Digital key calibration data determination method and device, vehicle and storage medium

Abstract

The invention relates to a digital key calibration data determination method and device, a vehicle and a storage medium, and relates to the technical field of vehicle communication. The method comprises the following steps: establishing communication connection with a target vehicle in response to electronic equipment carrying a digital key, and determining whether a scene where the target vehicle is located belongs to a calibration scene or not; determining a signal intensity distribution data set of the target calibration scene in response to the fact that the scene belongs to the calibration scene; and determining calibration data of the digital key corresponding to the target calibration scene based on the signal intensity distribution data set. The calibration data suitable for the calibration scene can be generated, and calibration optimization of the calibration scene is realized, so that the calibration effect can be improved, and the user experience is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of vehicle communication technology, and in particular to a method, device, vehicle and storage medium for determining digital key calibration data. Background Art

[0002] Digital keys, also often referred to as Bluetooth keys or virtual keys, can replace traditional car keys through smart terminals such as mobile phones, and can unlock or lock, start and other operations on the vehicle, which is faster and smarter. In order to ensure the reliability and accuracy of the use of digital keys and the user experience, the received signal strength indicator value is affected by many factors, including environmental noise, multipath effects and device characteristics, so it needs to be calibrated during use to help the vehicle estimate the signal strength more accurately, reduce errors and improve reliability.

[0003] In related technologies, calibration data is generated through preliminary tests and written into the vehicle system in advance or the adapted calibration data is sent to the vehicle system through the cloud to complete the digital key calibration. However, due to the instability of the communication connection signal, the functional experience provided to the user after calibration in different scenarios is unstable. For example, sometimes the key is unlocked when the user is far away from the vehicle, but sometimes it is unlocked when the user is very close to the vehicle, which affects the user experience.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The present disclosure provides a method, device, vehicle and storage medium for determining digital key calibration data.

[0006] According to a first aspect of an embodiment of the present disclosure, a method for determining digital key calibration data is provided, comprising: In response to the electronic device carrying the digital key establishing a communication connection with the target vehicle, determining whether the scene in which the target vehicle is located belongs to a calibration scene; In response to the scene being a calibration scene, determining a signal strength distribution data set of a target calibration scene; Based on the signal strength distribution data set, calibration data of the digital key corresponding to the target calibration scene is determined.

[0007] In some embodiments of the present disclosure, determining whether the scene in which the target vehicle is located belongs to a calibration scene includes: Acquiring location information and parking perception information of the target vehicle; determining at least one signal influencing factor based on the parking perception information; Based on the position information and the at least one signal influencing factor, determining whether there is an adapted target calibration scene from a calibration scene database; Wherein, the calibration scene database includes scene data of a plurality of calibration scenes stored in advance; the scene data includes position information and corresponding signal impact factors; If so, it is determined that the scene where the target vehicle is located belongs to the calibration scene, and the scene where the target vehicle is located is the target calibration scene.

[0008] In some embodiments of the present disclosure, the at least one signal influencing factor includes: a user holding the electronic device.

[0009] In some embodiments of the present disclosure, determining a signal strength distribution dataset includes: Determining a plurality of travel points of the user during travel based on the parking perception information; determining the distance between each of the travel points and the target vehicle; Recording the communication connection signal strength corresponding to each of the travel points; generating a plurality of data groups based on the distance between each of the travel points and the target vehicle and the communication connection signal strength corresponding to each of the travel points; The signal strength distribution data set includes the multiple data groups.

[0010] In some embodiments of the present disclosure, the signal strength distribution data set stores the distance between the electronic device and the target vehicle and the corresponding communication connection signal strength.

[0011] In some embodiments of the present disclosure, determining whether the scene in which the target vehicle is located belongs to a calibration scene includes: Acquiring location information and parking perception information of the target vehicle; Based on the location information, screening whether there is an adapted calibration scene in a calibration scene database; If it exists, get the initial screening and calibration scene; determining at least one signal influencing factor based on the parking perception information; Based on the at least one signal influencing factor, determining whether there is an adapted target calibration scene from the primary screening calibration scenes; If so, it is determined that the scene where the target vehicle is located belongs to the calibration scene, and the scene where the target vehicle is located is the target calibration scene; The calibration scene database includes scene data of a plurality of calibration scenes stored in advance; the scene data includes location information and corresponding signal impact factors.

[0012] In some embodiments of the present disclosure, a method for determining digital key calibration data is provided, further comprising: In response to the scene where the target vehicle is located not belonging to the calibration scene, determining whether the scene where the target vehicle is located belongs to the recognition scene based on the position information, the parking perception information and the recognition scene database; wherein the recognition scene database includes pre-stored scene data of multiple recognition scenes and the accumulated recognition times corresponding to each recognition scene; In response to the scene being a recognition scene, increasing the cumulative number of recognition times by one and updating the number of recognition times into the recognition scene database; In response to the scene not belonging to the recognition scene, scene data of the scene is generated based on the position information and the parking perception information, and stored in the recognition scene database.

[0013] In some embodiments of the present disclosure, a method for determining digital key calibration data is provided, further comprising: In response to the accumulated recognition times corresponding to the first recognition scene exceeding a preset times threshold, the first recognition scene is determined as the calibration scene, and the scene data of the first recognition scene is stored in the calibration scene database.

[0014] In some embodiments of the present disclosure, a method for determining digital key calibration data is provided, further comprising: Sorting the multiple recognition scenes stored in the recognition scene database from most to least according to the corresponding cumulative recognition times; A preset number of recognition scenes ranked top are determined as the calibration scenes, and scene data corresponding to the preset number of recognition scenes are stored in the calibration scene database.

[0015] In some embodiments of the present disclosure, determining the calibration data of the digital key corresponding to the target calibration scene based on the signal strength distribution data set includes: Obtain historical signal strength distribution data set; Based on the historical signal strength distribution data set and the signal strength distribution data set, performing data distribution analysis to obtain the calibration data; The historical signal strength distribution data set includes a plurality of historical signal strength distribution data subsets, each of which is a signal strength distribution data set determined when the scene in the historical digital key calibration data determination process is the target calibration scene.

[0016] In some embodiments of the present disclosure, it further includes: The signal strength distribution data set is stored as a historical signal strength distribution data subset in the historical signal strength distribution data set.

[0017] In some embodiments of the present disclosure, it further includes: Acquire historical calibration data of the digital key; the historical calibration data is determined based on the historical signal strength distribution data set; monitoring the real-time communication connection signal strength between the electronic device and the target vehicle; estimating a real-time distance between the electronic device and the target vehicle based on the historical calibration data and the real-time communication connection signal strength; In response to the real-time distance being within a preset distance range, a preset execution action is executed.

[0018] In some embodiments of the present disclosure, the communication connection includes at least: Bluetooth connection, ultra-wideband connection, and near field communication.

[0019] In some embodiments of the present disclosure, in response to the communication connection being the ultra-wideband connection, the method further includes: Based on the signal strength distribution data set, data filling is performed to obtain a blind spot signal strength distribution data set corresponding to the parking perception blind spot; Wherein, determining the calibration data of the digital key corresponding to the target calibration scene based on the signal strength distribution data set includes: Based on the signal strength distribution data set and the blind spot signal strength distribution data set, calibration data of the digital key is determined.

[0020] According to a second aspect of an embodiment of the present disclosure, a device for determining digital key calibration data is provided, comprising: a target scene determination unit, configured to determine whether a scene in which the target vehicle is located belongs to a calibration scene in response to the electronic device carrying the digital key establishing a communication connection with the target vehicle; A data determination unit, configured to determine a signal strength distribution data set of a target calibration scene in response to the scene being a calibration scene; A data calibration unit is used to determine the calibration data of the digital key corresponding to the target calibration scene based on the signal strength distribution data set.

[0021] According to a third aspect of an embodiment of the present disclosure, a vehicle is provided, comprising: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to: implement the method for determining digital key calibration data described in the first aspect above.

[0022] According to a fourth aspect of an embodiment of the present disclosure, a non-temporary computer-readable storage medium is provided. When the instructions in the storage medium are executed by a processor of a terminal, the terminal is enabled to execute the method for determining digital key calibration data described in the first aspect above.

[0023] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects: The present disclosure establishes a communication connection with a target vehicle in response to an electronic device carrying a digital key, determines whether the scene in which the target vehicle is located belongs to a calibration scene, and if it belongs to a calibration scene, determines a signal strength distribution data set of the target calibration scene, and determines the calibration data of the digital key corresponding to the target calibration scene based on the signal strength distribution data set. By judging the scene in which the target vehicle is located, a signal strength distribution data set is collected and generated for the calibration scene to generate calibration data of the digital key suitable for the calibration scene, and calibration optimization of the calibration scene is achieved, thereby improving the calibration effect and further enhancing the user experience.

[0024] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0026] Figure 1 The following is a flow chart of a method for determining digital key calibration data according to some embodiments of the present disclosure. Figure 1 .

[0027] Figure 2 This is an implementation process flow of step S110 according to some embodiments of the present disclosure. Figure 1 .

[0028] Figure 3 This is an implementation process flow of step S110 according to some embodiments of the present disclosure. Figure 2 .

[0029] Figure 4 The present invention is a flowchart showing an implementation process of determining a signal strength distribution data set according to some embodiments of the present disclosure.

[0030] Figure 5 The following is a flow chart of a method for determining digital key calibration data according to some embodiments of the present disclosure. Figure 2 .

[0031] Figure 6 is a flowchart of an implementation process of step S130 according to some embodiments of the present disclosure.

[0032] Figure 7 The following is a flow chart of a method for determining digital key calibration data according to some embodiments of the present disclosure. Figure 3 .

[0033] Figure 8 It is a block diagram of a device for determining digital key calibration data according to some embodiments of the present disclosure.

[0034] Fig. 9 It is a block diagram of a vehicle according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0035] Some embodiments of the present disclosure will be described in detail here, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. Various changes, modifications and equivalents of the methods, devices and / or systems described herein will become apparent after understanding the present disclosure. For example, the order of operations described herein is merely an example and is not limited to those orders set forth herein, but can be changed as becomes apparent after understanding the present disclosure, except for operations that must be performed in a specific order. In addition, for clarity and brevity, descriptions of features known in the art may be omitted.

[0036] The embodiments described in some embodiments of the present disclosure below do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0037] The specific implementation of the embodiment of the present disclosure is described in detail below with reference to the accompanying drawings.

[0038] Figure 1 The following is a flow chart of a method for determining digital key calibration data according to some embodiments of the present disclosure. Figure 1 ,like Figure 1 As shown, the digital key calibration data determination method can be applied to a vehicle.

[0039] Figure 1 The digital key calibration data determination method shown includes the following steps.

[0040] In step S110, in response to the electronic device carrying the digital key establishing a communication connection with the target vehicle, it is determined whether the scene in which the target vehicle is located belongs to a calibration scene.

[0041] In some embodiments of the present disclosure, when a user carries an electronic device carrying a digital key close to a target vehicle, a sensor or communication module on the vehicle detects the presence of the device and establishes a communication connection using short-range, low-power wireless communication. It should be noted that, in order to ensure security, the digital key may be authenticated before the communication connection is established to ensure that only legitimate users can access the vehicle, which can be achieved through encryption algorithms and security protocols.

[0042] It should be noted that the above-mentioned communication connections at least include: Bluetooth connection BLE, ultra-wideband connection UWB, and near-field communication NFC.

[0043] It should be noted that if the scene occurs frequently, that is, the scene where the target vehicle is located belongs to a calibration scene, not only can a large number of data sources be obtained, and the digital key calibration data is determined based on this, the calibration data obtained is more accurate, but users will also often park in this scene, and the obtained calibration data is more likely to be applied, and the corresponding digital key service can be frequently provided, providing a better user experience.

[0044] In step S120 , in response to the current scene being a calibration scene, a signal strength distribution data set of a target calibration scene is determined.

[0045] It should be noted that the signal strength distribution data set stores the distance between the electronic device and the target vehicle and the corresponding communication connection signal strength, and may include multiple data groups, where one data group represents a distance value and a corresponding communication connection signal strength.

[0046] In step S130 , the calibration data of the digital key corresponding to the target calibration scenario is determined based on the signal strength distribution data set.

[0047] It should be noted that the calibration data corresponding to the target calibration scene determined by the digital key calibration data is determined based on the signal strength distribution data set obtained this time. It can be understood that in the specific implementation, multiple digital key calibration data determinations can be performed. For example, every time a user leaves home, he or she generally goes to a fixed parking space to unlock the vehicle. At this time, if it is determined that the scene corresponding to the fixed parking space belongs to the calibration scene, each time the user goes to the fixed parking space to unlock the vehicle with a mobile phone, a digital key calibration data determination will be performed. Each digital key calibration data determination process will execute steps S110 to S130 to obtain the calibration data corresponding to the current target calibration scene, and can be applied to the next digital key use process, providing users with more accurate and stable services. And the calibration data is generated based on user personalization and applied to user use. From calibration to application, it is closed-loop and personalized, which can improve the problem of low flexibility in providing services after the application of general calibration data, and provide personalized services to users in specific scenarios.

[0048] It can be seen from the above steps that the method for determining digital key calibration data provided by the embodiment of the present disclosure determines whether the scene in which the target vehicle is located belongs to the calibration scene by establishing a communication connection with the target vehicle in response to the electronic device carrying the digital key. If it belongs to the calibration scene, the signal strength distribution data set of the target calibration scene is determined, and based on the signal strength distribution data set, the calibration data of the digital key corresponding to the target calibration scene is determined. By judging the scene in which the target vehicle is located, the signal strength distribution data set is collected and generated for the calibration scene to generate the calibration data of the digital key suitable for the calibration scene, and the calibration optimization of the calibration scene is achieved, so as to improve the calibration effect and enhance the user experience.

[0049] In some exemplary embodiments of the present disclosure, Figure 2 FIG. 1 is a flowchart of the implementation process of step S110 provided in some exemplary embodiments of the present disclosure. Figure 1 , comprising the following steps.

[0050] In step S210, the location information and parking perception information of the target vehicle are obtained.

[0051] In some embodiments of the present disclosure, when a user carries an electronic device with a digital key and approaches a target vehicle, a sensor or communication module on the vehicle detects the presence of the device and establishes a communication connection using short-range, low-power wireless communication. When the communication connection is established, the location information and parking perception information of the target vehicle are obtained.

[0052] In some embodiments of the present disclosure, the location information of the target vehicle can be obtained through the global navigation satellite system GNSS to determine the location of the target vehicle. The target vehicle can be equipped with a variety of sensors, such as cameras, ultrasonic radars, laser radars, etc., for sensing the surrounding environment, and can detect obstacles, pedestrians, other vehicles and other parking environments around the vehicle, thereby sensing and obtaining parking perception information.

[0053] It should be noted that the parking perception information represents the parking environment of the target vehicle, from which one or more influencing factors affecting the communication connection signal can be determined. Combined with the vehicle position reflected by the position information, the scene in which the target vehicle is located can be determined.

[0054] In step S220, at least one signal influencing factor is determined based on the parking perception information.

[0055] In some embodiments of the present disclosure, the signal influencing factor types can be predefined, and the predefined signal influencing factor types can include multiple types, and at least one signal influencing factor corresponding to the scene in which the target vehicle is located can be determined in combination with the parking perception information. For example, the predefined signal influencing factor types may include: users, pillars, other vehicles, walls, charging piles, garage ceilings, and other factors that can affect the communication connection signal. Each type may also include different values ​​to further determine the specific signal influencing factor. For example, the values ​​of the pillar factor may include: pillars on the side, pillars at the rear, pillars in front, etc.; the values ​​of other vehicle factors may include: other vehicles parked on the left, other vehicles parked on the right, other vehicles parked in front, etc.; the values ​​of the garage ceiling factor may include: metal ceilings, open air, concrete ceilings, gypsum boards or other lightweight material ceilings, etc.

[0056] It can be understood that the above-mentioned signal influencing factor types and different values ​​of each type are only examples, which can be pre-set according to the influencing factors of the communication connection signal, can be determined based on big data analysis of historical test data, or can be determined with the help of analysis models such as machine learning models, and the present disclosure does not limit them here.

[0057] In step S230, based on the position information and at least one signal influencing factor, it is determined from the calibration scene database whether there is an adapted target calibration scene.

[0058] It should be noted that the calibration scene database includes pre-stored scene data of multiple calibration scenes, and the scene data includes position information and corresponding signal impact factors.

[0059] In step S240, if it exists, it is determined that the scene where the target vehicle is located belongs to the calibration scene, and the scene where the target vehicle is located is the target calibration scene.

[0060] In some exemplary embodiments of the present disclosure, Figure 3 FIG. 1 is a flowchart of the implementation process of step S110 provided in some exemplary embodiments of the present disclosure. Figure 2 , comprising the following steps.

[0061] In step S310, the location information and parking perception information of the target vehicle are obtained.

[0062] In step S320, based on the position information, a calibration scene database is screened to see whether there is an adapted calibration scene.

[0063] In step S330, if it exists, the initial screening and calibration scene is obtained.

[0064] In step S340, at least one signal influencing factor is determined based on the parking perception information.

[0065] In step S350, based on at least one signal influencing factor, it is determined whether there is an adapted target calibration scene from the initial screening calibration scenes.

[0066] In step S360, if it exists, it is determined that the scene where the target vehicle is located belongs to the calibration scene, and the scene where the target vehicle is located is the target calibration scene.

[0067] It should be noted that the calibration scene database includes pre-stored scene data of multiple calibration scenes, and the scene data includes position information and corresponding signal impact factors.

[0068] It can be seen from the above steps that by preliminarily screening the calibration scene database to see whether there are calibration scenes that are compatible with the position information, the scenes where the position information is not compatible can be quickly eliminated without the need for subsequent processing, thereby reducing the amount of data processing and the processing process, reducing the resource pressure and computing pressure of the vehicle system, and also improving the judgment efficiency of the scene.

[0069] Figure 4 is a flow chart showing a method of determining a signal strength distribution data set according to an exemplary embodiment of the present disclosure. Figure 4 As shown, the following steps are included.

[0070] In step S410, based on the parking perception information, multiple travel points of the user during the travel process are determined.

[0071] In some embodiments of the present disclosure, based on the parking perception information, the user's walking speed, walking duration and other travel information during the travel process can be determined. Based on the travel information, the change of the distance between the user and the target vehicle over time can be obtained, and multiple travel points can be determined. For example, linear travel points can be determined, that is, the difference in distance between two adjacent travel points and the target vehicle is a constant value. Sampling can also be performed at the same time interval to determine multiple travel points.

[0072] For example, the target vehicle can use the cameras installed around the vehicle to obtain video data. Based on the video data, the time point when the user is detected can be determined as t0, and the time point when the user opens the door can be determined as t1. Based on the video data, the average walking speed of the user can be calculated as s, and the distance between the user and the target vehicle can be calculated as s×(t1–t0). Set n linear coordinate points as travel points, n can be defined in advance through calibration, the distance between two connected travel points is s×(t1–t0) / n, and the time point corresponding to each travel point can be determined.

[0073] In step S420 , the distance between each travel point and the target vehicle is determined.

[0074] In step S430, the communication connection signal strength corresponding to each travel point is recorded.

[0075] It should be noted that, based on the time point corresponding to each travel point, the communication connection signal strength corresponding to each travel point can be determined in combination with the recording timestamp of the communication connection signal strength.

[0076] In step S440, a plurality of data groups are generated based on the distance between each travel point and the target vehicle and the communication connection signal strength corresponding to each travel point.

[0077] It should be noted that the signal strength distribution data set includes multiple data groups.

[0078] It should be noted that each data group may be in the form of [p, q], where p represents the distance between the travel point and the target vehicle, and q represents the corresponding communication connection signal strength, such as the Bluetooth signal strength RSSI.

[0079] In some embodiments of the present disclosure, Figure 5 The following is a flow chart of a method for determining digital key calibration data according to an exemplary embodiment of the present disclosure. Figure 2 .

[0080] In the disclosed embodiment, Figure 5 Steps S510 to S530 in the method for determining digital key calibration data are similar to Figure 1 Steps S110 to S130 in the digital key calibration data determination method shown correspond to each other and are not repeated here.

[0081] In the embodiment of the present disclosure, Figure 1 Based on the method for determining the digital key calibration data shown, Figure 5 The digital key calibration data determination method shown may also include the following steps.

[0082] In step S540, in response to the scene where the target vehicle is located not belonging to the calibration scene, it is determined whether the scene where the target vehicle is located belongs to the recognition scene based on the position information, the parking perception information and the recognition scene database.

[0083] In step S550, in response to the current scene being a recognition scene, the accumulated number of recognitions is increased by one and updated into the recognition scene database.

[0084] In step S560, in response to the scene not belonging to the recognition scene, scene data of the scene is generated based on the position information and the parking perception information, and stored in the recognition scene database.

[0085] In some embodiments of the present disclosure, the recognition scene database includes scene data of multiple pre-stored recognition scenes and the cumulative number of recognitions corresponding to each recognition scene. If the scene in which the target vehicle is located does not belong to the calibration scene, it is characterized that the frequency of occurrence of the scene in the previous use of the digital key is not high, and it can be matched with the recognition scene database to determine whether the scene has ever appeared. The recognition scene database stores the scenes identified within the time period determined by the current digital key calibration data and the number of occurrences of each scene. In order to reduce unnecessary data storage and reduce system pressure, the recognition scene database only stores the recognition scene identifier, scene data and the cumulative number of recognitions.

[0086] In some exemplary embodiments of the present disclosure, the construction of the calibration scene database may be based on the recognition scene database. It is understandable that in the initial stage of the user using the target vehicle, the accumulated data forms the recognition scene database. After a period of use, when the recognition scene database accumulates enough data, a calibration scene database may be generated to characterize the scenes with a higher frequency of occurrence, and used as a calibration scene for subsequent personalized calibration, so as to provide users with more intelligent services.

[0087] In some exemplary embodiments of the present disclosure, the calibration scene can be determined by judging whether the cumulative number of recognitions exceeds a set threshold. Specifically, in these embodiments, the method for determining digital key calibration data also includes: in response to the cumulative number of recognitions corresponding to the first recognition scene exceeding a preset number threshold, determining the first recognition scene as a calibration scene, and storing the scene data of the first recognition scene in a calibration scene database. It should be noted that the preset number threshold can be determined according to user habits, experience values, user personalized settings, etc., and the specific value is not limited here, for example, it can be 50, 100, 120, etc.

[0088] In some exemplary embodiments of the present disclosure, several recognition scenes with higher cumulative recognition times can be determined as calibration scenes. Specifically, in these embodiments, the provided method for determining digital key calibration data also includes: sorting the multiple recognition scenes stored in the recognition scene database from most to least according to the corresponding cumulative recognition times; determining a preset number of recognition scenes with higher rankings as calibration scenes, and storing the scene data corresponding to the preset number of recognition scenes in the calibration scene database. It should be noted that the preset number can be determined according to user habits, experience values, user personalized settings, etc., and the specific value is not limited here, for example, it can be 3, 5, 8, etc.

[0089] In some embodiments of the present disclosure, the specific implementation process of step S130 is as follows: Figure 6 As shown, the following steps may be included.

[0090] In step S610, a historical signal strength distribution data set is obtained.

[0091] In step S620, data distribution analysis is performed based on the historical signal strength distribution data set and the signal strength distribution data set to obtain calibration data.

[0092] It should be noted that the historical signal strength distribution data set includes multiple historical signal strength distribution data subsets, each of which is a signal strength distribution data set determined when the scene in the historical digital key calibration data determination process is the target calibration scene. It is understandable that there will be multiple determinations of digital key calibration data for the same calibration scene, and for the current digital key calibration data determination, the data included in the historical signal strength distribution data set comes from each signal strength distribution data set determined in the previous multiple digital key calibration data determination processes.

[0093] In some embodiments of the present disclosure, data distribution analysis is performed based on a historical signal strength distribution data set and a data group contained in the signal strength distribution data set. For example, a Gaussian distribution, a normal distribution, a linear distribution, etc. can be used to obtain the calibrated communication connection signal strength corresponding to each travel point to obtain the calibration data of the digital key.

[0094] It is understandable that in order to prevent erroneous data from affecting subsequent results, the signal strength distribution data set may be filtered in advance to filter out erroneous data and abnormal data to ensure the accuracy of the calibration data.

[0095] Accordingly, the digital key calibration data determination method provided by the embodiment of the present disclosure also includes: storing the signal strength distribution data set as a historical signal strength distribution data subset to the historical signal strength distribution data set, so as to serve as a big data source for data distribution analysis in the next digital key calibration data determination process when the scene is the same target calibration scene.

[0096] In some embodiments of the present disclosure, it can be determined whether to perform data distribution analysis by determining the data volume of the historical signal strength distribution data set currently obtained. If the data volume exceeds the preset data volume, the above steps S610 to S620 can be executed to obtain calibration data. If the data volume does not exceed the preset data volume, it indicates that the data volume of the historical signal strength distribution data set is not large, that is, for the same target calibration scene in the scene, the number of historical digital key calibration data determinations is not large, and the amount of data obtained is limited. The effect of data distribution analysis may not be good enough, and the calibration data obtained at this time may not be stable enough. At this time, data distribution analysis is not performed, and calibration data is not determined. The historical signal strength distribution data set can be updated to accumulate data for subsequent calibration data determination until the data volume exceeds the preset data volume. Thereby, on the basis of ensuring the accuracy and stability of the calibration data, the amount of data processing and resource consumption can be reduced as much as possible, and the pressure on the processor in the vehicle is reduced.

[0097] In the disclosed embodiment, Figure 7 The following is a flow chart of a method for determining digital key calibration data according to some embodiments of the present disclosure. Figure 3 . Figure 7 Steps S710 to S730 of the method for determining digital key calibration data are similar to Figure 1 Steps S110 to S130 in the digital key calibration data determination method shown correspond to each other and are not repeated here.

[0098] In the embodiment of the present disclosure, Figure 1 Based on the method for determining the digital key calibration data shown, Figure 7 The digital key calibration data determination method shown may also include the following steps.

[0099] In step S740 , historical calibration data of the digital key is obtained.

[0100] It should be noted that the historical calibration data is determined based on the historical signal strength distribution data set. In other words, the historical calibration data is the calibration data obtained after the digital key calibration data is determined before the scene is the same target calibration scene.

[0101] In some embodiments of the present disclosure, the historical calibration data may be the calibration data obtained after the last digital key calibration data determination, so as to use the calibration data with the strongest timeliness for calibration. The number of times the digital key calibration data determination is performed may also be recorded, and the historical calibration data may also be the calibration data obtained by performing the digital key calibration data determination for a preset fixed number of times. For example, if the number of times the digital key calibration data determination is performed for the current time is 133, the calibration data obtained for the 100th time may be used as the historical calibration data of the digital key, and it is stipulated that the historical calibration data shall be used for the 101st to 200th times, the calibration data obtained for the 200th time shall be used for the 201st to 300th times, and so on. As a result, the calibration data used for the digital key calibration within a stage is the same, which can reduce the amount of data interaction, reduce the cumbersome process of the calibration process, and at the same time provide users with a relatively stable digital key service for a period of time.

[0102] In step S750 , the real-time communication connection signal strength between the electronic device and the target vehicle is monitored.

[0103] In some embodiments of the present disclosure, the API of the Bluetooth adapter can be directly accessed to read the signal strength, which is usually presented in the form of RSSI-received signal strength indication. A program can be written to periodically read the signal strength data from the UWB module.

[0104] In step S760, the real-time distance between the electronic device and the target vehicle is estimated based on the historical calibration data and the real-time communication connection signal strength.

[0105] It should be noted that the historical calibration data represents the correlation between the distance value and the calibrated communication connection signal strength. Based on the real-time communication connection signal strength, the real-time distance between the electronic device and the target vehicle can be estimated to avoid the impact of the environment on the communication connection signal strength, thereby determining a more accurate real-time distance.

[0106] In step S770, in response to the real-time distance being within the preset distance range, a preset execution action is performed.

[0107] In some embodiments of the present disclosure, the preset execution action to be executed can be determined based on the correspondence between the preset real-time distance and the execution action. The preset execution action may include preset execution actions such as unlocking and locking, and the preset distance ranges corresponding to unlocking and locking may be different. It is understandable that the preset distance range can be adjusted according to user needs, and the specific value is not limited. For example, it can be 2 meters to 2.5 meters. When the real-time distance is within the range of 2 meters to 2.5 meters, the vehicle executes the unlocking action, which may include functions such as automatic unlocking of the vehicle, activation of external lighting, and gradual lighting of internal lighting.

[0108] It should be noted that the area perceived by the parking perception information is limited. For example, the area that the camera can capture is limited, and there are blind spots that cannot be captured. For the blind spots, it is impossible to obtain the data group consisting of the distance between the electronic device and the target vehicle and the corresponding communication connection signal strength. In order to ensure that the coverage of the calibration data is strong enough, it is also necessary to ensure that the final calibration is accurate. In some embodiments of the present disclosure, in response to the communication connection being an ultra-wideband connection, the provided method for determining the calibration data of the digital key also includes: based on the signal strength distribution data set, data filling is performed to obtain a blind spot signal strength distribution data set corresponding to the parking perception blind spot. Accordingly, based on the signal strength distribution data set, the calibration data of the digital key corresponding to the target calibration scene is determined, including: based on the signal strength distribution data set and the blind spot signal strength distribution data set, the calibration data of the digital key is determined.

[0109] Specifically, the calibration area around the target vehicle can be divided, for example, into multiple circles with the target vehicle as the center, each travel point is located on a circle, and the radial direction of the circle is used as the direction. Combined with the calibrated communication signal connection strength of multiple travel points, the average is determined to determine how much the communication signal connection strength decreases for each unit increase in the distance value, so as to fill the blind spot signal strength distribution. For example, the calibration area is a circle with a radius of 10m around the vehicle body. Every 0.5m in the radial direction is a small circle that is a travel point. Each small circle corresponds to a calibrated communication signal connection strength. The camera can only see the scene within 7m. For scenes outside 7m, it can be inferred based on the data collected by the camera within 7m. For example, within 7m, for every 0.5m increase, the calibrated communication signal connection strength increases by 5db, and the scene outside 7m is also inferred and filled according to this rule.

[0110] In some embodiments of the present disclosure, the signal strength distribution to fill the blind spot can be inferred based on the known signal strength distribution through K-Nearest Neighbors (KNN), Radial Basis Function (RBF) interpolation, Kriging, machine learning methods, etc., which are not limited to the present disclosure.

[0111] Through the method for determining the digital key calibration data provided by the above embodiment, it can be seen that the present disclosure can generate personalized calibration data according to the user's usage scenario, and thereby provide a unique digital key service for the user, with good calibration effect for specific scenarios and improved user experience. For example, when using a Bluetooth key, in the related art, by limiting an RSSI value, such as -60db, as long as the mobile phone is within this signal strength range, the vehicle will welcome guests, such as the rearview mirror unfolds, the lights flash, etc., but affected by the actual environment, when the RSSI reaches this value, the user may sometimes be 5m away from the car, and sometimes the user may be 1m away from the car, which is not a good experience for the user. In a specific scenario, such as the presence of Bluetooth signal reflection, refraction, etc., the present disclosure dynamically adjusts the threshold of the RSSI according to the calibration value determined by the above embodiment, such as when there are many obstacles around and severe obstruction, it may be relaxed, such as to -70db, and when the surrounding is very open, it may be tightened, such as to -55db, etc., but the service experience provided to the user is that the user walks to about 5m away from the vehicle, the rearview mirror opens, and the lighting effect is presented.

[0112] The following are embodiments of the device disclosed herein, which can be used to execute the method embodiments disclosed herein. For details not disclosed in the device embodiments disclosed herein, please refer to the method embodiments disclosed herein.

[0113] Figure 8 FIG. 8 is a block diagram of a digital key calibration data determination device 800 according to some embodiments of the present disclosure. Figure 8 The device 800 includes: a target scene determination unit 801, a data determination unit 802 and a data calibration unit 803.

[0114] A target scene determination unit 801 is used to determine whether the scene in which the target vehicle is located belongs to a calibration scene in response to the electronic device carrying the digital key establishing a communication connection with the target vehicle; A data determination unit 802 is configured to determine a signal strength distribution data set of a target calibration scene in response to the scene being a calibration scene; The data calibration unit 803 is used to determine the calibration data of the digital key corresponding to the target calibration scene based on the signal strength distribution data set.

[0115] In some exemplary embodiments of the present disclosure, the target scene determination unit 801 is configured to: Obtaining the location information and parking perception information of the target vehicle; determining at least one signal influencing factor based on the parking perception information; Based on the position information and at least one signal influencing factor, determining whether there is an adapted target calibration scene from a calibration scene database; The calibration scene database includes scene data of a plurality of calibration scenes stored in advance; the scene data includes location information and corresponding signal impact factors; If it exists, it is determined that the scene where the target vehicle is located belongs to the calibration scene, and the scene where the target vehicle is located is the target calibration scene.

[0116] In some exemplary embodiments of the present disclosure, the target scene determination unit 801 is configured to: Obtaining the location information and parking perception information of the target vehicle; Based on the location information, filter the calibration scene database to see if there is an adapted calibration scene; If it exists, get the initial screening and calibration scene; determining at least one signal influencing factor based on the parking perception information; Based on at least one signal influencing factor, determining whether there is an adapted target calibration scene from the preliminary screening calibration scenes; If it exists, it is determined that the scene where the target vehicle is located belongs to the calibration scene, and the scene where the target vehicle is located is the target calibration scene; The calibration scene database includes scene data of a plurality of calibration scenes stored in advance; the scene data includes position information and corresponding signal influencing factors.

[0117] It should be noted that at least one signal influencing factor includes: a user holding the electronic device. Accordingly, the data determination unit 802 is configured to: Based on the parking perception information, determine multiple travel points of the user during the travel process; Determine the distance between each travel point and the target vehicle; Record the communication connection signal strength corresponding to each travel point; A plurality of data groups are generated based on the distance between each travel point and the target vehicle and the communication connection signal strength corresponding to each travel point.

[0118] The signal strength distribution data set includes multiple data groups.

[0119] In some exemplary embodiments of the present disclosure, the signal strength distribution data set stores the distance between the electronic device and the target vehicle and the corresponding communication connection signal strength.

[0120] In some exemplary embodiments of the present disclosure, the present invention further includes a scene recognition unit, configured to: In response to the scene where the target vehicle is located not belonging to the calibration scene, determining whether the scene where the target vehicle is located belongs to the recognition scene based on the position information, the parking perception information and the recognition scene database; wherein the recognition scene database includes scene data of a plurality of recognition scenes stored in advance and the accumulated recognition times corresponding to each recognition scene; In response to the scene being a recognition scene, the accumulated recognition times are increased by one and updated into the recognition scene database; In response to the scene not belonging to the recognized scene, scene data of the scene is generated based on the position information and the parking perception information, and stored in the recognized scene database.

[0121] In some exemplary embodiments of the present disclosure, the method further includes: a first calibration scene data maintenance unit, configured to: In response to the cumulative number of recognitions corresponding to the first recognition scene exceeding a preset number threshold, the first recognition scene is determined as a calibration scene, and the scene data of the first recognition scene is stored in a calibration scene database.

[0122] In some exemplary embodiments of the present disclosure, the method further includes: a second calibration scene data maintenance unit, configured to: Sorting the multiple recognition scenes stored in the recognition scene database from most to least according to the corresponding cumulative recognition times; A preset number of recognition scenes ranked top are determined as calibration scenes, and scene data corresponding to the preset number of recognition scenes are stored in a calibration scene database.

[0123] In some exemplary embodiments of the present disclosure, the data calibration unit 803 is configured to: Obtain historical signal strength distribution data set; Based on the historical signal strength distribution data set and the signal strength distribution data set, data distribution analysis is performed to obtain calibration data; The historical signal strength distribution data set includes a plurality of historical signal strength distribution data subsets, each of which is a signal strength distribution data set determined when the scene in the historical digital key calibration data determination process is a target calibration scene.

[0124] In some exemplary embodiments of the present disclosure, the data calibration unit 803 is further configured to: The signal strength distribution data set is taken as a subset of the historical signal strength distribution data and stored in the historical signal strength distribution data set.

[0125] In some exemplary embodiments of the present disclosure, the present invention further includes: a digital key calibration unit, configured to: Obtain historical calibration data of the digital key; the historical calibration data is determined based on a historical signal strength distribution data set; Monitor the real-time communication connection signal strength between the electronic device and the target vehicle; Estimate the real-time distance between the electronic device and the target vehicle based on historical calibration data and real-time communication connection signal strength; In response to the real-time distance being within a preset distance range, a preset execution action is performed.

[0126] It should be noted that the communication connection includes at least: Bluetooth connection, ultra-wideband connection, and near-field communication.

[0127] In response to the communication connection being an ultra-wideband connection, in some exemplary embodiments of the present disclosure, the method further includes: a blind spot filling unit, configured to: Based on the signal strength distribution data set, data filling is performed to obtain a blind spot signal strength distribution data set corresponding to the parking perception blind spot; Accordingly, the data calibration unit 803 is configured as follows: Based on the signal strength distribution data set and the blind spot signal strength distribution data set, the calibration data of the digital key is determined.

[0128] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0129] Fig. 9 is a block diagram of a vehicle 900 according to an exemplary embodiment. For example, the vehicle 900 may be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles. The vehicle 900 may be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle.

[0130] Reference Fig. 9 , the vehicle 900 may include various subsystems, for example, an infotainment system 910, a perception system 920, a decision control system 930, a drive system 940, and a computing platform 950. The vehicle 900 may also include more or fewer subsystems, and each subsystem may include multiple components. In addition, each subsystem and each component of the vehicle 900 may be interconnected by wire or wireless means.

[0131] In some embodiments, the infotainment system 910 may include a communication system, an entertainment system, and a navigation system, etc.

[0132] The perception system 920 may include several sensors for sensing information about the environment around the vehicle 900. For example, the perception system 920 may include a global positioning system (the global positioning system may be a GPS system, or a Beidou system or other positioning systems), an inertial measurement unit (IMU), a laser radar, a millimeter wave radar, an ultrasonic radar, and a camera.

[0133] The decision control system 930 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0134] The drive system 940 may include components that provide powered motion for the vehicle 900. In one embodiment, the drive system 940 may include an engine, an energy source, a transmission system, and wheels. The engine may be a combination of one or more of an internal combustion engine, an electric motor, and an air compression engine. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0135] Some or all functions of the vehicle 900 are controlled by a computing platform 950. The computing platform 950 may include at least one processor 951 and a memory 952, and the processor 951 may execute instructions 953 stored in the memory 952.

[0136] The processor 951 may be any conventional processor, such as a commercially available CPU. The processor may also include a data processor (Graphic Process Unit, GPU), a Field Programmable Gate Array (Field Programmable Gate Array, FPGA), a System on Chip (System on Chip, SOC), an Application Specific Integrated Circuit (Application Specific Integrated Circuit, ASIC) or a combination thereof.

[0137] The memory 952 may be implemented by any type of volatile or nonvolatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0138] In addition to instructions 953 , memory 952 may also store data, such as road maps, route information, vehicle location, direction, speed, etc. The data stored in memory 952 may be used by computing platform 950 .

[0139] In the embodiment of the present disclosure, the processor 951 may execute instruction 953 to complete all or part of the steps of the above-mentioned method for determining digital key calibration data.

[0140] In some embodiments of the present disclosure, a non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a processor of a terminal, enables the terminal to execute the above-mentioned digital key calibration data determination method.

[0141] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0142] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for determining digital key calibration data, characterized in that: include: In response to the electronic device carrying the digital key establishing a communication connection with the target vehicle, determining whether the scene in which the target vehicle is located belongs to a calibration scene; In response to the scene being a calibration scene, determining a signal strength distribution data set of a target calibration scene; Based on the signal strength distribution data set, calibration data of the digital key corresponding to the target calibration scene is determined.

2. The method for determining digital key calibration data according to claim 1, characterized in that: Determining whether the scene in which the target vehicle is located belongs to the calibration scene includes: Acquiring location information and parking perception information of the target vehicle; determining at least one signal influencing factor based on the parking perception information; Based on the position information and the at least one signal influencing factor, determining whether there is an adapted target calibration scene from a calibration scene database; Wherein, the calibration scene database includes scene data of a plurality of calibration scenes stored in advance; the scene data includes position information and corresponding signal impact factors; If so, it is determined that the scene where the target vehicle is located belongs to the calibration scene, and the scene where the target vehicle is located is the target calibration scene.

3. The method for determining digital key calibration data according to claim 2, characterized in that: The at least one signal influencing factor includes: a user holding the electronic device.

4. The method for determining digital key calibration data according to claim 3, characterized in that: Determine the signal strength distribution data set, including: Determining a plurality of travel points of the user during travel based on the parking perception information; determining the distance between each of the travel points and the target vehicle; Recording the communication connection signal strength corresponding to each of the travel points; generating a plurality of data groups based on the distance between each of the travel points and the target vehicle and the communication connection signal strength corresponding to each of the travel points; The signal strength distribution data set includes the multiple data groups.

5. The method for determining digital key calibration data according to claim 1, characterized in that: The signal strength distribution data set stores the distance between the electronic device and the target vehicle and the corresponding communication connection signal strength.

6. The method for determining digital key calibration data according to claim 1, characterized in that: Determining whether the scene in which the target vehicle is located belongs to the calibration scene includes: Acquiring location information and parking perception information of the target vehicle; Based on the location information, screening whether there is an adapted calibration scene in a calibration scene database; If it exists, get the initial screening and calibration scene; determining at least one signal influencing factor based on the parking perception information; Based on the at least one signal influencing factor, determining whether there is an adapted target calibration scene from the primary screening calibration scenes; If so, it is determined that the scene where the target vehicle is located belongs to the calibration scene, and the scene where the target vehicle is located is the target calibration scene; The calibration scene database includes scene data of a plurality of calibration scenes stored in advance; the scene data includes location information and corresponding signal impact factors.

7. The method for determining digital key calibration data according to claim 2 or 6, characterized in that: Also includes: In response to the scene where the target vehicle is located not belonging to the calibration scene, determining whether the scene where the target vehicle is located belongs to the recognition scene based on the position information, the parking perception information and the recognition scene database; wherein the recognition scene database includes pre-stored scene data of multiple recognition scenes and the accumulated recognition times corresponding to each recognition scene; In response to the scene being a recognition scene, increasing the cumulative number of recognition times by one and updating the number of recognition times into the recognition scene database; In response to the scene not belonging to the recognition scene, scene data of the scene is generated based on the position information and the parking perception information, and stored in the recognition scene database.

8. The method for determining digital key calibration data according to claim 7, characterized in that: Also includes: In response to the accumulated recognition times corresponding to the first recognition scene exceeding a preset times threshold, the first recognition scene is determined as the calibration scene, and the scene data of the first recognition scene is stored in the calibration scene database.

9. The method for determining digital key calibration data according to claim 7, characterized in that: Also includes: Sorting the multiple recognition scenes stored in the recognition scene database from most to least according to the corresponding cumulative recognition times; A preset number of recognition scenes ranked top are determined as the calibration scenes, and scene data corresponding to the preset number of recognition scenes are stored in the calibration scene database.

10. The method for determining digital key calibration data according to claim 1, characterized in that: Determining the calibration data of the digital key corresponding to the target calibration scene based on the signal strength distribution data set includes: Obtain historical signal strength distribution data set; Based on the historical signal strength distribution data set and the signal strength distribution data set, performing data distribution analysis to obtain the calibration data; The historical signal strength distribution data set includes a plurality of historical signal strength distribution data subsets, each of which is a signal strength distribution data set determined when the scene in the historical digital key calibration data determination process is the target calibration scene.

11. The method for determining digital key calibration data according to claim 10, characterized in that: Also includes: The signal strength distribution data set is taken as a historical signal strength distribution data subset and stored in the historical signal strength distribution data set.

12. The method for determining digital key calibration data according to claim 10, characterized in that: Also includes: Acquiring historical calibration data of the digital key; The historical calibration data is determined based on the historical signal strength distribution data set; monitoring the real-time communication connection signal strength between the electronic device and the target vehicle; estimating a real-time distance between the electronic device and the target vehicle based on the historical calibration data and the real-time communication connection signal strength; In response to the real-time distance being within a preset distance range, a preset execution action is executed.

13. The method for determining digital key calibration data according to claim 1, characterized in that: The communication connection includes at least: Bluetooth connection, ultra-wideband connection, and near field communication.

14. The method for determining digital key calibration data according to claim 13, characterized in that: In response to the communication connection being the ultra-wideband connection, the method further includes: Based on the signal strength distribution data set, data filling is performed to obtain a blind spot signal strength distribution data set corresponding to the parking perception blind spot; Wherein, determining the calibration data of the digital key corresponding to the target calibration scene based on the signal strength distribution data set includes: Based on the signal strength distribution data set and the blind spot signal strength distribution data set, calibration data of the digital key is determined.

15. A digital key calibration data determination device, characterized in that: include: a target scene determination unit, configured to determine whether a scene in which the target vehicle is located belongs to a calibration scene in response to the electronic device carrying the digital key establishing a communication connection with the target vehicle; A data determination unit, configured to determine a signal strength distribution data set of a target calibration scene in response to the scene being a calibration scene; A data calibration unit is used to determine the calibration data of the digital key corresponding to the target calibration scene based on the signal strength distribution data set.

16. A vehicle, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to: Implement the method for determining digital key calibration data as described in any one of claims 1 to 14.

17. A non-temporary computer-readable storage medium, when the instructions in the storage medium are executed by a processor of a terminal, enables the terminal to execute a method for determining digital key calibration data as described in any one of claims 1 to 14.

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