, determine that the vehicle has a second acceleration anomaly; wherein, the acceleration deviation integral is the integral result of the actual acceleration deviation within the acceleration duration, the second threshold is the unexpected speed increment threshold obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario, and the third threshold is the fault tolerance duration threshold of unexpected acceleration obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario.

[0019] Optionally, the above-mentioned vehicle acceleration abnormality handling device also includes a determination module, which is configured to: in response to the detection result that the vehicle has a first acceleration abnormality, determine the target processing strategy including: sending a torque clearance request to the vehicle's automatic driving execution end, and sending a fault report to the vehicle's automatic driving control end; in response to the detection result that the vehicle has a second acceleration abnormality, determine the target processing strategy including: adjusting the signal parameters in the acceleration command signal according to the actual acceleration deviation and the first threshold.

[0020] Optionally, the above-mentioned determination module is further configured to: perform acceleration correction adjustment on the signal parameters in the acceleration command signal based on the actual acceleration deviation, so that the actual acceleration deviation recalculated based on the adjusted acceleration command signal is less than or equal to the first threshold.

[0021] According to another aspect of an embodiment of the present invention, a storage medium is further provided, the storage medium including a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute any one of the above-mentioned vehicle acceleration abnormality processing methods.

[0022] According to another aspect of an embodiment of the present invention, a vehicle is also provided, including an on-board memory and an on-board processor, wherein a computer program is stored in the on-board memory, and the on-board processor is configured to run the computer program to execute any one of the above-mentioned vehicle acceleration abnormality handling methods.

[0023] In an embodiment of the present invention, a real-time acceleration command signal and actual acceleration signal of a vehicle are obtained, wherein the acceleration command signal is used to represent the expected acceleration to be executed calculated by the vehicle, and the actual acceleration signal is used to represent the actual execution acceleration measured by the vehicle; based on the acceleration command signal and the actual acceleration signal, the vehicle is detected for acceleration anomalies to obtain a detection result; in response to the detection result that the vehicle has an acceleration anomaly, the automatic driving acceleration behavior of the vehicle is adjusted according to a target processing strategy, wherein the target processing strategy is determined by the abnormality category of the acceleration anomaly. Thus, the present invention achieves the purpose of detecting and repairing acceleration anomalies in automatic driving based on the acceleration signal of the vehicle, thereby achieving the technical effect of improving the accuracy of acceleration anomaly detection and enhancing the safety of automatic driving, thereby solving the technical problem that the detection of acceleration anomalies in existing automatic driving functions is difficult and the accuracy is low, resulting in low safety of automatic driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0025] FIG1 is a hardware structure block diagram of a vehicle terminal for an optional method for handling vehicle acceleration abnormality according to an embodiment of the present invention;

[0026] FIG2 is a flow chart of a method for handling abnormal vehicle acceleration according to an embodiment of the present invention;

[0027] FIG3 is a schematic diagram of an optional implementation architecture of the above-mentioned vehicle acceleration abnormality processing method according to an embodiment of the present invention;

[0028] FIG4 is a schematic diagram of an optional vehicle acceleration abnormality processing process according to an embodiment of the present invention;

[0029] FIG5 is a structural block diagram of a vehicle acceleration abnormality processing device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] According to an embodiment of the present invention, a method embodiment of a vehicle acceleration abnormality handling method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0033] FIG1 is a block diagram of the hardware structure of a vehicle terminal for an optional vehicle acceleration abnormality handling method according to an embodiment of the present invention. As shown in FIG1 , the vehicle terminal (or a mobile device having a communication association with the vehicle) may include one or more processors 102 (the processor 102 may include but is not limited to a processing device such as a microcontroller unit (MCU) or a programmable logic device (Field Programmable Gate Array, FPGA)), a memory 104 configured to store data, and a transmission device 106 configured to implement a communication function. In addition, it may also include: a display device 110, an input and output device 108, a universal serial bus (USB) port (which may be included as one of the ports of a computer bus, not shown in the figure), a network interface (not shown in the figure), a power supply (not shown in the figure) and / or a camera (not shown in the figure). It will be understood by those skilled in the art that the structure shown in FIG1 is only illustrative and does not limit the structure of the above-mentioned vehicle terminal. For example, the vehicle terminal may also include more or fewer components than those shown in FIG1 , or have a configuration different from that shown in FIG1 .

[0034] It should be noted that the one or more processors 102 and / or other data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuit may be a single independent processing module, or may be fully or partially integrated into any of the other components in the vehicle terminal (or mobile device).

[0035] The memory 104 can be configured to store software programs and modules of application software, such as the program instruction / data storage device corresponding to the vehicle acceleration abnormality processing method in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, realizes the above-mentioned vehicle acceleration abnormality processing method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely located relative to the processor 102, and these remote memories may be connected to the vehicle terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0036] The transmission device 106 is configured to receive or transmit data via a network. A specific example of such a network may include a wireless network provided by a communications provider of the vehicle terminal. In one embodiment, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device 106 may be a radio frequency (RF) module configured to communicate with the Internet wirelessly.

[0037] Under the above operating environment, an embodiment of the present invention provides a method for handling abnormal vehicle acceleration as shown in FIG2 . FIG2 is a flow chart of a method for handling abnormal vehicle acceleration according to an embodiment of the present invention. As shown in FIG2 , the method includes the following implementation steps:

[0038] Step S201: Acquire a real-time acceleration command signal and an actual acceleration signal of the vehicle, wherein the acceleration command signal is used to represent the expected acceleration to be executed calculated by the vehicle, and the actual acceleration signal is used to represent the actual acceleration executed measured by the vehicle;

[0039] Step S202: performing acceleration abnormality detection on the vehicle based on the acceleration command signal and the actual acceleration signal to obtain a detection result;

[0040] Step S203, in response to the detection result that the vehicle has an acceleration anomaly, the automatic driving acceleration behavior of the vehicle is adjusted according to the target processing strategy, wherein the target processing strategy is determined by the abnormality category of the acceleration anomaly.

[0041] In an embodiment of the present invention, a real-time acceleration command signal and actual acceleration signal of a vehicle are obtained, wherein the acceleration command signal is used to represent the expected acceleration to be executed calculated by the vehicle, and the actual acceleration signal is used to represent the actual execution acceleration measured by the vehicle; based on the acceleration command signal and the actual acceleration signal, the vehicle is detected for acceleration anomalies to obtain a detection result; in response to the detection result that the vehicle has an acceleration anomaly, the automatic driving acceleration behavior of the vehicle is adjusted according to a target processing strategy, wherein the target processing strategy is determined by the abnormality category of the acceleration anomaly. Thus, the present invention achieves the purpose of detecting and repairing acceleration anomalies in automatic driving based on the acceleration signal of the vehicle, thereby achieving the technical effect of improving the accuracy of acceleration anomaly detection and enhancing the safety of automatic driving, thereby solving the technical problem that the detection of acceleration anomalies in existing automatic driving functions is difficult and the accuracy is low, resulting in low safety of automatic driving.

[0042] In an exemplary application scenario, an implementation architecture corresponding to the above-mentioned vehicle acceleration abnormality handling method is proposed as shown in FIG3 . Specifically, the implementation architecture includes:

[0043] The acceleration calculation module 310 is configured to calculate the expected acceleration that the vehicle currently needs to perform in real time based on the definition of the autonomous driving function, and is also configured to send an acceleration command signal to the vehicle speed abnormality detection control module 330. The acceleration calculation module 30 can be an acceleration calculation module for L3 autonomous driving;

[0044] The state acquisition module 320 is configured to obtain the real-time longitudinal acceleration of the vehicle and is also configured to send an actual acceleration signal to the vehicle speed abnormality detection control module 330;

[0045] The vehicle speed abnormality detection control module 330 is configured to determine whether the current vehicle speed is abnormal (i.e., whether abnormal acceleration occurs and affects safe driving) based on the longitudinal acceleration and the expected acceleration that takes into account the system response time. It is also configured to control and adjust the vehicle speed in response to the abnormal acceleration, generate an acceleration command, and send the acceleration command to the longitudinal electronic control module 340;

[0046] The longitudinal electric control module 340 is configured to calculate the driving torque required to be executed by the electric drive execution module 350 according to the acceleration instruction, and generate a driving instruction according to the driving torque and send it to the electric drive execution module 350;

[0047] The electric drive execution module 350 is configured to achieve vehicle acceleration by controlling the current and power of the drive motor according to the received drive torque.

[0048] Based on the above implementation architecture, the vehicle acceleration anomaly handling method provided by the embodiment of the present invention runs in the above vehicle speed anomaly detection and control module 330. In the vehicle speed anomaly detection and control module 330, acceleration anomalies in autonomous driving are detected and handled according to the vehicle acceleration anomaly handling process shown in FIG4 .

[0049] Optionally, in the above step S202, based on the acceleration command signal and the actual acceleration signal, the vehicle is subjected to acceleration abnormality detection to obtain a detection result, which may further include the following execution steps:

[0050] Step S221, in response to activation of the automatic driving function, determining actual acceleration data from the actual acceleration signal and determining acceleration command data from the acceleration command signal;

[0051] Step S222: Perform acceleration anomaly detection on the actual acceleration data and the acceleration instruction data to determine the detection result.

[0052] During the continuous monitoring of the vehicle for acceleration anomalies, the entire real-time actual acceleration signal and acceleration command signal are periodically acquired. After the L3 autonomous driving function is activated, the actual acceleration data is determined in real time from the actual acceleration signal and the acceleration command data is determined in real time from the acceleration command signal according to a preset period. Thus, the actual acceleration data and acceleration command data in autonomous driving are continuously detected for acceleration anomalies and the detection results are determined.

[0053] Optionally, in the above step S221, determining the actual acceleration data from the actual acceleration signal and determining the acceleration command data from the acceleration command signal may further include the following execution steps:

[0054] Step S2211, based on multiple sampling moments, sampling from the actual acceleration signal to obtain multiple acceleration actual values ​​in the acceleration actual data;

[0055] Step S2212: Based on the multiple sampling moments and the acceleration response time of the vehicle, multiple acceleration command values ​​in the acceleration command data are sampled from the acceleration command signal.

[0056] As shown in Figure 4, after the L3 autonomous driving function is activated, the vehicle speed anomaly detection control module 330 sets no less than three sampling moments according to a preset period. In this example, three sampling moments are used as an example for explanation, and the corresponding identifiers of the three sampling moments are 31, 32, and 33. Based on the three sampling moments, three actual acceleration values ​​are sampled from the actual acceleration signal and recorded as A31, A32, and A33 respectively. Furthermore, the acceleration response time of the vehicle drive system is recorded as Ta. Based on the above three sampling moments and the acceleration response time, three waiting time points 31-Ta, 32-Ta, and 33-Ta are determined. Based on the three waiting time points, three acceleration command values ​​are sampled from the actual acceleration signal and recorded as B31, B32, and B33 respectively.

[0057] Optionally, the acceleration anomaly detection includes acceleration deviation detection. In the above step S222, acceleration anomaly detection is performed on the actual acceleration data and the acceleration instruction data to determine the detection result, and the following execution steps may also be included:

[0058] Step S2221, perform acceleration deviation detection on the actual acceleration data and the acceleration command data, and in response to the actual acceleration deviation of the vehicle being greater than a first threshold, determine that the detection result is that the vehicle has a first acceleration abnormality, wherein the actual acceleration deviation is determined by the difference between the actual acceleration data and the acceleration command data, and the first threshold is the acceleration deviation threshold obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario.

[0059] Still as shown in Figure 4, the first threshold is the acceleration execution deviation threshold that is allowed to occur based on the safety metric analysis under the abnormal acceleration scenario of the whole vehicle, which is recorded as tolerance_a1. The acceleration deviation detection is performed on the actual acceleration data and the acceleration instruction data, that is, it is determined whether the acceleration deviation within the response time is greater than the first threshold. The acceleration deviation is the absolute value of the difference between the actual acceleration data and the acceleration instruction data. The judgment logic of the above acceleration deviation detection is: if |A31-B31|, |A32-B32| and |A33-B33| are all greater than tolerance_a1, it is considered that the acceleration deviation is greater than the first threshold, and it is determined that the vehicle has a first acceleration abnormality. The first acceleration abnormality may be a drive system failure, that is, the vehicle's drive system corresponds to an upper-level acceleration instruction abnormality.

[0060] Optionally, the acceleration anomaly detection includes: acceleration deviation integral detection and unexpected acceleration duration detection. In the above step S222, the acceleration anomaly detection is performed on the actual acceleration data and the acceleration instruction data to determine the detection result, and the following execution steps may also be included:

[0061] Step S2222: When the actual acceleration deviation of the vehicle is less than or equal to the first threshold, performing acceleration deviation integral detection and unexpected acceleration duration detection on the actual acceleration data and the acceleration command data; in response to the acceleration deviation integral of the vehicle being greater than the second threshold and the duration of the vehicle's acceleration exceeding the third threshold, determining that the vehicle has a first acceleration abnormality; and in response to the acceleration deviation integral of the vehicle being greater than the second threshold and the duration of the vehicle's acceleration not exceeding the third threshold, determining that the vehicle has a second acceleration abnormality.

[0062] Among them, the acceleration deviation integral is the integral result of the actual acceleration deviation within the acceleration duration, the second threshold is the unexpected speed increment threshold obtained by the safety measurement analysis of the vehicle in the abnormal acceleration scenario, and the third threshold is the fault tolerance duration threshold for unexpected acceleration obtained by the safety measurement analysis of the vehicle in the abnormal acceleration scenario.

[0063] Still as shown in Figure 4, when it is determined that the acceleration deviation within the response time is less than or equal to the first threshold, acceleration deviation integral detection and unexpected acceleration duration detection are performed on the actual acceleration data and acceleration command data. Specifically, the second threshold is the allowable unexpected acceleration increment threshold, denoted as tolerance_v1, obtained based on the safety metric analysis of the vehicle under abnormal acceleration scenarios. The third threshold is the fault tolerance time threshold for unexpected acceleration, denoted as tolerance_t1, obtained based on the safety metric analysis of the vehicle under abnormal acceleration scenarios. Based on this, if the acceleration deviation integral within the acceleration duration is less than or equal to the second threshold, the process returns to periodically acquiring the vehicle's real-time actual acceleration signal and acceleration command signal, and the next cycle of vehicle acceleration anomaly detection and processing begins again. If the vehicle's acceleration deviation integral is greater than the second threshold and the duration of the vehicle's acceleration exceeds the third threshold, the detection result is determined to be a first acceleration anomaly. If the vehicle's acceleration deviation integral is greater than the second threshold and the duration of the vehicle's acceleration does not exceed the third threshold, the detection result is determined to be a second acceleration anomaly.

[0064] In addition, based on the safety metric analysis of the vehicle under abnormal acceleration scenarios, the monitoring time for unexpected acceleration is recorded as Δt, the allowable unexpected speed increment is recorded as ΔV, the value of the vehicle's longitudinal acceleration at any time t is recorded as X, and the acceleration command value received at time t-Ta is recorded as Y, where t represents any sampling time among multiple sampling times (for example, t31 is the sampling time marked as 31). When it is determined that the acceleration deviation within the response time is less than or equal to the first threshold, the acceleration deviation integral and the acceleration duration can also be verified through the following process:

[0065] Step E1: Calculate the acceleration deviation integral and determine whether condition 1 is met. Condition 1 is

[0066] In step E2, if condition 1 is met, acceleration correction is started. The acceleration command signal is recorded as A0 and the actual acceleration signal is recorded as A1. Then, the acceleration command signal is corrected so that the following formula (1) is met:

[0067] Step E3: Based on the safety metric analysis of the vehicle under abnormal acceleration, the fault tolerance time of unexpected acceleration is recorded as tolerance_t1, and whether condition 2 is met is determined. Condition 2 is

[0068] In step E4, if both conditions 1 and 2 are met, it is determined that the upper-level acceleration command corresponding to the vehicle's drive system is abnormal; if condition 1 is met but condition 2 is not met, it is determined that the accuracy of the vehicle's acceleration command signal is too low (i.e., the second acceleration abnormality).

[0069] Therefore, the present invention realizes acceleration anomaly detection of the real-time actual acceleration signal and acceleration command signal of the whole vehicle from multiple dimensions, and the acceleration anomaly detection obtained in this way has high accuracy.

[0070] Optionally, the above vehicle acceleration abnormality handling method may further include the following method steps:

[0071] Step S241, in response to the detection result indicating that the vehicle has a first acceleration abnormality, determining a target processing strategy includes: sending a clear torque request to the vehicle's autonomous driving execution terminal and sending a fault report to the vehicle's autonomous driving control terminal;

[0072] Step S242 , in response to the detection result indicating that the vehicle has a second acceleration abnormality, determining a target processing strategy includes adjusting a signal parameter in the acceleration command signal according to the actual acceleration deviation and the first threshold.

[0073] Optionally, in the above step S242, adjusting the signal parameters in the acceleration command signal according to the actual acceleration deviation and the first threshold value may further include the following execution steps:

[0074] Step S2421: Based on the actual acceleration deviation, perform acceleration deviation correction adjustment on the signal parameters in the acceleration command signal, so that the actual acceleration deviation recalculated based on the adjusted acceleration command signal is less than or equal to the first threshold.

[0075] Still as shown in FIG4 , when a fault is determined in the vehicle drive system, a torque clearance request is sent to the autonomous driving execution terminal to cut off power output, and a fault report (i.e., an abnormality report) is sent to the autonomous driving control terminal. When the acceleration command signal is determined to be too low in accuracy, signal parameters in the acceleration command signal are adjusted based on the actual acceleration deviation and the first threshold.

[0076] Specifically, the first acceleration anomaly is caused by an abnormal acceleration execution due to the drive system's own fault or other factors. When the first acceleration anomaly is detected, if the drive system fails and does not cause an excessive acceleration anomaly, the vehicle speed anomaly detection control module 330 performs speed correction after meeting the above condition 1, so that the vehicle speed deviation is always kept within the safety measure allowed by the system and the impact is suppressed by the correction mechanism within the fault tolerance time. The automatic driving function will not be affected by this and frequent exits improve system availability. If the drive system fails and causes excessive acceleration, the abnormal vehicle speed anomaly detection control module 330 still exceeds the safe allowable value within the monitoring time after speed correction, then the vehicle's drive system corresponds to the upper-level acceleration instruction abnormality, and the vehicle speed anomaly detection control module 330 sends a clear torque request to the execution end and reports the system fault to the upper-level module, so that the upper-level software module activates the system degradation strategy to ensure personnel safety, thereby achieving the effect of fail-operation.

[0077] Specifically, the aforementioned second acceleration anomaly is an anomaly in which the drive system temporarily reduces acceleration accuracy due to environmental factors. When this second acceleration anomaly is detected, the vehicle speed anomaly detection and control module 330 performs speed correction after condition 2 is met, ensuring that the vehicle speed deviation remains within the system's permitted safety margin and eliminating the speed impact of the second acceleration anomaly within the fault tolerance period. This prevents the autonomous driving function from frequently exiting due to this speed impact, thereby improving system availability.

[0078] In addition, it should be noted that the present invention monitors and effectively controls abnormal vehicle acceleration in the context of in-loop control of the L3 autonomous driving function, thereby suppressing or reducing the adverse effects caused by abnormal vehicle acceleration. In-loop control of autonomous driving function refers to the real-time control and adjustment of the vehicle's autonomous driving system based on changes in the surrounding environment and the vehicle's status to ensure the safe driving of the vehicle under different road and traffic conditions. This includes control of vehicle speed, steering, braking, etc., adapting to and responding to changes in the surrounding environment as much as possible while ensuring safety. This type of in-loop control can obtain information about the surrounding environment through sensors, which is then analyzed and decided by the vehicle's autonomous driving system, ultimately achieving automatic driving of the vehicle.

[0079] In summary, the present invention proposes a vehicle speed anomaly detection and control method based on a longitudinal electronic control system. The vehicle speed anomaly detection and control system obtains longitudinal acceleration information and acceleration instructions sent by the automatic driving controller in real time, detects the current abnormal speed state of the automatic driving vehicle based on the longitudinal acceleration information and the acceleration instructions, and controls the vehicle to suppress or reduce the negative impact of the vehicle acceleration anomaly.

[0080] In this embodiment, a vehicle acceleration abnormality handling device is also provided. The device is configured to implement the above-described embodiments and preferred embodiments, and details already described will not be repeated. As used below, a "module" refers to a combination of software and / or hardware that can implement a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0081] FIG5 is a structural block diagram of a vehicle acceleration abnormality processing device according to an embodiment of the present invention. As shown in FIG5 , the device includes:

[0082] an acquisition module 501 configured to acquire a real-time acceleration command signal and an actual acceleration signal of the vehicle, wherein the acceleration command signal is used to represent the expected acceleration to be executed as calculated by the vehicle, and the actual acceleration signal is used to represent the actual acceleration executed as measured by the vehicle;

[0083] The detection module 502 is configured to perform acceleration abnormality detection on the vehicle based on the acceleration command signal and the actual acceleration signal to obtain a detection result;

[0084] The processing module 503 is configured to adjust the vehicle's automatic driving acceleration behavior according to a target processing strategy in response to a detection result indicating that the vehicle has an acceleration anomaly, wherein the target processing strategy is determined by the anomaly category of the acceleration anomaly.

[0085] Optionally, the above-mentioned detection module 502 is also configured to: in response to the activation of the automatic driving function, determine the actual acceleration data from the actual acceleration signal, and determine the acceleration command data from the acceleration command signal; perform acceleration anomaly detection on the actual acceleration data and the acceleration command data, and determine the detection result.

[0086] Optionally, the above-mentioned detection module 502 is also configured to: based on multiple sampling moments, sample from the actual acceleration signal to obtain multiple acceleration actual values ​​in the acceleration actual data; based on multiple sampling moments and the acceleration response time of the vehicle, sample from the acceleration command signal to obtain multiple acceleration command values ​​in the acceleration command data.

[0087] Optionally, acceleration anomaly detection includes: acceleration deviation detection, and the above-mentioned detection module 502 is also configured to: perform acceleration deviation detection on the actual acceleration data and the acceleration instruction data, and in response to the actual acceleration deviation of the vehicle being greater than a first threshold, determine that the detection result is that the vehicle has a first acceleration anomaly, wherein the actual acceleration deviation is determined by the difference between the actual acceleration data and the acceleration instruction data, and the first threshold is the acceleration deviation threshold obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario.

[0088] Optionally, acceleration anomaly detection includes: acceleration deviation integral detection and unexpected acceleration duration detection. The above-mentioned detection module 502 is also configured to: when the actual acceleration deviation of the vehicle is less than or equal to a first threshold, perform acceleration deviation integral detection and unexpected acceleration duration detection on the actual acceleration data and the acceleration instruction data; in response to the acceleration deviation integral of the vehicle being greater than a second threshold and the acceleration duration of the vehicle exceeding a third threshold, determine that the detection result is that the vehicle has a first acceleration anomaly; and in response to the acceleration deviation integral of the vehicle being greater than the second threshold and the acceleration duration of the vehicle not exceeding the third threshold, determine that the vehicle has a second acceleration anomaly; wherein, the acceleration deviation integral is the integral result of the actual acceleration deviation within the acceleration duration, the second threshold is the unexpected speed increment threshold obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario, and the third threshold is the fault tolerance duration threshold of unexpected acceleration obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario.

[0089] Optionally, in addition to all the above modules, the above-mentioned vehicle acceleration abnormality handling device also includes a determination module 504 (not shown in the figure), which is configured to: in response to the detection result that the vehicle has a first acceleration abnormality, determine the target processing strategy including: sending a torque clearance request to the vehicle's automatic driving execution end, and sending a fault report to the vehicle's automatic driving control end; in response to the detection result that the vehicle has a second acceleration abnormality, determine the target processing strategy including: adjusting the signal parameters in the acceleration command signal according to the actual acceleration deviation and the first threshold.

[0090] Optionally, the determination module 504 is further configured to perform acceleration deviation correction adjustment on signal parameters in the acceleration command signal based on the actual acceleration deviation, so that the actual acceleration deviation recalculated based on the adjusted acceleration command signal is less than or equal to a first threshold.

[0091] It should be noted that the above modules can be implemented through software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0092] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, which includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute any of the aforementioned vehicle acceleration abnormality processing methods.

[0093] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for executing the following steps: obtaining the vehicle's real-time acceleration command signal and actual acceleration signal, wherein the acceleration command signal is used to represent the expected acceleration to be executed calculated by the vehicle, and the actual acceleration signal is used to represent the actual execution acceleration measured by the vehicle; based on the acceleration command signal and the actual acceleration signal, performing acceleration anomaly detection on the vehicle to obtain a detection result; in response to the detection result that the vehicle has an acceleration anomaly, adjusting the vehicle's automatic driving acceleration behavior according to a target processing strategy, wherein the target processing strategy is determined by the anomaly category of the acceleration anomaly.

[0094] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for performing the following steps: in response to activation of the autonomous driving function, determining actual acceleration data from the actual acceleration signal, and determining acceleration command data from the acceleration command signal; performing acceleration anomaly detection on the actual acceleration data and the acceleration command data, and determining the detection results.

[0095] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for performing the following steps: based on multiple sampling moments, sampling from the actual acceleration signal to obtain multiple acceleration actual values ​​in the acceleration actual data; based on multiple sampling moments and the acceleration response duration of the vehicle, sampling from the acceleration command signal to obtain multiple acceleration command values ​​in the acceleration command data.

[0096] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for executing the following steps: performing acceleration deviation detection on actual acceleration data and acceleration instruction data, and in response to the actual acceleration deviation of the vehicle being greater than a first threshold, determining that the detection result is that the vehicle has a first acceleration abnormality, wherein the actual acceleration deviation is determined by the difference between the actual acceleration data and the acceleration instruction data, and the first threshold is the acceleration deviation threshold obtained by the safety metric analysis of the vehicle in an abnormal acceleration scenario.

[0097] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for performing the following steps: when the actual acceleration deviation of the vehicle is less than or equal to a first threshold, performing acceleration deviation integral detection and unexpected acceleration duration detection on the actual acceleration data and the acceleration instruction data; in response to the acceleration deviation integral of the vehicle being greater than a second threshold and the acceleration duration of the vehicle exceeding a third threshold, determining that the detection result is that the vehicle has a first acceleration abnormality; and in response to the acceleration deviation integral of the vehicle being greater than the second threshold and the acceleration duration of the vehicle not exceeding the third threshold, determining that the detection result is that the vehicle has a second acceleration abnormality; wherein, the acceleration deviation integral is the integral result of the actual acceleration deviation within the acceleration duration, the second threshold is the unexpected speed increment threshold obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario, and the third threshold is the fault tolerance duration threshold of unexpected acceleration obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario.

[0098] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for performing the following steps: in response to the detection result that the vehicle has a first acceleration abnormality, determining the target processing strategy includes: sending a clear torque request to the vehicle's automatic driving execution end, and sending a fault report to the vehicle's automatic driving control end; in response to the detection result that the vehicle has a second acceleration abnormality, determining the target processing strategy includes: adjusting the signal parameters in the acceleration command signal according to the actual acceleration deviation and the first threshold.

[0099] Optionally, in this embodiment, the above-mentioned storage medium can be configured to store a computer program for executing the following steps: based on the actual acceleration deviation, performing acceleration correction adjustment on the signal parameters in the acceleration command signal, so that the actual acceleration deviation recalculated based on the adjusted acceleration command signal is less than or equal to the first threshold.

[0100] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0101] According to another aspect of an embodiment of the present invention, a vehicle is provided, comprising an on-board memory and an on-board processor, wherein a computer program is stored in the on-board memory, and the on-board processor is configured to run the computer program to execute any one of the aforementioned vehicle acceleration abnormality handling methods.

[0102] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: obtaining the vehicle's real-time acceleration command signal and actual acceleration signal, wherein the acceleration command signal is used to represent the expected acceleration to be executed calculated by the vehicle, and the actual acceleration signal is used to represent the actual execution acceleration measured by the vehicle; based on the acceleration command signal and the actual acceleration signal, performing acceleration anomaly detection on the vehicle to obtain a detection result; in response to the detection result that the vehicle has an acceleration anomaly, adjusting the vehicle's automatic driving acceleration behavior according to a target processing strategy, wherein the target processing strategy is determined by the anomaly category of the acceleration anomaly.

[0103] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: in response to the activation of the automatic driving function, determine the actual acceleration data from the actual acceleration signal, and determine the acceleration command data from the acceleration command signal; perform acceleration anomaly detection on the actual acceleration data and the acceleration command data, and determine the detection results.

[0104] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: based on multiple sampling moments, sampling from the actual acceleration signal to obtain multiple acceleration actual values ​​in the acceleration actual data; based on multiple sampling moments and the acceleration response time of the vehicle, sampling from the acceleration command signal to obtain multiple acceleration command values ​​in the acceleration command data.

[0105] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: perform acceleration deviation detection on the actual acceleration data and the acceleration instruction data, and in response to the actual acceleration deviation of the vehicle being greater than a first threshold, determine that the detection result is that the vehicle has a first acceleration abnormality, wherein the actual acceleration deviation is determined by the difference between the actual acceleration data and the acceleration instruction data, and the first threshold is the acceleration deviation threshold obtained by the safety metric analysis of the vehicle in an abnormal acceleration scenario.

[0106] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: when the actual acceleration deviation of the vehicle is less than or equal to a first threshold, performing acceleration deviation integral detection and unexpected acceleration duration detection on the actual acceleration data and the acceleration instruction data; in response to the acceleration deviation integral of the vehicle being greater than a second threshold and the acceleration duration of the vehicle exceeding a third threshold, determining that the detection result is that the vehicle has a first acceleration abnormality; and in response to the acceleration deviation integral of the vehicle being greater than the second threshold and the acceleration duration of the vehicle not exceeding the third threshold, determining that the detection result is that the vehicle has a second acceleration abnormality; wherein, the acceleration deviation integral is the integral result of the actual acceleration deviation within the acceleration duration, the second threshold is the unexpected speed increment threshold obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario, and the third threshold is the fault tolerance duration threshold of unexpected acceleration obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario.

[0107] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: in response to the detection result that the vehicle has a first acceleration abnormality, determining the target processing strategy includes: sending a clear torque request to the vehicle's automatic driving execution end, and sending a fault report to the vehicle's automatic driving control end; in response to the detection result that the vehicle has a second acceleration abnormality, determining the target processing strategy includes: adjusting the signal parameters in the acceleration command signal according to the actual acceleration deviation and the first threshold.

[0108] Optionally, in this embodiment, the above-mentioned on-board processor can be configured to perform the following steps through a computer program: based on the actual acceleration deviation, perform acceleration correction adjustment on the signal parameters in the acceleration command signal, so that the actual acceleration deviation recalculated based on the adjusted acceleration command signal is less than or equal to the first threshold.

[0109] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiment and its optional implementation manners, which will not be repeated here.

[0110] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0111] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0112] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0113] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0114] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0115] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program code, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0116] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for handling abnormal vehicle acceleration, comprising: Obtaining a real-time acceleration command signal and an actual acceleration signal of the vehicle, wherein the acceleration command signal is used to represent the expected acceleration to be executed calculated by the vehicle, and the actual acceleration signal is used to represent the actual executed acceleration measured by the vehicle; Based on the acceleration command signal and the actual acceleration signal, performing abnormal acceleration detection on the vehicle to obtain a detection result; In response to the detection result indicating that the vehicle has abnormal acceleration, adjusting the autonomous driving acceleration behavior of the vehicle according to a target processing strategy, wherein the target processing strategy is determined by the abnormal category of the abnormal acceleration.

2. The vehicle acceleration anomaly handling method according to claim 1, wherein, Based on the acceleration command signal and the actual acceleration signal, performing abnormal acceleration detection on the vehicle to obtain the detection result, including: In response to the activation of the autonomous driving function, determining acceleration actual data from the actual acceleration signal and determining acceleration command data from the acceleration command signal; Performing abnormal acceleration detection on the acceleration actual data and the acceleration command data to determine the detection result.

3. The vehicle acceleration anomaly handling method according to claim 2, wherein, Determining acceleration actual data from the actual acceleration signal and determining acceleration command data from the acceleration command signal includes: Sampling a plurality of acceleration actual values in the acceleration actual data from the actual acceleration signal based on a plurality of sampling moments; Sampling a plurality of acceleration command values in the acceleration command data from the acceleration command signal based on the plurality of sampling moments and the acceleration response duration of the vehicle.

4. The vehicle acceleration anomaly handling method according to claim 1, wherein, The abnormal acceleration detection includes: acceleration deviation detection. Performing abnormal acceleration detection on the acceleration actual data and the acceleration command data to determine the detection result includes: Performing the acceleration deviation detection on the acceleration actual data and the acceleration command data. In response to the actual acceleration deviation of the vehicle being greater than a first threshold, determining the detection result as that the vehicle has a first abnormal acceleration, wherein the actual acceleration deviation is determined by the difference between the acceleration actual data and the acceleration command data, and the first threshold is an acceleration deviation threshold obtained by safety metric analysis of the vehicle in an abnormal acceleration scenario.

5. The vehicle acceleration anomaly handling method according to claim 4, wherein, The abnormal acceleration detection includes: acceleration deviation integral detection and unexpected acceleration duration detection. Performing abnormal acceleration detection on the acceleration actual data and the acceleration command data to determine the detection result further includes: When the actual acceleration deviation of the vehicle is less than or equal to the first threshold, perform the acceleration deviation integration detection and the unexpected acceleration duration detection on the actual acceleration data and the acceleration command data. In response to the acceleration deviation integration of the vehicle being greater than the second threshold and the acceleration duration of the vehicle exceeding the third threshold, determine that the detection result is that the vehicle has a first acceleration anomaly. And in response to the acceleration deviation integration of the vehicle being greater than the second threshold and the acceleration duration of the vehicle not exceeding the third threshold, determine that the detection result is that the vehicle has a second acceleration anomaly; Wherein, the acceleration deviation integration is the integration result of the actual acceleration deviation within the acceleration duration, the second threshold is the unexpected speed increment threshold obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario, and the third threshold is the fault tolerance duration threshold of the unexpected acceleration obtained by the safety metric analysis of the vehicle in the abnormal acceleration scenario.

6. The vehicle acceleration anomaly handling method according to claim 5, wherein, The vehicle acceleration anomaly processing method further includes: In response to the detection result being that the vehicle has the first acceleration anomaly, determine that the target processing strategy includes: sending a torque clearance request to the automatic driving execution end of the vehicle and sending a fault report to the automatic driving control end of the vehicle; In response to the detection result being that the vehicle has the second acceleration anomaly, determine that the target processing strategy includes: adjusting the signal parameters in the acceleration command signal according to the actual acceleration deviation and the first threshold.

7. The vehicle acceleration anomaly handling method according to claim 6, wherein, Adjusting the signal parameters in the acceleration command signal according to the actual acceleration deviation and the first threshold includes: Based on the actual acceleration deviation, perform acceleration deviation correction adjustment on the signal parameters in the acceleration command signal, so that the actual acceleration deviation recalculated based on the adjusted acceleration command signal is less than or equal to the first threshold.

8. A vehicle acceleration anomaly processing device, comprising: An acquisition module, configured to acquire the real-time acceleration command signal and the actual acceleration signal of the vehicle, wherein the acceleration command signal is used to represent the expected acceleration to be executed calculated by the vehicle, and the actual acceleration signal is used to represent the actual executed acceleration measured by the vehicle; A detection module, configured to perform acceleration anomaly detection on the vehicle based on the acceleration command signal and the actual acceleration signal to obtain a detection result; A processing module, configured to, in response to the detection result being that the vehicle has an acceleration anomaly, adjust the automatic driving acceleration behavior of the vehicle according to a target processing strategy, wherein the target processing strategy is determined by the anomaly category of the acceleration anomaly.

9. A storage medium, the storage medium comprising a stored program, wherein, When the program runs, control the device where the storage medium is located to execute the vehicle acceleration anomaly processing method according to any one of claims 1 to 7.

10. A vehicle, comprising an on-vehicle memory and an on-vehicle processor, wherein a computer program is stored in the on-vehicle memory, and the on-vehicle processor is configured to run the computer program to execute the vehicle acceleration anomaly handling method according to any one of claims 1 to 7.

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