CN116340332A - Method and device for updating scene library of vehicle-mounted intelligent system and vehicle - Google Patents
Method and device for updating scene library of vehicle-mounted intelligent system and vehicle Download PDFInfo
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Abstract
The application discloses a method, a device and a vehicle for updating a scene library of a vehicle-mounted intelligent system. Wherein the method comprises the following steps: acquiring historical data stored in a vehicle-mounted intelligent system of a vehicle, wherein the historical data is used for representing data generated by a user operating the vehicle; determining target data related to user behavior from the historical data; converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user requirements; and updating the plurality of vehicle use scenes into a scene library of the vehicle-mounted intelligent system. The method and the device solve the technical problem that human-computer interaction experience of the vehicle is poor because a scene library for learning of the vehicle-mounted intelligent operating system is usually preset and completed before the user uses the scene library.
Description
Technical Field
The present application relates to the field of vehicles, and in particular, to a method and apparatus for updating a scene library of an on-board intelligent system, and a vehicle.
Background
Under the large trend of automobile intellectualization, vehicle-mounted intelligent systems have become an emerging field of automobile industry, wherein intelligent voice interaction systems, automatic driving technologies and the like have become important components of automobile intellectualization. In daily use of the vehicle, the requirements of users on the operation experience, interaction mode and the like of the vehicle-mounted intelligent system are different, but in the prior art, a scene library for learning of the vehicle-mounted intelligent operation system is usually preset and completed before the users use the vehicle-mounted intelligent operation system, so that communication barriers between the users and the intelligent system are caused. How to improve the use satisfaction of users, enhance the man-machine interaction experience and become one of the problems to be solved urgently in the intelligent vehicle industry.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the application provides a method, a device and a vehicle for updating a scene library of a vehicle-mounted intelligent system, and at least solves the technical problem that human-computer interaction experience of the vehicle is poor because the scene library for learning of the vehicle-mounted intelligent operation system is preset and completed before a user uses the scene library.
According to one aspect of the embodiment of the application, there is provided a method for updating a scene library of an on-board intelligent system, including: acquiring historical data stored in a vehicle-mounted intelligent system of a vehicle, wherein the historical data is used for representing data generated by a user operating the vehicle; determining target data related to user behavior from the historical data; converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user requirements; and updating the plurality of vehicle use scenes into a scene library of the vehicle-mounted intelligent system.
Optionally, the vehicle-mounted intelligent system is provided with an acquisition device, and before acquiring the history data stored in the vehicle-mounted intelligent system, the method further comprises: responding to the situation that a user is positioned in a vehicle, acquiring user data and response data by utilizing acquisition equipment, wherein the user data comprises user operation data and user state information, the user state information is used for representing the physiological state and the emotional state of the user, and the response data is used for representing data generated by an intelligent vehicle-mounted system in response to a user operation instruction of the user; and storing the user operation data into the vehicle-mounted intelligent system.
Optionally, converting the target data into a plurality of vehicle usage scenarios includes: acquiring historical travel weather of the vehicle from the target data; and dividing the target data into a plurality of vehicle use scenes according to the historical travel weather, wherein the use scenes of different vehicles correspond to different historical travel weather.
Optionally, converting the target data into a plurality of vehicle usage scenarios includes: acquiring historical trip destination of the vehicle from the acquired target data, wherein the historical trip destination is confirmed through a starting point position and an end point position of a historical driving track in the target data; and dividing the target data into a plurality of vehicle use scenes according to the historical trip purposes, wherein different vehicle use scenes correspond to different historical trip purposes.
Optionally, converting the target data into a plurality of vehicle usage scenarios includes: acquiring vehicle components controlled by each historical user operation instruction from the target data; and dividing the target data into a plurality of vehicle use scenes according to the vehicle parts controlled by the historical control instructions, wherein the use scenes of different vehicles correspond to different vehicle parts.
Optionally, determining target data related to the user behavior from the historical data includes: and performing data cleaning and normalization processing on the historical data to obtain target data.
Optionally, the method further comprises: learning a scene library of the vehicle-mounted intelligent system by using a machine learning model to obtain a user portrait of a user; based on the user portrayal, pushing information.
According to another aspect of the embodiments of the present application, there is also provided an apparatus for updating a scene library of an on-vehicle intelligent system, including: the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring historical data stored in a vehicle-mounted intelligent system of a vehicle, and the historical data is used for representing data generated by a user operating the vehicle; a determining module, configured to determine target data related to user behavior from the historical data; the conversion module is used for converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user demands; and the updating module is used for updating the plurality of vehicle use scenes into a scene library of the vehicle-mounted intelligent system.
Optionally, the vehicle-mounted intelligent system is provided with an acquisition device, and the device further comprises: the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for responding to the user in a vehicle before acquiring historical data stored in the vehicle-mounted intelligent system, and acquiring user data and response data by utilizing acquisition equipment, wherein the user data comprises user operation data and user state information, the user state information is used for representing the physiological state and the emotional state of the user, and the response data is used for representing data generated by the intelligent vehicle-mounted system in response to a user operation instruction of the user; and the storage module is used for storing the user operation data into the vehicle-mounted intelligent system.
Optionally, the conversion module comprises: the weather acquisition unit is used for acquiring the historical travel weather of the vehicle from the target data; the first dividing unit is used for dividing the target data into a plurality of vehicle use scenes according to the historical travel weather, wherein the use scenes of different vehicles correspond to different historical travel weather.
Optionally, the conversion module comprises: the travel destination acquisition unit is used for acquiring the historical travel destination of the vehicle from the acquired target data, wherein the historical travel destination is confirmed through the starting point position and the end point position of the historical travel track in the target data; the second dividing unit is used for dividing the target data into a plurality of vehicle use scenes according to the historical trip purposes, wherein different vehicle use scenes correspond to different historical trip purposes.
Optionally, the conversion module comprises: the vehicle control acquisition unit is used for acquiring vehicle components controlled by each historical user operation instruction from the target data; and the third dividing unit is used for dividing the target data into a plurality of vehicle use scenes according to the vehicle parts controlled by the historical control instruction, wherein the use scenes of different vehicles correspond to different vehicle parts.
Optionally, the determining module includes: and the screening unit is used for carrying out data cleaning and normalization processing on the historical data to obtain target data.
Optionally, the apparatus further comprises: the learning module is used for learning a scene library of the vehicle-mounted intelligent system by using the machine learning model to obtain a user portrait of the user; and the pushing module is used for pushing information based on the user portrait.
According to another aspect of an embodiment of the present application, there is provided a vehicle including: the vehicle-mounted intelligent system is used for acquiring historical data stored in the vehicle-mounted intelligent system of the vehicle, wherein the historical data are used for representing data generated by a user operating the vehicle; determining target data related to user behavior from the historical data; converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user requirements; and updating the plurality of vehicle use scenes into a scene library of the vehicle-mounted intelligent system.
Optionally, the vehicle further comprises an acquisition device and a storage module, wherein the acquisition device is used for responding to the situation that the user is located in the vehicle, and acquiring user data and response data by utilizing the acquisition device, wherein the user data comprises user operation data and user state information, the user state information is used for representing the physiological state and the emotional state of the user, and the response data is used for representing data generated by the intelligent vehicle-mounted system in response to a user operation instruction of the user; and the storage module is used for storing the user operation data into the vehicle-mounted intelligent system.
Optionally, the vehicle-mounted intelligent system is further used for acquiring historical travel weather of the vehicle from the target data; and dividing the target data into a plurality of vehicle use scenes according to the historical travel weather, wherein the use scenes of different vehicles correspond to different historical travel weather.
Optionally, the vehicle-mounted intelligent system is further used for acquiring the historical trip purpose of the vehicle from the acquired target data, wherein the historical trip purpose is confirmed through the starting point position and the end point position of the historical trip track in the target data; and dividing the target data into a plurality of vehicle use scenes according to the historical trip purposes, wherein different vehicle use scenes correspond to different historical trip purposes.
Optionally, the vehicle-mounted intelligent system is further used for acquiring vehicle components controlled by each historical user operation instruction from the target data; and dividing the target data into a plurality of vehicle use scenes according to the vehicle parts controlled by the historical control instructions, wherein the use scenes of different vehicles correspond to different vehicle parts.
Optionally, the vehicle-mounted intelligent system is further used for performing data cleaning and normalization processing on the historical data to obtain target data.
Optionally, the vehicle-mounted intelligent system is further used for learning a scene library of the vehicle-mounted intelligent system by using a machine learning model to obtain a user portrait of the user; based on the user portrayal, pushing information.
According to another aspect of the embodiments of the present application, there is provided a computer readable storage medium having a computer program stored therein, wherein the computer program is configured to, when executed by a processor, perform a method of updating a scene library of an in-vehicle intelligent system of any of the embodiments of the present application.
Acquiring historical data stored in a vehicle-mounted intelligent system of a vehicle, wherein the historical data is used for representing data generated by a user operating the vehicle; determining target data related to user behavior from the historical data; converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user requirements; and updating the plurality of vehicle use scenes into a scene library of the vehicle-mounted intelligent system.
In the embodiment of the application, after the historical data stored in the vehicle-mounted intelligent system of the vehicle is obtained, the target data related to the user behavior is determined from the historical data, the target data is converted into a plurality of vehicle use scenes, and then the plurality of vehicle use scenes are updated to the scene library of the vehicle-mounted intelligent system.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a flow diagram of a method of updating a scene library of an on-board intelligent system according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a vehicle-mounted intelligent system in a method for updating a scene library of the vehicle-mounted intelligent system according to an alternative embodiment of the present application;
FIG. 3 is a schematic structural diagram of an apparatus for updating a scene library of an on-board intelligent system according to an embodiment of the present application;
fig. 4 is a schematic structural view of a vehicle according to an embodiment of the present application.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an embodiment of the present application, there is provided a method embodiment for updating a scene library of an on-board intelligent system, it being noted that the steps illustrated in the flowchart of the figures may be performed in a computer system, such as a set of computer executable instructions, and that although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different from that herein.
Fig. 1 is a flowchart of a method for updating a scene library of an on-board intelligent system according to an embodiment of the present application, as shown in fig. 1, the method includes the following steps:
step S102, historical data stored in an on-board intelligent system of the vehicle is obtained, wherein the historical data is used for representing data generated by a user operating the vehicle.
Specifically, the above-mentioned history data may be collected by a collection device such as a sensor and a camera provided in the vehicle, for example, data such as a driving behavior of the user, and a formed driving route, a driving speed, a seat position, and an angle generated during the driving behavior of the user. The user-operated vehicle includes: voice command, touch operation and the like.
Step S104, determining target data related to user behaviors from the historical data.
Specifically, after the historical data is acquired, initial target data related to the user behavior is needed to be first obtained, and the initial target data can be confirmed by adopting any one or a combination of the following modes:
statistical analysis: and (3) carrying out statistics and analysis on operation data of the user in the vehicle-mounted intelligent system, identifying functions and scenes frequently used by the user, and adding the functions and scenes into a scene library.
User feedback method: and the requirements and the preferences of the user on the vehicle-mounted intelligent system are known through the modes of user feedback, investigation and the like, and the requirements and the preferences are added into a scene library. For example, the user's usual scenes and scenes requiring optimization can be known through a questionnaire or a user feedback function.
Machine learning method: and processing and analyzing the acquired data by using a machine learning algorithm, identifying data related to user behaviors and requirements, and automatically updating a scene library. For example, user data may be grouped and categorized using a cluster analysis algorithm to identify scenes associated with user needs and automatically generate a corresponding scene library.
Domain specific method: and (5) requesting the expert in the related field to analyze and judge the acquired data, screening out the data related to the user behaviors and requirements, and adding the data into a scene library. For example, an expert in the automotive industry may be asked to classify and sort the scenes of the vehicle-mounted intelligent system, so as to improve the accuracy and practicality of the scene library.
After the initial target data is obtained, the data is preprocessed, namely, the data is cleaned, so that the accuracy and the integrity of the data are ensured, and then, as the historical data are usually derived from different controllers of the vehicle, the data from different sources are integrated together, and normalization processing is carried out, so that the target data are obtained.
Step S106, converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user demands.
Specifically, the artificial intelligent model may be used to analyze the target data to obtain an analysis result, and then the usage scenario is modeled and divided based on the analysis result, for example, the trip purpose of the user is divided into the scenes of commute, travel, shopping, etc., and the trip time is divided into the dimensions of daytime, nighttime, weekend, etc., so as to obtain a plurality of vehicle usage scenarios.
And step S108, updating a plurality of vehicle use scenes into a scene library of the vehicle-mounted intelligent system.
Specifically, after obtaining a plurality of vehicle usage scenarios, a high-frequency operation habit is determined from the plurality of vehicle scenarios, and the vehicle scenarios related to the single high-frequency operation habit are stored as a set of scenario data into a scenario library of the vehicle-mounted intelligent system. Then, based on the updated scene library, the vehicle-mounted intelligent system can better understand the user requirements of the user in various scenes and provide corresponding intelligent recommendation and services, such as intelligent navigation, vehicle control, multimedia playing and the like.
As an alternative implementation manner, after the historical data is obtained, the historical data can be processed in the vehicle, and the scene library of the vehicle-mounted intelligent system stored in the vehicle can be updated.
As an optional implementation manner, after the historical data is obtained, the historical data can be reported to the cloud end, the cloud end processes the target data, a plurality of vehicle use scenes are obtained, and the vehicle use scenes are updated to a scene library stored in the cloud end.
As an optional implementation manner, fig. 2 is a schematic structural diagram of a vehicle-mounted intelligent system in a method for updating a scene library of the vehicle-mounted intelligent system in an optional embodiment of the present application, as shown in fig. 2, where the scene library of the vehicle-mounted intelligent system is set in a cloud end, and the cloud end is further provided with a data processing and scene generating service for preprocessing and normalizing target data, and generating a vehicle usage scene, and a scene analyzing service for analyzing the scene and further grouping the scene. Android-APP is used for representing an Android application program arranged on a vehicle, the Android application program is provided with functions of buried point service, intelligent recommendation service, voice, weather, navigation, entertainment, ecology, driver health application, account number, individuation, vehicle setting and the like, the vehicle section also comprises a hardware device camera and a sensor, data collected through the camera can be processed through face recognition algorithm service in a Framework, and data collected through the sensor can be processed through a signal processing module. The system comprises a signal processing module, a face recognition algorithm service module, a camera and a sensor, wherein the signal processing module is used for converting signals into data and reporting the data to an android application layer of an automobile entertainment host, and the camera and the sensor are used for processing the data collected by the camera and the sensor by each service of the application layer and reporting the data in a real-time embedded point mode after the sensor information of the automobile and the sensor information of the automobile are collected by the hardware equipment, such as the camera and the sensor, such as the environment inside and outside the automobile, the health of a driver, the emotional state and the speed, the oil consumption, the electric quantity, the seat position and the angle of the running process. Other applications such as entertainment, ecology, navigation, weather, voice and the like in the vehicle report relevant user operation and voice instructions to the cloud through buried points. The cloud data processing module receives the embedded point data, performs preprocessing and screening, extracts high-frequency user operation and vehicle related state data under a certain scene according to scene classification, stores the group of data into 1 scene, and converts the group of data into operation scenes of the user, such as scenes of adjusting seat heating, air conditioning temperature and the like after getting on a car in winter according to voice instructions of the user, touch screen and other operation data. The scenes are stored in the scene library after being established one by one, and the scene library is classified and organized according to the relevance of the scenes so as to be used for subsequent intelligent recommendation, for example, all scenes related to air conditioning are stored in one air conditioning scene classification, and all scenes related to windows are stored in one window scene classification.
Through the steps, after the historical data stored in the vehicle-mounted intelligent system of the vehicle are obtained, the target data related to the user behaviors are determined from the historical data, the target data are converted into a plurality of vehicle use scenes, and then the plurality of vehicle use scenes are updated into the scene library of the vehicle-mounted intelligent system.
Optionally, the vehicle-mounted intelligent system is provided with an acquisition device, and before acquiring the history data stored in the vehicle-mounted intelligent system, the method further comprises: responding to the situation that a user is positioned in a vehicle, acquiring user data and response data by utilizing acquisition equipment, wherein the user data comprises user operation data and user state information, the user state information is used for representing the physiological state and the emotional state of the user, and the response data is used for representing data generated by an intelligent vehicle-mounted system in response to a user operation instruction of the user; and storing the user operation data into the vehicle-mounted intelligent system.
Specifically, the above-mentioned collection device may include, but is not limited to, a camera, a temperature sensor, a pressure sensor, a flexible electrode strip for collecting skin electric signals, etc., and the above-mentioned user operation data may be driving behavior of a user, operation behavior for a vehicle hardware button, touch operation for a touch screen on the vehicle, and voice instructions. The physiological state of the user may be a health state of the driver, for example, the vehicle-mounted intelligent system may be determined by analyzing the skin electric signal and the image data collected by the camera. The emotional state may be a mood of the user.
It should be noted that, the vehicle-mounted intelligent system can access the cloud and the local, and can store the user operation data into the local database, and also can store the user operation data into the database of the cloud.
Optionally, converting the target data into a plurality of vehicle usage scenarios includes: acquiring historical travel weather of the vehicle from the target data; and dividing the target data into a plurality of vehicle use scenes according to the historical travel weather, wherein the use scenes of different vehicles correspond to different historical travel weather.
Specifically, the historical travel weather may include, but is not limited to: the historical weather information can be confirmed by the weather information issued by the weather table and also can be confirmed by the information collected by the sensor equipment arranged on the vehicle in the categories of sunny days, rainy days, cloudy days, snowy days and the like. According to historical weather, the vehicle use scene is divided into a sunny use scene, a rainy use scene, a cloudy use scene and a snowy use scene.
Optionally, converting the target data into a plurality of vehicle usage scenarios includes: acquiring historical trip destination of the vehicle from the acquired target data, wherein the historical trip destination is confirmed through a starting point position and an end point position of a historical driving track in the target data; and dividing the target data into a plurality of vehicle use scenes according to the historical trip purposes, wherein different vehicle use scenes correspond to different historical trip purposes.
As an alternative embodiment, the user typically sets notes on the usual address when navigating, for example, sets notes "home" to the home address and sets addresses "company" to the company address, so that the historical trip purpose can be determined according to the starting position and the key position in the historical driving track. Historical travel purposes may include commuting, shopping, traveling, and the like.
Optionally, converting the target data into a plurality of vehicle usage scenarios includes: acquiring vehicle components controlled by each historical user operation instruction from the target data; and dividing the target data into a plurality of vehicle use scenes according to the vehicle parts controlled by the historical control instructions, wherein the use scenes of different vehicles correspond to different vehicle parts.
Specifically, the vehicle component may be any component in a vehicle: such as lighting systems, windows, seats, air conditioners, etc., for example, to divide air conditioner-related into air conditioner usage scenarios.
Optionally, determining target data related to the user behavior from the historical data includes: and performing data cleaning and normalization processing on the historical data to obtain target data.
Specifically, the data cleansing may include operations of deleting repeated data, processing abnormal data, and the like, specifically, the following manner may be adopted: if incomplete data or abnormal noise data deviating from normal data exist in the collected historical data, the abnormal noise data can be deleted directly. The normalization process is used for integrating data from different sensors or applications, including the data of user health and emotion obtained by a camera, fatigue driving state and the like, and the data of automobile driving route, driving time and the like into one scene, so that a more comprehensive and accurate user portrait is obtained.
Optionally, the method further comprises: learning a scene library of the vehicle-mounted intelligent system by using a machine learning model to obtain a user portrait of a user; based on the user portrayal, pushing information.
Fig. 3 is a schematic structural diagram of an apparatus for updating a scene library of an on-vehicle intelligent system according to an embodiment of the present application, as shown in fig. 3, the apparatus includes:
an acquisition module 32 for acquiring historical data stored in the on-board intelligent system of the vehicle, wherein the historical data is used for characterizing data generated by a user operating the vehicle.
A determining module 34 is configured to determine target data related to the user behavior from the historical data.
The conversion module 36 is configured to convert the target data into a plurality of vehicle usage scenarios, where different vehicle usage scenarios are used to satisfy different user requirements.
An updating module 38 is configured to update a plurality of vehicle usage scenarios into a scenario library of the vehicle-mounted intelligent system.
Optionally, the vehicle-mounted intelligent system is provided with an acquisition device, and the device further comprises: the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for responding to the user in a vehicle before acquiring historical data stored in the vehicle-mounted intelligent system, and acquiring user data and response data by utilizing acquisition equipment, wherein the user data comprises user operation data and user state information, the user state information is used for representing the physiological state and the emotional state of the user, and the response data is used for representing data generated by the intelligent vehicle-mounted system in response to a user operation instruction of the user; and the storage module is used for storing the user operation data into the vehicle-mounted intelligent system.
Optionally, the conversion module comprises: the weather acquisition unit is used for acquiring the historical travel weather of the vehicle from the target data; the first dividing unit is used for dividing the target data into a plurality of vehicle use scenes according to the historical travel weather, wherein the use scenes of different vehicles correspond to different historical travel weather.
Optionally, the conversion module comprises: the travel destination acquisition unit is used for acquiring the historical travel destination of the vehicle from the acquired target data, wherein the historical travel destination is confirmed through the starting point position and the end point position of the historical travel track in the target data; the second dividing unit is used for dividing the target data into a plurality of vehicle use scenes according to the historical trip purposes, wherein different vehicle use scenes correspond to different historical trip purposes.
Optionally, the conversion module comprises: the vehicle control acquisition unit is used for acquiring vehicle components controlled by each historical user operation instruction from the target data; and the third dividing unit is used for dividing the target data into a plurality of vehicle use scenes according to the vehicle parts controlled by the historical control instruction, wherein the use scenes of different vehicles correspond to different vehicle parts.
Optionally, the determining module includes: and the screening unit is used for carrying out data cleaning and normalization processing on the historical data to obtain target data.
Optionally, the apparatus further comprises: the learning module is used for learning a scene library of the vehicle-mounted intelligent system by using the machine learning model to obtain a user portrait of the user; and the pushing module is used for pushing information based on the user portrait.
Fig. 4 is a schematic structural view of a vehicle according to an embodiment of the present application, as shown in fig. 4, the vehicle includes:
the vehicle-mounted intelligent system 42 is configured to obtain historical data stored in the vehicle-mounted intelligent system of the vehicle, wherein the historical data is used for characterizing data generated by a user operating the vehicle; determining target data related to user behavior from the historical data; converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user requirements; and updating the plurality of vehicle use scenes into a scene library of the vehicle-mounted intelligent system.
Optionally, the vehicle further comprises an acquisition device and a storage module, wherein the acquisition device is used for responding to the situation that the user is located in the vehicle, and acquiring user data and response data by utilizing the acquisition device, wherein the user data comprises user operation data and user state information, the user state information is used for representing the physiological state and the emotional state of the user, and the response data is used for representing data generated by the intelligent vehicle-mounted system in response to a user operation instruction of the user; and the storage module is used for storing the user operation data into the vehicle-mounted intelligent system.
Optionally, the vehicle-mounted intelligent system is further used for acquiring historical travel weather of the vehicle from the target data; and dividing the target data into a plurality of vehicle use scenes according to the historical travel weather, wherein the use scenes of different vehicles correspond to different historical travel weather.
Optionally, the vehicle-mounted intelligent system is further used for acquiring the historical trip purpose of the vehicle from the acquired target data, wherein the historical trip purpose is confirmed through the starting point position and the end point position of the historical trip track in the target data; and dividing the target data into a plurality of vehicle use scenes according to the historical trip purposes, wherein different vehicle use scenes correspond to different historical trip purposes.
Optionally, the vehicle-mounted intelligent system is further used for acquiring vehicle components controlled by each historical user operation instruction from the target data; and dividing the target data into a plurality of vehicle use scenes according to the vehicle parts controlled by the historical control instructions, wherein the use scenes of different vehicles correspond to different vehicle parts.
Optionally, the vehicle-mounted intelligent system is further used for performing data cleaning and normalization processing on the historical data to obtain target data.
Optionally, the vehicle-mounted intelligent system is further used for learning a scene library of the vehicle-mounted intelligent system by using a machine learning model to obtain a user portrait of the user; based on the user portrayal, pushing information.
According to one embodiment of the present application, there is also provided a computer readable storage medium having a computer program stored therein, wherein the computer program is configured to perform, when run, a method of updating a scene library of an in-vehicle intelligent system of any of the above.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of:
s1, acquiring historical data stored in a vehicle-mounted intelligent system of a vehicle, wherein the historical data are used for representing data generated by a user operating the vehicle;
s2, determining target data related to user behaviors from historical data;
s3, converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user requirements;
and S4, updating the use scenes of the plurality of vehicles into a scene library of the vehicle-mounted intelligent system.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of: the vehicle-mounted intelligent system is provided with acquisition equipment, before the historical data stored in the vehicle-mounted intelligent system is acquired, the user data and response data are acquired by the acquisition equipment in response to the user being positioned in the vehicle, wherein the user data comprise user operation data and user state information, the user state information is used for representing the physiological state and the emotional state of the user, and the response data are used for representing data generated by the intelligent vehicle-mounted system in response to a user operation instruction of the user; and storing the user operation data into the vehicle-mounted intelligent system.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of: acquiring historical travel weather of the vehicle from the target data; and dividing the target data into a plurality of vehicle use scenes according to the historical travel weather, wherein the use scenes of different vehicles correspond to different historical travel weather.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of: acquiring historical trip destination of the vehicle from the acquired target data, wherein the historical trip destination is confirmed through a starting point position and an end point position of a historical driving track in the target data; and dividing the target data into a plurality of vehicle use scenes according to the historical trip purposes, wherein different vehicle use scenes correspond to different historical trip purposes.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of: acquiring vehicle components controlled by each historical user operation instruction from the target data; and dividing the target data into a plurality of vehicle use scenes according to the vehicle parts controlled by the historical control instructions, wherein the use scenes of different vehicles correspond to different vehicle parts.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of: and performing data cleaning and normalization processing on the historical data to obtain target data.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of: learning a scene library of the vehicle-mounted intelligent system by using a machine learning model to obtain a user portrait of a user; based on the user portrayal, pushing information.
The foregoing embodiment numbers of the present application are merely for describing, and do not represent advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application and are intended to be comprehended within the scope of the present application.
Claims (10)
1. A method of updating a scene library of an on-board intelligent system, comprising:
acquiring historical data stored in a vehicle-mounted intelligent system of a vehicle, wherein the historical data is used for representing data generated by a user operating the vehicle;
determining target data related to user behavior from the historical data;
converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user requirements;
and updating the plurality of vehicle use scenes into a scene library of the vehicle-mounted intelligent system.
2. The method according to claim 1, wherein the vehicle-mounted intelligent system is provided with an acquisition device, the method further comprising, prior to acquiring the historical data stored in the vehicle-mounted intelligent system:
responsive to a user being located in the vehicle, acquiring user data and response data by using the acquisition device, wherein the user data comprises user operation data and user state information, the user state information is used for representing physiological states and emotional states of the user, and the response data is used for representing data generated by the intelligent vehicle-mounted system in response to user operation instructions of the user;
and storing the user operation data into the vehicle-mounted intelligent system.
3. The method of claim 1, wherein converting the target data into a plurality of vehicle usage scenarios comprises:
acquiring historical travel weather of the vehicle from the target data;
and dividing the target data into a plurality of vehicle use scenes according to the historical travel weather, wherein the use scenes of different vehicles correspond to different historical travel weather.
4. The method of claim 1, wherein converting the target data into a plurality of vehicle usage scenarios comprises:
acquiring historical trip destination of the vehicle from the acquired target data, wherein the historical trip destination is confirmed through a starting point position and an end point position of a historical driving track in the target data;
and dividing the target data into a plurality of vehicle use scenes according to the historical trip purpose, wherein different vehicle use scenes correspond to different historical trip purposes.
5. The method of claim 1, wherein converting the target data into a plurality of vehicle usage scenarios comprises:
acquiring a vehicle component controlled by each historical user operation instruction from the target data;
and dividing the target data into a plurality of vehicle use scenes according to the vehicle parts controlled by the history control instruction, wherein the use scenes of different vehicles correspond to different vehicle parts.
6. The method of claim 1, wherein determining target data related to user behavior from the historical data comprises:
and performing data cleaning and normalization processing on the historical data to obtain the target data.
7. The method according to claim 1, wherein the method further comprises:
learning a scene library of the vehicle-mounted intelligent system by using a machine learning model to obtain a user portrait of the user;
pushing information based on the user portrait.
8. An apparatus for updating a scene library of an on-board intelligent system, comprising:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring historical data stored in a vehicle-mounted intelligent system of a vehicle, and the historical data is used for representing data generated by a user operating the vehicle;
a determining module, configured to determine target data related to user behavior from the historical data;
the conversion module is used for converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user demands;
and the updating module is used for updating the plurality of vehicle use scenes into a scene library of the vehicle-mounted intelligent system.
9. A vehicle, characterized by comprising:
the vehicle-mounted intelligent system is used for acquiring historical data stored in the vehicle-mounted intelligent system of the vehicle, wherein the historical data are used for representing data generated by a user operating the vehicle; determining target data related to user behavior from the historical data; converting the target data into a plurality of vehicle use scenes, wherein different vehicle use scenes are used for meeting different user requirements; and updating the plurality of vehicle use scenes into a scene library of the vehicle-mounted intelligent system.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program, wherein the computer program is arranged to, when run by a processor, perform the method of updating a scene library of an in-vehicle intelligent system as claimed in any of claims 1 to 7.
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| CN202310350561.3A CN116340332A (en) | 2023-04-03 | 2023-04-03 | Method and device for updating scene library of vehicle-mounted intelligent system and vehicle |
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| CN202310350561.3A CN116340332A (en) | 2023-04-03 | 2023-04-03 | Method and device for updating scene library of vehicle-mounted intelligent system and vehicle |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117422808A (en) * | 2023-12-19 | 2024-01-19 | 中北数科(河北)科技有限公司 | Three-dimensional scene data loading method and electronic equipment |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117422808A (en) * | 2023-12-19 | 2024-01-19 | 中北数科(河北)科技有限公司 | Three-dimensional scene data loading method and electronic equipment |
| CN117422808B (en) * | 2023-12-19 | 2024-03-19 | 中北数科(河北)科技有限公司 | Three-dimensional scene data loading method and electronic equipment |
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