Navigation positioning abnormity detection method, apparatus and device, and medium

Abstract

The invention relates to the field of vehicle navigation anomaly detection, in particular to a navigation positioning anomaly detection method, device and equipment and a medium. According to the method provided by the embodiment of the invention, whether the navigation positioning abnormity exists in the vehicle or not can be found in time by analyzing the change conditions of the fusion signal and the state signal, and the problem that the navigation positioning abnormity cannot be recognized in time in the current scheme is solved. And secondly, after the navigation positioning abnormity of the vehicle is determined, the positioning abnormity condition is sent to the cloud, and key information is provided for abnormity analysis. And then the cloud end can perform further analysis and processing according to the received abnormal positioning condition, so as to timely discover and solve the abnormal navigation positioning condition, and meanwhile, the reliability and the accuracy of the navigation system can be improved, and a better navigation service is provided for a user.

Description

Technical Field

[0001] The present invention relates to the field of vehicle navigation anomaly detection, and in particular to a navigation positioning anomaly detection method, device, equipment and medium. Background Art

[0002] During the current vehicle driving process, when the vehicle uses its own map on the vehicle computer for navigation, there is a very low probability situation. That is, during navigation, the vehicle position on the map may remain unchanged, or the vehicle position may experience large jumps or drifts. However, the current solution cannot timely identify navigation positioning anomalies and output abnormal key information to assist in abnormal analysis. This situation may cause trouble to the driver, affect the accuracy and reliability of navigation, and is not conducive to timely discovery and resolution of potential system problems. Summary of the invention

[0003] In view of this, an embodiment of the present invention provides a method, device, equipment and medium for detecting navigation positioning anomalies to solve the problem that the current solution cannot timely identify navigation positioning anomalies and output key anomaly information to assist in anomaly analysis.

[0004] In a first aspect, an embodiment of the present invention provides a method for detecting navigation positioning anomalies, the method comprising:

[0005] Acquire a fusion signal currently output by a map engine of the vehicle, wherein the fusion signal is obtained by fusing signals provided by multiple data sources by the map engine;

[0006] Acquire current status signals of the vehicle in different dimensions;

[0007] Analyze the changes of the fusion signal and each of the status signals, and determine whether the changes hit the positioning abnormality condition within a preset time period;

[0008] If the change condition hits the positioning abnormality condition, it is determined that the vehicle currently has a navigation positioning abnormality, and the current positioning abnormality of the vehicle is sent to the cloud.

[0009] Further, the analyzing the changes of the fusion signal and each of the state signals includes any one or more of the following:

[0010] Extracting a multi-source vehicle speed signal from the state signal, and extracting a fused vehicle speed signal from the fused signal, and analyzing whether the multi-source vehicle speed signal and the fused vehicle speed signal are both 0 within the preset time period;

[0011] Obtaining an average output frequency of the fusion signal within the preset time period, and analyzing whether the average output frequency is less than a preset frequency;

[0012] Extracting a navigation vehicle speed signal from the state signal, and extracting a fused vehicle speed signal from the fused signal, and analyzing whether a vehicle speed difference between the fused vehicle speed signal and the navigation vehicle speed signal is greater than a preset vehicle speed within the preset time period;

[0013] The number of repeated frames of the motion signal of the vehicle is extracted from the state signal, and it is analyzed whether the number of repeated frames of the motion signal is greater than a preset number of frames.

[0014] Further, the determining whether the change condition hits the location abnormality condition within a preset time period includes:

[0015] If the multi-source vehicle speed signal and the fused vehicle speed signal are not simultaneously 0 within the preset time period, and / or the average output frequency is less than the preset frequency, and / or the vehicle speed difference is greater than the preset vehicle speed within the preset time period, and / or the number of repeated frames of the motion signal is greater than the preset number of frames, it is determined that the abnormal positioning condition is hit;

[0016] If the multi-source vehicle speed signal and the fused vehicle speed signal are both 0 within the preset time period, the average output frequency is greater than or equal to the preset frequency, the vehicle speed difference is less than or equal to the preset vehicle speed within the preset time period, and the number of repeated frames of the motion signal is less than or equal to the preset number of frames, then a missed positioning abnormal condition is determined.

[0017] Furthermore, if the change condition hits the abnormal positioning condition, the method further includes:

[0018] Update the weight parameters of the fusion signal according to the weight adjustment strategy;

[0019] The updated weight parameters are sent to the functional modules related to navigation and positioning in the vehicle.

[0020] Furthermore, the method further comprises:

[0021] Obtaining update information from the cloud based on feedback from the abnormal positioning situation;

[0022] Parsing the update information to determine an update object and update parameters of the update object;

[0023] If the update object is the abnormal positioning condition, the update parameters are used to update the condition content corresponding to the abnormal positioning condition; or, if the update object is the signal fusion algorithm of the map engine, the update parameters are used to update the algorithm parameters of the signal fusion algorithm; or, if the update object is a hardware device related to navigation and positioning, the update parameters are used to update the working parameters of the hardware device.

[0024] Furthermore, the method further comprises:

[0025] Analyze the positioning abnormality according to a preset analysis strategy to obtain an update object that needs to be updated in the vehicle and an update parameter corresponding to the update object;

[0026] Generate update information based on the update object and the update parameter;

[0027] Sending the update information to a preset terminal, wherein the preset terminal is used to verify the update parameters;

[0028] receiving an execution instruction fed back by the preset terminal based on the update information, wherein the execution instruction is sent by the preset terminal after verifying the update parameters;

[0029] In response to the execution instruction, the update object is updated using the update parameter.

[0030] Furthermore, the method further comprises:

[0031] If no execution instruction fed back by the preset terminal is received within the preset waiting time, query whether there is a candidate object corresponding to the update object;

[0032] If there is a candidate object, obtain the configuration parameters of the candidate object;

[0033] The candidate objects are configured using the configuration parameters, and corresponding navigation operations are performed based on the configured candidate objects.

[0034] In a second aspect, an embodiment of the present invention provides a device for detecting navigation positioning anomalies, the device comprising:

[0035] A first acquisition module is used to acquire a fusion signal currently output by a map engine of the vehicle, wherein the fusion signal is obtained by fusing signals provided by multiple data sources by the map engine;

[0036] A second acquisition module is used to acquire current status signals of the vehicle in different dimensions;

[0037] A signal analysis module, used to analyze the changes of the fusion signal and each of the state signals, and determine whether the changes hit the positioning abnormality condition within a preset time period;

[0038] The sending module is used to determine that the vehicle currently has a navigation positioning anomaly if the change situation hits the positioning anomaly condition, and send the vehicle's current positioning anomaly situation to the cloud.

[0039] In a third aspect, an embodiment of the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0040] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method of the first aspect or any corresponding embodiment thereof.

[0041] The method provided in the embodiment of the present application can promptly detect whether there is an abnormality in the vehicle positioning by analyzing the changes in the fusion signal and each state signal within a preset time period and comparing it with the positioning abnormality conditions. The real-time monitoring and judgment mechanism can identify the abnormality in the early stage of occurrence, avoiding the problem of abnormal conditions persisting without being detected. Once it is determined that the vehicle has a navigation positioning abnormality, the abnormality is sent to the cloud. The cloud can summarize and analyze the abnormal conditions of a large number of vehicles, so as to have a more comprehensive understanding of the distribution, trends and potential causes of the abnormalities. It solves the problem that the current solution cannot promptly identify navigation positioning anomalies and output abnormal key information to assist in abnormal analysis.

[0042] The method provided in the embodiment of the present application can promptly detect whether the vehicle has navigation positioning anomalies by analyzing the changes in the fusion signal and the status signal, thereby solving the problem that the current solution cannot promptly identify navigation positioning anomalies. Secondly, after determining that the vehicle has navigation positioning anomalies, the positioning anomaly is sent to the cloud, providing key information for anomaly analysis. The cloud can then perform further analysis and processing based on the received positioning anomalies, promptly detect and resolve navigation positioning anomalies, and at the same time improve the reliability and accuracy of the navigation system, providing users with better navigation services. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 is a flowchart of a method for detecting navigation positioning anomalies according to some embodiments of the present invention;

[0045] Figure 2 is a flowchart of a method for detecting navigation positioning anomalies according to some embodiments of the present invention;

[0046] Figure 3 is a structural block diagram of a method and device for detecting navigation positioning anomalies according to some embodiments of the present invention;

[0047] Figure 4 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0049] According to an embodiment of the present invention, a method, apparatus, device and medium for detecting navigation positioning anomalies are provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0050] In this embodiment, a method for detecting abnormal navigation positioning is provided. Figure 1 is a flow chart of a method for detecting navigation positioning anomalies according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0051] Step S101, obtaining a fusion signal currently output by a map engine of the vehicle, wherein the fusion signal is obtained by fusing signals provided by multiple data sources by the map engine.

[0052] In an embodiment of the present application, first, multiple data sources related to the map engine are determined. Multiple data sources include global positioning system (GPS), inertial measurement unit (IMU, including accelerometer and gyroscope, etc.), vehicle-mounted sensors (such as wheel speed sensor, etc.), etc. Find the interface provided by the vehicle map engine to obtain the fusion signal, and then establish a connection with the map engine. Send a request to the map engine through the interface to obtain the currently output fusion signal. The map engine responds to the request and outputs the fusion signal.

[0053] In addition, in order to obtain the fusion signal in real time, a timer can be set to regularly request the fusion signal from the map engine. The request time interval is determined according to actual needs to ensure that the latest fusion signal data can be obtained in time.

[0054] Step S102, obtaining current status signals of the vehicle in different dimensions.

[0055] In the embodiment of the present application, the data acquisition device providing different status signals on the vehicle is identified. For example, the pulse vehicle speed is determined to come from the wheel sensor and the related electronic control unit (ECU); the GPS vehicle speed comes from the vehicle GPS receiver; the instrument vehicle speed comes from the display system of the vehicle dashboard; the gyroscope data comes from the vehicle's inertial measurement unit (IMU), etc. The status signals of different dimensions include: pulse vehicle speed signal, GPS vehicle speed signal, instrument vehicle speed signal, gyroscope data signal, etc.

[0056] Among them, the pulse speed signal is usually generated by the wheel speed sensor on the vehicle. The wheel speed sensor generates a fixed number of pulses per rotation by detecting the rotation of the wheel. By calculating the number of pulses per unit time, the rotation speed of the wheel can be determined. Combined with parameters such as the diameter of the wheel, the vehicle's driving speed can be converted. This speed signal is called a pulse speed signal. The GPS speed signal is obtained by a global positioning system (GPS) receiver. GPS can determine the position of the vehicle on the earth by receiving signals from satellites. By continuously measuring the position of the vehicle at different times and calculating the rate of change of the position, the vehicle's driving speed can be obtained. The GPS speed signal reflects the moving speed of the vehicle in the global positioning system coordinate system. The instrument speed signal is the speed information displayed on the vehicle's dashboard. It is calculated and processed by the vehicle's electronic control unit (ECU) based on the data of various sensors (including wheel speed sensors, transmission output shaft speed sensors, etc.), and then sent to the dashboard for display. The gyroscope data signal reflects the rotational motion state of the vehicle in space. A gyroscope is a sensor that measures the rotational motion of an object. In a vehicle, a gyroscope can measure information such as the vehicle's roll, pitch and yaw angular velocity.

[0057] Step S103: Analyze the changes of the fusion signal and each state signal, and determine whether the changes hit the positioning abnormality condition within a preset time period.

[0058] In the embodiment of the present application, analyzing the changes of the fusion signal and each state signal includes any one or more of the following:

[0059] ① Extract the multi-source vehicle speed signal from the state signal, and extract the fused vehicle speed signal from the fused signal, and analyze whether the multi-source vehicle speed signal and the fused vehicle speed signal are both 0 within a preset time period.

[0060] It should be noted that speed-related signals are selected from various status signals, such as pulse speed signals, GPS speed signals, instrument speed signals, and other status signals to form a multi-source speed signal set. This means that the speed information obtained from multiple channels is comprehensively considered for a more comprehensive analysis. The fused speed signal is further extracted from the fused signal transmitted by the map engine. This fused signal is obtained by the map engine fusing the signals provided by multiple data sources.

[0061] Determine a specific time period, which can be set according to actual needs, such as a few seconds, a few minutes, etc. Analyze the vehicle speed signal within this time period to check whether the multi-source vehicle speed signal and the fused vehicle speed signal are simultaneously 0 within the preset time period. If these vehicle speed signals are simultaneously 0, it means that the vehicle has an abnormality during driving.

[0062] ② Obtain the average output frequency of the fusion signal within a preset time period, and analyze whether the average output frequency is less than the preset frequency.

[0063] It should be noted that the output of the fusion signal is monitored and recorded within a preset time period. By counting the number of times the fusion signal is output within this period and dividing it by the length of the preset time period, the average output frequency of the fusion signal within this period can be obtained. For example, if the fusion signal is output 50 times within 10 seconds, the average output frequency is 5 Hz.

[0064] According to the performance requirements and normal operation standards of the vehicle system, a preset frequency value is determined. This preset frequency can be set based on experience, test data or design specifications, and represents the minimum output frequency that the fusion signal should reach under normal circumstances. Compare the average output frequency of the acquired fusion signal within the preset time period with the preset frequency. If the average output frequency is less than the preset frequency, it means that the output of the fusion signal is not frequent enough and there is a problem. For example, it means that the data source of the fusion signal is faulty, the fusion algorithm is abnormal, or the vehicle system is in some abnormal state.

[0065] ③ Extracting the navigation vehicle speed signal from the state signal and extracting the fusion vehicle speed signal from the fusion signal, and analyzing whether the vehicle speed difference between the fusion vehicle speed signal and the navigation vehicle speed signal is greater than the preset vehicle speed within a preset time period.

[0066] It should be noted that the status signal contains a variety of information related to vehicle operation, among which the navigation speed signal comes from the vehicle's navigation system. This specific navigation speed signal is extracted from the status signal for comparison and analysis with other speed signals. The fused signal is a comprehensive signal obtained by the map engine by fusing the signals provided by multiple data sources.

[0067] Subtract the fusion speed signal from the navigation speed signal to obtain the speed difference between the two. This difference reflects the degree of difference between the fusion speed signal and the navigation speed signal. Observe and analyze the speed difference within a preset time period to determine whether it is stable or whether there are abnormal changes. If the speed difference is greater than the preset speed within the preset time period, it means that there is a large difference between the fusion speed signal and the navigation speed signal, indicating that there is a problem with the vehicle's positioning or speed measurement system. For example, there may be an error in the fusion algorithm, interference with the navigation system, or a sensor failure.

[0068] ④ Extract the number of repeated frames of the vehicle's motion signal from the state signal, and analyze whether the number of repeated frames of the motion signal is greater than the preset number of frames.

[0069] It should be noted that the motion signal is a specific signal set that reflects the motion state of the vehicle, including gyroscope data, accelerometer data and other signals related to vehicle motion. In the motion signal, the number of repeated frames refers to the number of times the motion signal is repeated within a specific time period. For example, the number of times the gyroscope outputs the same data point within a period of time, or the number of times the accelerometer records the same value within a certain period of time can be regarded as the number of repeated frames. The number of repeated frames of the extracted motion signal is compared with the preset number of frames. The preset number of frames can be set based on empirical data, test results or design specifications, and represents the maximum acceptable number of repeated frames of the motion signal under normal circumstances. If the number of repeated frames of the motion signal is greater than the preset number of frames, it means that the motion signal of the vehicle is abnormally repeated or unstable. It may be caused by sensor failure, signal interference, data processing errors, etc.

[0070] In the embodiment of the present application, determining whether the change situation hits the location abnormality condition within a preset time period includes:

[0071] If the multi-source vehicle speed signals and the fused vehicle speed signal are not 0 at the same time within the preset time period, and / or the average output frequency is less than the preset frequency, and / or the vehicle speed difference is greater than the preset vehicle speed within the preset time period, and / or the number of repeated frames of the motion signal is greater than the preset number of frames, then it is determined that the abnormal positioning condition has been hit.

[0072] If the multi-source vehicle speed signal and the fused vehicle speed signal are both 0 within the preset time period, the average output frequency is greater than or equal to the preset frequency, the vehicle speed difference is less than or equal to the preset vehicle speed within the preset time period, and the number of repeated frames of the motion signal is less than or equal to the preset number of frames, then a missed positioning abnormality condition is determined.

[0073] It should be noted that the positioning abnormality condition comprehensively considers multiple aspects such as multi-source vehicle speed signals, fused vehicle speed signals, average output frequency, vehicle speed difference, and the number of repeated frames of motion signals. The judgment of vehicle positioning abnormalities is more comprehensive, avoiding the misjudgment or missed judgment that may occur when relying on a single indicator. At the same time, monitoring from different angles such as different sources of vehicle speed, output frequency of signals, differences in different vehicle speed signals, and stability of motion signals can more accurately capture various possible positioning abnormalities. In addition, different abnormal manifestations may occur in different driving environments, vehicle states, or fault modes. This condition can adapt to various complex situations, and positioning abnormalities caused by hardware failure, signal interference, algorithm problems, or other reasons can be detected.

[0074] Step S104: If the change condition hits the positioning abnormality condition, it is determined that the vehicle currently has a navigation positioning abnormality, and the vehicle's current positioning abnormality is sent to the cloud.

[0075] In an embodiment of the present application, when it is determined that the change hits the positioning abnormality condition, it is determined that the vehicle currently has a navigation positioning abnormality. That is, there is a problem with the vehicle's positioning system, resulting in inaccurate or unreliable navigation. At this time, the vehicle sends the current positioning abnormality to the cloud. The information sent about the positioning abnormality includes the specific abnormality type (such as abnormal speed signal, abnormal frequency, excessive speed difference or abnormal number of repeated frames, etc.), the time when the abnormality occurred, related signal data, etc. This can be achieved through the vehicle's communication system (such as cellular network, satellite communication, etc.) Upload of data.

[0076] After the cloud receives the positioning anomaly sent by the vehicle, it first receives and stores the data. The anomalies from different vehicles are classified and stored, and then the positioning anomaly is analyzed according to the preset analysis strategy to obtain the update objects that need to be updated in the vehicle and the update parameters corresponding to the update objects. Update information is generated based on the update objects and update parameters, and the update information is sent to the vehicle. For example, a notification is sent to the vehicle to inform the driver of the possible cause of the problem and the recommended solution.

[0077] The method provided in the embodiment of the present application can promptly detect whether the vehicle has navigation positioning anomalies by analyzing the changes in the fusion signal and the status signal, thereby solving the problem that the current solution cannot promptly identify navigation positioning anomalies. Secondly, after determining that the vehicle has navigation positioning anomalies, the positioning anomaly is sent to the cloud, providing key information for anomaly analysis. The cloud can then perform further analysis and processing based on the received positioning anomalies, promptly detect and resolve navigation positioning anomalies, and at the same time improve the reliability and accuracy of the navigation system, providing users with better navigation services.

[0078] In the embodiment of the present application, if the change situation hits the abnormal positioning condition, the method further includes the following steps A1-A2:

[0079] Step A1: update the weight parameters of the fusion signal according to the weight adjustment strategy.

[0080] Specifically, first obtain a pre-configured weight adjustment strategy, which includes a method for adjusting the weight of the fusion signal under different positioning anomalies. For example, different weight adjustment ranges can be set for different anomaly types. For example, when the speed difference is greater than the preset speed within a preset time period, the weight of the fusion signal can be reduced by a certain proportion; when the number of repeated frames of the motion signal is greater than the preset number of frames, the weight of the fusion signal can be gradually reduced according to the degree of anomaly.

[0081] The optimal weight adjustment strategy can be determined based on empirical data, test results, or through machine learning algorithms. For example, by analyzing a large amount of historical location anomaly data, the most appropriate weight adjustment method for different anomaly situations can be found.

[0082] Continuously monitor the vehicle's multi-source speed signals, fused speed signals, average output frequency, speed difference, and the number of repeated frames of motion signals to determine whether abnormal conditions are hit. This data can be obtained in real time using a sensor data acquisition system, a vehicle diagnostic interface, or specialized monitoring software.

[0083] When a positioning anomaly is detected, the anomaly type is immediately determined, and the weight adjustment direction and amplitude of the fusion signal are determined according to the pre-set weight adjustment strategy. According to the determined weight adjustment amplitude, the weight parameters of the fusion signal are updated. This can be achieved by modifying the weight coefficient in the software algorithm. For example, if the weight of the fusion signal in navigation positioning is 0.5, when a specific positioning anomaly is detected, the weight is reduced to 0.3 according to the strategy.

[0084] Step A2: sending the updated weight parameters to the functional modules related to navigation and positioning in the vehicle.

[0085] Specifically, obtain the functional modules related to navigation and positioning in the vehicle, including the map display module, the path planning module, the vehicle control system, etc. Package the updated weight parameters into a specific data format so that each functional module can parse it correctly. For example, the weight parameters and related identification information can be sent together in the form of a structure or a data packet. The weight parameters are sent to each functional module through the established communication connection. It can be sent in a broadcasting manner to ensure that all relevant modules can receive it.

[0086] When the changing situation hits the abnormal positioning condition, the present application updates the weight parameters of the fusion signal according to the weight adjustment strategy, thereby achieving immediate processing after the positioning abnormality is detected, rather than waiting for a long time for comprehensive system adjustment or maintenance. This quick response can reduce the impact time of positioning abnormalities on the vehicle navigation and positioning system and improve user experience. In addition, the updated weight parameters are sent to the functional modules related to navigation and positioning in the vehicle, so that these modules can promptly understand the changes in the fusion signal and make corresponding adjustments based on the new weight parameters. Thereby improving the accuracy of subsequent fusion signals.

[0087] In the embodiment of the present application, the method further includes the following steps B1-B3:

[0088] Step B1, obtaining update information based on feedback from the cloud based on abnormal positioning conditions.

[0089] Specifically, the vehicle registers with the cloud and subscribes to the positioning anomaly feedback service. For example, by sending a specific request message to the cloud, the vehicle indicates its need to receive positioning anomaly feedback information. After receiving the subscription request, the cloud will add the vehicle to the user list of the feedback service and push relevant update information to the vehicle when there is one.

[0090] When the cloud analyzes and locates the abnormal situation and generates updated information, it will push this information to the vehicles that have subscribed to the service. After the vehicle's communication module receives the updated information, it will pass it to the vehicle's processing system for subsequent processing.

[0091] Step B2: parsing the update information to determine the update object and the update parameters of the update object.

[0092] Specifically, determine the data format of the update information sent by the cloud. Use the corresponding parsing tool or library to parse the received update information. For example, if it is in JSON format, you can use the JSON parsing library in the programming language to convert it into an operable data structure.

[0093] In the parsed update information, find the field or parameter that identifies the update object, such as a specific string, code, or identifier that indicates whether the update target is positioning an abnormal condition, the map engine's signal fusion algorithm, or a navigation positioning-related hardware device.

[0094] The specific update object is determined based on this identifier. For example, if the identifier is "abnormal positioning condition", it is known that the update object is the abnormal positioning judgment logic of the vehicle. Once the update object is determined, the update parameters corresponding to the object are searched in the update information. These parameters can be values, configuration options, algorithm parameters, etc., depending on the type of update object.

[0095] Step B3: If the update object is a positioning abnormality condition, the condition content corresponding to the positioning abnormality condition is updated using the update parameters. Or, if the update object is a signal fusion algorithm of a map engine, the algorithm parameters of the signal fusion algorithm are updated using the update parameters. Or, if the update object is a hardware device related to navigation positioning, the working parameters of the hardware device are updated using the update parameters.

[0096] Specifically, if the update object is a positioning abnormality condition, the condition content corresponding to the positioning abnormality condition is modified according to the update parameter. For example, if the update parameter is to adjust the preset speed value of the speed difference, the part related to the speed difference judgment in the vehicle code is found, and the preset speed value is modified to a new value.

[0097] If the update object is the signal fusion algorithm of the map engine, find the software module related to the map engine in the vehicle. Update the algorithm parameters of the signal fusion algorithm according to the update parameters. This involves adjusting the fusion weight, the filtering parameters of the algorithm, etc. For example, if the update parameter is to increase the weight of a certain data source in the fusion algorithm, modify the corresponding part in the algorithm code to achieve the new weight distribution.

[0098] If the update object is a navigation and positioning related hardware device, determine the specific hardware device that needs to be updated. For example: GPS receiver, gyroscope, wheel speed sensor, etc. Use the update parameters to update the working parameters of the hardware device through the control interface or configuration tool of the hardware device. For example, if the update parameter is to adjust the search frequency of the GPS receiver, use the corresponding software tool to connect to the GPS receiver and modify its setting parameters.

[0099] The embodiment of the present application determines the specific update object according to the update information fed back by the cloud, adapting to the needs of different situations. According to the actual positioning abnormality, the part that needs to be updated can be accurately selected, which improves the efficiency and pertinence of problem solving.

[0100] Figure 2 is a flow chart of a method for detecting navigation positioning anomalies according to an embodiment of the present invention. Figure 2 As shown, the method includes:

[0101] Step S201, analyzing and locating abnormal situations according to a preset analysis strategy, obtaining update objects that need to be updated in the vehicle and update parameters corresponding to the update objects.

[0102] In an embodiment of the present application, first, a preset analysis strategy is determined based on factors such as the vehicle model, driving area, and historical abnormalities. For example, if the vehicle is mainly driven in an urban environment, a specific analysis strategy can be formulated for characteristics such as signal interference and high-rise building obstruction in the urban environment. If a certain type of positioning abnormality frequently occurs in a certain model of vehicle, an analysis can be performed based on the characteristics of the vehicle model. The analysis strategy may include methods such as statistical analysis, trend analysis, and correlation analysis. For example, for statistical analysis, the indicators to be counted can be determined, such as the frequency of occurrence of different types of positioning abnormalities, the average time interval between occurrences, etc. For trend analysis, the time span and time granularity of the analysis can be determined, such as analyzing the positioning abnormality trends of the past few months in units of months. For correlation analysis, the relationship between the abnormalities to be analyzed can be determined, such as the correlation between the vehicle speed difference and the number of motion signal re-frames.

[0103] Extract key information that needs to be analyzed from the stored positioning anomaly data. For example, extract vehicle status signals (such as vehicle speed, acceleration, steering angle, etc.), fusion signals (signals obtained by the map engine fusing multiple data sources), anomaly types (such as vehicle speed difference greater than the preset speed, motion signal frame count greater than the preset frame count, etc.), occurrence time and other information. Information extraction can be achieved through database query or data processing script. Classify and organize the extracted information for subsequent analysis. For example, store different types of anomalies in different data structures, and arrange the occurrence time in chronological order.

[0104] Preprocess the extracted data to ensure data quality and availability. Data cleaning can remove duplicate data, outliers, and erroneous data. For example, by setting a reasonable data range, outliers that exceed the range can be removed. Denoising can use filtering algorithms to remove noise from data. For example, use median filtering or mean filtering to denoise the vehicle speed signal. Format conversion can convert data from different sources into a unified format to facilitate subsequent analysis. For example, unify the time format into a specific standard format.

[0105] Analyze the processed data according to the preset analysis strategy. If the statistical analysis method is used, statistical software or programming tools can be used to calculate statistical indicators such as the mean, standard deviation, and median of different types of positioning anomalies. For example, calculate the proportion of abnormal situations where the speed difference is greater than the preset speed in all abnormal situations. If the trend analysis method is used, a curve of the change of abnormal situations over time can be plotted to analyze its trend. For example, a time series analysis tool is used to plot a curve of the change in the total number of positioning anomalies in the past few months to determine whether it is an upward, downward, or stable trend. If the correlation analysis method is used, the correlation coefficient between different abnormal situations can be calculated. For example, a correlation analysis function is used to calculate the correlation coefficient between the speed difference and the number of motion signal reframes to determine the strength of the correlation between them.

[0106] Based on the analysis results, determine the update objects that need to be updated in the vehicle and the update parameters corresponding to the update objects. For example, if the analysis finds that there is a problem with the fusion algorithm of the map engine, which causes an abnormal increase in the vehicle speed difference, it can be determined that the update object is the fusion algorithm of the map engine. The update parameters can be determined based on the specific problem, such as adjusting the weight distribution of different data sources in the fusion algorithm, optimizing the filtering parameters in the fusion algorithm, etc.

[0107] Step S202: Generate update information based on the update object and update parameters.

[0108] In the embodiment of the present application, the update information can be in a structured data format, such as JSON or XML. For example, a JSON object is designed to contain information such as the name of the update object, the specific values ​​of the update parameters, and instructions. In the update information, the reason and purpose of the update are clearly stated. For example, it is stated that due to the analysis results of the abnormal positioning situation, it is determined that the fusion algorithm of the map engine needs to adjust the weight distribution to improve the positioning accuracy.

[0109] Fill the determined update object and update parameters into the update information. For example, if the update object is the fusion algorithm of the map engine, and the update parameter is to reduce the weight of the GPS signal and increase the weight of the wheel speed sensor, these contents can be clearly listed in the update information.

[0110] Step S203: sending the update information to a preset terminal, wherein the preset terminal is used to verify the update parameters.

[0111] In the embodiment of the present application, the preset terminal can be a server of the vehicle manufacturer, a computer of an after-sales service center, or a special verification device. The preset terminal should have the ability to verify the updated parameters, such as having the function of simulating the vehicle operating environment and testing the effect of the updated parameters. Establishing a communication connection with the preset terminal can be achieved through a network connection (such as the Internet, a dedicated network, etc.). Ensure the stability and security of the communication connection to prevent the update information from being tampered with or lost during transmission.

[0112] The update information is sent to the preset terminal using a determined communication method. An encrypted transmission method can be used to ensure the security of the information. For example, the update information is encrypted using the SSL / TLS encryption protocol before being sent. When sending the update information, some auxiliary information can be sent at the same time, such as detailed data of locating abnormal conditions, records of the analysis process, etc., so that the preset terminal can perform more comprehensive verification.

[0113] As an example, suppose that the vehicle has abnormal positioning. After analysis, it is determined that the update object is the fusion algorithm of the map engine, and the update parameter is to reduce the weight of a specific sensor data source in the fusion algorithm and increase the weight of another sensor data source.

[0114] After receiving the update information, the preset terminal will first verify it in a simulated environment. The preset terminal is deployed with a dedicated software simulation platform that can simulate the driving of vehicles in various road conditions and environments. It will load the current vehicle's map data, sensor configuration, historical positioning anomaly data and other information, and then apply the update parameters to the simulated map engine fusion algorithm. During the simulation process, the preset terminal will simulate the vehicle driving in different environments such as urban high-rise areas, mountainous areas, tunnels, etc., and observe the accuracy and stability of the positioning results. If the positioning deviation in high-rise areas is significantly reduced after reducing the weight of a specific sensor data source, and the overall positioning stability is improved after increasing the weight of another sensor data source, and the deviation from the historical normal driving data is within an acceptable range, then it can be preliminarily considered that these updated parameters are effective.

[0115] Next, the preset terminal will also perform a stress test. It will simulate a large number of vehicles sending positioning data at the same time to test the performance of the updated fusion algorithm under high load. If the algorithm can still quickly and accurately fuse the signals of each sensor and generate stable positioning results under high load, then the feasibility of the updated parameters is further verified.

[0116] Finally, the preset terminal will combine the results of the simulated environment test and the stress test to determine whether the updated parameters can be applied to the actual vehicle. If the verification is passed, an execution instruction will be sent to the vehicle to let the vehicle use these updated parameters to update the update object.

[0117] Step S204: receiving an execution instruction fed back by the preset terminal based on the update information, wherein the execution instruction is sent by the preset terminal after verifying the update parameters.

[0118] In an embodiment of the present application, after receiving the update information, the preset terminal will verify the update parameters. The verification process includes simulating the vehicle operating environment, performing actual tests, etc. When the preset terminal verifies the update parameters, it will send an execution instruction to the vehicle side. The execution instruction can be a specific signal or message that notifies the vehicle side that the update operation can be performed. For example, the execution instruction can be a data packet containing a specific code. After receiving the execution instruction, the vehicle side parses and confirms it. Ensure the integrity and correctness of the execution instruction to prevent misoperation. If the execution instruction is incomplete or there is an error, you can request the preset terminal to resend it.

[0119] Step S205, responding to the execution instruction, updating the update object using the update parameters.

[0120] In an embodiment of the present application, in response to an execution instruction, the update object is updated using update parameters. If the update object is a fusion algorithm of a map engine, the new algorithm parameters can be applied to the map engine by means of a software update. The update can be performed using an on-board software update system or a remote update method. During the update process, the progress and status of the update are monitored in real time. The progress of the update can be displayed to the driver through the vehicle's display or indicator light to let the driver know about the update. If a problem occurs during the update process, the update is stopped in a timely manner and appropriate measures are taken, such as restoring the backup status, reporting the problem to a preset terminal, etc.

[0121] After the update is completed, the update is confirmed. The success of the update can be confirmed by re-acquiring the vehicle's status signal and fusion signal and analyzing whether the positioning anomaly has been improved. For example, check whether the vehicle speed difference is within a reasonable range, whether the number of motion signal reframes is normal, etc. If the update is successful, a confirmation message of the successful update can be sent to the preset terminal so that the preset terminal can record and manage it. If the update fails, the problem can be reported to the preset terminal.

[0122] The embodiment of the present application first analyzes the positioning abnormality through a preset analysis strategy, which can accurately determine the objects and corresponding parameters that need to be updated in the vehicle, improve the accuracy of problem location, and avoid blindly checking and updating the entire system. Secondly, the update information is generated and sent to the preset terminal for verification, which ensures the reliability and security of the update parameters and prevents more serious problems caused by erroneous updates. The verification process of the preset terminal also increases the authority and credibility of the update operation. The update is performed after receiving the execution instruction, which ensures the orderliness and legality of the update operation and avoids unauthorized update behavior. Overall, this solution helps to efficiently solve the problem of abnormal vehicle positioning, improve the stability and accuracy of the vehicle navigation system, and at the same time ensure the safety and reliability of vehicle operation.

[0123] In an embodiment of the present application, the method also includes: if no execution instruction is received from the preset terminal within the preset waiting time, querying whether there is an alternative object corresponding to the updated object; if there is an alternative object, obtaining the configuration parameters of the alternative object; configuring the alternative object using the configuration parameters, and performing corresponding navigation operations based on the configured alternative object.

[0124] Specifically, when the vehicle sends the update information to the preset terminal, a timer is started at the same time to start recording the waiting time. This timer can be a clock function built into the vehicle system or a special timing program. The time of the timer is continuously monitored and compared with the preset waiting time. The preset waiting time can be set according to actual conditions, for example, 1 hour, 24 hours, etc. If an execution instruction is received from the preset terminal during the waiting process, the timer is stopped and subsequent processing steps are performed.

[0125] If the timer reaches the preset waiting time, and the vehicle end still does not receive the execution instruction fed back by the preset terminal, it is determined to be a waiting timeout. At this time, the vehicle system needs to take corresponding measures to deal with this situation.

[0126] The range of candidate objects is determined based on the nature and function of the update object. For example, if the update object is the fusion algorithm of the map engine, the candidate objects can be other similar fusion algorithms or alternative positioning systems. The range of candidate objects can be determined by querying the vehicle system's configuration files, databases, or online services. These resources contain information about different positioning systems and algorithms, as well as their availability and applicability in different situations.

[0127] Using the determined candidate object range, a query is performed in the vehicle system to determine whether there is a candidate object corresponding to the updated object. The query can be performed through a programming interface or a command line tool, such as using a specific API function or system command to search for available resources in the vehicle system.

[0128] If the query result indicates that there is an alternative object, proceed to the next step; if there is no alternative object, other emergency measures need to be taken, such as prompting the driver to manually handle the positioning abnormality or contacting the vehicle manufacturer's customer service staff for help.

[0129] Determine the method for obtaining the configuration parameters of the candidate object based on its type and source. The configuration parameters are stored in the local files of the vehicle system, on an online server, or obtained from other devices through a specific communication protocol. For example, if the candidate object is an alternative positioning system, its configuration parameters are stored in the vehicle's storage device and can be obtained by reading the corresponding configuration file. If the candidate object is an algorithm provided by an online service, its configuration parameters need to be obtained through a network request.

[0130] Use the specified parameter acquisition method to obtain the configuration parameters of the candidate object. This involves file reading, network communication, data parsing and other operations. For example, if the configuration parameters are stored in a local file, you can use the file reading function to open the file and read the parameter content. If you obtain the parameters through a network request, you need to use the HTTP client library to send a request and receive the response data, and then parse the response data to obtain the configuration parameters.

[0131] Use the obtained configuration parameters to configure the candidate object. The configuration process involves operations such as modifying system settings, loading parameter files, and starting specific services. For example, if the candidate object is a positioning system, the obtained parameters need to be set in the configuration file of the system, or the parameters need to be passed to the system through the programming interface for initialization. When configuring the candidate object, it is necessary to ensure the correctness and completeness of the parameters, as well as the security and stability of the configuration operation. Parameter verification and error handling can be performed to prevent problems during the configuration process.

[0132] After the configuration is completed, the corresponding navigation operation is performed based on the configured candidate object. This includes functions such as obtaining location information, planning routes, and providing navigation instructions. For example, if the candidate object is a backup map engine, the engine can be used to obtain the current location of the vehicle, plan the best route based on the destination, and then provide navigation instructions to the driver through the vehicle's display or voice system.

[0133] During the navigation operation, it is necessary to continuously monitor the performance and stability of the candidate objects and whether the positioning anomalies have been resolved. If new problems or anomalies are found, appropriate measures need to be taken in a timely manner to deal with them.

[0134] In the embodiment of the present application, when the execution instruction fed back by the preset terminal is not received within the preset waiting time, the alternative object of the update object is actively queried, ensuring that the vehicle system can still take effective countermeasures when communication delays or other problems result in the inability to obtain the execution instruction from the preset terminal in time. If there is an alternative object, its configuration parameters are obtained and configured, so that the vehicle can perform navigation operations based on the configured alternative object, ensuring the continuity and stability of the vehicle navigation function, avoiding a long period of stagnation due to waiting for the preset terminal instruction, greatly improving the reliability and adaptability of the vehicle navigation system, providing users with a more stable navigation service, and reducing the inconvenience and risks caused by abnormal positioning.

[0135] In this embodiment, a detection device for abnormal navigation positioning is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0136] This embodiment provides a detection device for abnormal navigation positioning, such as Figure 3 As shown, including:

[0137] The first acquisition module 301 is used to acquire a fusion signal currently output by a map engine of the vehicle, wherein the fusion signal is obtained by fusing signals provided by multiple data sources by the map engine.

[0138] The second acquisition module 302 is used to acquire current status signals of different dimensions of the vehicle.

[0139] The signal analysis module 303 is used to analyze the changes in the fusion signal and each state signal, and determine whether the changes hit the positioning abnormality condition within a preset time period.

[0140] The sending module 304 is used to determine that the vehicle currently has a navigation positioning anomaly if the change situation hits the positioning anomaly condition, and send the vehicle's current positioning anomaly situation to the cloud.

[0141] In the embodiment of the present application, the signal analysis module 303 is used to extract the multi-source vehicle speed signal from the state signal, and to extract the fused vehicle speed signal from the fused signal, and to analyze whether the multi-source vehicle speed signal and the fused vehicle speed signal are both 0 within a preset time period. The average output frequency of the fused signal within a preset time period is obtained, and the average output frequency is analyzed to be less than the preset frequency. The navigation vehicle speed signal is extracted from the state signal, and the fused vehicle speed signal is extracted from the fused signal, and the vehicle speed difference between the fused vehicle speed signal and the navigation vehicle speed signal is analyzed to be greater than the preset vehicle speed within the preset time period. The number of repeated frames of the vehicle's motion signal is extracted from the state signal, and the number of repeated frames of the motion signal is analyzed to be greater than the preset number of frames.

[0142] In the embodiment of the present application, the signal analysis module 303 is used to determine that the abnormal condition of the positioning is hit if the multi-source vehicle speed signal and the fused vehicle speed signal are not 0 at the same time within the preset time period, and / or the average output frequency is less than the preset frequency, and / or the vehicle speed difference is greater than the preset vehicle speed within the preset time period, and / or the number of repeated frames of the motion signal is greater than the preset number of frames. If the multi-source vehicle speed signal and the fused vehicle speed signal are 0 at the same time within the preset time period, the average output frequency is greater than or equal to the preset frequency, the vehicle speed difference is less than or equal to the preset vehicle speed within the preset time period, and the number of repeated frames of the motion signal is less than or equal to the preset number of frames, it is determined that the abnormal condition of the positioning is not hit.

[0143] In the embodiment of the present application, the device further includes: a weight updating module, which is used to update the weight parameters of the fusion signal according to the weight adjustment strategy if the change situation hits the abnormal positioning condition, and send the updated weight parameters to the functional modules related to navigation positioning in the vehicle.

[0144] In an embodiment of the present application, the device further includes: a parameter update module, which is used to obtain update information based on feedback from the cloud based on the abnormal positioning situation. The update information is parsed to determine the update object and the update parameters of the update object. If the update object is a positioning abnormality condition, the condition content corresponding to the positioning abnormality condition is updated using the update parameters. Or, if the update object is a signal fusion algorithm of a map engine, the algorithm parameters of the signal fusion algorithm are updated using the update parameters. Or, if the update object is a hardware device related to navigation positioning, the working parameters of the hardware device are updated using the update parameters.

[0145] In an embodiment of the present application, the device also includes: an analysis module, which is used to analyze and locate abnormal situations according to a preset analysis strategy, and obtain update objects that need to be updated in the vehicle and update parameters corresponding to the update objects; generate update information based on the update objects and update parameters; send the update information to a preset terminal, wherein the preset terminal is used to verify the update parameters; receive an execution instruction fed back by the preset terminal based on the update information, wherein the execution instruction is sent after the preset terminal verifies the update parameters; respond to the execution instruction and update the update object using the update parameters.

[0146] In an embodiment of the present application, the device also includes: a processing module, which is used to query whether there is an alternative object corresponding to the updated object if no execution instruction is received from the preset terminal feedback within the preset waiting time; if there is an alternative object, obtain the configuration parameters of the alternative object; configure the alternative object using the configuration parameters, and perform corresponding navigation operations based on the configured alternative object.

[0147] See also Figure 4 , Figure 4 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 4 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system).

[0148] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0149] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0150] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the use of a computer device based on the presentation of a small program landing page, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0151] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0152] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0153] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0154] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for detecting navigation positioning anomaly, characterized in that: The method comprises: Acquire a fusion signal currently output by a map engine of the vehicle, wherein the fusion signal is obtained by fusing signals provided by multiple data sources by the map engine; Acquire current status signals of the vehicle in different dimensions; Analyze the changes of the fusion signal and each of the status signals, and determine whether the changes hit the positioning abnormality condition within a preset time period; If the change condition hits the positioning abnormality condition, it is determined that the vehicle currently has a navigation positioning abnormality, and the current positioning abnormality of the vehicle is sent to the cloud.

2. The method according to claim 1, characterized in that The analyzing the changes of the fusion signal and each of the state signals includes any one or more of the following: Extracting a multi-source vehicle speed signal from the state signal, and extracting a fused vehicle speed signal from the fused signal, and analyzing whether the multi-source vehicle speed signal and the fused vehicle speed signal are both 0 within the preset time period; Obtaining an average output frequency of the fusion signal within the preset time period, and analyzing whether the average output frequency is less than a preset frequency; Extracting a navigation vehicle speed signal from the state signal, and extracting a fused vehicle speed signal from the fused signal, and analyzing whether a vehicle speed difference between the fused vehicle speed signal and the navigation vehicle speed signal is greater than a preset vehicle speed within the preset time period; The number of repeated frames of the motion signal of the vehicle is extracted from the state signal, and it is analyzed whether the number of repeated frames of the motion signal is greater than a preset number of frames.

3. The method according to claim 2, characterized in that The determining whether the change condition hits the positioning abnormality condition within a preset time period includes: If the multi-source vehicle speed signal and the fused vehicle speed signal are not simultaneously 0 within the preset time period, and / or the average output frequency is less than the preset frequency, and / or the vehicle speed difference is greater than the preset vehicle speed within the preset time period, and / or the number of repeated frames of the motion signal is greater than the preset number of frames, it is determined that the abnormal positioning condition is hit; If the multi-source vehicle speed signal and the fused vehicle speed signal are both 0 within the preset time period, the average output frequency is greater than or equal to the preset frequency, the vehicle speed difference is less than or equal to the preset vehicle speed within the preset time period, and the number of repeated frames of the motion signal is less than or equal to the preset number of frames, then a missed positioning abnormal condition is determined.

4. The method according to claim 1, characterized in that: If the change condition hits the abnormal positioning condition, the method further includes: Update the weight parameters of the fusion signal according to the weight adjustment strategy; The updated weight parameters are sent to the functional modules related to navigation and positioning in the vehicle.

5. The method according to claim 1, characterized in that: The method further comprises: Obtaining update information from the cloud based on feedback from the abnormal positioning situation; Parsing the update information to determine an update object and update parameters of the update object; If the update object is the abnormal positioning condition, the update parameters are used to update the condition content corresponding to the abnormal positioning condition; or, if the update object is the signal fusion algorithm of the map engine, the update parameters are used to update the algorithm parameters of the signal fusion algorithm; or, if the update object is a hardware device related to navigation and positioning, the update parameters are used to update the working parameters of the hardware device.

6. The method according to claim 1, characterized in that The method further comprises: Analyze the positioning abnormality according to a preset analysis strategy to obtain an update object that needs to be updated in the vehicle and an update parameter corresponding to the update object; Generate update information based on the update object and the update parameter; Sending the update information to a preset terminal, wherein the preset terminal is used to verify the update parameters; receiving an execution instruction fed back by the preset terminal based on the update information, wherein the execution instruction is sent by the preset terminal after verifying the update parameters; In response to the execution instruction, the update object is updated using the update parameter.

7. The method according to claim 6, characterized in that The method further comprises: If no execution instruction fed back by the preset terminal is received within the preset waiting time, query whether there is a candidate object corresponding to the update object; If there is a candidate object, obtain the configuration parameters of the candidate object; The candidate objects are configured using the configuration parameters, and corresponding navigation operations are performed based on the configured candidate objects.

8. A detection device for abnormal navigation positioning, characterized in that: The device comprises: A first acquisition module is used to acquire a fusion signal currently output by a map engine of the vehicle, wherein the fusion signal is obtained by fusing signals provided by multiple data sources by the map engine; A second acquisition module is used to acquire current status signals of the vehicle in different dimensions; A signal analysis module, used to analyze the changes of the fusion signal and each of the state signals, and determine whether the changes hit the positioning abnormality condition within a preset time period; The sending module is used to determine that the vehicle currently has a navigation positioning anomaly if the change situation hits the positioning anomaly condition, and send the vehicle's current positioning anomaly situation to the cloud.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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