Vehicle navigation log real-time capturing method and system

Abstract

The invention discloses a method and a system for capturing a vehicle navigation log in real time. The method comprises the following steps: acquiring multi-dimensional operation data of positioning, environmental perception, vehicle state and user interaction interface influence navigation from multi-source heterogeneous equipment in real time; setting an annular buffer area, continuously recording navigation data of recent 30 minutes by adopting an annular queue structure, and optimizing a storage space utilization rate through a cyclic coverage writing mechanism; setting a user, system and cloud three-layer trigger mechanism, and cooperatively triggering log storage based on a user key or voice instruction, a system dynamic threshold and a cloud instruction; when a vehicle runs normally, new data continuously covers old data, and when a high-priority event or active triggering of a user is detected, current cache is frozen and key data is locked to ensure that complete context information before and after a fault occurs is not covered, and a closed-loop process of data acquisition, cache storage and triggering control is formed. The vehicle fault diagnosis efficiency can be improved, and the safety and the reliability are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle navigation logs, and more particularly to a vehicle navigation log real-time capturing method and system. BACKGROUND

[0002] As a core functional module of modern vehicles, the reliability of the vehicle navigation system directly affects the driving experience and road safety. However, in complex and variable actual driving environments (such as urban canyons, tunnels, and electromagnetic interference areas), the navigation system often causes abnormal functions due to occasional faults, such as positioning drift, path planning failure, or sensor data conflict. These faults are usually difficult to reproduce and cannot be predicted in advance, which brings great challenges to fault diagnosis and system optimization. However, the traditional log recording scheme often has the following technical bottlenecks: (1) log recording lag, relying on abnormal detection after the occurrence of faults to trigger recording, resulting in the loss of key data before the fault; (2) waste of storage resources, full-time recording or fixed-period storage occupies a large amount of storage space, and the actual effective data ratio is low; (3) lack of user participation, the driver cannot actively intervene in the log recording process, and only relies on system automation. These problems result in low efficiency of diagnosing occasional faults, affecting user experience and system reliability. Therefore, how to capture vehicle navigation logs in real time to ensure the reliability and real-time performance of key log data is of great significance. SUMMARY

[0003] The present application provides a vehicle navigation log real-time capturing method and system, which solves the problems of missing data, lag, and low and inaccurate fault diagnosis efficiency in capturing vehicle navigation logs in existing vehicles, improves vehicle fault diagnosis efficiency, and improves the safety and reliability of vehicle use.

[0004] To achieve the above purpose, the present application provides the following technical solutions:

[0005] A vehicle navigation log real-time capturing method, comprising:

[0006] Real-time acquisition of multi-dimensional running data of positioning, environment perception, vehicle state and user interaction interface affecting navigation from multiple source heterogeneous devices;

[0007] Setting a ring buffer, using a ring queue structure to continuously record navigation data in the last 30 minutes, and optimizing storage space utilization through a cyclic overwrite writing mechanism;

[0008] Setting a three-layer trigger mechanism of user, system and cloud, and cooperatively triggering log saving based on user key or voice instruction, system dynamic threshold and cloud instruction;

[0009] When the vehicle is running normally, new data continuously covers old data, when a high-priority event is detected or the user actively triggers, the current cache is frozen and the key data is locked, ensuring that the complete context information before and after the fault occurs is not covered, forming a closed-loop process of data acquisition, cache storage and trigger control.

[0010] Preferably, the log saving is triggered by the user key or voice instruction, the system dynamic threshold and the cloud instruction, including:

[0011] The user saves the current data through a physical key or a voice instruction;

[0012] The system automatically triggers the record based on the dynamic threshold;

[0013] The cloud issues an instruction to freeze the current data or extend the cache duration according to the analysis of group data, realizing the whole-scene demand of user perception, system detection and cloud cooperation.

[0014] Preferably, the system automatically triggers the record based on the dynamic threshold, including:

[0015] If the vehicle positioning drift is greater than the set distance threshold, the vehicle navigation log record is automatically triggered.

[0016] Preferably, the system automatically triggers the record based on the dynamic threshold, including:

[0017] If the path re-planning frequency is greater than the set frequency threshold, the vehicle navigation log record is automatically triggered.

[0018] Preferably, the cloud issues an instruction to freeze the current data or extend the cache duration according to the analysis of group data, including:

[0019] If it is in a high-risk road section early warning, the cloud issues an instruction to freeze the current data or extend the cache duration.

[0020] Preferably, the annular buffer zone is a first-in-first-out data structure, the write pointer returns to the beginning after reaching the end, covering the old data, and the storage space utilization rate is optimized through the cyclic coverage writing mechanism.

[0021] Preferably, it further includes:

[0022] After triggering the log cache freezing, the event timestamp is marked, then the data is compressed and encrypted and sent to the cloud platform for analysis.

[0023] The application also provides a vehicle navigation log real-time capture system using the above capture method, including a data acquisition module, a dynamic annular cache module and a trigger control module.

[0024] The data acquisition module serves as a perception layer of the system and is configured to acquire multi-dimensional operation data of positioning, environment perception, vehicle state and user interaction interface affecting navigation from multiple source heterogeneous devices in real time

[0025] The dynamic ring buffer module serves as a storage layer of the system and is configured to set a ring buffer area, continuously record navigation data in the last 30 minutes by using a ring queue structure, and optimize storage space utilization by using a cyclic overwrite writing mechanism.

[0026] The trigger control module serves as a decision layer of the system and is configured to set a three-layer trigger mechanism of user, system and cloud, and cooperatively trigger log saving based on user key or voice instruction, system dynamic threshold and cloud instruction.

[0027] When the vehicle is normally running, new data is obtained by the data acquisition module, and the new data continuously overwrites the old data by the dynamic ring buffer module. When the trigger control module detects a high-priority event or a user initiatively triggers, the current cache is frozen and the key data is locked, so that the complete context information before and after the fault occurs is not overwritten, thereby forming a closed-loop process of data acquisition, cache storage and trigger control.

[0028] Preferably, the data acquisition module comprises:

[0029] A positioning data acquisition unit configured to acquire positioning data from a GPS / Beidou receiver and an inertial navigation system in real time.

[0030] A sensor data fusion unit configured to acquire vehicle state and environment perception from a camera, a millimeter wave radar, a vehicle speed sensor and a steering wheel rotation sensor in real time.

[0031] A navigation logic data capture unit configured to acquire path rule engine decision log and map version and update state.

[0032] An environment and network state unit configured to monitor vehicle surrounding electromagnetic interference and mobile communication signal.

[0033] A user interaction data recording unit configured to record physical key trigger log and voice instruction log.

[0034] Preferably, the trigger control module comprises:

[0035] A user trigger module configured to trigger saving of current data when receiving user physical key or voice instruction.

[0036] A system trigger module configured to automatically trigger log recording when a set dynamic threshold has met a condition.

[0037] A cloud trigger module is configured to analyze the vehicle in a high-risk early warning according to the group data, and issue an instruction to control the dynamic ring buffer module to freeze the current data or extend the cache duration.

[0038] The application provides a vehicle navigation log real-time capturing method and system, which acquires multi-dimensional data from multi-source heterogeneous devices, and combines ring buffer real-time recording with a multi-source triggering mechanism to ensure that key log data at the failure time can be captured whether the problem is predicted or detected, solve the problems of missing data, hysteresis, low fault diagnosis efficiency and inaccuracy in capturing vehicle navigation logs, improve vehicle fault diagnosis efficiency, and improve the safety and reliability of vehicle use. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present application, the drawings needed in the embodiments will be briefly introduced as follows.

[0040] Figure 1 is a schematic diagram of a vehicle navigation log real-time capturing method provided by the application.

[0041] Figure 2 is a schematic diagram of a multi-source triggering process provided by the embodiment of the application.

[0042] Figure 3 is a schematic diagram of a vehicle navigation log real-time capturing system provided by the application.

[0043] Figure 4 is a schematic diagram of a data acquisition module provided by the embodiment of the application. DETAILED DESCRIPTION

[0044] In order to enable personnel in the art to better understand the scheme of the embodiments of the present application, the embodiments of the present application will be further described in detail below in combination with the drawings and embodiments.

[0045] In order to enable personnel in the art to better understand the scheme of the embodiments of the present application, the embodiments of the present application will be further described in detail below in combination with the drawings and embodiments.

[0046] As shown in Figure 1 and Figure 2 , a vehicle navigation log real-time capturing method comprises the following steps:

[0047] S1: Real-time acquisition of multi-dimensional running data of positioning, environment perception, vehicle state and user interaction interface affecting navigation from multi-source heterogeneous devices.

[0048] S2: Set up a ring buffer, continuously record the navigation data of the last 30 minutes with a ring queue structure, and optimize the storage space utilization through a cyclic overwrite writing mechanism.

[0049] S3: Set up a three-layer triggering mechanism of user, system, and cloud, and cooperatively trigger log saving based on user key or voice instruction, system dynamic threshold, and cloud instruction.

[0050] S4: When the vehicle is driving normally, new data continuously overwrite old data, when high-priority events are detected or the user actively triggers, freeze the current cache and lock the key data, ensure that the complete context information before and after the fault occurs is not overwritten, form a closed-loop process of data acquisition, cache storage, and trigger control.

[0051] Specifically, the multi-dimensional running data includes positioning coordinates, vehicle speed, path planning decision, etc., and the multi-source heterogeneous devices include GPS / Beidou receiver, inertial navigation system, camera, millimeter wave radar, vehicle speed sensor, etc. Real-time acquisition of positioning, environment perception, vehicle state, and user interaction data from multi-source heterogeneous devices that may affect navigation, covering the full-dimensional running state of the navigation system, providing complete context information for dynamic ring cache, supporting accurate backtracking and analysis during fault diagnosis. Through the three-layer triggering mechanism of user, system, and cloud, the flexibility and comprehensiveness of log recording are ensured: the user can save the current data through physical keys or voice instructions, and when using the navigation software for the first time, there will be a fault log upload guide; the system automatically triggers recording based on dynamic thresholds (such as positioning drift > 30 meters, path re-planning frequency > 5 times / minute), where the system can be an autonomous driving system or a driving control system; the cloud issues instructions (such as high-risk road warning) based on group data analysis, controls the dynamic ring cache module to freeze the current data or extend the cache duration; this multi-level triggering mechanism covers the full-scene demand from user perception to system detection to cloud coordination, ensuring that any fault at any time can be accurately captured, providing a reliable data foundation for fault diagnosis. This method is particularly aimed at the log capture problem of occasional navigation faults, through the combination of real-time recording by ring cache and multi-source triggering mechanism, ensuring that whether the problem is predicted or detected, the key log data at the fault time can be captured.

[0052] Further, the cooperative triggering of log saving by user key or voice instruction, system dynamic threshold, and cloud instruction includes:

[0053] The user saves the current data through physical keys or voice instructions;

[0054] The system automatically triggers recording based on dynamic thresholds;

[0055] The cloud end issues a command to freeze the current data or extend the cache time length according to the group data analysis, and realizes the full-scene requirement from user perception to system detection to cloud end cooperation.

[0056] Further, the system automatically triggers the record based on the dynamic threshold, including:

[0057] If the vehicle positioning drift is greater than the set distance threshold, the vehicle navigation log record is automatically triggered.

[0058] Further, the system automatically triggers the record based on the dynamic threshold, including:

[0059] If the path re-planning frequency is greater than the set frequency threshold, the vehicle navigation log record is automatically triggered.

[0060] Further, the cloud end issues a command to freeze the current data or extend the cache time length according to the group data analysis, including:

[0061] If it is in a high-risk road section early warning, the cloud end issues a command to freeze the current data or extend the cache time length.

[0062] Further, the annular buffer is a first-in first-out data structure, and the write pointer returns to the beginning after reaching the end, covering the old data, and the storage space utilization rate is optimized through the cyclic coverage writing mechanism.

[0063] The method further includes marking an event timestamp after triggering the log cache freezing, and then sending the data to the cloud end sub-platform for analysis after compression and encryption.

[0064] It can be seen that the present application provides a vehicle navigation log real-time capture method, which acquires multi-dimensional data in real time through multi-source heterogeneous devices, and combines annular cache real-time recording with a multi-source triggering mechanism, so as to ensure that key log data at the fault time can be captured whether the problem is pre-judged or detected, solve the problems of missing data, hysteresis, low fault diagnosis efficiency and inaccuracy in capturing vehicle navigation logs in existing vehicles, improve the vehicle fault diagnosis efficiency, and improve the safety and reliability of vehicle use.

[0065] As shown in Figure 3 The present application also provides a vehicle navigation log real-time capture system, which uses the above capture method and includes a data acquisition module, a dynamic annular cache module and a trigger control module.

[0066] The data acquisition module serves as the perception layer of the system and is used to acquire positioning, environmental perception, vehicle state and user interaction interface influence navigation multi-dimensional operation data from multi-source heterogeneous devices in real time.

[0067] The dynamic ring buffer module is used as a storage layer of the system, and is configured to set a ring buffer, continuously record navigation data in the last 30 minutes by using a ring queue structure, and optimize storage space utilization by using a cyclic cover write mechanism.

[0068] The trigger control module is used as a decision layer of the system, and is configured to set a three-layer trigger mechanism of a user, a system and a cloud, and cooperatively trigger log saving based on a user key or voice instruction, a system dynamic threshold and a cloud instruction.

[0069] When the vehicle is normally driven, new data is obtained by the data acquisition module, and the new data continuously covers old data by the dynamic ring buffer module, when the trigger control module detects a high-priority event or a user initiatively triggers, the current cache is frozen and the key data is locked, so that the complete context information before and after the fault occurs is not covered, and a closed-loop process of data acquisition, cache storage and trigger control is formed.

[0070] Specifically, the data acquisition module is used as a perception layer of the system, and is configured to acquire multi-dimensional data (such as positioning coordinates, vehicle speed, path planning decision, etc.) from a GPS, an inertial navigation system, an environment sensor and a user interaction interface in real time, so as to provide comprehensive input information for subsequent processing; the dynamic ring buffer module is used as a storage layer, and is configured to continuously record navigation data in the last 30 minutes by using a ring queue structure, and optimize storage space utilization by using a cyclic cover write mechanism, while supporting high-priority data locking (such as a GPS signal loss event), so as to ensure that the complete context information before and after the fault occurs is not covered; the trigger control module is used as a decision layer, and is configured to cooperatively trigger log saving based on a user key or voice instruction, a system dynamic threshold (such as positioning drift > 30 meters) and a cloud instruction (such as a high-risk road section early warning), and control the dynamic ring buffer module to freeze current data or extend cache duration, so as to cover the full-scene requirements from user perception to system detection to cloud cooperation. Through close cooperation of the three modules, a closed-loop process of data acquisition, cache storage and trigger control is formed, and the fault diagnosis efficiency and system reliability are significantly improved.

[0071] The dynamic ring buffer module is the core storage unit of the vehicle navigation log system. The module continuously records navigation-related data (such as GPS coordinates, sensor data, path planning decisions, etc.) collected by the data acquisition module for the last 30 minutes using a ring queue structure. The ring buffer is a first-in, first-out data structure. When the write pointer reaches the end, it returns to the beginning, overwriting old data. Through the cyclic overwrite write mechanism, the storage space utilization rate is optimized. When the vehicle is driving normally, new data continuously overwrites old data. When a high-priority event (such as GPS signal loss or sudden braking) is detected or the user actively triggers it, the module will freeze the current cache and lock the key data, ensuring that the complete context information before and after the fault is not overwritten. This design balances storage efficiency and data integrity, and only a small amount of storage space is required to store the complete context from 25 minutes before the fault to 5 minutes after the fault. At the same time, the cloud can dynamically extend the cache duration (such as extending to 1 hour on high-risk sections), thereby providing accurate and comprehensive data support for the diagnosis of occasional faults, significantly improving fault location efficiency and system reliability.

[0072] Further, as shown in Figure 4 the data acquisition module includes:

[0073] a positioning data acquisition unit for acquiring positioning data from a GPS / Beidou receiver and an inertial navigation system in real time;

[0074] a sensor data fusion unit for acquiring vehicle state and environmental perception from a camera, millimeter wave radar, vehicle speed sensor, and steering wheel rotation sensor in real time;

[0075] a navigation logic data capture unit for acquiring path rule engine decision logs and map version and update status;

[0076] an environment and network status unit for monitoring vehicle surrounding electromagnetic interference and mobile communication signal;

[0077] a user interaction data recording unit for recording physical button trigger logs and voice command logs.

[0078] Further, the trigger control module includes:

[0079] a user trigger module for triggering the saving of current data when receiving user physical button or voice command;

[0080] a system trigger module for automatically triggering log recording when the set dynamic threshold has met the condition;

[0081] a cloud trigger module for issuing instructions to control the dynamic ring buffer module to freeze the current data or extend the cache duration when the vehicle is in a high-risk warning state based on group data analysis.

[0082] In practical application, the trigger control module is an intelligent switch of the vehicle navigation log system, and cooperates with the data acquisition module and the dynamic ring buffer module closely.

[0083] It can be seen that the vehicle navigation log real-time capturing system provided by the application can acquire multi-dimensional data through multi-source heterogeneous devices, and the combination of the ring buffer real-time recording and the multi-source triggering mechanism ensures that the key log data at the fault moment can be captured whether the problem is predicted or detected, solves the problems of missing data and hysteresis in the existing vehicle navigation log capturing, and is easy to cause low fault diagnosis efficiency and inaccuracy, and can improve the vehicle fault diagnosis efficiency, improve the safety and reliability of the vehicle use.

[0084] The above describes the structure, features and effects of the application in detail according to the embodiments shown in the drawings, and the above description is only the preferred embodiments of the application, but the application is not limited to the embodiments shown in the drawings, any changes or modifications made according to the concept of the application, or equivalent embodiments with equivalent changes, as long as they are within the scope of the application, should be within the protection scope of the application.

Claims

1. A method for real-time capturing of a vehicle navigation log, characterized in that, The application relates to a vehicle navigation log record method and system. Real-time acquisition of multi-dimensional operation data of positioning, environment perception, vehicle state and user interactive interface influencing navigation from multiple source heterogeneous devices; A ring buffer is arranged, a ring queue structure is adopted to continuously record navigation data in the last 30 minutes, and a cyclic cover writing mechanism is used to optimize storage space utilization; A three-layer triggering mechanism of users, systems and clouds is arranged, and log saving is triggered based on user buttons or voice instructions, system dynamic thresholds and cloud instructions; When the vehicle is normally driven, new data continuously covers old data, when a high-priority event is detected or a user actively triggers, the current cache is frozen and key data is locked, complete context information before and after the fault is ensured not to be covered, and a closed-loop process of data acquisition, cache storage and trigger control is formed.

2. The in-vehicle navigation log real-time capturing method according to claim 1, characterized by, The three-layer triggering mechanism of users, systems and clouds is arranged, and log saving is triggered based on user buttons or voice instructions, system dynamic thresholds and cloud instructions. Users save current data through physical buttons or voice instructions. The system automatically triggers recording based on dynamic thresholds. The cloud issues instructions to freeze current data or extend cache duration according to group data analysis, and realizes full-scene requirements of user perception, system detection and cloud cooperation.

3. The in-vehicle navigation log real-time capturing method according to claim 2, wherein, The system automatically triggers recording based on dynamic thresholds. Whether the vehicle positioning drift is greater than a set distance threshold is judged, and if yes, the vehicle navigation log recording is automatically triggered.

4. The in-vehicle navigation log real-time capturing method according to claim 3, characterized by, Whether the path re-planning frequency is greater than a set frequency threshold is judged, and if yes, the vehicle navigation log recording is automatically triggered. Whether the cloud issues instructions to freeze current data or extend cache duration according to group data analysis, including:

5. The in-vehicle navigation log real-time capturing method according to claim 4, wherein, Whether a high-risk road section warning is judged, and if yes, the cloud issues instructions to freeze current data or extend cache duration. The ring buffer is a data structure of first-in-first-out, a writing pointer returns to the beginning after reaching the end, old data is covered, and storage space utilization is optimized through a cyclic cover writing mechanism.

6. The in-vehicle navigation log real-time capturing method according to claim 5, wherein, Further comprising:

7. The in-vehicle navigation log real-time capturing method according to claim 6, wherein, After triggering log cache freezing, an event timestamp is marked, then data is compressed and encrypted and sent to the cloud for analysis. Comprising:

8. A vehicle navigation log real-time capturing system using the capturing method according to any one of claims 1 to 7, characterized by, A data acquisition module, a dynamic ring cache module and a trigger control module; The data acquisition module serves as a perception layer of the system and is used for real-time acquisition of multi-dimensional operation data of positioning, environment perception, vehicle state and user interactive interface influencing navigation from multiple source heterogeneous devices; The dynamic ring cache module serves as a storage layer of the system and is used for setting a ring buffer, adopting a ring queue structure to continuously record navigation data in the last 30 minutes, and optimizing storage space utilization through a cyclic cover writing mechanism; The trigger control module serves as a decision layer of the system and is used for setting a three-layer triggering mechanism of users, systems and clouds, and triggering log saving based on user buttons or voice instructions, system dynamic thresholds and cloud instructions. ​ When the vehicle is running normally, the data acquisition module obtains new data, and the dynamic ring buffer module continuously covers the old data with the new data. When the trigger control module detects a high-priority event or the user actively triggers, the current buffer is frozen and the key data is locked, ensuring that the complete context information before and after the fault occurs is not covered, forming a closed-loop process of data acquisition, buffer storage, and trigger control.

9. The in-vehicle navigation log real-time capturing system of claim 8, wherein, The data acquisition module includes: A positioning data acquisition unit for acquiring positioning data from a GPS / Beidou receiver and an inertial navigation system in real time; A sensor data fusion unit for acquiring vehicle state and environment perception from a camera, millimeter wave radar, vehicle speed sensor, and steering wheel rotation sensor in real time; A navigation logic data capture unit for acquiring path rule engine decision logs and map version and update status; An environment and network state unit for monitoring vehicle surrounding electromagnetic interference and mobile communication signal; A user interaction data recording unit for recording physical key trigger logs and voice instruction logs.

10. The in-vehicle navigation log real-time capturing system of claim 9, wherein, The trigger control module includes: A user trigger module for triggering the saving of current data when receiving user physical key or voice instruction; A system trigger module for automatically triggering log recording when the set dynamic threshold has met the condition; A cloud trigger module for issuing instructions to control the dynamic ring buffer module to freeze the current data or extend the buffer duration when the vehicle is in a high-risk warning state based on group data analysis.

Images