A vehicle unlocking and locking control method and device, vehicle and storage medium

Abstract

This application provides a vehicle unlocking / locking control method, device, vehicle, and storage medium. The method includes: acquiring received signal strength indication values ​​from a target mobile device collected by multiple Bluetooth nodes over the most recent M periods; filtering the received signal strength indication values ​​collected by the target Bluetooth nodes over the most recent M periods to obtain the filtered received signal strength indication value of the target Bluetooth node in the current period; performing anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period to obtain the analysis result of the target Bluetooth node; determining the target weight coefficients of the multiple Bluetooth nodes based on their respective analysis results; obtaining the target received signal strength indication value based on the target weight coefficients of the multiple Bluetooth nodes and the filtered received signal strength indication value in the current period; and controlling the vehicle to perform an unlocking / locking operation based on the target received signal strength indication value.

Description

Technical Field

[0001] This application relates to the field of intelligent vehicle electronic and electrical technology, and in particular to a vehicle unlocking and locking control method, device, vehicle, and storage medium. Background Technology

[0002] With the rapid development of IoT and V2X technologies, contactless vehicle unlocking and closing technology based on Bluetooth Received Signal Strength Indicator (RSSI) has become a standard feature in smart vehicles. Its core functionality involves wireless communication between mobile devices and the vehicle's Bluetooth module to achieve user identification and near-field operation response. However, in scenarios involving signal obstruction, multipath effects, or human body dielectric interference, the RSSI value at a certain node can fluctuate drastically, leading to misjudgments. This can result in situations where the door cannot unlock promptly even when the owner is close, or the vehicle cannot lock even when the owner is far away, demonstrating low accuracy in intelligent unlocking and closing. Summary of the Invention

[0003] This application provides a method, apparatus, computer-readable storage medium, and computer program product that can effectively suppress the interference of abnormal nodes on the fusion results, thereby improving the accuracy of the target RSSI value after weighted fusion, and ultimately ensuring the reliability and accuracy of the vehicle intelligent unlocking and locking system.

[0004] The technical solution of this application embodiment is implemented as follows: This application provides a vehicle locking / unlocking control method, wherein multiple Bluetooth nodes are installed on the vehicle, and the method includes: Obtain the received signal strength indication values ​​from the target mobile device collected by multiple Bluetooth nodes in the most recent M periods; M≥2, M is an integer; The received signal strength indication values ​​of the target Bluetooth node collected in the most recent M periods are filtered to obtain the filtered received signal strength indication value of the target Bluetooth node in the current period; the target Bluetooth node is any one of the plurality of Bluetooth nodes; Anomaly analysis is performed on the filtered received signal strength indication value of the target Bluetooth node in the current period to obtain the analysis result of the target Bluetooth node; Based on the analysis results of each of the multiple Bluetooth nodes, the target weight coefficients of each of the multiple Bluetooth nodes are determined. Based on the target weight coefficients of each of the multiple Bluetooth nodes in the current period and the filtered received signal strength indication value, the target received signal strength indication value is obtained. Based on the target received signal strength indication value, the vehicle is controlled to perform an unlocking / locking operation.

[0005] This application provides a vehicle locking / unlocking control device, in which multiple Bluetooth nodes are installed on the vehicle. The device includes: The acquisition unit is used to acquire the received signal strength indication values ​​from the target mobile device collected by multiple Bluetooth nodes in the most recent M cycles; M≥2, where M is an integer; The filtering unit is used to filter the received signal strength indication values ​​of the target Bluetooth node collected in the most recent M cycles to obtain the filtered received signal strength indication value of the target Bluetooth node in the current cycle; the target Bluetooth node is any one of the plurality of Bluetooth nodes; An anomaly analysis unit is used to perform anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period, and obtain the analysis result of the target Bluetooth node. The processing unit is used to determine the target weight coefficient of each of the multiple Bluetooth nodes based on the analysis results of each of the multiple Bluetooth nodes. The processing unit is also configured to obtain a target received signal strength indication value based on the target weight coefficients of the multiple Bluetooth nodes in the current period and the filtered received signal strength indication value. The control unit is used to control the vehicle to perform locking and unlocking operations based on the target received signal strength indication value.

[0006] This application provides a vehicle, the vehicle comprising: Memory is used to store executable instructions or computer programs. The central controller is used to execute computer-executable instructions or computer programs stored in the memory to implement the vehicle locking / unlocking control method provided in the embodiments of this application.

[0007] This application provides a computer-readable storage medium storing a computer program or computer-executable instructions, which, when executed by a processor, implements the vehicle locking / unlocking control method provided in this application.

[0008] This application provides a computer program product, including a computer program or computer-executable instructions. When the computer program or computer-executable instructions are executed by a processor, they implement the vehicle locking / unlocking control method provided in this application.

[0009] The embodiments of this application have the following beneficial effects: Based on whether the analysis results of multiple Bluetooth nodes are normal or abnormal, their respective target weight coefficients are dynamically set. Typically, the target weight coefficient of Bluetooth nodes with normal analysis results is greater than that of Bluetooth nodes with abnormal analysis results. Subsequently, the target weight coefficients of multiple Bluetooth nodes and the filtered received signal strength index (RSSI) value are weighted and fused. This method effectively suppresses the interference of abnormal nodes on the fusion result, thereby improving the accuracy of the target RSSI value after weighted fusion, ultimately ensuring the reliability and accuracy of the vehicle intelligent unlocking and locking system. Attached Figure Description

[0010] Figure 1 This is a first flowchart illustrating the vehicle unlocking and locking control method provided in this application embodiment; Figure 2 This is a schematic diagram of the system architecture provided in the embodiments of this application; Figure 3 This is a schematic diagram of the second process of the vehicle unlocking and locking control method provided in the embodiments of this application; Figure 4 This is a schematic diagram of the third process of the vehicle unlocking and locking control method provided in the embodiments of this application; Figure 5 This is a schematic diagram of the fourth process of the vehicle unlocking and locking control method provided in the embodiments of this application; Figure 6 This is a schematic diagram showing the distribution of the unlocking area, buffer zone, and locking area centered on the vehicle, provided in an embodiment of this application. Figure 7 This is a schematic diagram of the fifth process of the vehicle unlocking and locking control method provided in the embodiments of this application; Figure 8 This is a sixth flowchart illustrating the vehicle unlocking and locking control method provided in this application embodiment; Figure 9 This is a schematic diagram of the structure of the vehicle unlocking and locking control device provided in the embodiments of this application; Figure 10 This is a schematic diagram of the vehicle assembly provided in the embodiments of this application.

[0011] It should be noted that the terms "first" and "second" mentioned above are only used to distinguish between different options and do not represent the degree of superiority or inferiority of the options or their priority in the implementation process. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] This application provides a vehicle locking / unlocking control method. Figure 1 This is a schematic diagram of the first process of the vehicle locking / unlocking control method provided in this application embodiment, which is applied to a vehicle equipped with multiple Bluetooth nodes. For example, as shown... Figure 2 As shown, the vehicle is equipped with four Bluetooth nodes, which can be fixed at the left B-pillar 101, right B-pillar 102, front bumper 103, and rear bumper 104 respectively, forming a spatially symmetrical signal sensing network covering a 360° area around the vehicle. The Bluetooth nodes on the left and right B-pillars are installed on the door pillars near the door handles to ensure stable signal when the user operates the vehicle from the side. The Bluetooth nodes on the front and rear bumpers are embedded inside the bumpers to avoid signal shielding by metal components, ensuring strong signal coverage in the front and rear directions.

[0014] like Figure 1 As shown, the vehicle's locking / unlocking control method includes the following steps: S101: Obtain the received signal strength indication values ​​from the target mobile device collected by multiple Bluetooth nodes in the most recent M cycles; M≥2, M is an integer.

[0015] In this embodiment, after the target mobile device with a Bluetooth module establishes a Bluetooth connection with the vehicle's Bluetooth master control module, the master control module polls multiple Bluetooth nodes according to a preset period. During the polling process, each Bluetooth node collects the Received Signal Strength Indicator (RSSI) value from the mobile device in real time, and transmits the raw RSSI value to the master control module for centralized processing via the vehicle's local area network (e.g., CAN bus).

[0016] The target mobile device can be a smartphone, a smart key, or other device with a Bluetooth module.

[0017] The Bluetooth connection can be either classic Bluetooth or Bluetooth Low Energy (BLE).

[0018] Here, for each Bluetooth node, M RSSI values ​​can be collected in the most recent M cycles.

[0019] It should be noted that the preset period can be set from 100ms to 500ms. This period can be dynamically adjusted according to the actual application scenario. For example, when the user is rapidly approaching the vehicle, it can be shortened to 100ms to improve response speed; when the user is stationary or moving away, it can be extended to 500ms to reduce power consumption.

[0020] S102: Filter the received signal strength indication values ​​of the target Bluetooth node collected in the most recent M cycles to obtain the filtered received signal strength indication value of the target Bluetooth node in the current cycle; the target Bluetooth node is any Bluetooth node among multiple Bluetooth nodes.

[0021] In this embodiment of the application, the filtering process may include moving average filtering and / or Kalman filtering.

[0022] For example, for any target Bluetooth node among multiple Bluetooth nodes, a moving average filtering process is performed on the M RSSI values ​​collected in the most recent M periods, that is, the average value of the M RSSI values ​​is calculated to obtain the filtered RSSI value of the target Bluetooth node in the current period.

[0023] For example, for any target Bluetooth node among multiple Bluetooth nodes, a moving average filter is applied to the M RSSI values ​​collected over the most recent M periods, i.e., the average of the M RSSI values ​​is calculated. Then, a Kalman filter is applied to obtain the filtered RSSI value of the target Bluetooth node in the current period. The Kalman filter, by establishing a dynamic signal model and combining prior estimates with the current measurement results for optimization, is more suitable for scenarios with drastic signal fluctuations, further improving data stability.

[0024] For example, the average value of RSSI over the most recent 5-10 periods can be calculated, and the impact of sudden interference can be reduced by smoothing over time to obtain a smoothed RSSI value. , , , ).

[0025] S103: Perform anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period to obtain the analysis results of the target Bluetooth node.

[0026] In this embodiment, the fluctuation range (or effective range) of the filtered RSSI value differs for Bluetooth nodes located at different positions. Based on this, anomaly analysis is performed on the filtered RSSI value of the target Bluetooth node in the current period. If the filtered RSSI value is outside the fluctuation range, it is determined to be abnormal, and the analysis result of the target Bluetooth node is marked as abnormal; if the filtered RSSI value is within the fluctuation range, it is determined to be normal, and the analysis result of the target Bluetooth node is marked as normal.

[0027] S104: Based on the analysis results of each Bluetooth node, determine the target weight coefficients for each Bluetooth node.

[0028] In this embodiment, target weight coefficients are dynamically assigned based on the analysis results of the Bluetooth nodes. Bluetooth nodes with normal analysis results are assigned higher target weight coefficients, while Bluetooth nodes with abnormal analysis results are assigned lower target weight coefficients. The sum of the target weight coefficients of multiple Bluetooth nodes is 1.

[0029] Here, for multiple Bluetooth nodes whose analysis results are normal or abnormal, their corresponding target weight coefficients can be equal or unequal. For unequal coefficients, the target weight coefficient can be set based on the historical frequency of the user's proximity to the Bluetooth node. The higher the historical frequency, the larger the assigned target weight coefficient.

[0030] For example, the vehicle is equipped with four Bluetooth nodes 1, 2, 3, and 4. If the analysis result of Bluetooth node 1 is abnormal, while the analysis results of Bluetooth nodes 2, 3, and 4 are normal, then the target weight coefficient of Bluetooth node 1 is less than the target weight coefficients of Bluetooth nodes 2, 3, and 4. The sum of the target weight coefficients of Bluetooth nodes 1, 2, 3, and 4 is 1.

[0031] Here, the target weight coefficients for Bluetooth nodes 2, 3, and 4 can be equal. In this case, the target weight coefficient for Bluetooth node 1 can be set to 0.1, and the target weight coefficients for Bluetooth nodes 2, 3, and 4 can all be set to 0.3.

[0032] Of course, the target weight coefficients for Bluetooth nodes 2, 3, and 4 can also be unequal. In this case, the target weight coefficient for Bluetooth node 1 can be set to 0.1, the target weight coefficient for Bluetooth node 2 can be set to 0.4, and the target weight coefficients for Bluetooth nodes 3 and 4 can both be set to 0.25. The user has historically been closer to Bluetooth node 2 more frequently.

[0033] S105: Based on the target weight coefficients of multiple Bluetooth nodes in the current period and the filtered received signal strength indication value, the target received signal strength indication value is obtained.

[0034] In this embodiment of the application, the target weight coefficient of each Bluetooth node in the current period is multiplied by the filtered Received Signal Strength Indicator (RSSI) value, and then summed to obtain the target Received Signal Strength Indicator (RSSI) value.

[0035] For example, the vehicle is equipped with four Bluetooth nodes 1, 2, 3, and 4. The target weight coefficient of Bluetooth node 1 in the current period is multiplied by the filtered RSSI value to obtain the first multiplied value. The target weight coefficient of Bluetooth node 2 in the current period is multiplied by the filtered RSSI value to obtain the second multiplied value. The target weight coefficient of Bluetooth node 3 in the current period is multiplied by the filtered RSSI value to obtain the third multiplied value. The target weight coefficient of Bluetooth node 4 in the current period is multiplied by the filtered RSSI value to obtain the fourth multiplied value. The first, second, third, and fourth multiplied values ​​are then added together to obtain the target RSSI value.

[0036] S106: Based on the target received signal strength indication value, control the vehicle to perform unlocking and locking operations.

[0037] In this embodiment, when the target RSSI value is greater than the unlock threshold, an unlock command is sent to the body controller, which controls the vehicle to perform an unlock operation. When the target RSSI value is less than the lock threshold, a lock command is sent to the body controller, which controls the vehicle to perform a lock operation.

[0038] In this embodiment, the target weight coefficients for each of the multiple Bluetooth nodes are dynamically set based on whether their analysis results are normal or abnormal. Typically, the target weight coefficient for Bluetooth nodes with normal analysis results is greater than that for Bluetooth nodes with abnormal analysis results. Subsequently, the target weight coefficients of each Bluetooth node and the filtered received signal strength index (RSSI) are weighted and fused. This method effectively suppresses interference from abnormal nodes on the fusion result, thereby improving the accuracy of the target RSSI value after weighted fusion, ultimately ensuring the reliability and accuracy of the vehicle intelligent unlocking and locking system.

[0039] In some embodiments of this application, the step of performing anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period to obtain the analysis result of the target Bluetooth node includes... Figure 3 The steps shown are as follows: S301: Based on the filtered received signal strength indication values ​​of other Bluetooth nodes in the current period, perform spatial dimension anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period to obtain the first analysis result of the target Bluetooth node.

[0040] In this embodiment of the application, the first analysis result reflects the signal stability of the target Bluetooth node in the spatial dimension.

[0041] In this embodiment, based on the spatial distribution of each Bluetooth node on the vehicle, if the absolute value of the difference between the filtered RSSI value of the target Bluetooth node and the filtered RSSI values ​​of all other Bluetooth nodes is less than a first preset threshold in the spatial dimension, it is determined that the signal of the target Bluetooth node is relatively stable in the spatial dimension, and the first analysis result of the target Bluetooth node is marked as normal. Conversely, if it is determined that the signal of the target Bluetooth node is unstable in the spatial dimension, the first analysis result of the target Bluetooth node is marked as abnormal.

[0042] S302: And / or, based on the filtered received signal strength indication value of the target Bluetooth node obtained N periods ago, perform time-dimensional anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period to obtain the second analysis result of the target Bluetooth node; N≥1, N is an integer.

[0043] In this embodiment of the application, the second analysis result reflects the signal stability of the target Bluetooth node in the time dimension.

[0044] In this embodiment, if the absolute value of the difference between the filtered RSSI value of the target Bluetooth node in the current period and the filtered RSSI value N periods ago is less than a second preset threshold, it is determined that the signal of the target Bluetooth node is relatively stable in the time dimension, and the second analysis result of the target Bluetooth node is marked as normal. Conversely, if it is determined that the signal of the target Bluetooth node is unstable in the time dimension, the second analysis result of the target Bluetooth node is marked as abnormal.

[0045] For example, N is 2. If the absolute value of the difference between the filtered RSSI value of the target Bluetooth node in the current period, such as the 6th period, and the filtered RSSI value two periods ago, i.e., the 4th period, is less than the second preset threshold (i.e., the second threshold below), then the second analysis result of the target Bluetooth node is marked as normal.

[0046] S303: Based on the first and / or second analysis results of the target Bluetooth node, obtain the analysis results of the target Bluetooth node.

[0047] In this embodiment, if the first analysis result of the target Bluetooth node is normal, the final analysis result of the target Bluetooth node is normal. If the first analysis result of the target Bluetooth node is abnormal, the final analysis result of the target Bluetooth node is abnormal.

[0048] Alternatively, if the second analysis result of the target Bluetooth node is normal, the final analysis result of the target Bluetooth node will also be normal. If the second analysis result of the target Bluetooth node is abnormal, the final analysis result of the target Bluetooth node will also be abnormal.

[0049] Alternatively, if both the first and second analysis results of the target Bluetooth node are normal, the final analysis result of the target Bluetooth node will be normal. If both the first and second analysis results of the target Bluetooth node are abnormal, the final analysis result of the target Bluetooth node will be abnormal. If both the first and second analysis results of the target Bluetooth node are abnormal, the final analysis result of the target Bluetooth node will be abnormal.

[0050] In some embodiments of this application, the step of performing spatial dimension anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period based on the filtered received signal strength indication value of other Bluetooth nodes in the current period to obtain a first analysis result of the target Bluetooth node includes: The filtered received signal strength indication values ​​of the other Bluetooth nodes in the current cycle are averaged to obtain the first value; In this embodiment, we take a vehicle equipped with four Bluetooth nodes 1, 2, 3, and 4 as an example. If spatial anomaly analysis of Bluetooth node 1 (i.e., the target Bluetooth node) is required, the filtered RSSI values ​​of Bluetooth nodes 2, 3, and 4 in the current period are averaged to obtain a first value.

[0051] The first absolute difference is obtained based on the absolute difference between the first value and the filtered received signal strength indication value of the target Bluetooth node in the current period; For example, the absolute difference between the average of the filtered RSSI values ​​of Bluetooth nodes 2, 3, and 4 in the current period and the filtered RSSI value of Bluetooth node 1 is calculated to obtain the first absolute difference value.

[0052] Based on the relationship between the first absolute difference and the first threshold, it is determined whether the first analysis result of the target Bluetooth node is normal or abnormal.

[0053] In this embodiment, if the first absolute difference is less than or equal to a first threshold, it is determined that the signal of the target Bluetooth node is relatively stable in the spatial dimension, and the first analysis result of the target Bluetooth node is determined to be normal; if the first absolute difference is greater than the first threshold, it is determined that the signal of the target Bluetooth node is unstable in the spatial dimension, and the first analysis result of the target Bluetooth node is determined to be abnormal. The first threshold is set based on the developer's experience or experimental results.

[0054] Here, the first absolute difference This can be expressed by formula (1): (1) in, This represents the filtered RSSI value of the target Bluetooth node j. This represents the average value of the filtered RSSI values ​​of the remaining Bluetooth nodes; This can be expressed by formula (2): (2) It should be noted that if the initial analysis result of the target Bluetooth node is abnormal, it can be further determined whether it is a mild or severe anomaly. For example, if the first absolute difference is greater than the first threshold but less than the third threshold, the initial analysis result of the target Bluetooth node is determined to be a mild anomaly; if the first absolute difference is greater than the third threshold, the initial analysis result of the target Bluetooth node is determined to be a severe anomaly. The third threshold is greater than the first threshold.

[0055] In this embodiment, different vehicle models have their own dedicated first and third thresholds. This eliminates the need for adjustments for individual vehicles, ensuring a simple and efficient calibration process.

[0056] In some embodiments of this application, the step of performing a time-dimensional anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period based on the filtered received signal strength indication value of the target Bluetooth node obtained N periods ago, to obtain a second analysis result of the target Bluetooth node, includes: The second absolute difference is obtained based on the absolute difference between the filtered received signal strength indication value of the target Bluetooth node N periods ago and the filtered received signal strength indication value of the target Bluetooth node in the current period. Based on the relationship between the second absolute difference and the second threshold, it is determined whether the second analysis result of the target Bluetooth node is normal or abnormal.

[0057] In this embodiment of the application, the second analysis result reflects the signal stability of the target Bluetooth node in the time dimension.

[0058] In this embodiment, if the absolute value of the difference between the filtered RSSI value of the target Bluetooth node in the current period and the filtered RSSI value N periods ago is less than a second threshold, it is determined that the signal of the target Bluetooth node is relatively stable in the time dimension, and the second analysis result of the target Bluetooth node is marked as normal. Conversely, if it is determined that the signal of the target Bluetooth node is unstable in the time dimension, the second analysis result of the target Bluetooth node is marked as abnormal.

[0059] For example, N is 2. If the absolute value of the difference between the filtered RSSI value of the target Bluetooth node in the current period, such as the 6th period, and the filtered RSSI value two periods ago, i.e., the 4th period, is less than the second threshold, then the second analysis result of the target Bluetooth node is marked as normal.

[0060] Here, the second absolute difference This can be expressed by formula (3): (3) in, This represents the filtered RSSI value of the target Bluetooth node j. This represents the filtered RSSI value of the target Bluetooth node j two cycles ago.

[0061] It should be noted that if the second analysis result of the target Bluetooth node is abnormal, it can be further determined whether it is a mild or severe anomaly. For example, if the second absolute difference is greater than the second threshold but less than the fourth threshold, the second analysis result of the target Bluetooth node is determined to be a mild anomaly; if the second absolute difference is greater than the fourth threshold, the second analysis result of the target Bluetooth node is determined to be a severe anomaly. The fourth threshold is greater than the second threshold.

[0062] In this embodiment, different vehicle models have their own dedicated second and fourth thresholds. This eliminates the need for adjustments for individual vehicles, ensuring a simple and efficient calibration process.

[0063] In some embodiments of this application, determining the target weight coefficients for each of the plurality of Bluetooth nodes based on their respective analysis results includes... Figure 4 The steps shown are as follows: S401: If the analysis result of at least one Bluetooth node indicates an anomaly, based on the analysis results of multiple Bluetooth nodes, perform joint correction processing on the preset weight coefficients of each Bluetooth node to obtain the corrected weight coefficients of each Bluetooth node, and use the corrected weight coefficients of each Bluetooth node as the corresponding target weight coefficients.

[0064] In this embodiment, the preset weight coefficients of the multiple Bluetooth nodes may be equal or unequal. The sum of the preset weight coefficients of the multiple Bluetooth nodes is 1.

[0065] For example, in the case of equality, if the vehicle is equipped with four Bluetooth nodes 1, 2, 3, and 4, then the preset weighting coefficient of each Bluetooth node 1, 2, 3, and 4 is 0.25.

[0066] For example, in cases of unequal frequency, a preset weighting coefficient can be set based on the historical frequency of the user's proximity to the Bluetooth node. If Bluetooth node 1 is installed on the driver's side door pillar near the door handle, Bluetooth node 2 is installed on the inside of the front bumper, Bluetooth node 3 is installed on the passenger side door pillar near the door handle, and Bluetooth node 4 is installed on the inside of the rear bumper, and the historical frequency of the user's proximity to Bluetooth node 1 is higher than that of Bluetooth node 2, the historical frequency of proximity to Bluetooth node 2 is higher than that of Bluetooth node 3, and the historical frequency of proximity to Bluetooth node 3 is the same as that of proximity to Bluetooth node 4, then the preset weighting coefficient for Bluetooth node 1 can be 0.4, the preset weighting coefficient for Bluetooth node 2 can be 0.3, the preset weighting coefficient for Bluetooth node 3 can be 0.15, and the preset weighting coefficient for Bluetooth node 4 can be 0.15.

[0067] In this embodiment of the application, when the analysis result of at least one Bluetooth node is abnormal, it is necessary to adjust the preset weight coefficients of all Bluetooth nodes as a whole, i.e., joint correction processing.

[0068] It should be noted that the corrected weighting coefficient of Bluetooth nodes with abnormal analysis results is less than that of Bluetooth nodes with normal analysis results.

[0069] S402: If the analysis results of multiple Bluetooth nodes indicate that they are normal, use the preset weight coefficients of each of the multiple Bluetooth nodes as the target weight coefficients.

[0070] For example, if a vehicle is equipped with four Bluetooth nodes 1, 2, 3, and 4, and the preset weight coefficient of each Bluetooth node 1, 2, 3, and 4 is 0.25, then the target weight coefficient of each Bluetooth node 1, 2, 3, and 4 is 0.25.

[0071] For example, if a vehicle is equipped with four Bluetooth nodes 1, 2, 3, and 4, and the preset weight coefficient of Bluetooth node 1 is 0.4, the preset weight coefficient of Bluetooth node 2 is 0.3, the preset weight coefficient of Bluetooth node 3 is 0.15, and the preset weight coefficient of Bluetooth node 4 is 0.15, then the target weight coefficient of Bluetooth node 1 is 0.4, the target weight coefficient of Bluetooth node 2 is 0.3, the target weight coefficient of Bluetooth node 3 is 0.15, and the target weight coefficient of Bluetooth node 4 is 0.15.

[0072] In this embodiment, the target weight coefficients of each Bluetooth node are dynamically adjusted based on the analysis results of each node. This is done to maximize the retention of effective signals while eliminating interference.

[0073] In some embodiments of this application, when the analysis results of at least one Bluetooth node indicate an anomaly, the step of jointly correcting the preset weight coefficients of the plurality of Bluetooth nodes based on their respective analysis results to obtain corrected weight coefficients for each of the plurality of Bluetooth nodes includes: For the first Bluetooth node with abnormal analysis results, the preset weight coefficient of the first Bluetooth node is reduced to obtain the corresponding corrected weight coefficient. For the second Bluetooth node with normal analysis results, increase the preset weight coefficient of the second Bluetooth node to obtain the corresponding corrected weight coefficient; The sum of the corrected weighting coefficients of the first Bluetooth node and the corrected weighting coefficients of the second Bluetooth node is 1.

[0074] For example, if the analysis results of Bluetooth node 1 indicate an abnormality, while the analysis results of Bluetooth nodes 2, 3, and 4 indicate a normality, the preset weight coefficient of Bluetooth node 1 is reduced by 0.25 to obtain the corresponding corrected weight coefficient of 0.1, and the preset weight coefficients of Bluetooth nodes 2, 3, and 4 are increased by 0.25 to obtain the corresponding corrected weight coefficient of 0.3.

[0075] For example, if the analysis results of Bluetooth node 1 indicate an anomaly, while the analysis results of Bluetooth nodes 2, 3, and 4 indicate normal results, the preset weight coefficient of Bluetooth node 1 is reduced by 0.4 to obtain the corresponding corrected weight coefficient of 0.1; the preset weight coefficient of Bluetooth node 2 is increased by 0.3 to obtain the corresponding corrected weight coefficient of 0.4; the preset weight coefficient of Bluetooth node 3 is increased by 0.15 to obtain the corresponding corrected weight coefficient of 0.25; and the preset weight coefficient of Bluetooth node 4 is increased by 0.15 to obtain the corresponding corrected weight coefficient of 0.25.

[0076] Furthermore, in some embodiments, for a third Bluetooth node with slightly abnormal analysis results, the preset weight coefficient of the third Bluetooth node is reduced to obtain the corresponding corrected weight coefficient; the corrected weight coefficient of the third Bluetooth node is greater than 0. For the fourth Bluetooth node, which shows a severe anomaly in the analysis results, the preset weight coefficient of the fourth Bluetooth node is reduced, resulting in a corrected weight coefficient of 0.

[0077] For example, if the analysis result of Bluetooth node 3 indicates severe abnormality, while the analysis results of Bluetooth nodes 1, 2, and 4 indicate normality, the preset weight coefficient of Bluetooth node 3 is reduced by 0.25 to obtain the corresponding corrected weight coefficient of 0, and the preset weight coefficients of Bluetooth nodes 1, 2, and 4 are increased by 0.25 to obtain the corresponding corrected weight coefficient of 1 / 3.

[0078] In some embodiments of this application, the method further includes: For the first Bluetooth node with abnormal analysis results, if the analysis results of the first Bluetooth node are normal for P consecutive periods, and the analysis results of the other Bluetooth nodes are normal, then the corrected weight coefficients of the multiple Bluetooth nodes are jointly restored to obtain the preset weight coefficients of the multiple Bluetooth nodes, and the preset weight coefficients of the multiple Bluetooth nodes are used as the corresponding target weight coefficients; P≥2, where P is an integer.

[0079] In this embodiment of the application, if the analysis results of the first Bluetooth node are normal for the next P consecutive periods, the abnormal state is determined to be resolved and the node is automatically restored to the preset weight coefficient.

[0080] For example, if the analysis result of Bluetooth node 1 indicates an anomaly, and the analysis results of the first Bluetooth node are normal for the next two consecutive cycles, and the analysis results of Bluetooth nodes 2, 3, and 4 are also normal, the corrected weight coefficient of Bluetooth node 1 (0.1) will be restored to the preset weight coefficient of 0.25, and the corrected weight coefficient of Bluetooth nodes 2, 3, and 4 (0.3) will be restored to the preset weight coefficient of 0.25.

[0081] In some embodiments of this application, the joint recovery processing of the corrected weight coefficients of the plurality of Bluetooth nodes to obtain the preset weight coefficients of the plurality of Bluetooth nodes includes: A smooth transition method is adopted, gradually increasing the corrected weight coefficient of the first Bluetooth node to the corresponding preset weight coefficient, and gradually decreasing the corrected weight coefficient of the other Bluetooth nodes to the corresponding preset weight coefficient. The latest value obtained during the weighting coefficient adjustment process is used as the target weighting coefficient.

[0082] In this embodiment of the application, a smooth transition method is adopted during the recovery process, which can avoid the target RSSI value from jumping due to sudden changes in the weight coefficient, thereby causing system misjudgment.

[0083] For example, if the analysis result of Bluetooth node 1 indicates an anomaly, and the analysis results of the first Bluetooth node are normal for the next two consecutive cycles, and the analysis results of Bluetooth nodes 2, 3, and 4 are also normal, then the corrected weight coefficient of Bluetooth node 1 (0.1) is adjusted to 0.13 (the latest value), and the corrected weight coefficient of Bluetooth nodes 2, 3, and 4 (0.3) is adjusted to 0.29. Then, in the next four cycles, if the analysis results of Bluetooth nodes 1, 2, 3, and 4 are normal, then the corrected weight coefficient of Bluetooth node 1 (0.13) is adjusted to 0.16, 0.19, 0.22, and 0.25 respectively, and the corrected weight coefficient of Bluetooth nodes 2, 3, and 4 (0.29) is adjusted to 0.28, 0.27, 0.26, and 0.25 respectively.

[0084] In some embodiments of this application, controlling the vehicle to perform the locking / unlocking operation based on the target received signal strength indication value includes... Figure 5 The steps shown are as follows: S501: When the target received signal strength indication value is greater than the target unlock threshold, an unlock command is sent to the vehicle body controller. The unlock command is used to control the vehicle to perform the unlock operation.

[0085] like Figure 6 As shown, with the vehicle body as the origin, unlocking area A, buffer area B, and locking area C are set.

[0086] In this embodiment, when the target RSSI value is detected to be greater than the minimum RSSI value (i.e., the unlock threshold) of the unlock area, that is, when the user is detected to have entered the unlock area A (the radius of which is usually set to 3 to 5 meters), the main control module sends an unlock command to the body controller, causing the body controller to respond to the unlock command and control the vehicle to unlock. This ensures that unlocking is triggered when the user approaches the door. In addition, related functions such as interior lighting and exterior rearview mirror deployment can also be activated simultaneously.

[0087] S502: When the target received signal strength indication value is less than the target locking threshold and continues for a preset duration, a locking command is sent to the vehicle body controller. The locking command is used to control the vehicle to perform a locking operation.

[0088] In this embodiment, when the target RSSI value is detected to be less than the maximum RSSI value of the locking area (i.e., the locking threshold), it is detected that the user has entered the locking area C (the radius of which is usually set to 8 to 10 meters). In order to avoid erroneous operation caused by instantaneous signal fluctuations, the system sets a 3 to 5 second delay confirmation mechanism. During this period, it continuously monitors whether the user is stably in the locking area. After confirming that there is no error, it sends a locking command to perform actions such as locking the doors, closing the windows, and folding the rearview mirrors.

[0089] In some embodiments of this application, the method further includes: Obtain the identification information of the target mobile device; Based on the correspondence between the identification information of multiple mobile devices and the unlock threshold and the lock threshold, the target unlock threshold and the target lock threshold corresponding to the identification information of the target mobile device are queried.

[0090] In this embodiment, multiple mobile devices may include a user's smartphone, smartwatch, or smart key, etc.

[0091] Different mobile devices have corresponding unlock thresholds and lock thresholds.

[0092] Based on this, the system obtains the correspondence between the identification information of multiple mobile devices (such as smartphones, smartwatches, and smart keys) and the unlocking and locking thresholds. If the target mobile device is a smart key, the system queries the target unlocking threshold and target locking threshold corresponding to the smart key from the correspondence.

[0093] This ensures the accuracy of locking and unlocking vehicles using different mobile devices.

[0094] In some embodiments of this application, the method further includes: Obtain the received signal strength indication values ​​from the mobile device collected by the plurality of Bluetooth nodes in the most recent Q periods; Q≥2, where Q is an integer; The second value is obtained by averaging all the received signal strength indication values ​​collected. Based on the difference between the second value and the first offset, the unlock threshold corresponding to the mobile device is obtained; Based on the difference between the second value and the second offset, the latching threshold corresponding to the mobile device is obtained; Establish and store the correspondence between the identification information of the multiple mobile devices and the unlocking threshold and the locking threshold.

[0095] In this embodiment of the application, different vehicle models have corresponding exclusive first and second offsets.

[0096] For example, taking a 200ms period as an example, for a mobile device, the filtered RSSI values ​​of the Bluetooth nodes are continuously collected for 10 seconds, generating 5 data points per second. The total of 200 data points from the four Bluetooth nodes form a mean sequence, and the arithmetic mean of this sequence is calculated as the calibration benchmark. (i.e., the second value). During the data acquisition process, the stability of the data is monitored in real time. If the data fluctuation exceeds the preset range (e.g., ±8dB) within a certain period of time, the acquisition time is automatically extended, for example, by 15 seconds, to ensure the reliability of the baseline value.

[0097] Unlock threshold Equation (4) expresses this as: (4) Lockout threshold Equation (5) is expressed as: (5) in, , Preset experience values ​​(such as) =6dB =12dB), determined by testing real vehicles in various environments (such as open fields, underground parking garages, and dense building complexes), ensuring that mobile devices with different transmission powers can achieve a consistent response distance. After calibration, the system will , The threshold is associated with the Bluetooth Media Access Control (MAC) address of the mobile device, and subsequent unlocking and locking decisions of the device are performed based on this threshold.

[0098] Based on the above embodiments, this application example illustrates the use of four Bluetooth nodes installed on a vehicle: like Figure 2 As shown, the vehicle is equipped with four Bluetooth nodes, which can be fixed at the left B-pillar 101, right B-pillar 102, front bumper 103, and rear bumper 104 respectively, forming a spatially symmetrical signal sensing network covering a 360° area around the vehicle. The Bluetooth nodes on the left and right B-pillars are installed on the door pillars near the door handles to ensure stable signal when the user operates the vehicle from the side. The Bluetooth nodes on the front and rear bumpers are embedded inside the bumpers to avoid signal shielding by metal components, ensuring strong signal coverage in the front and rear directions. The vehicle also includes an in-vehicle Bluetooth master control unit 300 and a body controller 400.

[0099] Based on this, the vehicle unlocking and locking control methods include Figure 7 The steps shown are as follows: S701: The vehicle establishes a Bluetooth connection with the target mobile device.

[0100] like Figure 2 As shown, the target mobile device 200 (such as a smartphone) establishes a BLE connection with the vehicle's in-vehicle Bluetooth master control unit 300. The user polls four Bluetooth nodes at 200ms intervals as they gradually approach the driver's seat from the front of the vehicle.

[0101] S702: Collects RSSI values ​​of four Bluetooth nodes for five consecutive cycles.

[0102] S703: Performs smoothing filtering on the 5 RSSI values ​​of each Bluetooth node to obtain the filtered RSSI value.

[0103] The original RSSI value at a certain moment is: , , , Assuming it undergoes a moving average filter (5 periods), we get: =-64dB =-67dB =-59dB =-65dB.

[0104] S704: Based on the weight coefficients corresponding to each Bluetooth node, the filtered RSSI values ​​of the four Bluetooth nodes are weighted and fused to obtain the target RSSI value.

[0105] The overall mean was calculated using a weighted average (with a weighting coefficient of 0.4 for the front bumper node, 0.25 for the left B-pillar node, and 0.225 for all other nodes). (i.e., the target RSSI value):

[0106] S705: Based on the relationship between the target RSSI value and the unlocking threshold and locking threshold, determine whether to enter the unlocked area or the locked area.

[0107] Known unlock threshold for the target mobile device -64dB, latching threshold It is -72dB.

[0108] exist (-63.4) is greater than the unlock threshold. If (-64) is detected, and the unlock zone is entered, then S706 is executed.

[0109] After unlocking the car, the user stays inside briefly, then leaves the vehicle with the device, gradually moving away from the driver's side.

[0110] The system continuously collects data at 200ms intervals. At a certain moment, the filtered RSSI value is: =-70dB =-73dB =-75dB =-71dB.

[0111] If the weighting coefficient of each Bluetooth node is 0.25, then

[0112] exist (-72.25) is less than the latching threshold. If (-72) is detected, and the locked area is entered, then S707 is executed.

[0113] S706: Sends an unlock command to the body controller, which is used to perform the unlocking operation.

[0114] It can also activate the welcome lights and unfold the exterior rearview mirrors.

[0115] S707: Determine whether the area remains in the locked zone for a preset duration.

[0116] A 3-second delay is initiated for confirmation, during which 15 cycles are continuously monitored (3000ms / 200ms=15 cycles, 15 cycles in 3 seconds). The average RSSI value is stable between -72.5dB and -73dB, confirming that the user has moved away. After the delay ends, a command is sent to the vehicle body controller to execute the actions of locking the doors, closing the windows, and folding the rearview mirrors.

[0117] If it is determined that the area remains in the locked zone for a preset duration, then S708 is executed; otherwise, the locking operation is not executed.

[0118] S708: Sends a locking command to the body control unit; the unlocking command is used to perform the locking operation.

[0119] S709: Do not perform the locking operation.

[0120] Different mobile devices have their own specific unlock and lock thresholds. Based on this, the calibration method for the unlock and lock thresholds of the new smartphone is described below: The user places the new smartphone 1.5 meters away from the car on the driver's side and initiates Bluetooth pairing via the central control screen. After successful pairing, the system prompts "Pacifying device, please keep the phone in a stable position".

[0121] Data acquisition: Collect 10 seconds of data (50 points) at a 200ms interval, and generate smooth values ​​for each node after moving average filtering.

[0122] Benchmark calculation: Calculate the arithmetic mean of a four-node mean sequence (50 means). .

[0123] Threshold generation: based on vehicle model presets =6dB =12dB, generating the unlock threshold: =-58-6=-64dB, latching threshold =-58-12=-70dB.

[0124] Storage association: , The threshold is associated with and stored in relation to the Bluetooth MAC address of the new smartphone and will be automatically invoked during subsequent use.

[0125] Because the filtered RSSI values ​​of Bluetooth nodes exhibit anomalies, it is necessary to perform anomaly analysis on the filtered RSSI values ​​of each Bluetooth node. This includes... Figure 8 The steps shown are as follows: S801: Obtain the filtered RSSI values ​​of the four Bluetooth nodes.

[0126] S802: Calculate the deviation and volatility of each of the four Bluetooth nodes.

[0127] Deviation is the first absolute difference. First absolute difference This can be expressed by formula (1): (1) in, This represents the filtered RSSI value of the target Bluetooth node j. This represents the average value of the filtered RSSI values ​​of the remaining Bluetooth nodes; This can be expressed by formula (2): (2) This feature reflects the spatial consistency of a single node with other nodes. If a node becomes abnormal due to occlusion, its deviation from other nodes will increase significantly.

[0128] Volatility, also known as the second absolute difference Second absolute difference This can be expressed by formula (3): (3) in, This represents the filtered RSSI value of the target Bluetooth node j. This represents the filtered RSSI value of the target Bluetooth node j two cycles ago.

[0129] This characteristic reflects the stability of the signal in the time dimension. Under normal circumstances, the user's movement speed is limited (walking speed is about 1.2m / s), and the rate of change of RSSI value with distance is relatively smooth. However, abnormal interference (such as sudden obstruction or metal reflection) will cause violent fluctuations in a short period of time.

[0130] S803: Determine abnormal status.

[0131] Grading and judgment rules: Abnormal states are divided into mild abnormality, severe abnormality and normal state.

[0132] Mild anomaly: When the node's deviation degree exist (i.e., the first threshold) to (i.e., between the third threshold) and volatility exist (i.e., the second threshold) to When the signal falls within the range of the fourth threshold, it is considered a mild anomaly. Such cases are mostly transient multipath reflections or partial obstruction; although the signal fluctuates, it is not completely distorted and still contains some valid information.

[0133] Severe anomaly: When the deviation of a node is... And volatility Initially, it is judged as a severe anomaly. To avoid misjudgment caused by transient interference, the above conditions must be met for two consecutive cycles (400ms) before the node is finally confirmed as a severe anomaly. Such situations are mostly due to complete blockage, equipment failure, or strong electromagnetic interference, where the signal is severely distorted, and continued use will significantly affect the judgment results.

[0134] Normal state: Nodes that do not meet the above mild or severe abnormal conditions are judged to be in a normal state and participate in regular calculations.

[0135] It should be noted that the deviation threshold required for anomaly detection (i.e., the first threshold) Second threshold Volatility threshold (i.e., the second threshold) Fourth threshold The parameters are preset to vehicle model-specific parameters through real-vehicle testing (applicable to all vehicles of the same model), eliminating the need for adjustments to individual vehicles or equipment, ensuring a simple and efficient calibration process that users can complete independently.

[0136] S804: Adjust weights for minor anomalies.

[0137] S805: Default weight in normal state.

[0138] S806: Severe anomaly removal process.

[0139] Dynamic processing strategy: Differentiated processing measures are adopted based on the anomaly level of Bluetooth nodes to maximize the retention of effective signals while eliminating interference. For mildly anomalous nodes: A weight reduction strategy is adopted, decreasing their weight in the overall average calculation from 0.25 (equal weight for all four nodes) to 0.1, while the weights of the other three normal nodes are increased to 0.3 (the sum remains 1). This strategy retains some information from mildly anomalous nodes (avoiding data loss due to complete removal) while reducing their interference with the overall result, making it suitable for scenarios with fluctuating but not completely failed signals. For severely anomalous nodes: A direct removal strategy is adopted, calculating the overall average (arithmetic mean) based on the filtered values ​​of the remaining three nodes. The logic is simple and easy to implement.

[0140] S807: Calculate the target RSSI value.

[0141] S808: Region determination.

[0142] For specific steps, please refer to S705 to S709, which will not be repeated here.

[0143] Based on this, here is an example of a single-point occlusion anomaly scenario: The user is standing on the right side of the vehicle, and their body is blocking the signal at node 102 on the right B-pillar. The filtered RSSI value is: =-62dB =-87dB =-64dB =-63dB.

[0144] Anomaly feature calculation: 102 Bluetooth nodes:

[0145] The condition is met for two consecutive cycles; (-66 is the RSSI value from 2 periods ago) Other Bluetooth nodes all dB all dB, determined to be normal; Assessment result: Bluetooth node 102 is severely abnormal. Processing strategy: Remove 102 Bluetooth nodes and calculate the average value based on the remaining three Bluetooth nodes.

[0146] Overall mean calculation: dB Region determination: dB dB, -63dB is in the unlocked zone ( <-63); Action Trigger: The system is in an abnormal processing state, triggering unlocking to prevent the user from being mistakenly judged to have moved away due to the abnormality of the 102 Bluetooth node.

[0147] Here is another example of a multipath interference scenario: The user was waiting in front of the vehicle. A nearby metal fence caused signal fluctuations at the Bluetooth node 103 on the front bumper. The system collected the following data: The RSSI value after filtering at a certain moment is: =-62dB =-64dB =-75dB =-63dB.

[0148] Anomaly feature calculation: For Bluetooth node 103: ,lie in to between ,lie in to between Other nodes: All < , All < =8dB, considered normal; Assessment result: Bluetooth node 103 is slightly abnormal; Processing strategy: Reduce the preset weight coefficient of Bluetooth node 103 from 0.25 to the target weight coefficient of 0.1, and increase the preset weight coefficient of the other three nodes from 0.25 to the target weight coefficient of 0.3; Overall mean calculation: dB Area determination: In the unlocked area ( =-65dB<-64.2); Action Trigger: Triggers the unlock action to avoid misjudgments caused by multipath interference.

[0149] Here is another example of an exception recovery scenario: Following the above embodiment, the user moves their body to remove the obstruction of Bluetooth node 102, and the signal gradually recovers.

[0150] The RSSI value after filtering at a certain moment is: =-63dB =-66dB =-65dB =-64dB.

[0151] Anomaly feature calculation: For 102 Bluetooth nodes: (< =10dB) (< =8dB), satisfied for 2 consecutive cycles; Judgment result: The abnormal state of Bluetooth node 102 has been resolved; Recovery strategy: The weight of Bluetooth node 102 is smoothly restored from the removed state (0.1 in the first cycle, 0.2 in the second cycle, and 0.25 in the third cycle). Comprehensive mean calculation (after restoration): all four nodes are equally weighted. .

[0152] Area determination: If the area is in the unlocked zone, the system resumes normal processing logic, and the locking delay is adjusted back to 3 seconds from 4 seconds.

[0153] This application has the following beneficial effects: 1. Enhanced anti-interference capability: Multi-node RSSI mean fusion can smooth single-point signal fluctuations. Combined with the abnormal node adaptive processing mechanism, even if a node fails due to occlusion, the remaining nodes can still maintain positioning stability.

[0154] 2. Significantly improved calibration efficiency: By using a unified threshold calibration mechanism, the traditional four-node independent calibration (each group of nodes needs to collect data at three locations: near, middle, and far, requiring a total of 12 sets of parameters) is simplified into a single global calibration, reducing the time taken from an average of 45 minutes to less than 10 minutes, improving efficiency by more than 75%, reducing the professional requirements for operators, and making it suitable for mass production deployment.

[0155] 3. User experience optimization: The buffer design avoids the phenomenon of "repeated unlocking-locking" in the boundary area; the unified threshold is adaptively adjusted through the benchmark value, which can be compatible with the differences in transmission power of different brands and models of mobile devices.

[0156] 4. High cost controllability: Based on standard Bluetooth modules, it does not require additional Angle of Arrival (AoA) / Time of Flight (ToF) dedicated chips, and has significant industrialization prospects.

[0157] Based on the above embodiments, this application also provides a vehicle locking / unlocking control device. Figure 9 This is a schematic diagram of the structure of the vehicle locking / unlocking control device provided in the embodiments of this application. Multiple Bluetooth nodes are installed on the vehicle, such as... Figure 9 As shown, the vehicle unlocking and locking control device 90 includes: Acquisition unit 901 is used to acquire received signal strength indication values ​​from the target mobile device collected by multiple Bluetooth nodes in the most recent M cycles; M≥2, M is an integer; The filtering unit 902 is used to filter the received signal strength indication values ​​of the target Bluetooth node collected in the most recent M periods to obtain the filtered received signal strength indication value of the target Bluetooth node in the current period; the target Bluetooth node is any one of the plurality of Bluetooth nodes; Anomaly analysis unit 903 is used to perform anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period, and obtain the analysis result of the target Bluetooth node. The processing unit 904 is used to determine the target weight coefficient of each of the plurality of Bluetooth nodes based on the analysis results of each of the plurality of Bluetooth nodes. The processing unit 904 is further configured to obtain a target received signal strength indication value based on the target weight coefficients of the plurality of Bluetooth nodes in the current period and the filtered received signal strength indication value. Control unit 905 is used to control the vehicle to perform unlocking and locking operations based on the target received signal strength indication value.

[0158] In this embodiment, the target weight coefficients for each of the multiple Bluetooth nodes are dynamically set based on whether their analysis results are normal or abnormal. Typically, the target weight coefficient for Bluetooth nodes with normal analysis results is greater than that for Bluetooth nodes with abnormal analysis results. Subsequently, the target weight coefficients of each Bluetooth node and the filtered received signal strength index (RSSI) are weighted and fused. This method effectively suppresses interference from abnormal nodes on the fusion result, thereby improving the accuracy of the target RSSI value after weighted fusion, ultimately ensuring the reliability and accuracy of the vehicle intelligent unlocking and locking system.

[0159] In some embodiments of this application, the anomaly analysis unit 903 is specifically used to perform spatial dimension anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period based on the filtered received signal strength indication value of other Bluetooth nodes in the current period, to obtain a first analysis result of the target Bluetooth node; and / or, based on the filtered received signal strength indication value of the target Bluetooth node obtained N periods ago, perform temporal dimension anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period, to obtain a second analysis result of the target Bluetooth node; N≥1, N is an integer; based on the first analysis result and / or the second analysis result of the target Bluetooth node, the analysis result of the target Bluetooth node is obtained.

[0160] In some embodiments of this application, the anomaly analysis unit 903 is further configured to average the filtered received signal strength indication values ​​of the other Bluetooth nodes in the current period to obtain a first value; based on the absolute difference between the first value and the filtered received signal strength indication value of the target Bluetooth node in the current period, obtain a first absolute difference; and based on the relationship between the first absolute difference and a first threshold, determine whether the first analysis result of the target Bluetooth node is normal or abnormal.

[0161] In some embodiments of this application, the anomaly analysis unit 903 is further configured to obtain a second absolute difference based on the absolute difference between the filtered received signal strength indication value of the target Bluetooth node N periods ago and the filtered received signal strength indication value of the target Bluetooth node in the current period; and to determine whether the second analysis result of the target Bluetooth node is normal or abnormal based on the relationship between the second absolute difference and the second threshold.

[0162] In some embodiments of this application, the processing unit 904 is specifically configured to, when the analysis results of at least one Bluetooth node indicate an anomaly, perform joint correction processing on the preset weight coefficients of the plurality of Bluetooth nodes according to the analysis results of the plurality of Bluetooth nodes, to obtain the corrected weight coefficients of the plurality of Bluetooth nodes, and use the corrected weight coefficients of the plurality of Bluetooth nodes as the corresponding target weight coefficients; when the analysis results of the plurality of Bluetooth nodes indicate a normal result, use the preset weight coefficients of the plurality of Bluetooth nodes as the target weight coefficients.

[0163] In some embodiments of this application, the processing unit 904 is further configured to reduce the preset weight coefficient of the first Bluetooth node for the first Bluetooth node with abnormal analysis results, and obtain the corresponding corrected weight coefficient; and to increase the preset weight coefficient of the second Bluetooth node for the second Bluetooth node with normal analysis results, and obtain the corresponding corrected weight coefficient; the sum of the corrected weight coefficient of the first Bluetooth node and the corrected weight coefficient of the second Bluetooth node is 1.

[0164] In some embodiments of this application, the processing unit 904 is further configured to, for the first Bluetooth node with abnormal analysis results, if the analysis results of the first Bluetooth node are normal for P consecutive cycles and the analysis results of the other Bluetooth nodes are normal, then perform joint recovery processing on the corrected weight coefficients of the multiple Bluetooth nodes to obtain the preset weight coefficients of the multiple Bluetooth nodes, and use the preset weight coefficients of the multiple Bluetooth nodes as the corresponding target weight coefficients; P≥2, where P is an integer.

[0165] In some embodiments of this application, the processing unit 904 is further configured to use a smooth transition method to gradually increase the corrected weight coefficient of the first Bluetooth node to the corresponding preset weight coefficient, and gradually decrease the corrected weight coefficient of the remaining Bluetooth nodes to the corresponding preset weight coefficient; and use the latest value obtained during the weight coefficient adjustment process as the target weight coefficient.

[0166] In some embodiments of this application, the control unit 905 is specifically configured to send an unlock command to the vehicle body controller when the target received signal strength indication value is greater than the target unlock threshold, the unlock command being used to control the vehicle to perform an unlock operation; and to send a lock command to the vehicle body controller when the target received signal strength indication value is less than the target lock threshold and remains so for a preset duration, the lock command being used to control the vehicle to perform a lock operation.

[0167] In some embodiments of this application, the processing unit 904 is further configured to obtain the identification information of the target mobile device; and based on the correspondence between the identification information of multiple mobile devices and the unlock threshold and the lock threshold, query the target unlock threshold and the target lock threshold corresponding to the identification information of the target mobile device.

[0168] In some embodiments of this application, the processing unit 904 is further configured to acquire received signal strength indication values ​​from the mobile device collected by the plurality of Bluetooth nodes in the most recent Q periods; Q≥2, where Q is an integer; average all the collected received signal strength indication values ​​to obtain a second value; obtain the unlock threshold corresponding to the mobile device based on the difference between the second value and the first offset; obtain the lock threshold corresponding to the mobile device based on the difference between the second value and the second offset; establish and store the correspondence between the identification information of the plurality of mobile devices and the unlock threshold and the lock threshold.

[0169] This application also provides another vehicle. Figure 10 This is a schematic diagram of the structure of the vehicle provided in the embodiments of this application, such as... Figure 10 As shown, the vehicle 100 includes: a processor 1001 and a memory 1002 configured to store computer programs capable of running on a central controller; When the processor 1001 is configured to run a computer program, it executes the method steps described in the foregoing embodiments.

[0170] Of course, in practical applications, such as Figure 10 As shown, the various components in the vehicle 100 are coupled together via a bus system 1003. It is understood that the bus system 1003 is used to enable communication between these components. In addition to a data bus, the bus system 1003 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 10 The general labeled all buses as Bus System 1003.

[0171] In practical applications, the aforementioned processor can be at least one of the following: Application-Specific Integrated Circuit (ASIC), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field-Programmable Gate Array (FPGA), controller, microcontroller, and microprocessor. It is understood that, for different devices, the electronic devices used to implement the functions of the aforementioned processor can also be other types, and this embodiment of the invention does not impose specific limitations.

[0172] The aforementioned memory can be volatile memory, such as random access memory (RAM). Access memory); or non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); or a combination of the above types of memory, and providing instructions and data to the processor.

[0173] In an exemplary embodiment, the present invention also provides a computer-readable storage medium for storing a computer program.

[0174] Optionally, the computer-readable storage medium can be applied to any of the methods in the embodiments of the present invention, and the computer program causes the computer to execute the corresponding processes implemented by the processor in the various methods of the embodiments of the present invention. For the sake of brevity, these will not be described in detail here.

[0175] In the several embodiments provided by this invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0176] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0177] Furthermore, in the various embodiments of the present invention, all functional units can be integrated into one processing module, or each unit can be a separate unit, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional units. Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0178] The methods disclosed in the several method embodiments provided by this invention can be arbitrarily combined without conflict to obtain new method embodiments.

[0179] The features disclosed in the several product embodiments provided by this invention can be arbitrarily combined without conflict to obtain new product embodiments.

[0180] The features disclosed in the several method or device embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0181] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, and improvements made within the spirit and scope of this application are included within the scope of protection of this application.

Claims

1. A vehicle unlocking / locking control method, characterized in that, The vehicle is equipped with multiple Bluetooth nodes, and the method includes: Obtain the received signal strength indication values ​​from the target mobile device collected by multiple Bluetooth nodes in the most recent M periods; M≥2, M is an integer; The received signal strength indication values ​​of the target Bluetooth node collected in the most recent M periods are filtered to obtain the filtered received signal strength indication value of the target Bluetooth node in the current period; the target Bluetooth node is any one of the plurality of Bluetooth nodes; Anomaly analysis is performed on the filtered received signal strength indication value of the target Bluetooth node in the current period to obtain the analysis result of the target Bluetooth node; Based on the analysis results of each of the multiple Bluetooth nodes, the target weight coefficients of each of the multiple Bluetooth nodes are determined. Based on the target weight coefficients of each of the multiple Bluetooth nodes in the current period and the filtered received signal strength indication value, the target received signal strength indication value is obtained. Based on the target received signal strength indication value, the vehicle is controlled to perform an unlocking / locking operation.

2. The method according to claim 1, characterized in that, The anomaly analysis of the filtered received signal strength indication value of the target Bluetooth node in the current period, to obtain the analysis result of the target Bluetooth node, includes: Based on the filtered received signal strength indication values ​​of other Bluetooth nodes in the current period, anomaly analysis is performed on the filtered received signal strength indication value of the target Bluetooth node in the current period in the spatial dimension to obtain the first analysis result of the target Bluetooth node. And / or, based on the filtered received signal strength indication value of the target Bluetooth node obtained N periods ago, perform time-dimensional anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period to obtain the second analysis result of the target Bluetooth node; N≥1, N is an integer; Based on the first and / or second analysis results of the target Bluetooth node, the analysis results of the target Bluetooth node are obtained.

3. The method according to claim 2, characterized in that, The first analysis result of the target Bluetooth node is obtained by performing spatial dimension anomaly analysis on the filtered received signal strength indication value of the other Bluetooth nodes in the current period, based on the filtered received signal strength indication value of the other Bluetooth nodes in the current period, including: The filtered received signal strength indication values ​​of the other Bluetooth nodes in the current cycle are averaged to obtain the first value; The first absolute difference is obtained based on the absolute difference between the first value and the filtered received signal strength indication value of the target Bluetooth node in the current period; Based on the relationship between the first absolute difference and the first threshold, it is determined whether the first analysis result of the target Bluetooth node is normal or abnormal.

4. The method according to claim 2, characterized in that, The second analysis result of the target Bluetooth node is obtained by performing a time-dimensional anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period based on the filtered received signal strength indication value of the target Bluetooth node obtained N periods ago, including: The second absolute difference is obtained based on the absolute difference between the filtered received signal strength indication value of the target Bluetooth node N periods ago and the filtered received signal strength indication value of the target Bluetooth node in the current period. Based on the relationship between the second absolute difference and the second threshold, it is determined whether the second analysis result of the target Bluetooth node is normal or abnormal.

5. The method according to any one of claims 1 to 4, characterized in that, The step of determining the target weight coefficients for each of the multiple Bluetooth nodes based on their respective analysis results includes: If the analysis results of at least one Bluetooth node indicate an anomaly, the preset weight coefficients of the Bluetooth nodes are jointly corrected based on their respective analysis results to obtain the corrected weight coefficients of the Bluetooth nodes. The corrected weight coefficients of the Bluetooth nodes are then used as the corresponding target weight coefficients. If the analysis results of the multiple Bluetooth nodes indicate that everything is normal, the preset weight coefficients of each of the multiple Bluetooth nodes are used as the target weight coefficients.

6. The method according to claim 5, characterized in that, In the event that the analysis results of at least one Bluetooth node indicate an anomaly, a joint correction process is performed on the preset weight coefficients of each of the multiple Bluetooth nodes based on their respective analysis results, resulting in corrected weight coefficients for each of the multiple Bluetooth nodes, including: For the first Bluetooth node with abnormal analysis results, the preset weight coefficient of the first Bluetooth node is reduced to obtain the corresponding corrected weight coefficient. For the second Bluetooth node with normal analysis results, increase the preset weight coefficient of the second Bluetooth node to obtain the corresponding corrected weight coefficient; The sum of the corrected weighting coefficients of the first Bluetooth node and the corrected weighting coefficients of the second Bluetooth node is 1.

7. The method according to claim 5, characterized in that, The method further includes: For the first Bluetooth node with abnormal analysis results, if the analysis results of the first Bluetooth node are normal for P consecutive periods, and the analysis results of the other Bluetooth nodes are normal, then the corrected weight coefficients of the multiple Bluetooth nodes are jointly restored to obtain the preset weight coefficients of the multiple Bluetooth nodes, and the preset weight coefficients of the multiple Bluetooth nodes are used as the corresponding target weight coefficients; P≥2, where P is an integer.

8. The method according to claim 7, characterized in that, The step of jointly recovering the corrected weight coefficients of the plurality of Bluetooth nodes to obtain the preset weight coefficients of each of the plurality of Bluetooth nodes includes: A smooth transition method is adopted, gradually increasing the corrected weight coefficient of the first Bluetooth node to the corresponding preset weight coefficient, and gradually decreasing the corrected weight coefficient of the other Bluetooth nodes to the corresponding preset weight coefficient. The latest value obtained during the weighting coefficient adjustment process is used as the target weighting coefficient.

9. The method according to any one of claims 1 to 4, characterized in that, The step of controlling the vehicle to perform an unlocking / locking operation based on the target received signal strength indication value includes: When the target received signal strength indication value is greater than the target unlock threshold, an unlock command is sent to the vehicle controller, and the unlock command is used to control the vehicle to perform an unlock operation. If the target received signal strength indication value is less than the target locking threshold and remains so for a preset duration, a locking command is sent to the vehicle body controller. The locking command is used to control the vehicle to perform a locking operation.

10. The method according to claim 9, characterized in that, The method further includes: Obtain the identification information of the target mobile device; Based on the correspondence between the identification information of multiple mobile devices and the unlock threshold and the lock threshold, the target unlock threshold and the target lock threshold corresponding to the identification information of the target mobile device are queried.

11. The method according to claim 10, characterized in that, The method further includes: Obtain the received signal strength indication values ​​from the mobile device collected by the plurality of Bluetooth nodes in the most recent Q periods; Q≥2, where Q is an integer; The second value is obtained by averaging all the received signal strength indication values ​​collected. Based on the difference between the second value and the first offset, the unlock threshold corresponding to the mobile device is obtained; Based on the difference between the second value and the second offset, the latching threshold corresponding to the mobile device is obtained; Establish and store the correspondence between the identification information of the multiple mobile devices and the unlocking threshold and the locking threshold.

12. A vehicle unlocking / locking control device, characterized in that, The vehicle is equipped with multiple Bluetooth nodes, and the device includes: The acquisition unit is used to acquire the received signal strength indication values ​​from the target mobile device collected by multiple Bluetooth nodes in the most recent M cycles; M≥2, where M is an integer; The filtering unit is used to filter the received signal strength indication values ​​of the target Bluetooth node collected in the most recent M cycles to obtain the filtered received signal strength indication value of the target Bluetooth node in the current cycle; the target Bluetooth node is any one of the plurality of Bluetooth nodes; An anomaly analysis unit is used to perform anomaly analysis on the filtered received signal strength indication value of the target Bluetooth node in the current period, and obtain the analysis result of the target Bluetooth node. The processing unit is used to determine the target weight coefficient of each of the multiple Bluetooth nodes based on the analysis results of each of the multiple Bluetooth nodes. The processing unit is also configured to obtain a target received signal strength indication value based on the target weight coefficients of the multiple Bluetooth nodes in the current period and the filtered received signal strength indication value. The control unit is used to control the vehicle to perform locking and unlocking operations based on the target received signal strength indication value.

13. A vehicle, characterized in that, The vehicles include: Memory is used to store executable instructions or computer programs. A processor, when executing computer-executable instructions or computer programs stored in the memory, implements the method according to any one of claims 1 to 11.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method described in any one of claims 1 to 11.

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