Vehicle machine interface layout system and method thereof

Abstract

The system comprises a human-computer interface layer and a back-end algorithm layer, the human-computer interface layer comprises a human-computer interface configuration file and a human-computer interface display layer, and the back-end algorithm layer is used for obtaining the use condition of a user when the user uses a vehicle machine system through vehicle machine burying points and displaying the use condition of the user when the user uses the vehicle machine system. The man-machine interface layer receives the use condition of the vehicle-mounted terminal and updates the man-machine interface configuration file according to the use condition, and the man-machine interface layer reads the man-machine interface configuration file when being started and arranges the vehicle-mounted terminal APP icon sequence of the man-machine interface display layer according to the content of the man-machine interface configuration file; the use condition of the in-vehicle infotainment system comprises in-vehicle infotainment starting time; compared with a random layout mode of a traditional vehicle machine, the layout system provided by the invention has the advantages that 63% of page turning operation of the user is reduced by collecting use habits of the user and carrying out periodic interface layout updating, and the use experience of the user is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle-machine systems, and in particular to a vehicle-machine interface layout system and method thereof. Background Art

[0002] With the rapid development of science and technology, the functionality of vehicles is becoming more and more diverse. As a component of the vehicle, the vehicle computer system is also constantly updating and improving with the development of information technology. The improvement of vehicle functionality and user experience is increasingly dependent on the vehicle computer system.

[0003] At present, although the car computer system has made great improvements and progress, most of the car computer systems still have certain problems: the layout of the car computer system often does not conform to everyone's usage habits. For some users, there are relatively commonly used functions and car computer APPs, but the APP is relatively far back in the interface layout and list of the car computer. It is often necessary to flip through the pages of the operation interface multiple times to find the car computer APP and use it, which affects the user experience to a certain extent.

[0004] To this end, we propose a vehicle-machine interface layout system and method. Summary of the Invention

[0005] The purpose of the present invention is to provide a vehicle-machine interface layout system and method thereof to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A vehicle-machine interface layout system includes a human-machine interface layer and a back-end algorithm layer. The human-machine interface layer includes a human-machine interface configuration file and a human-machine interface display layer. The back-end algorithm layer is used to obtain the user's usage status when using the vehicle-machine system through vehicle-machine embedding points, and update the human-machine interface configuration file according to the usage status. The human-machine interface layer will read the human-machine interface configuration file when it is started, and arrange the vehicle-machine APP icons of the human-machine interface display layer according to the content of the human-machine interface configuration file.

[0008] As a further solution of the present invention: the usage status of the vehicle system includes the vehicle startup time, the vehicle shutdown time, the vehicle APP opening time, the vehicle APP closing time, the vehicle APP foreground running time, the vehicle APP background running time, the vehicle APP opening position, the vehicle APP interface size and the frequency of use of the vehicle APP.

[0009] As a further solution of the present invention: the back-end algorithm layer collects usage information of the vehicle system to count the usage time L and usage times C of each vehicle APP, and sets different weights for the usage time L and usage times C of different vehicle APPs, and then calculates the weighted average of each vehicle APP, and performs short-term interest ranking and long-term interest ranking on each vehicle APP based on the weighted average value, and then updates the human-machine interface configuration file by combining the two ranking data.

[0010] As a further solution of the present invention: the statistical period of the short-term interest ranking is smaller than the statistical period of the long-term interest ranking.

[0011] As a further solution of the present invention: the human-machine interface display layer includes several display pages for displaying car-machine APP icons, and each display page can display several car-machine APP icons. The car-machine APP icon with higher ranking data will be displayed at the front on the display page.

[0012] As a further solution of the present invention: the back-end algorithm layer also collects the installation and uninstallation status of the car machine APP, and the icon of the newly installed car machine APP is arranged on the first page of the display page by default within a set time period.

[0013] The layout method of the above-mentioned vehicle-machine interface layout system includes the following steps:

[0014] Step 1: Get the last update time. If there is no last update time, select the full data as the short-term interest ranking data; if there is a last update time, get the last updated data ranking and score as the long-term interest ranking data;

[0015] Step 2: Obtain short-term interest data. The time period from the last update to the current time is considered a short-term interest period. Select all tracking data used by the car-mounted app within the short-term interest period from the tracking database.

[0016] Step 3: Build a machine learning statistical model based on embedded data, and calculate the scores of car-mounted apps based on weights according to different car-mounted app types to obtain the scores and rankings of car-mounted apps' short-term interest.

[0017] Step 4: Obtain the score and ranking of long-term interest;

[0018] Step 5: Combine the scores of long-term interest and short-term interest, calculate the overall score and ranking of the car APP according to fixed weights, and then update the human-machine interface configuration file based on the score and ranking.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] Compared with the random layout of traditional car computers, the layout system provided by the present invention reduces the user's page turning operations by 63% by collecting the user's usage habits and performing periodic interface layout updates, thereby greatly improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is the overall flow chart of the vehicle interface layout in the present invention.

[0022] Figure 2 This is a detailed flow chart of the vehicle interface layout in the invention. DETAILED DESCRIPTION

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0024] See also Figure 1 、 Figure 2 The present invention provides a vehicle interface layout system, including a human-machine interface layer and a back-end algorithm layer. The human-machine interface layer includes a human-machine interface configuration file (usually a JSON configuration file) and a human-machine interface display layer;

[0025] The back-end algorithm layer is a deployed model, the function of which is to monitor the user's usage status when using the car system. The usage status includes the frequency of use of the car APP and the size of the window when using the car APP.

[0026] In the present invention, after the vehicle computer is turned on, the human-machine interface layer will read the human-machine interface configuration file, and then perform layout according to the content of the human-machine interface configuration file when the vehicle computer APP is opened; the human-machine interface configuration file includes the layout position of the vehicle computer APP, the opening position and the size of the opened interface, as well as the background hidden mode (background running mode).

[0027] In the present invention, the back-end algorithm layer updates the configuration file of the human-computer interface based on the user's historical usage data, so as to ensure that the user can quickly find the APP they need with as little operation as possible, so as to achieve the purpose of improving the user experience. The historical usage data here includes the usage time of the car APP, the size of the interface when the car APP is used, and the path where the car APP is opened.

[0028] In the present invention, when laying out the car APP, the strategy adopted is that the more opportunities the APP has to be used, the more it should be placed at the front of the interface, and the fewer opportunities the APP has to be used, the more it should appear at the back of the interface or on the next screen.

[0029] Specifically, the present invention adopts a robot learning method to perform statistical analysis on the historical usage information of the car-machine APP, so it is necessary to collect data information such as the opening time of the car-machine APP, the closing time of the car-machine APP, the vehicle start-up time, the vehicle stop time, the size and position of the car-machine after it is turned on, and the time running in the background. All of the above data are obtained through car-machine burying points. Since most car-machine APPs are third-party applications, the present invention generally cannot obtain the specific operations after entering the car-machine APP.

[0030] After obtaining the above data information, the duration L and number C of the car APP are counted, and different weights are set for the duration and number of times respectively. Different weights are set for different car APPs. Here we mainly consider the different types of car APPs. For example, music players and navigation apps are applications that are opened for a long time but not opened very often. Therefore, the weight of the duration should be appropriately reduced and the weight of the number of times should be increased. For apps like air conditioning settings, they will be launched after opening and completing the operation. Therefore, the weight of the duration will be set higher, and the weight of the number of times will be set lower. Then calculate the weighted average of each car APP, so that a series of car APP rankings can be obtained. This ranking is called short-term interest.

[0031] Then, based on the above-mentioned short-term interest ranking and combined with long-term interest (the long-term interest is the data ranking of a longer time interval), the entire APP is ranked at regular intervals. The human-computer interface configuration file is updated in combination with the overall ranking, and an interface update can be obtained to complete an interface layout.

[0032] Combine Figure 1 It can be seen that in the present invention, the layout update of the human-machine interface display layer is completed through the human-machine interface configuration file. The human-machine interface display layer displays the layout of the car-machine APP on the car-machine display screen by reading the contents of the configuration file; and the server side accumulates the historical data of the car-machine APP and calculates the weight ranking of each car-machine APP through the statistical algorithm of the back-end algorithm layer, and then sets and updates the human-machine interface configuration file according to the corresponding rules.

[0033] Please combine the specific Figure 2 , the algorithm logic of the backend algorithm layer is:

[0034] The ranking of car-machine APPs at the back-end algorithm layer consists of two parts: the first part is long-term interest, and the second part is short-term interest; short-term interest includes historical data content within this update cycle, while long-term interest includes all historical data content before this update cycle.

[0035] Step 1: Get the last update time. If the last update time does not exist, select the full data as the short-term interest data. If the last update time exists, get the ranking and score of the last updated data as the long-term interest data.

[0036] Step 2: Obtain short-term interest data. The time period from the last update to the current time is considered as a short-term interest period. Select the tracking data used by all car-mounted apps within the short-term interest period from the tracking database.

[0037] Step 3: Build a machine learning statistical model based on the buried data. According to different types of car-mounted app types (the present invention divides car-mounted app types into two types: one is data tool type, such as car-mounted app control of air conditioning and ambient light adjustment. These types of apps are used on and off quickly and are used for a short time, so the weight of usage time is relatively large; the other type belongs to audio and video entertainment type, such as navigation apps and music players. They take up a lot of time during use, so the weight is more biased towards the number of times used). Calculate the scores and rankings of car-mounted app short-term interest;

[0038] Step 4: Obtain the score and ranking of long-term interests;

[0039] Step 5: Combine the scores of long-term interest and short-term interest, calculate the overall score and ranking of the car APP according to fixed weights, and then update the human-machine interface configuration file based on the score and ranking.

[0040] In one embodiment of the present invention, the vehicle computer uses an AVNT device, whose CPU model is Qualcomm 6145, RAM running capacity is 4GB, ROM storage capacity is 64GB, and the Android Automotive system is Andriod P.

[0041] The vehicle computer tracking data contains over 800 points. This example uses a one-month timeframe, with the last day of each month being the day for updating the vehicle computer interface layout. Over-the-air (OTA) updates are implemented. On the last day of each month, the database retrieves the date of the user's last vehicle computer interface layout based on the VIN code. Unless it's the first time, the retrieved date will be the last day of the previous month. The long-term interest score and ranking are also retrieved from the vehicle computer app score table.

[0042] Obtain the buried data of the car APP. According to the tid corresponding to the vin code, obtain the buried data of the car APP. Since most car APPs are third-party applications, such as music players, the buried data can only obtain the opening and closing information, and cannot obtain the specific playback content. Statistics are made on daily data based on the buried data. In order to obtain short-term interests more accurately, the logic adopted for the data in this embodiment is to calculate on a daily basis. The duration and number of calculation logics are based on the number of days from the current time N and the daily duration L, the number of openings per day C, the total duration = L*0.97^N sum, the total number of times = C*0.97^N sum. The advantage of doing this is that the closer to the present moment, the greater the weight of the data.

[0043] The total score of the car-mounted app is calculated based on the total duration and total number of times. This embodiment divides car-mounted apps into two categories: tools and data, audio, and entertainment. The corresponding duration and number of times matrix is ​​p = [[0.1, 0.9], [0.9, 0.1]]. The total score is calculated by taking the inner product of the vector of total duration and total number of times and p. The score is the short-term interest score.

[0044] Combining the short-term interest score and the long-term interest score, the weighted average is calculated with weights of 0.7 and 0.3 respectively, which is the score of the car APP in the present invention. The ranking is arranged in order from large to small.

[0045] In this embodiment, the car computer has 16 buttons on the first screen. By default, the top 16 buttons are the first screen, and the remaining screens are arranged in order. This ensures that the user can find the car computer APP that is most frequently used with as few page-turning operations as possible, thereby improving the user experience.

[0046] In addition, based on the previous embodiment, when a new APP is downloaded, it will be ranked on the first screen by default. The rule is that the newly downloaded APP has a 10-day protection period. The reason for this rule is that the newly downloaded APP will generally be the frequently used APP in the short term.

[0047] Combined with the above rules, the time point of downloading the APP is counted. If it is an APP within 10 days, it will be sorted according to the APP within 10 days, and the APP over 10 days will be sorted separately. In this way, there are two sequence combinations, and the APPs within the protection period are given priority on the first screen. The strategy adopted is to put the APPs within the protection period in the last few places of the first screen, which is equivalent to if there are two APPs in the protection period, then from the comprehensive ranking point of view, these two APPs should be ranked 15th and 16th, while the top 14 APPs outside the protection period remain unchanged, and the APPs after 15th are shifted back 2 places in ranking, and then the interface layout is carried out according to the rules in the above embodiment. This can ensure that the original APP layout is not adjusted too much, and the number of operations of the newly downloaded APP can be reduced as much as possible.

[0048] In addition, because each user has different usage habits, there is a situation where the car machine APP that is used less frequently cannot be found. Therefore, a one-key restore setting is added in some preferred embodiments of the present invention, which can largely avoid the occurrence of such operations.

[0049] Through data verification based on historical data, the layout system provided by the present invention reduces page turning operations by 63% compared to the random layout method of traditional car computers, greatly improving the user experience.

[0050] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A vehicle interface layout system, characterized by: It includes a human-machine interface layer and a back-end algorithm layer. The human-machine interface layer includes a human-machine interface configuration file and a human-machine interface display layer. The back-end algorithm layer is used to obtain the user's usage status when using the car-machine system through the car-machine embedding point, and update the human-machine interface configuration file according to the usage status. The human-machine interface layer will read the human-machine interface configuration file when it starts, and arrange the car-machine APP icons of the human-machine interface display layer according to the content of the human-machine interface configuration file.

2. The vehicle interface layout system according to claim 1, characterized in that: The usage status of the vehicle system includes the vehicle startup time, vehicle shutdown time, vehicle APP opening time, vehicle APP closing time, vehicle APP foreground running time, vehicle APP background running time, vehicle APP opening position, vehicle APP interface size and vehicle APP usage frequency.

3. The vehicle-machine interface layout system according to claim 2, characterized in that: The back-end algorithm layer collects usage information of the vehicle system to collect statistics on the usage time L and usage times C of each vehicle APP, and sets different weights for the usage time L and usage times C of different vehicle APPs. It then calculates the weighted average of each vehicle APP, and performs short-term interest ranking and long-term interest ranking on each vehicle APP based on the weighted average. The human-machine interface configuration file is then updated based on the two ranking data.

4. The vehicle interface layout system according to claim 3, characterized in that: The statistical period of the short-term interest ranking is shorter than the statistical period of the long-term interest ranking.

5. The vehicle interface layout system according to claim 3, characterized in that: The human-machine interface display layer includes several display pages for displaying vehicle-machine APP icons, and each display page can display several vehicle-machine APP icons. The vehicle-machine APP icon with higher ranking data is displayed at a front position on the display page.

6. The vehicle interface layout system according to claim 5, characterized in that: The backend algorithm layer also collects the installation and uninstallation status of the car-machine APP. The icon of the newly installed car-machine APP is arranged on the first page of the display page by default within the set time period.

7. A layout method for a vehicle-machine interface layout system according to any one of claims 1 to 6, characterized in that: The following steps are involved: Step 1: Get the last update time. If the last update time does not exist, select the full data as the short-term interest ranking data; If there is a last update time, the data ranking and score of the last update are obtained as the data of the long-term interest ranking; Step 2: Obtain short-term interest data. The time period from the last update to the current time is considered a short-term interest period. Select all tracking data used by the car-mounted app within the short-term interest period from the tracking database. Step 3: Build a machine learning statistical model based on embedded data, and calculate the scores of car-mounted apps based on weights according to different car-mounted app types to obtain the scores and rankings of car-mounted apps' short-term interest. Step 4: Obtain the score and ranking of long-term interest; Step 5: Combine the scores of long-term interest and short-term interest, calculate the overall score and ranking of the car APP according to fixed weights, and then update the human-machine interface configuration file based on the score and ranking.

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