Vehicle fault information determination method and device, equipment and storage medium

Abstract

The invention discloses a vehicle fault information determination method and device, equipment and a storage medium, and belongs to the technical field of vehicle detection. The method comprises the following steps: acquiring related information of a vehicle, wherein the related information of the vehicle comprises driving information and environment information; determining a driving scene and a driving condition of the vehicle based on the related information of the vehicle; determining a first threshold range corresponding to actual control parameters of the vehicle by using the driving scene and the driving working condition; under the condition that the actual control parameters are within the first threshold range, target control parameters of the vehicle are determined based on the vehicle control model, the driving information and the environment information; determining abnormal control information of the vehicle by using the actual control parameter, the target control parameter and a second threshold range; fault information of the vehicle is determined based on the abnormal control information and a parameter of a reference electronic device, the reference electronic device being a device in the vehicle related to the abnormal control information. According to the method, misjudgment or missed judgment of the fault information is effectively avoided, and the accuracy of the fault information is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of vehicle detection technology, and in particular to a method, apparatus, device, and storage medium for determining vehicle fault information. Background Art

[0002] With the rapid development of vehicle intelligence, the safety and reliability of vehicles during driving are receiving more and more attention.

[0003] In related technologies, vehicle fault detection generally relies on comparing parameters contained in vehicle driving information with preset parameter ranges to obtain vehicle fault information. The determination of vehicle fault information is single-minded, resulting in low accuracy of vehicle fault information. Summary of the Invention

[0004] The embodiment of the present application provides a method for determining vehicle fault information, which can improve the accuracy of the determined vehicle fault information, thereby improving the safety during vehicle driving. The technical solution is as follows:

[0005] In one aspect, an embodiment of the present application provides a method for determining vehicle fault information, the method comprising:

[0006] Acquiring relevant information about the vehicle, the relevant information about the vehicle including driving information and environmental information, the driving information being used to characterize the driving state of the vehicle, and the environmental information being used to characterize the external environment in which the vehicle is located;

[0007] determining a driving scenario and a driving condition of the vehicle based on the relevant information of the vehicle;

[0008] Determining a first threshold range corresponding to an actual control parameter of the vehicle using the driving scenario and the driving condition;

[0009] determining a target control parameter of the vehicle based on a vehicle control model, the driving information, and the environmental information when the actual control parameter is within the first threshold range;

[0010] determining abnormal control information of the vehicle using the actual control parameter, the target control parameter, and a second threshold range;

[0011] Fault information of the vehicle is determined based on the abnormal control information and parameters of a reference electronic component, where the reference electronic component is a component in the vehicle that is related to the abnormal control information.

[0012] On the other hand, an embodiment of the present application provides a device for determining vehicle fault information, the device comprising:

[0013] An acquisition module is used to acquire relevant information of the vehicle, wherein the relevant information of the vehicle includes driving information and environmental information, wherein the driving information is used to represent the driving state of the vehicle, and the environmental information is used to represent the external environment in which the vehicle is located;

[0014] a determination module, configured to determine a driving scenario and a driving condition of the vehicle based on relevant information of the vehicle;

[0015] The determining module is further configured to determine a first threshold range corresponding to the actual control parameter of the vehicle using the driving scenario and the driving condition;

[0016] The determining module is further configured to determine a target control parameter of the vehicle based on a vehicle control model, the driving information, and the environmental information when the actual control parameter is within the first threshold range;

[0017] The determining module is further configured to determine abnormal control information of the vehicle using the actual control parameter, the target control parameter, and a second threshold range;

[0018] The determination module is further configured to determine fault information of the vehicle based on the abnormal control information and parameters of a reference electronic component, where the reference electronic component is a component in the vehicle that is related to the abnormal control information.

[0019] In one possible implementation, the apparatus further includes a control module, configured to trigger a safety response mechanism of the vehicle when the fault information indicates that the fault type is a hardware fault, the safety response mechanism including at least one of recording the fault information, generating an alarm, performing a fault isolation operation on the faulty hardware, or initiating a safe parking procedure;

[0020] In a case where the safety response mechanism instructs to adjust the actual control parameters of the vehicle, a parameter adjustment instruction is generated, and the actual control parameters of the vehicle are adjusted based on the parameter adjustment instruction.

[0021] In one possible implementation, the determination module is used to obtain an initial threshold range corresponding to the actual control parameter of the vehicle; determine a first adjustment parameter based on the driving scenario, and determine a second adjustment parameter based on the driving condition; and adjust the initial threshold range using the first adjustment parameter and the second adjustment parameter to obtain the first threshold range.

[0022] In one possible implementation, the determination module is used to convert the actual control parameter to obtain the actual control parameter after conversion, and the conversion processing includes at least one of denoising processing or encryption and decryption processing; calculate the difference between the actual control parameter after conversion and the target control parameter; and determine the abnormal control information based on the actual control parameter corresponding to the difference exceeding the second threshold range.

[0023] In one possible implementation, the determination module is used to generate constraints corresponding to the vehicle control model using the driving information and the environmental information; generate initial control parameters and performance indicators corresponding to the initial control parameters based on the constraints, the vehicle control model, the driving information and the environmental information; and determine the initial control parameters whose performance indicators are greater than the indicator threshold as the target control parameters of the vehicle.

[0024] In one possible implementation, the determination module is used to perform feature extraction on the driving information to obtain a first feature; perform feature extraction on the environmental information to obtain a second feature; fuse the first feature and the second feature to obtain a fused feature; and use the fused feature to determine the driving scene and the driving condition.

[0025] On the other hand, an embodiment of the present application provides a computer device, which includes a processor and a memory, wherein the memory stores at least one program code, and the at least one program code is loaded and executed by the processor so that the computer device implements any of the above-mentioned methods for determining vehicle fault information.

[0026] On the other hand, a computer-readable storage medium is also provided, in which at least one program code is stored. The at least one program code is loaded and executed by a processor to enable the computer to implement any of the above-mentioned methods for determining vehicle fault information.

[0027] On the other hand, a computer program or computer program product is also provided, wherein the computer program or computer program product stores at least one computer instruction, and the at least one computer instruction is loaded and executed by a processor so that the computer implements any of the above-mentioned methods for determining vehicle fault information.

[0028] The technical solutions provided by the embodiments of the present application bring at least the following beneficial effects:

[0029] The technical solution provided by the exemplary embodiment of the present application determines the vehicle's driving scenario and driving conditions through the vehicle's driving information and environmental information, and uses the driving scenario and driving conditions to determine a first threshold range corresponding to the vehicle's actual control parameters, so that the first threshold range is more consistent with the current vehicle's driving state, and the determined first threshold range is more reasonable and accurate, so that the vehicle's safety state can be accurately determined through the first threshold range. When the vehicle's real-time control parameters are within the first threshold range, the vehicle's real-time control parameters, target control parameters, and second threshold range are used to further determine the vehicle's abnormal control information, and the abnormal control information is used to determine the vehicle's fault information, effectively avoiding misjudgment or omission of the vehicle's fault information, improving the accuracy of the vehicle's fault information, and ensuring the vehicle's driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0031] Figure 1 This is a schematic diagram of an implementation environment provided by an embodiment of the present application;

[0032] Figure 2 This is a flow chart of a method for determining vehicle fault information provided by an embodiment of the present application;

[0033] Figure 3 This is a schematic diagram of the structure of a device for determining vehicle fault information provided by an embodiment of the present application;

[0034] Figure 4 Schematic diagram of a device for determining vehicle fault information based on a vehicle-mounted intelligent power three-in-one control system provided by an embodiment of the present application;

[0035] Figure 5 This is a structural block diagram of a terminal device provided in an embodiment of the present application;

[0036] Figure 6 This is a structural diagram of a server provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0038] It should be noted that the terms "first," "second," and the like in this application are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0039] Figure 1 This is a schematic diagram of an implementation environment provided by an embodiment of the present application. Figure 1 As shown, the implementation environment may include a vehicle 101 and a vehicle control system 102. The vehicle control system 102 is used to control the vehicle 101 to perform corresponding operations. The vehicle control system 102 may be located in the vehicle 101, for example, the vehicle control system 102 is an on-board terminal; the vehicle control system 102 may also be located outside the vehicle 101, for example, the vehicle control system 102 is a cloud control system.

[0040] The vehicle control system 102 may be an independent server, or the vehicle control system 102 may be a server cluster composed of multiple servers that implement different functions, or the vehicle control system 102 may be a cloud computing center.

[0041] Vehicle 101 may be a vehicle with intelligent assisted driving capabilities and may be equipped with hardware such as cameras, millimeter-wave radars, lidars, positioning sensors, and communication sensors. Vehicle 101 obtains vehicle-related information through the configured hardware, which may include vehicle driving information and information about the vehicle's surroundings. Vehicle control system 102 may determine the vehicle's safe driving status based on the vehicle-related information from vehicle 101 and generate corresponding fault information if the vehicle's safe driving status is abnormal.

[0042] The vehicle 101 may also have a wireless communication function. A communication module supporting wireless communication technology or wired communication technology may be provided in the vehicle 101 . The vehicle 101 exchanges data with the vehicle control system 102 through the communication module.

[0043] Based on the above Figure 1 In the implementation environment shown, the present application embodiment provides a method for determining vehicle fault information. Figure 2 As shown, this method can be Figure 1 The method may be performed by the vehicle 101 in the vehicle control system 102, or may be performed interactively by the vehicle 101 and the vehicle control system 102. The method may include steps 201 to 206.

[0044] In step 201, relevant information of the vehicle is obtained. The relevant information of the vehicle includes driving information and environmental information. The driving information is used to characterize the driving state of the vehicle, and the environmental information is used to characterize the external environment in which the vehicle is located.

[0045] In an exemplary embodiment of the present application, the vehicle may be a vehicle with an on-board intelligent system, and the on-board intelligent system has an information acquisition device, through which vehicle information can be acquired. For example, the information acquisition device may include but is not limited to a camera, a millimeter-wave radar, a lidar, and a plurality of sensors, wherein the sensors may include an inertial sensor, a speed sensor, an acceleration sensor, an engine speed sensor, and a temperature sensor, etc. Through the information acquisition device installed on the vehicle, the vehicle's driving information and environmental information can be acquired in real time, wherein the driving information may include but is not limited to the parameters, speed, acceleration, position, engine speed, torque, and temperature of the vehicle's control system; and the environmental information includes but is not limited to the temperature, humidity, obstacles, and lighting conditions of the vehicle's external environment, etc. It should be noted that the vehicle's driving information and environmental information in this application are illustrative only, and the acquired information can be set based on the actual situation of the vehicle, and this application does not impose any restrictions on this.

[0046] In step 202 , a driving scenario and a driving condition of the vehicle are determined based on relevant information of the vehicle.

[0047] In an exemplary embodiment of the present application, the process of determining the driving scene and driving condition of the vehicle based on the relevant information of the vehicle includes steps 2021 to 2024.

[0048] In step 2021, feature extraction is performed on the driving information to obtain a first feature.

[0049] Exemplarily, data preprocessing is performed on the driving information to remove noise and outliers from the driving information. The preprocessed data is then selected to obtain information related to the driving condition. For example, the selected driving information may include speed, acceleration, and engine speed. Feature extraction is performed on the selected driving information to obtain a first feature. The feature extraction process may include extracting features from the driving information based on a deep learning model, such as a convolutional neural network (CNN) or a recurrent neural network (RNN).

[0050] In step 2022, feature extraction is performed on the environmental information to obtain a second feature.

[0051] For example, the vehicle's environmental information can come from different information acquisition devices, and the environmental information collected by these different information devices can be integrated. For example, radar data collected by a lidar and millimeter-wave radar can be integrated with camera data to obtain more comprehensive environmental information. Feature extraction is performed on this integrated environmental information to obtain a second feature. The method for extracting the second feature is similar to that for extracting the first feature and will not be repeated here.

[0052] In step 2023, the first feature and the second feature are fused to obtain a fused feature.

[0053] In an exemplary embodiment of the present application, after obtaining the first and second features, the first and second features can be aligned temporally and spatially. In other words, the first and second features represent the characteristics of the vehicle at the same time and location. The first and second features are then fused using a feature fusion algorithm to generate a fused feature. Feature fusion algorithms include, but are not limited to, direct concatenation, weighted fusion, and fusion model-based fusion.

[0054] In step 2024 , the fused features are used to determine the driving scene and driving conditions.

[0055] Exemplarily, machine learning or deep learning algorithms are used to process the fused features to obtain the vehicle's driving scenario and driving conditions. Driving conditions can include constant speed driving, accelerating, decelerating, sudden stops, and turning. Driving conditions can include road type, traffic conditions, weather conditions, and the location and dynamics of surrounding obstacles. For example, road types can include highways, urban roads, and rural roads; weather conditions can include rainy, snowy, sunny, and foggy days; and traffic conditions can include congestion and unobstructed conditions. Optionally, the congestion and unobstructed conditions can also include congestion levels and unobstructed levels.

[0056] The technical solution provided by the exemplary embodiment of the present application extracts and fuses features of the vehicle's driving information and environmental information, and uses the fused features to obtain the vehicle's driving scene and driving condition, which can improve the accuracy of the determined driving scene and driving condition, thereby improving the accuracy of subsequent determination of vehicle fault information using relevant content of the driving scene and driving condition.

[0057] In step 203 , a first threshold range corresponding to an actual control parameter of the vehicle is determined using the driving scenario and the driving condition.

[0058] In an exemplary embodiment of the present application, the process of determining the first threshold range corresponding to the actual control parameter of the vehicle by using the driving scenario and the driving condition may include steps 2032 to 2033.

[0059] In step 2031, an initial threshold range corresponding to the actual control parameter of the vehicle is obtained.

[0060] Exemplarily, the actual control parameters of the vehicle may include power control parameters, engine control parameters, and related parameters of various electronic components. For example, a vehicle may be configured with an on-board intelligent power three-in-one control system, which may integrate a battery management system (BMS), a microcontroller unit (MCU), and a power electronic converter (DC-DC Converter). The vehicle may be managed and controlled using the on-board intelligent power three-in-one control system. The on-board intelligent power three-in-one control system controls multiple electronic components, obtains the factory safety standard range corresponding to each electronic component, and determines the factory safety standard range as the initial threshold range corresponding to each electronic component. The initial threshold range corresponding to the electronic component includes, but is not limited to, the input voltage, input voltage, input current, output current of the electrical component, and the temperature of the electronic component.

[0061] In step 2032 , a first adjustment parameter is determined based on the driving scenario, and a second adjustment parameter is determined based on the driving condition.

[0062] For example, based on the parameter adjustment model that has been trained, the parameters corresponding to the driving scenario, the initial threshold range, and the real-time control parameters can be input into the parameter adjustment model. The parameter adjustment model can identify the parameter range with better real-time control parameters under different driving scenarios, compare the better parameter range with the initial threshold range, and determine the first adjustment parameter. For example, the parameter adjustment model can determine the first adjustment parameter corresponding to the multiple electronic devices controlled in the on-board intelligent power three-in-one control system based on the driving scenario. The first adjustment parameter can be an adjustment for at least one of the current or voltage of the electronic device. The process of determining the second adjustment parameter based on the driving condition is similar to the process of determining the first adjustment parameter based on the driving scenario, and will not be elaborated on here. Among them, the first adjustment parameter and the second adjustment parameter can be specific values ​​adjusted for the initial threshold range, or can be adjustment ratios.

[0063] It should be noted that the method of determining the first adjustment parameter and the second adjustment parameter in this application is an exemplary description. The first adjustment parameter and the second adjustment parameter can also be determined by looking up a table or calculating with a formula, and this application does not impose any restrictions on this.

[0064] In step 2033 , the initial threshold range is adjusted using the first adjustment parameter and the second adjustment parameter to obtain a first threshold range.

[0065] In an exemplary embodiment of the present application, after obtaining the first adjustment parameter and the second adjustment parameter, the initial threshold range may be adjusted using a weighted average method or a multiple iteration method to obtain the first threshold range.

[0066] The technical solution provided by the exemplary embodiment of the present application determines the first adjustment parameter and the second adjustment parameter through the driving scene and driving condition of the vehicle, and uses the first adjustment parameter and the second adjustment parameter to adjust the initial threshold range to obtain the first threshold range, so that the first threshold range is more in line with the current driving state of the vehicle, and the determined first threshold range is more reasonable and accurate.

[0067] In step 204 , when the actual control parameter is within the first threshold range, a target control parameter of the vehicle is determined based on the vehicle control model, the driving information, and the environmental information.

[0068] In an exemplary embodiment of the present application, after determining the first threshold range, the actual control parameter can be compared with the first threshold range. If the actual control parameter is within the first threshold range, it can be further detected whether the vehicle has a fault; if the actual control parameter is outside the first threshold range, it can be directly determined that the vehicle has a fault, and the vehicle fault information can be directly determined.

[0069] Taking the case where the actual control parameter is within the first threshold range as an example, the process of determining the target control parameter of the vehicle may include: generating constraints corresponding to the vehicle control model using driving information and environmental information; generating initial control parameters and performance indicators corresponding to the initial control parameters based on the constraints, the vehicle control model, the driving information, and the environmental information; and determining the initial control parameters whose performance indicators are greater than the indicator threshold as the target control parameters of the vehicle.

[0070] Exemplarily, the driving information and environmental information of the current vehicle are used to comprehensively judge the conditions for safe driving of the current vehicle, i.e., the constraints. The constraints may include the safe driving speed of the vehicle, the safe distance between the current vehicle and other vehicles, and the stability of the vehicle. Under the given constraints, the driving information and environmental information of the current vehicle are input into the vehicle control model, and the control parameters of the vehicle are optimized using the vehicle control model to obtain the initial control parameters of the vehicle and the performance indicators corresponding to the initial control parameters. The index threshold corresponding to the performance index is obtained, and the initial control parameter with a performance index greater than the index threshold is determined as the target control parameter of the vehicle, wherein the index threshold can be set based on different electronic devices, and this application does not impose any restrictions on this.

[0071] For example, the vehicle's initial control parameter is the voltage of the electronic components in the onboard intelligent power three-in-one control system, the performance indicator is the score, and the indicator threshold is the score threshold. The vehicle control model can output the initial control voltage of the electronic components under the constraints and the score corresponding to the initial control voltage. The voltage whose initial control voltage score exceeds the score threshold is determined as the target control voltage.

[0072] The technical solution provided by the embodiments of this application uses driving and environmental information to determine the constraints of the vehicle control model, thereby obtaining initial control parameters and performance indicators that better suit the current vehicle driving conditions. The initial control parameters are then further screened using indicator thresholds to obtain optimal target control parameters. The target control parameters are then used to determine more accurate abnormal control information, thereby obtaining more accurate fault information and improving vehicle driving safety.

[0073] In step 205 , abnormal control information of the vehicle is determined using the actual control parameter, the target control parameter, and the second threshold range.

[0074] In an exemplary embodiment of the present application, an abnormality monitoring system may be used to monitor the actual control parameters of the vehicle to determine whether the deviation between the actual control parameters and the target control parameters is within a safe range, thereby determining abnormal control information of the vehicle. The process of determining abnormal control information of the vehicle may include steps 2051 to 2053.

[0075] In step 2051, the actual control parameters are converted to obtain the converted actual control parameters. The conversion process includes at least one of a denoising process and an encryption / decryption process.

[0076] For example, the architecture of the anomaly monitoring system can include three layers: a function implementation layer, a function monitoring layer, and a program flow monitoring layer. After obtaining the actual control parameters of the vehicle, the function implementation layer of the anomaly monitoring system monitors the various functions corresponding to the actual control parameters of the vehicle, obtaining monitoring data corresponding to the actual control parameters.

[0077] For example, the actual control parameters may include charging parameters and AC-DC conversion parameters. The charging parameters and AC-DC conversion parameters correspond to the fast and slow charging functions of the vehicle. By monitoring the charging parameters and AC-DC conversion parameters, monitoring data of the vehicle charging process is obtained; the actual control parameters may also include temperature parameters, voltage parameters, and current parameters, etc. The temperature parameters can characterize the temperature of each electronic component in the vehicle. By monitoring the temperature parameters, temperature monitoring data during the vehicle driving process is obtained; current parameters and voltage parameters can characterize the current flowing through each electronic component in the vehicle or the voltage applied to each electronic component. By monitoring the voltage parameters and current parameters, current monitoring data and voltage monitoring data during the vehicle driving process are obtained.

[0078] De-noising is performed on the monitoring data of the actual control parameters to obtain the de-noised actual control parameters. For example, the electronic circuits in the vehicle may include filters, such as low-pass filters, high-pass filters, and band-pass filters. Spectral analysis is performed on the signals corresponding to the actual control parameters based on the filters to identify and remove noise from the signals corresponding to the actual control parameters. The de-noised actual control parameters are then encrypted to obtain the encrypted actual control parameters. The encryption process may be implemented based on an encryption algorithm, including but not limited to symmetric encryption algorithms, asymmetric encryption algorithms, and hash algorithms.

[0079] In step 2052, the difference between the actual control parameter after conversion and the target control parameter is calculated.

[0080] For example, the functional implementation layer of the abnormality monitoring system can obtain monitoring data on the actual control parameters of the vehicle and send it to the functional monitoring layer in real time. The functional monitoring layer decrypts the monitoring data to obtain the actual control parameters of the vehicle. The actual control parameters of the same electronic device in the vehicle at the same time are compared with the target control parameters to obtain the difference between the actual and target control parameters.

[0081] In step 2053, abnormal control information is determined based on the actual control parameter corresponding to the difference exceeding the second threshold range.

[0082] In an exemplary embodiment of the present application, the difference between the actual control parameter and the target control parameter is compared with a second threshold range. If the difference between the actual control parameter and the target control parameter is within the second threshold range, it indicates that the various functions corresponding to the actual control parameter of the vehicle are functioning normally. If the difference between the actual control parameter and the target control parameter is outside the second threshold range, it indicates that the various functions corresponding to the actual control parameter of the vehicle are functioning abnormally, thereby generating corresponding abnormal control information. It should be noted that the second threshold range can be set based on the actual situation of the vehicle, and this application does not impose any restrictions on this.

[0083] For example, by monitoring charging parameters and AC-DC conversion parameters, it is possible to confirm whether there are any abnormalities in the vehicle charging process; by monitoring temperature parameters, it is possible to prevent damage to electronic components or performance degradation caused by excessive temperature, resulting in high-temperature thermal runaway of the vehicle; by monitoring current parameters and voltage parameters, it is possible to prevent damage to electronic components caused by overcurrent, overvoltage and undervoltage, resulting in loss of control of the vehicle.

[0084] The technical solution provided in the embodiment of the present application performs denoising processing on the actual control parameters based on the abnormal monitoring system, which can reduce the influence of noise interference on the comparison result of the difference between the actual control parameters and the target control parameters and the second threshold range, and can improve the accuracy of determining abnormal control information; when the actual control parameters are carried out between the function implementation layer and the function monitoring layer of the abnormal monitoring system, the actual control parameters are encrypted and decrypted, which can prevent the real-time control parameters from being tampered with or forged, and ensure the data security and integrity of the real-time control parameters during the transmission process, thereby improving the accuracy of determining abnormal control information.

[0085] In step 206 , fault information of the vehicle is determined based on the abnormal control information and parameters of a reference electronic component, where the reference electronic component is a component in the vehicle that is related to the abnormal control information.

[0086] In an exemplary embodiment of the present application, the abnormality monitoring system may further include a fault library, which may include multiple fault information. The fault information may include, but is not limited to, the fault type, the fault cause, the electronic components involved in the fault, and the solution. The functional monitoring layer of the abnormality monitoring system can monitor the real-time control parameters in the functional implementation layer. For example, the engine, transmission system, braking system, and electrical system can be monitored. After receiving the abnormal control information, the abnormal information and the parameters of the electronic components related to the abnormal control information can be compared with the multiple fault information in the fault library to determine the fault information of the current vehicle.

[0087] Exemplarily, after determining the fault information, the vehicle's safety response mechanism can also be triggered based on the fault information. The safety response mechanism includes recording the fault information, generating alarm information, performing fault isolation operations on the faulty hardware, or initiating at least one of a safety parking procedure; when the safety response mechanism instructs to adjust the actual control parameters of the vehicle, a parameter adjustment instruction is generated, and the actual control parameters of the vehicle are adjusted based on the parameter adjustment instruction.

[0088] For example, the process monitoring layer of the anomaly monitoring system can also include a safety response mechanism corresponding to fault information. When fault information is generated, the corresponding safety response mechanism can be triggered. The safety response mechanism may include recording fault information, such as the time, location, type, and scope of the fault; generating an alarm based on the urgency and scope of the fault information; and alerting the driver through indicators on the dashboard, sound prompts, or displaying an alarm message on the vehicle's display screen.

[0089] If the safety response mechanism indicates that vehicle control parameters need to be adjusted, a corresponding parameter adjustment instruction can be generated. The parameter adjustment instruction may include, but is not limited to, shutting off power to electronic components, adjusting engine power, and controlling vehicle braking. The actual vehicle control parameters are then adjusted based on the parameter adjustment instruction.

[0090] For example, if the fault information indicates a hardware fault, the process monitoring layer can generate a parameter adjustment instruction to cut off the power supply to the faulty hardware, isolate the faulty hardware, prevent the fault from spreading, and avoid further impact on other hardware or software; if the fault information is more serious and may affect the safe driving of the vehicle, the process monitoring layer can also generate a parameter adjustment instruction to start the safe parking procedure and control the vehicle braking based on the parameter adjustment instruction.

[0091] The technical solution provided in the embodiment of the present application triggers the vehicle's safety response mechanism through fault information, and uses the parameter adjustment instructions corresponding to the safety response mechanism to adjust the vehicle's actual control parameters, thereby controlling the vehicle, reducing the impact of the fault on vehicle safety, and improving the safety of the vehicle during driving.

[0092] In an exemplary embodiment of the present application, while the vehicle is in motion, the program flow monitoring layer of the abnormality monitoring system can also perform program flow checking operations, memory partition management operations, and chip selection operations. For example, the program flow monitoring layer monitors the real-time control parameters in programs related to vehicle safety to ensure that the real-time control parameters are correctly executed in each program flow; the program flow monitoring layer can also partition the memory resources that store vehicle information to ensure that there are sufficient memory resources for the vehicle's relevant information, real-time control parameters, and the process of determining fault information; the program flow monitoring layer can also select chips with corresponding security requirements based on the vehicle's real-time control information to ensure that the chip's data processing performance can meet the needs of vehicle control.

[0093] The technical solution provided by the exemplary embodiment of the present application determines the vehicle's driving scenario and driving conditions through the vehicle's driving information and environmental information, and uses the driving scenario and driving conditions to determine a first threshold range corresponding to the vehicle's actual control parameters, so that the first threshold range is more consistent with the current vehicle's driving state, and the determined first threshold range is more reasonable and accurate, so that the vehicle's safety state can be accurately determined through the first threshold range. When the vehicle's real-time control parameters are within the first threshold range, the vehicle's real-time control parameters, target control parameters, and second threshold range are used to further determine the vehicle's abnormal control information, and the abnormal control information is used to determine the vehicle's fault information, effectively avoiding misjudgment or omission of the vehicle's fault information, improving the accuracy of the vehicle's fault information, and ensuring the vehicle's driving safety.

[0094] The present application also provides a device for determining vehicle fault information. Figure 3 is a schematic diagram of a vehicle fault information determination device provided by an embodiment of the present application, such as Figure 3 As shown, the device includes:

[0095] An acquisition module 301 is configured to acquire vehicle-related information, including driving information and environmental information. The driving information is used to represent the driving state of the vehicle, and the environmental information is used to represent the external environment in which the vehicle is located.

[0096] A determination module 302 is configured to determine a driving scenario and a driving condition of the vehicle based on relevant information of the vehicle;

[0097] The determination module 302 is further configured to determine a first threshold range corresponding to an actual control parameter of the vehicle using the driving scenario and the driving condition;

[0098] The determination module 302 is further configured to determine a target control parameter of the vehicle based on the vehicle control model, the driving information, and the environmental information when the actual control parameter is within the first threshold range;

[0099] The determination module 302 is further configured to determine abnormal control information of the vehicle using the actual control parameter, the target control parameter, and the second threshold range;

[0100] The determination module 302 is further configured to determine fault information of the vehicle based on the abnormal control information and parameters of a reference electronic component, where the reference electronic component is a component in the vehicle that is related to the abnormal control information.

[0101] In one possible implementation, the device also includes a control module (not shown in the figure), which is used to trigger the vehicle's safety response mechanism when the fault information indicates that the fault type is a hardware fault. The safety response mechanism includes recording fault information, generating alarm information, performing fault isolation operations on the faulty hardware, or starting a safe parking procedure. When the safety response mechanism indicates to adjust the actual control parameters of the vehicle, a parameter adjustment instruction is generated, and the actual control parameters of the vehicle are adjusted based on the parameter adjustment instruction.

[0102] In one possible implementation, a determination module 302 is configured to obtain an initial threshold range corresponding to an actual control parameter of the vehicle; determine a first adjustment parameter based on a driving scenario, and determine a second adjustment parameter based on a driving condition; and adjust the initial threshold range using the first adjustment parameter and the second adjustment parameter to obtain a first threshold range.

[0103] In one possible implementation, the determination module 302 is used to convert the actual control parameters to obtain the actual control parameters after conversion, where the conversion processing includes at least one of denoising processing or encryption and decryption processing; calculate the difference between the actual control parameters after conversion and the target control parameters; and determine abnormal control information based on the actual control parameters corresponding to the difference exceeding the second threshold range.

[0104] In one possible implementation, the determination module 302 is used to generate constraints corresponding to the vehicle control model using driving information and environmental information; generate initial control parameters and performance indicators corresponding to the initial control parameters based on the constraints, the vehicle control model, driving information and environmental information; and determine the initial control parameters whose performance indicators are greater than the indicator threshold as the target control parameters of the vehicle.

[0105] In one possible implementation, the determination module 302 is configured to perform feature extraction on driving information to obtain a first feature; perform feature extraction on environmental information to obtain a second feature; fuse the first feature and the second feature to obtain a fused feature; and use the fused feature to determine the driving scene and driving condition.

[0106] The technical solution provided by the exemplary embodiment of the present application obtains the vehicle's driving information and environmental information through an acquisition module, determines the vehicle's driving scenario and driving conditions based on the vehicle's driving information and environmental information using a determination module, and uses the driving scenario and driving conditions to determine a first threshold range corresponding to the vehicle's actual control parameters, so that the first threshold range is more consistent with the current vehicle's driving state, and the determined first threshold range is more reasonable and accurate, so that the vehicle's safety state can be accurately determined through the first threshold range. When the vehicle's real-time control parameters are within the first threshold range, the vehicle's real-time control parameters, target control parameters, and second threshold range are used to further determine the vehicle's abnormal control information, and the abnormal control information is used to determine the vehicle's fault information, effectively avoiding misjudgment or omission of the vehicle's fault information, improving the accuracy of the vehicle's fault information, and ensuring the vehicle's driving safety.

[0107] Figure 4 is a schematic diagram of a vehicle fault information determination device based on a vehicle-mounted intelligent power three-in-one control system provided by an embodiment of the present application, such as Figure 4As shown, the device includes: an acquisition module, a determination module, a control module, and a power module. The acquisition module may include an information acquisition device, including but not limited to a camera, a millimeter-wave radar, a lidar, and an inertial sensor. The acquisition module collects data about the vehicle itself and the environment in which the vehicle is located, and sends the collected data to the image processing unit, point cloud processing unit, and motion state processing unit of the determination module. The image processing unit and point cloud processing unit process the information collected by the camera, millimeter-wave radar, and lidar to obtain the vehicle's environmental information; the motion state processing unit processes the information collected by the inertial sensor to obtain the vehicle's driving information. The motion processing unit can also obtain the actual power control parameters of the power module. The power module may include an on-board intelligent power three-in-one control system. The on-board intelligent power three-in-one control system may include a power control center. The power control center is connected to the motor controller (Integrated Power Unit, IPU), the motor, and the power battery. The power control center can control the IPU, the motor, and the power battery based on the actual power control parameters. The motion state processing unit sends the driving information and actual power supply control parameters to the motion state planning unit. The motion state planning unit can combine the environmental information, driving information, and actual power supply control parameters from the data fusion unit to determine the safe driving state of the vehicle. After the motion state planning unit determines that the vehicle is in a safe driving state, it can send the relevant data to the fault information determination unit. The fault information determination unit combines the data from the data fusion unit and the data from the motion state planning unit to further determine the safe driving state of the vehicle and obtain the vehicle fault information. The determination module sends the vehicle fault information to the control module. The control center of the control module can trigger a safety response mechanism based on the vehicle fault information and use the parameter adjustment instructions corresponding to the safety response mechanism to control the alarm unit to issue a fault information alarm, store the fault information in the cloud, and perform lateral control or longitudinal control of the vehicle.

[0108] It should be noted that Figure 4 The relevant contents have been described in detail in steps 201 to 206. Please refer to the relevant descriptions of steps 201 to 206 and will not be repeated here.

[0109] It should be understood that the above-mentioned device is merely an example of the division of the above-mentioned functional modules when implementing its functions. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0110] Figure 5 The terminal device 1500 may be any electronic device capable of human-computer interaction with a user through one or more methods, such as a keyboard, touchpad, remote control, voice interaction, or handwriting device. Examples include a PC (Personal Computer), a mobile phone, a smartphone, a PDA (Personal Digital Assistant), a wearable device, a Pocket PC (PPC), a tablet computer, and a smart car computer.

[0111] Typically, the terminal device 1500 includes a processor 1501 and a memory 1502 .

[0112] The processor 1501 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 1501 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). The processor 1501 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 1501 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 1501 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0113] Memory 1502 may include one or more computer-readable storage media, which may be non-transitory. Memory 1502 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in memory 1502 is used to store at least one instruction, which is executed by processor 1501 to implement the vehicle fault information determination method provided in the method embodiment of the present application.

[0114] In some embodiments, terminal device 1500 may optionally include a peripheral device interface 1503 and at least one peripheral device. The processor 1501, memory 1502, and peripheral device interface 1503 may be connected via a bus or signal lines. Each peripheral device may be connected to peripheral device interface 1503 via a bus, signal lines, or circuit boards. Specifically, the peripheral device may include at least one of a radio frequency circuit 1504, a display screen 1505, a camera assembly 1506, an audio circuit 1507, and a power supply 1508.

[0115] The peripheral device interface 1503 can be used to connect at least one I / O (Input / Output)-related peripheral device to the processor 1501 and the memory 1502. In some embodiments, the processor 1501, the memory 1502, and the peripheral device interface 1503 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 1501, the memory 1502, and the peripheral device interface 1503 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0116] RF circuit 1504 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. RF circuit 1504 communicates with communication networks and other communication devices via electromagnetic signals. RF circuit 1504 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. RF circuit 1504 may optionally include an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, and the like. RF circuit 1504 may communicate with other terminal devices via at least one wireless communication protocol. Such wireless communication protocols include, but are not limited to, the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, RF circuit 1504 may also include circuitry related to Near Field Communication (NFC), although this application does not limit this.

[0117] The display screen 1505 is used to display a UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 1105 is a touch screen display, the display screen 1505 also has the ability to collect touch signals on the surface or above the surface of the display screen 1505. The touch signal can be input as a control signal to the processor 1501 for processing. In this case, the display screen 1505 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, there can be one display screen 1505, which is set on the front panel of the terminal device 1500; in other embodiments, there can be at least two display screens 1505, which are respectively set on different surfaces of the terminal device 1500 or in a folding design; in other embodiments, the display screen 1505 can be a flexible display screen, which is set on the curved surface or folding surface of the terminal device 1500. In fact, the display screen 1505 can also be set as a non-rectangular irregular shape, that is, a special-shaped screen. The display screen 1505 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0118] The camera assembly 1506 is used to capture images or videos. Optionally, the camera assembly 1506 includes a front camera and a rear camera. Typically, the front camera is arranged on the front panel of the terminal device 1500, and the rear camera is arranged on the back of the terminal device 1500. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, a wide-angle camera, and a telephoto camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, the fusion of the main camera and the wide-angle camera to realize panoramic shooting and VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 1506 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0119] The audio circuit 1507 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals that are input into the processor 1501 for processing, or input into the RF circuit 1504 to achieve voice communication. For the purpose of stereo sound collection or noise reduction, there may be multiple microphones, each located in different parts of the terminal device 1500. The microphone may also be an array microphone or an omnidirectional collection microphone. The speaker is used to convert electrical signals from the processor 1501 or the RF circuit 1504 into sound waves. The speaker may be a traditional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert electrical signals into sound waves audible to humans, but also convert electrical signals into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 1507 may also include a headphone jack.

[0120] Power supply 1508 is used to power various components in terminal device 1500. Power supply 1508 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 1508 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, while a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0121] In some embodiments, the terminal device 1500 further includes one or more sensors 1510 , including but not limited to: an acceleration sensor 1511 , a gyroscope sensor 1512 , a pressure sensor 1513 , an optical sensor 1514 , and a proximity sensor 1515 .

[0122] The accelerometer 1511 can detect the magnitude of acceleration along the three coordinate axes of the coordinate system established by the terminal device 1500. For example, the accelerometer 1511 can be used to detect the components of gravity acceleration along the three coordinate axes. The processor 1501 can control the display screen 1505 to display the user interface in a landscape or portrait view based on the gravity acceleration signal collected by the accelerometer 1511. The accelerometer 1511 can also be used to collect game or user motion data.

[0123] The gyroscope sensor 1512 can detect the body orientation and rotation angle of the terminal device 1500. The gyroscope sensor 1512 can work with the acceleration sensor 1511 to collect the user's 3D movements of the terminal device 1500. Based on the data collected by the gyroscope sensor 1512, the processor 1501 can implement the following functions: motion sensing (such as changing the UI based on the user's tilt operation), image stabilization during shooting, game control, and inertial navigation.

[0124] The pressure sensor 1513 can be set on the side frame of the terminal device 1500 and / or the lower layer of the display screen 1505. When the pressure sensor 1513 is set on the side frame of the terminal device 1500, it can detect the user's grip signal of the terminal device 1500, and the processor 1501 performs left and right hand recognition or shortcut operations based on the grip signal collected by the pressure sensor 1513. When the pressure sensor 1513 is set on the lower layer of the display screen 1505, the processor 1501 controls the operable controls on the UI interface based on the user's pressure operation on the display screen 1505. The operable controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

[0125] Optical sensor 1514 is used to detect ambient light intensity. In one embodiment, processor 1501 can control the display brightness of display screen 1505 based on the ambient light intensity detected by optical sensor 1514. Specifically, when the ambient light intensity is high, the display brightness of display screen 1505 is increased; when the ambient light intensity is low, the display brightness of display screen 1505 is decreased. In another embodiment, processor 1501 can also dynamically adjust the shooting parameters of camera assembly 1506 based on the ambient light intensity detected by optical sensor 1514.

[0126] Proximity sensor 1515, also known as a distance sensor, is typically located on the front panel of terminal device 1500. Proximity sensor 1515 is used to detect the distance between the user and the front of terminal device 1500. In one embodiment, when proximity sensor 1515 detects that the distance between the user and the front of terminal device 1500 is gradually decreasing, processor 1501 controls display screen 1505 to switch from the screen-on state to the screen-off state. When proximity sensor 1515 detects that the distance between the user and the front of terminal device 1500 is gradually increasing, processor 1501 controls display screen 1505 to switch from the screen-off state to the screen-on state.

[0127] Those skilled in the art will understand that Figure 5 The structure shown in the figure does not constitute a limitation on the terminal device 1500, and the terminal device 1500 may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0128] Figure 616 is a schematic diagram of the structure of the server provided in an embodiment of the present application. The server 1600 may vary significantly due to different configurations or performance, and may include one or more processors 1601 and one or more memories 1602. The one or more memories 1602 store at least one program code, which is loaded and executed by the one or more processors 1601 to implement the vehicle fault information determination method provided in each of the above-mentioned method embodiments. Of course, the server 1600 may also have components such as a wired or wireless network interface, a keyboard, and an input / output interface for input and output. The server 1600 may also include other components for implementing device functions, which will not be described in detail here.

[0129] In an exemplary embodiment, a computer-readable storage medium is further provided, in which at least one program code is stored. The at least one program code is loaded and executed by a processor to enable a computer to implement any of the above-mentioned methods for determining vehicle fault information.

[0130] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, or the like.

[0131] In an exemplary embodiment, a computer program or computer program product is also provided, in which at least one computer instruction is stored. The at least one computer instruction is loaded and executed by a processor to enable the computer to implement any of the above-mentioned methods for determining vehicle fault information.

[0132] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the driving information, environmental information, actual control parameters, and fault information involved in this application are all obtained with full authorization.

[0133] It should be understood that the term "plurality" used herein refers to two or more. "And / or" describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone. The character " / " generally indicates an "or" relationship between the associated objects.

[0134] The above description is merely an exemplary embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for determining vehicle fault information, characterized in that: The method comprises: Acquire relevant information of the vehicle, the relevant information of the vehicle including driving information and environmental information, the driving information is used to characterize the driving state of the vehicle, and the environmental information is used to characterize the external environment where the vehicle is located; Determining a driving scenario and a driving condition of the vehicle based on the relevant information of the vehicle; Determining a first threshold range corresponding to an actual control parameter of the vehicle by using the driving scenario and the driving condition; When the actual control parameter is within the first threshold range, determining a target control parameter of the vehicle based on a vehicle control model, the driving information, and the environmental information; Determining abnormal control information of the vehicle using the actual control parameter, the target control parameter and a second threshold range; Fault information of the vehicle is determined based on the abnormal control information and parameters of a reference electronic device, where the reference electronic device is a device in the vehicle that is related to the abnormal control information.

2. The method according to claim 1, characterized in that After determining the fault information of the vehicle based on the abnormal control information and the parameters of the reference electronic device, the method further includes: triggering a safety response mechanism of the vehicle based on the fault information, the safety response mechanism comprising at least one of recording the fault information, generating alarm information, performing a fault isolation operation on the faulty hardware, or initiating a safe parking procedure; In the case where the safety response mechanism indicates to adjust the actual control parameter of the vehicle, a parameter adjustment instruction is generated, and the actual control parameter of the vehicle is adjusted based on the parameter adjustment instruction.

3. The method according to claim 1, characterized in that The determining a first threshold range corresponding to an actual control parameter of the vehicle by using the driving scenario and the driving condition includes: Obtaining an initial threshold range corresponding to an actual control parameter of the vehicle; Determine a first adjustment parameter based on the driving scenario, and determine a second adjustment parameter based on the driving condition; The initial threshold range is adjusted using the first adjustment parameter and the second adjustment parameter to obtain the first threshold range.

4. The method according to claim 1, characterized in that: The determining the abnormal control information of the vehicle by using the actual control parameter, the target control parameter and a second threshold range includes: Performing conversion processing on the actual control parameter to obtain the converted actual control parameter, wherein the conversion processing includes at least one of denoising processing or encryption and decryption processing; Calculating the difference between the actual control parameter after the conversion process and the target control parameter; The abnormal control information is determined based on the actual control parameter corresponding to the difference exceeding the second threshold range.

5. The method according to any one of claims 1 to 4, characterized in that: The determining the target control parameter of the vehicle based on the vehicle control model, the driving information and the environmental information includes: Generating constraint conditions corresponding to the vehicle control model using the driving information and the environmental information; Generate initial control parameters and performance indicators corresponding to the initial control parameters based on the constraint conditions, the vehicle control model, the driving information, and the environmental information; An initial control parameter whose performance index is greater than an index threshold is determined as a target control parameter of the vehicle.

6. The method according to any one of claims 1 to 4, characterized in that: The determining the driving scene and driving condition of the vehicle based on the relevant information of the vehicle includes: Extracting features from the driving information to obtain a first feature; Extracting features from the environmental information to obtain a second feature; fusing the first feature and the second feature to obtain a fused feature; The driving scene and the driving condition are determined using the fusion features.

7. A device for determining vehicle fault information, characterized in that: The device comprises: An acquisition module, used to acquire relevant information of a vehicle, wherein the relevant information of the vehicle includes driving information and environmental information, wherein the driving information is used to characterize the driving state of the vehicle, and the environmental information is used to characterize the external environment in which the vehicle is located; A determination module, configured to determine a driving scenario and a driving condition of the vehicle based on relevant information of the vehicle; The determination module is further configured to determine a first threshold range corresponding to an actual control parameter of the vehicle by using the driving scenario and the driving condition; The determination module is further configured to determine, when the actual control parameter is within the first threshold range, a target control parameter of the vehicle based on a vehicle control model, the driving information, and the environmental information; The determination module is further used to determine abnormal control information of the vehicle using the actual control parameter, the target control parameter and a second threshold range; The determination module is further used to determine the fault information of the vehicle based on the abnormal control information and parameters of a reference electronic device, wherein the reference electronic device is a device in the vehicle that is related to the abnormal control information.

8. A computer device, characterized in that: The computer device includes a processor and a memory, wherein the memory stores at least one program code, and the at least one program code is loaded and executed by the processor so that the computer device implements the method for determining vehicle fault information as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: At least one program code is stored in the computer-readable storage medium, and the at least one program code is loaded and executed by the processor so that the computer implements the method for determining vehicle fault information as described in any one of claims 1 to 6.

10. A computer program product, characterized in that The computer program product stores at least one computer instruction, and the at least one computer instruction is loaded and executed by a processor so that a computer implements a method for determining vehicle fault information according to any one of claims 1 to 6.

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