A method, apparatus, equipment and medium for detecting vehicle anomalies

Abstract

This application provides a vehicle anomaly detection method, apparatus, device, and medium. The method includes: acquiring a sampling period for sampling heartbeat signals of at least one functional module of the vehicle, and the heartbeat period during which the at least one functional module sends the heartbeat signals; the different heartbeat signals exhibit periodic variations; determining a preset number of sampling periods based on the sampling period and the magnitude relationship between the heartbeat periods of the heartbeat signals; and for each functional module, determining an anomaly detection result for that functional module based on the heartbeat signals sampled for a consecutive preset number of sampling periods. This allows for real-time detection of the operating status of the vehicle's functional modules, thereby reducing the occurrence of safety accidents caused by functional module anomalies.

Description

Technical Field

[0001] This application relates to the field of intelligent driving, and in particular to a method, device, equipment and medium for detecting vehicle anomalies. Background Technology

[0002] In the field of intelligent driving, the intelligent driving module in a vehicle can assist the user in driving, and can also completely replace human driving in special situations, such as automatic parking. However, changes in the external environment, human operation, and the duration of driving can all affect the operating performance of the vehicle's software and hardware. Therefore, it is necessary to monitor the operating status of the intelligent driving module in real time during its operation. Summary of the Invention

[0003] This application provides a vehicle anomaly detection method, device, equipment, and medium, which can detect the operating status of the intelligent driving module in real time and promptly detect any abnormalities in the intelligent driving module.

[0004] The technical solution of this application embodiment is implemented as follows:

[0005] This application provides a vehicle anomaly detection method, applied to the vehicle detection module, including:

[0006] A sampling period for sampling the heartbeat signal of at least one functional module of the vehicle and the heartbeat period for the heartbeat signal sent by at least one functional module are obtained; the different heartbeat signals vary periodically; a preset number of sampling periods is determined based on the sampling period and the magnitude relationship between the heartbeat periods of the heartbeat signals; for each functional module, an anomaly detection result of the functional module is determined based on the heartbeat signal sampled by the functional module for a consecutive preset number of sampling periods.

[0007] In this embodiment, the preset number of sampling periods can be dynamically determined based on the relationship between the sampling period for sampling the heartbeat signals of at least one functional module of the vehicle and the heartbeat period of the heartbeat signals sent by at least one functional module. This reduces the inaccuracy of anomaly detection results caused by collecting a small number of heartbeat signals when the sampling period is short, and also reduces the efficiency reduction caused by collecting a large number of heartbeat signals when the sampling period is long. Finally, the anomaly detection result of each functional module is determined based on the heartbeat signals sampled for a consecutive preset number of sampling periods. This enables real-time detection of the operating status of the vehicle's functional modules, thereby reducing the occurrence of safety accidents due to functional module malfunctions.

[0008] In some embodiments, the preset quantity includes a first preset quantity and a second preset quantity greater than the first preset quantity; determining the preset quantity of the sampling period based on the relationship between the sampling period and the heartbeat period of the heartbeat signal includes: determining the preset quantity as a first preset quantity when the sampling period is greater than or equal to the heartbeat period of the heartbeat signal; and determining the preset quantity as a second preset quantity when the sampling period is less than the heartbeat period of the heartbeat signal.

[0009] In this embodiment, a first preset quantity can be determined when the sampling period is greater than or equal to the heartbeat period of the heartbeat signal; when the sampling period is less than the heartbeat period of the heartbeat signal, a second preset quantity greater than the first preset quantity can be determined. This allows the preset quantity to be dynamically determined based on the sampling period and the heartbeat period of the heartbeat signal, ensuring that the acquired heartbeat signal is as close as possible to the newly sent heartbeat signal from the functional module. This not only improves the accuracy of determining the anomaly detection results of the functional module, but also, when the sampling period is greater than or equal to the heartbeat period of the heartbeat signal, using a smaller first preset quantity can improve detection efficiency without reducing the accuracy of the anomaly detection results of the functional module.

[0010] In some embodiments, the heartbeat signal includes a heartbeat value; determining the anomaly detection result of each functional module based on the heartbeat signal sampled in a consecutive preset number of sampling periods of the functional module includes: for each functional module, if the heartbeat value sampled in a consecutive preset number of sampling periods of the functional module is the same as the historical heartbeat value in the corresponding previous sampling period, determining an anomaly detection result characterizing that the functional module has an anomaly.

[0011] In this embodiment, an anomaly is determined to have occurred in a functional module only if a predetermined number of consecutive heartbeat values ​​are identical to the historical heartbeat values ​​of their respective previous sampling periods. This reduces the possibility of false positives and improves the accuracy of anomaly detection results for functional modules.

[0012] In some embodiments, the method further includes: generating a detection result signal for the at least one functional module based on the anomaly detection result of each functional module; sending the detection result signal of the at least one functional module and other detection result signals of the at least one functional module to a security execution module; wherein the security execution module can shut down the at least one functional module if at least one of the detection result signals and other detection result signals indicates that an abnormal functional module exists in the at least one functional module.

[0013] In this embodiment, a detection result signal for at least one functional module can be generated based on the anomaly detection result of each functional module. This allows the security execution module to quickly determine whether an abnormal functional module exists within the at least one functional module based on the detection result signal. Then, the detection result signal for at least one functional module, along with other detection result signals for the at least one functional module, is sent to the security execution module. This allows the security execution module to determine whether to shut down at least one functional module based on the detection result signal and other detection result signals, reducing the likelihood of failing to shut down at least one functional module with an abnormal function in a timely manner due to inaccurate detection result signals.

[0014] In some embodiments, the method further includes: generating a restart request signal when, within a third preset number of transmission cycles in which the detection result signals are transmitted, all of the first preset condition, the second preset condition, and the third preset condition are met; wherein, the first preset condition is that at least one of the detection result signals and the other detection result signals indicates that at least one of the functional modules has an abnormal functional module; the second preset condition is that the product form of the vehicle is a preset value; and the third preset condition is that the decision module of at least one of the functional modules is in an abnormal state or a normal state; sending the restart request signal to a restart module; and the restart module is capable of restarting the abnormal functional module based on the restart request signal.

[0015] In this embodiment, if all three preset conditions (first to third) are met within a third consecutive preset number of transmission cycles, a restart request signal is generated and sent to the restart module to cause the restart module to restart at least one functional module. Thus, this application can limit the restart conditions for at least one functional module with an abnormal function, improving the accuracy of restarting at least one functional module.

[0016] In some embodiments, the method further includes: acquiring a driving mode signal of the vehicle; determining the current driving mode of the vehicle based on the driving mode signal; and determining at least one functional module of the vehicle corresponding to the current driving mode.

[0017] In this embodiment, the current driving mode can be determined by the vehicle's driving mode signal, and then the functional modules that need to be detected can be quickly identified by the current driving mode, reducing the decrease in detection efficiency caused by detecting all functional modules.

[0018] This application provides a vehicle anomaly detection method applied to a vehicle's safety execution module, comprising: receiving detection result signals of at least one functional module of the vehicle sent by the vehicle's detection module; performing format conversion processing on the detection result signals to obtain converted detection result signals; determining the detection order of the at least one functional module of the vehicle; determining each two bits in the converted detection result signal as an anomaly detection result of the functional module according to the detection order; and performing safety processing on the functional module corresponding to the anomaly detection result indicating that the functional module has an anomaly; wherein, the anomaly detection result of each functional module is determined based on the heartbeat signals sampled for a consecutive preset number of sampling periods of each functional module; the preset number is determined based on the sampling period of the heartbeat signals and the size relationship between the heartbeat periods of the heartbeat signals.

[0019] In this embodiment, the received detection result signals of at least one functional module can be format-converted. Then, according to the detection order of the at least one functional module, every two bits in the converted detection result signal are determined as the anomaly detection result of the functional module. This allows for precise determination of the anomaly detection result of each functional module, enabling secure handling of the functional module corresponding to the anomaly detection result indicating an anomaly.

[0020] This application provides a vehicle anomaly detection device, the device comprising:

[0021] The acquisition unit is configured to acquire the sampling period for sampling the heartbeat signal of at least one functional module of the vehicle and the heartbeat period for at least one of the functional modules to send the heartbeat signal; the different heartbeat signals vary periodically.

[0022] The first determining unit is used to determine a preset number of sampling periods based on the relationship between the sampling period and the heartbeat period of the heartbeat signal;

[0023] The second determining unit is used to determine the abnormal detection result of each functional module based on the heartbeat signal sampled for a consecutive preset number of sampling periods of the functional module.

[0024] This application provides a vehicle anomaly detection device, characterized in that the device includes:

[0025] A receiving unit is configured to receive detection result signals of at least one functional module of the vehicle sent by the vehicle's detection module.

[0026] A conversion unit is used to perform format conversion processing on the detection result signal to obtain a converted detection result signal;

[0027] The third determining unit is used to determine the detection order of at least one of the functional modules of the vehicle;

[0028] The fourth determining unit is used to determine each two bits in the converted detection result signal as the abnormal detection result of the functional module according to the detection arrangement order.

[0029] A security unit is used to perform security processing on the functional module corresponding to the anomaly detection result that indicates that the functional module has an anomaly.

[0030] The anomaly detection result of each functional module is determined based on the heartbeat signal sampled for a preset number of consecutive sampling periods of each functional module; the preset number is determined based on the sampling period of the heartbeat signal and the relationship between the heartbeat period of the heartbeat signal.

[0031] This application provides a vehicle anomaly detection device, including: a memory for storing executable instructions; and a processor for executing the executable instructions stored in the memory to implement the vehicle anomaly detection method provided in this application.

[0032] This application provides a storage medium storing executable instructions, which, when executed by a processor, implement the vehicle anomaly detection method provided in this application. Attached Figure Description

[0033] Figure 1 A schematic flowchart of the vehicle anomaly detection method provided in the embodiments of this application;

[0034] Figure 2 A schematic flowchart of the vehicle anomaly detection method provided in the embodiments of this application;

[0035] Figure 3 A schematic flowchart of the vehicle anomaly detection method provided in the embodiments of this application;

[0036] Figure 4 A schematic flowchart of the vehicle anomaly detection method provided in the embodiments of this application;

[0037] Figure 5 A schematic flowchart of the vehicle anomaly detection method provided in the embodiments of this application;

[0038] Figure 6 A schematic flowchart of the vehicle anomaly detection method provided in the embodiments of this application;

[0039] Figure 7 A schematic flowchart of the vehicle anomaly detection method provided in the embodiments of this application;

[0040] Figure 8 This is a schematic diagram of the composition of the vehicle anomaly detection device provided in the embodiments of this application;

[0041] Figure 9 This is a schematic diagram of the composition of the vehicle anomaly detection device provided in the embodiments of this application;

[0042] Figure 10 This is a schematic diagram of the composition of the vehicle anomaly detection device provided in the embodiments of this application. Detailed Implementation

[0043] The technical solution of this application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0044] To enable those skilled in the art to better understand the embodiments of this disclosure, the technical solutions of the embodiments of this disclosure will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some of the embodiments of this application, and not all of them.

[0045] The terms "first," "second," and "third," etc., in the specification, embodiments, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, such as including a series of steps or units. A method, system, product, or apparatus is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or apparatuses.

[0046] Figure 1 This is a flowchart illustrating a vehicle anomaly detection method according to an embodiment of this application. In this embodiment, the detection method can be applied to a vehicle detection module. Figure 1 As shown, the process may include:

[0047] In S101, the sampling period for sampling the heartbeat signal of at least one functional module of the vehicle and the heartbeat period for sending the heartbeat signal by at least one functional module are obtained.

[0048] Here, a functional module can refer to an intelligent driving module to be detected in a vehicle. This intelligent driving module can be a module that is currently running or a module that is about to run. In some embodiments, a functional module may include at least one of the following: an onboard chip module, an entity rendering module, a feature localization module, a semantic localization module, a sensor fusion module, a path planning module, a decision-making module, and a conversion signal module.

[0049] In some embodiments, the intelligent driving module to be detected can be determined by the vehicle's current driving mode, with different driving modes corresponding to at least two functional modules. For example, when the vehicle's current driving mode is integrated cruise mode, the functional modules corresponding to this integrated cruise mode include: an onboard chip module, a decision-making module, and an entity rendering module, etc., meaning that anomaly detection needs to be performed on the onboard chip module, the decision-making module, and the entity rendering module.

[0050] Here, each functional module can emit a heartbeat signal, which reflects its own state. The different heartbeat signals emitted by a functional module over time exhibit periodic changes. That is, when multiple consecutive heartbeat signals from a functional module do not exhibit periodic changes—for example, when multiple consecutive heartbeat signals are identical—it can be determined that the functional module has malfunctioned. In some embodiments, the heartbeat signals of a functional module can vary periodically within a preset numerical range. For example, this preset numerical range can be 0 to 255.

[0051] Here, the sampling period refers to the time interval when acquiring the heartbeat signal. The heartbeat period refers to the time interval when the functional module sends the heartbeat signal. In some embodiments, the sampling period and the heartbeat period can be the same or different.

[0052] In S102, the preset number of sampling periods is determined based on the relationship between the sampling period and the heartbeat period of the heartbeat signal.

[0053] In this embodiment, the relationship between the sampling period and the heartbeat period of the heartbeat signal can be determined first, and then the preset number of sampling periods can be determined based on the relationship between the sampling period and the heartbeat period of the heartbeat signal.

[0054] Here, the preset number refers to the number of sampling periods used to sample the heartbeat signal of at least one functional module of the vehicle. In other words, the preset number of sampling periods can vary depending on the relationship between the sampling period and the heartbeat signal's heartbeat period. This is because the relationship between the sampling period and the heartbeat signal's heartbeat period determines whether the sampling period can cover the heartbeat signal's heartbeat period. If the sampling period can cover the heartbeat signal's heartbeat period, it means that one sampling period may include multiple heartbeat periods, and thus a smaller preset number is sufficient to determine the functional module's operating status. If the sampling period cannot cover the heartbeat signal's heartbeat period, it means that one heartbeat period may include multiple sampling periods, requiring a larger preset number to accurately determine the functional module's operating status.

[0055] In S103, for each functional module, the abnormal detection result of the functional module is determined based on the heartbeat signal sampled for a continuously preset number of sampling periods.

[0056] In this embodiment of the application, the heartbeat signal of each functional module can be sampled according to a preset number of sampling periods. This will result in a preset number of heartbeat signals of the functional module. Then, based on the preset number of heartbeat signals, the abnormal detection result of the functional module, i.e., the operating status of the functional module, can be determined.

[0057] Here, the anomaly detection results of a functional module can characterize whether the functional module has experienced an anomaly.

[0058] In some embodiments, whether a functional module is malfunctioning can be determined by checking whether the heartbeat signal sampled for a consecutive preset number of sampling periods meets a periodic change condition. Here, the periodic change condition can be a functional relationship between time and the heartbeat signal. Because, under normal conditions, the heartbeat signal changes at a constant rate over time, the functional relationship between time and the heartbeat signal is also constant. When the heartbeat signal sampled for a consecutive preset number of sampling periods does not meet the periodic change condition, it indicates that the functional module has malfunctioned.

[0059] In one embodiment, the anomaly detection result of the functional module can also be determined by comparing the heartbeat signals sampled for a consecutive preset number of sampling periods with their corresponding historical heartbeat signals. This is because, under normal conditions, different heartbeat signals exhibit periodic changes. If the heartbeat signals sampled for a consecutive preset number of sampling periods and their corresponding historical heartbeat signals do not show periodic changes, it indicates that an anomaly has occurred in the functional module.

[0060] In this embodiment, the preset number of sampling periods can be dynamically determined based on the relationship between the sampling period for sampling the heartbeat signals of at least one functional module of the vehicle and the heartbeat period of the heartbeat signals sent by at least one functional module. This reduces the inaccuracy of anomaly detection results caused by collecting a small number of heartbeat signals when the sampling period is short, and also reduces the efficiency reduction caused by collecting a large number of heartbeat signals when the sampling period is long. Finally, the anomaly detection result of each functional module is determined based on the heartbeat signals sampled for a consecutive preset number of sampling periods. This enables real-time detection of the operating status of the vehicle's functional modules, thereby reducing the occurrence of safety accidents due to functional module malfunctions.

[0061] Figure 2 This is a flowchart illustrating the vehicle anomaly detection method provided in this application embodiment, based on... Figure 1 , Figure 1 S102 may also include S201 to S202, which will combine Figure 2 The steps shown are explained.

[0062] In S201, when the sampling period is greater than or equal to the heartbeat period of the heartbeat signal, the preset number is determined to be the first preset number.

[0063] In S202, if the sampling period is less than the heartbeat period of the heartbeat signal, the preset number is determined to be the second preset number.

[0064] Here, the second preset quantity is greater than the first preset quantity. For example, the second preset quantity can be 15, and the first preset quantity can be 7.

[0065] In this embodiment, when the sampling period is greater than or equal to the heartbeat period of the heartbeat signal, it means that the time interval for acquiring the heartbeat signal is greater than or equal to the time interval for the functional module to send the heartbeat signal. That is, when acquiring one heartbeat signal, the functional module sends at least one heartbeat signal, ensuring that each acquired heartbeat signal is a newly sent heartbeat signal from the functional module. In this case, a smaller preset number, i.e., a first preset number, can be used, thereby reducing the resource waste caused by acquiring a large number of heartbeat signals to determine the abnormal detection result of the functional module when the sampling period is large.

[0066] In this embodiment, when the sampling period is less than the heartbeat period of the heartbeat signal, it means that the time interval for acquiring the heartbeat signal is less than the time interval for the functional module to send the heartbeat signal. That is, when acquiring a heartbeat signal, the functional module may not have sent a new heartbeat signal, thus it cannot be guaranteed that each acquired heartbeat signal is a newly sent heartbeat signal from the functional module. In this case, to ensure the accuracy of the functional module's anomaly detection results, a larger preset number, i.e., a second preset number, is needed. This ensures that the acquired preset number of heartbeat signals contain as many newly sent heartbeat signals as possible from the functional module, thereby reducing the problem of inaccurate anomaly detection results caused by determining the functional module's anomaly detection results by acquiring a small number of heartbeat signals when the sampling period is small.

[0067] In this embodiment, a first preset quantity can be determined when the sampling period is greater than or equal to the heartbeat period of the heartbeat signal; and a second preset quantity greater than the first preset quantity can be determined when the sampling period is less than the heartbeat period of the heartbeat signal. This allows the preset quantity to be dynamically determined based on the sampling period and the heartbeat period of the heartbeat signal, ensuring that the acquired heartbeat signal is as close as possible to the newly sent heartbeat signal from the functional module. This not only improves the accuracy of anomaly detection results from the functional module but also, when the sampling period is greater than or equal to the heartbeat period of the heartbeat signal, using a smaller first preset quantity can improve detection efficiency without reducing the accuracy of the anomaly detection results from the functional module.

[0068] Figure 3 This is a flowchart illustrating the vehicle anomaly detection method provided in this application embodiment, based on... Figure 1 , Figure 1 S103 in the formula may also include S301, which combines Figure 3 The steps shown are explained.

[0069] In S301, for each functional module, if the heartbeat values ​​sampled in a consecutive preset number of sampling periods of the functional module are the same as the historical heartbeat values ​​of the corresponding previous sampling period, an abnormal detection result representing an abnormality in the functional module is determined.

[0070] Here, the heartbeat signal in the above embodiments may include a heartbeat value, which can be any value within a preset value range. The preset quantity may be a first preset quantity or a second preset quantity greater than the first preset quantity.

[0071] In this embodiment, a preset number of heartbeat values ​​for each functional module can be continuously collected according to a preset number of sampling periods. These values ​​are then compared with the corresponding historical heartbeat values. If the preset number of heartbeat values ​​are identical to their respective historical heartbeat values, it indicates that the functional module has malfunctioned. Because different heartbeat signals exhibit periodic changes, if a preset number of consecutive heartbeat signals are identical to their corresponding historical heartbeat values, it indicates that the functional module has malfunctioned, thus obtaining an anomaly detection result characterizing the functional module's malfunction.

[0072] For example, if the preset number of sampling periods for a certain functional module is 3, then the heartbeat signal collected in sampling period 1 is signal 1, the heartbeat signal collected in sampling period 2 is signal 2, and the heartbeat signal collected in sampling period 3 is signal 3. The historical heartbeat signal corresponding to signal 2 is signal 1, and the historical heartbeat signal corresponding to signal 3 is signal 2. The historical heartbeat signal corresponding to signal 1 can be obtained from the storage module based on the time information of sampling period 1. Then, when signal 1 is the same as the historical heartbeat signal corresponding to signal 1, signal 2 is the same as signal 1, and signal 3 is the same as signal 2, an anomaly detection result representing an abnormality in the functional module is determined.

[0073] In this embodiment, an anomaly is determined to have occurred in a functional module only if a predetermined number of consecutive heartbeat values ​​are identical to the historical heartbeat values ​​of their respective previous sampling periods. This reduces the possibility of false positives and improves the accuracy of anomaly detection results for functional modules.

[0074] Figure 4 This is a flowchart illustrating the vehicle anomaly detection method provided in this application embodiment, based on... Figure 1 ,exist Figure 1 Following S103, the above method may further include S401 to S402, combining Figure 4 The steps shown are explained.

[0075] In S401, based on the anomaly detection results of each functional module, a detection result signal of at least one functional module is generated.

[0076] Here, the anomaly detection result of each functional module in the at least one functional module to be detected can be represented by a two-bit signal. For example, when the anomaly detection result of a functional module indicates that the functional module has an anomaly, it can be represented by "10" or "01"; when the anomaly detection result of a functional module indicates that the functional module has not an anomaly, it can be represented by "00". When the at least one functional module to be detected includes multiple functional modules, the anomaly detection results of each functional module can be sorted and combined according to the detection order, and then the format conversion processing of the sorted and combined anomaly detection results of each functional module is performed to obtain the detection result signal of at least one functional module. The detection result signal of at least one functional module can be represented by a uint64 decimal signal.

[0077] For example, the anomaly detection result of functional module 1 is "10", the anomaly detection result of functional module 2 is "00", and the anomaly detection result of functional module 3 is "01". The sorted and combined anomaly detection result is "100001". After format conversion, the detection result signal of functional modules 1, 2, and 3 is "33". When the anomaly detection results of functional modules 1, 2, and 3 are all "00", the detection result signal of functional modules 1, 2, and 3 is "0". In this way, by generating the detection result signal of at least one functional module, it is possible to determine whether there is an abnormal functional module in the at least one functional module to be detected by judging whether the detection result signal is "0". That is, when the detection result signal is "0", there is no abnormal functional module in at least one functional module; when the detection result signal is not "0", at least one abnormal functional module exists in at least one functional module. Moreover, decimal signals are more convenient to transmit than binary signals.

[0078] In S402, at least one detection result signal of a functional module and at least one other detection result signal of a functional module are sent to the safety execution module.

[0079] In this embodiment, the detection module in the vehicle can not only send the detection result signal of at least one functional module to the safety execution module, but also forward other detection result signals of at least one functional module detected by other detection modules to the safety execution module.

[0080] Here, other detection modules can perform anomaly detection on at least one functional module to be detected, and obtain other detection results. These other detection results can be represented by decimal signals from uint64.

[0081] In this embodiment, the safety execution module can shut down at least one functional module if at least one of the detection result signal and other detection result signals indicates the presence of an abnormal functional module within at least one functional module. In some embodiments, the safety execution module can determine the presence of an abnormal functional module within at least one functional module by judging whether at least one of the detection result signal and other detection result signals is "0". When at least one of the detection result signal and other detection result signals is not "0", it can indicate the presence of an abnormal functional module within at least one functional module.

[0082] In this embodiment, a detection result signal for at least one functional module can be generated based on the anomaly detection result of each functional module. This allows the security execution module to quickly determine whether an abnormal functional module exists within the at least one functional module based on the detection result signal. Then, the detection result signal for at least one functional module, along with other detection result signals for the at least one functional module, is sent to the security execution module. This allows the security execution module to determine whether to shut down at least one functional module based on the detection result signal and other detection result signals, reducing the likelihood of failing to shut down at least one functional module with an abnormal function in a timely manner due to inaccurate detection result signals.

[0083] In some embodiments, the method may further include: generating a restart request signal if, within a third preset number of transmission cycles of sending detection result signals, the first preset condition, the second preset condition, and the third preset condition are all met; and sending the restart request signal to a restart module. The restart module is capable of restarting the abnormal function module based on the restart request signal.

[0084] Here, the third preset quantity can be pre-set; for example, the third preset quantity can be 3. The sending period is the period for sending the detection result signal, that is, the sending period is the same as the sampling period of the heartbeat signal of the acquisition function module.

[0085] The first preset condition is that the detection result signal indicates that at least one functional module has an abnormal functional module, that is, the detection result signal is not "0".

[0086] The second preset condition is that the product form of the vehicle is a preset value, where the preset value can be "0". By determining the product form of the vehicle, it can be determined whether the detection module has enabled the detection module abnormal function. If the product form of the vehicle is the preset value, it is determined that the detection module has enabled the detection module abnormal function. If the product form of the vehicle is not the preset value, it is determined that the detection module has not enabled the detection module abnormal function.

[0087] The third preset condition is that the decision module in at least one functional module is in an abnormal or normal state. In some embodiments, the decision module is included in all driving modes of the vehicle, so when determining at least one functional module, the current state of the decision module can be determined. In some embodiments, it can be determined whether the decision module is in an abnormal state by determining whether the abnormal detection result of the decision module is "0"; when the abnormal detection result of the decision module is not "0" and lasts for a preset time, it can be determined that the decision module is in an abnormal state. In some embodiments, it can be determined whether the decision module is in a normal state by obtaining the PD_APA function enable state; when the PD_APA function enable state is "0", it is determined that the decision module is in a normal state and exits the function based on the instruction of the safety execution module.

[0088] In this embodiment, if all three preset conditions (first to third) are met within a third consecutive preset number of transmission cycles, a restart request signal is generated and sent to the restart module to restart the abnormal function module. This allows the restart module to define the restart conditions for at least one function module with an abnormal function module, improving the accuracy of restarting at least one function module.

[0089] Figure 5 This is a flowchart illustrating the vehicle anomaly detection method provided in this application embodiment, based on... Figure 1 ,exist Figure 1 Before S101, the above method may further include S501 to S503, combining Figure 5 The steps shown are explained.

[0090] In S501, the vehicle's driving mode signal is acquired.

[0091] In S502, the current driving mode of the vehicle is determined based on the driving mode signal.

[0092] Here, the driving mode signal can be represented by a value within a preset range, with different values ​​representing different driving modes. In some embodiments, the preset range can be 1 to 30. For example, when the driving mode signal is 22, the vehicle's current driving mode is integrated cruise mode.

[0093] In some embodiments, a mapping table of driving mode signals and driving modes can be obtained. The mapping table includes the mapping relationship between each driving mode signal and the driving mode. The corresponding mapping relationship can be found in the mapping table based on the driving mode signal, and then the current driving mode corresponding to the driving mode signal can be determined based on the found mapping relationship.

[0094] In S503, at least one functional module of the vehicle corresponding to the current driving mode is identified.

[0095] Here, different driving modes correspond to different functional modules. For example, when the vehicle's current driving mode is integrated cruise mode, the corresponding functional modules include: on-board chip module, decision-making module, and entity rendering module, etc. That is, the on-board chip module, decision-making module, and entity rendering module need to be tested. In other words, when the current driving mode is integrated cruise mode, the above functional modules need to be tested.

[0096] In some embodiments, a mapping table of driving modes and functional modules can be obtained, which includes the mapping relationship between each driving mode and a functional module. The corresponding mapping relationship can be found in the mapping table based on the current driving mode, and then the functional module that needs to be detected corresponding to the current driving mode can be determined based on the found mapping relationship.

[0097] In this embodiment, the current driving mode can be determined by the vehicle's driving mode signal, and then the functional modules that need to be detected can be quickly identified by the current driving mode, reducing the decrease in detection efficiency caused by detecting all functional modules.

[0098] Figure 6 This is a flowchart illustrating a vehicle anomaly detection method according to an embodiment of this application. In this embodiment, the detection method can be applied to the vehicle's safety execution module. Figure 6 As shown, the process may include:

[0099] In S601, the detection result signal of at least one functional module of the vehicle is received from the vehicle's detection module.

[0100] Here, the detection result signal of at least one functional module can be represented by a decimal signal of uint64.

[0101] In some embodiments, after receiving the detection result signal from at least one functional module, the safety execution module can judge the detection result signal of the at least one functional module. If the detection result signal is not "0", then at least one functional module is shut down. Wherein, a detection result signal not being "0" indicates that there is an abnormal functional module among the at least one functional module, and at this time, at least one functional module needs to be shut down.

[0102] In some embodiments, the security execution module can also receive other detection result signals of at least one functional module forwarded by the detection module, and can judge the other detection result signals of at least one functional module. If the other detection result signals are not "0", then at least one functional module is shut down. Wherein, if the other detection result signals are not "0", it indicates that there is an abnormal functional module in at least one functional module, and at this time, at least one functional module needs to be shut down.

[0103] In S602, the detection result signal is processed for format conversion to obtain the converted detection result signal.

[0104] Here, format conversion processing can be a method of converting decimal signals into binary signals. In other words, the converted detection result signal is a binary signal.

[0105] In some embodiments, the security execution module may also perform format conversion processing on other detection result signals received from at least one functional module to obtain converted other detection result signals.

[0106] In S603, the detection sequence of at least one functional module of the vehicle is determined.

[0107] Here, the detection order can be a preset order for at least one functional module, which corresponds to the driving mode. For example, the functional modules corresponding to driving mode 1 include functional module a, functional module b, and functional module c. Then, the corresponding detection order is functional module a as sequence 1, functional module a as sequence 2, and functional module a as sequence 3.

[0108] In S604, according to the detection order, every two bits in the converted detection result signal are determined as the abnormal detection result of the functional module.

[0109] Here, the anomaly detection result of each functional module is determined based on the heartbeat signal sampled for a consecutive preset number of sampling periods of each functional module; the preset number is determined based on the sampling period of the heartbeat signal and the magnitude relationship between the heartbeat periods of the heartbeat signal.

[0110] In this embodiment of the application, after obtaining the detection order of at least one functional module, each two bits in the converted detection result signal can be determined as the abnormal detection result of the functional module according to the corresponding detection order.

[0111] For example, the detection order of at least one functional module is functional module a as sequence 1, functional module a as sequence 2, and functional module a as sequence 3. The corresponding converted detection result signal is 100001. According to the detection order of functional module a as sequence 1, functional module a as sequence 2, and functional module a as sequence 3, it can be determined that the two bits corresponding to functional module a are "10", so the abnormal detection result of functional module a is "10". The two bits corresponding to functional module b are "00", so the abnormal detection result of functional module b is "00". The two bits corresponding to functional module c are "01", so the abnormal detection result of functional module c is "01". That is, functional modules a and functional modules c are abnormal functional modules, and functional module b is a normal functional module.

[0112] In some embodiments, the security execution module may also determine each two bits in the converted other detection result signals as the abnormal detection result of the functional module according to the detection order.

[0113] In S605, the functional module corresponding to the anomaly detection result of the characterization functional module is subjected to safety processing.

[0114] In this embodiment of the application, the security execution module can determine at least one abnormal functional module (i.e., the functional module corresponding to the abnormal detection result that represents the abnormality of the functional module) after obtaining the abnormal detection result of each functional module, and then perform security processing on the abnormal functional module.

[0115] In some embodiments, the safe execution module can modify the code of the exception function module.

[0116] In this embodiment, the received detection result signals of at least one functional module can be format-converted. Then, according to the detection order of the at least one functional module, every two bits in the converted detection result signal are determined as the anomaly detection result of the functional module. This allows for precise determination of the anomaly detection result of each functional module, enabling secure handling of the functional module corresponding to the anomaly detection result indicating an anomaly.

[0117] Figure 7 This is a flowchart illustrating the vehicle anomaly detection method according to an embodiment of this application. Figure 7 As shown, the process may include:

[0118] In S701, the security monitoring system identifies the functional modules to be tested.

[0119] In this embodiment of the application, the safety monitoring system can determine the current driving mode through driving signals, and then determine the functional modules to be detected based on the current driving mode.

[0120] In some embodiments, the driving signal (adc_status) is a value from 1, 2, 3...30 (different values ​​represent different driving modes). The heartbeat of the corresponding module to be monitored in each driving mode can be selected based on that mode (each module is a small system with its own inputs and outputs; its heartbeat indicates whether the module is operating normally).

[0121] In the S702, the safety monitoring system collects heartbeat signals from functional modules.

[0122] In this embodiment of the application, the heartbeat signal of the module may include at least one of the following: the heartbeat signal of the vehicle chip module (ab8155_counter), the heartbeat signal of the entity rendering module (net_mng_counter), the heartbeat signal of the feature localization module (vf_loc_counter), the heartbeat signal of the semantic localization module (vs_loc_counter), the heartbeat signal of the sensor fusion module (fus_obj_counter), the heartbeat signal of the sensor fusion module (fus_fs_counter), the heartbeat signal of the path planning module (mts_counter), the heartbeat signal of the parking space release and mapping module (dcs_counter), the heartbeat signal of the decision module (stm_counter), the heartbeat signal of the conversion signal module (render_counter), and the heartbeat signal of the module outside the system (zm counter).

[0123] In S703, the security monitoring system detects functional modules based on their heartbeat signals and obtains its own monitoring result signals.

[0124] In this embodiment, when the heartbeat signal transmission period of the functional module is less than or equal to the sampling period of the safety monitoring system, if the heartbeat value of the functional module in the current period (sampling period) is the same as the heartbeat value of the previous period for seven consecutive sampling periods during normal vehicle operation, the functional module is determined to be malfunctioning, and a signal indicating the malfunction (its own monitoring result signal) is sent downstream. Otherwise, the functional module's heartbeat is considered normal. When the heartbeat transmission period of the functional module is greater than the sampling transmission period of the safety monitoring system, if the heartbeat value of the functional module in the current period is the same as the heartbeat value of the previous period for 15 consecutive monitoring periods during normal vehicle operation, the functional module is determined to be malfunctioning, and a signal indicating the malfunction (i.e., its own monitoring result signal, which can be represented by mnt_soc_result) is sent downstream. Otherwise, the functional module's heartbeat is considered normal.

[0125] Here, the operating status of a module can be observed through the heartbeat signals emitted by that module. The heartbeat signal transmission period refers to the time interval required for the module's heartbeat to complete once. The sampling period refers to the time interval at which the security monitoring system acquires the heartbeat signals from the functional modules.

[0126] In S704, the security monitoring system sends its own monitoring result signals and forwarded monitoring result signals to the security policy execution system.

[0127] After the monitoring logic module determines that there is an anomaly, the security monitoring system sends a decimal monitoring result (mnt_soc_result) and a forwarded monitoring result (mnt_zm_result) to the security policy execution system every 100ms.

[0128] In S705, the security policy enforcement system processes functional modules based on its own monitoring results signals and the forwarded monitoring results signals.

[0129] In this embodiment, the safety policy execution system can determine whether at least one of its own monitoring result signal and the forwarded monitoring result signal is 0. If at least one of its own monitoring result signal and the forwarded monitoring result signal is 0, it indicates that a functional module is malfunctioning. The safety policy execution system can force the system to exit all functions and switch from intelligent driving to human driving, thus ensuring safety during driving or parking.

[0130] In some embodiments, the security policy execution system can convert its own monitoring result signal and the forwarded monitoring result signal into a 64-bit binary number string. Each two bits in the binary number string represent a module, with 0 indicating normal and 1 indicating abnormal. Then, by looking up a table, the system can parse out which module is malfunctioning, thus accurately locating which module has encountered an abnormal situation.

[0131] In S706, the security monitoring system generates a restart request signal based on its own monitoring results and sends the restart request signal to the restart module.

[0132] In some embodiments, if the monitoring result signal of the system itself is not 0, the product form of the vehicle is 0, the PD_APA function enable state is 0, or the monitoring logic judgment result of the STM is not 0 for 10 seconds, and these three conditions are met simultaneously and remain unchanged in the three sending cycles of the safety monitoring system, then the safety monitoring system will send a restart request signal (mnt_soc_restart_req=1) to the restart module. After receiving the signal, the restart module can restart the abnormal function module.

[0133] The safety monitoring system in this embodiment can perform real-time online monitoring of the heartbeats of different functional modules for different driving modes. This monitoring mode minimizes the waste of SOC system-level chip resources, improves software operating efficiency, and reduces the possibility of system crashes due to excessive resource consumption. When the vehicle control system is affected by external environmental factors, the autonomous driving function may be impacted. This safety monitoring system can perform real-time online monitoring of the main functional modules in the control system and transmit the driving results to the safety policy execution module and restart module in real time. Before a safety issue occurs, it can promptly and effectively restart the modules after the vehicle exits the parking function, thereby reducing the occurrence of vehicle loss of control and other problems without affecting the next activation of the autonomous driving function.

[0134] This application provides a vehicle anomaly detection device. Figure 8 This is a schematic diagram of the structural composition of a vehicle anomaly detection device 800 provided in an embodiment of this application, as shown below. Figure 8 As shown, the device includes: an acquisition unit 801, a first determination unit 802, and a second determination unit 803, wherein:

[0135] The acquisition unit 801 is used to acquire the sampling period for sampling the heartbeat signal of at least one functional module of the vehicle and the heartbeat period for at least one of the functional modules to send the heartbeat signal; the different heartbeat signals vary periodically.

[0136] The first determining unit 802 is used to determine a preset number of sampling periods based on the relationship between the sampling period and the heartbeat period of the heartbeat signal.

[0137] The second determining unit 803 is used to determine the abnormal detection result of each functional module based on the heartbeat signal sampled for a consecutive preset number of sampling periods of the functional module.

[0138] In some embodiments, the preset quantity includes a first preset quantity and a second preset quantity greater than the first preset quantity; the first determining unit 802 is further configured to determine the preset quantity as the first preset quantity when the sampling period is greater than or equal to the heartbeat period of the heartbeat signal; and to determine the preset quantity as the second preset quantity when the sampling period is less than the heartbeat period of the heartbeat signal.

[0139] In some embodiments, the heartbeat signal includes a heartbeat value; the second determining unit 803 is further configured to, for each of the functional modules, determine an anomaly detection result characterizing an anomaly of the functional module when the heartbeat values ​​sampled in a consecutive preset number of sampling periods of the functional module are all the same as the historical heartbeat values ​​of the corresponding previous sampling period.

[0140] In some embodiments, the apparatus further includes: a generation unit and a transmission unit; wherein: the generation unit is configured to generate a detection result signal for the at least one functional module based on the anomaly detection result of each functional module; the transmission unit is configured to transmit the detection result signal of the at least one functional module and other detection result signals of the at least one functional module to the security execution module; wherein the security execution module is capable of shutting down the at least one functional module if at least one of the detection result signals and the other detection result signals indicates the presence of an abnormal functional module in the at least one functional module.

[0141] In some embodiments, the generating unit is further configured to generate a restart request signal when, within a third preset number of transmission cycles of the detection result signals or the other detection result signals, all of the first preset condition, the second preset condition, and the third preset condition are met; wherein, the first preset condition is that at least one of the detection result signals and the other detection result signals indicates that at least one of the functional modules has an abnormal functional module; the second preset condition is that the product form of the vehicle is a preset value; and the third preset condition is that the decision module of at least one of the functional modules is in an abnormal state or a normal state; the sending unit is further configured to send the restart request signal to the restart module; the restart module is capable of restarting the at least one functional module based on the restart request signal.

[0142] In some embodiments, the acquisition unit 801 is further configured to acquire a driving mode signal of the vehicle; the device further includes: a fifth determining unit and a sixth determining unit; wherein: the fifth determining unit is configured to determine the current driving mode of the vehicle based on the driving mode signal; the sixth determining unit is configured to determine at least one functional module of the vehicle corresponding to the current driving mode.

[0143] This application provides a vehicle anomaly detection device. Figure 9 This is a schematic diagram of the structural composition of a vehicle anomaly detection device 900 provided in an embodiment of this application, as shown below. Figure 9 As shown, the device includes: a receiving unit 901, a conversion unit 902, a third determining unit 903, a fourth determining unit 904, and a security unit 905, wherein:

[0144] The receiving unit 901 is used to receive the detection result signal of at least one functional module of the vehicle sent by the vehicle's detection module;

[0145] The conversion unit 902 is used to perform format conversion processing on the detection result signal to obtain the converted detection result signal;

[0146] The third determining unit 903 is used to determine the detection order of at least one of the functional modules of the vehicle;

[0147] The fourth determining unit 904 is used to determine each two bits in the converted detection result signal as the abnormal detection result of the functional module according to the detection arrangement order.

[0148] Security unit 905 is used to perform security processing on the functional module corresponding to the anomaly detection result that characterizes the functional module's abnormality; wherein, the anomaly detection result of each functional module is determined based on the heartbeat signal sampled for a consecutive preset number of sampling periods of each functional module; the preset number is determined based on the sampling period of the heartbeat signal and the magnitude relationship between the heartbeat period of the heartbeat signal.

[0149] The descriptions of the apparatus embodiments above are similar to those of the method embodiments above, and have similar beneficial effects. In some embodiments, the functions or modules included in the apparatus provided in this application can be used to perform the methods described in the method embodiments above. For technical details not disclosed in the apparatus embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0150] It should be noted that, in the embodiments of this application, if the above-described vehicle anomaly detection method is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, or the part that contributes to the related technology, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware, software, or firmware, or any combination of hardware, software, and firmware.

[0151] This application provides a computer device including a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the program, it implements some or all of the steps in the above-described method.

[0152] This application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements some or all of the steps in the above-described method. The computer-readable storage medium can be transient or non-transient.

[0153] This application provides a computer program including computer-readable code, wherein when the computer-readable code is executed in a computer device, a processor in the computer device performs some or all of the steps in the above-described method.

[0154] This application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program. When the computer program is read and executed by a computer, it implements some or all of the steps in the above-described method. This computer program product can be implemented specifically through hardware, software, or a combination thereof. In some embodiments, the computer program product is specifically embodied as a computer storage medium; in other embodiments, the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc.

[0155] It should be noted that the descriptions of the various embodiments above tend to emphasize the differences between them, while their similarities or commonalities can be referred to interchangeably. The descriptions of the above embodiments of the device, storage medium, computer program, and computer program product are similar to the descriptions of the above method embodiments and have similar beneficial effects. For technical details not disclosed in the embodiments of the device, storage medium, computer program, and computer program product of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0156] This application provides a vehicle anomaly detection device. Figure 10 This is a schematic diagram of the composition structure of the vehicle anomaly detection device 1000 provided in the embodiments of this application, as shown below. Figure 10 As shown, the device includes: a processor 1001, a communication interface 1002, and a memory 1003, wherein:

[0157] The processor 1001 typically controls the overall operation of the computer device 1000, which may include implementing the vehicle anomaly detection method provided in the embodiments of this application, for example... Figures 1 to 7 The method shown.

[0158] The communication interface 1002 enables computer devices to communicate with other terminals or servers via a network.

[0159] The memory 1003 is configured to store instructions and applications executable by the processor 1001, and can also cache data to be processed or already processed (e.g., image data, audio data, voice communication data, and video communication data) in the processor 1001 and various modules in the computer device 1000. It can be implemented using flash memory or random access memory (RAM). Data transfer between the processor 1001, the communication interface 1002, and the memory 1003 can be performed via bus 1004.

[0160] This application provides a computer program product or computer program that includes computer instructions stored in a readable storage medium. A processor of a computer device reads the computer instructions from the readable storage medium and executes the computer instructions, causing the computer device to perform the vehicle anomaly detection method described above in this application.

[0161] This application provides a readable storage medium storing executable instructions. When these executable instructions are executed by a processor, they cause the processor to execute the vehicle anomaly detection method provided in this application. For example... Figures 1 to 7 The method shown.

[0162] It should be noted that the descriptions of the storage medium and device embodiments above are similar to the descriptions of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0163] The aforementioned processor can be at least one of the following: Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), Central Processing Unit (CPU), Controller, Microcontroller, and Microprocessor. It is understood that other electronic devices can also implement the functions of the aforementioned processor, and this application does not specifically limit the specific implementation.

[0164] The aforementioned computer storage media / memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM), etc.; or it can be various terminals that include one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc.

[0165] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above steps / processes do not imply a sequential order of execution; the execution order of each step / process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above embodiments of this application are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0166] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0167] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and 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. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0168] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0169] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0170] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0171] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence or the part that contributes to related technologies, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, magnetic disks, or optical disks.

[0172] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for detecting vehicle anomalies, characterized in that, The detection module applied to the vehicle includes: The sampling period for sampling the heartbeat signal of at least one functional module of the vehicle and the heartbeat period for at least one of the functional modules to send the heartbeat signal are obtained; the different heartbeat signals vary periodically. Based on the relationship between the sampling period and the heartbeat period of the heartbeat signal, a preset number of sampling periods is determined; for each functional module, based on the heartbeat signal sampled by the functional module for a consecutive preset number of sampling periods, the abnormal detection result of the functional module is determined.

2. The method according to claim 1, characterized in that, The preset quantity includes a first preset quantity and a second preset quantity greater than the first preset quantity; determining the preset quantity of the sampling period based on the relationship between the sampling period and the heartbeat period of the heartbeat signal includes: If the sampling period is greater than or equal to the heartbeat period of the heartbeat signal, the preset number is determined to be a first preset number; If the sampling period is less than the heartbeat period of the heartbeat signal, the preset number is determined to be a second preset number.

3. The method according to claim 1, characterized in that, The heartbeat signal includes a heartbeat value; for each functional module, determining the anomaly detection result of the functional module based on the heartbeat signal sampled for a consecutive preset number of sampling periods includes: For each functional module, if the heartbeat values ​​sampled in a consecutive preset number of sampling periods of the functional module are all the same as the historical heartbeat values ​​of the corresponding previous sampling period, an anomaly detection result representing an anomaly in the functional module is determined.

4. The method according to any one of claims 1 to 3, characterized in that, The method further includes: Based on the anomaly detection results of each of the functional modules, a detection result signal for the at least one functional module is generated. Send the detection result signal of the at least one functional module and other detection result signals of the at least one functional module to the safety execution module; The security execution module can shut down the at least one functional module if at least one of the detection result signals and other detection result signals indicates that there is an abnormal functional module in the at least one functional module.

5. The method according to claim 4, characterized in that, The method further includes: If, within a third preset number of consecutive transmission cycles of sending the detection result signal, the first preset condition, the second preset condition, and the third preset condition are all met, a restart request signal is generated; wherein, the first preset condition is that the detection result signal indicates that at least one of the functional modules has an abnormal functional module; the second preset condition is that the product form of the vehicle is a preset value; and the third preset condition is that at least one of the functional modules is in an abnormal or normal state. The restart request signal is sent to the restart module; the restart module can restart the abnormal function module based on the restart request signal.

6. The method according to any one of claims 1 to 3, characterized in that, The method further includes: Acquire the driving mode signal of the vehicle; The current driving mode of the vehicle is determined based on the driving mode signal; Identify at least one functional module of the vehicle corresponding to the current driving mode.

7. A method for detecting vehicle anomalies, characterized in that, The safety execution module applied to the vehicle includes: Receive the detection result signal of at least one functional module of the vehicle sent by the vehicle's detection module; The detection result signal is processed by format conversion to obtain the converted detection result signal; Determine the detection order of at least one of the functional modules of the vehicle; According to the detection order, each two bits in the converted detection result signal are determined as the abnormal detection result of the functional module; The functional modules corresponding to the anomaly detection results that indicate that the functional modules have become abnormal are subject to security processing. The anomaly detection result of each functional module is determined based on the heartbeat signal sampled for a preset number of consecutive sampling periods of each functional module; the preset number is determined based on the sampling period of the heartbeat signal and the relationship between the heartbeat period of the heartbeat signal.

8. A vehicle anomaly detection device, characterized in that, The device includes: The acquisition unit is configured to acquire the sampling period for sampling the heartbeat signal of at least one functional module of the vehicle and the heartbeat period for at least one of the functional modules to send the heartbeat signal; the different heartbeat signals vary periodically. The first determining unit is used to determine a preset number of sampling periods based on the relationship between the sampling period and the heartbeat period of the heartbeat signal; The second determining unit is used to determine the abnormal detection result of each functional module based on the heartbeat signal sampled for a consecutive preset number of sampling periods of the functional module.

9. A vehicle anomaly detection device, characterized in that, The device includes: A receiving unit is configured to receive detection result signals of at least one functional module of the vehicle sent by the vehicle's detection module. A conversion unit is used to perform format conversion processing on the detection result signal to obtain a converted detection result signal; The third determining unit is used to determine the detection order of at least one of the functional modules of the vehicle; The fourth determining unit is used to determine each two bits in the converted detection result signal as the abnormal detection result of the functional module according to the detection arrangement order. A security unit is used to perform security processing on the functional module corresponding to the anomaly detection result that characterizes the anomaly of the functional module; wherein, the anomaly detection result of each functional module is determined based on the heartbeat signal sampled for a consecutive preset number of sampling periods of each functional module; the preset number is determined based on the sampling period of the heartbeat signal and the magnitude relationship between the heartbeat period of the heartbeat signal.

10. A vehicle anomaly detection device, characterized in that, include: Memory, used to store executable instructions; A processor, when executing executable instructions stored in the memory, implements the method according to any one of claims 1 to 7.

11. A storage medium, characterized in that, The storage medium stores executable instructions that, when executed by a processor, implement the method described in any one of claims 1 to 7.

Images