A method for allocating vehicle Bluetooth key permissions for multi-device collaborative management

Abstract

The present invention relates to the technical field of vehicle Bluetooth key control, and relates to a method for allocating vehicle Bluetooth key permissions for multi-device collaborative management. The present invention receives a Bluetooth access request and parses the member role tag, matches it with a preset permission rule library after authentication to generate an initial permission allocation instruction, combines the current system timestamp and the vehicle positioning location, dynamically judges the spatio-temporal validity of the initial permission instruction by comparing the time window and calculating the spatial offset, establishes a two-way encryption link after the instruction is valid, collects spatio-temporal environment and operating state data in real time, substitutes them into the constructed demand permission collaborative analysis model to determine the user's demand permission, and dynamically adjusts the initial instruction, monitors the user operation behavior data in real time, constructs a normal range threshold by periodically analyzing historical operation data, determines abnormal data after comparison and dynamically updates the control permission, so as to realize the full-process intelligent management and security control of vehicle Bluetooth key permissions.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle Bluetooth key control, and relates to a method for allocating vehicle Bluetooth key permissions for multi-device collaborative management. Background Art

[0002] With the rapid development of intelligent vehicle technology, keyless entry and vehicle control technology based on Bluetooth keys has become the mainstream trend. However, the problem of permission allocation in multi-device collaborative scenarios has become increasingly prominent, such as the dynamic permission management requirements of family members, shared users, or temporary drivers. Existing technologies generally adopt static permission allocation or single-dimensional identity verification mechanisms, which are difficult to meet the dynamic permission adjustment requirements in complex scenarios, and there are problems such as potential safety hazards and insufficient user experience.

[0003] For example, Chinese Patent Publication No. CN115471933B discloses a method, device, electronic device, and readable storage medium for allocating vehicle Bluetooth keys, which are applied to the technical field of Bluetooth keys. The vehicle Bluetooth key allocation method includes: obtaining user characteristics of a user, where the user characteristics include identity information and driving characteristics; if the identity information is a non-owner identity, then according to the driving characteristics, generating the corresponding key usage limit times for the user, and according to the identity information, generating the corresponding key permission level for the user; generating a shared Bluetooth key corresponding to the user according to the key usage limit times and the key permission level. This application solves the technical problem of relatively low borrowing security of vehicles.

[0004] However, the existing technologies have the following problems: 1. The permission rules are fixed to the identity label, and the real-time linkage verification of the permission validity through time windows and geographical fences is not carried out, which may lead to permission abuse or misoperation. There is a situation where users can still operate the vehicle at unauthorized times or in unauthorized areas, increasing potential safety hazards.

[0005] 2. The key usage limit times cannot be dynamically adjusted after being generated, cannot adapt to changes in actual usage scenarios, and do not combine multi-source information such as vehicle operating status and spatio-temporal environment data to jointly determine the required permissions of users, reducing the user experience and vehicle usage efficiency.

[0006] 3. The existing technologies lack a real-time comparison mechanism for user operation behaviors and historical normal thresholds, making it difficult to dynamically identify and restrict abnormal operations. There are security vulnerabilities caused by rigid permission allocation, reducing the adaptive ability of the system. Summary of the Invention

[0007] The present invention aims to solve the problems in the prior art such as inaccurate vehicle Bluetooth key permission allocation, rigid usage restrictions, and poor environmental adaptability. It provides a method for allocating vehicle Bluetooth key permissions with multi-device collaborative management. Through comprehensive means such as spatio-temporal dynamic constraints, multi-source data collaborative analysis, dynamic permission adjustment, and biometric verification, it realizes the refined management and security control of vehicle permissions.

[0008] The technical solution adopted by the present invention to solve its technical problems is: A method for allocating vehicle Bluetooth key permissions with multi-device collaborative management, including: S1. Receive a Bluetooth access request and parse the member role tag in the request, match the member role tag with the corresponding vehicle control permission set in the preset permission rule library, and generate an initial permission allocation instruction.

[0009] S2. According to the time constraint condition and the geographical fence area constraint condition in the initial permission allocation instruction, combine the current system timestamp and the positioning position of the target vehicle for data linkage, and dynamically judge the spatio-temporal validity of the initial permission allocation instruction.

[0010] S3. After the instruction is valid, establish a communication link between the Bluetooth device and the target vehicle, real-time monitor the spatio-temporal environment data and operation status data of the target vehicle, and determine the user's required permissions through collaborative analysis.

[0011] S4. Dynamically adjust the initial permission allocation instruction based on the user's required permissions, and real-time monitor the user's operation behavior data. Compare it with the normal range threshold of the historical operation behavior data in the vehicle's historical usage records to determine abnormal data, and dynamically update the control permissions.

[0012] Compared with the prior art, the present invention has the following beneficial effects: (1) By parsing the unique identity identifier and member role tag in the Bluetooth access request, and verifying the identity based on biometric comparison, and matching it with the vehicle control permission set in the preset permission rule library, the present invention generates an initial permission allocation instruction, thus changing the traditional fixed permission allocation mode, realizing accurate identity verification based on user roles and biometrics, ensuring the initial match between the initial permissions and the user identity and usage scenarios, and improving the security and pertinence of permission allocation.

[0013] (2) By comparing the timestamp with the permission validity period window and calculating the spatial offset between the positioning data and the geographical fence area boundary, and determining the validity of the initial permission instruction based on the spatio-temporal condition association rule, the present invention realizes the dynamic binding of permission allocation with time and space scenarios, avoids the risk of unauthorized operations, and ensures the controlled use of the vehicle within the legal spatio-temporal range.

[0014] (3) The present invention collects spatio-temporal environment data and operating status data in real time. After normalization processing, the data is input into the demand-permission collaborative analysis model. This model integrates the spatio-temporal environment-permission and operating status-permission association models, and dynamically outputs the user's demand permissions, thereby changing the traditional static permission allocation mode, making the permission allocation more suitable for the actual usage scenario, and enhancing the user experience and vehicle control security.

[0015] (4) The present invention extracts operation behavior data from the vehicle's historical usage records, constructs a normal range threshold through periodic analysis, compares the user's operation data with the threshold in real time, restricts the permissions associated with abnormal data and alerts the user, thereby preventing potential risks by dynamically updating control permissions. At the same time, an alarm log is generated to provide a basis for security audits, realizing a closed-loop control of the entire process from permission allocation to usage, and significantly enhancing the security and reliability of vehicle collaborative management. Brief Description of the Drawings

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for describing the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0017] Figure 1 It is a schematic diagram of the method step flow of the present invention.

[0018] Figure 2 It is a schematic diagram of the spatio-temporal validity analysis step of the initial permission allocation instruction in the present invention.

[0019] Figure 3 It is a schematic diagram of the user demand permission determination step in the present invention.

[0020] Figure 4 It is a schematic diagram of the dynamic update control permission analysis step in the present invention. Detailed Description of the Embodiments

[0021] Now, various exemplary embodiments of the present invention will be described in detail with reference to the drawings. It should be noted that: unless otherwise specifically stated, the relative arrangements, numerical expressions, and numerical values of the components and steps described in these embodiments do not limit the scope of the present invention. At the same time, it should be understood that for the sake of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationships.

[0022] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way a limitation on the invention, its application, or its use. Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such technologies, methods, and devices should be considered as part of the specification.

[0023] In all examples shown and discussed herein, any specific values should be construed as merely exemplary and not as a limitation. Thus, other examples of the exemplary embodiments may have different values.

[0024] The present invention provides a method for allocating vehicle Bluetooth key permissions with multi-device collaborative management. First, it receives a Bluetooth access request and parses the member role tag, performs identity verification through unique identity identification matching and biometric comparison, and then matches with a preset permission rule library to generate an initial permission allocation instruction containing time and geofence constraints. Then, in combination with the current system timestamp and the vehicle positioning location, it dynamically determines the spatio-temporal validity of the initial permission instruction by comparing the time window and calculating the spatial offset. After the instruction is valid, a two-way encrypted link is established, and spatio-temporal environment and operating state data are collected in real time. After normalization processing, they are substituted into a demand permission collaborative analysis model constructed based on historical data association rules analysis to determine the user's required permissions. Finally, based on the required permissions, the initial instruction is dynamically adjusted, the user operation behavior data is monitored in real time, a normal range threshold is constructed by periodically analyzing historical operation data, and after comparison, abnormal data is determined and the control permissions are dynamically updated to achieve the full-process intelligent management and security control of vehicle Bluetooth key permissions.

[0025] Please refer to Figure 1 As shown, the present invention provides a method for allocating vehicle Bluetooth key permissions with multi-device collaborative management, including: S1. Receive a Bluetooth access request and parse the member role tag in the request, match the member role tag with the corresponding vehicle control permission set in the preset permission rule library, and generate an initial permission allocation instruction.

[0026] S2. According to the time constraint condition and the geofence area constraint condition in the initial permission allocation instruction, perform data linkage in combination with the current system timestamp and the target vehicle positioning location, and dynamically determine the spatio-temporal validity of the initial permission allocation instruction.

[0027] S3. After the instruction is valid, establish a communication link between the Bluetooth device and the target vehicle, monitor the spatio-temporal environment data and the operating state data of the target vehicle in real time, and determine the user's required permissions through collaborative analysis.

[0028] S4. Dynamically adjust the initial permission allocation instruction based on user requirements, and monitor the user operation behavior data in real time. Compare it with the normal range threshold of the historical operation behavior data in the vehicle historical usage record to determine abnormal data and dynamically update the control permission.

[0029] It should be noted that the specific content of parsing the member role label in the request in step S1 is as follows: Receive the Bluetooth access request through the target vehicle Bluetooth communication device, decode to obtain the unique identity identifier of the Bluetooth access request. If it is not in the authorized Bluetooth device list stored in the vehicle association database, reject the access and generate an illegal request warning log. Otherwise, according to the corresponding role labels and associated role information of each Bluetooth device in the authorized Bluetooth device list, authenticate the member corresponding to the Bluetooth access request. After the authentication is passed, match the member role label of the Bluetooth access request.

[0030] In the above, the target vehicle Bluetooth communication device scans the specific radio frequency signal emitted in the Bluetooth access request, and decodes the specific radio frequency signal through decoding technology to obtain the unique identity identifier of the Bluetooth access request. The decoding technology involved is common existing technology in this field, so it will not be elaborated in detail in the present invention.

[0031] Further, the authentication of the member corresponding to the Bluetooth access request is as follows: Call the associated role information and role label of the Bluetooth device matching the unique identity identifier of the Bluetooth access request, extract the biometric identifier in the associated role information, and collect the real-time biometric of the member corresponding to the Bluetooth access request through the in-vehicle biometric recognition terminal. Compare it with the biometric standard in the associated role information to obtain the biometric comparison result, and authenticate the identity of the member corresponding to the Bluetooth access request according to the biometric comparison result to generate an identity authentication result. Verifying the identity through biometric comparison greatly reduces the risk of illegal devices or impostors accessing, reduces the possibility of the vehicle system being attacked or data being tampered with, and ensures the safety of the vehicle and users.

[0032] In the above, the biometric identifier can be features with individual uniqueness such as fingerprints, face images, voices, and body shape contours. These biometric features have uniqueness and stability, and can effectively distinguish different individuals. Collect the real-time biometric through the in-vehicle biometric recognition terminal and compare it with the pre-stored biometric identifier. If the real-time biometric and the pre-stored biometric identifier are the same, the identity authentication of the member corresponding to the Bluetooth access request passes, so as to accurately verify the identity of the member corresponding to the Bluetooth access request and improve the security and reliability of the identity authentication.

[0033] The steps for constructing the preset permission rule library are as follows: A1. Hierarchical structure design: Construct a multi-level tree-shaped permission rule library.

[0034] Root node definition: The root node stores the vehicle's global permission policy.

[0035] Intermediate node division: Branch nodes are created according to the role tag type, and each node is associated with the permission level of the role tag. The role tag types include vehicle owners, long-term users, and temporary members, and the permission levels include full-function control permissions, partial permission restrictions, and basic operation permissions.

[0036] Leaf node extension: Further subdivide specific permission items under the role tag branch. For example, vehicle owners have full vehicle function permissions, such as vehicle door lock control, navigation system access, entertainment system access, vehicle setting modification, security system access, and power system operation, etc.

[0037] Long-term users: Have partial permission restrictions, such as prohibiting vehicle setting modification and security system access, etc.

[0038] Temporary members: Only basic operation permissions are open, such as door unlocking and power system operation, etc.

[0039] A2. Embedding dynamic constraint conditions: Attach a time window for the permission validity period and the geographical fence coordinate range to the leaf node.

[0040] Permission timestamp effective range: Embed time window parameters in the leaf node, such as start time and end time, or relative time, such as 24 hours after the permission becomes effective.

[0041] Geographical fence area range: Attach geographical fence parameters to the temporary permission node, and store the polygon vertex coordinates or the center point and radius of the circular area. For example, the temporary member permission is bound to "Geographical Fence A", and the coordinate range is: longitude X to X + Δ, latitude Y to Y + Δ, and the permission will automatically expire after exceeding the range.

[0042] A3. Permission template generation: Generate a permission configuration template, including role tags, specific control permission sets, and dynamic constraint conditions, and build a preset permission rule library.

[0043] The present invention parses the unique identity identifier and member role tag in the Bluetooth access request, verifies the identity based on biometric comparison, matches it with the vehicle control permission set in the preset permission rule library, and generates an initial permission allocation instruction, thereby changing the traditional fixed permission allocation mode, realizing accurate identity verification based on user roles and biometrics, ensuring the initial match between permissions and user identities and usage scenarios, and enhancing the security and pertinence of permission allocation.

[0044] As Figure 2 shown, the specific content of step S2 is as follows: S21. Obtain the current system timestamp through the in-vehicle terminal clock, and synchronously obtain the real-time positioning location of the target vehicle through the in-vehicle GPS.

[0045] S22. Compare the current system timestamp with the time window of the permission validity period in the time constraint condition to identify whether it is within the time window of the permission validity period, and mark the time validity. When the current system timestamp is within the time window of the permission validity period, mark the time validity as the valid state; otherwise, mark the time validity as the invalid state.

[0046] S23. Construct the boundary of the polygon geofence area according to the geofence area, calculate the spatial position offset in combination with the real-time positioning position of the vehicle, and judge the geofence validity according to the spatial position offset. When the spatial position offset is greater than the set spatial position offset, mark the geofence validity as the invalid state; otherwise, mark the geofence validity as the valid state.

[0047] S24. Set the spatio-temporal condition association rule, and judge the spatio-temporal validity of the initial permission allocation instruction according to the time validity and the geofence validity. The spatio-temporal condition association rule is set such that when the time validity is in the valid state and the geofence validity is in the valid state, the spatio-temporal validity of the initial permission allocation instruction is judged to be valid; otherwise, mark it as spatio-temporal invalidation and synchronize the verification process to the monitoring log.

[0048] Further, the calculation method of the spatial position offset includes: converting the boundary of the polygon geofence area into vertex data of the polygon in the geodetic coordinate system, obtaining the longitude and latitude coordinates according to the real-time positioning position of the vehicle, and using the ray method to judge the spatial position relationship between the coordinate point and the geofence area. When the coordinate point is outside the geofence area, calculate the Euclidean distance from this point to the nearest boundary of the polygon geofence area as the spatial position offset.

[0049] The present invention realizes the dynamic binding of permission allocation with time and space scenarios by comparing the timestamp with the permission validity window and calculating the spatial offset between the positioning data and the geofence area boundary, and judging the validity of the initial permission instruction based on the spatio-temporal condition association rule, so as to avoid the risk of unauthorized operations and ensure the controlled use of the vehicle within the legal spatio-temporal range.

[0050] As Figure 3 shown, the specific content of step S3 is as follows: S31. Establish a two-way encrypted communication link between the Bluetooth device and the target vehicle through the Bluetooth 5.0 low-power protocol.

[0051] S32. Real-time obtain spatio-temporal environment data and operation state data through the multi-source data acquisition device deployed inside the target vehicle. The spatio-temporal environment data includes the positioning positions and weather information at different times, such as weather categories and temperatures, etc., and the operation state data includes vehicle speed and battery power.

[0052] S33. Normalize the collected data to generate a multi-dimensional data set containing spatio-temporal features and operating status features.

[0053] S34. Substitute the multi-dimensional data set into the constructed requirement-permission collaborative analysis model to obtain user requirement permissions.

[0054] Further, the construction method of the requirement-permission collaborative analysis model is as follows: Q1. Extract the historical spatio-temporal environment data set, the operating status data set, and the vehicle permission usage records at corresponding times from the vehicle historical usage records.

[0055] For example, the historical spatio-temporal environment data set is information such as positioning locations and weather conditions at different times, as well as the usage of vehicle permissions at corresponding times, such as the permission to open the trunk in a specific parking lot, etc., and is organized into a data set in chronological order.

[0056] The operating status data set is to integrate vehicle operating status data, including vehicle speed and battery power, etc., and the enabling or disabling of vehicle permissions at corresponding times, such as some non-critical function permissions may be disabled when driving at high speed. The non-critical function permissions include vehicle window permissions and entertainment system access permissions. When the battery power is too low, the vehicle power charging permission needs to be enabled.

[0057] Q2. Conduct association rule analysis on the historical spatio-temporal environment data set and the vehicle permission usage records to obtain the correlation between spatio-temporal environment data and permissions, and construct a spatio-temporal environment-permission association model based on the correlation.

[0058] The correlation analysis process between spatio-temporal environment data and permissions is as follows: Form a transaction data set of spatio-temporal features and permissions according to the historical spatio-temporal environment characteristics and the vehicle permission usage records at corresponding times, scan the transaction data set, calculate the support degree of each candidate item set, screen the item sets with a support degree greater than or equal to the minimum support degree, and generate frequent item sets.

[0059] Generate association rules for multiple frequent item sets, calculate the confidence and lift of multiple frequent item sets, screen the correlations of different frequent item sets according to the set confidence and lift thresholds, and then statistically analyze the correlation between spatio-temporal environment data and permission usage.

[0060] In a specific embodiment, extract the historical spatio-temporal environment data set from the vehicle historical usage records, such as the longitude and latitude grid encoding of the positioning location, the timestamp, the weather category, the temperature, and the type of geographical fence, which includes parking lot / residential area / highway, and synchronously mark the permission enabling events at corresponding times, such as trunk opening, seat heating, engine starting, etc., to form a transaction data set of "spatio-temporal feature set + permission label".

[0061] Generate 1-item sets of single spatio-temporal features or permission items based on the transaction dataset, calculate their support degrees, and the calculation formula is the ratio of the number of transactions containing the item to the total number of transactions. Filter out the items with support degrees lower than the minimum threshold to form frequent 1-item sets.

[0062] Generate candidate (k + 1)-item sets by combining multiple frequent 1-item sets, and perform pruning using the rule that all subsets of a frequent item set must be frequent, and only retain the candidate sets whose all subsets are frequent item sets. For example, if {area = parking lot, permission = trunk opening} is a frequent 2-item set, then all its subsets {area = parking lot} and {permission = trunk opening} must already exist in the frequent 1-item sets.

[0063] Scan the transaction dataset, calculate the support degrees of each candidate item set, retain the item sets with support degrees greater than or equal to the minimum threshold to generate frequent k-item sets. Repeat this process until no higher-order frequent item sets can be generated, and finally obtain all frequent spatio-temporal-permission combinations, such as {area = parking lot, timestamp = daytime, permission = trunk opening}).

[0064] For each frequent item set , where is a spatio-temporal feature item, is a permission item, generate association rules , calculate the confidence degrees of multiple frequent item sets, , for example, the confidence degree of the rule {area = parking lot, timestamp = daytime} → {permission = trunk opening} represents the probability of opening the trunk permission in the parking lot scenario during the day. Calculate the lift according to the confidence degree, , and regard the correlation of the frequent item sets with confidence degrees greater than the set confidence degree threshold and lifts greater than the set lift threshold as relevant relationships, and construct a spatio-temporal environment-permission association model based on the spatio-temporal feature items and permission items in the corresponding frequent item sets of the relevant relationships.

[0065] Q3. Validate other historical spatio-temporal environment datasets against the spatio-temporal environment-permission association model, evaluate the accuracy of the spatio-temporal environment-permission association model in predicting required permissions. When the accuracy is less than the set accuracy threshold, re-perform association rule analysis to construct a new spatio-temporal environment-permission association model, and then continuously optimize the spatio-temporal environment-permission association model. Similarly, obtain an optimized operation state-permission association model according to the spatio-temporal environment-permission association model construction method.

[0066] Among them, to evaluate the accuracy of the spatio-temporal environment - permission association model in predicting the required permissions, specifically including: substituting each spatio-temporal environment data in other historical spatio-temporal environment datasets into the spatio-temporal environment - permission association model for verification, outputting the required permissions, comparing the vehicle permission usage records corresponding to each spatio-temporal environment data at the corresponding moment in other historical spatio-temporal environment datasets with the required permissions, screening the number of times with the same permissions, and taking the ratio of it to the total number of times in other historical spatio-temporal environment datasets as the accuracy of the spatio-temporal environment - permission association model in predicting the required permissions.

[0067] Q4. Integrate the optimized spatio-temporal environment - permission association model and the operation status - permission association model to generate a collaborative analysis model for required permissions.

[0068] The present invention collects spatio-temporal environment data and operation status data in real time. After normalization processing, they are input into the collaborative analysis model for required permissions. This model integrates the spatio-temporal environment - permission and operation status - permission association models, and dynamically outputs the user's required permissions, thereby changing the traditional static permission allocation mode, making the permission allocation more in line with the actual usage scenario, and improving the user experience and vehicle control safety.

[0069] As Figure 4 shown, the specific content of step S4 is as follows: S41. Extract the historical operation behavior data corresponding to the user's vehicle usage records from the vehicle historical usage records, divide the historical operation behavior data according to the set time window, perform periodic law analysis on the historical operation behavior data under each divided time window, judge the periodicity of the historical operation behavior data, and based on the periodicity analysis, determine the normal range threshold of the historical operation behavior data.

[0070] The set time windows are week, month, and quarter. For example, taking one week as a window, grouping the user's operation behavior data of each week into one group, which is convenient for observing the operation rules within each week.

[0071] The method for judging the periodicity of the historical operation behavior data is as follows: for each time window, calculate the key features of the operation behavior data, such as operation frequency, operation time interval, the number of times a specific function is used, etc. For example, count the frequencies of operations such as door unlocking and air conditioner adjustment from 8:00 to 9:00 every Monday.

[0072] Use time series analysis methods to identify the repeated patterns of the operation behavior data in the time dimension. If a certain operation behavior data frequently shows similar features or is the same in the same period of consecutive multiple time windows, such as the user usually adjusts the air conditioner temperature to at 8 - 9 am every Monday, and the seat heating function is always turned on, then this behavior is the user's fixed operation habit during the work commute period, and it is judged that this behavior has a periodic pattern.

[0073] S42. Compare the user operation behavior data with the normal range threshold of the corresponding historical operation behavior data. If the user operation behavior data is not within the corresponding normal range threshold, the user operation behavior data is abnormal data, restrict the associated control permission of the abnormal data and remind the user.

[0074] Further, the normal range threshold for analyzing historical operation behavior data based on periodicity specifically includes: when the historical operation behavior data is periodic, calculate the mean and standard deviation of the historical operation behavior data, take the sum of the mean and standard deviation of the historical operation behavior data as the maximum threshold of the normal range, take the difference between the mean and standard deviation of the historical operation behavior data as the minimum threshold of the normal range, and construct the normal range threshold according to the minimum threshold and maximum threshold of the normal range. For example, the average occurrence time of a certain periodic operation is 8:15, and the standard deviation is 5 minutes, then the normal range threshold can be set to 8:10 - 8:20.

[0075] When the historical operation behavior data is non-periodic, calculate the minimum value and the minimum value of the historical operation behavior data, and construct the normal range threshold of the historical operation behavior data.

[0076] The present invention extracts operation behavior data from the vehicle historical usage records, constructs the normal range threshold through periodic analysis, compares the user operation data with the threshold in real time, restricts the associated permission of the abnormal data and reminds the user, thereby preventing potential risks by dynamically updating the control permission, and at the same time generating an alarm log to provide a basis for security audit, realizing the closed-loop management and control from permission allocation to the whole usage process, and significantly improving the security and reliability of vehicle collaborative management.

[0077] The above formulas are all dimensionless and take their numerical values for calculation. The formula is obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation.

[0078] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0079] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0080] In addition, in each embodiment of the present application, each functional module may be integrated into one processing module, may exist physically alone for each module, or two or more modules may be integrated into one module.

[0081] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0082] Finally, the above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A vehicle Bluetooth key authority allocation method for multi-device collaborative management, characterized in that: include: S1. Receive a Bluetooth access request and parse the member role tag in the request, match the member role tag with the corresponding vehicle control permission set in the preset permission rule library, and generate an initial permission allocation instruction; S2. According to the time constraint conditions and geographic fence area constraint conditions in the initial permission allocation instruction, the current system timestamp is combined with the target vehicle positioning position to perform data linkage and dynamically determine the spatiotemporal validity of the initial permission allocation instruction; S3. After the command is effective, a communication link between the Bluetooth device and the target vehicle is established, the temporal and spatial environmental data and operating status data of the target vehicle are monitored in real time, and the user's required permissions are determined through collaborative analysis; S4. Dynamically adjust the initial permission allocation instructions based on user required permissions, and monitor the user's operation behavior data in real time, compare it with the normal range threshold of historical operation behavior data in the vehicle's historical usage records, determine abnormal data, and dynamically update control permissions.

2. A vehicle Bluetooth key authority allocation method for multi-device collaborative management according to claim 1, characterized in that: The specific content of the member role tag in the parsing request in step S1 is: The Bluetooth access request is received through the Bluetooth communication device of the target vehicle, and the unique identity of the Bluetooth access request is decoded. If it is not in the authorized Bluetooth device list stored in the vehicle-related database, access is denied and an illegal request alarm log is generated. On the contrary, the member corresponding to the Bluetooth access request is authenticated according to the corresponding role tag and associated role information of each Bluetooth device in the authorized Bluetooth device list. After the identity authentication is passed, the member role tag of the Bluetooth access request is matched.

3. A vehicle Bluetooth key authority allocation method for multi-device collaborative management according to claim 2, characterized in that: The identity authentication of the member corresponding to the Bluetooth access request is as follows: Call the associated role information and role tag corresponding to the Bluetooth device that matches the unique identity identifier of the Bluetooth access request, extract the biometric identifier in the associated role information, and collect the real-time biometrics of the member corresponding to the Bluetooth access request through the on-board biometric terminal, compare it with the biometric standard in the associated role information to obtain the biometric comparison result, verify the identity of the member corresponding to the Bluetooth access request based on the biometric comparison result, and generate an identity authentication result.

4. A vehicle Bluetooth key authority allocation method for multi-device collaborative management according to claim 1, characterized in that: The specific content of step S2 is as follows: S21, obtaining the current system timestamp through the vehicle terminal clock, and synchronously obtaining the real-time positioning position of the target vehicle through the vehicle GPS; S22, comparing the current system timestamp with the permission validity period time window in the time constraint condition, identifying whether it is within the permission validity period time window, and marking the time validity; S23, constructing a polygonal geo-fence area boundary according to the geo-fence area, calculating a spatial position offset in combination with the real-time positioning position of the vehicle, and determining the validity of the geo-fence according to the spatial position offset; S24. Set the time-space condition association rules to determine the time-space validity of the initial permission allocation instruction based on the time validity and the geographic fence validity.

5. The method for assigning vehicle Bluetooth key permissions for multi-device collaborative management according to claim 1, characterized in that: The specific content of step S3 is as follows: S31, establishing a two-way encrypted communication link between the Bluetooth device and the target vehicle through the Bluetooth 5.0 low power protocol; S32, acquiring spatiotemporal environment data and operating status data in real time through a multi-source data acquisition device deployed in the target vehicle, wherein the spatiotemporal environment data includes positioning positions and weather conditions at different times, and the operating status data includes vehicle speed and battery power; S33, normalizing the collected data to generate a multidimensional data set including spatiotemporal features and operating status features; S34. Substitute the multidimensional data set into the constructed demand and authority collaborative analysis model to obtain user demand and authority.

6. A vehicle Bluetooth key authority allocation method for multi-device collaborative management according to claim 5, characterized in that: The demand authority collaborative analysis model is constructed in the following way: Extract the historical spatiotemporal environment dataset and the operating status dataset as well as the vehicle authority usage records at the corresponding time from the vehicle historical usage records; Perform association rule analysis on historical spatiotemporal environment data sets and vehicle authority usage records to obtain the correlation between spatiotemporal environment data and authority, and build a spatiotemporal environment-authority association model based on the correlation; Use other historical spatiotemporal environment data sets to verify the spatiotemporal environment-authority association model, evaluate the accuracy of the spatiotemporal environment-authority association model in predicting required permissions, optimize the spatiotemporal environment-authority association model based on the accuracy, and similarly obtain the optimized operation status-authority association model; Integrate the optimized spatiotemporal environment-authority association model and the operation status-authority association model to generate a demand-authority collaborative analysis model.

7. A vehicle Bluetooth key authority allocation method for multi-device collaborative management according to claim 6, characterized in that: The correlation analysis process between the spatiotemporal environment data and the authority is as follows: According to the historical spatiotemporal environmental characteristics and the corresponding vehicle authority usage records, a transaction data set of spatiotemporal characteristics and authority is formed. The transaction data set is scanned, the support of each candidate item set is calculated, and the item sets with support greater than or equal to the minimum support are screened to generate frequent item sets. Generate association rules for multiple frequent item sets, calculate the confidence and lift of multiple frequent item sets, filter the correlation of different frequent item sets according to the set confidence and lift threshold filtering rules, and then count the correlation between spatiotemporal environmental data and permission usage.

8. The vehicle Bluetooth key authority allocation method for multi-device collaborative management according to claim 6 is characterized by: The accuracy of evaluating the spatiotemporal environment-authority association model in predicting the required authority specifically includes: Substitute the spatiotemporal environmental data of each time in other historical spatiotemporal environmental data sets into the spatiotemporal environment-authority association model for verification, output the required authority, compare the vehicle authority usage records at the corresponding moments of each spatiotemporal environmental data in other historical spatiotemporal environmental data sets with the required authority, filter out the number of times with the same authority, and use the ratio of it to the total number of times in other historical spatiotemporal environmental data sets as the accuracy of the spatiotemporal environment-authority association model in predicting the required authority.

9. The vehicle Bluetooth key authority allocation method for multi-device collaborative management according to claim 1 is characterized by: The specific content of step S4 is as follows: Extracting historical operation behavior data corresponding to the user's vehicle use record from the vehicle's historical use record, dividing the historical operation behavior data according to the set time window, performing periodic regularity analysis on the historical operation behavior data in each divided time window, determining the periodicity of the historical operation behavior data, and analyzing the normal range threshold of the historical operation behavior data based on the periodicity; The user operation behavior data is compared with the normal range threshold of the corresponding historical operation behavior data. If the user operation behavior data is not within the corresponding normal range threshold, the user operation behavior data is abnormal data, and the control authority associated with the abnormal data is restricted and the user is reminded.

10. A vehicle Bluetooth key authority allocation method for multi-device collaborative management according to claim 9, characterized in that: The normal range threshold based on periodic analysis of historical operation behavior data specifically includes: When the historical operation behavior data is periodic, the mean and standard deviation of the historical operation behavior data are counted, the sum of the mean and standard deviation of the historical operation behavior data is used as the maximum threshold of the normal range, the difference between the mean and standard deviation of the historical operation behavior data is used as the minimum threshold of the normal range, and the normal range threshold is constructed according to the minimum threshold and maximum threshold of the normal range; When the historical operation behavior data is non-periodic, the minimum and maximum values ​​of the historical operation behavior data are counted to construct a normal range threshold of the historical operation behavior data.

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