Driving data analysis method and device, electronic equipment, storage medium and program product

Abstract

The embodiment of the invention discloses a driving data analysis method and device, equipment and a medium. The method comprises the following steps: sending an access request to a successfully connected vehicle terminal, and receiving a key seed returned by the vehicle terminal based on the access request; generating a corresponding secret key based on the secret key seed, and sending a downloading request of driving data to the vehicle terminal after the secret key passes verification of the vehicle terminal; if the downloading of the driving data is completed and the data is normal, analyzing the driving data to obtain a corresponding analysis result; and determining corresponding working condition information and environment state information of the vehicle when the risk event occurs based on an analysis result. According to the embodiment of the invention, the corresponding working condition information and environment information of the vehicle when the risk event occurs can be accurately obtained, and powerful support is provided for subsequently improving the safety and reliability of the automatic driving technology.

Description

Technical Field

[0001] The present application relates to the field of data analysis technology, and specifically to a driving data analysis method and device, an electronic device, a computer-readable storage medium, and a computer program product. Background Art

[0002] With the rapid development of intelligent driving technology, automobiles are gradually transforming from traditional mechanized vehicles to highly intelligent mobile terminals. In recent years, autonomous driving systems, centered on deep learning, high-precision sensor fusion, and vehicle-road collaboration, have achieved significant breakthroughs in key areas such as environmental perception, path planning, and decision-making and control. However, the large-scale implementation of intelligent driving systems still faces significant challenges. On the one hand, autonomous vehicles continuously generate massive amounts of structured and unstructured data through multimodal sensors such as cameras, LiDAR, millimeter-wave radar, and inertial navigation systems. On the other hand, how to efficiently extract high-value information from this heterogeneous data. For example, after a vehicle activates autonomous driving and triggers a risk event such as a collision or collision risk, how to obtain the vehicle's driving data and analyze the corresponding risk data to determine the cause of the risk event remains a pressing technical challenge. Summary of the Invention

[0003] To solve the above technical problems, embodiments of the present application provide a driving data analysis method and device, an electronic device, a computer-readable storage medium, and a computer program product.

[0004] According to one aspect of an embodiment of the present application, a driving data parsing method is provided, comprising: sending an access request to a successfully connected vehicle terminal, and receiving a key seed returned by the vehicle terminal based on the access request; generating a corresponding key based on the key seed, and after the key passes verification by the vehicle terminal, sending a driving data download request to the vehicle terminal; if the driving data download is complete and the data is normal, parsing the driving data to obtain a corresponding parsing result; and determining the corresponding operating condition information and environmental status information of the vehicle when a risk event occurs based on the parsing result.

[0005] According to one aspect of an embodiment of the present application, the driving data includes risk event data, and the method further includes: sending a risk event data download request to the vehicle terminal to determine the associated file corresponding to the risk event data through the vehicle terminal; if the information indicating that the associated file generation is completed is received from the vehicle terminal, the associated file is downloaded.

[0006] According to one aspect of an embodiment of the present application, the associated file includes a time period file, and the method further includes: determining the storage address of the time period file in the vehicle terminal, and sending a download request for the time period file to the vehicle terminal based on the storage address; if the information indicating that the time period file generation is completed is received from the vehicle terminal, the time period file is downloaded.

[0007] According to one aspect of an embodiment of the present application, the time period file includes at least one timestamp file, and the method further includes: sending a timestamp file download request to the vehicle terminal, the timestamp file download request including the start time and end time corresponding to the timestamp of the timestamp file; generating a corresponding timestamp file based on the start time and the end time by the vehicle terminal; if the timestamp file generation completion information returned by the vehicle terminal is received, the timestamp file is downloaded.

[0008] According to one aspect of an embodiment of the present application, the associated file also includes a video file, and the method also includes: sending a directory browsing request to the vehicle terminal, the directory including a directory of event data stored by the vehicle terminal; receiving the event data directory returned by the vehicle terminal, and displaying the event data directory on a target page; selecting a target video from a video list corresponding to the event data directory displayed on the target page based on the risk event data, and downloading the target video.

[0009] According to one aspect of an embodiment of the present application, the driving data includes a timestamp file and a target video, and the method further includes: parsing the timestamp file and the target video in time sequence to obtain a parsing result; performing risk detection based on the parsing result to determine the operating condition information and environmental status information corresponding to the vehicle when a risk event occurs based on the detection result.

[0010] According to one aspect of an embodiment of the present application, the method further includes: if it is detected that the driving data download is complete, obtaining the driving data to generate a corresponding local verification value; obtaining the original verification value corresponding to the driving data from the vehicle terminal; if the local verification value matches the original verification value, determining that the driving data download is complete and normal.

[0011] According to one aspect of an embodiment of the present application, a driving data parsing device is provided, which includes: a sending module for sending an access request to a successfully connected vehicle terminal and receiving a key seed returned by the vehicle terminal based on the access request; a downloading module for generating a corresponding key based on the key seed and sending a download request for driving data to the vehicle terminal after the key is verified by the vehicle terminal; a parsing module for parsing the driving data to obtain a corresponding parsing result if the driving data download is complete and the data is normal; and a determination module for determining, based on the parsing result, the corresponding operating condition information and environmental status information of the vehicle when a risk event occurs.

[0012] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device implements the driving data analysis method as described above.

[0013] According to one aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a computer, the computer executes the driving data analysis method as described above.

[0014] According to one aspect of an embodiment of the present application, a computer program product is further provided, including a computer program, which implements the steps in the driving data analysis method described above when executed by a processor.

[0015] In the technical solution provided in the embodiments of the present application, after successfully connecting to the vehicle terminal, a secure authentication mechanism is established by sending an access request and receiving a key seed returned by the vehicle terminal, ensuring that only authorized devices or systems can access the vehicle terminal, thereby effectively preventing unauthorized access and data leakage. Afterwards, by verifying whether the data download is complete and the data is normal, the integrity and reliability of the data are further guaranteed, and by parsing the downloaded data, the corresponding operating condition information and environmental information of the vehicle when a risk event occurs can be accurately obtained, providing strong support for the subsequent improvement of the safety and reliability of autonomous driving technology.

[0016] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are incorporated into and constitute a part of the specification, illustrating embodiments consistent with the present application and, together with the specification, serving to explain the principles of the present application. It is obvious that the drawings described below are merely some embodiments of the present application, and a person of ordinary skill in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0018] Figure 1 is a schematic diagram of an implementation environment for driving data analysis according to an exemplary embodiment of the present application;

[0019] Figure 2 is a flowchart of a driving data analysis method shown in an exemplary embodiment of the present application;

[0020] Figure 3 is a flowchart of a driving data analysis method shown in another exemplary embodiment of the present application;

[0021] Figure 4 is a flowchart of a driving data analysis method shown in another exemplary embodiment of the present application;

[0022] Figure 5 is a flowchart of a driving data analysis method shown in another exemplary embodiment of the present application;

[0023] Figure 6 is a flowchart of a driving data analysis method shown in another exemplary embodiment of the present application;

[0024] Figure 7 is a flowchart of a driving data analysis method shown in another exemplary embodiment of the present application;

[0025] Figure 8 is a flowchart of a driving data analysis method shown in another exemplary embodiment of the present application;

[0026] Figure 9 This is a schematic diagram of a brief process for parsing driving data in a navigation interface in an exemplary application scenario;

[0027] Figure 10 is a block diagram of a driving data analysis device shown in an exemplary embodiment of the present application;

[0028] Figure 11 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0029] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different figures represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0030] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0031] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0032] In this application, "plurality" refers to two or more. "And / or" describes the relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.

[0033] Automated driving systems use a variety of sensors (such as lidar, cameras, millimeter-wave radar, ultrasonic sensors, inertial measurement units (IMUs), and GPS) to collect real-time information about the surrounding environment, including distance, speed, location, road signs, traffic signals, other vehicles, pedestrians, and obstacles. Based on the current vehicle state, destination information, and environmental perception, the automated driving system uses advanced algorithms to plan a route and make decisions in different scenarios, such as avoiding obstacles, complying with traffic regulations, changing lanes, stopping, or accelerating. These decisions are then translated into specific vehicle action commands, which are transmitted via the electronic control system to the vehicle's powertrain, braking system, steering system, and other auxiliary equipment, ensuring the vehicle follows the predetermined route and strategy.

[0034] During autonomous driving, autonomous vehicles rely on a variety of sensors (such as cameras, radar, and lidar) to perceive their surroundings. If a sensor malfunctions, the vehicle may not accurately acquire surrounding information, leading to erroneous decisions. Alternatively, in complex or unusual situations, the autonomous driving system may not accurately identify objects or predict the behavior of other road users, potentially causing accidents. For example, in environments such as direct sunlight or low-contrast roads, the visual system's object recognition accuracy may decline, potentially triggering collision avoidance or collision events. Once autonomous driving is engaged, the vehicle automatically saves various aspects of its current vehicle status and video if a collision or collision risk event is triggered. For example, if a pedestrian suddenly appears close to the vehicle during autonomous driving, triggering a collision risk, the vehicle will record dozens of data items, including current speed, accelerator pedal position, brake position, radar parameters, and turn signal status. Furthermore, by analyzing the driving data corresponding to the triggering of risk events during autonomous driving, the reliability and safety of subsequent autonomous driving can be strongly supported.

[0035] Figure 1 FIG. 1 is a schematic diagram of an implementation environment for obtaining and analyzing vehicle driving data according to an exemplary embodiment of the present application. Figure 1 As shown, after the vehicle activates autonomous driving, the vehicle terminal 110 automatically saves the vehicle's driving data. This driving data includes dozens of items such as the vehicle's current speed, accelerator pedal opening, brake opening, and turn signal status. If the vehicle's driving data needs to be parsed, the server 120 connects to the vehicle terminal 110 using the corresponding address information and identity information. After the connection is successful, the server 120 issues an access request to the vehicle terminal 110 and receives a key seed from the vehicle terminal 110. The server 120 generates a corresponding key based on the key seed. After the key is verified by the vehicle terminal 110, the server 120 requests the vehicle terminal 110 to download the driving data. Once the driving data download is complete and the data is normal, the server 120 parses the driving data to obtain the corresponding parsing results. The parsing results can then be used to determine the vehicle's operating condition and environmental status at the time of the risk event. This allows for parsing the vehicle's driving data, providing strong support for subsequent autonomous driving.

[0036] in, Figure 1 The vehicle terminal 110 shown can be any terminal device that supports the installation of navigation map software, such as a smart phone, an in-vehicle computer, a tablet computer, a laptop computer, or a wearable device, but is not limited thereto. Figure 1The server side 120 shown can be, for example, an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms, and there is no limitation here. The vehicle terminal 110 can communicate with the server side 120 through wireless networks such as 3G (third generation mobile information technology), 4G (fourth generation mobile information technology), and 5G (fifth generation mobile information technology), and there is no limitation here.

[0037] In actual application, the large-scale implementation of intelligent driving systems still faces severe challenges: on the one hand, autonomous vehicles continuously generate massive amounts of structured and unstructured data through multimodal sensors such as cameras, laser radar (LiDAR), millimeter-wave radar and inertial navigation systems; on the other hand, how to efficiently extract high-value information from these heterogeneous data. For example, after the vehicle starts automatic driving, if the vehicle triggers a risk event such as a collision or collision risk, how to obtain the vehicle's driving data and analyze the risk data corresponding to the risk event to obtain the cause of the risk event is a technical problem that needs to be solved urgently.

[0038] The above-mentioned issues are generally applicable to general intelligent driving systems. To address these issues, the present application provides a driving data analysis method, a driving data analysis device, an electronic device, a computer-readable storage medium, and a computer program product, which are described in detail below.

[0039] See also Figure 2 , Figure 2 This is a flowchart of a driving data analysis method shown in an exemplary embodiment of the present application. This method can be applied to Figure 1 The implementation environment shown is specifically executed by the server 120 in the implementation environment. It should be understood that the method can also be applied to other exemplary implementation environments and specifically executed by devices in other implementation environments. This embodiment does not limit the implementation environment to which the method is applicable.

[0040] Exemplarily, in the implementation environment applicable to the driving data parsing method disclosed in this embodiment, the industry-standard UDS diagnostic protocol (Unified Diagnostic Services UDS) can be used as a diagnostic protocol, wherein the UDS protocol is a defined automotive diagnostic communication protocol used for the diagnosis, debugging, programming and maintenance of automotive electronic control units (Engine Control Unit ECUs). Through the UDS protocol, external diagnostic equipment can communicate with each ECU of the vehicle to obtain the vehicle's status information and fault information, thereby realizing the diagnosis and maintenance of the vehicle, wherein the DOIP protocol (Diagnostic Communication over Internet Protocol) is a diagnostic communication technology based on the Internet protocol, which is mainly used to realize remote diagnosis and data transmission between devices. Exemplarily, the UDS diagnostic instructions sent to the vehicle terminal are packaged into data frames in DOIP format, and then the data frames of the DOIP protocol returned by the vehicle terminal are parsed into UDS instructions.

[0041] like Figure 2 As shown, in an exemplary embodiment, the driving data analysis method includes at least steps S210 to S240, which are described in detail as follows:

[0042] Step S210: Send an access request to the successfully connected vehicle terminal, and receive a key seed returned by the vehicle terminal based on the access request.

[0043] Exemplarily, a communication connection can be established with the vehicle terminal through the vehicle terminal's IP address, logical address, port number, and communication protocol. After a successful connection, a security access service request is sent to the vehicle terminal, wherein the request can carry a specific identifier that indicates the security level of the request. After the vehicle terminal receives the security access service request, a key seed is randomly generated and returned through the corresponding message, wherein the key seed can be generated based on a random number generator inside the ECU in the vehicle terminal.

[0044] Optionally, in some feasible embodiments, the request sender sends a connection request to the vehicle terminal, and the request includes necessary authentication information (such as user name, password, certificate, etc.). The connection request can be sent through a specified communication protocol and port. After receiving the connection request, the vehicle terminal verifies the authentication information in the request. If the authentication is successful, the vehicle terminal sends a connection confirmation response to the request sender. The two parties establish a communication session based on the connection confirmation response, at which point data transmission can begin. The request sender sends an access request to the vehicle terminal, where the access request should be encapsulated using the communication protocol and format agreed upon by both parties (such as the DOIP data frame format). After receiving the access request, the vehicle terminal parses the parameters in the request and, based on the request type, performs the corresponding operation (such as reading vehicle information, executing control commands, etc.). During the execution of the operation, the vehicle terminal generates a key seed, encapsulates the generated key seed into a response message, and sends it using the communication protocol and format agreed upon by both parties. The response message should include the value of the key seed and necessary verification information (such as a signature, timestamp, etc.).

[0045] In step S220 , a corresponding key is generated based on the key seed, and after the key is verified by the vehicle terminal, a download request for the driving data is sent to the vehicle terminal.

[0046] For example, ensure that the key seed has been successfully received from the vehicle terminal and that the seed has been verified to confirm its authenticity and integrity. Then, use the agreed key generation algorithm to generate the corresponding key based on the key seed. The generated key is then sent to the vehicle terminal through a secure communication channel, so that the vehicle terminal will use the same key generation algorithm and key seed to generate a local key and compare it with the received key. If the verification is successful, the requester will be granted permission to proceed with subsequent operations. The requester prepares a download request for the driving data as required. The request should include necessary information such as data type, version, and request time. The requester waits for the vehicle terminal to respond to the download request. The vehicle terminal will prepare the corresponding driving data according to the request.

[0047] Step S230: If the driving data download is complete and the data is normal, the driving data is analyzed to obtain a corresponding analysis result.

[0048] For example, after receiving a download request, the vehicle terminal downloads driving data from the specified data source based on the information in the request. After the download is complete, the vehicle terminal performs a preliminary check of the data to ensure its integrity and accuracy. This typically includes verifying the data's checksum, checking the correct format, and confirming that the data contains the expected content. If the data is deemed "normal," meaning it is free of corruption, loss, or obvious errors, further processing is possible. Once the data is confirmed to be normal, the vehicle terminal begins parsing the data.

[0049] The parsing process may involve a variety of technologies and algorithms, such as data cleaning (removing noise, outliers, etc.), data conversion (such as converting raw sensor data into an environmental model that can be understood by the vehicle), feature extraction (extracting key information that is useful for autonomous driving decisions), etc.

[0050] The results of the analysis may include a detailed map of the vehicle's surroundings, the location and speed of obstacles, planning suggestions for driving paths, decision support in emergency situations, etc.

[0051] These analytical results are the basis for the autonomous driving system to make decisions and control vehicle driving, and are crucial to ensuring the safety and efficiency of autonomous driving.

[0052] Step S240: Determine the vehicle's operating condition information and environmental status information corresponding to the risk event when the risk event occurs based on the analysis result.

[0053] For example, the autonomous driving system will conduct an in-depth analysis of the analysis results. The analysis results typically include detailed information about the vehicle's surroundings, such as road conditions, the location and speed of other traffic participants, and weather conditions. Once a risk event is identified, the autonomous driving system will immediately analyze the vehicle's current operating conditions. This operating condition information may include the vehicle's speed, acceleration, steering angle, braking status, etc. This information is crucial for understanding the vehicle's dynamic behavior when the risk event occurs. Furthermore, detailed environmental status information at the time of the risk event can be recorded. This environmental status information may include weather conditions (such as rain, snow, fog), road type (such as highways, urban roads), traffic density, lighting conditions, etc. This information helps the autonomous driving system more comprehensively understand the context and potential impact of the risk event. Furthermore, the autonomous driving system will record the risk event and its related operating condition and environmental status information for subsequent analysis and improvement. These records can be used for accident investigation, system optimization, or as training data to improve autonomous driving algorithms.

[0054] In some embodiments of the application, after successfully connecting to the vehicle terminal, a secure authentication mechanism is established by sending an access request and receiving a key seed returned by the vehicle terminal, ensuring that only authorized devices or systems can access the vehicle terminal, thereby effectively preventing unauthorized access and data leakage. Afterwards, by verifying whether the data download is complete and the data is normal, the integrity and reliability of the data are further guaranteed, and by parsing the downloaded data, the corresponding operating condition information and environmental information of the vehicle when a risk event occurs can be accurately obtained, providing strong support for the subsequent improvement of the safety and reliability of autonomous driving technology.

[0055] Based on the above examples, see Figure 3In one of the exemplary embodiments provided in this application, the driving data includes risk event data. The specific implementation process of the driving data analysis method may further include steps S310 and S320, which are described in detail as follows:

[0056] Step S310: Sending a risk event data download request to the vehicle terminal to determine the associated file corresponding to the risk event data through the vehicle terminal;

[0057] Step S320: If the vehicle terminal receives information indicating that the associated file generation is complete, the associated file is downloaded.

[0058] Exemplarily, a request to download risk event data is sent to a vehicle terminal. The request should include necessary information, such as the risk event type, time and location of occurrence, and a description of the required associated files (e.g., file format, content type, etc.). The request is sent via a secure communication protocol (e.g., DOIP) to ensure the confidentiality and integrity of data during transmission. Upon receiving the download request, the vehicle terminal determines the associated files corresponding to the risk event data based on the information in the request. Associated files may include video, images, sensor data, log information, etc. recorded by the vehicle at the time of the risk event. The vehicle terminal then checks the availability of these files and ensures that they match the risk event data in the request. Once the vehicle terminal determines the associated files and that they are ready for download, it generates a response indicating that the associated files have been prepared and can be accessed via a specified download link or identifier. Furthermore, this response may include detailed information, such as the download link, file size, and checksum, to ensure that the requester can correctly download and verify the associated files. Upon receiving the response from the vehicle terminal indicating that the associated files have been prepared, the requester begins downloading the associated files.

[0059] The download process is usually carried out through a secure communication protocol (such as the DOIP protocol) to ensure the integrity and confidentiality of the file. The requester may verify the checksum or signature of the downloaded file to ensure that the file has not been tampered with or damaged during transmission. After the download is complete, the requester will process and analyze the associated files. This may include reviewing videos or images to understand the specific circumstances of the risk event, analyzing sensor data to understand the dynamic behavior of the vehicle, and reviewing log information to understand the system's response. By analyzing the associated files, a deeper understanding of the causes and impacts of risk events can be achieved, and improvement suggestions can be provided for future autonomous driving decisions.

[0060] In one embodiment of the present application, the accuracy and integrity of risk event data can be ensured by using a vehicle terminal to determine the associated files corresponding to risk event data. As a direct source of data, the vehicle terminal can more accurately identify and extract data files related to risk events. The downloaded associated files provide rich material for subsequent risk data analysis and mining. Through in-depth analysis of this data, patterns, trends, and potential issues in vehicle operation can be discovered. The data analysis results can provide strong support for vehicle improvement, maintenance, and safety management.

[0061] Based on the above examples, please refer to Figure 4 In one of the exemplary embodiments provided in this application, the associated file includes a time period file. The specific implementation process of the driving data parsing method may further include steps S410 and S420, which are described in detail as follows:

[0062] Step S410, determining the storage address of the time period file in the vehicle terminal, and sending a download request for the time period file to the vehicle terminal based on the storage address;

[0063] Step S420: If the vehicle terminal receives information indicating that the time period file generation is complete, the time period file is downloaded.

[0064] For example, it is necessary to determine the specific storage address of the time period file to be downloaded within the vehicle terminal. This address may be a path based on a file management system or protocol (such as FTP or HTTP). Determining the storage address may involve communicating with the vehicle terminal to query or confirm the file's storage location. Once the file's storage address is determined, a download request is sent to the vehicle terminal based on this address. The download request typically includes the file's storage address, the requester's identity information (such as IP address, authentication credentials, etc.), and possibly other parameters (such as download priority, file format requirements, etc.). After sending the download request, it is necessary to wait for the vehicle terminal's response. In this scenario, the "time period file generation completed" message returned by the vehicle terminal is of particular interest. This indicates that the vehicle terminal is ready to provide the required file and that the file has been generated or organized and is available for download. Once the file generation completion message is received from the vehicle terminal, the time period file download can begin. The download process may involve establishing a stable communication connection with the vehicle terminal to ensure the integrity and security of the data transmission. After the download is complete, the file can be saved to the local system or a designated storage location for subsequent use or processing.

[0065] Optionally, in some feasible embodiments, the vehicle terminal stores multiple time period files, wherein the time period files can be named according to the time sequence number. Therefore, by sending the time sequence number corresponding to the time period information as the storage address, it is possible to query whether the time sequence number in the vehicle terminal exceeds the maximum time sequence number in the vehicle terminal. If it is judged as no, the vehicle terminal generates the corresponding time period file and returns the information that the time period file generation is completed so that the time period file can be downloaded.

[0066] In some embodiments of the present application, through a clear storage address and download request mechanism, it can be ensured that only authorized users or systems can access and download time period files, thereby enhancing the security of data transmission. Determining the storage address of the time period file helps to better plan and manage the storage space of the vehicle terminal, avoiding waste and fragmentation of storage space, and the downloaded time period file can provide basic data for subsequent data analysis and mining, and can provide strong support for the analysis of the vehicle driving process.

[0067] Based on the above examples, please refer to Figure 5 In one of the exemplary embodiments provided in this application, the time period file includes at least one timestamp file. The specific implementation process of the driving data parsing method may further include steps S510 to S530, which are described in detail as follows:

[0068] Step S510: Send a timestamp file download request to the vehicle terminal, where the timestamp file download request includes a start time and an end time corresponding to the timestamp of the timestamp file;

[0069] Step S520, generating a corresponding timestamp file based on the start time and the end time by the vehicle terminal;

[0070] Step S530: If the vehicle terminal receives information indicating that the timestamp file has been generated, the timestamp file is downloaded.

[0071] For example, a timestamp file download request is sent to a vehicle terminal. This request contains two key time parameters, the start time and end time of the timestamp file. These two time parameters define the coverage of the timestamp file that the requester wants to obtain. After receiving the request, the vehicle terminal generates a corresponding timestamp file based on its internal data records or logs and the start time and end time provided in the request.

[0072] A timestamp file typically contains a record of all relevant events or operations that occurred during that time period, each with a precise timestamp. Once the timestamp file is generated, the vehicle terminal sends a notification to the requester, indicating that the file is ready for download. Upon receiving the notification from the vehicle terminal, the requester initiates the download process. The timestamp file download process may involve establishing a secure connection, verifying the file's integrity, and saving the file to local storage.

[0073] Optionally, by downloading a timestamp file for a specific time period, you can analyze the vehicle's operating status during that time period to help diagnose faults. This method can be used to conveniently obtain data for the required time period for vehicle data that requires regular audits. By monitoring vehicle behavior at different time periods, potential safety risks or abnormal behavior can be identified.

[0074] Optionally, in some feasible embodiments, the vehicle terminal stores multiple time period files, wherein the time period files can be named according to the time sequence number. Therefore, by sending the time sequence number corresponding to the time period information as the storage address, it is possible to query whether the time sequence number in the vehicle terminal exceeds the maximum time sequence number in the vehicle terminal. If it is judged to be yes, the associated file corresponding to the time period file is determined, wherein the associated file includes multiple timestamp files. The vehicle terminal generates the multiple timestamp files and returns the generation completion information to realize the download of the multiple timestamp files.

[0075] In some embodiments of this application, by specifying a start and end time, relevant data recorded by vehicle terminals during that time period can be accurately extracted and a timestamp file generated. This precise data extraction method avoids processing large amounts of irrelevant data, improving data processing efficiency and accuracy. The timestamp file provides foundational data for subsequent data analysis and mining. By conducting in-depth analysis of data within a specific time period, temporal patterns, trends, and potential issues in vehicle operation can be revealed, providing support for decision-making.

[0076] Further, based on the above embodiment, please refer to Figure 6 In one of the exemplary embodiments provided in this application, the associated file further includes a video file. The specific implementation process of the driving data analysis method may further include steps S610 to S630, which are described in detail as follows:

[0077] Step S610, sending a directory browsing request to the vehicle terminal, wherein the directory includes a directory of event data stored in the vehicle terminal;

[0078] Step S620: receiving the event data directory returned by the vehicle terminal and displaying the event data directory on the target page;

[0079] Step S630: Select a target video from a video list corresponding to the event data directory displayed on the target page based on the risk event data, and download the target video.

[0080] Exemplarily, a directory browsing request is sent to the vehicle terminal. The purpose of this request is to obtain the directory of event data stored in the vehicle terminal, that is, a list or structure of all available event data on the vehicle terminal. After receiving the request, the vehicle terminal will return the directory of event data stored in it. After receiving this directory, it will be displayed on the target page. The target page may be a user interface, a management console, or any interface that can display information. The event data directory may include information such as the name, timestamp, type, size, etc. of the event, so that users can identify and select the events they are interested in. In the event data directory displayed on the target page, they can select the target video they are interested in from the video list based on risk event data or other filtering conditions. The risk event data may be a predefined standard or condition used to identify which events or videos are important or require special attention. Once the user selects the target video, the requester will start the download process.

[0081] In addition, the download process may involve establishing a connection with the vehicle terminal, verifying the availability of the video, transmitting the video data to local storage, etc., which will not be described in detail in this embodiment. After the download is completed, the video can be viewed, analyzed or saved locally.

[0082] Optionally, in some feasible embodiments, downloading the target video file from the vehicle terminal may be used in a variety of scenarios in actual applications, for example: by browsing and downloading the video data stored in the vehicle terminal, the accident scene can be restored to help investigate the cause of the accident; regularly browsing and downloading video data can monitor the operating status of the vehicle, and potential safety risks can be discovered and handled in a timely manner; by analyzing the video data during driving, the driver's driving behavior can be evaluated, and driving training or improvement suggestions can be provided.

[0083] In some embodiments of the present application, by sending a directory browsing request to the vehicle terminal, the user can easily obtain the event data directory stored in the vehicle terminal, which makes the data more visual. The user can intuitively see all available event data and display the event data directory on the target page. The user can access this data anytime and anywhere through the network, which improves the accessibility of the data. The downloaded target video can provide strong evidence for subsequent data analysis and event investigation. Through in-depth analysis of the video, the detailed process of the risk event can be revealed, providing a basis for decision-making and improvement.

[0084] Based on the above examples, please refer to Figure 7 In one of the exemplary embodiments provided in this application, the driving data includes a timestamp file and a target video. The specific implementation process of the driving data parsing method may further include steps S710 and S720, which are described in detail as follows:

[0085] Step S710, parsing the timestamp file and the target video in time sequence to obtain a parsing result;

[0086] Step S720 : performing risk detection based on the analysis result to determine the vehicle's corresponding operating condition information and environmental status information when the risk event occurs based on the detection result.

[0087] Exemplarily, the driving data obtained from the vehicle terminal also includes a timestamp file and a target video file recorded during the vehicle's driving process. Therefore, the timestamp file and the target video file downloaded from the vehicle terminal can be parsed according to a temporal relationship. The temporal relationship is essentially parsed based on the target video file with the same timestamp as the timestamp file. For example, vehicle operating data such as the throttle opening value, vehicle speed, brake opening, radar parameters, and turn signal status in the timestamp file can be parsed. Then, the video information in the target video file with the same timestamp can be parsed, such as the surrounding vehicle status, traffic status, and the presence of pedestrians, to obtain the corresponding parsing results. Subsequently, based on the parsing results, risk events can be identified, such as vehicle collisions and pedestrians crossing the road in the target video. The vehicle's operating condition information at the time of the risk event, such as vehicle speed, acceleration, and steering angle, can be extracted. Environmental information such as weather conditions, road conditions, and traffic density can also be extracted.

[0088] In addition, in some feasible embodiments, the vehicle's intelligent driving strategy can be improved or optimized by extracting operating condition information and environmental information when a risk event occurs, which helps to improve the accuracy and reliability of the intelligent driving system and provide better support for future autonomous driving applications.

[0089] In some embodiments of the present application, by parsing the timestamp file and the target video in chronological order, the specific moment when the risk event occurs can be accurately located. The timestamp file provides an accurate time record of the event, while the target video displays the actual scene of the event through visual information. This precise positioning capability helps in subsequent risk analysis and responsibility definition, ensuring that risk events are properly handled.

[0090] Based on the above examples, please refer to Figure 8In one of the exemplary embodiments provided in this application, the specific implementation process of the driving data analysis method may further include steps S810 to S830, which are described in detail as follows:

[0091] Step S810: If it is detected that the driving data download is complete, a corresponding local check value is generated based on the driving data;

[0092] Step S820, obtaining an original verification value corresponding to the driving data from the vehicle terminal;

[0093] In step S830, if the local verification value matches the original verification value, it is determined that the driving data download is complete and normal.

[0094] For example, if the download of driving data from the vehicle terminal is detected to be complete, a corresponding local checksum can be generated based on the driving data. The local checksum can be a hash value or an ASCII code. For example, if the local checksum is a hash value, once the data download is complete, the system will hash the downloaded driving data using a hash algorithm (such as SHA-256 or MD5). The hash algorithm generates a fixed-length hash value, which can be considered a "fingerprint" of the data. Even small changes to the data will result in a significant change in the hash value. This generated hash value is the local checksum. The original checksum corresponding to the downloaded driving data is then obtained from the vehicle terminal. The original checksum is calculated using the same hash algorithm when the data was generated or uploaded and is stored and transmitted as part of the data integrity. The local checksum is then compared with the original checksum. If the two match, it indicates that the downloaded driving data has not been modified during transmission and is complete. If the two do not match, it may mean that the data has been tampered with, corrupted, or downloaded incompletely during transmission, and appropriate measures must be taken, such as re-downloading the data or reporting an error.

[0095] Furthermore, if the checksum matches, the driving data download is confirmed to be complete and normal. The system can then further process this data, such as analyzing it to determine the vehicle's operating conditions and the environment in which it was located when the risk event occurred.

[0096] In some embodiments of the present application, by generating a local check value and comparing it with the original check value provided by the vehicle terminal, it can be verified whether the downloaded driving data remains intact during the transmission process and is not lost or damaged. The check value mechanism can prevent the data from being tampered with or forged to a certain extent. If the data is tampered with during the transmission process, the locally generated check value will not match the original check value provided by the vehicle terminal, so that this security risk can be discovered and dealt with in a timely manner.

[0097] Figure 9This is a brief flowchart of driving data analysis in an exemplary application scenario. Figure 9 In the illustrated application scenario, the server sends a connection request carrying address information to the vehicle terminal. The vehicle terminal returns a key seed based on the connection request. The server generates a corresponding key based on the key seed and sends it to the vehicle terminal. The vehicle terminal verifies the key sent by the server and, if successful, sends a verification success message to the server. The server then sends a download request for driving data to the vehicle terminal. This download request may include a download request for a time period file. The time period file may consist of multiple timestamp files. The vehicle terminal can then generate a corresponding timestamp file based on the start and end times of the timestamp files for the server to download. Alternatively, the server can also send a directory browse request to the vehicle terminal, including a directory of event data stored by the vehicle terminal. The server receives the event data directory returned by the vehicle terminal and displays the event data directory on a target page. Based on the risk event data, the server selects a target video from a video list corresponding to the event data directory displayed on the target page and downloads the target video. The server parses the timestamp file and the target video in chronological order to obtain a parsing result. Based on the parsing result, the server performs risk detection to determine the vehicle's operating condition and environmental status information corresponding to the risk event. For the detailed implementation process, please refer to the description in the aforementioned embodiments, which will not be described in detail here.

[0098] Figure 10 This is a block diagram of a driving data device according to an exemplary embodiment of the present application. Figure 1 The implementation environment shown is specifically configured in the server 120. The apparatus may also be applicable to other exemplary implementation environments and specifically configured in other devices. This embodiment does not limit the implementation environment to which the apparatus is applicable.

[0099] like Figure 10 As shown, the exemplary driving data device includes: a sending module 1010, which is used to send an access request to a successfully connected vehicle terminal and receive a key seed returned by the vehicle terminal based on the access request; a downloading module 1020, which is used to generate a corresponding key based on the key seed, and after the key is verified by the vehicle terminal, send a download request for driving data to the vehicle terminal; a parsing module 1030, which is used to parse the driving data to obtain a corresponding parsing result if the driving data download is completed and the data is normal; and a determining module 1040, which is used to determine the corresponding operating condition information and environmental status information of the vehicle when a risk event occurs based on the parsing result.

[0100] According to one aspect of an embodiment of the present application, the above-mentioned download module 1020 also includes: sending a risk event data download request to the vehicle terminal to determine the associated file corresponding to the risk event data through the vehicle terminal; if the information indicating that the associated file generation is completed is received from the vehicle terminal, the associated file is downloaded.

[0101] According to one aspect of an embodiment of the present application, the above-mentioned download module 1020 also includes: determining the storage address of the time period file in the vehicle terminal, and sending a download request for the time period file to the vehicle terminal based on the storage address; if the information indicating that the time period file generation is completed is received from the vehicle terminal, the time period file is downloaded.

[0102] According to one aspect of an embodiment of the present application, the above-mentioned download module 1020 also includes: sending a timestamp file download request to the vehicle terminal, the timestamp file download request including the start time and end time corresponding to the timestamp of the timestamp file; generating a corresponding timestamp file based on the start time and end time through the vehicle terminal; if the timestamp file generation completion information is received from the vehicle terminal, the timestamp file is downloaded.

[0103] According to one aspect of an embodiment of the present application, the above-mentioned download module 1020 is also used to send a directory browsing request to the vehicle terminal, where the directory includes a directory of event data stored by the vehicle terminal; receive the event data directory returned by the vehicle terminal, and display the event data directory on the target page; select a target video from the video list corresponding to the event data directory displayed on the target page based on the risk event data, and download the target video.

[0104] According to one aspect of an embodiment of the present application, the above-mentioned parsing module 1030 is also used to parse the timestamp file and the target video in time sequence to obtain a parsing result; perform risk detection based on the parsing result to determine the corresponding operating condition information and environmental status information of the vehicle when a risk event occurs based on the detection result.

[0105] According to one aspect of an embodiment of the present application, the above-mentioned download module 1020 is also used to, if it is detected that the driving data download is completed, generate a corresponding local verification value based on the driving data; obtain the original verification value corresponding to the driving data from the vehicle terminal; if the local verification value matches the original verification value, it is determined that the driving data download is complete and normal.

[0106] It should be noted that the driving data analysis device provided in the above-described embodiments and the driving data analysis method provided in the above-described embodiments share the same concept. The specific manner in which the various modules and units perform their operations has been described in detail in the method embodiments and will not be repeated here. In actual applications, the driving data analysis device provided in the above-described embodiments can, as needed, allocate the aforementioned functions to different functional modules, i.e., divide the internal structure of the device into different functional modules to perform all or part of the aforementioned functions. This is not a limitation herein.

[0107] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device implements the driving data parsing method provided in the above-mentioned embodiments.

[0108] Figure 11 The following is a schematic diagram showing the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application. Figure 11 The computer system 1100 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0109] like Figure 11 As shown, the computer system 1100 includes a central processing unit (CPU) 1101, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1102 or the program loaded from the storage part 1108 to the random access memory (RAM) 1103, such as executing the method described in the above embodiment. Various programs and data required for system operation are also stored in the RAM 1103. The CPU 1101, ROM 1102 and RAM 1103 are connected to each other via a bus 1104. An input / output (I / O) interface 1105 is also connected to the bus 1104.

[0110] The following components are connected to the I / O interface 1105: an input section 1106 including a keyboard, a mouse, and the like; an output section 1107 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 1108 including a hard disk and the like; and a communication section 1109 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to the I / O interface 1105 as needed. Removable media 1111, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 1110 as needed, so that computer programs read therefrom can be installed into the storage section 1108 as needed.

[0111] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 1109, and / or installed from a removable medium 1111. When the computer program is executed by the central processing unit (CPU) 1101, the various functions defined in the system of the present application are executed.

[0112] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable computer program. This propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0113] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0114] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0115] Another aspect of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned driving data parsing method. The computer-readable storage medium may be included in the electronic device described in the above embodiments, or may exist independently and not be incorporated into the electronic device.

[0116] Another aspect of the present application provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the driving data parsing method provided in each of the above embodiments.

[0117] The above content is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation scheme of the present application. Ordinary technicians in this field can easily make corresponding changes or modifications based on the main ideas and spirit of the present application. Therefore, the scope of protection of the present application shall be based on the scope of protection required by the claims.

Claims

1. A driving data analysis method, characterized in that: include: Sending an access request to the successfully connected vehicle terminal, and receiving a key seed returned by the vehicle terminal based on the access request; generating a corresponding key based on the key seed, and sending a download request for driving data to the vehicle terminal after the key is verified by the vehicle terminal; If the driving data is downloaded and the data is normal, the driving data is parsed to obtain a corresponding parsing result; Based on the analysis results, the operating condition information and environmental status information of the vehicle corresponding to the risk event are determined.

2. The method according to claim 1, wherein The driving data includes risk event data, and the method further includes: Sending a risk event data download request to the vehicle terminal, so as to determine, through the vehicle terminal, an associated file corresponding to the risk event data; If the information indicating that the associated file is generated is received from the vehicle terminal, the associated file is downloaded.

3. The method according to claim 2, wherein The associated file includes a time period file, and the method further includes: determining a storage address of the time period file in the vehicle terminal, and sending a download request for the time period file to the vehicle terminal based on the storage address; If the information indicating that the time period file is generated is received from the vehicle terminal, the time period file is downloaded.

4. The method according to claim 3, wherein The time period file includes at least one timestamp file, and the method further includes: Sending a timestamp file download request to the vehicle terminal, wherein the timestamp file download request includes a start time and an end time corresponding to the timestamp of the timestamp file; generating, by the vehicle terminal, a corresponding timestamp file based on the start time and the end time; If the information indicating that the timestamp file generation is complete is received from the vehicle terminal, the timestamp file is downloaded.

5. The method according to claim 2, wherein The associated file also includes a video file, and the method further includes: sending a directory browsing request to the vehicle terminal, the directory including a directory of event data stored by the vehicle terminal; receiving the event data directory returned by the vehicle terminal, and displaying the event data directory on a target page; A target video is selected from a video list corresponding to the event data directory displayed on the target page based on the risk event data, and the target video is downloaded.

6. The method according to claim 1, wherein The driving data includes a timestamp file and a target video, and the method further includes: Parsing the timestamp file and the target video in time sequence to obtain a parsing result; Risk detection is performed based on the analysis result to determine the operating condition information and environmental status information corresponding to the vehicle when the risk event occurs based on the detection result.

7. The method according to claim 1, wherein The method further comprises: If it is detected that the driving data download is complete, generating a corresponding local check value based on the driving data; Obtaining an original verification value corresponding to the driving data from the vehicle terminal; If the local verification value matches the original verification value, it is determined that the driving data download is complete and normal.

8. A driving data analysis device, characterized in that: The device comprises: a sending module, configured to send an access request to a successfully connected vehicle terminal and receive a key seed returned by the vehicle terminal based on the access request; a download module, configured to generate a corresponding key based on the key seed, and send a download request for driving data to the vehicle terminal after the key is verified by the vehicle terminal; An analysis module, configured to analyze the driving data to obtain corresponding analysis results if the driving data download is complete and the data is normal; The determination module is used to determine the operating condition information and environmental status information corresponding to the vehicle when the risk event occurs based on the analysis result.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the electronic device to implement the driving data analysis method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that Computer-readable instructions are stored thereon, and when the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the driving data analysis method according to any one of claims 1 to 7.

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