Method for positioning problem based on intelligent cabin log and related device
Through the Internet of Vehicles platform and prediction model, remote return and problem positioning of smart cockpit logs are realized, solving the problem of difficulty in positioning of smart cockpit problems and improving the efficiency of log acquisition and problem positioning.
Patent Information
- Application Number
- CN202411442791.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-16
- Publication Date
- 2025-02-18
AI Technical Summary
Due to the complex functions and complex logic of smart cockpit products, it is difficult to locate problems, and it is difficult for existing technologies to quickly and accurately locate the problem.
Receive user problem location requests through the Internet of Vehicles platform, use prediction models to predict related functional modules and their log levels, configure log switches and recording rules, and realize remote return and problem location of smart cockpit logs.
It realizes quick and convenient acquisition of system logs, and accurately locates problems based on logs, improving the efficiency of log acquisition and problem location.
Smart Images
Figure CN119479101A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of new energy vehicles, specifically to technical fields such as smart cockpits and log transmission, and in particular to a method and related devices based on the problem of smart cockpit log positioning. Background Art
[0002] With the strong development of new energy vehicles in the country, the development speed of the automobile industry has far exceeded any previous period. As the "face" of the car, every vehicle user will intuitively feel and use the products and functions of the smart cockpit after getting on the car. Therefore, the product strength of the smart cockpit has become the most important factor affecting consumers' first impression of the car. Only by striving to improve the product strength and leading nature of the smart cockpit can we have a first-mover advantage and win a place in such a fierce market competition environment.
[0003] As the functions of smart cockpit products become more and more abundant, the product logic becomes more and more complex, and the development workload increases exponentially. As an embedded vehicle system, smart cockpit products have various possible inducing factors for various problems. It is not only time-consuming and laborious to check the cross-influence of different functions or fields one by one from a design perspective, but also requires high technical capabilities of developers.
[0004] Therefore, it is urgent to find a new problem location and troubleshooting method to solve the problem of difficulty in locating problems in smart cockpits. Summary of the invention
[0005] The present application provides a method and related devices for locating problems based on smart cockpit logs to solve the problem of difficulty in locating problems in the smart cockpit.
[0006] The technical solution is as follows:
[0007] In a first aspect, a method for locating a problem based on an intelligent cockpit log is provided, comprising:
[0008] The Internet of Vehicles platform receives a problem location request sent by a user; the problem location request carries at least one keyword characterizing the problem phenomenon of the smart cockpit;
[0009] The Internet of Vehicles platform predicts the function modules of the smart cockpit related to the current problem location request and their corresponding log levels using a set prediction model based on at least one keyword in the problem location request; wherein the set prediction model is repeatedly trained based on historical problems of the smart cockpit;
[0010] The Internet of Vehicles platform adds the functional module and its corresponding log level to the log configuration information, and forwards the log configuration information to the smart cockpit controller through the vehicle terminal; wherein the log configuration information further includes: recording rules, return address, and user name and password;
[0011] The smart cockpit controller starts the smart cockpit log corresponding to the functional module based on the received log configuration information, and sets the log level;
[0012] After collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs and returns the collected logs to the Internet of Vehicles platform based on the return address, user name and password;
[0013] The Internet of Vehicles platform locates the problem based on the returned logs.
[0014] In a possible implementation, if the Internet of Vehicles platform successfully locates the problem according to the returned log, the method further includes:
[0015] The Internet of Vehicles platform sends log closing information to the smart cockpit controller through the vehicle terminal; wherein the log closing information includes: the function module to be closed, the return address, and the user name and password;
[0016] The smart cockpit controller closes the smart cockpit log corresponding to the functional module based on the received log closing information, and returns the closing result to the Internet of Vehicles platform through the vehicle terminal.
[0017] In a possible implementation, if the Internet of Vehicles platform fuzzily locates the problem according to the returned log, the method further includes:
[0018] The Internet of Vehicles platform selects the initially located functional modules from the predicted functional modules of the smart cockpit based on the result of fuzzy positioning, and increases the log level before the initially located functional modules;
[0019] The Internet of Vehicles platform adds the initially located functional modules and the increased log levels thereof to the log configuration information, and forwards the log configuration information to the smart cockpit controller via the vehicle terminal;
[0020] The smart cockpit controller increases the log level of the smart cockpit log corresponding to the initially located functional module based on the received log configuration information, and closes other functional modules except the initially located functional module; wherein the higher the log level, the more detailed the information recorded;
[0021] After collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs and returns the compressed logs to the Internet of Vehicles platform;
[0022] The Internet of Vehicles platform accurately locates the functional modules that have been initially located based on the returned logs.
[0023] In a possible implementation, the log level before the initially located functional module is increased, including:
[0024] According to the type of the initially located functional module, the log level of the initially located functional module is set to a higher level; or, the previous log level of the initially located functional module is randomly increased.
[0025] In a possible implementation, the method further includes:
[0026] The intelligent cockpit controller periodically cleans up the saved logs according to the local storage capacity.
[0027] In the second aspect, a system based on the smart cockpit log positioning problem is provided, including: a vehicle networking puzzle, a vehicle terminal and a smart cockpit controller; wherein,
[0028] The Internet of Vehicles platform receives a problem location request sent by a user; the problem location request carries at least one keyword characterizing the problem phenomenon of the smart cockpit;
[0029] The Internet of Vehicles platform predicts the function modules of the smart cockpit related to the current problem location request and their corresponding log levels using a set prediction model based on at least one keyword in the problem location request; wherein the set prediction model is repeatedly trained based on historical problems of the smart cockpit;
[0030] The Internet of Vehicles platform adds the functional module and its corresponding log level to the log configuration information, and forwards the log configuration information to the smart cockpit controller through the vehicle terminal; wherein the log configuration information further includes: recording rules, return address, and user name and password;
[0031] The smart cockpit controller starts the smart cockpit log corresponding to the functional module based on the received log configuration information, and sets the log level;
[0032] After collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs and returns the collected logs to the Internet of Vehicles platform based on the return address, user name and password;
[0033] The Internet of Vehicles platform locates the problem based on the returned logs.
[0034] In a third aspect, a computer-readable storage medium is provided, wherein at least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to implement the method of the aspect as described above and any possible implementation method.
[0035] In a fourth aspect, an electronic device is provided, including:
[0036] at least one processor; and
[0037] a memory communicatively connected to the at least one processor; wherein,
[0038] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any possible implementation manner and the aspects described above.
[0039] According to a fifth aspect, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the above-mentioned aspects and any possible implementation method.
[0040] In a sixth aspect, a new energy commercial vehicle is provided, comprising the electronic device as described above.
[0041] The beneficial effects of the technical solution provided by this application include at least:
[0042] It can be seen from the above technical solution that the Internet of Vehicles platform receives a problem location request sent by a user, and based on at least one keyword in the problem location request, uses a set prediction model to predict the functional module of the smart cockpit related to the problem location request and its corresponding log level; then, the functional module and its corresponding log level are added to the log configuration information, and the log configuration information is forwarded to the smart cockpit controller through the vehicle terminal; the smart cockpit controller opens the smart cockpit log corresponding to the functional module based on the received log configuration information, and sets the log level; after collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs, and returns the collected logs to the Internet of Vehicles platform based on the return address as well as the user name and password; the Internet of Vehicles platform locates the problem based on the returned logs. Therefore, through the remote communication technology of the Internet of Vehicles, the system interacts with users and the entire vehicle, and sends functional modules, log levels and other related configurations according to the Internet of Vehicles platform, which are forwarded by the vehicle terminal to the smart cockpit controller to adjust the log switch and recorded content; afterwards, the smart cockpit log is remotely transmitted and the problem is located according to the specified return address provided by the Internet of Vehicles platform. In this way, the expected system logs can be obtained quickly and conveniently, and the problem can be accurately located according to the system logs, which improves the efficiency of log acquisition and problem location.
[0043] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0045] Figure 1 It is a schematic diagram of the steps of a method for locating problems based on intelligent cockpit logs provided by an embodiment of the present application.
[0046] Figure 2 It is a flowchart of the problem of positioning based on the intelligent cockpit log provided in another embodiment of the present application.
[0047] Figure 3 It is a control flow diagram based on the smart cockpit log positioning problem provided by an embodiment of the present application.
[0048] Figure 4It is a structural block diagram of a device for locating problems based on an intelligent cockpit log provided in yet another embodiment of the present application.
[0049] Figure 5 It is a block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION
[0050] The following is a description of exemplary embodiments of the present application in conjunction with the accompanying drawings, including various details of the embodiments of the present application to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description.
[0051] Obviously, the described embodiments are only part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.
[0052] It should be noted that the terminal devices involved in the embodiments of the present application may include but are not limited to mobile phones, personal digital assistants (PDAs), wireless handheld devices, tablet computers and other smart devices; display devices may include but are not limited to personal computers, televisions and other devices with display functions.
[0053] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.
[0054] As the functions of smart cockpit products become more and more abundant, the product logic becomes more and more complex, and the development workload increases exponentially. Moreover, various unknown defects and bugs will still appear in the smart cockpit after the vehicle is delivered. These defects and bugs may be due to the lack of comprehensive testing and verification before leaving the factory, or due to various unexpected usage scenarios caused by user DIY, which leads to frequent maintenance and repair work after the vehicle is delivered. In the field of smart cars, the system log can record the key information of the whole vehicle system. This information can further confirm the operating environment when the problem occurs, which is of great benefit to the analysis and solution of the problem. Developers can quickly and efficiently locate the problem through the log, so as to formulate targeted solutions. However, considering that the system log of the smart cockpit product is only stored locally in the system and is closed after the vehicle is sold, it is difficult for developers to obtain relevant logs to locate the problem.
[0055] In view of this, the present application proposes a solution based on the smart cockpit log location problem, and the inventive concept is that: the Internet of Vehicles platform receives a problem location request sent by a user, and based on at least one keyword in the problem location request, uses a set prediction model to predict the functional modules of the smart cockpit related to this problem location request and their corresponding log levels; then, the functional modules and their corresponding log levels are added to the log configuration information, and the log configuration information is forwarded to the smart cockpit controller through the vehicle-mounted terminal; the smart cockpit controller, based on the received log configuration information, turns on the smart cockpit log corresponding to the functional module and sets the log level; after collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs, and returns the collected logs to the Internet of Vehicles platform based on the return address as well as the user name and password; the Internet of Vehicles platform locates the problem based on the returned logs. Therefore, through the remote communication technology of the Internet of Vehicles, the system interacts with users and the entire vehicle, and sends functional modules, log levels and other related configurations according to the Internet of Vehicles platform, which are forwarded by the vehicle terminal to the smart cockpit controller to adjust the log switch and recorded content; afterwards, the smart cockpit log is remotely transmitted and the problem is located according to the specified return address provided by the Internet of Vehicles platform. In this way, the expected system logs can be obtained quickly and conveniently, and the problem can be accurately located according to the system logs, which improves the efficiency of log acquisition and problem location.
[0056] Reference Figure 1 As shown, it is a schematic diagram of the steps of a method for locating a problem based on an intelligent cockpit log provided by an embodiment of the present application. Figure 1 As shown, the method for locating the problem based on the intelligent cockpit log may include the following steps:
[0057] Step 102: The Internet of Vehicles platform receives a problem location request sent by a user; the problem location request carries at least one keyword characterizing the problem phenomenon of the smart cockpit.
[0058] Among them, the problem location request can be sent by the user to the Internet of Vehicles platform through a mobile terminal (for example, a mobile phone or tablet, etc.) or a vehicle-mounted terminal (for example, TBOX); the problem location request can carry keywords and the device identification of the target vehicle with the problem, and each problem location request can carry one or more keywords, which are used to characterize the problem phenomenon of the smart cockpit of the target vehicle. Specifically, these keywords can be words or short sentences extracted from sentences describing abnormal problem phenomena of the smart cockpit. For example, "the audio of the smart cockpit cannot be turned on", the keywords can be extracted: "audio" & "cannot be turned on" or the keyword "audio cannot be turned on" can be extracted.
[0059] It should be understood that, in general, a problem location request is generated based on an abnormal problem phenomenon, that is, a problem location request carries at least one keyword characterizing a problem phenomenon. Optionally, in the case of tight business demand, a problem location request can be generated based on multiple abnormal problem phenomena, that is, a problem location request carries multiple keywords characterizing multiple problem phenomena. Because in some cases, the failure of a component of the smart cockpit can cause multiple problem phenomena, therefore, different problem phenomena are not distinguished here, and all keywords of multiple problem phenomena can be aggregated together to obtain a keyword set.
[0060] Step 104: The Internet of Vehicles platform uses a set prediction model based on at least one keyword in the problem location request to predict the functional modules of the smart cockpit related to this problem location request and their corresponding log levels; wherein the set prediction model is repeatedly trained based on historical problems of the smart cockpit.
[0061] The Internet of Vehicles platform is preloaded with a set prediction model, which is trained repeatedly based on the keywords of abnormal problem phenomena caused by historical problems of smart cockpits of specific models or various models. Therefore, the prediction model can effectively predict the functional module where the problem is located for the Internet of Vehicles platform.
[0062] It should be understood that the training method of the prediction model here can refer to the training method of existing machine learning models, such as neural network models, decision number models, etc., and this application is not limited to this.
[0063] The Internet of Vehicles platform extracts features based on at least one keyword in the problem location request, and then inputs the set prediction model for prediction to obtain the functional module of the smart cockpit related to the abnormal problem. At the same time, it can also predict the log level corresponding to the functional module. The log level is used to reflect the level of detail of the diary record information, which can be divided according to the importance and detail of the information.
[0064] Step 106: The Internet of Vehicles platform adds the functional module and its corresponding log level to the log configuration information, and forwards the log configuration information to the smart cockpit controller through the vehicle terminal; wherein the log configuration information also includes: recording rules, return address, and user name and password.
[0065] The IoV platform adds the predicted function modules and corresponding log levels to the log configuration information. In this way, the function modules, log levels, recording rules, return addresses, user names and passwords form new log configuration information. The IoV platform sends the new log configuration information to the on-board terminal of the target vehicle, which is then forwarded to the smart cockpit controller by the on-board terminal.
[0066] Step 108: The smart cockpit controller enables the smart cockpit log corresponding to the functional module based on the received log configuration information, and sets the log level.
[0067] The smart cockpit controller parses the received log configuration information and obtains the corresponding configuration content. Enable the smart cockpit log corresponding to the functional module and set the log level of the corresponding smart cockpit log. After enabling the corresponding smart cockpit log, the smart cockpit log of the corresponding functional module can be recorded and collected according to the recording rules in the log configuration information. The recording rules can be to save the records according to the recording duration or file size.
[0068] Step 110: After collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs and returns the collected logs to the Internet of Vehicles platform based on the return address, user name and password.
[0069] Afterwards, the smart cockpit controller will compress the recorded logs according to the local capacity or transmission requirements, and return the compressed logs to the Internet of Vehicles platform corresponding to the return address. In fact, when returning the logs, the smart cockpit controller can also be verified according to the user name and password to avoid sending other redundant and irrelevant information to the Internet of Vehicles platform, ensuring the information security of the Internet of Vehicles platform.
[0070] Step 112: The Internet of Vehicles platform locates the problem based on the returned logs.
[0071] In this application, the Internet of Vehicles platform locates the problem based on the returned logs, and can analyze the problem according to the working status of the system recorded in the logs and locate it accurately. For details, you can refer to the existing solutions for analyzing and locating problems based on logs, which are not limited to the automotive field.
[0072] Optionally, if the Internet of Vehicles platform successfully locates the problem based on the returned log, the Internet of Vehicles platform sends log closing information to the smart cockpit controller through the vehicle terminal; wherein the log closing information includes: the function module to be closed, the return address, and the user name and password; the smart cockpit controller closes the smart cockpit log corresponding to the function module based on the received log closing information, and returns the closing result to the Internet of Vehicles platform through the vehicle terminal. Thus, after the problem is located, the smart cockpit log is closed in time through the log closing information to avoid the waste of computing power caused by collecting and returning the log.
[0073] Optionally, if the Internet of Vehicles platform fuzzily locates the problem according to the returned log, then the Internet of Vehicles platform, based on the result of fuzzy location, selects the initially located function module from the predicted function modules of the smart cockpit, and increases the log level before the initially located function module; the Internet of Vehicles platform adds the initially located function module and its increased log level to the log configuration information, and forwards the log configuration information to the smart cockpit controller through the vehicle terminal; the smart cockpit controller, based on the received log configuration information, increases the log level of the smart cockpit log corresponding to the initially located function module, and closes other function modules other than the initially located function module; wherein, the higher the log level, the more detailed the information recorded; after collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs and returns the compressed logs to the Internet of Vehicles platform; the Internet of Vehicles platform accurately locates the initially located function module according to the returned log. In this way, if the Internet of Vehicles platform still cannot accurately locate the problem after fuzzy location of the problem based on the returned log, it can filter out the initially located function module based on the result of fuzzy location and adjust its log level. Afterwards, the log configuration information for adjusting the log level is sent to the smart cockpit controller again. Since the log level is more detailed after the adjustment, the Internet of Vehicles platform can accurately locate the problem based on the log with higher details.
[0074] Furthermore, when the Internet of Vehicles platform increases the log level before the initially located functional module, it may specifically set an increased level for the log level of the initially located functional module according to the type of the initially located functional module; or, randomly increase the log level before the initially located functional module.
[0075] For example, if the initially located functional module is a hardware device, the adjustment level can be appropriately set according to the complexity of the hardware device, for example, the higher the complexity, the higher the adjustment level. If the initially located functional module is a software module, the adjustment level can be appropriately set according to the importance of the function implemented by the software module and / or the priority of the log record content.
[0076] Furthermore, the log level before the initially located functional module can be randomly increased based on historical experience data, that is, the increased level here can be roughly determined in the increased range based on experience, and then the increased level can be randomly selected.
[0077] Optionally, the smart cockpit controller may also periodically clean up the saved logs according to the local storage capacity to ensure the stability of its own system functions and sufficient free memory space.
[0078] Reference Figure 2 The figure is a flow chart of the problem of positioning based on the intelligent cockpit log provided by the embodiment of the present application. Figure 2 The figure shows a system built with the Internet of Vehicles platform TSP, the Internet of Vehicles controller T-BOX, and the smart cockpit controller MP5. TSP serves as the monitoring background, manages all vehicles, and issues relevant instructions to designated vehicles; it also serves as the storage end for data feedback, storing the vehicle-side feedback logs. T-BOX serves as the access end for the vehicle-side to connect to TSP, realizes data communication with the TSP background, and provides the necessary mobile network for MP5. MP5, as the core product for processing smart cockpit functions and services, records its own system logs, and uploads logs according to the configuration issued by the platform. In addition, the log files need to be saved, compressed, cleaned, and processed. TSP and T-BOX can establish a connection through HTTP or TCP / IP protocol, and T-BOX and MP5 can realize data interaction through vehicle-mounted CAN / WiFi communication.
[0079] like Figure 2 As shown, the process includes the following steps:
[0080] ①TSP sends log configuration information to the vehicle-side T-BOX. The configuration information includes whether the log is enabled, the log enablement level, the log upload address & port, and the user name & password.
[0081] ②T-BOX completely parses the configuration information, and synchronizes the log configuration to MP5 according to the format and specifications defined by the CAN protocol.
[0082] ③MP5 parses CAN commands and saves log configuration parameters.
[0083] ④ According to the log configuration parameters, turn on or off the log, set the log level and start logging.
[0084] ⑤ Save and compress the recorded logs according to certain rules (such as file size or recording duration).
[0085] ⑥ According to the upload address and access username provided by TSP, the compressed log file is sent back to TSP.
[0086] ⑦TSP locates the problem based on the returned logs.
[0087] ⑧The MP5 terminal can also clean up logs regularly to ensure the stability of its own system functions and free memory space.
[0088] Reference Figure 3 As shown, it is a schematic diagram of the control flow based on the intelligent cockpit log positioning problem provided in an embodiment of the present application.
[0089] Step 302: The Internet of Vehicles platform receives a problem location request sent by a user.
[0090] Step 304: The Internet of Vehicles platform uses a set prediction model based on at least one keyword in the problem location request to predict the functional modules of the smart cockpit related to the problem location request and their corresponding log levels.
[0091] Step 306: The Internet of Vehicles platform adds the functional module and its corresponding log level to the log configuration information, and forwards the log configuration information to the smart cockpit controller through the vehicle terminal.
[0092] Step 308: The smart cockpit controller enables the smart cockpit log corresponding to the functional module based on the received log configuration information, and sets the log level.
[0093] Step 310: After collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs and returns the collected logs to the Internet of Vehicles platform based on the return address, user name and password.
[0094] Step 312: The Internet of Vehicles platform locates the problem based on the returned logs.
[0095] If the Internet of Vehicles platform successfully locates the problem according to the returned log, then execute step 314 ; if the Internet of Vehicles platform fuzzily locates the problem according to the returned log, then execute step 318 .
[0096] It should be understood that in the present application, successfully locating a problem means that diagnosis and repair can be performed based on the determined problem location, and the problem can be solved. If effective diagnosis and repair cannot be performed based on the determined problem location, it is considered as fuzzy positioning.
[0097] Step 314: The Internet of Vehicles platform sends log closing information to the smart cockpit controller through the vehicle terminal.
[0098] The log closing information includes: the function module to be closed, the return address, and the user name and password.
[0099] Step 316: The smart cockpit controller closes the smart cockpit log corresponding to the functional module based on the received log closing information, and returns the closing result to the Internet of Vehicles platform through the vehicle terminal.
[0100] Step 318: Based on the result of fuzzy positioning, the Internet of Vehicles platform selects the initially located functional modules from the predicted functional modules of the smart cockpit, and increases the log level before the initially located functional modules.
[0101] Step 320: The Internet of Vehicles platform adds the initially located functional modules and their increased log levels to the log configuration information, and forwards the log configuration information to the smart cockpit controller via the vehicle terminal.
[0102] Step 322: The smart cockpit controller increases the log level of the smart cockpit log corresponding to the initially located functional module based on the received log configuration information, and closes other functional modules except the initially located functional module.
[0103] The higher the log level, the more detailed the information recorded.
[0104] Step 324: After collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs and returns the compressed logs to the Internet of Vehicles platform.
[0105] Step 326: The Internet of Vehicles platform accurately locates the initially located functional module based on the returned log.
[0106] This solution can adjust the log settings of smart cockpit products from the background, and configure the log switch and log level as needed. In addition, the automatic upload of the vehicle-side log can solve the problem of finding vehicles and logs, and reduce the cost of obtaining logs. In addition, based on the original uploaded data from the vehicle, the TSP side can realize automatic parsing, visualize the abnormal situations in the logs, and simplify the problem retrieval process. At the same time, problems that are successfully located can be quickly resolved, and problems that cannot be successfully located can be further obtained by adjusting the log level to facilitate successful positioning by obtaining more detailed log information, thereby improving the flexibility and efficiency of the positioning method.
[0107] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.
[0108] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.
[0109] Figure 4 The structure diagram of the system based on intelligent cockpit log location problem provided by one embodiment of the present application is shown as follows: Figure 4As shown. The system 400 based on smart cockpit log location problem of this embodiment may include an Internet of Vehicles platform 401, an on-board terminal 402 and an intelligent cockpit controller 403. Among them, the Internet of Vehicles platform 401 receives a problem location request sent by a user; the problem location request carries at least one keyword characterizing the problem phenomenon of the intelligent cockpit; the Internet of Vehicles platform 401 uses a set prediction model based on at least one keyword in the problem location request to predict the functional modules of the intelligent cockpit related to this problem location request and their corresponding log levels; wherein the set prediction model is obtained by repeated training based on historical problems of the intelligent cockpit; the Internet of Vehicles platform 401 adds the functional modules and their corresponding log levels to the log configuration information, and transmits the same to the on-board terminal 402. The log configuration information is forwarded to the smart cockpit controller 403; wherein, the log configuration information also includes: recording rules, return address, user name and password; the smart cockpit controller 403, based on the received log configuration information, turns on the smart cockpit log corresponding to the functional module, and sets the log level; after collecting logs according to the recording rules in the log configuration information, the smart cockpit controller 403 compresses the collected logs, and based on the return address, user name and password, returns the collected logs to the Internet of Vehicles platform 401; the Internet of Vehicles platform 401 locates the problem based on the returned logs.
[0110] Optionally, in a possible implementation of this embodiment, if the Internet of Vehicles platform 401 successfully locates the problem based on the returned log, the Internet of Vehicles platform 401 may also send log closing information to the smart cockpit controller 403 through the vehicle terminal 402; wherein the log closing information includes: the functional module to be closed, the return address, and the user name and password; the smart cockpit controller 403 closes the smart cockpit log corresponding to the functional module based on the received log closing information, and returns the closing result to the Internet of Vehicles platform 401 through the vehicle terminal 402.
[0111] Optionally, in a possible implementation of this embodiment, if the Internet of Vehicles platform 401 fuzzily locates the problem according to the returned log, the Internet of Vehicles platform 401 can also filter out the preliminarily located functional modules from the predicted functional modules of the smart cockpit based on the result of the fuzzy positioning, and increase the log level before the preliminarily located functional modules; the Internet of Vehicles platform adds the preliminarily located functional modules and their increased log levels to the log configuration information, and forwards the log configuration information to the smart cockpit controller through the vehicle terminal; the smart cockpit controller increases the log level of the smart cockpit log corresponding to the preliminarily located functional modules based on the received log configuration information, and closes other functional modules except the preliminarily located functional modules; wherein, the higher the log level, the more detailed the information recorded; after collecting logs according to the recording rules in the log configuration information, the smart cockpit controller 403 compresses the collected logs and returns the compressed logs to the Internet of Vehicles platform 401; the Internet of Vehicles platform 401 accurately locates the preliminarily located functional modules according to the returned logs.
[0112] Optionally, in a possible implementation of the present embodiment, when the Internet of Vehicles platform 401 increases the log level before the initially located functional module, it is specifically used to set an increased level for the log level of the initially located functional module according to the type of the initially located functional module; or, randomly increase the log level before the initially located functional module.
[0113] Optionally, in a possible implementation of this embodiment, the smart cockpit controller is further used to periodically clean up the saved logs according to the local storage capacity.
[0114] In this embodiment, the Internet of Vehicles remote communication technology can be used to interact with users and the entire vehicle. The functional modules, log levels and other related configurations are sent down according to the Internet of Vehicles platform, and forwarded to the smart cockpit controller by the vehicle terminal to realize the switch of the log and the adjustment of the recorded content; afterwards, the remote return of the smart cockpit log and the location of the problem are realized according to the specified return address provided by the Internet of Vehicles platform. In this way, the desired system logs can be obtained quickly and conveniently, and the problem can be accurately located according to the system logs, which improves the efficiency of log acquisition and problem location.
[0115] An embodiment of the present application provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is loaded and executed by a processor to implement the method for locating problems based on intelligent cockpit logs as described above.
[0116] An embodiment of the present application provides an electronic device, which includes a processor and a memory, wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the method for locating problems based on intelligent cockpit logs as described above.
[0117] An embodiment of the present application provides a new energy commercial vehicle, comprising the electronic device as described above. Specifically, the new energy commercial vehicle may be a vehicle of level L2 or above.
[0118] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the relevant laws and regulations and do not violate public order and good morals.
[0119] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement an embodiment of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.
[0120] like Figure 5 As shown, the electronic device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.
[0121] Multiple components in the electronic device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the electronic device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.
[0122] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 501 performs the various methods and processes described above, such as a method for locating problems based on an intelligent cockpit log. For example, in some embodiments, the method for locating problems based on an intelligent cockpit log may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the method for locating problems based on the intelligent cockpit log described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to execute the problem location method based on the intelligent cockpit log in any other appropriate manner (for example, by means of firmware).
[0123] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
[0124] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.
[0125] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or 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 foregoing.
[0126] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).
[0127] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.
[0128] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.
[0129] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in this application can be achieved, and this document is not limited here.
[0130] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.
Claims
1. A method for locating problems based on intelligent cockpit logs, characterized in that: include: The Internet of Vehicles platform receives a problem location request sent by the user; The problem location request carries at least one keyword characterizing the problem phenomenon of the smart cockpit; The Internet of Vehicles platform predicts the function modules of the smart cockpit related to the current problem location request and their corresponding log levels using a set prediction model based on at least one keyword in the problem location request; wherein the set prediction model is repeatedly trained based on historical problems of the smart cockpit; The Internet of Vehicles platform adds the functional module and its corresponding log level to the log configuration information, and forwards the log configuration information to the smart cockpit controller through the vehicle terminal; wherein the log configuration information further includes: recording rules, return address, and user name and password; The smart cockpit controller starts the smart cockpit log corresponding to the functional module based on the received log configuration information, and sets the log level; After collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs and returns the collected logs to the Internet of Vehicles platform based on the return address, user name and password; The Internet of Vehicles platform locates the problem based on the returned logs.
2. The method according to claim 1, characterized in that If the Internet of Vehicles platform successfully locates the problem according to the returned log, the method further includes: The Internet of Vehicles platform sends log closing information to the smart cockpit controller through the vehicle terminal; wherein the log closing information includes: the function module to be closed, the return address, and the user name and password; The smart cockpit controller closes the smart cockpit log corresponding to the functional module based on the received log closing information, and returns the closing result to the Internet of Vehicles platform through the vehicle terminal.
3. The method according to claim 1, characterized in that If the Internet of Vehicles platform fuzzily locates the problem according to the returned log, the method further includes: The Internet of Vehicles platform selects the initially located functional modules from the predicted functional modules of the smart cockpit based on the result of fuzzy positioning, and increases the log level before the initially located functional modules; The Internet of Vehicles platform adds the initially located functional modules and the increased log levels thereof to the log configuration information, and forwards the log configuration information to the smart cockpit controller via the vehicle terminal; The smart cockpit controller increases the log level of the smart cockpit log corresponding to the initially located functional module based on the received log configuration information, and closes other functional modules except the initially located functional module; wherein the higher the log level, the more detailed the information recorded; After collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs and returns the compressed logs to the Internet of Vehicles platform; The Internet of Vehicles platform accurately locates the functional modules that have been initially located based on the returned logs.
4. The method according to claim 3, characterized in that The Internet of Vehicles platform increases the log level of the functional modules initially located, including: According to the type of the initially located functional module, set a higher log level for the initially located functional module; or, Randomly increase the log level before the initially located functional module.
5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: The intelligent cockpit controller periodically cleans up the saved logs according to the local storage capacity.
6. A system based on intelligent cockpit log location problem, characterized in that: include: Internet of Vehicles platform, vehicle terminal and smart cockpit controller; among them, The Internet of Vehicles platform receives a problem location request sent by a user; the problem location request carries at least one keyword characterizing the problem phenomenon of the smart cockpit; The Internet of Vehicles platform predicts the function modules of the smart cockpit related to the current problem location request and their corresponding log levels using a set prediction model based on at least one keyword in the problem location request; wherein the set prediction model is repeatedly trained based on historical problems of the smart cockpit; The Internet of Vehicles platform adds the functional module and its corresponding log level to the log configuration information, and forwards the log configuration information to the smart cockpit controller through the vehicle terminal; wherein the log configuration information further includes: recording rules, return address, and user name and password; The smart cockpit controller starts the smart cockpit log corresponding to the functional module based on the received log configuration information, and sets the log level; After collecting logs according to the recording rules in the log configuration information, the smart cockpit controller compresses the collected logs and returns the collected logs to the Internet of Vehicles platform based on the return address, user name and password; The Internet of Vehicles platform locates the problem based on the returned logs.
7. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.
8. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-5.
9. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 5.
10. A new energy commercial vehicle, characterized in that: Comprising the electronic device as claimed in claim 7.