A method, device, equipment and storage medium for generating an upgrade result report

Abstract

The present invention discloses a method, device, equipment and storage medium for generating an upgrade result report. The method comprises: constructing a target classifier; sending an upgrade task to a vehicle to be upgraded, and receiving the upgrade result fed back by the vehicle to be upgraded; inputting the upgrade result into the target classifier to obtain an upgrade result report. The technical solution of the present invention can solve the technical problem that there is a certain error in the statistics of the upgrade status of the cloud management system for remote upgrade of automobiles, and can improve the data statistical accuracy of remote upgrade of automobiles.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of vehicle technology, and in particular, to an upgrade result report generation method, device, equipment and storage medium. Background Art

[0002] The remote upgrade of the car software is realized by the cooperation of the vehicle-side components and the cloud management system. When the remote upgrade task of the car is deployed, the cloud management system issues the upgrade task, and the car-side receives the upgrade task and waits for the user's permission to upgrade. The status of the remote upgrade of the car is recorded by the vehicle-side upgrade component and reported to the cloud management system by the management node of the vehicle-side.

[0003] Currently, the remote upgrade status of a car is recorded by the vehicle-side components and reported directly to the cloud. Therefore, there is a certain error in the statistics of the remote upgrade status by the cloud management system. Summary of the invention

[0004] The embodiments of the present invention provide an upgrade result report generation method, device, equipment and storage medium to solve the technical problem that there are certain errors in the statistics of upgrade status in the cloud management system of automobile remote upgrade, and can improve the data statistics accuracy of automobile remote upgrade.

[0005] In a first aspect, an embodiment of the present invention provides a method for generating an upgrade result report, comprising:

[0006] Build target classifier;

[0007] Sending an upgrade task to the vehicle to be upgraded, and receiving the upgrade result fed back by the vehicle to be upgraded;

[0008] The upgrade result is input into the target classifier to obtain an upgrade result report.

[0009] In a second aspect, an embodiment of the present invention further provides an upgrade result report generating device, the device comprising:

[0010] The first building module is used to build a target classifier;

[0011] A processing module, used for sending an upgrade task to the vehicle to be upgraded, and receiving an upgrade result fed back by the vehicle to be upgraded;

[0012] The input module is used to input the upgrade result into the target classifier to obtain an upgrade result report.

[0013] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, an upgrade result report generating method as described in any one of the embodiments of the present invention is implemented.

[0014] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements an upgrade result report generating method as described in any one of the embodiments of the present invention.

[0015] The embodiment of the present invention constructs a target classifier; sends an upgrade task to the vehicle to be upgraded, and receives the upgrade result fed back by the vehicle to be upgraded; inputs the upgrade result into the target classifier to obtain an upgrade result report. The technical solution of the present invention can solve the technical problem that there is a certain error in the statistics of the upgrade status of the cloud management system for remote upgrade of automobiles, and improve the data statistics accuracy of remote upgrade of automobiles. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 is a flow chart of a method for generating an upgrade result report provided in Embodiment 1 of the present invention;

[0018] Figure 2 It is a flow chart of optimizing classification of a cloud management system in a method for generating an upgrade result report provided in the first embodiment of the present invention;

[0019] Figure 3 It is a flowchart of constructing a target classifier in a method for generating an upgrade result report provided in the first embodiment of the present invention;

[0020] Figure 4 It is a structural diagram of an upgrade result report generating device provided by Embodiment 2 of the present invention;

[0021] Figure 5 is a schematic diagram of the structure of an electronic device provided by Embodiment 3 of the present invention;

[0022] Figure 6 It is a structural diagram of a computer-readable storage medium containing a computer program provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0023] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only the parts related to the present invention, rather than all structures, are shown in the accompanying drawings. In addition, the embodiments of the present invention and the features in the embodiments may be combined with each other without conflict.

[0024] It should be mentioned before discussing exemplary embodiments in more detail that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe various operations (or steps) as sequential processes, many operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of various operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to methods, functions, procedures, subroutines, subprograms, etc. In addition, the embodiments in the present invention and the features in the embodiments can be combined with each other without conflict.

[0025] The term “including” and its variations used in the present invention are open inclusions, that is, “including but not limited to.” The term “based on” means “based at least in part on.” The term “one embodiment” means “at least one embodiment.”

[0026] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0027] Embodiment 1

[0028] Figure 1 is a flowchart of a method for generating an upgrade result report provided in the first embodiment of the present invention. This embodiment is applicable to the case of generating an upgrade result report. The method can be executed by the upgrade result report generating device in the embodiment of the present invention. The device can be implemented in software and / or hardware. Figure 1 As shown, the method specifically comprises the following steps:

[0029] S101. Build a target classifier.

[0030] It should be explained that the target classifier refers to a classifier that automatically trains the information in the cloud management system to achieve the purpose of information classification. In this embodiment, the target classifier can be a support vector machine (SVM) classifier, which is a classification algorithm based on statistical theory in the field of machine learning.

[0031] In actual operation, the cloud management system uses the software version number, upgrade pop-up window information, and download pop-up window information after the vehicle upgrade as sample features, and selects a multi-classification support vector machine (SVM) classifier for automatic training in the cloud management system. After the vehicle upgrade task is completed, the current software version, upgrade pop-up window information, and download pop-up window information are reported to the cloud management system for classification to obtain accurate upgrade result information.

[0032] S102: Send an upgrade task to the vehicle to be upgraded, and receive an upgrade result fed back by the vehicle to be upgraded.

[0033] In this embodiment, the vehicle to be upgraded refers to the vehicle whose software version is to be upgraded. The upgrade task refers to upgrading the software version of the vehicle to be upgraded. The upgrade result can be the software version number after the upgrade is successful, or a pop-up notification of whether the upgrade is successful.

[0034] The cloud management system sends an upgrade task to the vehicle to be upgraded. After the vehicle to be upgraded completes the upgrade task, it feeds back the upgrade result to the cloud management system. The cloud management system receives a pop-up notification of whether the upgrade of the vehicle to be upgraded is successful or the software version number after the upgrade is successful.

[0035] S103: Input the upgrade result into the target classifier to obtain an upgrade result report.

[0036] It should be noted that the upgrade result report refers to the upgrade result report formed after the target classifier in the cloud management system classifies the upgrade results fed back by each vehicle to be upgraded. For example, it may be that vehicle A is upgraded successfully, while vehicle B fails to upgrade, and the reason for the failure is that the owner of vehicle B did not click to download.

[0037] After completing the upgrade task, each vehicle to be upgraded will feed back the upgrade results to the cloud management system. The trained target classifier in the cloud management system will classify the upgrade results and produce an upgrade result report.

[0038] Optionally, before sending the upgrade task to the vehicle to be upgraded and receiving the upgrade result fed back by the vehicle to be upgraded, the process further includes:

[0039] Get upgrade task information.

[0040] The upgrade task information includes: task name, release deadline, vehicle model configuration of the vehicle to be upgraded, target version number, software package, location of the vehicle to be upgraded, and upgrade strategy of the vehicle to be upgraded.

[0041] Exemplarily, the task name refers to the name of the upgrade task, such as software version upgrade or version update. The release deadline refers to the expiration date of the released upgrade task, such as October 31, 2021, 24:00. The vehicle model configuration to be upgraded refers to the model and configuration of the vehicle to be upgraded, and the model may be, for example, a small car, a medium car, or a high-end car, and the configuration may be, for example, the wheelbase, maximum engine power, and fuel consumption of the vehicle.

[0042] It should be noted that the target version number refers to the version number of the new version to which the current version number of the vehicle to be upgraded can be upgraded. The software package refers to the installation package of the software corresponding to the target version number.

[0043] It should be explained that the upgrade strategy of the vehicle to be upgraded refers to the strategy for upgrading the vehicle to be upgraded, for example, it may be an upgrade of the vehicle speed, handbrake and safety information of the vehicle to be upgraded.

[0044] Build an upgrade task based on the upgrade task information.

[0045] During the actual operation, the cloud management system obtains the upgrade task information, constructs the upgrade task according to the upgrade task information, and sends it to the vehicle to be upgraded.

[0046] The technical solution of this embodiment, by constructing a target classifier; sending an upgrade task to the vehicle to be upgraded, and receiving the upgrade result fed back by the vehicle to be upgraded; inputting the upgrade result into the target classifier, and obtaining an upgrade result report, can solve the technical problem that there is a certain error in the statistics of the upgrade status of the cloud management system for remote upgrade of automobiles, and improve the data statistics accuracy of remote upgrade of automobiles.

[0047] Optionally, build a target classifier, including:

[0048] The training label of the historical data corresponding to the version number that is the same as the target version number is determined as the first training label.

[0049] It should be noted that historical data refers to the previous software version data already in the cloud management system. The historical data carries a training label, for example, the training label carried by the software version with version number 7 may be 1.

[0050] In this embodiment, the first training tag refers to the training tags carried by all software versions corresponding to the same version number as the target version number in the previous software version data in the cloud management system. Exemplarily, the first training tag can be set to 1, for example.

[0051] The training label of the historical data corresponding to the version number different from the target version number is determined as the second training label.

[0052] The second training label refers to the training labels carried by all software versions corresponding to version numbers different from the target version number in the previous software version data in the cloud management system. For example, the first training label can be set to 1, and the second training label can be set to -1.

[0053] A first training sample set is generated according to the historical data corresponding to the first training label and the historical data corresponding to the second training label.

[0054] It should be noted that the first training sample set refers to a training sample set generated by historical data corresponding to a version number that is the same as the target version number and historical data corresponding to a version number that is different from the target version number.

[0055] The first model is iteratively trained through the first training sample set to obtain a first classifier.

[0056] Exemplarily, the first model may be a support vector machine (SVM) model, which may be used to automatically train samples in a cloud management system.

[0057] The first classifier refers to a classifier for classifying software versions corresponding to a version number that is the same as a target version number and software versions corresponding to a version number that is different from the target version number.

[0058] In actual operation, a first training sample set is generated by iteratively training a first model with historical data corresponding to a version number that is the same as the target version number and historical data corresponding to a version number that is different from the target version number to obtain a first classifier.

[0059] The training label of the historical data including the upgrade pop-up window information in the historical data corresponding to the version number different from the target version number is determined as the third training label.

[0060] In this embodiment, the upgrade pop-up window information refers to a pop-up window information that reminds the user that the vehicle has an upgrade task. The upgrade pop-up window information may include selection buttons of "upgrade" and "not upgrade yet".

[0061] It should be noted that the third training tag refers to the training tag of historical data containing upgrade pop-up information in the historical data corresponding to the version number different from the target version number in the cloud management system. Exemplarily, the third training tag can be set to 2, for example.

[0062] The training label of the historical data that does not contain the upgrade pop-up window information in the historical data corresponding to the version number different from the target version number is determined as the fourth training label.

[0063] In this embodiment, the fourth training tag refers to the training tag of historical data that does not contain the upgrade pop-up window information in the historical data corresponding to the version number different from the target version number in the cloud management system. For example, the third training tag can be set to 2, and the fourth training tag can be set to -2.

[0064] During actual operation, historical data corresponding to the version number that is the same as the target version number and carrying the first label is eliminated, and historical data corresponding to the version number that is different from the target version number and carrying the second training label is classified into historical data containing upgrade pop-up information and historical data not containing upgrade pop-up information. The training label of the historical data containing the upgrade pop-up information is determined as the third training label, and the training label of the historical data not containing the upgrade pop-up information is determined as the fourth training label.

[0065] A second training sample set is generated according to the historical data corresponding to the third training label and the historical data corresponding to the fourth training label.

[0066] It should be noted that the second training sample set refers to a training sample set generated by training labels of historical data containing upgrade pop-up window information and training labels of historical data not containing upgrade pop-up window information in historical data corresponding to version numbers different from the target version number in the cloud management system.

[0067] The first model is iteratively trained through the second training sample set to obtain a second classifier.

[0068] The second classifier refers to a classifier for classifying historical data corresponding to a version number different from the target version number in the cloud management system into historical data containing upgrade pop-up window information and historical data not containing upgrade pop-up window information.

[0069] The training label of the historical data that does not contain the upgrade pop-up window information and contains the download pop-up window information in the historical data corresponding to the version number different from the target version number is determined as the fifth training label.

[0070] In this embodiment, the download pop-up window information refers to the pop-up window information that reminds the user whether to download the software installation package in the upgrade task. The download pop-up window information may include a selection button of "yes" and "no".

[0071] In this embodiment, the fifth training tag refers to the training tag of historical data that does not contain upgrade pop-up window information and contains download pop-up window information in the historical data corresponding to the version number different from the target version number in the cloud management system. Exemplarily, the fifth training tag can be set to 3, for example.

[0072] The training label of the historical data that does not include the upgrade pop-up window information and does not include the download pop-up window information in the historical data corresponding to the version number different from the target version number is determined as the sixth training label.

[0073] It should be noted that the sixth training label refers to the training label of historical data corresponding to a version number different from the target version number in the cloud management system that does not contain upgrade pop-up information and does not contain download pop-up information. For example, the fifth training label can be set to 3, and the sixth training label can be set to -3.

[0074] During actual operation, historical data containing upgrade pop-up information among historical data corresponding to a version number the same as the target version number and carrying a first label and corresponding to a version number different from the target version number and carrying a third label are eliminated; historical data not containing upgrade pop-up information among historical data corresponding to a version number different from the target version number and carrying a fourth training label are classified into historical data containing download pop-up information and historical data not containing download pop-up information; the training label of the historical data containing download pop-up information is determined as the fifth training label, and the training label of the historical data not containing download pop-up information is determined as the sixth training label.

[0075] A third training sample set is generated according to the historical data corresponding to the fifth training label and the historical data corresponding to the sixth training label.

[0076] It needs to be explained that the third training sample set refers to the training sample set generated by the training labels of historical data that does not contain upgrade pop-up information but contains download pop-up information in the historical data corresponding to the version number different from the target version number in the cloud management system, and the training labels of historical data that does not contain upgrade pop-up information and does not contain download pop-up information.

[0077] The first model is iteratively trained through the third training sample set to obtain a third classifier.

[0078] Among them, the third classifier refers to a classifier used to divide the historical data corresponding to the version number different from the target version number in the cloud management system that does not contain the upgrade pop-up information into the historical data containing the download pop-up information and the historical data not containing the download pop-up information.

[0079] A target classifier is generated according to the first classifier, the second classifier and the third classifier.

[0080] A target classifier is generated according to the first classifier, the second classifier and the third classifier, and then the information in the cloud management system is classified by the target classifier.

[0081] Optionally, an upgrade task is sent to the vehicle to be upgraded, and the upgrade result fed back by the vehicle to be upgraded is received, including:

[0082] Send an upgrade task to the vehicle to be upgraded, and receive the controller version number sent by the vehicle to be upgraded.

[0083] It should be explained that the controller version number refers to the version number of the controller of the vehicle to be upgraded before the upgrade.

[0084] In actual operation, the cloud management system sends an upgrade task to the vehicle to be upgraded. After the vehicle to be upgraded is powered on, the remote communication module TBOX (Telematics BOX, the vehicle-mounted network terminal, i.e., the car box) is awakened, and after passing the certificate authentication, it communicates with the cloud management system and reports the controller version number every 5 minutes. When the engine is not started, the cloud management system obtains the vehicle controller version number based on the cache. After the engine is started, the gateway automatically collects the vehicle version and updates the cache.

[0085] If the controller version number of the vehicle to be upgraded is different from the target version number, a download instruction is sent to the vehicle to be upgraded.

[0086] In this embodiment, the download instruction refers to an instruction for downloading a software package of an upgrade task sent by the cloud management system to the vehicle to be upgraded.

[0087] The cloud management system sends an upgrade task to the vehicle to be upgraded, receives the controller version number sent by the vehicle to be upgraded, and compares whether the controller version number sent by the vehicle to be upgraded is the same as the target version number. If the controller version number of the vehicle to be upgraded is different from the target version number, a download instruction is sent to the vehicle to be upgraded; if they are the same, no processing is performed.

[0088] If a download confirmation signal sent by the vehicle to be upgraded is received, the software package corresponding to the target version number is sent to the vehicle to be upgraded.

[0089] Exemplarily, the download confirmation signal may be a confirmation signal generated after the user clicks a “yes” selection button in the download pop-up window information.

[0090] If the cloud management system receives a download confirmation signal from the vehicle to be upgraded, the software package corresponding to the target version number will be sent to the vehicle to be upgraded for upgrading. If the automatic update button is turned on for the vehicle to be upgraded, it will automatically reply to the download confirmation signal to the cloud management system and start downloading immediately. If the automatic update is not turned on for the vehicle to be upgraded, the cloud management system will send a download pop-up window message to the vehicle-side TBOX, and TBOX will transmit the download pop-up window message to IVI (In-Vehicle Infotainment, host screen). After the vehicle to be upgraded displays the download pop-up window message, the user clicks "Yes" to confirm the download. After the download is completed, dmclient (download manager) receives the differential restoration completion signal and sends an installation pop-up window reminder. The vehicle to be upgraded pops up an installation prompt window, and the user can choose to install it in three ways: immediate upgrade, scheduled upgrade, and off-vehicle upgrade.

[0091] When the upgrade result sent by the vehicle to be upgraded is received, the upgrade result is displayed.

[0092] After the vehicle to be upgraded has completed the installation of the software package corresponding to the target version number, that is, after the upgrade is successful, the upgrade result is sent to the cloud management system. After receiving the upgrade result sent by the vehicle to be upgraded, the cloud management system displays the upgrade result.

[0093] The embodiment of the present invention uses the software version number, upgrade pop-up window information and download pop-up window information in the vehicle upgrade history data as sample features, and selects the support vector machine (SVM) classifier for automatic training in the cloud management system. After the upgrade task of the upgraded vehicle is completed, the upgraded software version number, upgrade pop-up window information and download pop-up window information are reported to the cloud management system for classification to obtain accurate upgrade result information. The data statistical accuracy of the remote upgrade of the car is improved, the necessary steps of entering the database and exporting the data after the upgrade is completed are eliminated, and the accuracy of the upgrade result statistics of the cloud management system is greatly improved.

[0094] As an exemplary description of this embodiment, Figure 2 Detailed description of the optimization classification of the cloud management system in the method for generating an upgrade result report. Figure 2 As shown, the process of optimizing classification of the cloud management system in the upgrade result report generation method provided in this embodiment specifically includes the following operations:

[0095] The previous actual data (ie the historical data mentioned above) is used for training to obtain a support vector machine (SVM) classifier in the cloud management system.

[0096] An upgrade task for more than 100 vehicles to be upgraded is established in the cloud management system. The number of vehicles to be upgraded can be more than 100 or a small number. The more the number of vehicles, the more intuitive the upgrade result information obtained by the cloud management system.

[0097] The vehicle to be upgraded will be upgraded after receiving the upgrade task, and the upgrade result data will be reported to the cloud management system after the upgrade is completed.

[0098] After all vehicles to be upgraded have been upgraded, the cloud management system locks the task and classifies the upgrade results uniformly. The cloud management system sets the upgrade time, locks the task after the upgrade time arrives, and uses the support vector machine (SVM) classifier to classify the upgrade results uniformly.

[0099] The cloud management system generates a vehicle upgrade result report.

[0100] As an exemplary description of this embodiment, Figure 3 1 is a flowchart of constructing a target classifier in a method for generating an upgrade result report provided in the first embodiment of the present invention. The process of constructing a target classifier in a method for generating an upgrade result report is described in detail. Figure 3 As shown, the process of constructing a target classifier in a method for generating an upgrade result report provided in this embodiment specifically includes the following operations:

[0101] The upgrade task information sent by the cloud management system to the vehicle to be upgraded includes the target version number. The target version number is compared with the historical data. The training label of the historical data corresponding to the version number consistent with the target version number is set to 1, otherwise it is -1. The historical data with a training label of 1 and the historical data with a training label of -1 are used to generate the first training sample set for training to obtain classifier 1.

[0102] The historical data with a training label of 1 is eliminated, and the historical data with a training label of -1 is divided. The training label of the historical data containing the upgrade pop-up information is set to 2, otherwise it is -2. The historical data with a training label of 2 and the historical data with a training label of -2 are used to generate a second training sample set for training to obtain classifier 2.

[0103] The historical data with training labels of 1 and 2 are eliminated, and the historical data with training label of -2 is divided. The training label of the historical data containing download pop-up information is set to 3, otherwise it is -3. The historical data with training label 3 and the historical data with training label -3 are used to generate a third training sample set for training to obtain classifier 3.

[0104] Classifiers 1, 2, and 3 are used to obtain four types of data (i.e., historical data corresponding to the same version number as the target version number with a training label of 1, historical data corresponding to a version number different from the target version number with a training label of 2, historical data containing upgrade pop-up information, historical data corresponding to a version number different from the target version number with a training label of 3, historical data not containing upgrade pop-up information but containing download pop-up information, and historical data corresponding to a version number different from the target version number with a training label of -3, not containing upgrade pop-up information and not containing download pop-up information), generate a target classifier, and when new data is input, the upgrade status of the cloud management system can be divided.

[0105] Embodiment 2

[0106] Figure 4 Schematic diagram of the structure of an upgrade result report generation device provided in the second embodiment of the present invention. This embodiment is applicable to the generation of upgrade result reports. The device can be implemented in software and / or hardware. The device can be integrated in any device that provides the function of generating upgrade result reports, such as Figure 4 As shown, the upgrade result report generating device specifically includes: a first construction module 210, a processing module 220 and an input module 230.

[0107] Wherein, the first construction module 210 is used to construct a target classifier;

[0108] The processing module 220 is used to send an upgrade task to the vehicle to be upgraded and receive an upgrade result fed back by the vehicle to be upgraded;

[0109] The input module 230 is used to input the upgrade result into the target classifier to obtain an upgrade result report.

[0110] Furthermore, before sending the upgrade task to the vehicle to be upgraded and receiving the upgrade result fed back by the vehicle to be upgraded, the method further includes:

[0111] An acquisition module is used to acquire upgrade task information, wherein the upgrade task information includes: task name, release deadline, vehicle model configuration of the vehicle to be upgraded, target version number, software package, location of the vehicle to be upgraded, and upgrade strategy of the vehicle to be upgraded;

[0112] The second building module is used to build an upgrade task according to the upgrade task information.

[0113] Furthermore, the first building block includes:

[0114] A first determining unit, configured to determine a training label of historical data corresponding to a version number that is the same as a target version number as a first training label;

[0115] A second determining unit, configured to determine a training label of historical data corresponding to a version number different from the target version number as a second training label;

[0116] A first generating unit, configured to generate a first training sample set according to the historical data corresponding to the first training label and the historical data corresponding to the second training label;

[0117] A first obtaining unit, configured to iteratively train a first model through the first training sample set to obtain a first classifier;

[0118] A third determining unit, configured to determine a training label of historical data containing upgrade pop-up window information in historical data corresponding to a version number different from the target version number as a third training label;

[0119] A fourth determining unit, configured to determine a training label of historical data that does not contain the upgrade pop-up window information in the historical data corresponding to a version number different from the target version number as a fourth training label;

[0120] A second generating unit, configured to generate a second training sample set according to the historical data corresponding to the third training label and the historical data corresponding to the fourth training label;

[0121] A second obtaining unit, configured to iteratively train the first model through the second training sample set to obtain a second classifier;

[0122] A fifth determining unit, configured to determine, as a fifth training label, a training label of historical data that does not contain the upgrade pop-up window information and contains the download pop-up window information in the historical data corresponding to a version number different from the target version number;

[0123] A sixth determining unit, configured to determine, as a sixth training label, a training label of historical data that does not include upgrade pop-up window information and does not include download pop-up window information in historical data corresponding to a version number different from the target version number;

[0124] A third generating unit, configured to generate a third training sample set according to the historical data corresponding to the fifth training label and the historical data corresponding to the sixth training label;

[0125] A third obtaining unit, configured to iteratively train the first model through the third training sample set to obtain a third classifier;

[0126] A fourth generating unit is used to generate a target classifier according to the first classifier, the second classifier and the third classifier.

[0127] Furthermore, the processing module includes:

[0128] A processing unit, used for sending an upgrade task to the vehicle to be upgraded, and receiving a controller version number sent by the vehicle to be upgraded;

[0129] A first sending unit, configured to send a download instruction to the vehicle to be upgraded if the controller version number of the vehicle to be upgraded is different from the target version number;

[0130] A second sending unit is configured to send the software package corresponding to the target version number to the vehicle to be upgraded if a download confirmation signal sent by the vehicle to be upgraded is received;

[0131] The display unit is used for receiving the upgrade result sent by the vehicle to be upgraded and displaying the upgrade result.

[0132] The above-mentioned product can execute the upgrade result report generation method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the upgrade result report generation method.

[0133] The technical solution of this embodiment, by constructing a target classifier; sending an upgrade task to the vehicle to be upgraded, and receiving the upgrade result fed back by the vehicle to be upgraded; inputting the upgrade result into the target classifier, and obtaining an upgrade result report, can solve the technical problem that there is a certain error in the statistics of the upgrade status of the cloud management system for remote upgrade of automobiles, and improve the data statistics accuracy of remote upgrade of automobiles.

[0134] Embodiment 3

[0135] Figure 5 It is a structural schematic diagram of an electronic device provided in Embodiment 3 of the present invention. Figure 5 A block diagram of an electronic device 312 suitable for implementing embodiments of the present invention is shown. Figure 5 The electronic device 312 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention. The device 312 is a typical computing device with the function of generating an upgrade result report.

[0136] like Figure 5 As shown, the electronic device 312 is in the form of a general purpose computing device. The components of the electronic device 312 may include, but are not limited to: one or more processors 316, a storage device 328, and a bus 318 connecting different system components (including the storage device 328 and the processor 316).

[0137] Bus 318 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnect (PCI) bus.

[0138] The electronic device 312 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 312, including volatile and non-volatile media, removable and non-removable media.

[0139] The storage device 328 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 330 and / or cache memory 332. The electronic device 312 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 334 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 not shown, usually called a "hard drive"). Although Figure 5 Not shown in the figure, a disk drive for reading and writing a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing a removable non-volatile optical disk (e.g., a read-only optical disk (Compact Disc-Read Only Memory, CD-ROM), a digital video disk (Digital Video Disc-Read Only Memory, DVD-ROM) or other optical media) may be provided. In these cases, each drive may be connected to the bus 318 via one or more data medium interfaces. The storage device 328 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0140] A program 336 having a set (at least one) of program modules 326 may be stored, for example, in a storage device 328, such program modules 326 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 326 generally perform the functions and / or methods of the embodiments described herein.

[0141] The electronic device 312 may also communicate with one or more external devices 314 (e.g., keyboard, pointing device, camera, display 324, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 312, and / or communicate with any device that enables the electronic device 312 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 322. In addition, the electronic device 312 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN) and / or a public network, such as the Internet) through a network adapter 320. As shown, the network adapter 320 communicates with other modules of the electronic device 312 through a bus 318. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 312, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, disk arrays (Redundant Arrays of Independent Disks, RAID) systems, tape drives, and data backup storage systems.

[0142] The processor 316 executes various functional applications and data processing by running the programs stored in the storage device 328, for example, implementing the upgrade result report generation method provided in the above embodiment of the present invention:

[0143] Build target classifier;

[0144] Sending an upgrade task to the vehicle to be upgraded, and receiving the upgrade result fed back by the vehicle to be upgraded;

[0145] The upgrade result is input into the target classifier to obtain an upgrade result report.

[0146] Embodiment 4

[0147] Figure 66 is a schematic diagram of the structure of a computer-readable storage medium containing a computer program provided in Embodiment 4 of the present invention. The embodiment of the present invention provides a computer-readable storage medium 61 on which a computer program 610 is stored. When the program is executed by one or more processors, the upgrade result report generation method provided in all the embodiments of the present invention is implemented:

[0148] Build target classifier;

[0149] Sending an upgrade task to the vehicle to be upgraded, and receiving the upgrade result fed back by the vehicle to be upgraded;

[0150] The upgrade result is input into the target classifier to obtain an upgrade result report.

[0151] Any combination of one or more computer-readable media can be used. Computer-readable media can be computer-readable signal media or computer-readable storage media or any combination of the above two. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0152] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0153] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0154] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (Hyper Text Transfer Protocol), and may be interconnected with 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"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0155] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0156] Computer program code for performing the operation of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0157] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square 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 square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0158] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

[0159] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0160] In the context of the present disclosure, 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.

[0161] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for generating an upgrade result report, characterized in that: include: Build target classifier; Sending an upgrade task to the vehicle to be upgraded, and receiving the upgrade result fed back by the vehicle to be upgraded; Inputting the upgrade result into the target classifier to obtain an upgrade result report; Before sending the upgrade task to the vehicle to be upgraded and receiving the upgrade result fed back by the vehicle to be upgraded, the method further includes: Obtaining upgrade task information, wherein the upgrade task information includes: task name, release deadline, vehicle model configuration of the vehicle to be upgraded, target version number, software package, location of the vehicle to be upgraded, and upgrade strategy of the vehicle to be upgraded; Constructing an upgrade task according to the upgrade task information; Wherein, constructing a target classifier includes: Determine the training label of the historical data corresponding to the version number that is the same as the target version number as the first training label; Determine the training label of the historical data corresponding to the version number different from the target version number as the second training label; Generate a first training sample set according to the historical data corresponding to the first training label and the historical data corresponding to the second training label; Iteratively training the first model through the first training sample set to obtain a first classifier; wherein the first classifier is a classifier for classifying software versions corresponding to a version number that is the same as a target version number and software versions corresponding to a version number that is different from the target version number; Determine the training label of the historical data containing the upgrade pop-up window information in the historical data corresponding to the version number different from the target version number as the third training label; Determine the training label of historical data that does not contain the upgrade pop-up window information in the historical data corresponding to the version number different from the target version number as the fourth training label; Generate a second training sample set according to the historical data corresponding to the third training label and the historical data corresponding to the fourth training label; Iteratively training the first model through the second training sample set obtains a second classifier; wherein the second classifier is a classifier for dividing historical data corresponding to a version number different from the target version number in the cloud management system into historical data containing upgrade pop-up window information and historical data not containing upgrade pop-up window information; Determine the training label of the historical data that does not contain the upgrade pop-up window information and contains the download pop-up window information in the historical data corresponding to the version number different from the target version number as the fifth training label; Determine the training label of historical data that does not contain upgrade pop-up window information and does not contain download pop-up window information in the historical data corresponding to the version number different from the target version number as the sixth training label; Generate a third training sample set according to the historical data corresponding to the fifth training label and the historical data corresponding to the sixth training label; Iteratively training the first model through the third training sample set obtains a third classifier; wherein the third classifier is a classifier for dividing historical data that does not contain upgrade pop-up window information among historical data corresponding to version numbers different from the target version number in the cloud management system into historical data that contains download pop-up window information and historical data that does not contain download pop-up window information; A target classifier is generated according to the first classifier, the second classifier and the third classifier.

2. The method according to claim 1, characterized in that Sending an upgrade task to the vehicle to be upgraded and receiving the upgrade result fed back by the vehicle to be upgraded, including: Send an upgrade task to the vehicle to be upgraded, and receive the controller version number sent by the vehicle to be upgraded; If the controller version number of the vehicle to be upgraded is different from the target version number, sending a download instruction to the vehicle to be upgraded; If a download confirmation signal sent by the vehicle to be upgraded is received, the software package corresponding to the target version number is sent to the vehicle to be upgraded; When the upgrade result sent by the vehicle to be upgraded is received, the upgrade result is displayed.

3. An upgrade result report generating device, characterized in that: include: The first building module is used to build a target classifier; A processing module, used for sending an upgrade task to the vehicle to be upgraded, and receiving an upgrade result fed back by the vehicle to be upgraded; An input module, used for inputting the upgrade result into a target classifier to obtain an upgrade result report; Before sending the upgrade task to the vehicle to be upgraded and receiving the upgrade result fed back by the vehicle to be upgraded, the method further includes: An acquisition module is used to acquire upgrade task information, wherein the upgrade task information includes: task name, release deadline, vehicle model configuration of the vehicle to be upgraded, target version number, software package, location of the vehicle to be upgraded, and upgrade strategy of the vehicle to be upgraded; A second building module, used to build an upgrade task according to the upgrade task information; The first building block comprises: A first determining unit, configured to determine a training label of historical data corresponding to a version number that is the same as a target version number as a first training label; A second determining unit, configured to determine a training label of historical data corresponding to a version number different from the target version number as a second training label; A first generating unit, configured to generate a first training sample set according to the historical data corresponding to the first training label and the historical data corresponding to the second training label; A first obtaining unit, configured to iteratively train a first model through the first training sample set to obtain a first classifier; wherein the first classifier is a classifier for classifying software versions corresponding to a version number that is the same as a target version number and software versions corresponding to a version number that is different from the target version number; A third determining unit, configured to determine a training label of historical data containing upgrade pop-up window information in historical data corresponding to a version number different from the target version number as a third training label; A fourth determining unit, configured to determine a training label of historical data that does not contain the upgrade pop-up window information in the historical data corresponding to a version number different from the target version number as a fourth training label; A second generating unit, configured to generate a second training sample set according to the historical data corresponding to the third training label and the historical data corresponding to the fourth training label; A second obtaining unit is used to iteratively train the first model through the second training sample set to obtain a second classifier; wherein the second classifier is a classifier for dividing historical data corresponding to a version number different from the target version number in the cloud management system into historical data containing upgrade pop-up window information and historical data not containing upgrade pop-up window information; A fifth determining unit, configured to determine, as a fifth training label, a training label of historical data that does not contain the upgrade pop-up window information and contains the download pop-up window information in the historical data corresponding to a version number different from the target version number; A sixth determining unit, configured to determine, as a sixth training label, a training label of historical data that does not include upgrade pop-up window information and does not include download pop-up window information in historical data corresponding to a version number different from the target version number; A third generating unit, configured to generate a third training sample set according to the historical data corresponding to the fifth training label and the historical data corresponding to the sixth training label; A third obtaining unit is used to iteratively train the first model through the third training sample set to obtain a third classifier; wherein the third classifier is a classifier for dividing the historical data that does not contain the upgrade pop-up window information among the historical data corresponding to the version number different from the target version number in the cloud management system into the historical data that contains the download pop-up window information and the historical data that does not contain the download pop-up window information; A fourth generating unit is used to generate a target classifier according to the first classifier, the second classifier and the third classifier.

4. The device according to claim 3, characterized in that The processing module comprises: A processing unit, used for sending an upgrade task to the vehicle to be upgraded, and receiving a controller version number sent by the vehicle to be upgraded; A first sending unit, configured to send a download instruction to the vehicle to be upgraded if the controller version number of the vehicle to be upgraded is different from the target version number; A second sending unit is configured to send the software package corresponding to the target version number to the vehicle to be upgraded if a download confirmation signal sent by the vehicle to be upgraded is received; The display unit is used for receiving the upgrade result sent by the vehicle to be upgraded and displaying the upgrade result.

5. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the processors are enabled to implement the method according to any one of claims 1 to 2.

6. A computer-readable storage medium containing a computer program, wherein the computer program is stored thereon, characterized in that: When the program is executed by one or more processors, the method according to any one of claims 1 to 2 is implemented.

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