Automobile drunk driving automatic monitoring method and related equipment

Abstract

The invention discloses an automobile drunk driving automatic monitoring method and related equipment, relates to the field of drunk driving monitoring, and mainly aims to solve the problem that current automobile drunk driving automatic monitoring is not intelligent and accurate enough. The method comprises the following steps: acquiring driver seat personnel information and alcohol content information; determining light reflection data of pupils of the driver under the condition that alcohol is fed back to exceed the standard according to the driver seat personnel information and the alcohol content information; and determining the drunk driving state of the driver based on the light reflection data of the pupil of the driver. The method is used for the automobile drunk driving automatic monitoring process.

Description

Technical Field

[0001] The present invention relates to the field of drunk driving monitoring, and in particular to an automatic drunk driving monitoring method and related equipment. Background Art

[0002] Currently, drunk driving detection mainly relies on traffic police setting up drunk driving monitoring points at specific locations to conduct breath alcohol tests on passing drivers. Drivers may evade detection by refusing to cooperate or taking other means, increasing the risk of drunk driving; on the other hand, traffic police on-site enforcement cannot cover all roads and time periods, and there may be cases of missed detection. Summary of the invention

[0003] In view of the above problems, the present invention provides a method and related equipment for automatic monitoring of drunk driving by automobile, the main purpose of which is to solve the problem that the current automatic monitoring of drunk driving by automobile is not intelligent and accurate enough.

[0004] In order to solve at least one of the above technical problems, in a first aspect, the present invention provides a method for automatically monitoring drunk driving, the method comprising:

[0005] Obtain driver's seat information and alcohol content information;

[0006] When the driver's seat occupant information and the alcohol content information indicate that the alcohol level exceeds the limit, determining the driver's pupil light reflex data;

[0007] The driver's drunk driving status is determined based on the driver's pupil light reflection data.

[0008] Optionally, the step of obtaining the driver's seat information and alcohol content information includes:

[0009] Real-time monitoring of driver's seat information;

[0010] When the driver's seat occupancy information is detected, the driver's seat occupant information within the preset range of the steering wheel is obtained;

[0011] When the driver's seat occupant information is that there is only one person, the alcohol content information of the gas within a preset range of the steering wheel is detected.

[0012] Optionally, when the driver's seat occupant information is one person, detecting the alcohol content information of the gas within a preset range of the steering wheel includes:

[0013] When the driver's seat occupant information is that there is only one person, the alcohol content information of the gas within a preset range of the steering wheel is detected based on non-dispersive infrared gas detection technology.

[0014] Optionally, the pupil light reflection data includes pupil contraction and dilation speeds, and when the driver's seat occupant information and the alcohol content information feedback that the alcohol content exceeds the standard, determining the driver's pupil light reflection data includes:

[0015] Determine the driver's pupil area;

[0016] Detecting the pupil area based on a Canny edge detection algorithm to extract a pupil boundary;

[0017] Performing Hough ellipse fitting on the pupil boundary to determine the pupil diameter;

[0018] The pupil diameter is monitored to determine the rate of pupil constriction and dilation.

[0019] Optionally, determining the driver's pupil area includes:

[0020] Obtaining a facial image of the driver;

[0021] The pupil is roughly located in the facial image by integral projection based on the following formula:

[0022]

[0023] Among them, IPF h is horizontal projection, IPF v is a vertical projection, p(x, y) is a point with coordinates (x, y) in the facial image, and the horizontal projection and the vertical projection are used for coarse pupil positioning;

[0024] The pupil rough positioning result is segmented by binarizing the image to determine the pupil area based on the following formula:

[0025]

[0026] Wherein, T is the segmentation processing threshold.

[0027] Optionally, detecting the pupil area based on a Canny edge detection algorithm to extract a pupil boundary includes:

[0028] Performing noise reduction processing on the pupil area based on the following Gaussian filter;

[0029]

[0030] The gradient and direction of each pixel in the pupil area are calculated based on the following Sobel operator:

[0031]

[0032]

[0033] Among them, the gradient strength M(x,y) is expressed as:

[0034]

[0035] The gradient direction θ is:

[0036] θ=arctan(G x / G y )

[0037] Mark edge points based on the gradient magnitude and the gradient direction;

[0038] The pupil boundary is extracted based on the joint result of the edge points.

[0039] Optionally, performing Hough ellipse fitting on the pupil boundary to determine the pupil diameter includes:

[0040] Extracting edge points of the pupil boundary to transform the coordinate axis parameter space;

[0041] Based on the parameters of the fitting target in the coordinate axis parameter space, wherein the parameters of the fitting target are the parameters corresponding to the point with the largest cumulative value among the intersection points in the coordinate axis parameter space;

[0042] A pupil diameter is determined based on the parameters of the fitted target.

[0043] In a second aspect, an embodiment of the present invention further provides an automatic monitoring device for drunk driving, comprising:

[0044] An acquisition unit, used to acquire information about the driver and the alcohol content;

[0045] A first determination unit is used to determine the pupil light reflection data of the driver when the driver's seat occupant information and the alcohol content information feedback that the alcohol content exceeds the limit;

[0046] The second determination unit is used to determine the driver's drunk driving status based on the driver's pupil light reflection data.

[0047] In order to achieve the above-mentioned purpose, according to the third aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the above-mentioned program is executed by a processor, the steps of the above-mentioned method for automatic monitoring of drunk driving of a vehicle are implemented.

[0048] In order to achieve the above-mentioned purpose, according to the fourth aspect of the present invention, there is provided an electronic device, comprising at least one processor and at least one memory connected to the processor; wherein the above-mentioned processor is used to call the program instructions in the above-mentioned memory to execute the steps of the above-mentioned method for automatic monitoring of drunk driving of a vehicle.

[0049] Through the above technical scheme, the automatic monitoring method and related equipment for drunk driving provided by the present invention solve the problem that the current automatic monitoring of drunk driving is not intelligent and accurate enough. The present invention obtains the information of the driver and the alcohol content information; when the information of the driver and the alcohol content information feedback that the alcohol exceeds the standard, the driver's pupil light reflection data is determined; the driver's drunk driving status is determined based on the driver's pupil light reflection data. In the above scheme, the alcohol content in the airflow is detected, and the driver's exhaled gas is monitored in real time. In the case of suspected drunk driving, the driver's facial features and behaviors are captured and analyzed in real time through high-definition cameras and image recognition technology, and the driver is judged whether he is drunk driving based on PLR (pupil light reflex). This method does not require the cooperation of the driver and can be carried out without the driver's knowledge. Therefore, the air sensor is combined with the driver monitoring system to achieve efficient judgment of whether the driver is drunk driving in the car.

[0050] Correspondingly, the automatic automobile drunk driving monitoring device, equipment and computer-readable storage medium provided in the embodiments of the present invention also have the above-mentioned technical effects.

[0051] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0053] Figure 1 A schematic diagram of a process flow of an automatic monitoring method for drunk driving of a vehicle provided by an embodiment of the present invention is shown;

[0054] Figure 2 A schematic block diagram showing the composition of an automatic monitoring device for drunk driving of a vehicle provided by an embodiment of the present invention is shown;

[0055] Figure 3 A schematic block diagram of the composition of an electronic device for automatically monitoring drunk driving in a car provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0056] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to enable the scope of the present invention to be fully communicated to those skilled in the art.

[0057] In order to solve the problem that the current automatic monitoring of drunk driving is not intelligent and accurate enough, the embodiment of the present invention provides an automatic monitoring method for drunk driving, such as Figure 1 As shown, the method includes:

[0058] S101, obtaining driver's seat information and alcohol content information;

[0059] The above step S101 further includes S1011:

[0060] Real-time monitoring of driver's seat occupancy information; when the driver's seat occupancy information is monitored, obtaining driver's seat occupant information within a preset range of the steering wheel; when the driver's seat occupant information is that there is one person, detecting the alcohol content information of the gas within a preset range of the steering wheel.

[0061] For example, the driver monitoring system is first used to determine whether the driver is in the driving seat and is the only person near the steering wheel, that is, to determine whether the prerequisite for drunk driving monitoring is met, to avoid the situation where someone else exhales on behalf of the driver to deceive the sensor and cause a misjudgment.

[0062] Specifically, it determines whether there is only one person at the gas collection point. If no one is detected, it will prompt "no one driving"; if more than one person is detected at the steering wheel, it will prompt "multiple driving" to prevent others from replacing alcohol testing.

[0063] It is understandable that the above-mentioned operation of monitoring the seating information of the driver's seat can be carried out through technologies such as infrared sensors, radars or gravity sensors, and the information of the driver's seat occupant within the preset range of the above-mentioned steering wheel can also be obtained through technologies such as infrared sensors, radars, etc., which will not be elaborated here.

[0064] Based on the above solution, the driver's alcohol intake can be detected in real time and actively. Once the driver enters the vehicle and starts driving, the device can start working immediately, and can identify the potential risk of drunk driving in time, so as to take corresponding measures.

[0065] The above step S1011 further includes S1011:

[0066] When the driver's seat occupant information is that there is only one person, the alcohol content information of the gas within a preset range of the steering wheel is detected based on non-dispersive infrared gas detection technology.

[0067] Exemplarily, the present application collects the breath exhaled by the driver by arranging an air sensor next to the steering column of the steering wheel, and monitors the alcohol content in the airflow in real time by using non-dispersive infrared gas detection technology.

[0068] It is understandable that non-dispersive infrared gas detection technology is based on the principle of infrared spectroscopy. The infrared light source in the sensor emits infrared light of a specific wavelength. When these lights pass through the airflow, the light intensity will be weakened due to the absorption of gas molecules. The concentration of alcohol in the gas is determined based on the absorption rate. Compared with traditional breath alcohol detection, it has higher sensitivity and accuracy.

[0069] Furthermore, when the sensor detects that the alcohol content in the driver's exhaled gas exceeds the standard, it will be combined with the driver monitoring system to determine whether the driver is driving under the influence of alcohol.

[0070] S102, when the driver's seat occupant information and the alcohol content information feedback that the alcohol content exceeds the limit, determining the driver's pupil light reflection data;

[0071] The driver monitoring system consists of multiple high-definition cameras in the car. Through high-definition cameras and image recognition technology, the driver's facial features and behaviors are captured and analyzed in real time. When the driver shows typical symptoms of drunk driving such as blurred eyes and slow reaction, the system can quickly identify and make corresponding judgments. PLR (Pupillary Light Reflex) is the focus of system monitoring. It uses the natural reaction of the pupil under light stimulation to indirectly infer the possibility of alcohol content in the driver's body. Under normal circumstances, when light shines on the eyes, the pupil will automatically adjust its size according to the intensity of the light. This is a natural physiological reaction of the human body, called pupillary light reflex (PLR). However, when the human body ingests alcohol, alcohol affects the nervous system, including the regulation mechanism of pupillary light reflex. After drinking, the driver's pupil's sensitivity to light reflex may decrease, that is, the pupil's reaction to light stimulation will become slow or not obvious. Combined with the driver's facial features and behavioral performance, it is judged whether he is drunk driving.

[0072] Based on the above scheme, an air sensor and a driver monitoring system are used to combine judgment to monitor the alcohol content in the driver's exhaled gas and the driver's pupil state and behavior in real time. The two systems work together, which makes the method more accurate in judging drunk driving behavior and can avoid the influence of external factors in various scenarios, such as when the occupants of the car drink a lot of alcohol or the driver uses alcohol hand sanitizer.

[0073] The present applicant has considered that PLR monitoring uses an infrared lens to capture the pupil. Under infrared light imaging, the edge information of the pupil area is obvious, is not easily disturbed by ambient light, and has a more stable imaging effect.

[0074] Exemplarily, the pupil light reflex data includes pupil contraction and dilation speeds.

[0075] The above step S102 further includes S1021:

[0076] S1021. Determine the driver's pupil area, including:

[0077] Obtaining a facial image of the driver;

[0078] The pupil is roughly located in the facial image by integral projection based on the following formula:

[0079]

[0080]

[0081] Among them, IPF h is horizontal projection, IPF v is a vertical projection, p(x, y) is a point with coordinates (x, y) in the facial image, and the horizontal projection and the vertical projection are used for coarse pupil positioning;

[0082] The pupil rough positioning result is segmented by binarizing the image to determine the pupil area based on the following formula:

[0083]

[0084] Wherein, T is the segmentation processing threshold.

[0085] Based on the above scheme, the collected facial image of the driver is preprocessed, and the pupil position in the image is roughly located using integral projection (i.e., the sum of the grayscale values ​​of the pixels in each row and column in the horizontal and vertical directions is calculated as the projection curve function value).

[0086] In the infrared image, the grayscale value of the pupil area is low, while the grayscale values ​​of other areas are high. Based on this, it can be known that the grayscale sum of the row or column where the pupil is located is smaller than the surrounding background, thereby locating the pupil.

[0087] After obtaining the located area, the pupil area is segmented from the image through binary segmentation. That is, by selecting a threshold T, the entire image or target area is processed, and the values ​​greater than the threshold are set to 255, and the values ​​less than the threshold are set to 0.

[0088] This helps locate the pupil area, and then monitors the change in pupil diameter, calculates the speed of pupil contraction and expansion, and obtains the sensitivity of pupil to light reflection, so as to analyze whether the driver is driving under the influence of alcohol. If the driver monitoring system determines that the driver is at risk of driving under the influence of alcohol, the system will issue an alarm to remind the driver to stop the car as soon as possible.

[0089] S1022, detecting the pupil area based on a Canny edge detection algorithm to extract a pupil boundary, including:

[0090] Performing noise reduction processing on the pupil area based on the following Gaussian filter;

[0091]

[0092] The gradient and direction of each pixel in the pupil area are calculated based on the following Sobel operator:

[0093]

[0094]

[0095] Among them, the gradient strength M(x,y) is expressed as:

[0096]

[0097] The gradient direction θ is:

[0098] θ=arctan(G x / G y )

[0099] Mark edge points based on the gradient magnitude and the gradient direction;

[0100] The pupil boundary is extracted based on the joint result of the edge points.

[0101] Exemplarily, after the pupil area is determined based on binarization processing of the image, the Canny edge detection algorithm is used to extract the boundary, a Gaussian filter is first used for noise reduction, and then the Sobel operator is used to calculate the gradient and direction of each pixel in the image.

[0102] Furthermore, after obtaining the gradient strength and direction, non-maximum suppression is performed. That is, for each pixel M(x, y), check the adjacent pixels in the gradient direction. If the gradient strength of the current pixel is not the largest, it is marked as a non-edge point. Set two thresholds (high threshold TH and low threshold TL). For pixels with gradient strength greater than TH, they are directly marked as edge points; for pixels with gradient strength less than TL, they are directly marked as non-edge points; for pixels with gradient strength between the two thresholds, if they are connected to pixels marked as edge points, they are also marked as edge points, otherwise they are marked as non-edge points.

[0103] This helps locate the pupil boundary, and then monitors the change in pupil diameter, calculates the speed of pupil contraction and expansion, and obtains the sensitivity of pupil to light reflection, so as to analyze whether the driver is driving under the influence of alcohol. If the driver monitoring system determines that the driver is at risk of driving under the influence of alcohol, the system will issue an alarm to remind the driver to stop the car as soon as possible.

[0104] S1023, performing Hough ellipse fitting on the pupil boundary to determine the pupil diameter, including: extracting edge points of the pupil boundary to transform the coordinate axis parameter space; based on parameters of the fitting target in the coordinate axis parameter space, wherein the parameters of the fitting target are parameters corresponding to the point with the largest cumulative value among the intersections in the coordinate axis parameter space; determining the pupil diameter based on the parameters of the fitting target.

[0105] Finally, based on the edge detection results, Hough ellipse transform is used for fitting, that is, the edge points in the image space are converted to the parameter space with (B, C, D, E, F) as the coordinate axes, and then the parameters corresponding to the points with the largest cumulative values ​​in the intersection of the parameter space are extracted as the parameters of the target to be fitted, and the final pupil diameter is obtained.

[0106]

[0107] This helps determine the pupil diameter, which is then used to monitor changes in pupil diameter, calculate the speed of pupil contraction and dilation, and obtain the pupil's sensitivity to light reflection, thereby analyzing whether the driver is driving under the influence of alcohol. If the driver monitoring system determines that the driver is at risk of driving under the influence of alcohol, the system will sound an alarm to remind the driver to stop the car as soon as possible.

[0108] S103: Determine the drunk driving status of the driver based on the driver's pupil light reflection data.

[0109] By monitoring the changes in pupil diameter, calculating the speed of pupil contraction and dilation, and obtaining the sensitivity of pupil to light reflection, the driver can be analyzed to determine whether he is driving under the influence of alcohol. If the driver monitoring system determines that the driver is at risk of driving under the influence of alcohol, the system will sound an alarm to remind the driver to stop the car as soon as possible.

[0110] It is understandable that the algorithm of the above solution can further improve its accuracy and reliability through continuous iteration and upgrading. With the continuous advancement of technology and the continuous accumulation of data, the algorithm can improve its performance through learning and optimization to adapt to more complex and changing environments.

[0111] Through the above technical scheme, the automatic monitoring method for drunk driving of automobiles provided by the present invention solves the problem that the current automatic monitoring of drunk driving of automobiles is not intelligent and accurate enough. The present invention obtains the information of the person in the driver's seat and the information of the alcohol content; when the information of the person in the driver's seat and the information of the alcohol content feedback that the alcohol exceeds the standard, the driver's pupil light reflection data is determined; the driver's drunk driving status is determined based on the driver's pupil light reflection data. In the above scheme, the alcohol content in the airflow is detected, and the driver's exhaled gas is monitored in real time. In the case of suspected drunk driving, the driver's facial features and behaviors are captured and analyzed in real time through high-definition cameras and image recognition technology, and the driver is judged whether he is drunk driving based on PLR (pupil light reflex). This method does not require the cooperation of the driver and can be carried out without the driver's knowledge. Therefore, the air sensor is combined with the driver monitoring system to achieve efficient judgment of whether the driver is drunk driving in the car.

[0112] Furthermore, as a response to the above Figure 1 The embodiment of the present invention also provides an automatic monitoring device for drunk driving of a car, which is used to monitor the above Figure 1 The device embodiment corresponds to the aforementioned method embodiment. For ease of reading, this device embodiment will not repeat the details of the aforementioned method embodiment one by one, but it should be clear that the device in this embodiment can correspond to all the contents of the aforementioned method embodiment. Figure 2 As shown, the device includes: an acquisition unit 21, a first determination unit 22, and a second determination unit 23, wherein

[0113] An acquisition unit 21 is used to acquire driver's seat occupant information and alcohol content information;

[0114] The first determination unit 22 is used to determine the pupil light reflection data of the driver when the driver's seat occupant information and the alcohol content information feedback that the alcohol content exceeds the limit;

[0115] The second determining unit 23 is used to determine the

[0116] The driver's drunk driving status is determined based on the driver's pupil light reflection data.

[0117] The processor includes a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be set, and a method for automatically monitoring drunk driving can be implemented by adjusting kernel parameters, which can solve the problem that the current automatic monitoring of drunk driving is not intelligent and accurate enough.

[0118] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, and when the program is executed by a processor, the automatic monitoring method for drunk driving of a vehicle is implemented.

[0119] An embodiment of the present invention provides a processor, which is used to run a program, wherein the method for automatically monitoring drunk driving of a vehicle is executed when the program is running.

[0120] An embodiment of the present invention provides an electronic device, the electronic device comprising at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the above-mentioned automatic monitoring method for drunk driving of a vehicle

[0121] An embodiment of the present invention provides an electronic device 30, such as Figure 3 As shown, the electronic device includes at least one processor 301, and at least one memory 302 and a bus 303 connected to the processor; wherein the processor 301 and the memory 302 communicate with each other via the bus 303; the processor 301 is used to call the program instructions in the memory to execute the above-mentioned automatic monitoring method for drunk driving of a car.

[0122] The intelligent electronic devices in this article can be PCs, PADs, mobile phones, etc.

[0123] The present application also provides a computer program product, which, when executed on a process management electronic device, is suitable for executing a program that initializes the above-mentioned steps of the automatic monitoring method for drunk driving of a vehicle.

[0124] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0125] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0126] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0127] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0128] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0129] The present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device is caused to execute the following Figure 1 This corresponds to the flow of control of the memory in the embodiment.

[0130] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)), etc.

[0131] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0132] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, 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 an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0133] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0134] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0135] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0136] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for automatically monitoring drunk driving, characterized in that: include: Obtain driver's seat information and alcohol content information; When the driver's seat occupant information and the alcohol content information indicate that the alcohol level exceeds the limit, determining the driver's pupil light reflex data; The driver's drunk driving status is determined based on the driver's pupil light reflection data.

2. The method according to claim 1, characterized in that The obtaining of the driver's seat information and alcohol content information includes: Real-time monitoring of driver's seat information; When the driver's seat occupancy information is detected, the driver's seat occupant information within the preset range of the steering wheel is obtained; When the driver's seat occupant information is that there is only one person, the alcohol content information of the gas within a preset range of the steering wheel is detected.

3. The method according to claim 1, characterized in that When the driver's seat occupant information is one person, detecting the alcohol content information of the gas within a preset range of the steering wheel includes: When the driver's seat occupant information is that there is only one person, the alcohol content information of the gas within a preset range of the steering wheel is detected based on non-dispersive infrared gas detection technology.

4. The method according to claim 1, characterized in that: The pupil light reflection data includes pupil contraction and dilation speeds. When the driver's seat occupant information and the alcohol content information feedback that the alcohol content exceeds the standard, determining the driver's pupil light reflection data includes: Determine the driver's pupil area; Detecting the pupil area based on a Canny edge detection algorithm to extract a pupil boundary; Performing Hough ellipse fitting on the pupil boundary to determine the pupil diameter; The pupil diameter is monitored to determine the rate of pupil constriction and dilation.

5. The method according to claim 4, characterized in that Determining the driver's pupil area includes: Obtaining a facial image of the driver; The pupil is roughly located in the facial image by integral projection based on the following formula: Among them, IPF h is horizontal projection, IPF v is a vertical projection, p(x, y) is a point with coordinates (x, y) in the facial image, and the horizontal projection and the vertical projection are used for coarse pupil positioning; The pupil rough positioning result is segmented by binarizing the image to determine the pupil area based on the following formula: Wherein, T is the segmentation processing threshold.

6. The method according to claim 4, characterized in that The detecting the pupil area based on the Canny edge detection algorithm to extract the pupil boundary includes: Performing noise reduction processing on the pupil area based on the following Gaussian filter; The gradient and direction of each pixel in the pupil area are calculated based on the following Sobel operator: Among them, the gradient strength M(x,y) is expressed as: The gradient direction θ is: θ=arctane(G x / G y ) Mark edge points based on the gradient magnitude and the gradient direction; The pupil boundary is extracted based on the joint result of the edge points.

7. The method according to claim 4, characterized in that The performing Hough ellipse fitting on the pupil boundary to determine the pupil diameter comprises: Extracting edge points of the pupil boundary to transform the coordinate axis parameter space; Based on the parameters of the fitting target in the coordinate axis parameter space, wherein the parameters of the fitting target are the parameters corresponding to the point with the largest cumulative value among the intersection points in the coordinate axis parameter space; A pupil diameter is determined based on the parameters of the fitted target.

8. An automatic monitoring device for drunk driving, characterized in that: Also includes: An acquisition unit, used to acquire information about the driver and the alcohol content; A first determination unit is used to determine the pupil light reflection data of the driver when the driver's seat occupant information and the alcohol content information feedback that the alcohol content exceeds the limit; The second determination unit is used to determine the driver's drunk driving status based on the driver's pupil light reflection data.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the steps of the automatic monitoring method for drunk driving of a vehicle as claimed in any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: The electronic device includes at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the steps of the automatic monitoring method for drunk driving of a vehicle as described in any one of claims 1 to claim 7.

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