Vehicle control method and device, vehicle and storage medium

Abstract

The embodiment of the invention relates to the technical field of vehicles, and discloses a vehicle control method and device, a vehicle and a storage medium, and the method comprises the steps: obtaining the multi-source biological information of a user in the vehicle and the information of the environment where the vehicle is located; performing authentication verification on the user according to the multi-source biological information and the environment information; and after the authentication verification of the user is passed, cabin control adjustment is performed on the vehicle according to the multi-source biological information and / or the environment information. By applying the technical scheme of the invention, the user authentication can be more accurately realized, so that the adjustment of the intelligent cabin is more suitable for the use of the current user.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of vehicle technology, and more particularly to a vehicle control method, device, vehicle, and storage medium. Background Art

[0002] With the rapid development of smart cockpits in vehicle technology, users' demand for vehicle safety, comfort, and personalized experience is increasing. Currently, vehicle authentication methods mainly rely on fingerprint or facial recognition. After passing, the default settings of the smart cockpit are controlled to improve the user experience.

[0003] Under the current implementation, the above authentication method has insufficient authentication accuracy, resulting in the adjustment of the smart cockpit being unable to suit the current user. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a vehicle control method, device, vehicle and storage medium, which are used to solve the technical problem in the prior art that user authentication accuracy is low, resulting in the adjustment of the smart cockpit being unable to suit the current user.

[0005] According to one aspect of an embodiment of the present invention, a vehicle control method is provided, the method comprising:

[0006] Acquiring multi-source biometric information of a user in a vehicle and environmental information of the vehicle;

[0007] authenticating the user based on the multi-source biometric information and the environmental information;

[0008] After the user's authentication is passed, the vehicle's cabin control is adjusted according to the multi-source biometric information and / or the environmental information.

[0009] According to another aspect of an embodiment of the present invention, there is provided a vehicle control device, comprising:

[0010] An acquisition module, configured to acquire multi-source biometric information of a user in a vehicle and environmental information of the vehicle;

[0011] a verification module, configured to authenticate the user based on the multi-source biometric information and the environmental information;

[0012] A processing module is used to adjust the cabin control of the vehicle according to the multi-source biometric information and / or the environmental information after the user's authentication is passed.

[0013] According to another aspect of an embodiment of the present invention, a vehicle is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus;

[0014] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform the operation of the vehicle control method as described above.

[0015] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores at least one executable instruction. When the executable instruction is executed on a vehicle control device / vehicle, the vehicle control device / vehicle performs the operation of the vehicle control method as described above.

[0016] According to another aspect of an embodiment of the present invention, a computer program product is provided, comprising a computer program, which, when executed by a processor, causes a vehicle control device / vehicle to perform the operations of the above method.

[0017] The embodiments of the present invention obtain multi-source biometric information of users in a vehicle and information about the vehicle's environment; authenticate the user based on the multi-source biometric information and environmental information; and after the user's authentication is successful, adjust the vehicle's cabin control based on the multi-source biometric information and / or environmental information. This technical solution, firstly, combines multi-source biometric information and environmental data for comprehensive authentication, which can compensate for the shortcomings of single biometric feature recognition and improve the robustness and accuracy of verification; secondly, after authentication is successful, the cabin parameters are dynamically adjusted through real-time analysis of multi-source biometric information and / or environmental information, achieving collaborative optimization of the human-vehicle-environment relationship, enhancing the emotional and intelligent level of human-machine interaction, and ultimately improving driving safety and user satisfaction.

[0018] The above description is only an overview of the technical solutions of the embodiments of the present invention. In order to more clearly understand the technical means of the embodiments of the present invention, they can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiments of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present invention. In addition, the same reference symbols are used to represent the same components throughout the drawings. In the drawings:

[0020] Figure 1 A flow chart showing a first embodiment of a vehicle control method provided by the present invention;

[0021] Figure 2 A flow chart showing a second embodiment of the vehicle control method provided by the present invention;

[0022] Figure 3 A flow chart showing a third embodiment of the vehicle control method provided by the present invention;

[0023] Figure 4 A flowchart of a fourth embodiment of the vehicle control method provided by the present invention is shown;

[0024] Figure 5 A schematic diagram of the authentication and verification process in the vehicle control method provided by the present invention is shown;

[0025] Figure 6 A schematic diagram of the biometric-environment-cabin adjustment process in the vehicle control method provided by the present invention is shown;

[0026] Figure 7 A schematic structural diagram of an embodiment of a vehicle control device provided by the present invention is shown;

[0027] Figure 8 A schematic structural diagram of an embodiment of a vehicle provided by the present invention is shown. DETAILED DESCRIPTION

[0028] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0029] With the rapid development of smart cockpit technology, users' demand for vehicle safety, comfort and personalized experience is increasing.

[0030] Currently, vehicle authentication relies primarily on a single biometric feature (such as fingerprint or facial recognition), while cabin environment adjustments are often based on simple manual settings or fixed modes. This leads to the following technical issues:

[0031] 1. Single-modal recognition flaws: Existing systems often rely on a single biometric feature (such as fingerprint or facial recognition), which cannot effectively handle complex scenarios (e.g., facial recognition failure due to a driver wearing sunglasses, or fingerprint failure due to wet fingers).

[0032] 2. Insufficient intelligent linkage between the environment and the cockpit: The linkage between external environmental changes and the cockpit is not intelligent enough. For example, the cockpit cannot adapt to weather changes in a timely manner.

[0033] 3. Insufficient intelligence in the linkage between driver emotions and the cockpit: The smart cockpit fails to form a synergistic effect with the user's emotional characteristics. For example, fragrances and music cannot be adjusted in real time according to personal mood changes.

[0034] Based on the above technical problems, the technical concept of the present invention is as follows: in the face of the high failure rate of current single-modal biometrics in complex in-vehicle scenarios, we can get inspiration from multi-factor authentication and introduce multi-source biometric collaborative verification into vehicle authentication. However, the current failure is mainly caused by fingerprint failure, excessive brightness of facial acquisition, etc. Then, environmental information can be introduced to adjust the impact of multi-source biometric information during authentication, so as to achieve more accurate authentication. After the authentication is passed, multi-source biometric information and environmental information can also be used to adjust the relevant hardware in the cabin to better suit the current user.

[0035] The technical solution of the present invention is described in detail with reference to the following embodiments. The subject of the present invention is a vehicle.

[0036] It should be noted that the following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0037] Figure 1 FIG1 shows a flow chart of a first embodiment of a vehicle control method provided by the present invention, which is executed by a vehicle. Figure 1 As shown, the method includes the following steps:

[0038] Step 11: Acquire multi-source biometric information of the user in the vehicle and information about the vehicle's environment;

[0039] In this step, the user's biometric information is obtained through different biometric identification-related sensors installed in the vehicle, which is called multi-source biometric information; and the vehicle's environmental information is obtained through different environment-related sensors in the vehicle.

[0040] Optionally, the multi-source biometric information may include at least two of the following biometric information: facial information, fingerprint information, and voiceprint information.

[0041] In this implementation, fingerprint information can be collected based on a fingerprint sensor set on the steering wheel of the vehicle, for example, the fingerprint sensor is set inside the 3 / 9 o'clock position of the steering wheel; facial information can be collected based on a camera set on the vehicle, for example, the camera is set inside the A-pillar or the instrument cluster of the vehicle; voiceprint information can be collected based on a voice sensor set on the vehicle, for example, the voice sensor is set at the base of the interior rearview mirror or inside the A-pillar.

[0042] Optionally, the environmental information may include at least one of the following: lighting information, noise information, and temperature and humidity information.

[0043] In this implementation, the lighting information can be obtained by a lighting sensor installed on the vehicle; the noise information can be obtained by a voice sensor installed on the vehicle; and the temperature and humidity information can be obtained by a temperature sensor (behind the front bumper or the front wall panel of the cab) and a humidity sensor installed on the vehicle.

[0044] In addition, the environmental information may further include at least one of the following: rainfall information (obtained by a rain sensor provided on the vehicle, which may be provided on the top of the front windshield and integrated with the light sensor).

[0045] Step 12: Authenticate and verify the user based on multi-source biometric information and environmental information;

[0046] In this step, environmental information will have a certain impact on the collection accuracy of sensors and other equipment corresponding to the multi-source biometric information. The multi-source biometric information is adjusted according to the environmental information. After that, more accurate authentication data suitable for authentication verification can be determined (i.e., the target fusion biometric features mentioned below).

[0047] Furthermore, the authentication data is authenticated to determine whether the user is an authorized user to perform the following cockpit control adjustment operations.

[0048] Step 13: After the user's authentication is passed, the vehicle cabin control is adjusted based on the multi-source biometric information and / or environmental information.

[0049] In this step, after the above-mentioned authentication verification is passed, the hardware equipment or software in the vehicle's cabin can be controlled and adjusted accordingly based on the multi-source biometric information and environmental information respectively, so that the use of the vehicle cabin meets the needs of the user and the requirements of the environment.

[0050] In addition, the driver's seat parameter settings can be identified and generated through the user's multi-source biometric information.

[0051] The vehicle control method provided by an embodiment of the present invention obtains multi-source biometric information of the user in the vehicle and information about the vehicle's environment; authenticates the user based on the multi-source biometric information and environmental information; and after the user's authentication and verification is successful, adjusts the vehicle's cabin control based on the multi-source biometric information and / or environmental information. This technical solution, firstly, combines multi-source biometric information and environmental data for comprehensive authentication, which can compensate for the shortcomings of single biometric feature recognition and improve the robustness and accuracy of verification; secondly, after authentication is successful, the cabin parameters are dynamically adjusted through real-time analysis of multi-source biometric information and environmental information, achieving coordinated optimization of the human-vehicle-environment relationship, enhancing the emotional and intelligent level of human-machine interaction, and ultimately improving driving safety and user satisfaction.

[0052] Based on the above embodiments, Figure 2 FIG2 shows a flow chart of a second embodiment of a vehicle control method provided by the present invention, which is executed by a vehicle. Figure 2 As shown, the above step 12 may include the following steps:

[0053] Step 21: Determine the target fusion biological feature based on the multi-source biological information and environmental information;

[0054] In this step, based on the multi-source biometric information, the multi-source biometric information can be converted into the same dimension to facilitate fusion processing, that is, the biometric features corresponding to at least two items of biometric information in the multi-source biometric information can be extracted, and then the weights of different biometric features are adjusted based on the environmental information to obtain a stable and reliable biometric feature combination in the current environment, which is recorded as the target fusion biometric feature.

[0055] Optionally, a possible implementation of step 21 may be:

[0056] Step 1: Determine the biometric characteristics corresponding to at least two pieces of biometric information;

[0057] Different biological information can be converted into computable biological feature vectors through feature extraction algorithms and recorded as biological features.

[0058] That is, different biometric features include: voiceprint feature vectors, texture feature vectors, and face feature vectors.

[0059] Step 2: Update the weight coefficients corresponding to at least two biometric features based on the environmental information;

[0060] In this implementation, since environmental information may affect the acquisition of biometric information, it is necessary to update the weight coefficients corresponding to at least two biometric features based on the environmental information.

[0061] It should be understood that the initial weight coefficient can be preset. For example, if there is only facial information and fingerprint information, the initial weight coefficients are 0.5 and 0.5 respectively; for another example, if there is facial information, fingerprint information, and voiceprint information, the initial weight coefficients are 0.4, 0.3, and 0.3 respectively.

[0062] Exemplarily, the implementation of step 2 may include at least one of the following:

[0063] 1) if the illumination information indicates that the illumination intensity is greater than a first intensity threshold or less than a second intensity threshold, reducing the weight coefficient corresponding to the facial feature of at least two biometric features, and the first intensity threshold is greater than the second intensity threshold;

[0064] For example, when the light intensity is too large or too small, the acquired face information is not accurate enough, and thus the weight coefficient corresponding to the face feature needs to be reduced.

[0065] 2) If the noise information indicates that the noise intensity is greater than a third intensity threshold, the weight coefficient corresponding to the voiceprint feature in the at least two biometric features is reduced.

[0066] For example, when the noise intensity is too large, the noise in the acquired voiceprint information is too large, and thus the weight coefficient corresponding to the voiceprint feature needs to be reduced.

[0067] 3) If the temperature and humidity information indicates that the temperature and humidity is greater than a first temperature and humidity threshold, the weight coefficient corresponding to the fingerprint feature in the at least two biometric features is reduced.

[0068] For example, when the temperature and humidity is too large, the user's fingers may sweat, and thus the acquired fingerprint information is not accurate enough, and thus the weight coefficient corresponding to the fingerprint feature needs to be reduced.

[0069] For example, before the third step, the following can also be performed: determining a user feature state corresponding to each of the at least two biometric information; and for each user feature state, updating the weight coefficient corresponding to the biometric information according to the user feature state.

[0070] In this implementation, taking the face information as an example, when it is detected that the user feature state corresponding to the face information indicates that the user is in a fatigue state (which can be determined based on the eye closure frequency EAR value), the weight coefficient corresponding to the face information can be reduced.

[0071] Taking the voiceprint information as an example, when it is detected that the user feature state corresponding to the voiceprint information indicates that the user is in a nervous emotional state (which can be determined based on an increase in the standard deviation of the fundamental frequency F0 in the voiceprint information), the weight coefficient corresponding to the voiceprint information can be reduced.

[0072] It should be understood that the sum of the updated weight coefficients and the sum of the weight coefficients before updating are both 1, and when the weight coefficient corresponding to a certain item is reduced, the weight coefficients of the other one or two items should be increased accordingly.

[0073] 3) Determining a target fused biometric feature according to the updated weight coefficients and the at least two biometric features.

[0074] In this implementation, the sum of the products of each biometric feature and the updated weight coefficient corresponding to each biometric feature is determined as the target fused biometric feature.

[0075] 22) Authenticating the user according to the target fused biometric feature and the first mapping relationship.

[0076] The first mapping relationship includes: a correspondence between at least one fused biometric feature range and at least one authorized user.

[0077] In this step, the fused biometric feature range may be determined based on the historical multi-source biometric information corresponding to the authorized user, and then a first mapping relationship may be constructed based on the authorized user and the fused biometric feature range.

[0078] Furthermore, after determining the target fused biometric feature, the fused biometric feature range where the target fused biometric feature is located is determined in the first mapping relationship. If it exists, the user is determined to be an authorized user and subsequent steps can be executed.

[0079] Optionally, the fused biometric feature range may be an upper limit and a lower limit determined by adding or subtracting a first preset value based on the fused biometric feature vector; the first preset value may be set based on actual conditions.

[0080] The vehicle control method provided by an embodiment of the present invention determines a target fused biometric feature based on multi-source biometric information and environmental information. It then authenticates the user based on the target fused biometric feature and a first mapping relationship, which includes a correspondence between at least one fused biometric feature range and at least one authorized user. This technical solution first determines a more accurate target fused biometric feature based on real-time analysis of multi-source biometric information and environmental information, addressing the issue of single features being susceptible to environmental interference. Secondly, the preset first mapping relationship accurately determines whether the current user is an authorized user, thereby achieving authentication verification.

[0081] Based on the above embodiments, Figure 3 FIG. 1 is a flow chart showing a third embodiment of a vehicle control method provided by the present invention, wherein the method is executed by a vehicle. Figure 3 As shown, the above step 13 of "adjusting the vehicle cabin control according to the multi-source biometric information" may include the following steps:

[0082] Step 31: Determine the target emotion type of the user based on the facial information or voiceprint information in the multi-source biometric information;

[0083] In this step, the user's target emotion type can generally be obtained from the user's facial information or voiceprint information.

[0084] One possible implementation involves scanning the driver's face using a vehicle's built-in infrared or visible light camera to capture facial information. 3D structured light technology then locates 72 key feature points (such as eyebrows, eyes, face, and mouth corners). An algorithm is then used to detect micro-expressions within seconds, combined with muscle movement models to identify emotions. A classifier is trained using a convolutional neural network (CNN) architecture to map expressions to discrete emotion models, resulting in the target emotion type.

[0085] Another possible implementation involves using built-in voice sensors to capture the user's voiceprint information (such as pitch, speaking rate, and spectral characteristics). Acoustic features are significantly correlated with emotion. For example, anger leads to a higher pitch and faster speaking rate, while frustration may manifest as a lower, more intermittent voice. In this case, the time-frequency domain features of the voiceprint can be extracted and then mapped to the target emotion type using a pre-trained emotion classification model.

[0086] Step 32: Determine the target interaction strategy corresponding to the target emotion type in the second mapping relationship;

[0087] The second mapping relationship includes: a correspondence between at least one emotion type and at least one interaction strategy, and each interaction strategy includes at least one of the following: an atmosphere light control strategy, a music control strategy, and a fragrance control strategy;

[0088] In this step, after determining the target emotion type of the user, an emotion type consistent with the target emotion type is determined in the second mapping relationship, and the interaction strategy corresponding to the emotion type is determined as the target interaction strategy.

[0089] Optionally, the second mapping relationship may be constructed based on continuous learning of the driver's preference settings for the ambient light control information, the music control information, and the fragrance control information, as well as corresponding emotional responses.

[0090] Exemplarily, the second mapping relationship may include the following:

[0091] 1) If the emotion type is anger, the ambient light control strategy is: blue and light beige; the music control strategy is: pure music (tones that evoke feelings of calmness and joy); the fragrance control strategy is: sandalwood;

[0092] 2) If the emotion type is fear, the ambient light control strategy is: yellow to green gradient; the music control strategy is: match the theme to inspirational songs with a cheerful rhythm; the fragrance control strategy is: lavender + sandalwood;

[0093] 3) If the emotion type is surprise, the ambient light control strategy is: a dynamic breathing pattern, alternating between rose red and white; the music control strategy is: select songs with a soft theme; the fragrance control strategy is: lemon scent;

[0094] 4) If the emotion type is sadness, the ambient light control strategy is: alternating flashing yellow and light pink; the music control strategy is: matching and playing cheerful background music; the fragrance control strategy is: lavender + lemon;

[0095] 5) If the emotion type is disgust, the ambient light control strategy is: soft light purple and light green; the music control strategy is: using soothing music or natural white noise; the fragrance control strategy is: lemon flavor;

[0096] 6) If the emotion type is happiness, the ambient light control strategy is: sky blue or bright orange indirect constant light mode; the music control strategy is: using soft rhythm, white noise and classical music style; the fragrance control strategy is: lavender.

[0097] Step 33, adjusting the cabin control of the vehicle according to the target interaction strategy.

[0098] In this step, after the target interaction strategy is determined as described above, the ambient light system, the music playing system, and the fragrance system are controlled according to the corresponding ambient light control strategy, music control strategy, and / or fragrance control strategy in the target interaction strategy, respectively, to perform corresponding adjustment operations, so as to realize the cabin control adjustment of the vehicle.

[0099] The vehicle control method provided by the embodiment of the application determines the target emotion type of the user according to the face information or voiceprint information in the multi-source biological information, determines the target interaction strategy corresponding to the target emotion type in the second mapping relationship, wherein the second mapping relationship includes the corresponding relationship between at least one emotion type and at least one interaction strategy, and each interaction strategy includes at least one of the following: ambient light control strategy, music control strategy, and fragrance control strategy; and the cabin control of the vehicle is adjusted according to the target interaction strategy. In the technical solution, first, the target emotion type of the user is accurately identified through the face information or voiceprint information, solving the defect that the current cabin system has no perception of the psychological state of the user; second, based on the second mapping relationship, the optimal control strategy is intelligently matched, and the coordinated adjustment of the multi-modal cabin parameters is realized; the emotional interaction ability of the cabin system is improved, and the adjustment effect is enhanced through the linkage optimization of environmental elements, so that the cabin becomes an emotional intelligent space that can dynamically adapt to the psychological state of the user.

[0100] On the basis of the above-mentioned embodiments, Figure 4 A flow chart of a fourth embodiment of the vehicle control method provided by the application is shown, which is executed by a vehicle. As shown in Figure 4 The step 13 of adjusting the cabin control of the vehicle according to the environment information can include the following steps:

[0101] Step 41: Determine a target climate state outside the vehicle based on the environmental information;

[0102] In this step, environmental information can be obtained from relevant sensors installed on the vehicle, or by calling a weather information acquisition interface provided by a third party, so as to directly determine the target climate state outside the vehicle.

[0103] For example, the target climate state may be indicated as heavy rain, snow, high temperature, low temperature, and the like.

[0104] Step 42: Determine the target adjustment strategy corresponding to the target climate state in the third mapping relationship;

[0105] The third mapping relationship includes: a correspondence between at least one climate state and at least one adjustment strategy, each adjustment strategy including at least one of the following: an air conditioning adjustment strategy, a waterproof mode strategy, a seat adjustment strategy, a steering wheel adjustment strategy, and a lighting adjustment strategy;

[0106] In this step, after the target climate state is determined, a climate state consistent with the target climate state is determined in the third mapping relationship, and the adjustment strategy corresponding to the climate state is determined as the target adjustment strategy.

[0107] In this step, after the user's target climate state is determined, a climate state consistent with the target climate state is determined in the third mapping relationship, and the adjustment strategy corresponding to the climate state is determined as the target adjustment strategy.

[0108] Exemplarily, the third mapping relationship may include the following:

[0109] 1) If the weather condition indicates heavy rain or snow, the lighting adjustment strategy is: start the lighting system; the waterproof mode strategy is: turn on the waterproof mode;

[0110] 2) If the climate status indicates high temperature, the air conditioning adjustment strategy is to increase the air conditioning power and activate the cooling system;

[0111] 3) If the climate status indicates low temperature, the air conditioning adjustment strategy is: turn on the heater; the seat adjustment strategy is: heating level 3; the steering wheel adjustment strategy is: preheat the steering wheel.

[0112] Step 43: Adjust the vehicle cabin control according to the target adjustment strategy.

[0113] In this step, after the target adjustment strategy is determined as above, the air conditioning system, seat control system, and steering wheel control system are controlled to perform corresponding adjustment operations according to the corresponding air conditioning adjustment strategy, waterproof mode strategy, seat adjustment strategy, and / or steering wheel adjustment strategy in the target adjustment strategy to achieve cabin control adjustment of the vehicle.

[0114] The vehicle control method provided by an embodiment of the present invention determines a target climate state outside the vehicle based on environmental information; determines a target adjustment strategy corresponding to the target climate state in a third mapping relationship, wherein the third mapping relationship includes a correspondence between at least one climate state and at least one adjustment strategy, each adjustment strategy including at least one of the following: an air conditioning adjustment strategy, a waterproofing mode strategy, a seat adjustment strategy, a steering wheel adjustment strategy, and a lighting adjustment strategy; and adjusts the vehicle's cabin control according to the target adjustment strategy. This technical solution, firstly, accurately identifies the target climate state by collecting information about the vehicle's external environment in real time, resolving the lag problem of the current cabin system's passive response to environmental changes; secondly, based on the third mapping relationship, intelligently triggers an optimal control strategy combination to achieve active environmental adaptation of the cabin system. This not only improves driving comfort but also enhances safety through the coordinated adjustment of key components, making the cabin an "adaptive protective space" that can intelligently respond to complex climate conditions.

[0115] Based on the above embodiments, Figure 5 The figure shows a schematic diagram of the authentication and verification process in the vehicle control method provided by the present invention, which is executed by the vehicle. Figure 5 As shown, the authentication and verification process includes: three-factor fusion authentication module, dynamic weight model, and authentication decision.

[0116] The three-factor fusion authentication module includes: fingerprint feature extraction, facial feature collection, voiceprint feature extraction, and feature fusion engine;

[0117] The dynamic weight model includes: weight adjustment of three factors based on environmental information and user characteristic status.

[0118] Based on the above embodiments, Figure 6 The figure shows a schematic diagram of the biometric-environment-cabin adjustment process in the vehicle control method provided by the present invention, which is executed by the vehicle. Figure 6 As shown, the biometric-environment-cockpit adjustment process includes: a perception layer, a decision layer, and an execution layer.

[0119] The perception layer includes: multimodal biometric authentication, user login after authentication, real-time face scanning, user login timing (first time or long-term), and environmental information collection (rainfall sensor, humidity sensor, temperature sensor, light sensor);

[0120] The decision-making layer includes: determining the user's height percentage and sitting posture preference; determining the user's emotional type; determining the weather conditions;

[0121] The execution layer includes: the controller performs three adjustments based on the decision layer, namely: seat adjustment, emotional environment adjustment, environmental cabin adjustment, real-time monitoring, and dynamic compensation adjustment.

[0122] Among them, emotional environment adjustment includes: fragrance combination matching, music scene adaptation, and interior ambient light adaptation; environmental cabin adjustment includes: (heavy rain / snow) start waterproof mode / start lighting system; (high temperature) activate cooling system / increase air conditioning power; (low temperature) preheat steering wheel / seat heating level 3 / turn on interior warm air conditioning.

[0123] The authentication and verification process and the biometric-environment-cabin adjustment process provided by the embodiments of the present invention have the following technical effects:

[0124] 1) Improved recognition accuracy: The multimodal misrecognition rate is reduced to 0.003% (two orders of magnitude lower than a single-sensor system);

[0125] 2) Improved user experience in the intelligent cockpit: cockpit settings adjust with changes in human emotions; cockpit settings automatically adjust with changes in external weather.

[0126] Figure 7 FIG. 1 shows a schematic structural diagram of an embodiment of a vehicle control device provided by the present invention. Figure 7 As shown, the device includes:

[0127] An acquisition module 71 is used to acquire multi-source biometric information of the user in the vehicle and environmental information of the vehicle;

[0128] The verification module 72 is used to authenticate the user based on multi-source biometric information and environmental information; the processing module 73 is used to adjust the vehicle cabin control based on the multi-source biometric information and / or environmental information after the user's authentication is passed.

[0129] In one or more embodiments, the verification module 72 is specifically configured to:

[0130] Determine the target fusion biological features based on multi-source biological information and environmental information;

[0131] The user is authenticated and verified according to the target fused biometric feature and the first mapping relationship, wherein the first mapping relationship includes: a correspondence between at least one fused biometric feature range and at least one authorized user.

[0132] In one or more embodiments, the multi-source biometric information includes at least two of the following biometric information: facial information, fingerprint information, and voiceprint information;

[0133] Accordingly, the verification module 72 determines the target fused biometric feature based on the multi-source biometric information and the environmental information, specifically for:

[0134] determine at least two biological features corresponding to the biological information respectively;

[0135] update weight coefficients corresponding to the at least two biological features according to the environment information;

[0136] determine a target fusion biological feature according to the updated weight coefficients and the at least two biological features.

[0137] In one or more embodiments, before determining the target fusion biological feature according to the updated weight coefficients and the at least two biological features, the verification module 72 is further configured to:

[0138] determine user feature states corresponding to the at least two biological features respectively;

[0139] for each user feature state, update a weight coefficient corresponding to the biological information according to the user feature state.

[0140] In one or more embodiments, the environment information includes at least one of the following: illumination information, noise information, temperature and humidity information;

[0141] Correspondingly, the verification module 72 updates the weight coefficients corresponding to the at least two biological features according to the environment information, and is specifically configured to perform at least one of the following:

[0142] if the illumination information indicates that the illumination intensity is greater than a first intensity threshold or less than a second intensity threshold, the weight coefficient corresponding to the face feature in the at least two biological features is reduced, the first intensity threshold is greater than the second intensity threshold;

[0143] if the noise information indicates that the noise intensity is greater than a third intensity threshold, the weight coefficient corresponding to the voiceprint feature in the at least two biological features is reduced;

[0144] if the temperature and humidity information indicates that the temperature and humidity is greater than a first temperature and humidity threshold, the weight coefficient corresponding to the fingerprint feature in the at least two biological features is reduced.

[0145] In one or more embodiments, the processing module 73 performs seat control adjustment on the vehicle according to the multi-source biological information, and is specifically configured to:

[0146] determine a target emotion type of the user according to face information or voiceprint information in the multi-source biological information;

[0147] determine a target interaction strategy corresponding to the target emotion type in a second mapping relationship, the second mapping relationship including a corresponding relationship between at least one emotion type and at least one interaction strategy, each interaction strategy including at least one of the following: atmosphere lamp control strategy, music control strategy, and fragrance control strategy;

[0148] Adjust the vehicle's cabin control based on the target interaction strategy.

[0149] In one or more embodiments, the processing module 73 adjusts the vehicle cabin control based on the environmental information, specifically for:

[0150] Determine the target climate state outside the vehicle based on environmental information;

[0151] Determining a target adjustment strategy corresponding to the target climate state in a third mapping relationship, the third mapping relationship including: a correspondence between at least one climate state and at least one adjustment strategy, each adjustment strategy including at least one of the following: an air conditioning adjustment strategy, a waterproof mode strategy, a seat adjustment strategy, a steering wheel adjustment strategy, and a lighting adjustment strategy;

[0152] Adjust the vehicle's cabin controls based on the target adjustment strategy.

[0153] It should be noted that it should be understood that the division of the various modules of the above device is merely a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical element, or physically separated. Moreover, these modules can all be implemented in the form of software called by a processing element. They can also all be implemented in the form of hardware. Some modules can also be implemented in the form of software called by a processing element, and some modules can be implemented in the form of hardware. In addition, these modules can all or partly be integrated together or implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. During implementation, each step of the above method or each of the above modules can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.

[0154] From the above, it can be seen that the vehicle control device provided by the embodiment of the present invention can combine multi-source biometric information and environmental data for comprehensive authentication, which can make up for the defects of single biometric feature recognition and improve the robustness and accuracy of verification; and after the authentication is passed, through real-time analysis of multi-source biometric information and environmental information, dynamically adjust the cabin parameters, realize the coordinated optimization of human-vehicle-environment, enhance the emotional and intelligent level of human-computer interaction, and ultimately improve driving safety and user satisfaction.

[0155] Figure 8 A schematic structural diagram of an embodiment of a vehicle provided by the present invention is shown. Figure 8 As shown, the vehicle may include a processor 82 , a communications interface 84 , a memory 86 , and a communication bus 88 .

[0156] Processor 82, communication interface 84, and memory 86 communicate with each other via communication bus 88. Communication interface 84 is used to communicate with other devices, such as clients or other server network elements. Processor 82 is used to execute program 80, specifically, the steps described in the above method embodiments.

[0157] Specifically, the program 80 may include program code including computer-executable instructions.

[0158] Processor 82 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in the vehicle may be of the same type, such as one or more CPUs, or may be of different types, such as one or more CPUs and one or more ASICs.

[0159] The memory 86 is used to store the program 80. The memory 86 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0160] The program 80 may be specifically called by the processor 82 to cause the vehicle to perform the following operations:

[0161] Acquire multi-source biometric information of users in the vehicle and information about the vehicle's environment;

[0162] Authenticate and verify users based on multi-source biological and environmental information;

[0163] After the user's authentication is passed, the vehicle cabin control is adjusted based on multi-source biometric information and / or environmental information.

[0164] In one or more embodiments, user authentication and verification based on multi-source biometric information and environmental information includes:

[0165] Determine the target fusion biological features based on multi-source biological information and environmental information;

[0166] The user is authenticated and verified according to the target fused biometric feature and the first mapping relationship, wherein the first mapping relationship includes: a correspondence between at least one fused biometric feature range and at least one authorized user.

[0167] In one or more embodiments, the multi-source biometric information includes at least two of the following biometric information: facial information, fingerprint information, and voiceprint information;

[0168] Correspondingly, the target fused biometric feature is determined according to the multi-source biometric information and the environmental information, including:

[0169] determining biometric features corresponding to the at least two items of biometric information respectively;

[0170] updating weight coefficients corresponding to the at least two biometric features respectively according to the environmental information;

[0171] determining the target fused biometric feature according to the updated weight coefficients and the at least two biometric features.

[0172] In one or more embodiments, before determining the target fused biometric feature according to the updated weight coefficients and the at least two biometric features, the following is further performed:

[0173] determining user feature states corresponding to the at least two items of biometric information respectively;

[0174] for each user feature state, updating the weight coefficients corresponding to the biometric information according to the user feature state.

[0175] In one or more embodiments, the environmental information includes at least one of the following: illumination information, noise information, temperature and humidity information;

[0176] Correspondingly, the weight coefficients corresponding to the at least two biometric features are updated according to the environmental information, including at least one of the following:

[0177] if the illumination information indicates that the illumination intensity is greater than a first intensity threshold or less than a second intensity threshold, the weight coefficient corresponding to the face feature in the at least two biometric features is reduced, the first intensity threshold is greater than the second intensity threshold;

[0178] if the noise information indicates that the noise intensity is greater than a third intensity threshold, the weight coefficient corresponding to the voiceprint feature in the at least two biometric features is reduced;

[0179] if the temperature and humidity information indicates that the temperature and humidity is greater than a first temperature and humidity threshold, the weight coefficient corresponding to the fingerprint feature in the at least two biometric features is reduced.

[0180] In one or more embodiments, the vehicle is controlled and adjusted in the cabin according to the multi-source biometric information, including:

[0181] determining a target emotion type of the user according to face information or voiceprint information in the multi-source biometric information;

[0182] determining a target interaction strategy corresponding to the target emotion type in the second mapping relationship, the second mapping relationship including a corresponding relationship between at least one emotion type and at least one interaction strategy, each interaction strategy including at least one of the following: atmosphere lamp control strategy, music control strategy, and fragrance control strategy;

[0183] Adjust the vehicle's cabin control based on the target interaction strategy.

[0184] In one or more embodiments, adjusting cabin control of a vehicle based on environmental information includes:

[0185] Determine the target climate state outside the vehicle based on environmental information;

[0186] Determining a target adjustment strategy corresponding to the target climate state in a third mapping relationship, the third mapping relationship including: a correspondence between at least one climate state and at least one adjustment strategy, each adjustment strategy including at least one of the following: an air conditioning adjustment strategy, a waterproof mode strategy, a seat adjustment strategy, a steering wheel adjustment strategy, and a lighting adjustment strategy;

[0187] Adjust the vehicle's cabin controls based on the target adjustment strategy.

[0188] From the above, it can be seen that the vehicle provided by the embodiment of the present invention can combine multi-source biometric information and environmental data for comprehensive authentication, which can make up for the shortcomings of single biometric feature recognition and improve the robustness and accuracy of verification; and after the authentication is passed, through real-time analysis of multi-source biometric information and environmental information, the cabin parameters are dynamically adjusted to achieve collaborative optimization of human-vehicle-environment, enhance the emotional and intelligent level of human-computer interaction, and ultimately improve driving safety and user satisfaction.

[0189] An embodiment of the present invention provides a computer-readable storage medium storing at least one executable instruction. When the executable instruction is executed on a vehicle control device / vehicle, the vehicle control device / vehicle executes the vehicle control method in any of the above method embodiments.

[0190] The executable instructions may be specifically used to cause the vehicle control device / vehicle to perform the following operations:

[0191] Acquire multi-source biometric information of users in the vehicle and information about the vehicle's environment;

[0192] Authenticate and verify users based on multi-source biological and environmental information;

[0193] After the user's authentication is passed, the vehicle cabin control is adjusted based on multi-source biometric information and / or environmental information.

[0194] In one or more embodiments, user authentication and verification based on multi-source biometric information and environmental information includes:

[0195] Determine the target fusion biological features based on multi-source biological information and environmental information;

[0196] The user is authenticated and verified according to the target fused biometric feature and the first mapping relationship, wherein the first mapping relationship includes: a correspondence between at least one fused biometric feature range and at least one authorized user.

[0197] In one or more embodiments, the multi-source biometric information includes at least two of the following biometric information: facial information, fingerprint information, and voiceprint information;

[0198] Accordingly, based on multi-source biological information and environmental information, target fusion biological features are determined, including:

[0199] Determine the biometric characteristics corresponding to at least two pieces of biometric information;

[0200] updating weight coefficients corresponding to at least two biometric features according to the environmental information;

[0201] A target fused biometric feature is determined according to the updated weight coefficient and at least two biometric features.

[0202] In one or more embodiments, before determining the target fused biometric feature based on the updated weight coefficient and at least two biometric features, the following steps are further performed:

[0203] Determining user characteristic states corresponding to at least two pieces of biometric information;

[0204] For each user feature state, the weight coefficient corresponding to the biometric information is updated according to the user feature state.

[0205] In one or more embodiments, the environmental information includes at least one of the following: illumination information, noise information, temperature and humidity information;

[0206] Accordingly, based on the environmental information, the weight coefficients corresponding to the at least two biometric features are updated, including at least one of the following:

[0207] If the illumination information indicates that the illumination intensity is greater than a first intensity threshold or less than a second intensity threshold, reducing a weight coefficient corresponding to a facial feature among the at least two biometric features, the first intensity threshold being greater than the second intensity threshold;

[0208] If the noise information indicates that the noise intensity is greater than a third intensity threshold, reducing a weight coefficient corresponding to the voiceprint feature of the at least two biometric features;

[0209] If the temperature and humidity information indicates that the temperature and humidity are greater than a first temperature and humidity threshold, a weight coefficient corresponding to the fingerprint feature of the at least two biometric features is reduced.

[0210] In one or more embodiments, adjusting cabin control of a vehicle based on multi-source biometric information includes:

[0211] Determine the user's target emotion type based on facial information or voiceprint information in multi-source biometric information;

[0212] Determining a target interaction strategy corresponding to the target emotion type in a second mapping relationship, the second mapping relationship including: a correspondence between at least one emotion type and at least one interaction strategy, each interaction strategy including at least one of the following: an ambient light control strategy, a music control strategy, and a fragrance control strategy;

[0213] Adjust the vehicle's cabin control based on the target interaction strategy.

[0214] In one or more embodiments, adjusting cabin control of a vehicle based on environmental information includes:

[0215] Determine the target climate state outside the vehicle based on environmental information;

[0216] Determining a target adjustment strategy corresponding to the target climate state in a third mapping relationship, the third mapping relationship including: a correspondence between at least one climate state and at least one adjustment strategy, each adjustment strategy including at least one of the following: an air conditioning adjustment strategy, a waterproof mode strategy, a seat adjustment strategy, a steering wheel adjustment strategy, and a lighting adjustment strategy;

[0217] Adjust the vehicle's cabin controls based on the target adjustment strategy.

[0218] From the above, it can be seen that the vehicle / vehicle control device provided by the embodiment of the present invention can combine multi-source biometric information and environmental data for comprehensive authentication, which can make up for the defects of single biometric feature recognition and improve the robustness and accuracy of verification; and after the authentication is passed, through real-time analysis of multi-source biometric information and environmental information, dynamically adjust the cabin parameters to achieve collaborative optimization of human-vehicle-environment, enhance the emotional and intelligent level of human-computer interaction, and ultimately improve driving safety and user satisfaction.

[0219] An embodiment of the present invention provides a computer program product, including a computer program, which implements the operations of the above-mentioned vehicle control method when executed by a processor.

[0220] Its implementation principle and technical effects are shown in the above disclosure.

[0221] The above description of the various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced with each other and will not be repeated herein for the sake of brevity.

[0222] The methods disclosed in the various method embodiments provided by the present invention can be arbitrarily combined without conflict to obtain new method embodiments.

[0223] The features disclosed in the various product embodiments of the present application can be combined, if not mutually exclusive, to form new product embodiments.

[0224] The features disclosed in the various method or device embodiments of the present application can be combined, if not mutually exclusive, to form new method embodiments or device embodiments.

[0225] It should be noted that the computer-readable storage medium described above can be a ROM, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a ferromagnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM), etc. It can also be various vehicles including one or any combination of the above memories.

[0226] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusions, so that a process, method, article, or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such a process, method, article, or device. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of other identical elements in the process, method, article, or device including the element.

[0227] The above-mentioned embodiment numbers of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0228] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus necessary general hardware nodes, or of course by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, vehicle terminal or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0229] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices, apparatuses, and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0230] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0231] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The algorithm or display provided herein for the steps of the functions specified in the blocks or blocks is not inherently related to any specific computer, virtual system or other device. In addition, the embodiments of the present invention are not directed to any specific programming language.

[0232] It should be noted that the above embodiments illustrate rather than limit the invention, and that alternative embodiments may be devised by a person skilled in the art without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments should not be understood as limiting the order of execution unless otherwise specified.

Claims

1. A vehicle control method, characterized in that: The method comprises: Acquiring multi-source biometric information of a user in a vehicle and environmental information of the vehicle; authenticating the user based on the multi-source biometric information and the environmental information; After the user's authentication is passed, the vehicle's cabin control is adjusted according to the multi-source biometric information and / or the environmental information.

2. The method according to claim 1, characterized in that The authenticating and verifying the user based on the multi-source biometric information and the environmental information includes: determining a target fused biometric feature based on the multi-source biometric information and the environmental information; The user is authenticated according to the target fused biometric feature and a first mapping relationship, wherein the first mapping relationship includes a correspondence between at least one fused biometric feature range and at least one authorized user.

3. The method according to claim 2, characterized in that The multi-source biometric information includes at least two of the following biometric information: face information, fingerprint information, and voiceprint information; Accordingly, determining a target fused biometric feature based on the multi-source biometric information and the environmental information includes: Determining biometric features corresponding to the at least two pieces of biometric information respectively; updating weight coefficients corresponding to at least two biometric features respectively according to the environmental information; The target fused biometric feature is determined according to the updated weight coefficient and the at least two biometric features.

4. The method according to claim 3, characterized in that Before determining the target fused biometric feature based on the updated weight coefficient and the at least two biometric features, the method further includes: Determining user characteristic states corresponding to the at least two items of biometric information respectively; For each user feature state, the weight coefficient corresponding to the biometric information is updated according to the user feature state.

5. The method according to claim 3, characterized in that The environmental information includes at least one of the following: lighting information, noise information, temperature and humidity information; Accordingly, the updating of the weight coefficients corresponding to the at least two biometric features according to the environmental information includes at least one of the following: if the illumination information indicates that the illumination intensity is greater than a first intensity threshold or less than a second intensity threshold, reducing a weight coefficient corresponding to a facial feature among the at least two biometric features, and the first intensity threshold is greater than the second intensity threshold; If the noise information indicates that the noise intensity is greater than a third intensity threshold, reducing a weight coefficient corresponding to the voiceprint feature among the at least two biometric features; If the temperature and humidity information indicates that the temperature and humidity are greater than a first temperature and humidity threshold, a weight coefficient corresponding to the fingerprint feature of the at least two biometric features is reduced.

6. The method according to any one of claims 1 to 5, characterized in that Performing cabin control adjustment on the vehicle according to the multi-source biometric information includes: determining a target emotion type of the user based on facial information or voiceprint information in the multi-source biometric information; Determining a target interaction strategy corresponding to the target emotion type in a second mapping relationship, wherein the second mapping relationship includes: a correspondence between at least one emotion type and at least one interaction strategy, each interaction strategy including at least one of the following: an atmosphere light control strategy, a music control strategy, and a fragrance control strategy; The vehicle cabin control is adjusted according to the target interaction strategy.

7. The method according to any one of claims 1 to 5, characterized in that Performing cabin control adjustment on the vehicle according to the environmental information includes: determining a target climate state outside the vehicle based on the environmental information; Determining a target adjustment strategy corresponding to the target climate state in a third mapping relationship, the third mapping relationship including: a correspondence between at least one climate state and at least one adjustment strategy, each adjustment strategy including at least one of the following: an air conditioning adjustment strategy, a waterproof mode strategy, a seat adjustment strategy, a steering wheel adjustment strategy, and a lighting adjustment strategy; The vehicle cabin control is adjusted according to the target adjustment strategy.

8. A vehicle control device, characterized in that: The device comprises: An acquisition module, configured to acquire multi-source biometric information of a user in a vehicle and environmental information of the vehicle; a verification module, configured to authenticate the user based on the multi-source biometric information and the environmental information; A processing module is used to adjust the cabin control of the vehicle according to the multi-source biometric information and / or the environmental information after the user's authentication is passed.

9. A vehicle, characterized in that: include: A processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform the operation of the vehicle control method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The storage medium stores at least one executable instruction, and when the executable instruction is executed on the vehicle control device / vehicle, the vehicle control device / vehicle performs the operation of the vehicle control method according to any one of claims 1 to 7.

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