CN110826039B - Remote networked automobile training platform - Google Patents
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- CN110826039B CN110826039B CN201911061412.5A CN201911061412A CN110826039B CN 110826039 B CN110826039 B CN 110826039B CN 201911061412 A CN201911061412 A CN 201911061412A CN 110826039 B CN110826039 B CN 110826039B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
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- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B9/00—Simulators for teaching or training purposes
- G09B9/02—Simulators for teaching or training purposes for teaching control of vehicles or other craft
- G09B9/04—Simulators for teaching or training purposes for teaching control of vehicles or other craft for teaching control of land vehicles
Abstract
The application provides real platform of instructing of car of long-range networking includes, should instruct the platform to include in fact: automobile driving simulation terminal and automobile driving center. The technical scheme provided by the application has the advantages of providing personalized service for the user and improving the user experience.
Description
Technical Field
The application relates to the field of internet and communication, in particular to a remote networked automobile training platform.
Background
The automobile driving simulation teaching system software conforms to the evaluation rule of '123 order of the ministry of public security', and 5 necessary tests are carried out on a small automobile, a small automatic transmission passenger automobile special for the disabled and a low-speed cargo vehicle field; 16 sites of large buses, tractors, city buses, medium buses and large trucks are necessary to be examined. The software also reserves the original driving training subject of the No. 91 order field.
The existing automobile training platform is set by single hardware, a networking platform is not provided, data cannot be shared, and user experience is reduced.
Content of application
The embodiment of the application provides a remote networked automobile training platform, which can realize the universality of trainee data and improve the user experience.
In a first aspect, an embodiment of the present application provides a remote networked automobile training platform, where the remote networked automobile training platform includes: the system comprises an automobile driving simulation terminal and an automobile driving center;
the automobile driving simulation terminal is used for acquiring biological parameters of a target object, identifying the biological parameters to obtain a first identity corresponding to the biological parameters, inquiring historical data on a first platform according to the first identity, and sending the first identity and a data template of a training project to an automobile driving center if the first historical data of the first identity is not inquired;
the automobile driving center is used for querying a second platform corresponding to the first identity after receiving the first identity and a data template, extracting second historical data of the training item of the first identity from the second platform, carrying out natural language identification on the second historical data to obtain second content of the second historical data, matching the second content with first content required by the data template to obtain a plurality of parameters of the same type, wherein the plurality of parameters of the same type are parameters of the same type in the first content and the second content, filling values of the plurality of parameters of the same type in the second content in the first content, generating the data template according to the first content, and sending the data template containing the first content to the automobile driving simulation terminal;
the automobile driving simulation terminal is used for updating the parameters of the automobile driving simulation terminal according to the parameter values in the first content
The embodiment of the application has the following beneficial effects:
according to the technical scheme, when the first identity of the target object is determined not to belong to the local user, the first identity and the data template of the updating project corresponding to the platform are sent to the automobile driving center, after the automobile driving center obtains the historical data of the first identity from other platforms, the historical data are analyzed to obtain the second content, the parameters in the second content, which are the same as the first content in type, are filled in as the first content, the data template is generated according to the first content, and then the data template is sent to the automobile driving simulation terminal for parameter updating, so that the personalized service of the automobile driving simulation platform is realized. The technical scheme provided by the application is that the values of the parameters are directly extracted, and the generated data template is the same as the data template of the first platform, so that the first platform and the second platform can be compatible, the problem that the parameter values cannot be used universally due to inconsistency of the data templates is avoided, and the user experience is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of an automobile driving simulation terminal according to an embodiment of the present application.
Fig. 2 is a schematic structural diagram of a remote networked automobile training platform disclosed in an embodiment of the present application.
Fig. 3 is a schematic flow chart of a remote networked automobile training method.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of this application and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an automobile driving simulation terminal, as shown in fig. 1, the automobile driving simulation terminal may include: processor 101, input unit 102, communication module 103, memory 104 and camera 105.
Automobile driving simulation software is provided by many companies, such as the millet driving school of Beijing, the school bus of Shenzhen, and the like. For the physical school bus, the training is based on the normal driving school, for example, the hai lake driving school in Beijing is the physical driving school, the user cannot learn to drive in other driving schools after the hai lake driving school signs the school bus, and the user generally has no requirement for learning to drive in other driving schools. However, as the automobile driving simulation software belongs to a software simulation platform, the requirement on a driving field is not so high, and therefore the requirement on cross-platform contact is required for a trained student. For example, the learner A lives on work in Beijing, but the learner A goes on business in Shenzhen for a certain period of time, the learner A may realize automobile driving simulation training on a simulation platform of Shenzhen, but the platform of the conventional Shenzhen cannot acquire training data of the Beijing, so that personalized service cannot be realized for the learner A, and the user experience is reduced.
Referring to fig. 2, fig. 2 provides a remote networked automobile training platform, where the method is executed by the automobile driving simulation terminal shown in fig. 1, and the platform shown in fig. 2 includes: the driving simulation terminal 20 and the driving center 21 (which may be connected via a 5G network) may be specifically configured as shown in fig. 1, and the driving simulation terminal 20 may be a cloud platform, a data center, or the like, or the driving center may also be a device combining the cloud platform and the data center.
The automobile driving simulation terminal 20 is configured to acquire a biological parameter of a target object, recognize the biological parameter to obtain a first identity corresponding to the biological parameter, query historical data on a first platform according to the first identity, and send the first identity and a data template of a training program to the automobile driving center 21 if the first historical data of the first identity is not queried;
such biological parameters include, but are not limited to: face pictures, fingerprint pictures, palm print pictures, vein pictures, etc., and the biometric identification techniques include but are not limited to: face recognition, optical fingerprint recognition, palm print recognition, vein recognition, etc., and the manner in which the first identity is determined is not limited by the present application.
The first platform may be a first identity platform.
With the human face picture as the calendar, the automobile driving simulation terminal 20 composes the first picture into input data CO1*CI1*H1*W1(ii) a Will input data CO1*CI1*H1*W1And executing multilayer convolution operation to obtain an operation result, and obtaining the first identity according to the operation result.
The above-mentioned manner of obtaining the first identity according to the operation result may be various, for example, the first identity is determined by comparing the difference between the template result and the operation result, and of course, a determination method of a face recognition algorithm such as face recognition with hundred degrees or Huawei may also be adopted.
The performing the layer 1 convolution operation in the multilayer convolution operation may specifically include:
the automobile driving simulation terminal 20 determines the number y1 of processors and obtains the size CO of the input data1*CI1*H1*W1And convolution kernel size M CI23 x 3, calculating α 1 ═ CI1Y 1/3. if α 1 is an integer greater than 1, the driving simulation terminal will input the size CO of the data1*CI1*H1*W1Edge CI1The direction is evenly cut into α 1 basic data blocks, α 1 basic data blocks are distributed to y1 processors, convolution kernels are broadcast to y1 processors, the y1 processors calculate the received basic data blocks and the convolution kernels to obtain y1 basic results, and y1 basic results are sent to the automobile driving simulation terminal 20 and the automobile driving simulation terminal 20Extracting a spliced data block CO between two adjacent basic data blocks of the y1 basic data blocks1*4*H1*W1Wherein the data blocks CO are concatenated1*4*H1*W1The data block splicing method includes the steps that the last 2 data blocks of a basic data block x in the CI direction and the first 2 data blocks of the basic data block x +1 in the CI direction are spliced, a server calculates y1-1 spliced data blocks and convolution kernels to obtain splicing results, and the automobile driving simulation terminal 20 splices the splicing results and the basic results together to obtain convolution results.
CO as described above1*CI1*H1*W1In (H)1、W1Respectively representing a height value and a width value; CO 21、CI1Representing a numerical value and a depth value. M is CI2In 4 x 3, M, CI2Representing a numerical value and a depth value.
The automobile driving center 21 is configured to query a second platform corresponding to the first identity after receiving the first identity and a data template, extract second history data of the training item of the first identity from the second platform, perform natural language identification on the second history data to obtain second content of the second history data, match the second content with first content required by the data template to obtain a plurality of parameters of the same type, where the plurality of parameters of the same type are parameters of the same type in the first content and the second content, fill values of the plurality of parameters of the same type in the second content in the first content, generate a data template according to the first content, and send the data template including the first content to an automobile driving simulation terminal;
the specific implementation method for obtaining a plurality of parameters of the same type by matching the second content with the first content required by the data template may include:
acquiring n types in the first content required in the data template, inquiring whether n parameter values corresponding to the n types exist in the second content, if so, determining that the n parameter values are a plurality of parameters of the same type, wherein the n is an integer greater than or equal to 1.
In the following, a practical example is described, and it is assumed that the first content required in the data template includes: seat length value, seat height value, left rearview mirror distance, right rearview mirror distance. If the second content of the figure contains 4 parameter values of the seat length value, the height value, the left rearview mirror distance and the right rearview mirror distance, the 4 parameter values are determined as the same type of parameters.
And the automobile driving simulation terminal 20 is used for updating the parameters of the automobile driving simulation terminal according to the parameter values in the first content.
The updating of the parameters of the automobile driving simulation terminal according to the parameter values in the first content may specifically include:
and adjusting the parameter of the automobile driving simulation terminal to the parameter value. Taking the above example as an example, the length value, the height value, the left rearview mirror distance and the right rearview mirror distance of the seat are adjusted to 4 parameter values corresponding to the second content.
Therefore, the user can realize the cross-platform and cross-region parameter sharing of the remote networked automobile practical training without self-adjusting the corresponding parameters.
According to the technical scheme, when the first identity of the target object is determined not to belong to a local user, the first identity and a data template of a new project corresponding to the platform are sent to the automobile driving center, the automobile driving center obtains historical data of the first identity from other platforms, analyzes the historical data to obtain second content, fills parameters of the second content, which are the same as the first content in type, in the first content, generates the data template according to the first content, and sends the data template to the automobile driving simulation terminal to update the parameters, so that personalized service of the automobile driving simulation platform is achieved. The technical scheme provided by the application is that the values of the parameters are directly extracted, and the generated data template is the same as the data template of the first platform, so that the first platform and the second platform can be compatible, the problem that the parameter values cannot be used universally due to inconsistency of the data templates is avoided, and the user experience is improved.
Referring to fig. 3, fig. 3 provides a remote networked automobile training method, which may be implemented by using the remote networked automobile training platform shown in fig. 2, and the method includes the following steps:
s301, the automobile driving simulation terminal acquires biological parameters of a target object, identifies the biological parameters to obtain a first identity corresponding to the biological parameters, inquires historical data on a first platform according to the first identity, and sends the first identity and a data template of a training project to an automobile driving center if the first historical data of the first identity is not inquired;
step S302, after receiving a first identity and a data template, an automobile driving center queries a second platform corresponding to the first identity, extracts second historical data of the training item of the first identity from the second platform, carries out natural language identification on the second historical data to obtain second content of the second historical data, matches the second content with first content required by the data template to obtain a plurality of parameters of the same type, wherein the plurality of parameters of the same type are parameters of the same type in the first content and the second content, fills values of the plurality of parameters of the same type in the second content in the first content, generates the data template according to the first content, and sends the data template containing the first content to an automobile driving simulation terminal;
and step S303, the automobile driving simulation terminal updates the parameters of the automobile driving simulation terminal according to the parameter values in the first content.
The remote networked automobile practical training method provided by the application is characterized in that when the first identity of a target object is determined not to belong to a local user, the first identity and a data template of a new project corresponding to the platform are sent to an automobile driving center, the automobile driving center obtains historical data of the first identity from other platforms, analyzes the historical data to obtain second content, fills parameters of the second content, which are the same as the first content in type, into the first content, generates the data template according to the first content, and sends the data template to an automobile driving simulation terminal for parameter updating, so that personalized service of an automobile driving simulation platform is realized. The technical scheme provided by the application is that the values of the parameters are directly extracted, and the generated data template is the same as the data template of the first platform, so that the first platform and the second platform can be compatible, the problem that the parameter values cannot be used universally due to inconsistency of the data templates is avoided, and the user experience is improved.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (3)
1. The utility model provides a real platform of instructing of long-range networked car which characterized in that, real platform of instructing of long-range networked car includes: the system comprises an automobile driving simulation terminal and an automobile driving center;
the automobile driving simulation terminal is used for acquiring biological parameters of a target object, identifying the biological parameters to obtain a first identity corresponding to the biological parameters, inquiring historical data on a first platform according to the first identity, and sending the first identity and a data template of a training project to an automobile driving center if the first historical data of the first identity is not inquired;
the automobile driving center is used for querying a second platform corresponding to the first identity after receiving the first identity and a data template, extracting second historical data of the training item of the first identity from the second platform, carrying out natural language identification on the second historical data to obtain second content of the second historical data, matching the second content with first content required by the data template to obtain a plurality of parameters of the same type, wherein the plurality of parameters of the same type are parameters of the same type in the first content and the second content, filling values of the plurality of parameters of the same type in the second content in the first content, generating the data template according to the first content, and sending the data template containing the first content to the automobile driving simulation terminal;
the automobile driving simulation terminal is used for updating the parameters of the automobile driving simulation terminal according to the parameter values in the first content;
the automobile driving center is specifically configured to obtain n types in first content required in a data template, query whether n parameter values corresponding to the n types exist in second content, and determine that the n parameter values are multiple parameters of the same type if the n parameter values corresponding to the n types are queried, where n is an integer greater than or equal to 1.
2. The remotely networked automotive training platform of claim 1,
the plurality of parameters of the same type include: seat length value, seat height value, left rearview mirror distance and right rearview mirror distance.
3. The remotely networked automotive training platform of claim 1,
the biological parameters include: a face picture, a fingerprint picture, a palm print picture or a vein picture.
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