Method, device and storage medium for managing vehicle calibration database

Abstract

The present invention relates to a method, an apparatus, and a storage medium for managing a vehicle calibration database. The portable device includes a communication unit and a processing unit. The method includes: A. generating a calibration database, the calibration database including one or more sets of calibration data and a default tag set associated with each set of calibration data; B. obtaining a current tag set associated with a user account from a vehicle end and a digital key end in response to a calibration request; C. respectively calculating the degree of association between the current tag set and one or more sets of default tag sets; and D. selecting a set of calibration data from the calibration database as the calibration data to be issued based at least on the degree of association. The scheme for managing a vehicle calibration database proposed in the present invention can reduce the randomness of the issuance of calibration data, improve the positioning accuracy of the digital key and the user's experience, and adaptively adjust and update the existing calibration database.

Description

Technical Field

[0001] The present invention relates to the automotive field, and more particularly to a method for managing a vehicle calibration database, a data processing device, a storage medium, and a terminal device with a digital key function. Background Art

[0002] Nowadays, more and more passenger cars use mobile phone Bluetooth as digital keys to replace traditional physical keys. Digital keys based on Bluetooth technology rely on the signal strength information between the vehicle's Bluetooth antenna and the smart device for positioning during Bluetooth positioning. When performing Bluetooth positioning, the Bluetooth positioning algorithm calculates the position of the smart device relative to the vehicle based on the signal strength between the current vehicle's Bluetooth antenna and the smart device, combined with calibration data.

[0003] However, compared with physical keys, digital keys have problems such as instability and poor positioning. One of the main reasons is that different mobile phone brands and models use different hardware chips, antennas, and powers. If the vehicle uses a fixed receiving power to respond to mobile phone requests, or uses a set of calibration parameters to adapt to the combination of hundreds of mainstream smartphones or smart wearable devices on the market, there is too much randomness, resulting in a very poor performance experience.

[0004] In addition, most of the current cloud service platforms for car computers and mobile phone applications are not interconnected. For example, the cloud services for car computers and mobile phones are provided by two or more suppliers. Most platforms, including OnStar, Mercedes Cloud, and E-Car, only support the transmission of a portion of public data (for example, simple instructions such as user names and remote operation commands), and there is no interoperable platform database that can achieve adaptive optimization of mobile phones and car computers. Summary of the invention

[0005] According to one aspect of the present invention, a method for managing a vehicle calibration database is provided, characterized in that it includes the following steps: A. generating a calibration database, the calibration database including one or more sets of calibration data and a default tag set associated with each set of calibration data; B. obtaining a current tag set associated with a user account from a vehicle end and a digital key end in response to a calibration request; C. respectively calculating the degree of association between the current tag set and the one or more sets of default tag sets; and

[0006] D. Selecting a set of calibration data from the calibration database at least based on the correlation as the calibration data to be sent.

[0007] As an alternative or supplement to the above solution, the method according to an embodiment of the present invention also includes: E. transmitting the issued calibration data to the vehicle end and the digital key end, and the digital key end includes a smart phone and a smart wearable device.

[0008] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, the tag set includes one or more of the following items: vehicle model label, device type label, device model label, operating system version label, application version label, antenna performance label.

[0009] As an alternative or supplement to the above solution, in a method according to an embodiment of the present invention, in step C, the correlation R between the current tag set and the one or more default tag sets is calculated using the following formula:

[0010] R = a×R1 + b×R2 + c×R3 + d×R4 + e×R5 + f×R6

[0011] a + b + c + d + e + f = 1

[0012] Among them, R1 is the device type association, R2 is the operating system association, R3 is the device model association, R4 is the application version association, R5 is the antenna performance association, R6 is the adaptive association, and a, b, c, d, e, and f are preset coefficients.

[0013] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, step D includes: D1, if the maximum degree of association among the degrees of association is greater than or equal to a first threshold, selecting the calibration data corresponding to the maximum degree of association as the calibration data to be sent down; and D2, if the maximum degree of association among the degrees of association is less than the first threshold, selecting the default calibration data as the calibration data to be sent down.

[0014] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, step D further includes: D3, obtaining positioning parameters in the calibration process from the vehicle end and the digital key end, the positioning parameters including antenna field strength parameters, distance parameters, distance-field strength characteristic curve, and result parameters; D4, using the positioning parameters to train a ranging model, and generating new calibration data based on the ranging model; and D5, using the new calibration data to update the calibration database.

[0015] According to another aspect of the present invention, a data processing device for managing a vehicle calibration database is provided, comprising: a memory; a processor; and a computer program stored on the memory and executable on the processor, wherein the execution of the computer program causes the following steps to be performed: A. generating a calibration database, the calibration database comprising one or more sets of calibration data and a default tag set associated with each set of calibration data; B. obtaining a current tag set associated with a user account from a vehicle end and a digital key end in response to a calibration request; C. respectively calculating the degree of association between the current tag set and the one or more sets of default tag sets; and D. selecting a set of calibration data from the calibration database as the calibration data to be issued based at least on the degree of association.

[0016] As an alternative or supplement to the above scheme, in an apparatus according to an embodiment of the present invention, the operation of the computer program also causes the following steps to be executed: E. transmitting the issued calibration data to a vehicle controller and a key device, wherein the key device includes a smart phone and a smart wearable device.

[0017] As an alternative or supplement to the above scheme, in an apparatus according to an embodiment of the present invention, the tag set includes one or more of the following items: vehicle model label, device type label, device model label, operating system version label, application version label, antenna performance label.

[0018] As an alternative or supplement to the above solution, in an apparatus according to an embodiment of the present invention, the execution of the computer program causes step C to be performed in the following manner:

[0019] The correlation R between the current tag set and the one or more default tag sets is calculated using the following formula:

[0020] R = a×R1 + b×R2 + c×R3 + d×R4 + e×R5 + f×R6

[0021] a + b + c + d + e + f = 1

[0022] Among them, R1 is the device type association, R2 is the operating system association, R3 is the device model association, R4 is the application version association, R5 is the antenna performance association, R6 is the adaptive association, and a, b, c, d, e, and f are preset coefficients.

[0023] As an alternative or supplement to the above scheme, in an apparatus according to an embodiment of the present invention, the operation of the computer program causes step D to be executed in the following manner: D1. If the maximum degree of association among the degrees of association is greater than or equal to a first threshold, the calibration data corresponding to the maximum degree of association is selected as the calibration data to be sent; and D2. If the maximum degree of association among the degrees of association is less than the first threshold, the default calibration data is selected as the calibration data to be sent.

[0024] As an alternative or supplement to the above scheme, in an apparatus according to an embodiment of the present invention, the operation of the computer program also causes step D to be executed in the following manner: D3, obtaining positioning parameters in the calibration process from the vehicle end and the digital key end, the positioning parameters including antenna field strength parameters, distance parameters, distance-field strength characteristic curve, and result parameters; D4, using the positioning parameters to train a ranging model, and generating new calibration data based on the ranging model; and D5, using the new calibration data to update the calibration database.

[0025] According to another aspect of the present invention, there is provided a computer-readable storage medium storing a computer program, wherein the program implements any one of the methods described above when executed by a processor.

[0026] According to another aspect of the present invention, a terminal device with a digital key function is provided, comprising: a memory; a processor; and a computer program stored on the memory and executable on the processor, wherein the execution of the computer program results in the following operations: A. in response to a digital key activation command, obtaining one or more default tag sets from a calibration database end; B. respectively calculating the current tag set associated with a user account and the degree of association between the one or more default tag sets; and C. sending a calibration request to the calibration database end based at least on the degree of association for downloading corresponding calibration data.

[0027] As an alternative or supplement to the above scheme, in a device according to an embodiment of the present invention, the operation of the computer program causes step C to be executed in the following manner: C1. If the maximum degree of association among the degrees of association is greater than or equal to a first threshold, a first request is sent to the calibration database end to download calibration data corresponding to the maximum degree of association; and C2. If the maximum degree of association among the degrees of association is less than the first threshold, a second request is sent to the calibration database end to download default calibration data.

[0028] As an alternative or supplement to the above scheme, in a device according to an embodiment of the present invention, the operation of the computer program also causes one or more of the following steps to be executed: D. downloading corresponding calibration data from the calibration database end; E. obtaining positioning parameters during the calibration process, the positioning parameters including antenna field strength parameters, distance parameters, distance-field strength characteristic curve, and result parameters; and F. transmitting the positioning parameters to the calibration database end for updating the calibration database.

[0029] On the one hand, the solution for managing the vehicle calibration database proposed in the present invention can perform label management on user account information (for example, the vehicle model, device type, device model, operating system version, application version, antenna performance, etc. used by the user), and innovatively proposes the concept of the correlation between the current user information and the calibration data (that is, the correlation between the current label set associated with the user account and the default label set already existing on the calibration database side), so that users can quickly and efficiently download calibration data that matches their current account information, thereby reducing the randomness of the calibration data issuance and improving the positioning accuracy of the digital key and the user experience.

[0030] On the other hand, the solution for managing the vehicle calibration database proposed in the present invention can record the positioning parameters in real time according to the actual calibration situation of the digital key, and adaptively adjust the calibration data that has been stored. According to some embodiments, the calibration data corresponding to the association with the maximum value can be downloaded when the association is high (for example, for the calibration database, the digital key end is a known device, or the key tag is known) to provide the best positioning experience. According to another embodiment, the default calibration data can be downloaded when the association is low (for example, for the calibration database, the key tag of the digital key end is unknown), and the positioning parameters in the calibration process are recorded and uploaded at a high frequency to train and obtain new calibration data, thereby updating the existing calibration database.

[0031] In addition, the present invention proposes a solution for interconnecting the vehicle side, the digital key side, and the calibration database side, so that the calibration data corresponding to different devices does not need to be stored on the vehicle side, thereby saving storage space on the vehicle side. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The above and / or other aspects and advantages of the present invention will become clearer and easier to understand through the following description in conjunction with the accompanying drawings, in which the same or similar elements are represented by the same reference numerals. The accompanying drawings include:

[0033] Figure 1 is a schematic flow chart of a method 10 for managing a vehicle calibration database according to an embodiment of the present invention;

[0034] Figure 2 is a schematic block diagram of a data processing device 20 for managing a vehicle calibration database according to an embodiment of the present invention;

[0035] Figure 3 is a schematic block diagram of a terminal device 30 having a digital key function according to an embodiment of the present invention; and

[0036] Figure 4 FIG. 4 is a schematic flow chart of a calibration data download process 40 according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In this specification, the present invention is more fully described with reference to the accompanying drawings in which exemplary embodiments of the present invention are illustrated. However, the present invention may be implemented in different forms and should not be construed as being limited to the embodiments given herein. The embodiments given are intended to make the disclosure herein comprehensive and complete, so as to more fully convey the scope of the present invention to those skilled in the art.

[0038] It should be noted that the terms "first", "second", etc. in this document are used to distinguish similar objects, and are not necessarily used to describe the order of objects in terms of time, space, size, etc. In addition, unless otherwise specifically stated, the terms "including", "having" and similar expressions in this document are intended to indicate non-exclusive inclusion.

[0039] In this specification, the term "vehicle" or other similar terms include general motor vehicles, such as passenger cars (including sports utility vehicles, buses, trucks, etc.), various commercial vehicles, etc., and include hybrid electric vehicles, electric vehicles, plug-in hybrid electric vehicles, etc. A hybrid electric vehicle is a vehicle with two or more power sources, such as gasoline-powered and electric vehicles.

[0040] In this specification, the term "digital key terminal" refers to any electronic device that can be used to unlock a vehicle, which may include but is not limited to: wearable electronic devices such as smart watches, smart bracelets, smart necklaces, smart keys, and mobile terminals such as smart phones.

[0041] In order to better understand the present invention, the meaning of digital key calibration is briefly introduced here. Digital keys can achieve keyless entry and one-button start. In order to ensure safety, the vehicle communication module needs to use sensors to comprehensively determine whether the distance between the digital key end (for example, smart key or mobile phone) and the vehicle is within the effective range (for example, less than or equal to 3 meters). In view of the differences between different digital key ends, in order to ensure the accuracy of the vehicle's positioning of the digital key end, calibration is required before use. The calibration process requires the collection of RSSI (Received Signal Strength Indicator) when the digital key end is at different positions inside and outside the vehicle as a positioning parameter.

[0042] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings.

[0043] Reference now Figure 1 , Figure 1 FIG. 1 is a schematic flow chart of a method 10 for managing a vehicle calibration database according to an embodiment of the present invention.

[0044] In step S110 , a calibration database is generated, where the calibration database includes one or more sets of calibration data and a default label set associated with each set of calibration data.

[0045] Exemplarily, the calibration data refers to a threshold distance parameter used to determine whether to execute a vehicle state switch (e.g., automatic unlocking, automatic locking, trunk opening, etc.). Optionally, the calibration data may include one or more of a key activation determination threshold, a vehicle start determination threshold, a vehicle keyless entry determination threshold, a vehicle welcome determination threshold, a vehicle automatic unlock determination threshold, a vehicle automatic locking determination threshold, and a trunk opening determination threshold.

[0046] It is understandable that the digital key calibration data of each vehicle model matching different digital key terminals needs to be pre-stored in the calibration database (e.g., cloud database). Optionally, in step S110, the digital key calibration data of each vehicle model corresponding to the digital key terminal of each device type, each device model, each operating system version, each application version, and each antenna performance version can be obtained in advance by manual calibration and stored in the calibration database.

[0047] Optionally, a label for each device type, each device model, each operating system version, each application version, and each antenna performance version may be pre-generated as a default label, and the label set may be matched to the corresponding calibration data in a hashing manner. For example, the first set of calibration data and its corresponding first label set may be stored in the calibration database, and the second set of calibration data and its corresponding second label set may be stored in the calibration database, and so on. In the calibration database, each set of calibration data corresponds one-to-one to its default label set.

[0048] In step S120 , in response to the calibration request, the current tag set associated with the user account is obtained from the vehicle side and the digital key side.

[0049] For example, when the user starts the smart key program on the digital key end, the digital key end can send a calibration request to the calibration database end through the network and access the calibration database. Optionally, the vehicle end can also send a calibration request to the calibration database end and access the calibration database.

[0050] Optionally, after receiving the calibration request from the vehicle and / or digital key, the calibration database may verify the identity information of the vehicle and / or digital key, and after the verification is successful, send a response message indicating that the identity authentication is successful to the vehicle and / or digital key. Optionally, after the identity authentication is successful, the vehicle and digital key may send the current tag set associated with the user account to the calibration database.

[0051] Optionally, the current tag set may include one or more of the following: a vehicle model tag, a device type tag, a device model tag, an operating system version tag, an application version tag, and an antenna performance tag.

[0052] In step S130, the association degree between the current tag set and one or more default tag sets may be calculated respectively. Exemplarily, the association degree may be calculated by the calibration database end, and the association degree reflects the matching degree between the current tag set and the stored default tag set.

[0053] Optionally, the correlation R between the current tag set and one or more default tag sets may be calculated using the following formula:

[0054] R = a×R1 + b×R2 + c×R3 + d×R4 + e×R5 + f×R6 (Formula 1)

[0055] a + b + c + d + e + f = 1 (Equation 2)

[0056] Among them, R1 is the device type association, R2 is the operating system association, R3 is the device model association, R4 is the application version association, R5 is the antenna performance association, R6 is the adaptive association, and a, b, c, d, e, and f are preset coefficients.

[0057] Alternatively, a = 0.4, b = 0.2, c = 0.2, d = 0.1, e = 0.05, f = 0.05.

[0058] Optionally, the device type association R1 refers to the degree of matching between the device type of the current digital key end and the default device type. For example, if the device type of the current digital key end is a smart phone, and the default device type indicated by the device type label in the set of default labels is a smart watch, then R1 = 0; if the device type of the current digital key end and the default device type indicated by the device type label in the set of default labels are both smart watches, then R1 = 1.

[0059] Optionally, the operating system association R2 refers to the degree of matching between the operating system of the current digital key terminal and the default operating system. Exemplarily, if the operating system of the current digital key terminal and the default operating system referred to by the operating system label in the set of default labels belong to a cross-platform system (e.g., the current operating system is Linux, and the default operating system is RTOS), then R2 = 0; if the operating system of the current digital key terminal and the default operating system referred to by the operating system label in the set of default labels belong to a cross-platform system (e.g., the current operating system is Linux, and the default operating system is RTOS), then R2 = 0.5; if the operating system of the current digital key terminal and the default operating system referred to by the operating system label in the set of default labels belong to a cross-operating system version system (e.g., the current operating system is Linux xx.1, and the default operating system is Linux xx.2), then R2 = 0.8; if the operating system of the current digital key terminal is the same as the default operating system referred to by the operating system label in the set of default labels, then R2 = 1.

[0060] Optionally, the device model association degree R3 refers to the degree of matching between the device model of the current digital key end and the default device model. Exemplarily, if the device model of the current digital key end and the default device model referred to by the device model label in the set of default labels belong to cross-model models (e.g., the current device model is Android OPPO, and the default device model is Android VIVO), then R3 = 0; if the device model of the current digital key end and the default device model referred to by the device model label in the set of default labels belong to cross-model platform models (e.g., the current device model is Huawei Mate 40, and the default device model is Huawei Mate 40 pro), then R3 = 0.5; if the device model of the current digital key end is the same as the default device model referred to by the device model label in the set of default labels, then R3 = 1.

[0061] Optionally, the application version association R4 refers to the degree of matching between the application version of the current digital key and the default application version. For example, if the application version of the current digital key and the default application version indicated by the application version label in the default label set belong to the same version across major versions, then R4 = 0; if they belong to the same version across minor versions, then R4 = 0.2; if they are equal, then R4 = 1.

[0062] Optionally, the antenna performance correlation R5 refers to the degree of matching between the antenna performance version of the current digital key and the default antenna performance version. Exemplarily, if the antenna performance version of the current digital key and the default antenna performance version indicated by the antenna performance version tag in the default tag set belong to a cross-large version (for example, the current antenna performance version is Bluetooth 5.0, and the default antenna performance version is Bluetooth 4.0), then R5 = 0; if they belong to a cross-small version (for example, the current antenna performance version is Bluetooth 4.3, and the default antenna performance version is Bluetooth 4.2), then R5 = 0.2; if they are equal, then R5 = 1.

[0063] Optionally, the adaptive correlation degree R6 is a preset fixed value, or refers to the matching degree of other variable environmental factors such as software environment version.

[0064] In step S140, a group of calibration data is selected from the calibration database as the calibration data to be sent based at least on the correlation degree. Exemplarily, the calibration data to be sent may be selected based on the calculated magnitude of one or more correlation degrees.

[0065] Optionally, the calibration data corresponding to the calculated maximum correlation degree may be selected as the calibration data to be sent. For example, if the correlation degree between the current label set and the first default label set is 0.32, and the correlation degree between the current label set and the second default label set is 0.74, then the second set of calibration data corresponding to the second default label set may be directly selected as the calibration data to be sent.

[0066] Optionally, the calibration data may be selected to be sent by comparing the calculated correlation degree with a preset threshold.

[0067] Exemplarily, if the maximum degree of association among the degrees of association is greater than or equal to a first threshold, a set of calibration data corresponding to the maximum degree of association is selected as the calibration data to be sent; and if the maximum degree of association among the degrees of association is less than the first threshold, default calibration data is selected as the calibration data to be sent. Exemplarily, the first threshold is 0.8.

[0068] The numerical range of the preset value (eg, the first threshold value, etc.) described herein can be set according to actual needs and is not limited to the numerical range shown in this embodiment.

[0069] For example, if the calculated maximum correlation is high (for example, greater than or equal to 0.8), it can be considered that the current digital key terminal is a known device for the calibration database, or the key tags (for example, device type tags, operating system tags, device model tags, etc.) are known. In this case, the calibration data corresponding to the maximum correlation can be selected as the calibration data to be issued to provide the best positioning experience.

[0070] For example, if the calculated maximum correlation is low (for example, less than 0.8), it can be considered that the current digital key terminal is an unknown device for the calibration database, or the key tag is unknown. In this case, the default calibration data can be directly selected as the calibration data to be issued, and the positioning parameters in the calibration process can be recorded and uploaded at a high frequency to train and obtain new calibration data, and the new calibration data can be used to update the existing calibration database.

[0071] Optionally, the calibration database can be updated according to the following process: obtaining positioning parameters during the calibration process from the vehicle end and the digital key end, the positioning parameters including antenna field strength parameters, distance parameters, distance-field strength characteristic curve, and result parameters; using the positioning parameters to train the ranging model to generate new calibration data; and using the new calibration data to update the calibration database.

[0072] Exemplarily, the ranging model is constructed based on a training data set that includes positioning parameters (e.g., antenna field strength parameters, distance parameters, distance-field strength characteristic curve) and result parameter annotations that characterize whether the vehicle successfully performs a vehicle state switch (e.g., automatic unlocking, automatic locking, trunk opening, etc.).

[0073] Exemplarily, the vehicle side and the digital key side can be calibrated according to the calibration data downloaded from the calibration database side. Optionally, the vehicle side and the digital key side can communicate data through Bluetooth connection, NFC (Near Field Communication) connection, and UWB (Ultra Wideband) connection, and the vehicle side determines the exact position of the digital key side. The vehicle side can determine whether the digital key side is outside or inside the car, how far it is from the vehicle side, etc. based on the RSSI value and calibration data of the current digital key side. After the vehicle side determines the exact position of the digital key side, it can send the location information to the keyless entry and start system (PEPS) to perform subsequent operations (for example, opening the door, starting the car, etc.). The content here is not the focus of the present invention and will not be described in detail here.

[0074] Optionally, after the calibration process is completed, the vehicle end and / or the digital key end can transmit the positioning parameters recorded during the calibration process (e.g., antenna field strength parameters, distance parameters, distance-field strength characteristic curve, and result parameters) to the calibration database end. The calibration database end can use the above positioning parameters to train the ranging model, and continuously update and adaptively adjust the existing calibration data in the calibration database.

[0075] Optionally, the calibration database can be manually maintained regularly to discard or merge invalid calibration data. Optionally, the subclass calibration database can also be automatically called or completed from the parent class calibration database according to the preset global dependency and inheritance relationship. For example, iPhone X can automatically inherit the calibration data of iPhone 8, and Apple watch can automatically inherit the calibration data of iPhone.

[0076] Continue to refer Figure 2 , Figure 2 FIG. 2 is a schematic block diagram of a data processing device 20 for managing a vehicle calibration database according to an embodiment of the present invention. Figure 2 The device 20 shown can be used to implement Figure 1 The process shown in .

[0077] like Figure 2As shown, the data processing device 20 includes a communication unit 210, a memory 220 (e.g., a non-volatile memory such as a flash memory, a ROM, a hard disk drive, a magnetic disk, an optical disk, etc.), a processor 230 (e.g., a microprocessor, a microcontroller, etc.), and a computer program 240 stored on the memory 220 and executable on the processor 230.

[0078] The communication unit 210 serves as a communication interface and is configured to establish a communication connection between the apparatus and an external device or network (eg, a vehicle end, a digital key end).

[0079] The memory 220 stores a computer program 240 executable by the processor 230. The processor 230 is configured to execute the computer program 240 to implement the corresponding process for managing the vehicle calibration database. The process for managing the vehicle calibration database has been described in detail above and will not be repeated here.

[0080] Figure 3 1 is a schematic block diagram of a terminal device 30 with a digital key function according to an embodiment of the present invention. By way of example, the terminal device 30 may be a wearable electronic device such as a smart watch, a smart bracelet, a smart necklace, a smart key, or a mobile terminal such as a smart phone.

[0081] like Figure 3 As shown, the terminal device 30 includes a communication unit 310 , a memory 320 , a processor 330 , and a computer program 340 stored in the memory 320 and executable on the processor 330 .

[0082] The communication unit 310 serves as a communication interface and is configured to establish a communication connection between the apparatus and an external device or network (eg, a vehicle side, a calibration database side).

[0083] The memory 320 stores a computer program 340 executable by the processor 330. The processor 330 is configured to execute the computer program 340 to implement the following Figure 4 The calibration data download process is shown.

[0084] Continue to refer Figure 4 , which shows a schematic flow chart of a calibration data download process 40 according to an embodiment of the present invention.

[0085] In step S410, the vehicle end or the digital key end obtains one or more default tag sets from the calibration database end in response to the digital key activation command.

[0086] In step S420, the vehicle end or the digital key end respectively calculates the correlation between the current tag set associated with the user account and one or more default tag sets.

[0087] In step S430, the vehicle end or the digital key end sends a calibration request to the calibration database end based on at least the association degree, so as to download the corresponding calibration data. Optionally, step S410 includes: if the maximum association degree in the association degree is greater than or equal to a first threshold, sending a first request to the calibration database end to download the calibration data corresponding to the maximum association degree; and C2, if the maximum association degree in the association degree is less than the first threshold, sending a second request to the calibration database end to download the default calibration data.

[0088] Optionally, the process 40 may further include step S440: downloading corresponding calibration data from the calibration database.

[0089] Optionally, the process 40 may further include step S450: acquiring positioning parameters during the calibration process, the positioning parameters including antenna field strength parameters, distance parameters, distance-field strength characteristic curve, and result parameters; and

[0090] Optionally, the process 40 may further include step S460: transmitting the positioning parameters to the calibration database end for updating the calibration database.

[0091] According to another aspect of the present invention, there is also provided a computer readable storage medium storing a computer program, which, when executed by a processor, implements the following Figure 1 or Figure 4 The computer-readable storage medium may include a random access memory (RAM) such as a synchronous dynamic random access memory (SDRAM), a read-only memory (ROM), a non-volatile random access memory (NVRAM), an electrically erasable programmable read-only memory (EEPROM), flash memory, other known storage media, etc.

[0092] According to some embodiments of the present invention, by managing user account information in a labeling manner and calculating the correlation between the current user information and the default label set, users can quickly and efficiently download calibration data that matches their current account information, thereby reducing the randomness of the calibration data being sent down and improving the positioning accuracy of the digital key and the user experience.

[0093] According to some embodiments of the present invention, the positioning parameters during the actual calibration process of the digital key can be recorded and uploaded to train and obtain new calibration data, so that the data in the calibration database can be adaptively updated according to changes in the digital key end and changes in the actual positioning situation.

[0094] It should be understood that some of the block diagrams shown in the accompanying drawings of the present invention are functional entities, which do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0095] It should also be understood that in some alternative embodiments, the functions / steps included in the foregoing method may not occur in the order shown in the flow chart. For example, two functions / steps shown in sequence may be performed substantially simultaneously or even in reverse order. This specifically depends on the functions / steps involved.

[0096] In addition, it is easy for a person skilled in the art to understand that the methods provided by one or more embodiments of the present invention can be implemented by a computer program. For example, when a computer storage medium (such as a USB flash drive) storing the computer program is connected to a computer, the methods of one or more embodiments of the present invention can be executed by running the computer program.

[0097] Although only some of the embodiments of the present invention are described above, it should be understood by those skilled in the art that the present invention can be implemented in many other forms without departing from its subject matter and scope. Therefore, the examples and embodiments shown are considered to be illustrative rather than restrictive, and the present invention may include various modifications and substitutions without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A method for managing a vehicle calibration database, characterized in that: The following steps are involved: A. generating a calibration database, wherein the calibration database includes one or more sets of calibration data and a default label set associated with each set of calibration data; B. In response to the calibration request, obtain the current tag set associated with the user account from the vehicle and the digital key; C. respectively calculating the association degree between the current tag set and the one or more default tag sets; as well as D. Selecting a set of calibration data from the calibration database at least based on the association as the calibration data to be issued, wherein step D comprises: D1. If the maximum degree of association among the degrees of association is greater than or equal to a first threshold, selecting a set of calibration data corresponding to the maximum degree of association as the calibration data to be issued; and D2. If the maximum degree of association among the degrees of association is less than a first threshold, select default calibration data as the calibration data to be sent.

2. The method according to claim 1, further comprising: E. Transmit the sent calibration data to the vehicle end and the digital key end, where the digital key end includes a smart phone and a smart wearable device.

3. The method according to claim 1, wherein: The current tag set and / or default tag set includes one or more of the following: vehicle type label, device type label, device model label, operating system version label, application version label, antenna performance label.

4. According to the method of claim 1, in step C, the correlation R between the current tag set and the one or more default tag sets is calculated using the following formula: R=a×R1+b×R2+c×R3+d×R4+e×R5+f×R6 a+b+c+d+e+f=1, where R1 is the device type association, R2 is the operating system association, R3 is the device model association, R4 is the application version association, R5 is the antenna performance association, R6 is the adaptive association, and a, b, c, d, e, and f are preset coefficients.

5. The method according to claim 1, wherein: Step D further comprises: D3. Acquire positioning parameters in the calibration process from the vehicle end and the digital key end, wherein the positioning parameters include antenna field strength parameters, distance parameters, distance-field strength characteristic curve, and result parameters; D4. Training a distance measurement model using the positioning parameters, and generating new calibration data based on the distance measurement model; and D5. Update the calibration database using the new calibration data.

6. A data processing device for managing a vehicle calibration database, comprising: Memory; processor; as well as A computer program stored on the memory and executable on the processor, the execution of which causes the following steps to be performed: A. generating a calibration database, wherein the calibration database includes one or more sets of calibration data and a default label set associated with each set of calibration data; B. In response to the calibration request, obtain the current tag set associated with the user account from the vehicle and the digital key; C. respectively calculating the association degree between the current tag set and the one or more default tag sets; as well as D. Selecting a set of calibration data from the calibration database at least based on the correlation as the calibration data to be issued, wherein step D comprises: D1. If the maximum degree of association among the degrees of association is greater than or equal to a first threshold, selecting a set of calibration data corresponding to the maximum degree of association as the calibration data to be issued; and D2. If the maximum degree of association among the degrees of association is less than a first threshold, select default calibration data as the calibration data to be sent.

7. The apparatus according to claim 6, wherein the execution of the computer program further causes the following steps to be performed: E. Transmitting the issued calibration data to a vehicle controller and a key device, wherein the key device includes a smart phone and a smart wearable device.

8. The device according to claim 6, wherein: The current tag set and / or default tag set includes one or more of the following: vehicle type label, device type label, device model label, operating system version label, application version label, antenna performance label.

9. The apparatus according to claim 6, wherein the operation of the computer program causes step C to be performed in the following manner: calculating the correlation R between the current tag set and the one or more default tag sets using the following formula: R=a×R1+b×R2+c×R3+d×R4+e×R5+f×R6 a+b+c+d+e+f=1, where R1 is the device type association, R2 is the operating system association, R3 is the device model association, R4 is the application version association, R5 is the antenna performance association, R6 is the adaptive association, and a, b, c, d, e, and f are preset coefficients.

10. The device according to claim 6, wherein: The execution of the computer program also causes step D to be performed in the following manner: D3. Acquire positioning parameters in the calibration process from the vehicle end and the digital key end, wherein the positioning parameters include antenna field strength parameters, distance parameters, distance-field strength characteristic curve, and result parameters; D4. Training a distance measurement model using the positioning parameters, and generating new calibration data based on the distance measurement model; and D5. Update the calibration database using the new calibration data.

11. A computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium, characterized in that: When the instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 5.

12. A terminal device with a digital key function, comprising: Memory; processor; as well as A computer program stored on the memory and executable on the processor, the execution of which results in the following operations: A. Responding to a digital key activation command, obtaining one or more default tag sets from a calibration database; B. respectively calculating the association degree between the current tag set associated with the user account and the one or more default tag sets; as well as C. Sending a calibration request to the calibration database end at least based on the association degree to download corresponding calibration data, wherein step C includes: C1. If the maximum degree of association among the degrees of association is greater than or equal to a first threshold, sending a first request to the calibration database end to download calibration data corresponding to the maximum degree of association; and C2. If the maximum degree of association among the degrees of association is less than a first threshold, a second request is sent to the calibration database end to download default calibration data.

13. The terminal device according to claim 12, wherein the execution of the computer program further causes one or more of the following steps to be performed: D. downloading the corresponding calibration data from the calibration database; E. acquiring positioning parameters during the calibration process, wherein the positioning parameters include antenna field strength parameters, distance parameters, distance-field strength characteristic curve, and result parameters; and F. Transmitting the positioning parameters to the calibration database end for updating the calibration database.

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