Vehicle safety management method and device

Abstract

The invention discloses a vehicle safety management method and device, and belongs to the field of intelligent cabins. According to the method, the physiological index data, the image data and the like of the person in the vehicle are collected, so that multi-dimensional state judgment on the person in the vehicle is realized. For example, the health state of the person in the vehicle can be determined based on the physiological index data. For example, based on the image data, the emotional state of the person in the vehicle can be recognized, and posture detection is conducted on the person in the vehicle. Through the health state, the emotional state and the current posture of the person in the vehicle, whether the person in the vehicle has an accident or not can be analyzed, and corresponding measures are taken. For example, the alarm mode can be determined according to the analysis result, and the alarm operation matched with the alarm mode is executed. In addition, the vehicle control mode can be determined based on the driving environment data and the riding position of the person in the vehicle, and then the vehicle is controlled based on the determined vehicle control mode. The safety of people and the vehicle in the vehicle can be powerfully guaranteed.

Description

Technical Field

[0001] The present application relates to the field of smart cockpits, and in particular to a vehicle safety management method and device. Background Art

[0002] Driving safety is the primary concern of people when driving. Speeding, fatigue driving or unexpected driver situations can pose serious safety threats to the vehicle itself, the driver, passengers and surrounding objects. Therefore, how to manage vehicle safety to ensure the safety of passengers and vehicles is a key issue in the field of smart cockpits. Summary of the invention

[0003] The embodiment of the present application provides a vehicle safety management method and device. The technical solution is as follows:

[0004] In one aspect, a vehicle safety management method is provided, the system comprising:

[0005] Acquiring physiological index data and image data of passengers;

[0006] Determining the health status of the passenger based on the physiological indicator data;

[0007] If the health status indicates that the passenger has health abnormalities, based on the image data of the passenger, respectively, emotion recognition and posture detection are performed on the passenger to obtain an emotion recognition result and a posture detection result;

[0008] Determining an alarm mode that matches the health status, emotion recognition result, and posture detection result of the passenger;

[0009] Determining a vehicle control method based on current driving environment data and the riding position of the riding object;

[0010] The vehicle is controlled based on the vehicle control mode, and an alarm operation matching the alarm mode is executed.

[0011] In some embodiments, the step of obtaining physiological indicator data of the passenger includes at least one of the following:

[0012] Acquiring the physiological index data based on a sensor placed on a seat back;

[0013] Acquiring the physiological index data based on a sensor placed on a seat headrest;

[0014] Acquiring the physiological index data based on a sensor placed on the steering wheel;

[0015] The physiological index data is obtained based on a sensor placed on the rearview mirror inside the vehicle.

[0016] In some other embodiments, determining the health status of the passenger based on the physiological indicator data includes:

[0017] Determining a change trend of the physiological index of the passenger based on the physiological index data;

[0018] Determining the preliminary health status of the passenger based on the normal value range of each physiological indicator and the change trend of the physiological indicator;

[0019] Obtaining the electronic health record of the passenger;

[0020] Based on the electronic health record, the preliminary health status of the passenger is corrected to obtain the final health status of the passenger.

[0021] In other embodiments, the determining of an alarm mode that matches the health status, emotion recognition result, and posture detection result of the passenger includes:

[0022] Determining a first alarm mode matching the health status;

[0023] Determining a second alarm mode that matches the emotion recognition result;

[0024] Determining a third alarm mode that matches the posture detection result;

[0025] The alarm mode with the highest alarm level among the first alarm mode, the second alarm mode and the third alarm mode is used as the final alarm mode.

[0026] In some other embodiments, determining the vehicle control mode based on the current driving environment data and the riding position of the riding object includes:

[0027] The vehicle control mode is determined based on current in-vehicle driving environment data, out-vehicle driving environment data and the riding position of the riding object.

[0028] In some other embodiments, the vehicle control based on the vehicle control method includes at least one of the following:

[0029] Controlling the driving speed of the vehicle;

[0030] Performing safe driving distance control on the vehicle;

[0031] performing posture control on the vehicle;

[0032] The vehicle is controlled to stop in a safe area and maintain a parking state.

[0033] In some other embodiments, the performing of an alarm operation matching the alarm mode includes at least one of the following:

[0034] Performing a first warning operation in the vehicle through the vehicle speaker;

[0035] Performing a second warning operation outside the vehicle through the vehicle-mounted speaker;

[0036] Execute the third alarm operation through the display screen;

[0037] Initiate a call request to the service number;

[0038] Initiate a call request to the pre-set contact number.

[0039] In some other embodiments, the method further comprises:

[0040] Upload vehicle positioning data to the cloud server;

[0041] Upload at least one of the physiological indicator data, image data, health status, emotion recognition result or posture detection result of the passenger to the cloud server.

[0042] In another aspect, a vehicle safety management device is provided, the device comprising:

[0043] An acquisition module, configured to acquire physiological index data and image data of a passenger;

[0044] A first determination module is configured to determine the health status of the passenger based on the physiological indicator data;

[0045] a processing module configured to, if the health status indicates that the passenger has health abnormalities, perform emotion recognition and posture detection on the passenger based on the image data of the passenger to obtain an emotion recognition result and a posture detection result;

[0046] A second determination module is configured to determine an alarm mode that matches the health status, emotion recognition result, and posture detection result of the passenger;

[0047] A third determination module is configured to determine a vehicle control mode based on current driving environment data and a riding position of the riding object;

[0048] The safety management module is configured to control the vehicle based on the vehicle control method and execute an alarm operation matching the alarm method.

[0049] In some embodiments, the acquisition module is configured to perform at least one of the following:

[0050] Acquiring the physiological index data based on a sensor placed on a seat back;

[0051] Acquiring the physiological index data based on a sensor placed on a seat headrest;

[0052] Acquiring the physiological index data based on a sensor placed on the steering wheel;

[0053] The physiological index data is obtained based on a sensor placed on the rearview mirror inside the vehicle.

[0054] In some other embodiments, the first determining module is configured to:

[0055] Determining a change trend of the physiological index of the passenger based on the physiological index data;

[0056] Determining the preliminary health status of the passenger based on the normal value range of each physiological indicator and the change trend of the physiological indicator;

[0057] Obtaining the electronic health record of the passenger;

[0058] Based on the electronic health record, the preliminary health status of the passenger is corrected to obtain the final health status of the passenger.

[0059] In some other embodiments, the second determining module is configured to:

[0060] Determining a first alarm mode matching the health status;

[0061] Determining a second alarm mode that matches the emotion recognition result;

[0062] Determining a third alarm mode that matches the posture detection result;

[0063] The alarm mode with the highest alarm level among the first alarm mode, the second alarm mode and the third alarm mode is used as the final alarm mode.

[0064] In some other embodiments, the third determining module is configured to:

[0065] The vehicle control mode is determined based on current in-vehicle driving environment data, out-vehicle driving environment data and the riding position of the riding object.

[0066] In some other embodiments, the security management module is configured to perform at least one of the following:

[0067] Controlling the driving speed of the vehicle;

[0068] Performing safe driving distance control on the vehicle;

[0069] performing posture control on the vehicle;

[0070] The vehicle is controlled to stop in a safe area and maintain a parking state.

[0071] In some other embodiments, the security management module is configured to perform at least one of the following:

[0072] Performing a first warning operation in the vehicle through the vehicle speaker;

[0073] Performing a second warning operation outside the vehicle through the vehicle-mounted speaker;

[0074] Execute the third alarm operation through the display screen;

[0075] Initiate a call request to the service number;

[0076] Initiate a call request to the pre-set contact number.

[0077] In some other embodiments, the device further comprises:

[0078] An upload module, configured to upload the vehicle positioning data to a cloud server;

[0079] The uploading module is further configured to upload at least one of the physiological indicator data, image data, health status, emotion recognition results or posture detection results of the passenger to the cloud server.

[0080] On the other hand, a smart cockpit domain controller is provided, which includes a main control module, the main control module includes a processor and a memory, the memory is used to store at least one program code, and the at least one program code is loaded by the processor and executes the above-mentioned vehicle safety management method.

[0081] On the other hand, a computer-readable storage medium is provided, in which at least one program code is stored. The at least one program code is loaded and executed by a processor to implement the above-mentioned vehicle safety management method.

[0082] On the other hand, a computer program product or a computer program is provided, which includes a computer program code, which is stored in a computer-readable storage medium. A processor of a smart cockpit domain controller reads the computer program code from the computer-readable storage medium, and the processor executes the computer program code, so that the smart cockpit domain controller executes the above-mentioned vehicle safety management method.

[0083] The embodiment of the present application realizes multi-dimensional status determination of the occupants by collecting physiological indicator data and image data of the occupants. For example, the health status of the occupants can be determined based on the physiological indicator data. For another example, the emotional state of the occupants can be identified based on the image data and the posture detection of the occupants can be performed. And through the health status, emotional state and current posture of the occupants, it can be analyzed whether there is an unexpected situation for the occupants and corresponding measures can be taken. For example, the alarm mode is determined based on the analysis results and the alarm operation matching the alarm mode is executed. In addition, the embodiment of the present application can also determine the vehicle control mode based on the driving environment data and the riding position of the occupants, and then control the vehicle based on the determined vehicle control mode. This safety management solution can effectively ensure the safety of the occupants and vehicles, and significantly improve driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0085] Figure 1 is a structural schematic diagram of an intelligent cockpit system provided in an embodiment of the present application;

[0086] Figure 2 is a flow chart of a vehicle safety management method provided by an embodiment of the present application;

[0087] Figure 3 It is a structural schematic diagram of a vehicle safety management device provided in an embodiment of the present application;

[0088] Figure 4 It is a structural diagram of a smart cockpit domain controller provided in an embodiment of the present application. DETAILED DESCRIPTION

[0089] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0090] In this application, the terms "first", "second", etc. are used to distinguish the same or similar items with substantially the same role and function. It should be understood that there is no logical or temporal dependency between "first", "second", and "nth", nor is there a limitation on the quantity and execution order. It should also be understood that although the following description uses the terms first, second, etc. to describe various elements, these elements should not be limited by the terms.

[0091] These terms are only used to distinguish one element from another element. For example, without departing from the scope of various examples, a first element can be referred to as a second element, and similarly, a second element can also be referred to as a first element. Both the first element and the second element can be elements, and in some cases, can be separate and different elements.

[0092] Here, at least one means one or more than one, for example, at least one element can be one element, two elements, three elements, or any other integer greater than or equal to one. And multiple means two or more than two, for example, multiple elements can be two elements, three elements, or any other integer greater than or equal to two.

[0093] The "and / or" mentioned in this article indicates 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. The character " / " generally indicates that the objects before and after are in an "or" relationship.

[0094] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards in the relevant regions.

[0095] Figure 1 It is a structural schematic diagram of an intelligent cockpit system provided in an embodiment of the present application.

[0096] See also Figure 1 The system includes: an intelligent cockpit control module 1, a seat control module 2, a heart rate sensor, a data acquisition module 3, a combined antenna 4, a display screen 5, a speaker 6 and a cloud server 7.

[0097] Among them, the intelligent cockpit control module 1 is connected to the seat control module 2 through a CAN (Controller Area Network) bus, the data acquisition module 3 is connected to the seat control module 2 through a serial port connection, and the display screen 5 is connected to the intelligent cockpit control module 1 through an LVDS (Low-Voltage Differential Signaling) harness. The speaker 6 is connected to the intelligent cockpit control module 1 through a serial port connection.

[0098] As an example, in terms of structure, the intelligent cockpit control module 1 includes hardware, software architecture, information input and output systems, and high-computing power chips, and the seat control module 2 includes an integrated circuit board, a micro-walled bidirectional rotating motor, a stepless regulator, various switches and electronic control units, etc., but this application does not limit this.

[0099] As another example, the intelligent cockpit control module 1 integrates an emergency call customer service function, and the occupants can communicate directly with the customer service personnel through voice calls, so that the occupants can get help in time when an accident occurs. It should be noted that the occupants mentioned in this article can be either drivers or passengers, and this application does not limit this.

[0100] In some embodiments, the data acquisition module 3 is used to collect physiological index data of the occupants of the vehicle, wherein the physiological index data includes but is not limited to heart rate, blood oxygen saturation, respiratory rate or blood pressure, etc.; accordingly, the data acquisition module 3 includes but is not limited to a heart rate sensor, a blood oxygen saturation sensor, a respiratory rate sensor or a blood pressure sensor, etc., which is not limited in this application.

[0101] Taking the heart rate sensor as an example, the heart rate sensor is set on the seat back. Among them, the heart rate sensor set on the seat back is designed with electrodes, which allows the heart rate sensor to monitor the user's heart activity through clothes. In this way, the seat control module 2 can continuously monitor the heart rate of the people in the car through the heart rate sensor. Of course, in addition to the heart rate sensor, other types of sensors can also be set on the seat, such as the seat back or the seat headrest, which is not limited in this application. In addition, the sensor not set on the seat can also transmit data to the intelligent cockpit control module 1 without going through the seat control module 2.

[0102] In other embodiments, the data acquisition module 3 is also used to collect image data of the occupants, such as images or videos. Accordingly, the data acquisition module 3 also includes a vehicle-mounted camera, which is not limited in this application. Exemplarily, the intelligent cockpit control module 1 determines whether to trigger an alarm by analyzing the physiological indicator data and / or image data of the occupants.

[0103] The combined antenna 4 is used to receive satellite signals so as to locate the real-time position of the vehicle.

[0104] In other embodiments, the intelligent cockpit control module 1 includes: a positioning submodule 11, a wireless communication submodule 12 and a user identification submodule 1. Among them, the positioning submodule 11 is connected to the combined antenna 4 in a serial port connection mode for processing positioning data. The wireless communication submodule 12 is connected to a communication base station, and the communication base station is connected to a router via an optical fiber, and the router is connected to a cloud server 7 via an optical fiber. Among them, the cloud server 7 is used to receive the positioning data sent by the intelligent cockpit control module 1 and the collected data about the occupants, such as physiological indicator data, which will be permanently stored in the cloud server.

[0105] The vehicle safety management solution provided in the embodiment of the present application is described in detail below through the following implementation method.

[0106] Figure 2 is a flow chart of a vehicle safety management method provided by an embodiment of the present application. The execution subject of the method is a vehicle, such as Figure 1 The smart cockpit control module in the smart cockpit system shown in Figure 1. Figure 2 The method flow includes:

[0107] 201. The intelligent cockpit control module obtains physiological index data and image data of passengers.

[0108] In the embodiment of the present application, the above-mentioned passenger can be either a driver or a passenger, and the present application does not limit this. In addition, in addition to the physiological index data, the image data of the passenger can also be obtained through the vehicle camera. Among them, the image data includes but is not limited to images or videos, etc., and the present application does not limit this. In addition, the number of sensors of the same type can be one or more, and the present application also does not limit this.

[0109] In some embodiments, obtaining physiological indicator data of the passenger includes at least one of the following:

[0110] 2011. Based on the sensor placed on the seat back, physiological index data is obtained. For example, the heart rate value of the driver is obtained through the heart rate sensor placed on the seat back.

[0111] 2012. Obtain physiological index data based on sensors placed on the seat headrest. For example, obtain the heart rate value of the passenger through a heart rate sensor placed on the seat headrest.

[0112] 2013. Based on the sensor placed on the steering wheel, physiological index data is obtained. For example, the breathing rate sensor placed on the steering wheel is used to obtain the driver's breathing rate.

[0113] 2014. Obtain physiological index data based on sensors placed on the rearview mirror inside the car. For example, obtain the heart rate values ​​of all people in the car through a heart rate sensor placed on the rearview mirror inside the car.

[0114] 202. The intelligent cockpit control module determines the health status of the passenger based on the passenger's physiological indicator data.

[0115] In some embodiments, the health status of the passenger is determined based on the passenger's physiological indicator data, including but not limited to the following methods:

[0116] First, based on the physiological index data of the passenger, the change trend of the physiological index of the passenger is determined, such as the change trend of the heart rate or the change trend of the blood pressure.

[0117] Next, the preliminary health status of the passengers is determined based on the normal value range of each physiological indicator and the determined change trend of the physiological indicators.

[0118] Taking heart rate as an example, the normal range of heart rate is generally 60-100 beats / minute. If the monitored heart rate is less than 60 beats / minute or greater than 100 beats / minute, it is determined that the passenger may have an abnormal heart rate. Next, by analyzing the passenger's heart rate data over a period of time, health abnormalities can be predicted more accurately. For another example, assuming that the passenger's heart rate gradually increases during the ride, even if the monitored heart rate is still within the normal range, it may be the body's response to some underlying factor. Therefore, it may be necessary to continue to pay attention to the passenger's heart rate changes in the future.

[0119] In addition to the physiological indicators themselves, other dimensions of the passenger's data can also be combined to comprehensively judge their health status. For example, the passenger's electronic health record can be obtained, and then based on the passenger's electronic health record, the passenger's initial health status can be corrected to obtain the passenger's final health status. For example, a passenger with a history of heart disease may need to be treated more cautiously even if his heart rate is only slightly elevated.

[0120] It should be noted that in addition to the health status of the passengers, the intelligent cockpit control module can also combine other factors to make more accurate warnings, as shown in the following steps 203-206.

[0121] 203. If the determined health status indicates that the occupant has health abnormalities, the intelligent cockpit control module performs emotion recognition and posture detection on the occupant based on the image data of the occupant to obtain emotion recognition results and posture detection results.

[0122] In some embodiments, emotion recognition is implemented based on facial expression analysis, including two steps: feature extraction and expression classification. For feature extraction, the key features of the face are first extracted, such as the shape and position of the eyes, eyebrows, and mouth. Next, the expression classification stage is entered. For expression classification, it is used to match the extracted facial features with known expression patterns. Among them, expression categories include but are not limited to happiness, sadness, anger, surprise, disgust or fear, etc., which are not limited in this application. In addition, expression classification can be implemented based on deep learning technology. By training the deep learning model with a large number of annotated facial expression images, the deep learning model can learn the characteristic patterns of different expressions, and then obtain an expression classification model. The trained expression classification model can perform expression classification on newly input facial images.

[0123] In other embodiments, posture detection is implemented based on a binocular vision method, including two steps: depth information extraction and 3D posture reconstruction. For depth information extraction, the same scene is photographed from different angles by two or more vehicle-mounted cameras. Using the principle of triangulation, the depth information is calculated based on the parallax of corresponding points in the captured image. Depth information can help more accurately locate the position and posture of the human body in three-dimensional space. For example, by obtaining the distance between each part of the human body and the camera, the degree of inclination and bending of the human body can be better judged. For 3D posture reconstruction, the 3D posture of the human body can be reconstructed by combining the extracted depth information and key point positioning. By processing human body images from multiple perspectives, the 2D key point information can be converted into coordinates in three-dimensional space, thereby more comprehensively analyzing the human body posture.

[0124] 204. The intelligent cockpit control module determines an alarm method that matches the health status, emotion recognition results, and posture detection results of the passenger.

[0125] In some embodiments, determining an alarm method that matches the health status, emotion recognition result, and posture detection result of the passenger includes, but is not limited to, the following methods:

[0126] A. Determine the first alarm mode that matches the health status.

[0127] Exemplarily, the alarm methods matching the health status include alarm methods corresponding to serious health abnormalities and alarm methods corresponding to potential health abnormalities, which is not limited in this application.

[0128] Among them, the alarm method corresponding to serious health abnormalities can be to initiate a call request to the service number, that is, to communicate directly with the customer service staff by voice to request the customer service staff to rescue the vehicle. At the same time, the vehicle can also send information including vehicle positioning data and the current health status of the passengers to the cloud server, which is not limited in this application.

[0129] In addition, the warning method corresponding to potential health abnormalities can be to remind passengers to pay attention to their physical conditions through a loudspeaker, which is not limited in this application.

[0130] B. Determine a second alarm method that matches the emotion recognition result.

[0131] Exemplarily, the alarm mode that matches the emotion recognition result may be an alarm mode corresponding to an out-of-control emotion state and an alarm mode corresponding to a negative emotion state.

[0132] Among them, the warning method corresponding to serious health abnormalities can be voice comfort to the passengers through a speaker, automatically reducing the vehicle's speed, sounding an alarm or automatically locking the doors, etc. This application does not limit this.

[0133] In addition, the warning method corresponding to the negative emotional state can be playing soothing music through a speaker or using voice prompts to improve the mood.

[0134] C. Determine a third alarm mode that matches the posture detection result.

[0135] Exemplarily, the warning modes matched with the posture detection results include warning modes corresponding to abnormal postures and warning modes corresponding to bad postures.

[0136] Among them, the warning method corresponding to abnormal posture (such as a large body tilt) can be to sound an alarm through a speaker, control the vehicle to stop in a safe area and put it in a parking state, and this application does not limit this. In addition, the warning method corresponding to a bad posture can be to give a voice prompt to the passenger through a speaker or a display screen.

[0137] D. The alarm method with the highest alarm level among the first alarm method, the second alarm method and the third alarm method is used as the final alarm method.

[0138] In other embodiments, in addition to the above methods, weights can be set for health status, emotion recognition results, and posture detection results. Exemplarily, the health status corresponds to the first weight, the emotion recognition result corresponds to the second weight, and the posture detection result corresponds to the third weight, wherein the third weight < the second weight < the first weight, and the sum of the three weights is 1. Afterwards, based on the first weight, the second weight, and the third weight, the alarm level corresponding to the first alarm method, the alarm level corresponding to the second alarm method, and the alarm level corresponding to the third alarm method are weighted respectively, and the alarm method indicated by the weighted alarm level is used as the final alarm method, which is not limited in this application.

[0139] 205. The intelligent cockpit control module determines the vehicle control mode based on the current driving environment data and the passenger's position.

[0140] In some embodiments, the vehicle control mode is determined based on the current driving environment data and the riding position of the passengers, including: determining the vehicle control mode based on the current in-vehicle driving environment data, out-of-vehicle driving environment data and the riding position of the passengers.

[0141] The external driving environment data includes but is not limited to traffic congestion data, weather data, etc., and the internal driving environment data includes but is not limited to temperature, humidity, etc., which are not limited in this application. In addition, the riding position includes the driving position and the non-driving position.

[0142] 206. The intelligent cockpit control module controls the vehicle based on the determined vehicle control mode, and executes an alarm operation that matches the determined alarm mode.

[0143] In some embodiments, controlling the vehicle based on the determined vehicle control method includes at least one of the following:

[0144] 1. Control the vehicle's speed;

[0145] 2. Control the safe driving distance of vehicles;

[0146] 3. Control the vehicle’s posture; in order to provide passengers with a comfortable riding experience, the vehicle can adjust its posture according to the passenger’s position and driving environment. In addition, the position of the passenger will also be considered during emergency braking or avoidance. For example, during emergency braking, the braking force will be reasonably distributed according to the passenger’s position and weight distribution to prevent the vehicle from skidding or tailspinning, thus ensuring the safety of the passenger.

[0147] 4. Control the vehicle to stop in a safe area and keep it parked.

[0148] In some other embodiments, executing an alarm operation that matches the determined alarm mode includes at least one of the following:

[0149] 1. Execute the first warning operation in the car through the car speaker;

[0150] Among them, the first alarm operation can be to sound an alarm, play a voice prompt or play music, etc., which is not limited in this application.

[0151] 2. Perform a second warning operation outside the vehicle through the vehicle speaker;

[0152] Among them, the second alarm operation can be to control the external lighting component to turn on the flashing mode, sound an alarm or play a voice prompt to attract the attention of surrounding pedestrians or vehicles.

[0153] 3. Execute the third alarm operation through the display screen;

[0154] Among them, the third alarm operation can be displaying a warning icon or warning text on the display screen, etc., which is not limited in this application.

[0155] 4. Initiate a call request to the service number, that is, directly communicate with the customer service staff by voice to request the customer service staff to rescue the vehicle.

[0156] 5. Initiate a call request to a pre-set contact number. The contact number here can be set by the car owner, and this application does not limit this.

[0157] In other embodiments, in addition to uploading the vehicle's positioning data to the cloud server, at least one of the passenger's physiological indicator data, image data, health status, emotion recognition results, or posture detection results may also be uploaded to the cloud server, but this application does not limit this.

[0158] The embodiment of the present application realizes multi-dimensional status determination of the occupants by collecting physiological indicator data and image data of the occupants. For example, the health status of the occupants can be determined based on the physiological indicator data. For another example, the emotional state of the occupants can be identified based on the image data and the posture detection of the occupants can be performed. And through the health status, emotional state and current posture of the occupants, it can be analyzed whether there is an unexpected situation for the occupants and corresponding measures can be taken. For example, the alarm mode is determined based on the analysis results and the alarm operation matching the alarm mode is executed. In addition, the embodiment of the present application can also determine the vehicle control mode based on the driving environment data and the riding position of the occupants, and then control the vehicle based on the determined vehicle control mode. This safety management solution can effectively ensure the safety of the occupants and vehicles, and significantly improve driving safety.

[0159] Figure 3 is a schematic diagram of the structure of a vehicle safety management device provided in an embodiment of the present application. Figure 3 , the device comprises:

[0160] An acquisition module 301 is configured to acquire physiological index data and image data of a passenger;

[0161] A first determination module 302 is configured to determine the health status of the passenger based on the physiological indicator data;

[0162] The processing module 303 is configured to, if the health status indicates that the passenger has health abnormalities, perform emotion recognition and posture detection on the passenger based on the image data of the passenger to obtain an emotion recognition result and a posture detection result;

[0163] The second determination module 304 is configured to determine an alarm mode that matches the health status, emotion recognition result and posture detection result of the passenger;

[0164] The third determination module 305 is configured to determine the vehicle control mode based on the current driving environment data and the riding position of the riding object;

[0165] The safety management module 306 is configured to control the vehicle based on the vehicle control mode and execute an alarm operation matching the alarm mode.

[0166] The embodiment of the present application realizes multi-dimensional status determination of the occupants by collecting physiological indicator data and image data of the occupants. For example, the health status of the occupants can be determined based on the physiological indicator data. For another example, the emotional state of the occupants can be identified based on the image data and the posture detection of the occupants can be performed. And through the health status, emotional state and current posture of the occupants, it can be analyzed whether there is an unexpected situation for the occupants and corresponding measures can be taken. For example, the alarm mode is determined based on the analysis results and the alarm operation matching the alarm mode is executed. In addition, the embodiment of the present application can also determine the vehicle control mode based on the driving environment data and the riding position of the occupants, and then control the vehicle based on the determined vehicle control mode. This safety management solution can effectively ensure the safety of the occupants and vehicles, and significantly improve driving safety.

[0167] In some embodiments, the acquisition module is configured to perform at least one of the following:

[0168] Acquiring the physiological index data based on a sensor placed on a seat back;

[0169] Acquiring the physiological index data based on a sensor placed on a seat headrest;

[0170] Acquiring the physiological index data based on a sensor placed on the steering wheel;

[0171] The physiological index data is obtained based on a sensor placed on the rearview mirror inside the vehicle.

[0172] In some other embodiments, the first determining module is configured to:

[0173] Determining a change trend of the physiological index of the passenger based on the physiological index data;

[0174] Determining the preliminary health status of the passenger based on the normal value range of each physiological indicator and the change trend of the physiological indicator;

[0175] Obtaining the electronic health record of the passenger;

[0176] Based on the electronic health record, the preliminary health status of the passenger is corrected to obtain the final health status of the passenger.

[0177] In some other embodiments, the second determining module is configured to:

[0178] Determining a first alarm mode matching the health status;

[0179] Determining a second alarm mode that matches the emotion recognition result;

[0180] Determining a third alarm mode that matches the posture detection result;

[0181] The alarm mode with the highest alarm level among the first alarm mode, the second alarm mode and the third alarm mode is used as the final alarm mode.

[0182] In some other embodiments, the third determining module is configured to:

[0183] The vehicle control mode is determined based on current in-vehicle driving environment data, out-vehicle driving environment data and the riding position of the riding object.

[0184] In some other embodiments, the security management module is configured to perform at least one of the following:

[0185] Controlling the driving speed of the vehicle;

[0186] Performing safe driving distance control on the vehicle;

[0187] performing posture control on the vehicle;

[0188] The vehicle is controlled to stop in a safe area and maintain a parking state.

[0189] In some other embodiments, the security management module is configured to perform at least one of the following:

[0190] Performing a first warning operation in the vehicle through the vehicle speaker;

[0191] Performing a second warning operation outside the vehicle through the vehicle-mounted speaker;

[0192] Execute the third alarm operation through the display screen;

[0193] Initiate a call request to the service number;

[0194] Initiate a call request to the pre-set contact number.

[0195] In some other embodiments, the device further comprises:

[0196] An upload module, configured to upload the vehicle positioning data to a cloud server;

[0197] The uploading module is further configured to upload at least one of the physiological indicator data, image data, health status, emotion recognition results or posture detection results of the passenger to the cloud server.

[0198] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described one by one here.

[0199] It should be noted that: the vehicle safety management device provided in the above embodiment only uses the division of the above functional modules as an example to illustrate when performing safety management on the vehicle. In actual applications, the above 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. In addition, the vehicle safety management provided in the above embodiment and the vehicle safety management method embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0200] Figure 4 It is a structural diagram of a smart cockpit domain controller provided according to an embodiment of the present application.

[0201] Typically, the smart cockpit domain controller 400 includes: a main control module 401, a CAN interface 402, a hard-line input interface 403, and a hard-line output interface 404. The main control module 401 is connected to the CAN interface 402, the hard-line input interface 403, and the hard-line output interface 404, respectively.

[0202] The main control module 401 generally includes a processor and a memory. The processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array).

[0203] The processor may also include a main processor and a coprocessor. The main processor is a processor used to process data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor used to process data in the standby state.

[0204] In some embodiments, the processor may be integrated with a GPU (Graphics Processing Unit), and the GPU is responsible for rendering and drawing the content that needs to be displayed on the vehicle display screen.

[0205] In other embodiments, the processor may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning. The memory may include one or more computer-readable storage media, which may be non-transitory. The memory may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices, flash memory storage devices.

[0206] In other embodiments, the non-transitory computer-readable storage medium in the memory is used to store at least one program code, and the at least one program code is used to be executed by the processor to implement the vehicle safety management method provided by the method embodiment in the embodiment of the present application.

[0207] The hard-line input interface 403 is used to receive hard-line control signals, and the hard-line output interface 404 is used to send control instructions.

[0208] Those skilled in the art will understand that Figure 4 The structure shown in the figure does not constitute a limitation on the smart cockpit domain controller 400, and may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0209] The embodiment of the present application also provides a computer-readable storage medium, such as a memory including a program code, and the program code can be executed by a processor in the smart cockpit domain controller to complete the above-mentioned vehicle safety management method. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device.

[0210] An embodiment of the present application also provides a computer program product or a computer program, which includes a computer program code, and the computer program code is stored in a computer-readable storage medium. The processor of the smart cockpit domain controller reads the computer program code from the computer-readable storage medium, and the processor executes the computer program code, so that the smart cockpit domain controller executes the above-mentioned vehicle safety management method.

[0211] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0212] The above description is only an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A vehicle safety management method, characterized in that: The method comprises: Acquiring physiological index data and image data of passengers; Determining the health status of the passenger based on the physiological indicator data; If the health status indicates that the passenger has health abnormalities, based on the image data of the passenger, respectively, emotion recognition and posture detection are performed on the passenger to obtain an emotion recognition result and a posture detection result; Determining an alarm mode that matches the health status, emotion recognition result, and posture detection result of the passenger; Determining a vehicle control method based on current driving environment data and the riding position of the riding object; The vehicle is controlled based on the vehicle control mode, and an alarm operation matching the alarm mode is executed.

2. The method according to claim 1, characterized in that The step of obtaining physiological index data of the passenger includes at least one of the following: Acquiring the physiological index data based on a sensor placed on a seat back; Acquiring the physiological index data based on a sensor placed on a seat headrest; Acquiring the physiological index data based on a sensor placed on the steering wheel; The physiological index data is obtained based on a sensor placed on the rearview mirror inside the vehicle.

3. The method according to claim 1, characterized in that The determining the health status of the passenger based on the physiological indicator data includes: Determining a change trend of the physiological index of the passenger based on the physiological index data; Determining the preliminary health status of the passenger based on the normal value range of each physiological indicator and the change trend of the physiological indicator; Obtaining the electronic health record of the passenger; Based on the electronic health record, the preliminary health status of the passenger is corrected to obtain the final health status of the passenger.

4. The method according to claim 1, characterized in that The determining of an alarm mode that matches the health status, emotion recognition result, and posture detection result of the passenger includes: Determining a first alarm mode matching the health status; Determining a second alarm mode that matches the emotion recognition result; Determining a third alarm mode that matches the posture detection result; The alarm mode with the highest alarm level among the first alarm mode, the second alarm mode and the third alarm mode is used as the final alarm mode.

5. The method according to claim 1, characterized in that The determining of the vehicle control mode based on the current driving environment data and the riding position of the riding object includes: The vehicle control mode is determined based on current in-vehicle driving environment data, out-vehicle driving environment data and the riding position of the riding object.

6. The method according to claim 1, characterized in that The performing of vehicle control based on the vehicle control method includes at least one of the following: Controlling the driving speed of the vehicle; Performing safe driving distance control on the vehicle; performing posture control on the vehicle; The vehicle is controlled to stop in a safe area and maintain a parking state.

7. The method according to claim 1, characterized in that The performing of the alarm operation matching the alarm mode includes at least one of the following: Performing a first warning operation in the vehicle through the vehicle speaker; Performing a second warning operation outside the vehicle through the vehicle-mounted speaker; Execute the third alarm operation through the display screen; Initiate a call request to the service number; Initiate a call request to the pre-set contact number.

8. The method according to any one of claims 1 to 7, characterized in that The method further comprises: Upload vehicle positioning data to the cloud server; Upload at least one of the physiological indicator data, image data, health status, emotion recognition result or posture detection result of the passenger to the cloud server.

9. A vehicle safety management device, characterized in that: The device comprises: An acquisition module, configured to acquire physiological index data and image data of a passenger; A first determination module is configured to determine the health status of the passenger based on the physiological indicator data; a processing module configured to, if the health status indicates that the passenger has health abnormalities, perform emotion recognition and posture detection on the passenger based on the image data of the passenger to obtain an emotion recognition result and a posture detection result; A second determination module is configured to determine an alarm mode that matches the health status, emotion recognition result, and posture detection result of the passenger; A third determination module is configured to determine a vehicle control mode based on current driving environment data and a riding position of the riding object; The safety management module is configured to control the vehicle based on the vehicle control method and execute an alarm operation matching the alarm method.

10. An intelligent cockpit domain controller, characterized in that: The smart cockpit domain controller includes a main control module, which includes a processor and a memory. The memory is used to store at least one program code, and the at least one program code is loaded by the processor and executes the vehicle safety management method according to any one of claims 1 to 8.

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