Method and device for detecting organisms in vehicle, vehicle and storage medium

Abstract

The invention provides a method and device for detecting living beings in a vehicle, the vehicle and a storage medium, the method is applied to the field of vehicle safety detection, and the method comprises the steps that according to M state parameters collected by M collection devices of the vehicle, the total detection score of the M state parameters is determined, and the state parameters are used for representing the running state of the vehicle, the total detection score is used for representing the probability that living organisms exist in the vehicle; determining whether living organisms exist in the vehicle or not according to the total detection score; and generating target alarm information according to the position of the vehicle and the type of the living organism under the condition that the living organism exists in the vehicle. According to the method, under the condition that extra hardware equipment is not introduced, whether the living organisms are left in the vehicle or not can be detected in time through the collection equipment of the vehicle, an alarm is given, and the safety risk caused by the fact that the living organisms are left in the vehicle for a long time is avoided.

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 may be 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 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 timely detect whether there are any living organisms left in the vehicle and 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 things in a vehicle is provided, the method comprising: determining a total detection score of the M state parameters based on M state parameters collected by M collection devices of the vehicle, the state parameter being used to represent the operating state of the vehicle, M being a positive integer greater than 1, and the total detection score being used to represent the probability of the presence of living things in the vehicle; determining whether there are living things in the vehicle based on the total detection score; and generating target alarm information based on the location of the vehicle and the type of living things if there are living things in the vehicle.

[0007] In the above technical solution, after the vehicle is locked, in order to prevent children or pets from being left in the car, the present application proposes a method for detecting organisms in the car. Specifically, the vehicle can determine the total detection score based on the M state parameters collected by its own M acquisition devices. The total detection score can represent the probability of the existence of living organisms in the car. In other words, the higher the total detection score, the greater the probability of the existence of living organisms in the car. The smaller the total detection score, the smaller the probability of the existence of living organisms in the car. Further, the vehicle determines whether there are living organisms in the car through the specific value of the total detection score, and if there are, generates target alarm information according to the location of the vehicle and the type of living organisms. In the above implementation process, the vehicle can rely on its own sensors to detect whether there are living organisms in the car, without the need to introduce additional detection equipment, thereby reducing the hardware and software costs of the vehicle, and can promptly detect whether there are living organisms left in the car. In addition, by detecting data collected by multiple acquisition devices of the vehicle, the in-vehicle environment can be more comprehensively evaluated to avoid false alarms caused by a single parameter. When there are living organisms in the car, the vehicle will sound an alarm based on the location and type of the living organism, allowing people outside the car and users to discover and deal with it in time, avoiding safety hazards caused by living organisms 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, the detection level being 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 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 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: when the total detection score is greater than or equal to a first preset score, determining that there is a living creature in the vehicle; when the total detection score is less than the first preset score, determining that there is no living creature in the vehicle.

[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 the above technical solution, in the process of determining the total detection score, the vehicle can assign different weights to each detection level according to the detection level of each state parameter, which can ensure that higher feedback is given to state parameters with higher sensitivity during detection. Furthermore, according to different detection levels, the detection score at each detection level is calculated respectively and the corresponding weights are combined to obtain the total detection score, which can comprehensively consider the collection results of multiple collection devices of the vehicle and improve the accuracy of the 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 satisfies the first preset condition; if the first state parameter satisfies 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 existence of living organisms in the vehicle is extremely high. Based on this, when the vehicle determines the first detection score of this type of state parameter, it 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 evaluates the probability of the existence of living organisms in the vehicle.

[0014] In combination with the first aspect and the above-mentioned implementation manner, in some possible implementation manners, the second detection score is determined according to the V second state parameters, including: 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 satisfies the second preset condition; 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, 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, determining that the sub-detection score of the second state parameter is a fourth preset score; when the trigger state is triggered, or the acceleration is greater than the preset acceleration, determining 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, determining that the sub-detection score of the second state parameter is the fifth preset score; determining that the second detection score is the sum of the sub-detection scores of the V second state parameters.

[0015] In the above technical solution, the detection level corresponding to the V second state parameters is slightly lower than the detection level of the U first 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. Therefore, when determining the second detection score of this type of state parameter, when the state parameter meets the corresponding preset conditions, it is also necessary to check whether the change of the state parameter is caused by external factors through the blind spot alarm signal and acceleration of the vehicle, so as to accurately perceive the surrounding environment and avoid misjudgment caused by interference from external factors, thereby enhancing the stability and reliability of the score determination process.

[0016] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the third detection score is determined according to 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 satisfies the third preset condition; when the third state parameter satisfies the third 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 time length when the third state parameter satisfies 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 surface will cause a small shake). In general, if the change in the vehicle's own state lasts for a short time. 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 check whether the change in the state parameter is caused by external factors through the vehicle's blind spot alarm signal and acceleration. When the change in the state parameter is not caused by external factors, it is also 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 an 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 identify the type of forgotten objects in the vehicle through image recognition algorithms, thereby generating target alarm information, allowing users to take corresponding treatment measures more quickly.

[0020] In a second aspect, a device for detecting living things in a vehicle is provided, the device comprising: a score determination module, for determining a total detection score of M state parameters based on M state parameters collected by M collection devices of the vehicle, the state parameter being used to represent the operating state of the vehicle, M being a positive integer greater than 1, and the total detection score being used to represent the probability of the presence of living things in the vehicle; a living thing detection module, for determining whether there are living things 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 things when there are living things 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 collected by 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 satisfies the first preset condition; if the first state parameter satisfies the first preset condition, determine that the sub-detection score of the first state parameter is the second preset score; if the first state parameter does not meet the first preset condition, determine that the sub-detection score of the first state parameter is the third preset score, and the second preset score is greater than the third preset score; determine that the first detection score is 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 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; 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 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 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 organism when there is a living organism in the vehicle; classify and identify the facial image to determine the type of the living organism.

[0028] In a third aspect, a vehicle is provided, comprising a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the vehicle executes the method in 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 manner of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a schematic diagram of a scene for detecting living things in a car 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 in an embodiment of the present application;

[0033] Figure 3 It 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 is a schematic diagram of the structure of a device for detecting living things in a vehicle provided in 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 technical solution in the present application will be described clearly and in detail below in conjunction with the accompanying drawings. In the description of the embodiments of the present 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 the present application, "multiple" means two or more than two.

[0040] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, 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 scene for detecting living things in a vehicle provided in 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 safety, 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 through a digital key in a terminal device, through a remote control key of the vehicle 101, through a mechanical key, etc.

[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 a 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 be found, they are easily overlooked when the user gets out of the car, resulting in them being forgotten in the car after locking the car.

[0047] When children or small pets are forgotten in the vehicle, if the vehicle 101 is parked in a high temperature environment, as the parking time gradually increases, the temperature inside the vehicle may rise to a high level in a short period of time. Children or pets cannot bear such high temperatures, which may easily cause skin diseases, and in more serious cases, may cause skin burns. If the vehicle 101 is parked in a low temperature environment, the temperature inside the vehicle gradually drops, which may easily cause hypothermia in children or pets. In addition, being trapped in the car for a long time will also cause psychological fear and anxiety to children or pets.

[0048] In order to solve the above problems, the related art generally installs a life detection system in the vehicle to detect the organisms left in the vehicle. The life detection system usually includes various types of sensors and devices, such as visible light cameras, thermal imaging cameras, millimeter wave radars, microphone arrays, etc. The installation of the life detection system in the vehicle requires the installation of other sensors or devices in the vehicle, which increases the hardware and software costs of the vehicle.

[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 any living organisms left in the vehicle and alarm without introducing additional hardware equipment, thereby avoiding the safety risks caused 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 is a schematic flow chart of a method for detecting a living being in a vehicle provided in an embodiment of the present application. It should be understood that the method is applied to Figure 1 The scenario shown can be applied to Figure 1 Any electronic control unit (ECU) in the vehicle 101 shown is not limited in the embodiment of the present application.

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

[0053] 201. Determine a total detection score of the M state parameters according to the M state parameters collected by the M collection devices of the vehicle, where the state parameters are used to represent the running 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 existence of a living organism in the vehicle.

[0054] It should be understood that the method provided in the embodiment of the present application, when detecting whether there are living organisms in the vehicle after the vehicle is locked, specifically, the ECU collects M state parameters collected by M collection devices in the vehicle, and obtains a total detection score based on the M state parameters to determine whether there are living organisms in the vehicle. Among them, the state parameters represent the operating state of the vehicle. The total detection score is used to indicate the probability of the existence of living organisms in the vehicle. In other words, the higher the total detection score, the greater the probability of the existence of living organisms in the vehicle; the lower the total detection score, the smaller the probability of the existence of living organisms in 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 glass 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 the vehicle, the ECU detects that the vehicle is in a locked state, i.e., the scheme of the embodiment of the present application is activated. 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 organisms in the car, the M acquisition devices mentioned above have different sensitivities to the organisms in the car. In other words, the movement of living organisms has different degrees of influence on the M state parameters. For example, when the acquisition device is a glass lift switch. When the vehicle is locked, if there are living organisms left in the car, the living organisms may try to open the window by pressing the glass lift switch, thereby changing the state of the glass lift switch. Therefore, if the ECU detects that the glass lift switch has changed, it means that there must be living organisms in the car. When the acquisition device is a steering wheel angle sensor, after the vehicle is locked, affected by external factors, if the vehicle is parked on an uneven road or under the influence of external wind, the steering wheel of the vehicle may also shake slightly. Therefore, if the ECU detects that the steering wheel angle has changed, it cannot be said that there must be living organisms in the car.

[0059] Based on the degree of influence of living organisms in the vehicle on the changes of M state parameters, technicians can set corresponding detection levels for M acquisition devices or M state parameters in advance and store them in the ECU. The higher the detection level, the greater the possibility that the change in the state parameter is caused by a living organism; the lower the detection level, the lower the possibility that the change in the state parameter is caused by a living organism.

[0060] Figure 3 It 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, the technicians divide the detection levels of the M acquisition devices into three types according to different detection levels.

[0062] like Figure 3 As shown in the figure, the three detection levels include detection level 1, detection level 2 and detection level 3. Among them, the acquisition devices corresponding to detection level 1 include glass lift switch, electric inner door handle switch, wiper switch and gear switch. The acquisition devices corresponding to detection level 2 include steering wheel angle sensor, steering wheel torque sensor and seat pressure sensor. The acquisition devices corresponding to detection level 3 include slope sensor, air suspension height sensor and audio acquisition device. Detection level 1 is higher than detection level 2 and higher than detection level 3.

[0063] Correspondingly, among the M state parameters, the state parameters collected by the glass 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 glass lift switch are the glass lift switch state, the state parameters collected by the electric inner door handle switch are the electric inner 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 glass lift switch state may be the state of any glass lift switch in the vehicle. The electric inner door handle switch state may be the state of any electric inner 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 height sensor is the wheel height, and the state parameter collected by the audio acquisition device (e.g., a microphone) is the volume decibel value. Among them, the wheel height refers to the relative distance between the wheel suspension system and the vehicle body, and the wheel height can be the height of any wheel in the vehicle.

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

[0068] When calculating the total detection score of M state parameters, the ECU may 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 a 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 the living organism on the state parameter;

[0071] And, according to the M state parameters collected by the M collection devices of the vehicle, determining the total detection score of the M state parameters, 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 U first state parameters, V second state parameters, and 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, based on the detection level of each state parameter, the ECU can obtain U first state parameters, V second state parameters and W third state parameters corresponding to the three detection levels. Among them, the detection level of U first state parameters is higher than that of V second state parameters, and the detection level of V second state parameters is higher than that of 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 according to U first state parameters, V second state parameters and W third state parameters respectively.

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

[0081] In a possible implementation, before 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 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 according to 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 V second state parameters;

[0086] Determining a third detection score according to 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 influences on the result of determining whether there are living organisms in the vehicle, in the embodiment of the present application, the technicians can pre-set different influence factors (i.e., weights) for each detection level and store them in the ECU.

[0089] When calculating the detection scores of multiple state parameters at each detection level, the ECU can first obtain the weights corresponding to different detection levels. In the embodiment of the present application, the weights corresponding to the detection levels of U first state parameters are called "first weights", the weights corresponding to the detection levels of V second state parameters are called "second weights", and the weights corresponding to the detection levels of W third state parameters are called "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 through U first state parameters, the second detection score through V second state parameters, and the third detection score through W third state parameters. Finally, the total detection score is obtained through 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 detection 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 there is a living organism 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"; on the contrary, 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 detection level of the U first state parameters is the highest, indicating that the change of the first state parameters is most likely to be triggered by a living organism in the car. 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 is considered that the probability of the existence of a living organism in the car is extremely high, and the alarm signal flag of the first state parameter is set to the "true" state, indicating that the probability of the existence of a living organism in the current car is relatively high. On the contrary, when the ECU does not detect that the first state parameter meets the alarm condition, it is considered that there is no living organism in the car, and the alarm signal flag of the first state parameter is set to the "false" state.

[0106] Based on the setting result of the alarm signal flag or the judgment result of the ECU, the ECU will determine the sub-detection score of the first state parameter. Different judgment results or setting results will result in different values ​​of the sub-detection score of the first state parameter. Based on this, by calculating the sub-detection score of each first state parameter, the ECU can obtain the first detection scores of U first state parameters.

[0107] In a 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 the "first preset condition". When the ECU determines that the first state parameter meets the first preset condition, the alarm signal flag of the first state parameter is set to "true", and the sub-detection score of the first state parameter is determined to be the second preset score. On the contrary, when the first state parameter does not meet the first preset condition, the ECU can set the alarm signal flag of the first state parameter to "false", and determine the sub-detection score of the first state parameter to be the third preset score. Among them, 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. The embodiment of the present application can preset the state parameters of different detection levels, and 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 organisms in the car, therefore, the sub-detection scores of the state parameters of different detection levels in this case can be set to be 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 of 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 the 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 parameter is different, the corresponding first preset condition is also different.

[0118] Specifically, when any one of the first state parameters is the glass lift switch state, the first preset condition corresponding to the first state parameter is: the glass lift switch state has changed. The glass lift switch state has changed, which means that the current glass lift switch state is different from the previous glass lift switch state. When any one of the first state parameters is the electric inner door handle switch state, the first preset condition corresponding to the first state parameter is: the electric inner door handle switch state has changed. When any one of the first state parameters is the wiper switch state, the first preset condition corresponding to the first state parameter is: the wiper switch state has changed. When any one of the first state parameters is the 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 of the first state parameter, when the ECU determines whether the first state parameter satisfies the first preset condition, the specific process is as follows.

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

[0121] When the first state parameter is the state of the glass lifting switch, if the state of the glass lifting switch changes, it is determined that the first state parameter meets the first preset condition; if the state of the glass lifting 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 gear switch state, if the gear switch state changes, it is determined that the first state parameter meets the first preset condition; if the gear 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 satisfies its corresponding first preset condition by detecting whether the first state parameter changes, and obtain a sub-detection score of the first state parameter according to 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] To facilitate understanding of the calculation process of the first detection score, Figure 4 The above calculation process is introduced in detail.

[0128] Figure 4 It 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 lifting switch state, execute 402;

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

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

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

[0135] 402, determine whether the state of the glass lifting switch changes.

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

[0137] When the state of the glass lift switch does not change, execute 407 .

[0138] 403, determine whether the switch state of the electric inner door handle changes.

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

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

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

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

[0143] When the wiper switch state does not change, execute 407.

[0144] 405, determine whether the state of the gear switch changes.

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

[0146] When the state of the shift switch does not change, execute 407.

[0147] 406 , determining the sub-detection score of the first state parameter to be 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. Please refer to the introduction of method 200 for details, which 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 existence of living organisms in the vehicle is extremely high. Based on this, when the vehicle determines the first detection score of this type of state parameter, it 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 evaluates the probability of the existence of living organisms in the vehicle.

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

[0154] It should be understood that the detection level of the V second state parameters is lower than the detection level 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 living organisms in the vehicle. In this case, in order to ensure the accuracy of the judgment result, the ECU also needs to make a judgment in combination with other conditions.

[0155] In a 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 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;

[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] When 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 for the second state parameters 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 vehicle, but may also be caused by external factors. For example, when a large vehicle passes by outside the vehicle, 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 large vehicles 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 of the second state parameter may be caused by other factors, which cannot indicate that there is a high probability of living organisms in the vehicle. In this case, the ECU also 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 trigger state and acceleration of the blind spot alarm signal of the vehicle.

[0165] Among them, Blind Spot Monitoring (BSM) is a safety function in the vehicle that detects whether there are other vehicles in the blind spots behind the vehicle on both sides and warns the driver when potential danger is detected. The realization of this function mainly relies on radar sensors, ultrasonic sensors and cameras in the vehicle.

[0166] The triggering status of the blind spot warning 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 warning signal flag.

[0167] When the vehicle's blind spot alarm system determines through the above-mentioned various acquisition devices 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 above-mentioned various acquisition devices 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 that there are other vehicles behind the vehicle on both sides. When other vehicles pass by the side of the vehicle, other vehicles will generate airflow during driving. When the airflow is large, it may cause the vehicle to move slightly, causing the acceleration of the vehicle to change. Therefore, when the second state parameter changes, it can be determined whether the change of the second state parameter is caused by external factors through the blind spot warning signal and acceleration.

[0170] In the embodiment of the present application, the technician can set a preset acceleration in advance according to the change of the acceleration of the vehicle 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 trigger state of the blind spot alarm signal of the vehicle is not triggered, it means that there are no other passing vehicles on both sides of the current vehicle; when the acceleration is less than or equal to the preset acceleration, it means that the vehicle has not moved or the moving range is within the allowed range of change. The above results can show that the change of the second state parameter is not caused by external factors, but by the activity of living organisms in the vehicle. Therefore, the ECU can set the alarm signal flag of the second state parameter to "true" and determine the sub-detection score of the second state parameter to the fourth preset score. On the contrary, when the trigger state is triggered, or the acceleration is greater than the preset acceleration, it means that the current change of the second state parameter may be caused by external factors. The ECU can set the alarm signal flag of the second state parameter to "false". Or, when the ECU determines that the second state parameter does not meet the second preset condition, the alarm signal flag of the second state parameter is set to "false". In the above two cases, when the alarm signal flag of the second state parameter is set to "false", the ECU determines the sub-detection score of the second state parameter to be the fifth preset score. Among them, the fourth preset score is greater than the fifth preset score.

[0172] Optionally, in one case, for state parameters of different detection levels, when the alarm signal flag is in the position "true", the corresponding sub-detection scores are different, and the fourth preset score can be 2 points, and the fifth preset score can be 0 points. For state parameters of different detection levels, when the alarm flag is in the position "true", the corresponding sub-detection scores are the same, and the fourth preset score can be 1 point, and the fifth preset score can be 0 points.

[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 one of the second state parameters is a steering wheel angle, the second preset condition corresponding to the second state parameter is: the angle difference between the steering wheel angle and the steering wheel angle at the previous moment is greater than the preset angle. When any one of the second state parameters 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 one of the second state parameters is a seat pressure, the second preset condition corresponding to the second state parameter is: the pressure difference between the seat pressure and the seat pressure at the previous moment is greater than the preset pressure.

[0176] Optionally, the preset angle may be a change in the angle of the steering wheel under normal circumstances due to external environmental factors, and the preset angle may be 10°. The preset torque may be a torque when the steering wheel is turned due to external environmental factors under normal circumstances, and the preset torque may be 4N˙m. The preset pressure may be a minimum pressure change value of the seat when there is an object sitting on it, and the preset pressure may be 50N.

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

[0178] In a possible implementation manner, 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 the 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 any 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 5It 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, 504 is executed.

[0192] 502, determine 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, determine 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 that the sub-detection score of the second state parameter is 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 that the sub-detection score of the second state parameter is 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 , determine 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. Please refer to the introduction of method 200 for details, which 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 level corresponding to the V second state parameters is slightly lower than the detection level of the U first 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. Therefore, when determining the second detection score of this type of state parameter, when the state parameter meets the corresponding preset conditions, it is also necessary to check whether the change of the state parameter is caused by external factors through the blind spot alarm signal and acceleration of the vehicle, so as to accurately perceive the surrounding environment and avoid misjudgment caused by interference from external factors, thereby enhancing the stability and reliability of the score determination process.

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

[0210] It should be understood that the detection level of the W third state parameters is lower than the detection level of the V second state parameters. Therefore, when any third state parameter among the W second state parameters changes, it is not necessarily caused by the activity of living organisms in the vehicle. In this case, similar to the second state parameter, in order to ensure the accuracy of the judgment result, the ECU also needs to make a judgment in combination with other conditions.

[0211] In a 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 satisfies the third preset condition, the trigger state and acceleration of the blind spot alarm signal of the vehicle are obtained, and the trigger state is used to indicate whether there is an abnormality in the blind spot of the vehicle.

[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] When 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 embodiments of the present application, such as slope, wheel height and sound decibel value. When the second state parameter changes, it is not necessarily caused by the 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, a small movement may occur, causing the slope to change.

[0219] Furthermore, if the state parameter changes are caused by the state of the vehicle itself, the duration is relatively short. If the state parameter changes are caused by living organisms in the vehicle, when children or pets are left in the vehicle, due to the panic effect, the children or pets may continue to move around in 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, it is possible that the change in the third state parameter is caused by other factors, which does not mean that there is a high probability 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] Since the detection level of the third state parameter is lower than that of the second state parameter, that is, the probability of false alarm is higher, when the ECU determines that the third state parameter meets the third preset condition, it can first determine whether the change of the third state parameter is caused by external factors or the vehicle's own state by obtaining the trigger state and acceleration of the blind spot alarm signal and the duration of the change.

[0223] If the duration of the third state parameter meeting the third preset condition is longer than the preset duration, and the triggering state is not triggered within the preset duration, it means that there are no other passing vehicles on both sides of the current vehicle, and the acceleration within the preset duration is less than or equal to the preset acceleration, indicating that the vehicle has not moved or the moving range is within the change range allowed by the change of the state parameter. Therefore, the above results can show that the change of the third state parameter is neither caused by external factors nor by the vehicle itself. Therefore, the ECU can set the alarm signal flag of the third state parameter to "true" and determine the sub-detection score of the third state parameter to the sixth preset score. On the contrary, when the duration of the third state parameter meeting the third preset condition is less than or equal to the preset duration, or the triggering state within the preset duration is not all untriggered, or the acceleration within the preset duration is not all less than or equal to the preset acceleration, it means that the change of the current third state parameter may be caused by external factors or caused by the change of the vehicle's own state. The ECU can set the alarm signal flag of the third state parameter to "false". Or, when the ECU determines that the third state parameter does not meet the third preset condition, the alarm signal flag of the third state parameter is set 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, for status parameters of different detection levels, when the alarm signal flag is in the position "true", if the corresponding sub-detection scores are different, the sixth preset score may be 1 point, and the seventh preset score may be 0 point. For status parameters of different detection levels, when the alarm flag is in the position "true", if the corresponding sub-detection scores are the same, the sixth preset score may be 1 point, and the seventh preset score may be 0 point.

[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 a slope, the third preset condition corresponding to the third state parameter is: the slope change frequency is within a preset frequency range. The slope change frequency refers to the rate at which the slope changes over time, that is, the number of times the slope changes per unit time, in Hz.

[0228] In the embodiment of the present application, the technician may pre-set a frequency range for identifying a slope change that may be caused by the 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 third state parameter is wheel height, the third preset condition corresponding to the third state parameter is: the height difference between the wheel height and the wheel height at the previous moment is greater than the preset height. When any third state parameter is volume decibel value, the third preset condition corresponding to the third state parameter is: the volume decibel value is greater than the preset decibel.

[0231] The preset height may be a critical change value of the wheel height when there is a living organism in the vehicle. Optionally, the preset height may be 5 mm. The preset decibel is a critical decibel value of the volume in the vehicle when there is a living organism in the vehicle, and the preset decibel may be 70 dB.

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

[0233] In a possible implementation manner, 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 third state parameter 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, and 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 It 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 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 , determining the sub-detection score of the third state parameter to be 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, when the third state parameter continues to meet 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 satisfy 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. Please refer to the introduction in method 200 for details, which 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 surface will cause a small shake). In general, if the change in the vehicle's own state lasts for a short time. 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 check whether the change in the state parameter is caused by external factors through the vehicle's blind spot alarm signal and acceleration. When the change in the state parameter is not caused by external factors, it is also 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, determine whether there are living organisms in the vehicle based on the total detection score.

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

[0266] In a possible implementation, determining whether there is a living organism in the vehicle based on the total detection score includes:

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

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

[0269] Optionally, in combination with the above-mentioned determination of the total detection score, the state 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] Exemplarily, in one case, when the status parameters of different detection levels, when the alarm signal flag is in the position of "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 according to this scoring method, the ECU can compare the calculated total detection score with the first preset score. When the total detection score is greater than or equal to the first preset score, it is determined that there is a living organism in the vehicle. When the total detection score is less than the first preset score, it is determined that there is no living organism in the vehicle.

[0272] When the status parameters of different detection levels, when the alarm signal flag is in the position of "true", 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 according to this scoring method, the ECU can compare the calculated total detection score with the first preset score. When the total detection score is greater than or equal to the first preset score, it is determined that there is a living organism in the vehicle. When the total detection score is less than the first preset score, it is determined that there is no living organism 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 time.

[0276] In a possible implementation manner, 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 identify facial images to determine the type of living organism.

[0279] When there is a living organism 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 organism 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 organism.

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

[0281] The ECU can send the 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 identify the type of forgotten objects in the vehicle through image recognition algorithms, thereby generating target alarm information, allowing users to take corresponding treatment measures more quickly.

[0283] In summary, after the vehicle is locked, in order to prevent children or pets from being left in the car, the present application proposes a method for detecting organisms in the car. Specifically, the vehicle can determine the total detection score based on the M state parameters collected by its own M acquisition devices. The total detection score can represent the probability of the existence of living organisms in the car. In other words, the higher the total detection score, the greater the probability of the existence of living organisms in the car. The smaller the total detection score, the smaller the probability of the existence of living organisms in the car. Further, the vehicle determines whether there are living organisms in the car through the specific value of the total detection score, and if there are, generates target alarm information according to the location of the vehicle and the type of living organisms. In the above implementation process, the vehicle can rely on its own sensors to detect whether there are living organisms in the car, without the need to introduce additional detection equipment, thereby reducing the hardware and software costs of the vehicle, and can promptly detect whether there are living organisms left in the car. In addition, by detecting data collected by multiple acquisition devices of the vehicle, the in-vehicle environment can be more comprehensively evaluated to avoid false alarms caused by a single parameter. When there are living organisms in the car, the vehicle will sound an alarm based on the location and type of the living organism, allowing people outside the car and users to discover and deal with it in time, avoiding safety hazards caused by living organisms being left in the car for a long time.

[0284] Figure 7 It is a 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 device 700 includes:

[0286] The score determination module 701 is used to determine the total detection score of the M state parameters collected by the M collection devices of the vehicle according to the M state parameters, where the state parameters are used to represent the running 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 existence of a living organism in the vehicle;

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

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

[0289] In a possible implementation, before determining the total detection score of the M state parameters collected by M collection devices of the vehicle, the score determination module 701 is also 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 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.

[0290] In a possible implementation, the biological detection module 702 is further used 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 a 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 also used to: obtain 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, the score determination module 701 is also used to: determine a first detection score based on the U first state parameters; determine a second detection score based on the V second state parameters; determine a 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 satisfies the first preset condition; if the first state parameter satisfies 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 a possible implementation, the score determination module 701 is also 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; 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 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; determine that the second detection score is the sum of the sub-detection scores of the V second state parameters.

[0294] In a 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 for 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. 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.

[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 a 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 execute a method for detecting living things in a vehicle provided by an embodiment of the present application.

[0299] In this embodiment, the functional modules of the device can be divided according to the above method example. For example, each functional module can be corresponded, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0300] In the case of dividing each functional module according to each function, the device may also 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, which 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 applied to a vehicle, the processing module may be used to control and manage the actions of the vehicle. The storage module may be used to support the vehicle in executing relevant program codes, etc.

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

[0304] In addition, the device provided in the embodiments of the present application may specifically be a chip, a component or a module, and the chip may include a connected processor and a 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 embodiments.

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

[0306] This embodiment also 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 a 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 is used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method 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 assigned to 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 the present 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 only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, 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 contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for detecting living things in a vehicle, characterized in that: The method comprises: Determine, according to M state parameters collected by M collection devices of the vehicle, a total detection score of the M state parameters, wherein the state parameters are used to represent the running 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 existence of a living organism in the vehicle; determining whether there is a living organism in the vehicle according to the total detection score; In the case that there is a living organism in the vehicle, target alarm information is generated according to the location of the vehicle and the type of the living organism.

2. The method according to claim 1, characterized in that 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 the living organism on the state parameter; And, determining the total detection score of the M state parameters according to 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 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; The total detection score is determined according to the U first state parameters, the V second state parameters and the W third state parameters.

3. The method according to claim 1 or 2, characterized in that: The determining whether there is a living organism in the vehicle according to the total detection score includes: When 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 organism exists in the vehicle.

4. The method according to claim 2, characterized in that: Before 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 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 comprises: 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.

5. The method according to claim 4, characterized in that The 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; 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; The first detection score is determined as the sum of the sub-detection scores of the U first state parameters.

6. The method according to claim 4, 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; When 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.

7. The method according to claim 4, 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, wherein the trigger state is 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; In a case where 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.

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

9. A device for detecting living things in a vehicle, characterized in that: The device comprises: A score determination module, used to determine a total detection score of the M state parameters collected by the M collection devices of the vehicle, wherein the state parameters are used to represent the running 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 existence of a living organism in the vehicle; A biological detection module, used to determine whether there are living organisms in the vehicle according to the total detection score; The alarm module is used to generate target alarm information according to the location of the vehicle and the type of the living organism when there is a living organism in the vehicle.

10. A vehicle, characterized in that: The vehicle comprises: A memory for storing executable program codes; A processor, 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 8.

11. 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 8 is implemented.

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