Data processing method and device, electronic equipment and vehicle

Abstract

The invention relates to a data processing method and device, electronic equipment and a vehicle, and is applied to the technical field of vehicle intelligent driving. The data processing method comprises the following steps: carrying out classification processing on acquired vehicle driving data to obtain target driving data corresponding to at least one category; inputting the target driving data corresponding to each category into a first processing layer corresponding to the category, performing normalization processing on the target driving data based on the first processing layer to obtain normalized data, and storing the normalized data; and obtaining normalized data corresponding to the target driving data based on a second processing layer, and performing data rendering and interface display on the normalized data, the second processing layer being at least one page display layer having a corresponding relationship with the first processing layer, thereby performing normalization processing on the data, ensuring the universality of the data, and improving the user experience. Data multiplexing is achieved, the data processing amount and resource consumption are reduced, and the operation efficiency of the system is improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of vehicle intelligent driving, and in particular to a data processing method and device, an electronic device and a vehicle. BACKGROUND

[0002] With the continuous development of vehicle intelligence, intelligent driving technology is also being integrated into the vehicle field at an unprecedented pace. By installing an intelligent driving system in a vehicle, the vehicle is equipped with environmental perception and autonomous decision-making capabilities to achieve assisted driving or even higher-level autonomous driving, bringing a new revolution to travel.

[0003] Currently, the human-computer interaction interface is closely related to intelligent driving technology. The human-computer interaction interface cooperates with the intelligent driving system to realize the interaction between the human and the vehicle. The intelligent driving system includes multiple functions such as driving world reconstruction, intelligent parking, memory parking, and seamless switching between driving and parking, and needs to process data in real time after receiving intelligent driving related data and display on multiple display screens such as instrument, head-up display device, and central screen. However, when displaying on multiple display screens, the same to-be-displayed content needs to be processed for each screen, which causes heavy computing tasks, large data processing volume, and other problems, resulting in large system resource consumption and low running efficiency. SUMMARY

[0004] To solve the above technical problems, the present disclosure provides a data processing method, device, electronic device and vehicle.

[0005] A first aspect of an embodiment of the present disclosure provides a data processing method, comprising:

[0006] obtaining vehicle driving data, classifying and processing the vehicle driving data to obtain target driving data corresponding to at least one category;

[0007] for the target driving data corresponding to each category, inputting the target driving data into a first processing layer corresponding to the category, performing normalization processing on the target driving data based on the first processing layer to obtain normalized data and store the normalized data;

[0008] obtaining the normalized data corresponding to the target driving data based on a second processing layer, and performing data rendering and interface display on the normalized data, the second processing layer being at least one page display layer corresponding to the first processing layer.

[0009] In some embodiments of the present disclosure, the normalized processing of the target driving data based on the first processing layer obtains the normalized data and stores the normalized data, comprising:

[0010] The first processing layer is used for normalizing the data format, data structure and data form of the target driving data to obtain normalized data.

[0011] A data entity corresponding to the normalized data is created and stored.

[0012] In some embodiments of the present disclosure, before the normalized data is obtained and stored, the method further comprises:

[0013] The first processing layer is used for performing validity detection and rationality detection on the normalized data to obtain validity detection results and rationality detection results. The validity detection is used for determining whether the normalized data is empty and whether the data format is abnormal. The rationality detection is used for determining whether the normalized data lacks data agreed in a protocol and whether the numerical range is abnormal.

[0014] The normalized data is stored, including:

[0015] When the validity detection results and / or the rationality detection results of the normalized data determined based on the first processing layer are not passed, the normalized data is rejected.

[0016] In some embodiments of the present disclosure, the method further comprises:

[0017] After the normalized data is stored, the third processing layer is used for obtaining the normalized data from the first processing layer and storing the normalized data. The third processing layer is located between the first processing layer and the second processing layer and has a binding relationship with the first processing layer and the second processing layer.

[0018] In some embodiments of the present disclosure, after the third processing layer is used for obtaining the normalized data from the first processing layer and storing the normalized data, the method further comprises:

[0019] The third processing layer is used for performing smoothing processing on the normalized data to obtain smoothed data.

[0020] The normalized data is stored, including:

[0021] The smoothed data is stored.

[0022] In some embodiments of the present disclosure, the second processing layer is used for obtaining the normalized data corresponding to the target driving data and performing data rendering and interface display on the normalized data, including:

[0023] The second processing layer is used for obtaining the smoothed data corresponding to the target driving data from the third processing layer and performing data rendering and interface display on the smoothed data.

[0024] In some embodiments of the present disclosure, after obtaining the normalized data from the first processing layer based on the third processing layer and storing the normalized data, the method further comprises:

[0025] obtaining the changed data from the first processing layer based on the third processing layer when the third processing layer monitors that the data in the first processing layer changes, and storing the changed data.

[0026] A second aspect of the embodiments of the present disclosure provides a data processing apparatus, comprising:

[0027] a data classification processing module, configured to obtain vehicle driving data, and perform classification processing on the vehicle driving data to obtain target driving data corresponding to at least one category;

[0028] a data normalization processing module, configured to input the target driving data corresponding to each category into a first processing layer corresponding to the category, perform normalization processing on the target driving data based on the first processing layer, and obtain and store normalized data;

[0029] a data display module, configured to obtain the normalized data corresponding to the target driving data based on a second processing layer, and perform data rendering and interface display on the normalized data, the second processing layer being at least one page display layer corresponding to the first processing layer.

[0030] In some embodiments of the present disclosure, the data normalization processing module is specifically configured to perform normalization processing on a data format, a data structure and a data representation form of the target driving data based on the first processing layer to obtain the normalized data.

[0031] create a data entity corresponding to the normalized data, and store the data entity.

[0032] In some embodiments of the present disclosure, the data processing apparatus further comprises a data detection module.

[0033] The data detection module is configured to, before obtaining and storing the normalized data, perform validity detection and rationality detection on the normalized data based on the first processing layer to obtain a validity detection result and a rationality detection result, the validity detection being used to determine whether the normalized data is empty and whether a data format is abnormal, and the rationality detection being used to determine whether the normalized data lacks data agreed in a protocol and whether a numerical range is abnormal.

[0034] The data normalization processing module is further specifically configured to, when the validity detection result and / or the rationality detection result of the normalized data based on the first processing layer is not passed, perform rejection processing on the normalized data.

[0035] In some embodiments of the present disclosure, the data processing apparatus further comprises a data storage module.

[0036] The data storage module is used to obtain the normalized data from the first processing layer based on the third processing layer after storing the normalized data, and store the normalized data. The third processing layer is located between the first processing layer and the second processing layer, and has a binding relationship with the first processing layer and the second processing layer respectively.

[0037] In some embodiments of the present disclosure, the data processing device further includes a data smoothing processing module.

[0038] The data smoothing processing module is used to obtain normalized data from the first processing layer based on the third processing layer, store the normalized data, and then smooth the normalized data based on the third processing layer to obtain smoothed data after smoothing.

[0039] The data storage module is specifically used to store smoothed data.

[0040] In some embodiments of the present disclosure, the data display module is specifically used to obtain smooth data corresponding to the target driving data from the third processing layer based on the second processing layer, and perform data rendering and interface display on the smooth data.

[0041] In some embodiments of the present disclosure, the data processing device further includes a data monitoring module.

[0042] The data monitoring module is used to obtain normalized data from the first processing layer based on the third processing layer and store the normalized data. When the third processing layer monitors that the data in the first processing layer has changed, the module obtains the changed data from the first processing layer and stores the changed data.

[0043] A third aspect of the present disclosure provides an electronic device, including:

[0044] processor;

[0045] a memory for storing executable instructions;

[0046] The processor is used to read executable instructions from the memory and execute the executable instructions to implement the data processing method provided in the first aspect above.

[0047] A fourth aspect of an embodiment of the present disclosure provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the data processing method provided by the first aspect above.

[0048] A fifth aspect of an embodiment of the present disclosure provides a computer program product, which includes a computer program or instructions, and when the computer program or instructions are executed by a processor, implements the data processing method of the first aspect described above.

[0049] A sixth aspect of the embodiments of the present disclosure provides a vehicle, which comprises the electronic device provided in the third aspect.

[0050] The technical solutions provided by the embodiments of the present disclosure have the following advantages:

[0051] The data processing method, device, electronic device and vehicle provided by the embodiments of the present disclosure can obtain vehicle driving data, and after obtaining the vehicle driving data, the vehicle driving data is classified and processed according to different data categories to obtain target driving data corresponding to at least one category; for the target driving data corresponding to each category, the target driving data is input into a first processing layer corresponding to the category, the target driving data is normalized based on the first processing layer to obtain normalized data, and the normalized data is stored; the normalized data corresponding to the target driving data is obtained based on a second processing layer, and the normalized data is data-rendered and interface-displayed, the second processing layer being at least one page display layer corresponding to the first processing layer. Thus, the same data of each category can be normalized to ensure the universality of the data, and the data is processed only once, which can be used by multiple second processing layers at the same time or multiple times, so as to realize data reuse, and when the same data is displayed on multiple screens, it only needs to be processed once, without the need for each screen to process the data once when displaying, thereby reducing the data processing amount and resource consumption, and improving the running efficiency of the system. BRIEF DESCRIPTION OF DRAWINGS

[0052] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present disclosure and, together with the specification, serve to explain the principles of the present disclosure.

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, those skilled in the art can obtain other drawings from these drawings without creative effort.

[0054] Figure 1 is a flowchart of a data processing method provided by the embodiments of the present disclosure;

[0055] Figure 2 is an architecture schematic diagram of a processing layer provided by the embodiments of the present disclosure;

[0056] Figure 3 is a schematic diagram of an application scenario provided by the embodiments of the present disclosure;

[0057] Figure 4is a flowchart of another data processing method provided by an embodiment of the present disclosure.

[0058] Figure 5 is a structural schematic diagram of a data processing apparatus provided by an embodiment of the present disclosure.

[0059] Figure 6 is a structural schematic diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0060] In order to more clearly understand the above-mentioned purposes, features and advantages of the present disclosure, the schemes of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0061] In the following description, a large number of specific details are set forth in order to facilitate a thorough understanding of the present disclosure, but the present disclosure can also be implemented in other manners different from those described herein; obviously, the embodiments described in the specification are only a part of the embodiments of the present disclosure, and not all the embodiments.

[0062] It should be understood that each of the steps recorded in the method embodiments of the present disclosure can be executed in different orders and / or in parallel. In addition, the method embodiments can include additional steps and / or omit the execution of the steps shown. The scope of the present disclosure is not limited in this respect.

[0063] It should be noted that, in this document, relational terms such as "first" and "second", and the like, are used solely to distinguish one entity or action from another entity or action, without necessarily requiring or implying any actual such relationship or order between or among the entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without more limitations, an element defined by the phrase "comprising a..." does not exclude the existence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0064] It should be noted that the modification of "one" and "multiple" mentioned in the present disclosure is illustrative rather than limiting, and those skilled in the art should understand that, unless otherwise explicitly indicated in the context, it should be understood as "one or more".

[0065] Generally, with the continuous development of vehicle intelligence, intelligent driving technology is also being integrated into the vehicle field at an unprecedented pace. By installing an intelligent driving system in the vehicle, the vehicle is equipped with environmental perception and autonomous decision-making capabilities to achieve assisted driving or even higher-level autonomous driving, bringing a new revolution to travel.

[0066] Currently, the human-computer interaction interface is closely related to intelligent driving technology. The human-computer interaction interface cooperates with the intelligent driving system to realize the interaction between the human and the vehicle. Among them, the intelligent driving system is deployed with intelligent driving driving application programs and intelligent driving parking application programs, which specifically include a plurality of functions such as driving world restoration, intelligent parking, memory parking, and seamless switching between driving and parking. After receiving intelligent driving related data, real-time data processing is required, and the data is displayed on multiple display screens such as instrument, head-up display device, and central screen. However, because the vehicle driving data corresponding to different functions, such as vehicle driving data and parking data, has different communication channels, the data structure and data form of different communication channels are different, which leads to the fact that the data of different communication channels, such as vehicle parking data and vehicle driving data, cannot be cross-used, and at the same time, the same data cannot be reused when displayed on different screens. Therefore, when displaying on multiple display screens, for each screen, the same to-be-displayed content needs to be processed respectively, which has problems such as heavy computing task and large data processing amount, resulting in large system resource consumption and low running efficiency. In view of this problem, the embodiment of the present disclosure provides a data processing method, which will be introduced below in combination with specific embodiments.

[0067] Figure 1 A flowchart of a data processing method provided by the embodiment of the present disclosure, which can be executed by a data processing device, can be realized in the form of software and / or hardware, and can be configured in an electronic device, such as a server or a terminal. The terminal specifically includes a vehicle-mounted terminal, a computer, or a tablet computer, etc.

[0068] As shown in Figure 1 The data processing method provided by the embodiment of the present disclosure can be applied to the field of vehicle intelligent driving technology, and can be used for processing driving and parking data in the process of vehicle intelligent driving, for example. The data processing method can include the following steps.

[0069] S110, obtaining vehicle driving data, classifying and processing the vehicle driving data to obtain target driving data corresponding to at least one category.

[0070] In the embodiment of the present disclosure, the vehicle driving data can include vehicle driving data and / or vehicle parking data.

[0071] The vehicle driving data can be driving data of the vehicle in different modes, such as an intelligent driving mode. For example, the vehicle driving data can include a driving path of the vehicle, operation data during driving of the vehicle, obstacle data, lane line data, environmental data around the vehicle, and the like.

[0072] The vehicle parking data can be parking data of the vehicle in different modes, such as an intelligent driving mode. For example, the vehicle parking data can include parking space information corresponding to parking of the vehicle, floor information of the parking space, map information of the parking lot, environmental data around the vehicle, and the like.

[0073] The categories of the data can include lane lines, parking spaces, obstacles, and the like.

[0074] Specifically, the electronic device can control the various sensors in the vehicle to start and collect data in response to starting of the vehicle, and can also determine data related to driving of the vehicle, such as a driving path of the vehicle, in response to an operation of the user, and then obtain vehicle driving data. After obtaining the vehicle driving data, the vehicle driving data is classified based on roles, features, and influences on driving of the vehicle in a road environment, and the vehicle driving data is classified to obtain target driving data corresponding to at least one category.

[0075] In S120, for the target driving data corresponding to each category, the target driving data is input to a first processing layer corresponding to the category, the target driving data is normalized by the first processing layer, and normalized data is obtained and stored.

[0076] In the embodiments of the present disclosure, the first processing layer can be used to normalize the data, and can also be used to store the normalized data after normalization.

[0077] Specifically, after obtaining the target driving data corresponding to at least one category, the electronic device determines a first processing layer corresponding to each category, inputs the target driving data corresponding to each type to the first processing layer corresponding thereto, normalizes the target driving data of the category by the first processing layer, and then obtains normalized data, and stores the normalized data.

[0078] The first processing layer can store the normalized data to a first position of the first processing layer after obtaining the normalized data, or can store the normalized data to a second position of a cache database or a third position of a preset database, which is not limited herein.

[0079] In S130, the normalized data corresponding to the target driving data is obtained based on a second processing layer, and the normalized data is data-rendered and interface-displayed, and the second processing layer is at least one page display layer corresponding to the first processing layer.

[0080] In some embodiments of the present disclosure, the electronic device can determine at least one second processing layer corresponding to the first processing layer after storing the normalized data in the first processing layer, and then acquire the normalized data from the first processing layer based on the second processing layer and perform data rendering and interface display on the normalized data. In this way, the acquired vehicle driving data can be displayed in real time.

[0081] In an embodiment of the present disclosure, the second processing layer can be used to render data and display interfaces on the display screen, and can also be used to process user interaction operations.

[0082] In some other embodiments of the present disclosure, the electronic device can determine a category corresponding to the target driving data and at least one second processing layer corresponding to the category in response to an operation of displaying the target driving data, acquire normalized data corresponding to the target driving data based on the second processing layer, and perform data rendering and interface display on the normalized data, so that the user can view the interface display graph corresponding to the target driving data on the screen display interface. The specific implementation of data rendering and interface display is similar to the existing implementation of data rendering and interface display, and will not be repeated here.

[0083] The operation of displaying the target driving data can be a data display click operation of the user on any one or more display screens, or a data display operation corresponding to a data display instruction triggered by the intelligent driving system during execution of the business logic process.

[0084] In an embodiment of the present disclosure, vehicle driving data can be acquired, and after the vehicle driving data is acquired, the vehicle driving data is classified and processed according to different data categories to obtain target driving data corresponding to at least one category. For the target driving data corresponding to each category, the target driving data is input into a first processing layer corresponding to the category, the target driving data is normalized based on the first processing layer to obtain normalized data, and the normalized data is stored. The normalized data corresponding to the target driving data is acquired based on a second processing layer, and the normalized data is rendered and displayed in an interface. The second processing layer is at least one page display layer corresponding to the first processing layer. In this way, the same data of each category can be normalized to ensure the universality of the data, and the data is processed only once and can be used by multiple second processing layers at the same time or multiple times, thereby realizing data reuse. When the same data is displayed on multiple screens, it only needs to be processed once, without the need to process the data once for each screen to display, thereby reducing the data processing amount and resource consumption and improving the running efficiency of the system.

[0085] In the embodiments of the present disclosure, due to different communication channels corresponding to the vehicle driving data, such as driving and parking, the data structures and data forms of different communication channels are different, resulting in that the data of different communication channels, such as vehicle parking data and vehicle driving data, cannot be cross-used. Therefore, the electronic device performs normalization processing on the data format, data structure and data form of the target driving data to ensure the universality of the data. Meanwhile, in order to ensure the completeness of data storage and the convenience of subsequent use, the electronic device stores the data by creating a data entity of the data.

[0086] In the embodiments of the present disclosure, the normalization processing on the target driving data based on the first processing layer obtains normalized data and stores the normalized data, which can specifically include: performing normalization processing on the data format, data structure and data form of the target driving data based on the first processing layer to obtain normalized data; creating a data entity corresponding to the normalized data and storing the data entity.

[0087] In the embodiments of the present disclosure, the data entity can include identification information corresponding to the data, attribute information of the data, state information (such as life cycle state) of the data, relationship information (such as information for describing the relationship with other entities) of the data, and the like.

[0088] In the embodiments of the present disclosure, the specific implementation of the normalization processing on the data format, data structure and data form of the target driving data is similar to the existing implementation of data normalization processing, which is not described here.

[0089] Specifically, after obtaining the target driving data, the electronic device performs normalization processing on the data format, data structure and data form of the target driving data based on the first processing layer to obtain normalized data, determines the scene information corresponding to the target driving data, obtains the attribute information and state information corresponding to the target driving data, determines other entity information associated with the entity corresponding to the target driving data and the relationship between the other entities, creates a data entity based on the scene information, attribute information and state information corresponding to the target driving data, and other entity information and the relationship between the other entities, and then stores the created data entity.

[0090] In the embodiments of the present disclosure, the normalization processing on the target driving data can make the obtained normalized data no longer dependent on specific protocol objects, ensuring the universality of the data. Meanwhile, the data storage is performed by creating a data entity, ensuring the completeness of the data storage. In the subsequent data rendering and display, all data of this category can be directly obtained, and then the convenience of data rendering, display and analysis is brought.

[0091] In the embodiments of the present disclosure, in order to avoid the influence of illegal data on the normal operation of the system and the influence of invalid data on the operation efficiency of the system, after obtaining the normalized data based on the first processing layer, the normalized data is subjected to validity detection and rationality detection.

[0092] In the embodiments of the present disclosure, before obtaining and storing the normalized data, the data processing method can further include: performing validity detection and rationality detection on the normalized data based on the first processing layer to obtain validity detection results and rationality detection results, the validity detection being used to determine whether the normalized data is empty and whether the data format is abnormal; and the rationality detection being used to determine whether the normalized data is missing data agreed in a protocol and whether the numerical range is abnormal.

[0093] Specifically, after obtaining the normalized data, the electronic device detects the validity of the data, determines whether the normalized data is empty and whether the data format is abnormal, and detects the rationality of the data, determines whether the data is missing data agreed in a protocol and whether the numerical value of the data exceeds a preset numerical range, and further obtains validity detection results and rationality detection results.

[0094] Further, the normalized data obtained after normalization is stored, and specifically can include: when it is determined based on the first processing layer that the validity detection result and / or the rationality detection result of the normalized data is not passed, performing rejection processing on the normalized data; and when it is determined based on the first processing layer that the validity detection result and the rationality detection result of the normalized data are both passed, storing the normalized data.

[0095] In the embodiments of the present disclosure, by performing validity detection and rationality detection on the normalized data, only the data whose validity detection result and rationality detection result are both passed is stored, the normalized data whose validity detection result and / or rationality detection result is not passed is rejected, the accuracy and validity of the stored data are ensured, the waste of storage resources is avoided, the resource consumption and data processing amount caused by processing invalid or unreasonable data in the subsequent use of the data are avoided, the subsequent use of the data is facilitated, and the subsequent use efficiency of the data is improved.

[0096] In the embodiments of the present disclosure, the electronic device can further set a third processing layer between the first processing layer and the second processing layer, and perform storage and secondary processing of the data by the third processing layer, so as to not only reserve the original normalized data, but also perform rendering and display of the data based on the data after secondary processing, thereby improving the display effect of the data.

[0097] In the embodiments of the present disclosure, the data processing method can further include: after storing the normalized data, obtaining the normalized data from the first processing layer based on a third processing layer, and storing the normalized data, the third processing layer being located between the first processing layer and the second processing layer, and respectively having a binding relationship with the first processing layer and the second processing layer.

[0098] Figure 2 is a schematic diagram of an architecture of a processing layer provided by an embodiment of the present disclosure, as shown in Figure 2 The third processing layer is located between the first processing layer and the second processing layer, the third processing layer only binds and queries changes to the first processing layer, and the second processing layer only binds and queries changes to the third processing layer, thereby improving the flexibility and reusability of the first processing layer and the third processing layer through one-way binding.

[0099] The following takes the architecture of the processing layer as a model layer-view model layer-view layer (i.e., model-view model-view, MVVM) as an example for illustration, at this time, the first processing layer is a model layer (i.e., model layer), the second processing layer is a view layer (i.e., view layer), and the third processing layer is a view model layer (viewmodel layer). The model layer can perform normalization processing on target driving data and store the target driving data, the viewmodel layer has a binding relationship with the model layer, i.e., a corresponding relationship, can obtain data from the model layer, and query data changes in the model layer, and the view layer has a binding relationship with the viewmodel layer, can obtain data from the viewmodel layer, and perform data rendering and interface display.

[0100] Further, Figure 3 is a schematic diagram of an application scenario provided by an embodiment of the present disclosure, as shown in Figure 3 The application scenario includes a data processing layer, a first display layer, and a second display layer, wherein the data processing layer can be a core data processing layer of intelligent driving application programs and intelligent parking application programs in an intelligent driving system of a vehicle; the first display layer can be a display layer corresponding to a head-up display device of the vehicle, and is used to display target driving data on a screen corresponding to the head-up display device; and the second display layer can be a display layer corresponding to a center screen of the vehicle, and is used to display the target driving data on the center screen. Figure 3 Only part of the application scenario is shown, and the data processing method can also be applied to other application scenarios.

[0101] The data processing layer comprises an obstacle view model layer, a lane line view model layer and a parking space view model layer; the first display layer comprises a first obstacle view layer, a first lane line view layer and a first parking space view layer; the second display layer comprises a second obstacle view layer, a second lane line view layer and a second parking space view layer. The first obstacle view layer and the second obstacle view layer can obtain normalized data corresponding to obstacle data from the obstacle view model layer and perform data rendering and interface display; the first lane line view layer and the second lane line view layer can obtain normalized data corresponding to lane line data from the lane line view model layer and perform data rendering and interface display; and the first parking space view layer and the second parking space view layer can obtain normalized data corresponding to parking space data from the parking space view model layer and perform data rendering and interface display. Thus, the same data of the same category is processed once, and can be reused or reused multiple times by multiple view layers of the category, avoiding data processing by the display layer corresponding to each screen when multiple screens correspond to multiple display layers.

[0102] In the embodiments of the present disclosure, by setting a third processing layer between the first processing layer and the second processing layer and establishing a binding relationship between the third processing layer and the first processing layer and the second processing layer, the use and reuse of data can be more flexible.

[0103] In the embodiments of the present disclosure, after the third processing layer obtains normalized data from the first processing layer and stores the normalized data, the data processing method can further comprise: performing smoothing processing on the normalized data based on the third processing layer to obtain smoothed data.

[0104] Further, storing the normalized data can specifically comprise: storing the smoothed data.

[0105] In the embodiments of the present disclosure, the smoothing processing can be understood as anti-shake processing on the data to eliminate noise and jitter of the data, i.e., to avoid the problem of poor data display effect caused by data abnormalities.

[0106] Specifically, after the electronic device obtains the normalized data at the third processing layer, the normalized data can be smoothed based on a preset algorithm to obtain smoothed data, and the smoothed data can be stored. The preset algorithm can include a median filter method, a Kalman filter method, a spline interpolation method, etc., without limitation.

[0107] In the embodiments of the present disclosure, the normalized data can be smoothed based on the third processing layer, and the smoothed data after smoothing can be stored, which eliminates noise and jitter of the data, improves the accuracy and reliability of the data, and provides a better basis for subsequent data use.

[0108] In the embodiment of the present disclosure, the second processing layer obtains the normalized data corresponding to the target driving data, and performs data rendering and interface display on the normalized data. Specifically, the second processing layer can obtain the smoothed data corresponding to the target driving data from the third processing layer, and perform data rendering and interface display on the smoothed data.

[0109] In the embodiment of the present disclosure, the specific implementation of performing data rendering and interface display on the smoothed data is similar to the existing implementation of performing data rendering and interface display, and will not be repeated here.

[0110] In the embodiment of the present disclosure, when displaying the target driving data, the second processing layer can obtain the smoothed data corresponding to the target driving data from the third processing layer, and then perform data rendering and interface display on the smoothed data. Thus, the smoothness and continuity of the data are improved, and the effect of data display is improved.

[0111] In the embodiment of the present disclosure, after the third processing layer obtains the normalized data from the first processing layer and stores the normalized data, the data processing method can further include: when the third processing layer detects that the data in the first processing layer changes, obtaining the changed data from the first processing layer, and storing the changed data.

[0112] Specifically, the electronic device can monitor the data stored in the first processing layer based on the binding relationship between the third processing layer and the first processing layer and the change query authority, and when it is detected that the data changes, obtain the changed data from the first processing layer, and store the changed data.

[0113] In some embodiments of the present disclosure, the electronic device can further monitor the data stored based on the first processing layer (such as the data stored in the second location of the cache database or the third location of the preset database) based on the third processing layer, and then when it is detected that the data changes, obtain the changed data from the second location of the cache database or the third location of the preset database, and store the changed data. Alternatively, the changed data is stored after being smoothed.

[0114] In the embodiment of the present disclosure, by setting the change query or monitoring authority of the first processing layer for the third processing layer, when the data of the first processing layer changes, the third processing layer can obtain the changed data and store the changed data, thereby ensuring the real-time synchronization and consistency of the data, and further ensuring the accuracy of the data rendering and interface display of the second processing layer.

[0115] Figure 4 is a flowchart of another data processing method provided by the embodiment of the present disclosure, as shown in Figure 4As shown, the data processing method can include the following steps:

[0116] S410, vehicle driving data is acquired, and the vehicle driving data is classified and processed to obtain target driving data corresponding to at least one category.

[0117] S420, for the target driving data corresponding to each category, the target driving data is input to a first processing layer corresponding to the category, the target driving data is normalized based on the first processing layer, validity detection and rationality detection are performed on normalized data obtained after the normalization, and the normalized data passing the validity detection result and the rationality detection result are stored.

[0118] S430, the normalized data is acquired from the first processing layer based on a third processing layer, and the normalized data is smoothed, and the smoothed data is stored after the smoothing.

[0119] S440, the target driving data corresponding to the smoothed data is acquired from the third processing layer based on a second processing layer, and the smoothed data is rendered and displayed on an interface.

[0120] It should be noted that the specific implementation of steps S410 to S440 is similar to the implementation of the related steps in the above-mentioned embodiments of the present disclosure, and will not be repeated here.

[0121] In the embodiments of the present disclosure, vehicle driving data can be acquired, and after the vehicle driving data is acquired, the vehicle driving data is classified based on roles, features and influences on vehicle driving of the vehicle driving data in a road environment, and the vehicle driving data is classified to obtain target driving data corresponding to at least one category. For the target driving data corresponding to each category, a first processing layer corresponding to each category is determined, the target driving data corresponding to each category is input into the first processing layer corresponding thereto, the target driving data of the category is normalized by the first processing layer, and then normalized data is obtained, and the normalized data obtained after normalization is detected for validity and reasonableness, and then only data that passes the validity detection result and the reasonableness detection result is stored when storing, and the normalized data that does not pass the validity detection result and / or the reasonableness detection result is eliminated, so as to ensure the accuracy and validity of the stored data, avoid waste of storage resources, avoid resource consumption and data processing amount caused by processing of invalid or unreasonable data in subsequent use of data, provide convenience for subsequent use of data, and improve the subsequent use efficiency of data. Then, the normalized data is acquired from the first processing layer based on the third processing layer, and the normalized data is smoothed, the smoothed data after smoothing is stored, and in response to an operation of displaying the target driving data, the smoothed data corresponding to the target driving data is acquired from the third processing layer based on the second processing layer, and the smoothed data is data-rendered and interface-displayed, so as to improve the accuracy and reliability of the data, improve the smoothness and continuity of the data, and improve the data display effect.

[0122] In the embodiments of the present disclosure, the electronic device can also adopt a model-view-presenter (MVP) architecture or a model-view-controller (MVC) architecture to execute the data processing method for different application scenarios.

[0123] In the embodiments of the present disclosure, the electronic device can also perform data processing based on a pipeline mode without data persistence and data query and analysis requirements, that is, the normalized data is directly transmitted to the third processing layer for smoothing after the normalized data is acquired in the first processing layer, the third processing layer directly transmits the smoothed data to the second processing layer for data rendering and interface display, or the first processing layer directly transmits the normalized data to the second processing layer for data rendering and interface display, so as to reduce resource consumption caused by storage and further improve system running efficiency.

[0124] Figure 5 FIG. 1 is a structural schematic diagram of a data processing device provided by an embodiment of the present disclosure.

[0125] In the embodiments of the present disclosure, the data processing apparatus can be arranged in an electronic device, which is understood as a part of the function module of the electronic device. Specifically, the electronic device can be a server or a terminal, wherein the terminal specifically includes a vehicle-mounted terminal, a computer, a tablet computer, and the like, which are not limited herein.

[0126] As shown in FIG. 5, the data processing apparatus 500 can include a data classification processing module 510, a data normalization processing module 520, and a data display module 530. Figure 5 The data classification processing module 510 can be configured to obtain vehicle driving data, and perform classification processing on the vehicle driving data to obtain target driving data corresponding to at least one category.

[0127] The data normalization processing module 520 can be configured to input the target driving data corresponding to each category into a first processing layer corresponding to the category, perform normalization processing on the target driving data based on the first processing layer, obtain normalized data, and store the normalized data.

[0128] The data display module 530 can be configured to obtain the normalized data corresponding to the target driving data based on a second processing layer, and perform data rendering and interface display on the normalized data, wherein the second processing layer is at least one page display layer corresponding to the first processing layer.

[0129] In the embodiments of the present disclosure, the vehicle driving data can be obtained, and after obtaining the vehicle driving data, the vehicle driving data is classified and processed according to different data categories to obtain target driving data corresponding to at least one category. For the target driving data corresponding to each category, the target driving data is input into a first processing layer corresponding to the category, the target driving data is normalized based on the first processing layer, normalized data is obtained, and the normalized data is stored. The normalized data corresponding to the target driving data is obtained based on a second processing layer, and the normalized data is rendered and displayed on an interface. The second processing layer is at least one page display layer corresponding to the first processing layer. Thus, the same data of each category is normalized, ensuring the universality of the data. The data is processed only once, and can be used by multiple second processing layers at the same time or multiple times, achieving data reuse. When the same data is displayed on multiple screens, it only needs to be processed once, without the need to process the data for each screen, thereby reducing the data processing amount and resource consumption, and improving the running efficiency of the system.

[0130]

[0131] ​In some embodiments of the present disclosure, the data normalization processing module 520 can be specifically configured to normalize the data format, data structure and data representation of the target driving data based on the first processing layer to obtain normalized data.

[0132] The data entity corresponding to the normalized data is created and stored.

[0133] In some embodiments of the present disclosure, the data processing apparatus 500 can further include a data detection module.

[0134] The data detection module can be configured to, before obtaining and storing the normalized data, detect the validity and reasonableness of the normalized data based on the first processing layer to obtain validity detection results and reasonableness detection results. The validity detection is used to determine whether the normalized data is empty and whether the data format is abnormal. The reasonableness detection is used to determine whether the normalized data is missing data agreed in the protocol and whether the numerical range is abnormal.

[0135] The data normalization processing module 520 can be further configured to, when the validity detection result and / or the reasonableness detection result of the normalized data based on the first processing layer is not passed, perform rejection processing on the normalized data.

[0136] In some embodiments of the present disclosure, the data processing apparatus 500 can further include a data storage module.

[0137] The data storage module can be configured to, after storing the normalized data, acquire the normalized data from the first processing layer based on the third processing layer and store the normalized data. The third processing layer is located between the first processing layer and the second processing layer, and has a binding relationship with the first processing layer and the second processing layer, respectively.

[0138] In some embodiments of the present disclosure, the data processing apparatus 500 can further include a data smoothing processing module.

[0139] The data smoothing processing module can be configured to, after acquiring the normalized data from the first processing layer based on the third processing layer and storing the normalized data, perform smoothing processing on the normalized data based on the third processing layer to obtain smoothed data.

[0140] The data storage module can be specifically configured to store the smoothed data.

[0141] In some embodiments of the present disclosure, the data display module 530 can be specifically configured to acquire the smoothed data corresponding to the target driving data from the third processing layer based on the second processing layer, and perform data rendering and interface display on the smoothed data.

[0142] In some embodiments of the present disclosure, the data processing apparatus 500 can further comprise a data monitoring module.

[0143] The data monitoring module can be configured to, after obtaining the normalized data from the first processing layer based on the third processing layer and storing the normalized data, obtain changed data from the first processing layer based on the third processing layer when the data in the first processing layer is changed, and store the changed data.

[0144] It should be noted that, Figure 5 The data processing apparatus 500 shown can perform each step in the above method embodiments, and achieve each process and effect in the above method embodiments, which will not be repeated here.

[0145] Figure 6 FIG. 1 is a structural schematic diagram of an electronic device provided by an embodiment of the present disclosure.

[0146] In an embodiment of the present disclosure, Figure 6 The electronic device shown can be a server or a terminal, where the terminal specifically includes a vehicle-mounted terminal, a computer, a tablet computer, and the like, which are not limited here.

[0147] As shown in Figure 6 The electronic device can include a processor 610 and a memory 620 storing computer program instructions.

[0148] Specifically, the processor 610 can include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or can be configured as one or more integrated circuits implementing one or more embodiments of the present disclosure.

[0149] The memory 620 can include mass storage for data or instructions. As an example and not by way of limitation, the memory 620 can include a hard disk drive (HDD), a floppy disk drive, flash memory, an optical disc (e.g., a compact disc (CD) or a digital versatile disc (DVD)), a solid-state drive (SSD), a USB drive, or a combination of two or more of these. Where appropriate, the memory 620 can include removable or non-removable (or fixed) media. Where appropriate, the memory 620 can be internal or external to the integrated gateway device. In particular embodiments, the memory 620 is non-volatile, solid-state memory. In particular embodiments, the memory 620 includes read-only memory (ROM). Where appropriate, this ROM can be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically alterable ROM (EAROM), or flash memory, or a combination of two or more of these. The processor 610 can execute instructions, for example, stored in the memory 620 to implement processes of the present disclosure. Furthermore, those instructions can be written as computer programs, for example, executable programs.

[0150] The processor 610 can execute instructions, for example, stored in the memory 620 to implement processes of the present disclosure. Furthermore, those instructions can be written as computer programs, for example, executable programs.

[0151] In one example, the electronic device can also include a transceiver 630 and a bus 640. As shown, the processor 610, the memory 620, and the transceiver 630 are connected by the bus 640 and complete communication among each other. Figure 6

[0152] ​Bus 640 includes a hardware, software, or both that couples components of computer system 600 to each other. As an example without limitation, bus 640 can include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side BUS (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or another suitable bus or a combination of two or more of these. Where appropriate, bus 640 can include one or more buses of the same type or buses of different types.

[0153] The embodiment of the present disclosure further provides a computer readable storage medium, which can store a computer program. When the computer program is executed by a processor, the processor implements the data processing method provided by the embodiment of the present disclosure.

[0154] The computer program is executed by the processor to implement the following steps: obtaining vehicle driving data, performing classification processing on the vehicle driving data to obtain target driving data corresponding to at least one category; inputting the target driving data corresponding to each category into a first processing layer corresponding to the category, performing normalization processing on the target driving data based on the first processing layer to obtain normalized data and store the normalized data; obtaining the normalized data corresponding to the target driving data based on a second processing layer, and performing data rendering and interface display on the normalized data, the second processing layer being at least one page display layer corresponding to the first processing layer.

[0155] The vehicle driving data can be acquired, after the vehicle driving data is acquired, the vehicle driving data is classified according to different data categories, and target driving data corresponding to at least one category is obtained; for the target driving data corresponding to each category, the target driving data is input into a first processing layer corresponding to the category, the target driving data is normalized based on the first processing layer, normalized data is obtained, and the normalized data is stored; the normalized data corresponding to the target driving data is obtained based on a second processing layer, and the normalized data is data-rendered and interface-displayed, the second processing layer being at least one page display layer corresponding to the first processing layer. Thus, the same data of each category can be normalized to ensure the universality of the data, and the data is processed only once and can be used by multiple second processing layers simultaneously or multiple times, thereby realizing data reuse, and when the same data is displayed on multiple screens, the data is processed only once, without the need for processing the data once for each screen to display, thereby reducing the data processing amount and resource consumption and improving the running efficiency of the system.

[0156] In some embodiments of the present disclosure, the normalization of the target driving data based on the first processing layer to obtain and store the normalized data includes: normalizing the data format, data structure and data representation of the target driving data based on the first processing layer to obtain the normalized data; creating a data entity corresponding to the normalized data, and storing the data entity.

[0157] In some embodiments of the present disclosure, before the normalized data is obtained and stored, the method further includes: performing validity detection and rationality detection on the normalized data based on the first processing layer to obtain validity detection results and rationality detection results, the validity detection being used to determine whether the normalized data is empty and whether the data format is abnormal; the rationality detection being used to determine whether the normalized data lacks data agreed in a protocol and whether the numerical range is abnormal.

[0158] The normalized data is stored, including: when the validity detection result and / or the rationality detection result of the normalized data based on the first processing layer is not passed, the normalized data is rejected.

[0159] In some embodiments of the present disclosure, the method further includes: after the normalized data is stored, the normalized data is obtained from the first processing layer based on a third processing layer, and the normalized data is stored, the third processing layer being located between the first processing layer and the second processing layer and having a binding relationship with the first processing layer and the second processing layer, respectively.

[0160] In some embodiments of the present disclosure, after the normalized data is obtained from the first processing layer based on the third processing layer and stored, the method further includes: performing smoothing processing on the normalized data based on the third processing layer to obtain smoothed data.

[0161] The storing of the normalized data includes storing the smoothed data.

[0162] In some embodiments of the present disclosure, the normalized data corresponding to the target driving data is obtained based on the second processing layer, and the normalized data is subjected to data rendering and interface display, including: obtaining the smoothed data corresponding to the target driving data from the third processing layer based on the second processing layer, and performing data rendering and interface display on the smoothed data.

[0163] In some embodiments of the present disclosure, after the normalized data is obtained from the first processing layer based on the third processing layer and stored, the method further includes: when the data in the first processing layer is monitored to change based on the third processing layer, obtaining the changed data from the first processing layer, and storing the changed data.

[0164] The storage medium described above may, for example, include a memory 620 of computer program instructions, which can be executed by the processor 610 of the electronic device to complete the data processing method provided by the embodiments of the present disclosure. Optionally, the storage medium can be a non-transitory computer-readable storage medium, for example, the non-transitory computer-readable storage medium can be a Read-Only Memory (ROM), a Random Access Memory (RAM), an external cache memory, an optical disc read-only memory (Compact Disc ROM, CD-ROM), a magnetic tape, a floppy disk, a flash memory, and an optical data storage device, etc. As an illustration but not limitation, RAM is available in various forms, such as Static Random Access Memory (SRAM) and Dynamic Random Access Memory (DRAM), etc.

[0165] The embodiments of the present disclosure also provide a vehicle including an electronic device, which can realize the various processes and effects in the above-mentioned embodiments of the present disclosure, and details are not repeated here.

[0166] The embodiments of the present disclosure also provide a computer program product, which includes a computer program or instructions, and the computer program or instructions are executed by a processor to realize the data processing method provided by the embodiments of the present disclosure, and can realize the various processes and effects in the above-mentioned embodiments of the present disclosure, and details are not repeated here.

[0167] The foregoing detailed description of the technology has been presented for purposes of illustration and description. Various modifications to the description will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other embodiments without departing from the spirit or scope of the disclosure. Therefore, the disclosure is not intended to be limited to the embodiments described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A data processing method, characterized in that: include: Acquiring vehicle driving data, classifying the vehicle driving data, and obtaining target driving data corresponding to at least one category; For target driving data corresponding to each category, input the target driving data into a first processing layer corresponding to the category, perform normalization processing on the target driving data based on the first processing layer, obtain normalized data, and store the normalized data; Normalized data corresponding to the target driving data is obtained based on the second processing layer, and data rendering and interface display are performed on the normalized data. The second processing layer is at least one page display layer corresponding to the first processing layer.

2. The method according to claim 1, characterized in that The normalizing the target driving data based on the first processing layer to obtain and store normalized data includes: Normalizing the data format, data structure, and data representation of the target driving data based on the first processing layer to obtain the normalized data; A data entity corresponding to the normalized data is created, and the data entity is stored.

3. The method according to claim 1, characterized in that Before obtaining and storing the normalized data, the method further includes: Performing validity testing and rationality testing on the normalized data based on the first processing layer to obtain validity testing results and rationality testing results, wherein the validity testing is used to determine whether the normalized data is empty and whether there is any abnormality in the data format; and the rationality testing is used to determine whether the normalized data lacks data agreed in the protocol and whether there is any abnormality in the value range; Storing the normalized data includes: When it is determined based on the first processing layer that the validity detection result and / or the rationality detection result of the normalized data is failed, the normalized data is eliminated.

4. The method according to claim 1, wherein The method further comprises: After the normalized data is stored, the normalized data is obtained from the first processing layer based on the third processing layer and the normalized data is stored. The third processing layer is located between the first processing layer and the second processing layer, and has a binding relationship with the first processing layer and the second processing layer respectively.

5. The method according to claim 4, characterized in that After acquiring the normalized data from the first processing layer based on the third processing layer and storing the normalized data, the method further includes: performing smoothing processing on the normalized data based on the third processing layer to obtain smoothed data after smoothing processing; The storing of the normalized data includes: The smoothed data is stored.

6. The method according to claim 5, characterized in that The obtaining of normalized data corresponding to the target driving data based on the second processing layer, and performing data rendering and interface display on the normalized data, includes: Based on the second processing layer, smooth data corresponding to the target driving data is obtained from the third processing layer, and data rendering and interface display are performed on the smooth data.

7. The method according to claim 4, characterized in that After acquiring the normalized data from the first processing layer based on the third processing layer and storing the normalized data, the method further includes: When the third processing layer monitors that the data in the first processing layer has changed, the third processing layer obtains the changed data from the first processing layer and stores the changed data.

8. A data processing device, characterized in that: include: a data classification processing module, configured to obtain vehicle driving data, classify the vehicle driving data, and obtain target driving data corresponding to at least one category; a data normalization processing module, configured to input the target driving data corresponding to each category into a first processing layer corresponding to the category, perform normalization processing on the target driving data based on the first processing layer, obtain normalized data, and store the normalized data; A data display module is used to obtain normalized data corresponding to the target driving data based on a second processing layer, and to render and display the normalized data on an interface. The second processing layer is at least one page display layer that corresponds to the first processing layer.

9. An electronic device, characterized in that: include: processor; a memory for storing executable instructions; The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the data processing method according to any one of claims 1 to 7.

10. A vehicle, characterized in that: Comprising the electronic device as claimed in claim 9.

Images