A method, apparatus, vehicle, and storage medium for detecting a living being in a vehicle

Abstract

The application provides a method and device for detecting living beings in a vehicle, a vehicle and a storage medium. The method is applied to the field of vehicle safety detection, and comprises the following steps: determining a total detection score of M state parameters according to the M state parameters collected by M collection devices of the vehicle, wherein the state parameters are used for representing the running state of the vehicle, and the total detection score is used for representing the probability of the presence of living beings in the vehicle; determining whether there is a living being in the vehicle according to the total detection score; and generating target alarm information according to the position of the vehicle and the type of the living being in the case that there is a living being in the vehicle. The method can timely detect whether there is a living being left in the vehicle and alarm without introducing additional hardware devices, and can avoid the safety risk caused by the long-time leaving of the living being in the vehicle.

Description

Technical Field

[0001] The present application relates to the field of vehicle safety detection, and more specifically, to a method, device, vehicle, and storage medium for detecting living things in a vehicle in the field of vehicle safety detection. Background Art

[0002] Currently, when users use vehicles, when there are children or pets in the vehicle, they are often overlooked when getting off the vehicle because these living creatures are small and difficult to observe.

[0003] When children or pets are left in a car, if the temperature of the vehicle's environment is high, the temperature inside the car will rise rapidly in a short period of time, which can easily cause the living creatures to become unconscious or suffer from heatstroke, endangering their lives and health.

[0004] Therefore, how to effectively and timely detect living organisms in the car has become an urgent problem that needs to be solved. Summary of the Invention

[0005] The present application provides a method, device, vehicle and storage medium for detecting living organisms in a vehicle. The method can use the vehicle's own collection equipment to promptly detect whether there are living organisms left in the vehicle and issue an alarm without introducing additional hardware equipment, thereby avoiding the safety risks caused by living organisms left in the vehicle for a long time.

[0006] In a first aspect, a method for detecting living organisms within a vehicle is provided, the method comprising: determining a total detection score for M state parameters collected by M acquisition devices of the vehicle, where the state parameters are used to represent the operating state of the vehicle, M is a positive integer greater than 1, and the total detection score is used to represent the probability of the presence of a living organism within the vehicle; determining whether there is a living organism within the vehicle based on the total detection score; and, if there is a living organism within the vehicle, generating target alarm information based on the location of the vehicle and the type of the living organism.

[0007] In the above technical solution, to prevent children or pets from being left behind in a locked vehicle, this application proposes a method for detecting living organisms inside the vehicle. Specifically, the vehicle can determine a total detection score based on M status parameters collected by its M acquisition devices. The total detection score can represent the probability of the presence of a living organism inside the vehicle. In other words, the higher the total detection score, the greater the probability of the presence of a living organism inside the vehicle. The lower the total detection score, the lower the probability of the presence of a living organism inside the vehicle. Furthermore, the vehicle uses the specific value of the total detection score to determine whether a living organism is inside the vehicle. If a living organism is present, a targeted alarm message is generated based on the vehicle's location and the type of living organism. In this implementation, the vehicle can rely on its own sensors to detect the presence of living organisms inside the vehicle, eliminating the need for additional detection equipment. This reduces the vehicle's hardware and software costs and enables timely detection of whether a living organism has been left behind inside the vehicle. In addition, using data collected by multiple acquisition devices on the vehicle for detection can provide a more comprehensive assessment of the vehicle's interior environment, avoiding false alarms caused by a single parameter. When there are living creatures in the car, the vehicle will sound an alarm based on the location and type of the living creature, allowing people outside the car and users to discover and deal with it in time, avoiding safety hazards caused by living creatures being left in the car for a long time.

[0008] In combination with the first aspect, in some possible implementations, before determining the total detection score of the M state parameters based on the M state parameters collected by the M collection devices of the vehicle, the method also includes: obtaining the detection level corresponding to each of the M state parameters, and the detection level is used to indicate the degree of influence of the living organism on the state parameter; and determining the total detection score of the M state parameters based on the M state parameters collected by the M collection devices of the vehicle, including: based on the detection level corresponding to each of the M state parameters, dividing the M state parameters into U first state parameters, V second state parameters and W third state parameters, the detection level of the U first state parameters is higher than the detection level of the V second state parameters, and the detection level of the V second state parameters is higher than the detection level of the W third state parameters; determining the total detection score based on the U first state parameters, the V second state parameters and the W third state parameters.

[0009] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, determining whether there is a living creature in the vehicle based on the total detection score includes: determining that there is a living creature in the vehicle when the total detection score is greater than or equal to a first preset score; and determining that there is no living creature in the vehicle when the total detection score is less than the first preset score.

[0010] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, before determining the total detection score based on the U first state parameters, the V second state parameters and the W third state parameters, the method also includes: obtaining a first weight corresponding to the detection level of the U first state parameters, a second weight corresponding to the detection level of the V second state parameters, and a third weight corresponding to the detection level of the W third state parameters; and determining the total detection score based on the U first state parameters, the V second state parameters and the W third state parameters includes: determining a first detection score based on the U first state parameters; determining a second detection score based on the V second state parameters; determining a third detection score based on the W third state parameters; and determining the total detection score based on the first detection score, the second detection score, the third detection score, the first weight, the second weight and the third weight.

[0011] In this technical solution, when determining the overall detection score, the vehicle can assign different weights to each detection level based on the detection level of each state parameter. This ensures that more sensitive state parameters receive higher feedback during detection. Furthermore, the detection score for each detection level is calculated separately and the corresponding weights are combined to produce an overall detection score. This comprehensively considers the data collected by multiple collection devices on the vehicle, improving the accuracy of detection results.

[0012] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the first detection score is determined based on the U first state parameters, including: for any first state parameter among the U first state parameters, obtaining the first preset condition corresponding to the first state parameter; determining whether the first state parameter meets the first preset condition; if the first state parameter meets the first preset condition, determining the sub-detection score of the first state parameter to be the second preset score; if the first state parameter does not meet the first preset condition, determining the sub-detection score of the first state parameter to be the third preset score, and the second preset score is greater than the third preset score; determining the first detection score to be the sum of the sub-detection scores of the U first state parameters.

[0013] In the above technical solution, since the first state parameter is a state parameter that is highly sensitive to the activities of living organisms in the vehicle, changes in this type of state parameter are usually caused by living organisms rather than external environmental factors. Therefore, when this type of state parameter changes, it indicates that the probability of the presence of living organisms in the vehicle is extremely high. Based on this, when determining the first detection score of this type of state parameter, the vehicle can ignore the influence of the external environment and directly perform a cumulative score on the first state parameter based on whether the first state parameter meets its corresponding first preset condition to obtain the first detection score of the U first state parameters with the highest detection level. The above process simplifies the scoring logic for state parameters with high detection levels and quickly and accurately assesses the probability of the presence of living organisms in the vehicle.

[0014] In combination with the first aspect and the above-mentioned implementation manner, in some possible implementation manners, determining the second detection score based on the V second state parameters includes: for any second state parameter among the V second state parameters, obtaining the second preset condition corresponding to the second state parameter; determining whether the second state parameter meets the second preset condition; when the second state parameter meets the second preset condition, obtaining the trigger state and acceleration of the blind spot alarm signal of the vehicle, the trigger state being used to indicate whether there is an abnormality in the blind spot of the vehicle; when the trigger state is not triggered and the acceleration is less than or equal to the preset acceleration, determining the sub-detection score of the second state parameter to be a fourth preset score; when the trigger state is triggered, or when the acceleration is greater than the preset acceleration, determining the sub-detection score of the second state parameter to be a fifth preset score, and the fourth preset score is greater than the fifth preset score; when the second state parameter does not meet the second preset condition, determining the sub-detection score of the second state parameter to be the fifth preset score; and determining the second detection score to be the sum of the sub-detection scores of the V second state parameters.

[0015] In the above technical solution, the detection levels corresponding to the V second state parameters are slightly lower than those corresponding to the U first state parameters. Changes in these state parameters are not solely due to biological activity within the vehicle but may also be due to external factors. Therefore, when determining the second detection score for these state parameters, even if the state parameters meet the corresponding preset conditions, it is necessary to verify whether the state parameter changes are caused by external factors through the vehicle's blind spot warning signal and acceleration. This ensures accurate perception of the surrounding environment, avoids misjudgments due to external interference, and enhances the stability and reliability of the scoring process.

[0016] In combination with the first aspect and the above-mentioned implementation method, in some possible implementation methods, the third detection score is determined based on the W third state parameters, including: for any third state parameter of the W third state parameters, obtaining a third preset condition corresponding to the third state parameter; determining whether the third state parameter meets the third preset condition; when the third state parameter meets the third preset condition, obtaining the trigger state and acceleration of the blind spot alarm signal of the vehicle, the trigger state is used to indicate whether there is an abnormality in the blind spot of the vehicle; the time length when the third state parameter meets the third preset condition is greater than the preset time length, and the trigger state is not triggered within the preset time length, and the acceleration is When the acceleration is less than or equal to the preset acceleration, the sub-detection score of the third state parameter is determined to be the sixth preset score; when the duration for which the third state parameter meets the third preset condition is less than or equal to the preset duration, or, the trigger state is not entirely untriggered within the preset duration, or, the acceleration is not entirely less than or equal to the preset acceleration within the preset duration, the sub-detection score of the third state parameter is determined to be the seventh preset score, and the sixth preset score is greater than the seventh preset score; when the third state parameter does not meet the third preset condition, the sub-detection score of the third state parameter is determined to be the seventh preset score; the third detection score is determined to be the sum of the sub-detection scores of the W third state parameters.

[0017] In the above technical solution, the detection level corresponding to the W third state parameters is slightly lower than the detection level of the V second state parameters. Compared with the second state parameters, the change of this type of state parameters is not entirely caused by the activity of living organisms in the vehicle, but may also be caused by external factors or changes in the vehicle's own state (for example, a vehicle parked on an uneven road will cause a small shake). In general, if the change occurs in the vehicle's own state, the duration is relatively short. Therefore, when determining the third detection score of this type of state parameter, when the state parameter meets the corresponding preset conditions, it is also necessary to use the vehicle's blind spot alarm signal and acceleration to check whether the change in the state parameter is caused by external factors. When the change in the state parameter is not caused by external factors, it is necessary to further determine whether the current change is caused by the change in the vehicle's own state through the duration of the change. Therefore, for the state parameters with lower detection levels and lower sensitivity, all external factors that may cause false alarms can be excluded when determining the detection score, thereby enhancing the stability and reliability of the score determination process.

[0018] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the method also includes: when there is a living organism in the vehicle, calling the image acquisition device in the vehicle to obtain a facial image of the living organism; classifying and identifying the facial image to determine the type of the living organism.

[0019] In the above technical solution, when the vehicle determines that there are living organisms in the vehicle, it can further use image recognition algorithms to identify the type of forgotten objects in the vehicle, thereby generating target alarm information, allowing users to take corresponding treatment measures more quickly.

[0020] In a second aspect, a device for detecting living organisms in a vehicle is provided, the device comprising: a score determination module for determining a total detection score of M state parameters collected by M collection devices of the vehicle, wherein the state parameters are used to represent the operating state of the vehicle, M is a positive integer greater than 1, and the total detection score is used to represent the probability of the presence of a living organism in the vehicle; a living organism detection module for determining whether there is a living organism in the vehicle based on the total detection score; and an alarm module for generating target alarm information based on the location of the vehicle and the type of the living organism when there is a living organism in the vehicle.

[0021] In combination with the second aspect, in some possible implementations, before determining the total detection score of the M state parameters based on the M state parameters collected by the M collection devices of the vehicle, the score determination module is also used to: obtain the detection level corresponding to each of the M state parameters, and the detection level is used to indicate the degree of influence of the living organism on the state parameter; and the score determination module is specifically used to: based on the detection level corresponding to each of the M state parameters, divide the M state parameters into U first state parameters, V second state parameters and W third state parameters, the detection level of the U first state parameters is higher than the detection level of the V second state parameters, and the detection level of the V second state parameters is higher than the detection level of the W third state parameters; determine the total detection score based on the U first state parameters, the V second state parameters and the W third state parameters.

[0022] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the biological detection module is also used to: determine that there are living organisms in the vehicle when the total detection score is greater than or equal to a first preset score; and determine that there are no living organisms in the vehicle when the total detection score is less than the first preset score.

[0023] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, before determining the total detection score based on the U first state parameters, the V second state parameters and the W third state parameters, the score determination module is also used to: obtain the first weight corresponding to the detection level of the U first state parameters, the second weight corresponding to the detection level of the V second state parameters, and the third weight corresponding to the detection level of the W third state parameters; and the score determination module is also used to: determine the first detection score based on the U first state parameters; determine the second detection score based on the V second state parameters; determine the third detection score based on the W third state parameters; and determine the total detection score based on the first detection score, the second detection score, the third detection score, the first weight, the second weight and the third weight.

[0024] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the score determination module is also used to: for any first state parameter among the U first state parameters, obtain the first preset condition corresponding to the first state parameter; determine whether the first state parameter meets the first preset condition; if the first state parameter meets the first preset condition, determine the sub-detection score of the first state parameter to be the second preset score; if the first state parameter does not meet the first preset condition, determine the sub-detection score of the first state parameter to be the third preset score, and the second preset score is greater than the third preset score; determine the first detection score to be the sum of the sub-detection scores of the U first state parameters.

[0025] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the score determination module is also used to: for any second state parameter of the V second state parameters, obtain the second preset condition corresponding to the second state parameter; determine whether the second state parameter meets the second preset condition; when the second state parameter meets the second preset condition, obtain the trigger state and acceleration of the blind spot alarm signal of the vehicle, and the trigger state is used to indicate whether there is an abnormality in the blind spot of the vehicle; when the trigger state is not triggered and the acceleration is less than or equal to the preset acceleration, determine that the sub-detection score of the second state parameter is a fourth preset score; when the trigger state is triggered, or when the acceleration is greater than the preset acceleration, determine that the sub-detection score of the second state parameter is a fifth preset score, and the fourth preset score is greater than the fifth preset score; when the second state parameter does not meet the second preset condition, determine that the sub-detection score of the second state parameter is the fifth preset score; and determine that the second detection score is the sum of the sub-detection scores of the V second state parameters.

[0026] In combination with the second aspect and the above-mentioned implementation manner, in some possible implementation manners, the scoring determination module is further used to: for any third state parameter of the W third state parameters, obtain a third preset condition corresponding to the third state parameter; determine whether the third state parameter satisfies the third preset condition; if the third state parameter satisfies the third preset condition, obtain the trigger state and acceleration of the blind spot alarm signal of the vehicle, and the trigger state is used to indicate whether there is an abnormality in the blind spot of the vehicle; the time length during which the third state parameter meets the third preset condition is greater than the preset time length, and the trigger state is not triggered within the preset time length, and the acceleration is less than or equal to the preset time length. In the case of acceleration, the sub-detection score of the third state parameter is determined to be the sixth preset score; when the duration for which the third state parameter meets the third preset condition is less than or equal to the preset duration, or, the trigger state is not entirely untriggered within the preset duration, or, the acceleration is not entirely less than or equal to the preset acceleration within the preset duration, the sub-detection score of the third state parameter is determined to be the seventh preset score, and the sixth preset score is greater than the seventh preset score; when the third state parameter does not meet the third preset condition, the sub-detection score of the third state parameter is determined to be the seventh preset score; the third detection score is determined to be the sum of the sub-detection scores of the W third state parameters.

[0027] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the device also includes: a type determination module, which is used to call the image acquisition device in the vehicle to obtain a facial image of the living creature when there is a living creature in the vehicle; and classify and identify the facial image to determine the type of the living creature.

[0028] In a third aspect, a vehicle is provided, comprising a memory and a processor. The memory is configured to store executable program code, and the processor is configured to retrieve and execute the executable program code from the memory, so that the vehicle executes the method of the first aspect or any possible implementation of the first aspect.

[0029] In a fourth aspect, a computer program product is provided, comprising: a computer program code, which, when executed on a computer, enables the computer to execute the method in the first aspect or any possible implementation of the first aspect.

[0030] In a fifth aspect, a computer-readable storage medium is provided, which stores a computer program code. When the computer program code runs on a computer, the computer executes the method in the above-mentioned first aspect or any possible implementation of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a schematic diagram of a scenario for detecting living things in a vehicle provided by an embodiment of the present application;

[0032] Figure 2 is a schematic flow chart of a method for detecting living things in a vehicle provided by an embodiment of the present application;

[0033] Figure 3 : This is a schematic diagram of a scenario for dividing detection levels corresponding to M state parameters provided in an embodiment of the present application;

[0034] Figure 4 is a schematic flow chart of a method for calculating a first detection score provided in an embodiment of the present application;

[0035] Figure 5 is a schematic flow chart of a method for calculating a second detection score provided in an embodiment of the present application;

[0036] Figure 6 is a schematic flow chart of a method for calculating a third detection score provided in an embodiment of the present application;

[0037] Figure 7 1 is a schematic structural diagram of a device for detecting living things in a vehicle provided by an embodiment of the present application;

[0038] Figure 8 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] The following will clearly and thoroughly describe the technical solutions in this application in conjunction with the accompanying drawings. In the description of the embodiments of this application, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more than two.

[0040] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0041] Before introducing the method of the embodiment of the present application, the application scenario of the embodiment of the present application is first introduced.

[0042] Figure 1 This is a schematic diagram of a scenario for detecting living things in a vehicle provided by an embodiment of the present application.

[0043] For example, Figure 1 As shown, after the user finishes using the vehicle 101 and gets off, in order to ensure the safety of the vehicle 101 and the user's property, the user can control the vehicle 101 to be in a locked state.

[0044] Optionally, the user controls the locking of the vehicle 101 in ways including but not limited to a digital key in a terminal device, a remote control key of the vehicle 101 , a mechanical key, and the like.

[0045] Optionally, types of digital keys include Near Field Communication (NFC) keys, Ultra Wide Band (UWB) keys, and Bluetooth Low Energy (BLE) keys.

[0046] In one possible implementation, if the user is driving the vehicle 101 and there are children or small pets (e.g. Figure 1 Since these creatures are usually small and difficult to spot, they are easily overlooked when the user gets out of the car, resulting in them being forgotten in the car after locking it.

[0047] If a child or small pet is forgotten in a vehicle 101 parked in a high-temperature environment, the temperature inside the vehicle may rise to a high level within a short period of time as the vehicle is parked for an extended period of time. Such high temperatures are difficult for children or pets to withstand, and they may develop skin diseases or, in more serious cases, burns. If the vehicle 101 is parked in a low-temperature environment, the temperature inside the vehicle may gradually drop, potentially causing hypothermia in children or pets. Furthermore, being trapped in a vehicle for an extended period of time can cause psychological fear and anxiety in children or pets.

[0048] To address this issue, related technologies typically install life detection systems in vehicles to detect any living organisms within them. These systems typically include various types of sensors and devices, such as visible light cameras, thermal imaging cameras, millimeter-wave radars, and microphone arrays. Installing these systems requires the installation of additional sensors and devices, increasing both hardware and software costs.

[0049] Based on this, an embodiment of the present application provides a method for detecting living organisms in a vehicle. This method can use the vehicle's own collection equipment to timely detect whether there are living organisms left in the vehicle and alarm without introducing additional hardware equipment, thereby avoiding the safety risks brought about by living organisms left in the vehicle for a long time.

[0050] After introducing the application scenarios of the embodiments of the present application, a method for detecting living things in a vehicle provided by the embodiments of the present application is introduced below.

[0051] Figure 2 This is a schematic flow chart of a method for detecting living things in a vehicle provided by an embodiment of the present application. It should be understood that this method is applied to Figure 1 The scenario shown can be applied to Figure 1 Any electronic control unit (ECU) in the vehicle 101 is shown, and this embodiment of the application does not limit this.

[0052] For example, Figure 2 As shown, the method 200 includes:

[0053] 201. Determine a total detection score of the M state parameters based on M state parameters collected by M acquisition devices of the vehicle, where the state parameters are used to represent the operating state of the vehicle, M is a positive integer greater than 1, and the total detection score is used to represent the probability of the presence of a living organism in the vehicle.

[0054] It should be understood that the method provided in the embodiments of the present application, when detecting the presence of a living organism in a locked vehicle, specifically involves the ECU collecting M state parameters from M acquisition devices within the vehicle, and deriving a total detection score based on these M state parameters to determine whether a living organism is present within the vehicle. The state parameters represent the vehicle's operating state. The total detection score represents the probability of the presence of a living organism within the vehicle. In other words, a higher total detection score indicates a greater probability of the presence of a living organism within the vehicle; a lower total detection score indicates a lower probability of the presence of a living organism within the vehicle.

[0055] Optionally, living organisms include but are not limited to children, pets and other objects with life characteristics.

[0056] Optionally, the M acquisition devices include but are not limited to a slope sensor, an air suspension height sensor, an audio acquisition device, a steering wheel angle sensor, a steering wheel torque sensor, a seat pressure sensor, a window lift switch, an electric interior door handle switch, a wiper switch, and a gear switch in the vehicle.

[0057] In an embodiment of the present application, when the user gets off the vehicle and locks it, the ECU detects that the vehicle is in a locked state, which activates the solution of the embodiment of the present application. The ECU controls the above-mentioned M acquisition devices to be in a detection state to detect whether there are living organisms in the vehicle based on the M state parameters collected by the M acquisition devices.

[0058] When detecting living creatures inside a vehicle, the M data acquisition devices described above have varying degrees of sensitivity. In other words, the movement of a living creature affects the M state parameters to varying degrees. For example, consider a window lift switch. If a living creature remains inside after the vehicle is locked, the creature may attempt to open the window by pressing the switch, causing the switch to change state. Therefore, if the ECU detects a change in the switch, it indicates the presence of a living creature inside the vehicle. If the data acquisition device is a steering wheel angle sensor, after the vehicle is locked, the steering wheel may also experience slight shaking due to external factors, such as parking on an uneven surface or wind. Therefore, detecting a change in the steering wheel angle does not necessarily indicate the presence of a living creature inside the vehicle.

[0059] Based on the degree of influence of living organisms on changes in M ​​state parameters, technicians can pre-set corresponding detection levels for each of the M acquisition devices or M state parameters and store them in the ECU. A higher detection level indicates a greater likelihood that the state parameter change was caused by a living organism; a lower detection level indicates a lower likelihood that the state parameter change was caused by a living organism.

[0060] Figure 3 This is a schematic diagram of a scenario for dividing detection levels corresponding to M state parameters provided in an embodiment of the present application.

[0061] For example, Figure 3 As shown, in the embodiment of the present application, technicians divide the detection levels of M acquisition devices into three types according to different detection levels.

[0062] like Figure 3 As shown in the , there are three detection levels: Detection Level 1, Detection Level 2, and Detection Level 3. Detection Level 1 corresponds to the acquisition devices including the window lift switch, power interior door handle switch, wiper switch, and gear switch. Detection Level 2 corresponds to the acquisition devices including the steering wheel angle sensor, steering wheel torque sensor, and seat pressure sensor. Detection Level 3 corresponds to the acquisition devices including the slope sensor, suspension height sensor, and audio acquisition device. Detection Level 1 is higher than Detection Level 2 and Detection Level 3.

[0063] Correspondingly, among the M state parameters, the state parameters collected by the window lift switch, the state parameters collected by the electric inner door handle switch, the state parameters collected by the wiper switch, and the state parameters collected by the gear switch also correspond to detection level 1; the state parameters collected by the steering wheel angle sensor, the state parameters collected by the steering wheel torque sensor, and the state parameters collected by the seat pressure sensor also correspond to detection level 2; the state parameters collected by the slope sensor, the state parameters collected by the air suspension height sensor, and the state parameters collected by the audio acquisition device correspond to detection level 3.

[0064] Specifically, the state parameters collected by the window lift switch are the window lift switch state, the state parameters collected by the electric interior door handle switch are the electric interior door handle switch state, the state parameters collected by the wiper switch are the wiper switch state, and the state parameters collected by the gear switch are the gear switch state. The window lift switch state can be the state of any window lift switch in the vehicle. The electric interior door handle switch state can be the state of any electric interior door handle switch in the vehicle.

[0065] The state parameter collected by the steering wheel angle sensor is the steering wheel angle, the state parameter collected by the steering wheel torque sensor is the steering wheel torque, and the state parameter collected by the seat pressure sensor is the seat pressure. The seat pressure can be the pressure borne by any seat in the vehicle.

[0066] The state parameter collected by the slope sensor is the slope, the state parameter collected by the free-ride height sensor is the wheel height, and the state parameter collected by the audio collection device (e.g., a microphone) is the volume decibel value. Wheel height refers to the relative distance between the wheel suspension system and the vehicle body, and can be the height of any wheel on the vehicle.

[0067] After the vehicle is locked, the ECU may collect M state parameters through the M collection devices, and calculate a total detection score of the M state parameters based on the M state parameters.

[0068] When calculating the total detection score of M state parameters, the ECU can first obtain the pre-divided detection level of each state parameter, divide the M state parameters based on the detection level, and then calculate a total detection score.

[0069] In one possible implementation, before determining the total detection score of the M state parameters collected by the M collection devices of the vehicle, the method further includes:

[0070] Obtaining a detection level corresponding to each of the M state parameters, where the detection level is used to indicate the degree of influence of living organisms on the state parameters;

[0071] And, determining a total detection score of the M state parameters based on the M state parameters collected by the M collection devices of the vehicle, including:

[0072] Based on the detection level corresponding to each of the M state parameters, the M state parameters are divided into U first state parameters, V second state parameters, and W third state parameters, the detection level of the U first state parameters is higher than the detection level of the V second state parameters, and the detection level of the V second state parameters is higher than the detection level of the W third state parameters;

[0073] A total detection score is determined based on the U first state parameters, the V second state parameters, and the W third state parameters.

[0074] Based on the detection level of each state parameter stored in the ECU, the ECU can obtain the detection level of each state parameter.

[0075] After obtaining M state parameters, the ECU can obtain U first state parameters, V second state parameters, and W third state parameters corresponding to the three detection levels based on the detection level of each state parameter. The detection level of the U first state parameters is higher than the detection level of the V second state parameters, and the detection level of the V second state parameters is higher than the detection level of the W third state parameters.

[0076] For example, Figure 3 As shown, the U first state parameters include the glass lift switch state, the electric inner door handle switch state, the wiper switch state, and the gear switch state.

[0077] The V second state parameters include steering wheel angle, steering wheel torque, and seat pressure.

[0078] The W third state parameters include slope, wheel height, and volume decibel value.

[0079] After dividing the M state parameters into multiple state parameters under different detection levels according to the detection level, the ECU can determine the total detection score based on U first state parameters, V second state parameters and W third state parameters respectively.

[0080] When calculating the total detection score based on multiple status parameters under three different detection levels, the ECU can calculate the detection scores of the multiple status parameters under each detection level respectively based on the multiple status parameters under each detection level, and comprehensively obtain the total detection score.

[0081] In one possible implementation, before determining the total detection score based on the U first state parameters, the V second state parameters, and the W third state parameters, the method further includes:

[0082] Obtaining first weights corresponding to detection levels of U first state parameters, second weights corresponding to detection levels of V second state parameters, and third weights corresponding to detection levels of W third state parameters;

[0083] And, determining a total detection score based on the U first state parameters, the V second state parameters, and the W third state parameters, including:

[0084] Determining a first detection score according to U first state parameters;

[0085] Determining a second detection score according to the V second state parameters;

[0086] Determining a third detection score according to the W third state parameters;

[0087] A total detection score is determined based on the first detection score, the second detection score, the third detection score, the first weight, the second weight, and the third weight.

[0088] It should be understood that since the state parameters at different detection levels have different degrees of influence on the result of determining whether there are living organisms in the vehicle, based on this, in the embodiment of the present application, technicians can pre-set different influencing factors (i.e., weights) for each detection level and store them in the ECU.

[0089] When calculating the detection scores for multiple state parameters at each detection level, the ECU can first obtain the weights corresponding to the different detection levels. In this embodiment of the present application, the weights corresponding to the detection levels of the U first state parameters are referred to as "first weights," the weights corresponding to the detection levels of the V second state parameters are referred to as "second weights," and the weights corresponding to the detection levels of the W third state parameters are referred to as "third weights."

[0090] Optionally, the first weight may be 0.5, the second weight may be 0.3, and the third weight may be 0.2.

[0091] After obtaining the weights corresponding to the three detection levels, the ECU can calculate the first detection score using U first state parameters, the second detection score using V second state parameters, and the third detection score using W third state parameters. Finally, the total detection score is calculated using the first detection score, the first weight, the second detection score, the second weight, the third detection score, and the third weight.

[0092] Specifically, the calculation formula of the total detection score is shown in the following formula (1).

[0093] λ=μ1·A+μ2·B+μ3·C Formula (1)

[0094] Wherein, in formula (1):

[0095] λ: total detection score;

[0096] μ1: first weight;

[0097] A: first detection score;

[0098] μ2: second weight;

[0099] B: first probe score;

[0100] μ3: third weight;

[0101] C: Third probe score.

[0102] The calculation process of each detection score is introduced one by one below.

[0103] (1) Calculation process of the first detection score

[0104] It should be understood that in the embodiment of the present application, each of the M state parameters corresponds to an alarm signal flag. The alarm signal flag is used to indicate whether a living organism is present in the vehicle. When the state parameter meets the corresponding alarm condition, the ECU will set the alarm signal flag of the state parameter to "true"; conversely, when the state parameter does not meet the corresponding alarm condition, the ECU will set the alarm signal flag of the state parameter to "false".

[0105] The highest detection level for the U first-state parameters indicates that changes in the first-state parameters are most likely to trigger a living being in the vehicle. Therefore, for any of the U first-state parameters, as long as the ECU detects that the first-state parameter meets the corresponding alarm condition, it assumes that there is a high probability of a living being in the vehicle and sets the alarm signal flag for the first-state parameter to "true," indicating a high probability of a living being in the vehicle. Conversely, if the ECU fails to detect that the first-state parameter meets the alarm condition, it assumes that there is no living being in the vehicle and sets the alarm signal flag for the first-state parameter to "false."

[0106] Based on the alarm signal flag's setting or the ECU's determination, the ECU determines a sub-detection score for the first state parameter. Different determinations or setting results result in different sub-detection scores for the first state parameter. By calculating the sub-detection score for each first state parameter, the ECU can obtain the first detection scores for all U first state parameters.

[0107] In one possible implementation, determining the first detection score according to the U first state parameters includes:

[0108] For any first state parameter among the U first state parameters, obtaining a first preset condition corresponding to the first state parameter;

[0109] determining whether the first state parameter satisfies a first preset condition;

[0110] When the first state parameter satisfies the first preset condition, determining the sub-detection score of the first state parameter to be a second preset score;

[0111] When the first state parameter does not satisfy the first preset condition, determining that the sub-detection score of the first state parameter is a third preset score, and the second preset score is greater than the third preset score;

[0112] The first detection score is determined as the sum of the sub-detection scores of the U first state parameters.

[0113] For any of the first state parameters, the ECU can determine its corresponding alarm condition as a "first preset condition." When the ECU determines that the first state parameter satisfies the first preset condition, it sets the alarm signal flag for the first state parameter to "true" and determines the sub-detection score of the first state parameter to be the second preset score. Conversely, when the first state parameter does not meet the first preset condition, the ECU can set the alarm signal flag for the first state parameter to "false" and determine the sub-detection score of the first state parameter to be the third preset score. The second preset score is greater than the third preset score.

[0114] Optionally, since the state parameters of different detection levels have different degrees of influence on the final judgment result. In the embodiment of the present application, the state parameters of different detection levels can be preset. When the alarm signal flag is in the position of "true", the corresponding sub-detection scores are different. Specifically, the higher the detection level, the higher the sub-detection score of the state parameter. Since the state parameters of different detection levels, when the alarm signal flag is in the position of "false", indicate that there are no living creatures in the car, the sub-detection scores of the state parameters of different detection levels in this case can be set to the same. Optionally, the second preset score can be 3 points, and the third preset score can be 0 points.

[0115] Alternatively, the embodiment of the present application may also preset state parameters for different detection levels, and when the alarm flag is set to "true", the corresponding sub-detection scores are the same. Optionally, the second preset score may be 1 point, and the third preset score may be 0 point.

[0116] Exemplarily, in an embodiment of the present application, the U first state parameters include a glass lift switch state, an electric interior door handle switch state, a wiper switch state, and a gear switch state.

[0117] When the first state parameters are different, the corresponding first preset conditions are also different.

[0118] Specifically, when any first state parameter is a glass lift switch state, the first preset condition corresponding to the first state parameter is: the glass lift switch state has changed. A change in the glass lift switch state means that the current glass lift switch state is different from the previous glass lift switch state. When any first state parameter is a power interior door handle switch state, the first preset condition corresponding to the first state parameter is: the power interior door handle switch state has changed. When any first state parameter is a wiper switch state, the first preset condition corresponding to the first state parameter is: the wiper switch state has changed. When any first state parameter is a gear switch state, the first preset condition corresponding to the first state parameter is: the gear switch state has changed.

[0119] Based on the difference in the first state parameter, when the ECU determines whether the first state parameter meets the first preset condition, the specific process is as follows.

[0120] In one possible implementation, determining whether the first state parameter satisfies a first preset condition includes:

[0121] When the first state parameter is the state of the glass lift switch, if the state of the glass lift switch changes, it is determined that the first state parameter meets the first preset condition; if the state of the glass lift switch does not change, it is determined that the first state parameter does not meet the first preset condition;

[0122] When the first state parameter is the switch state of the electric inner door handle, if the switch state of the electric inner door handle changes, it is determined that the first state parameter meets the first preset condition; if the switch state of the electric inner door handle does not change, it is determined that the first state parameter does not meet the first preset condition;

[0123] When the first state parameter is the wiper switch state, if the wiper switch state changes, it is determined that the first state parameter meets the first preset condition; if the wiper switch state does not change, it is determined that the first state parameter does not meet the first preset condition;

[0124] When the first state parameter is the shift switch state, if the shift switch state changes, it is determined that the first state parameter meets the first preset condition; if the shift switch state does not change, it is determined that the first state parameter does not meet the first preset condition.

[0125] For any first state parameter, the ECU can determine whether the first state parameter meets its corresponding first preset condition by detecting whether the first state parameter changes, and obtain a sub-detection score of the first state parameter based on the judgment result.

[0126] By calculating the sub-detection score of each first state parameter and summing them up, the first detection scores corresponding to the U first state parameters can be obtained.

[0127] In order to facilitate the understanding of the calculation process of the first detection score, the following Figure 4 The above calculation process is introduced in detail.

[0128] Figure 4 This is a schematic flowchart of a method for calculating a first detection score provided in an embodiment of the present application.

[0129] For example, Figure 4 As shown, the method 400 includes:

[0130] 401. For any first state parameter among U first state parameters, obtain a first preset condition corresponding to the first state parameter.

[0131] When the first state parameter is the glass lift switch state, execute 402;

[0132] When the first state parameter is the switch state of the electric interior door handle, execute 403;

[0133] When the first state parameter is the wiper switch state, execute 404;

[0134] When the first state parameter is the shift switch state, execute 405 .

[0135] 402 , determine whether the state of the window lift switch has changed.

[0136] When the state of the glass lift switch changes, execute 406;

[0137] When the state of the glass lift switch has not changed, execute 407 .

[0138] 403, determine whether the switch state of the electric interior door handle has changed.

[0139] When the state of the electric interior door handle switch changes, execute 406;

[0140] When the switch state of the electric inner door handle has not changed, execute 407 .

[0141] 404 , determine whether the wiper switch state has changed.

[0142] When the wiper switch state changes, execute 406;

[0143] When the wiper switch state has not changed, execute 407 .

[0144] 405 , determining whether the state of the shift switch has changed.

[0145] When the state of the shift switch changes, execute 406;

[0146] When the state of the shift switch has not changed, execute 407 .

[0147] 406 : Determine the sub-detection score of the first state parameter as a second preset score.

[0148] 407 : Determine the sub-detection score of the first state parameter as a third preset score.

[0149] 408 : Determine the first detection score as the sum of the sub-detection scores of the U first state parameters.

[0150] The above method 400 and the process of determining the first detection score in method 200 belong to the same inventive concept. For details, please refer to the introduction of method 200 and will not be repeated here.

[0151] Therefore, through the above steps, the ECU can obtain the first detection scores of U first state parameters.

[0152] In the above technical solution, since the first state parameter is a state parameter that is highly sensitive to the activities of living organisms in the vehicle, changes in this type of state parameter are usually caused by living organisms rather than external environmental factors. Therefore, when this type of state parameter changes, it indicates that the probability of the presence of living organisms in the vehicle is extremely high. Based on this, when determining the first detection score of this type of state parameter, the vehicle can ignore the influence of the external environment and directly perform a cumulative score on the first state parameter based on whether the first state parameter meets its corresponding first preset condition to obtain the first detection score of the U first state parameters with the highest detection level. The above process simplifies the scoring logic for state parameters with high detection levels and quickly and accurately assesses the probability of the presence of living organisms in the vehicle.

[0153] (2) Calculation process of the second detection score

[0154] It should be understood that the detection levels of the V second state parameters are lower than the detection levels of the U first state parameters. Therefore, when any of the V second state parameters changes, it is not necessarily caused by the activity of a living organism within the vehicle. In this case, to ensure the accuracy of the judgment result, the ECU needs to consider other conditions when making a judgment.

[0155] In one possible implementation, determining the second detection score according to the V second state parameters includes:

[0156] For any second state parameter among the V second state parameters, obtaining a second preset condition corresponding to the second state parameter;

[0157] determining whether the second state parameter satisfies a second preset condition;

[0158] When the second state parameter satisfies the second preset condition, obtaining the trigger state and acceleration of the blind spot alarm signal of the vehicle, where the trigger state is used to indicate whether there is an abnormality in the blind spot of the vehicle;

[0159] When the trigger state is not triggered and the acceleration is less than or equal to the preset acceleration, the sub-detection score of the second state parameter is determined to be the fourth preset score; when the trigger state is triggered, or the acceleration is greater than the preset acceleration, the sub-detection score of the second state parameter is determined to be the fifth preset score, and the fourth preset score is greater than the fifth preset score;

[0160] If the second state parameter does not satisfy the second preset condition, determining the sub-detection score of the second state parameter to be a fifth preset score;

[0161] The second detection score is determined as the sum of the sub-detection scores of the V second state parameters.

[0162] For any one of the second state parameters, the ECU can determine its corresponding alarm condition as the "second preset condition". The difference from the first state parameter is that the second state parameter provided in the embodiment of the present application, such as steering wheel angle, steering wheel torque and seat pressure. When the second state parameter changes, it is not necessarily caused by the activity of living organisms in the car, but may also be caused by external factors. For example, when a large vehicle passes by outside the car, the influence of airflow and wind will cause the steering wheel angle and steering wheel torque to change, causing the steering wheel to rotate. In addition, the vibration generated by the passage of a large vehicle may also be transmitted to the pressure sensor, causing the seat pressure to change.

[0163] Therefore, when the ECU determines that the second state parameter meets the second preset condition, the change in the second state parameter may be caused by other factors, which does not indicate a high probability of the presence of living organisms in the vehicle. In this case, the ECU still needs to consider the influence of external factors.

[0164] Specifically, when the ECU determines that the second state parameter meets the second preset condition, it can further determine whether the current change in the second state parameter is caused by external factors by obtaining the triggering state and acceleration of the vehicle's blind spot alarm signal.

[0165] Blind Spot Monitoring (BSM) is a safety feature that detects other vehicles in the blind spots behind the vehicle and warns the driver when potential danger is detected. This feature relies primarily on radar sensors, ultrasonic sensors, and cameras within the vehicle.

[0166] The triggering status of the blind spot alarm signal is used to indicate whether there is an abnormality in the blind spot of the vehicle, that is, the status of the blind spot alarm signal flag.

[0167] When the vehicle's blind spot alarm system determines through the various acquisition devices mentioned above that there are other vehicles in the blind spots on both sides of the rear of the vehicle, the triggering status of the blind spot alarm signal will be configured as "triggered", which is equivalent to the blind spot alarm signal flag being set to "true"; on the contrary, when the blind spot alarm system determines through the various acquisition devices mentioned above that there are no other vehicles in the blind spots on both sides of the rear of the vehicle, the violation status of the blind spot alarm signal will be configured as "not triggered", which is equivalent to the blind spot alarm signal flag being set to "false".

[0168] Based on this, the ECU can obtain the triggering status of the blind spot alarm signal through the blind spot alarm system and obtain the current acceleration of the vehicle through the acceleration sensor.

[0169] It should be understood that the blind spot warning signal can indicate the presence of other vehicles behind or on either side of the vehicle. When other vehicles pass by the side of the vehicle, they generate airflow during their travel. Strong airflow can cause the vehicle to move slightly, resulting in changes in its acceleration. Therefore, when the second state parameter changes, the blind spot warning signal and acceleration can be used to determine whether the change in the second state parameter is due to external factors.

[0170] In the embodiment of the present application, the technician can set a preset acceleration in advance according to the change of the vehicle's acceleration when the second state parameter changes, and compare the acquired acceleration with the preset acceleration. Optionally, the preset acceleration can be 4m / s 2 .

[0171] When the vehicle's blind spot warning signal is in the "not triggered" state, indicating that there are no other vehicles passing on either side of the vehicle; and when the acceleration is less than or equal to the preset acceleration, indicating that the vehicle is not moving or its movement is within the permitted range, these results indicate that the change in the second state parameter is not due to external factors but rather to biological activity within the vehicle. Therefore, the ECU may set the warning signal flag for the second state parameter to "true" and determine the sub-detection score for the second state parameter to the fourth preset score. Conversely, when the trigger state is "triggered" or the acceleration is greater than the preset acceleration, indicating that the change in the second state parameter may be due to external factors, the ECU may set the warning signal flag for the second state parameter to "false." Alternatively, when the ECU determines that the second state parameter does not meet the second preset condition, it sets the warning signal flag for the second state parameter to "false." In both cases, when the warning signal flag for the second state parameter is set to "false," the ECU determines the sub-detection score for the second state parameter to be the fifth preset score. The fourth preset score is greater than the fifth preset score.

[0172] Optionally, in one case, if the status parameters of different detection levels have different corresponding sub-detection scores when the alarm signal flag is set to "true," the fourth preset score may be 2, and the fifth preset score may be 0. If the status parameters of different detection levels have the same corresponding sub-detection scores when the alarm flag is set to "true," the fourth preset score may be 1, and the fifth preset score may be 0.

[0173] Exemplarily, in an embodiment of the present application, the V second state parameters include steering wheel angle, steering wheel torque, and seat pressure.

[0174] When the second state parameter is different, the corresponding second preset condition is also different.

[0175] Specifically, when any second state parameter is a steering wheel angle, the second preset condition corresponding to the second state parameter is: the difference between the steering wheel angle and the steering wheel angle at a previous moment is greater than the preset angle. When any second state parameter is a steering wheel torque, the second preset condition corresponding to the second state parameter is: the steering wheel torque is greater than the preset torque. When any second state parameter is seat pressure, the second preset condition corresponding to the second state parameter is: the difference between the seat pressure and the seat pressure at a previous moment is greater than the preset pressure.

[0176] Optionally, the preset steering angle can be the steering wheel's normal steering angle change due to external environmental factors, and the preset steering angle can be 10°. The preset torque can be the steering wheel's normal steering torque due to external environmental factors, and the preset torque can be 4 N˙m. The preset pressure can be the minimum pressure change in the seat when an object is seated, and the preset pressure can be 50 N.

[0177] Based on the difference in the second state parameter, when the ECU determines whether the second state parameter meets the second preset condition, the specific process is as follows.

[0178] In one possible implementation, determining whether the second state parameter satisfies a second preset condition includes:

[0179] When the second state parameter is a steering wheel angle, if the angle difference is greater than a preset angle, it is determined that the second state parameter meets the second preset condition; if the angle difference is less than or equal to the preset angle, it is determined that the second state parameter does not meet the second preset condition;

[0180] When the second state parameter is a steering wheel torque, if the steering wheel torque is greater than a preset torque, it is determined that the second state parameter meets the second preset condition; if the steering wheel torque is less than or equal to the preset torque, it is determined that the second state parameter does not meet the second preset condition;

[0181] When the second state parameter is the seat pressure, if the pressure difference is greater than the preset pressure, it is determined that the second state parameter meets the second preset condition; if the pressure difference is less than or equal to the preset pressure, it is determined that the second state parameter does not meet the second preset condition.

[0182] Based on this, for any second state parameter, the ECU can determine whether the second state parameter meets its corresponding second preset condition, and obtain the sub-detection score of each second state parameter based on the judgment result, combined with the trigger state and acceleration of the blind spot alarm signal.

[0183] By calculating the sub-detection score of each second state parameter and summing them up, the second detection scores corresponding to the V second state parameters can be obtained.

[0184] It should be understood that, since both the steering wheel angle and the steering wheel torque are parameters reflecting the state of the steering wheel, the above-mentioned V second state parameters may also select only one of the steering wheel angle and the steering wheel torque.

[0185] In order to facilitate the understanding of the calculation process of the second detection score, the following Figure 5 The above calculation process is introduced in detail.

[0186] Figure 5This is a schematic flowchart of a method for calculating a second detection score provided in an embodiment of the present application.

[0187] For example, Figure 5 As shown, the method 500 includes:

[0188] 501. For any second state parameter among V second state parameters, obtain a second preset condition corresponding to the second state parameter.

[0189] When the second state parameter is the steering wheel angle, execute 502;

[0190] When the second state parameter is the steering wheel torque, execute 503;

[0191] When the second state parameter is the seat pressure, execute 504 .

[0192] 502, determining whether the angle difference is greater than a preset angle.

[0193] When the angle difference is less than or equal to the preset angle, execute 505;

[0194] When the angle difference is greater than the preset angle, execute 506.

[0195] 503 , determining whether the steering wheel torque is greater than a preset torque.

[0196] When the steering wheel torque is less than or equal to the preset torque, execute 505;

[0197] When the steering wheel torque is greater than the preset torque, execute 506 .

[0198] 504 , determining whether the pressure difference is greater than a preset difference.

[0199] When the pressure difference is less than or equal to the preset difference, execute 505;

[0200] When the pressure difference is greater than the preset difference, execute 506.

[0201] 505 , determining the sub-detection score of the second state parameter to be a fifth preset score.

[0202] 506 , obtaining the triggering state and acceleration of the blind spot warning signal.

[0203] 507 , when the trigger state of the blind spot warning signal is not triggered and the acceleration is less than or equal to the preset acceleration, determine the sub-detection score of the second state parameter to be a fourth preset score.

[0204] 508 , when the triggering state of the blind spot warning signal is triggered, or the acceleration is greater than the preset acceleration, return to 505 .

[0205] 509 , determining the second detection score as the sum of the sub-detection scores of the V second state parameters.

[0206] The above method 500 and the process of determining the second detection score in method 200 belong to the same inventive concept. For details, please refer to the introduction of method 200 and will not be repeated here.

[0207] Therefore, through the above steps, the ECU can obtain the second detection scores of V second state parameters.

[0208] In the above technical solution, the detection levels corresponding to the V second state parameters are slightly lower than those corresponding to the U first state parameters. Changes in these state parameters are not solely due to biological activity within the vehicle but may also be due to external factors. Therefore, when determining the second detection score for these state parameters, even if the state parameters meet the corresponding preset conditions, it is necessary to verify whether the state parameter changes are caused by external factors through the vehicle's blind spot warning signal and acceleration. This ensures accurate perception of the surrounding environment, avoids misjudgments due to external interference, and enhances the stability and reliability of the scoring process.

[0209] (3) Calculation process of the third detection score

[0210] It should be understood that the detection levels of the W third state parameters are lower than the detection levels of the V second state parameters. Therefore, when any of the W second state parameters changes, it is not necessarily due to the activity of a living organism within the vehicle. In this case, similar to the second state parameters, to ensure the accuracy of the judgment result, the ECU needs to consider other conditions.

[0211] In one possible implementation, determining the third detection score according to the W second state parameters includes:

[0212] For any third state parameter among the W third state parameters, obtaining a third preset condition corresponding to the third state parameter;

[0213] determining whether the third state parameter satisfies a third preset condition;

[0214] When the third state parameter meets the third preset condition, the trigger state and acceleration of the vehicle's blind spot alarm signal are obtained. The trigger state is used to indicate whether there is an abnormality in the vehicle's blind spot.

[0215] When the duration that the third state parameter satisfies the third preset condition is greater than the preset duration, and the trigger states are all untriggered within the preset duration, and the accelerations are all less than or equal to the preset accelerations within the preset duration, the sub-detection score of the third state parameter is determined to be the sixth preset score; when the duration that the third state parameter satisfies the third preset condition is less than or equal to the preset duration, or, not all trigger states are untriggered within the preset duration, or, not all accelerations are less than or equal to the preset acceleration within the preset duration, the sub-detection score of the third state parameter is determined to be the seventh preset score, and the sixth preset score is greater than the seventh preset score;

[0216] If the third state parameter does not satisfy the third preset condition, determining the sub-detection score of the third state parameter to be a seventh preset score;

[0217] The third detection score is determined as the sum of the sub-detection scores of the W third state parameters.

[0218] For any one of the third state parameters, the ECU can determine its corresponding alarm condition as the "third preset condition". For the third state parameters provided in the embodiment of the present application, for example, slope, wheel height and sound decibel value. When the second state parameter changes, it is not necessarily caused by the activity of living organisms in the car, but may also be caused by external factors or the vehicle itself. For example, in combination with the above description, when a large vehicle passes by outside the car, for vehicles with poor sound insulation, the sound will be transmitted to the car, causing the decibel value of the sound inside the car to rise. For another example, when the vehicle is parked in a bumpy place, it may move slightly, causing the slope to change.

[0219] Furthermore, if the state parameter changes are caused by the vehicle's own state, the duration is relatively short. If the state parameter changes are caused by living organisms inside the vehicle, when a child or pet is left inside the vehicle, due to panic, the child or pet may continue to move around inside the vehicle for a long time in an attempt to attract the attention of pedestrians outside the vehicle and seek help.

[0220] The technician can pre-set the critical time required for the third state parameter to change due to the vehicle's own state, and store it in the ECU as a preset time. Optionally, the preset time is 30 seconds.

[0221] Therefore, when the ECU determines that the third state parameter meets the third preset condition, the change in the third state parameter may be caused by other factors and does not indicate a high probability of the presence of living organisms in the vehicle. In this case, the ECU also needs to consider the influence of external factors and the vehicle's own state.

[0222] Because the detection level of the third state parameter is lower than that of the second state parameter, the probability of false alarms is higher. When the ECU determines that the third state parameter meets the third preset condition, it first determines whether the change in the third state parameter is caused by external factors or the vehicle's internal state by obtaining the trigger state and acceleration of the blind spot warning signal, as well as the duration of the change.

[0223] If the third state parameter meets the third preset condition for a duration greater than the preset duration, and the trigger state remains untriggered for the preset duration, it indicates that there are no other vehicles passing on either side of the vehicle, and the acceleration remains less than or equal to the preset acceleration for the preset duration, indicating that the vehicle has not moved or that the vehicle's movement range is within the permitted range of the state parameter change. Therefore, this result indicates that the change in the third state parameter is neither due to external factors nor to internal vehicle factors. Therefore, the ECU may set the alarm signal flag for the third state parameter to "true" and determine the sub-detection score for the third state parameter to the sixth preset score. Conversely, if the third state parameter meets the third preset condition for a duration less than or equal to the preset duration, or if the trigger state remains untriggered for the preset duration, or if the acceleration remains less than or equal to the preset acceleration for the preset duration, it indicates that the change in the third state parameter may be due to external factors or a change in the vehicle's internal state. The ECU may set the alarm signal flag for the third state parameter to "false." Alternatively, if the ECU determines that the third state parameter does not meet the third preset condition, it may set the alarm signal flag for the third state parameter to "false." In the above two cases, when the warning signal flag of the third state parameter is set to "false", the ECU determines that the sub-detection score of the third state parameter is the seventh preset score, wherein the sixth preset score is greater than the seventh preset score.

[0224] Optionally, in one case, when the alarm signal flag is set to "true" for status parameters of different detection levels, and the corresponding sub-detection scores are different, the sixth preset score may be 1, and the seventh preset score may be 0. When the alarm flag is set to "true" for status parameters of different detection levels, and the corresponding sub-detection scores are the same, the sixth preset score may be 1, and the seventh preset score may be 0.

[0225] Exemplarily, in the embodiment of the present application, the W third state parameters include slope, wheel height, and volume decibel value.

[0226] When the third state parameter is different, the corresponding third preset condition is also different.

[0227] Specifically, when any third state parameter is slope, the third preset condition corresponding to the third state parameter is that the slope change frequency is within a preset frequency range. The slope change frequency refers to the rate at which slope changes occur over time, that is, the number of slope changes per unit time, measured in Hz.

[0228] In the embodiment of the present application, a technician may pre-set a frequency range for identifying a slope change that may be caused by movement of a living body in the vehicle as a preset frequency range. Optionally, the preset frequency range may be 1-10 Hz.

[0229] The ECU can collect the slope at multiple consecutive moments, perform first-order filtering on the slope signal to remove high-frequency noise and other unnecessary interference, and use the remaining slope signal to calculate the slope change frequency.

[0230] When any of the third state parameters is wheel height, the third preset condition corresponding to the third state parameter is: the difference between the wheel height and the wheel height at the previous moment is greater than a preset height. When any of the third state parameters is volume decibel value, the third preset condition corresponding to the third state parameter is: the volume decibel value is greater than a preset decibel value.

[0231] The preset height can be a critical change in wheel height when a living organism is present in the vehicle. Optionally, the preset height can be 5 mm. The preset decibel level is a critical decibel level for the volume inside the vehicle when a living organism is present in the vehicle. The preset decibel level can be 70 dB.

[0232] Based on the difference in the third state parameter, when the ECU determines whether the third state parameter meets the third preset condition, the specific process is as follows.

[0233] In one possible implementation, determining whether the third state parameter satisfies a third preset condition includes:

[0234] When any of the third state parameters is a slope, if the slope change frequency is within a preset frequency range, it is determined that the third state parameter meets the third preset condition; if the slope change frequency is not within the preset frequency range, it is determined that the third state parameter does not meet the third preset condition;

[0235] When any of the third state parameters is the wheel height, if the height difference is greater than the preset height, it is determined that the third state parameter meets the third preset condition; if the height difference is less than or equal to the preset height, it is determined that the third state parameter does not meet the third preset condition;

[0236] When any third state parameter is a volume decibel value, if the volume decibel value is greater than the preset decibel, it is determined that the third state parameter meets the third preset condition; if the volume decibel value is less than or equal to the preset decibel, it is determined that the third state parameter does not meet the third preset condition.

[0237] Based on this, for any third state parameter, the ECU can determine whether the third state parameter meets its corresponding third preset condition, and determine the sub-detection score of the third state parameter based on the change duration of the third state parameter, as well as the trigger state and acceleration of the blind spot alarm signal.

[0238] By calculating the sub-detection score of each third state parameter and summing them up, the third detection scores corresponding to the W third state parameters can be obtained.

[0239] In order to facilitate the understanding of the calculation process of the third detection score, the following Figure 6 The above calculation process is introduced in detail.

[0240] Figure 6 This is a schematic flowchart of a method for calculating a third detection score provided in an embodiment of the present application.

[0241] For example, Figure 6 As shown, the method 600 includes:

[0242] 601. For any third state parameter among the W third state parameters, obtain a third preset condition corresponding to the third state parameter.

[0243] When the third state parameter is the slope, execute 602;

[0244] When the third state parameter is the wheel height, execute 603;

[0245] When the third state parameter is the sound decibel value, execute 604.

[0246] 602 , determining whether the slope change frequency is within a preset frequency range.

[0247] When the slope change frequency is not within the preset frequency range, execute 605;

[0248] When the slope change frequency is within the preset frequency range, execute 606 .

[0249] 603 , determining whether the height difference of the wheels is greater than a preset height.

[0250] When the height difference of the wheels is less than or equal to the preset height, execute 605;

[0251] When the height difference of the wheels is greater than the preset height, execute 606.

[0252] 604, determine whether the sound decibel is greater than a preset decibel.

[0253] When the sound decibel is less than or equal to the preset decibel, execute 605;

[0254] When the pressure difference is greater than the preset decibel, execute 606.

[0255] 605 : Determine the sub-detection score of the third state parameter as a sixth preset score.

[0256] 606 , obtaining the triggering state and acceleration of the blind spot warning signal.

[0257] 607. Within the preset time period, if the third state parameter continuously satisfies the third preset condition and the trigger states are all untriggered and the accelerations are all less than or equal to the preset acceleration, determine that the sub-detection score of the third state parameter is the sixth preset score.

[0258] 608. If the third state parameter does not continuously meet the third preset condition within the preset time period, or the trigger state is not entirely triggered, or the acceleration is not entirely less than or equal to the preset acceleration, return to 605.

[0259] 609 : Determine the third detection score as the sum of the sub-detection scores of the W third state parameters.

[0260] The above method 600 and the process of determining the third detection score in method 200 belong to the same inventive concept. For details, please refer to the introduction of method 200 and will not be repeated here.

[0261] Therefore, through the above steps, the ECU can obtain the third detection scores of W third state parameters.

[0262] In the above technical solution, the detection level corresponding to the W third state parameters is slightly lower than the detection level of the V second state parameters. Compared with the second state parameters, the change of this type of state parameters is not entirely caused by the activity of living organisms in the vehicle, but may also be caused by external factors or changes in the vehicle's own state (for example, a vehicle parked on an uneven road will cause a small shake). In general, if the change occurs in the vehicle's own state, the duration is relatively short. Therefore, when determining the third detection score of this type of state parameter, when the state parameter meets the corresponding preset conditions, it is also necessary to use the vehicle's blind spot alarm signal and acceleration to check whether the change in the state parameter is caused by external factors. When the change in the state parameter is not caused by external factors, it is necessary to further determine whether the current change is caused by the change in the vehicle's own state through the duration of the change. Therefore, for the state parameters with lower detection levels and lower sensitivity, all external factors that may cause false alarms can be excluded when determining the detection score, thereby enhancing the stability and reliability of the score determination process.

[0263] After respectively obtaining the first detection score, the second detection score, and the third detection score, the ECU may calculate the sum of the first detection score, the second detection score, and the third detection score to obtain a total detection score.

[0264] 202, based on the total detection score, determine whether there are living organisms in the vehicle.

[0265] Specifically, the ECU may compare the total detection score with a first preset score to determine whether there is a living creature in the vehicle. The first preset score is a detection score threshold value preset by a technician for when a living creature is present in the vehicle.

[0266] In one possible implementation, determining whether there are living organisms in the vehicle based on the total detection score includes:

[0267] When the total detection score is greater than or equal to a first preset score, determining that a living organism exists in the vehicle;

[0268] When the total detection score is less than the first preset score, it is determined that no living creature exists in the vehicle.

[0269] Optionally, in combination with the above-mentioned determination of the total detection score, the status parameters of different detection levels, when the alarm signal flag is set to "true", whether the corresponding sub-detection scores are the same, the values ​​of the first preset scores can be set to be different.

[0270] For example, in one case, when the status parameters of different detection levels are different and the alarm signal flag is set to "true", the corresponding sub-detection scores are different. Combined with the above statement, it can be seen that the second preset score is 3 points, the fourth preset score is 2 points, and the sixth preset score is 1 point, then the first preset score can be 18 points.

[0271] If the ECU calculates the total detection score using this scoring method, the ECU may compare the calculated total detection score with the first preset score. If the total detection score is greater than or equal to the first preset score, the ECU determines that a living organism is present in the vehicle. If the total detection score is less than the first preset score, the ECU determines that no living organism is present in the vehicle.

[0272] When the status parameters of different detection levels, when the alarm signal flag is in the "true" position, the corresponding sub-detection scores are the same, combined with the above statement, it can be seen that the second preset score is 1 point, the fourth preset score is 1 point, and the sixth preset score is 1 point, then the first preset score can be 8 points.

[0273] Similarly, if the ECU calculates the total detection score using this scoring method, the ECU may compare the calculated total detection score with the first preset score. If the total detection score is greater than or equal to the first preset score, the ECU determines that a living organism is present in the vehicle. If the total detection score is less than the first preset score, the ECU determines that no living organism is present in the vehicle.

[0274] 203 , when there is a living organism in the vehicle, generating target alarm information according to the location of the vehicle and the type of the living organism.

[0275] Based on 202 , if the ECU determines that there is a living organism in the vehicle, it can further identify the type of the living organism in the vehicle so as to prompt the user to handle it in a timely manner.

[0276] In one possible implementation, the method further includes:

[0277] In the case where there is a living creature in the vehicle, calling an image acquisition device in the vehicle to obtain a facial image of the living creature;

[0278] Classify and recognize facial images to determine the type of living organism.

[0279] When there is a living creature in the car, the ECU can call the image acquisition device in the car (for example, the camera in the car) to obtain the facial image of the living creature in the car, and use the image recognition algorithm to extract the image features of the facial image, perform classification and recognition based on the image features, and obtain the type of the current living creature.

[0280] Furthermore, the ECU may obtain the current location of the vehicle through a positioning device in the vehicle (eg, Global Positioning System, GPS) and generate target alarm information according to the location and the type of living organism.

[0281] The ECU can send target alarm information to the user's terminal device through the vehicle's telematics box (T-box) to remind the user to handle it in time.

[0282] In the above technical solution, when the vehicle determines that there are living organisms in the vehicle, it can further use image recognition algorithms to identify the type of forgotten objects in the vehicle, thereby generating target alarm information, allowing users to take corresponding treatment measures more quickly.

[0283] In summary, after a vehicle is locked, to prevent children or pets from being left behind, this application proposes a method for detecting living organisms inside a vehicle. Specifically, the vehicle can determine a total detection score based on M status parameters collected by its own M acquisition devices. The total detection score can represent the probability of the presence of a living organism inside the vehicle. In other words, the higher the total detection score, the greater the probability of the presence of a living organism inside the vehicle. The lower the total detection score, the lower the probability of the presence of a living organism inside the vehicle. Furthermore, the vehicle uses the specific value of the total detection score to determine whether a living organism is inside the vehicle. If so, a targeted alarm message is generated based on the vehicle's location and the type of living organism. In the above implementation process, the vehicle can rely on its own sensors to detect the presence of living organisms inside the vehicle, without the need for additional detection equipment, thereby reducing the vehicle's hardware and software costs and enabling timely detection of whether a living organism has been left behind inside the vehicle. In addition, by performing detection based on data collected by multiple acquisition devices in the vehicle, a more comprehensive assessment of the vehicle's in-vehicle environment can be achieved, avoiding false alarms caused by a single parameter. When there are living creatures in the car, the vehicle will sound an alarm based on the location and type of the living creature, allowing people outside the car and users to discover and deal with it in time, avoiding safety hazards caused by living creatures being left in the car for a long time.

[0284] Figure 7 Schematic diagram of the structure of a device for detecting living things in a vehicle provided in an embodiment of the present application.

[0285] For example, Figure 7 As shown, the apparatus 700 includes:

[0286] Score determination module 701, configured to determine a total detection score for M state parameters collected by M acquisition devices of the vehicle, where the state parameters represent the operating state of the vehicle, M is a positive integer greater than 1, and the total detection score represents the probability of the presence of a living organism within the vehicle;

[0287] A biological detection module 702 is used to determine whether there is a living organism in the vehicle based on the total detection score;

[0288] The alarm module 703 is configured to generate target alarm information according to the location of the vehicle and the type of the living creature when there is a living creature in the vehicle.

[0289] In one possible implementation, before determining the total detection score of the M state parameters collected by the M collection devices of the vehicle, the score determination module 701 is further used to: obtain the detection level corresponding to each of the M state parameters, where the detection level is used to indicate the degree of influence of the living organism on the state parameter; and the score determination module 701 is specifically used to: based on the detection level corresponding to each of the M state parameters, divide the M state parameters into U first state parameters, V second state parameters, and W third state parameters, the detection level of the U first state parameters being higher than the detection level of the V second state parameters, and the detection level of the V second state parameters being higher than the detection level of the W third state parameters; and determine the total detection score based on the U first state parameters, the V second state parameters, and the W third state parameters.

[0290] In one possible implementation, the biological detection module 702 is further configured to: determine that there is a living organism in the vehicle when the total detection score is greater than or equal to a first preset score; and determine that there is no living organism in the vehicle when the total detection score is less than the first preset score.

[0291] In one possible implementation, before determining the total detection score based on the U first state parameters, the V second state parameters and the W third state parameters, the score determination module 701 is further used to: obtain the first weight corresponding to the detection level of the U first state parameters, the second weight corresponding to the detection level of the V second state parameters, and the third weight corresponding to the detection level of the W third state parameters; and, the score determination module 701 is further used to: determine the first detection score based on the U first state parameters; determine the second detection score based on the V second state parameters; determine the third detection score based on the W third state parameters; and determine the total detection score based on the first detection score, the second detection score, the third detection score, the first weight, the second weight and the third weight.

[0292] In one possible implementation, the score determination module 701 is also used to: for any first state parameter among the U first state parameters, obtain the first preset condition corresponding to the first state parameter; determine whether the first state parameter meets the first preset condition; if the first state parameter meets the first preset condition, determine the sub-detection score of the first state parameter to be the second preset score; if the first state parameter does not meet the first preset condition, determine the sub-detection score of the first state parameter to be the third preset score, and the second preset score is greater than the third preset score; determine the first detection score to be the sum of the sub-detection scores of the U first state parameters.

[0293] In one possible implementation, the score determination module 701 is further used to: for any second state parameter among the V second state parameters, obtain the second preset condition corresponding to the second state parameter; determine whether the second state parameter meets the second preset condition; if the second state parameter meets the second preset condition, obtain the trigger state and acceleration of the blind spot alarm signal of the vehicle, and the trigger state is used to indicate whether there is an abnormality in the blind spot of the vehicle; if the trigger state is not triggered and the acceleration is less than or equal to the preset acceleration, determine that the sub-detection score of the second state parameter is a fourth preset score; if the trigger state is triggered, or the acceleration is greater than the preset acceleration, determine that the sub-detection score of the second state parameter is a fifth preset score, and the fourth preset score is greater than the fifth preset score; if the second state parameter does not meet the second preset condition, determine that the sub-detection score of the second state parameter is the fifth preset score; and determine that the second detection score is the sum of the sub-detection scores of the V second state parameters.

[0294] In one possible implementation, the scoring determination module 701 is further used to: for any third state parameter among the W third state parameters, obtain a third preset condition corresponding to the third state parameter; determine whether the third state parameter satisfies the third preset condition; if the third state parameter satisfies the third preset condition, obtain the trigger state and acceleration of the blind spot alarm signal of the vehicle, the trigger state being used to indicate whether there is an abnormality in the blind spot of the vehicle; if the duration during which the third state parameter satisfies the third preset condition is greater than a preset duration, and the trigger state is not triggered within the preset duration, and the acceleration is less than or equal to the preset acceleration within the preset duration. Under the condition that the third state parameter satisfies the third preset condition, the sub-detection score of the third state parameter is determined to be the sixth preset score; when the duration for which the third state parameter satisfies the third preset condition is less than or equal to the preset duration, or the trigger state is not entirely untriggered within the preset duration, or the acceleration is not entirely less than or equal to the preset acceleration within the preset duration, the sub-detection score of the third state parameter is determined to be the seventh preset score, and the sixth preset score is greater than the seventh preset score; when the third state parameter does not satisfy the third preset condition, the sub-detection score of the third state parameter is determined to be the seventh preset score; the third detection score is determined to be the sum of the sub-detection scores of the W third state parameters.

[0295] Optionally, the device further includes: a type determination module, which is used to call the image acquisition device in the vehicle to obtain a facial image of the living creature when there is a living creature in the vehicle; and classify and identify the facial image to determine the type of the living creature.

[0296] Figure 8 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application.

[0297] For example, Figure 8 As shown, the vehicle 101 includes: a memory 801 and a processor 802, wherein the memory 801 stores an executable program code 8011, and the processor 802 is used to call and execute the executable program code 8011 to perform a method for detecting living things in the vehicle.

[0298] In addition, an embodiment of the present application also protects a device, which may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform a method for detecting living things in a vehicle provided by an embodiment of the present application.

[0299] In this embodiment, the device can be divided into functional modules based on the above-described method examples. For example, each functional module can be mapped to a specific functional module, or two or more functions can be integrated into a single processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and represents only a logical functional division. In actual implementation, other division methods may be used.

[0300] In the case of dividing the functional modules into corresponding functional modules, the device may further include a score determination module, a biological detection module, an alarm module, etc. It should be noted that all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module and will not be repeated here.

[0301] It should be understood that the device provided in this embodiment is used to execute the above-mentioned method for detecting living things in a vehicle, and thus can achieve the same effect as the above-mentioned implementation method.

[0302] In the case of an integrated unit, the device may include a processing module and a storage module. When the device is used in a vehicle, the processing module may be used to control and manage the vehicle's movements, while the storage module may be used to support the vehicle's execution of relevant program codes.

[0303] The processing module may be a processor or controller that implements or executes the various exemplary logic blocks, modules, and circuits described in conjunction with the present disclosure. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a digital signal processing (DSP) and a microprocessor, and the storage module may be a memory.

[0304] In addition, the device provided in the embodiments of the present application can specifically be a chip, component or module, and the chip may include a connected processor and memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute a method for detecting living things in a vehicle provided in the above embodiment.

[0305] This embodiment also provides a computer-readable storage medium, which stores computer program code. When the computer program code runs on a computer, the computer executes the above-mentioned related method steps to implement a method for detecting living things in a vehicle provided by the above embodiment.

[0306] This embodiment further provides a computer program product. When the computer program product is run on a computer, the computer is caused to execute the above-mentioned related steps to implement the method for detecting living things in a vehicle provided by the above embodiment.

[0307] Among them, the device, computer-readable storage medium, computer program product or chip provided in this embodiment are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0308] Through the description of the above implementation methods, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0309] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0310] The above content is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for detecting living things in a vehicle, characterized in that: The method comprises: Determining, based on M state parameters collected by M collection devices of the vehicle, a total detection score of the M state parameters, where the state parameters are used to represent the operating state of the vehicle, M is a positive integer greater than 1, and the total detection score is used to represent the probability of the presence of a living organism in the vehicle; determining whether there is a living organism in the vehicle based on the total detection score; In the case where there is a living organism in the vehicle, generating target alarm information according to the location of the vehicle and the type of the living organism; Before determining the total detection score of the M state parameters collected by the M collection devices of the vehicle, the method further includes: Obtaining a detection level corresponding to each of the M state parameters, where the detection level is used to indicate the degree of influence of a living organism on the state parameter; Furthermore, determining the total detection score of the M state parameters collected by the M collection devices of the vehicle includes: Based on the detection level corresponding to each of the M state parameters, the M state parameters are divided into U first state parameters, V second state parameters, and W third state parameters, the detection level of the U first state parameters being higher than the detection level of the V second state parameters, and the detection level of the V second state parameters being higher than the detection level of the W third state parameters; Determining the total detection score according to the U first state parameters, the V second state parameters, and the W third state parameters; The method does not introduce additional hardware equipment and utilizes the vehicle's own acquisition equipment.

2. The method according to claim 1, characterized in that Determining whether there is a living organism in the vehicle based on the total detection score includes: If the total detection score is greater than or equal to a first preset score, determining that a living organism exists in the vehicle; When the total detection score is less than the first preset score, it is determined that no living creature exists in the vehicle.

3. The method according to claim 1, characterized in that Before determining the total detection score based on the U first state parameters, the V second state parameters, and the W third state parameters, the method further includes: Obtaining first weights corresponding to the detection levels of the U first state parameters, second weights corresponding to the detection levels of the V second state parameters, and third weights corresponding to the detection levels of the W third state parameters; And, determining the total detection score according to the U first state parameters, the V second state parameters, and the W third state parameters includes: Determining a first detection score according to the U first state parameters; Determining a second detection score according to the V second state parameters; determining a third detection score according to the W third state parameters; The total detection score is determined according to the first detection score, the second detection score, the third detection score, the first weight, the second weight, and the third weight.

4. The method according to claim 3, characterized in that Determining a first detection score according to the U first state parameters includes: For any first state parameter among the U first state parameters, obtaining a first preset condition corresponding to the first state parameter; determining whether the first state parameter satisfies the first preset condition; When the first state parameter satisfies the first preset condition, determining the sub-detection score of the first state parameter to be a second preset score; If the first state parameter does not satisfy the first preset condition, determining that the sub-detection score of the first state parameter is a third preset score, and the second preset score is greater than the third preset score; The first detection score is determined as the sum of the sub-detection scores of the U first state parameters.

5. The method according to claim 3, characterized in that Determining a second detection score according to the V second state parameters includes: For any second state parameter among the V second state parameters, obtaining a second preset condition corresponding to the second state parameter; determining whether the second state parameter satisfies the second preset condition; When the second state parameter satisfies the second preset condition, obtaining a trigger state and acceleration of a blind spot warning signal of the vehicle, wherein the trigger state is used to indicate whether there is an abnormality in the blind spot of the vehicle; When the trigger state is not triggered and the acceleration is less than or equal to the preset acceleration, the sub-detection score of the second state parameter is determined to be a fourth preset score; when the trigger state is triggered, or the acceleration is greater than the preset acceleration, the sub-detection score of the second state parameter is determined to be a fifth preset score, and the fourth preset score is greater than the fifth preset score; If the second state parameter does not satisfy the second preset condition, determining the sub-detection score of the second state parameter to be the fifth preset score; The second detection score is determined as the sum of the sub-detection scores of the V second state parameters.

6. The method according to claim 3, characterized in that Determining a third detection score according to the W third state parameters includes: For any third state parameter among the W third state parameters, obtaining a third preset condition corresponding to the third state parameter; determining whether the third state parameter satisfies the third preset condition; When the third state parameter satisfies the third preset condition, obtaining a trigger state and acceleration of a blind spot warning signal of the vehicle, the trigger state being used to indicate whether there is an abnormality in the blind spot of the vehicle; When the duration for which the third state parameter satisfies the third preset condition is greater than the preset duration, and the trigger states are all untriggered within the preset duration, and the accelerations are all less than or equal to the preset accelerations within the preset duration, the sub-detection score of the third state parameter is determined to be the sixth preset score; when the duration for which the third state parameter satisfies the third preset condition is less than or equal to the preset duration, or, not all of the trigger states are untriggered within the preset duration, or, not all of the accelerations are less than or equal to the preset acceleration within the preset duration, the sub-detection score of the third state parameter is determined to be the seventh preset score, and the sixth preset score is greater than the seventh preset score; If the third state parameter does not satisfy the third preset condition, determining the sub-detection score of the third state parameter to be the seventh preset score; The third detection score is determined as the sum of the sub-detection scores of the W third state parameters.

7. The method according to claim 1, characterized in that The method further comprises: In the case where there is a living creature in the vehicle, calling an image acquisition device in the vehicle to obtain a facial image of the living creature; Classify and identify the facial image to determine the type of the living creature.

8. A device for detecting living things in a vehicle, characterized in that: The device comprises: a score determination module, configured to determine, based on M state parameters collected by M collection devices of the vehicle, a total detection score for the M state parameters, wherein the state parameters represent the operating state of the vehicle, M is a positive integer greater than 1, and the total detection score represents the probability of the presence of a living organism in the vehicle; a biological detection module, configured to determine whether there are any living organisms in the vehicle based on the total detection score; an alarm module, configured to generate target alarm information according to the location of the vehicle and the type of the living organism when a living organism is present in the vehicle; Before determining the total detection score of the M state parameters collected by the M collection devices of the vehicle, the score determination module is further configured to: Obtaining a detection level corresponding to each of the M state parameters, where the detection level is used to indicate the degree of influence of a living organism on the state parameter; Furthermore, the scoring determination module is specifically configured to: Based on the detection level corresponding to each of the M state parameters, the M state parameters are divided into U first state parameters, V second state parameters, and W third state parameters, the detection level of the U first state parameters being higher than the detection level of the V second state parameters, and the detection level of the V second state parameters being higher than the detection level of the W third state parameters; Determining the total detection score according to the U first state parameters, the V second state parameters, and the W third state parameters; The device does not introduce any additional hardware devices, but utilizes the vehicle's own acquisition device.

9. A vehicle, characterized in that: The vehicle comprises: a memory for storing executable program code; A processor is configured to call and run the executable program code from the memory, so that the vehicle executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed, the method according to any one of claims 1 to 7 is implemented.

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