A driving safety detection method and device, electronic equipment and medium

Abstract

The application provides a driving safety detection method and device, electronic equipment and medium, the method comprises the following steps: in response to the starting signal of the vehicle, obtaining the pressure data, gravity data and foot image data of the main driving area of the vehicle, the pressure data is obtained by the pressure sensor arranged at the pedal, the gravity data is obtained by the gravity sensor arranged on the ground of the main driving area of the vehicle, and the foot image data is obtained by the camera arranged in the main driving area by shooting the area around the pedal; according to the pressure data, the pressure distribution borne by the pedal is identified, according to the gravity data, the weight borne on the ground of the main driving area is identified, and according to the foot image data, the contour feature of the driver's foot of the vehicle is identified; according to the pressure distribution, the weight and the contour feature, the driving safety warning is carried out for the vehicle. Through the application, the non-standard driving behavior of the driver is monitored and reminded, and the driving safety is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle driving detection, in particular to a driving safety detection method and device, an electronic device and a medium. BACKGROUND

[0002] Currently, non-standard driving behaviors of drivers, such as driving with high heels, seriously threaten road traffic safety. The existing technology mainly relies on two pressure sensors to determine whether the driver is wearing high heels, and accordingly sends a reminder.

[0003] However, this method has the risk of misjudgment, which affects the customer's driving experience. High heels can change the driver's foot support, affect brake and throttle control, and increase the risk of traffic accidents. SUMMARY

[0004] Therefore, the purpose of the present application is to provide a driving safety detection method, device, electronic device and medium, which aims to monitor and remind the non-standard driving behavior of the driver, so as to improve the driving safety.

[0005] In a first aspect, the present application provides a driving safety detection method, comprising: in response to a start signal of a vehicle, acquiring pressure data, gravity data and foot image data of a main driving area of the vehicle, the pressure data being obtained by a pressure sensor arranged at a pedal, the gravity data being obtained by a gravity sensor arranged on the ground of the main driving area of the vehicle, and the foot image data being obtained by a camera arranged in the main driving area by shooting the area around the pedal; identifying the pressure distribution borne by the pedal according to the pressure data, identifying the weight borne on the ground of the main driving area according to the gravity data, and identifying the contour feature of the driver's foot of the vehicle according to the foot image data; and performing driving safety warning for the vehicle according to the pressure distribution, the weight and the contour feature.

[0006] In a possible implementation, the pressure sensor includes a plurality of pressure sensors, which are distributed and arranged at the pedal, and the pressure data includes pressure values borne by a plurality of force detection points on the pedal collected by the plurality of pressure sensors, wherein the pressure distribution borne by the pedal is identified by: for each force detection point, determining the pressure value borne by the force detection point; determining the maximum pressure value and the minimum pressure value in the pressure values borne by all force detection points; and obtaining a pressure performance score according to the pressure values corresponding to all force detection points, the maximum pressure value and the minimum pressure value, the pressure performance score representing the pressure distribution borne by the pedal.

[0007] In one possible implementation, the weight borne on the ground in the driver's area is identified by comparing the gravity data with a preset gravity threshold to determine whether the gravity data is less than the preset gravity threshold; if the gravity data is less than the preset gravity threshold, the difference between the preset gravity threshold and the gravity data is quantified to obtain a gravity performance score, the gravity performance score representing the degree of difference between the gravity data and the preset gravity threshold.

[0008] In one possible implementation, the shape features of the driver's feet are identified by: preprocessing the foot image data to extract edge features from the foot image data; identifying the shape of the driver's feet based on the edge features; and comparing the foot shape with a pre-stored high-heeled shoe shape to obtain an image performance score, wherein the image performance score characterizes the degree of similarity between the shape of the driver's feet and the pre-stored high-heeled shoe shape.

[0009] In one possible implementation, the step of providing a driving safety warning for the vehicle based on the pressure distribution, the weight, and the shape characteristics includes: determining the probability value of the driver wearing high heels based on the obtained pressure performance score, gravity performance score, image performance score, and the dynamic weight values ​​corresponding to the pressure performance score, the gravity performance score, and the image performance score; if the probability value exceeds a warning threshold, then the vehicle is prohibited from starting, and a driving safety warning is issued on the vehicle's display terminal.

[0010] In one possible implementation, the dynamic weight values ​​corresponding to the pressure performance score, the gravity performance score, and the image performance score are calculated respectively using the following formulas:

[0011]

[0012] Among them, Dynamic Weight i This refers to the dynamic weight value corresponding to the i-th coefficient type, where the coefficient types include pressure coefficient type, gravity coefficient type, and image coefficient type, i is an index variable used to refer to the pressure coefficient type, the gravity coefficient type, and the image coefficient type, respectively, and s i For the performance score of the i-th coefficient type, ∑ i∈{G,P,I} s i The sum of performance scores for all coefficient types, where G is the gravity performance score, P is the pressure performance score, I is the image performance score, and ω is the sum of performance scores for all coefficient types. i This is the preset static base weight corresponding to the i-th coefficient type.

[0013] In a possible implementation, the preset gravity threshold is calculated by the following formula:

[0014] G t = βμ H + (1-β)μ N + γσ

[0015] wherein, G t is the preset gravity threshold, β is a preset weight factor, μ H is an average value of a plurality of first resultant acceleration amplitudes on the three axes of the gravity sensor when wearing high heels in the pre-acquired data, μ N is an average value of a plurality of second resultant acceleration amplitudes on the three axes of the gravity sensor when not wearing high heels in the pre-acquired data, γ is a preset positive scaling factor, and σ is an average value of a standard deviation of the plurality of first resultant acceleration amplitudes and a standard deviation of the plurality of second resultant acceleration amplitudes.

[0016] In a second aspect, the present application provides a driving safety detection device, which comprises: an acquisition module, configured to acquire pressure data, gravity data and foot image data of a main driving area of a vehicle in response to a start signal of the vehicle, the pressure data being obtained by a pressure sensor arranged at a pedal, the gravity data being obtained by a gravity sensor arranged on the ground of the main driving area of the vehicle, and the foot image data being obtained by a camera arranged in the main driving area by shooting the area around the pedal; an identification module, configured to identify a pressure distribution borne by the pedal according to the pressure data, identify a weight borne on the ground of the main driving area according to the gravity data, and identify an outline feature of a foot of a driver of the vehicle according to the foot image data; and a warning module, configured to perform driving safety warning for the vehicle according to the pressure distribution, the weight and the outline feature.

[0017] In a third aspect, the present application further provides an electronic device, which comprises a processor, a memory and a bus, the memory stores machine readable instructions executable by the processor, the processor and the memory communicate through the bus when the electronic device is running, and the machine readable instructions are executed by the processor to perform the steps of the above method.

[0018] In a fourth aspect, the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to perform the steps of the above method.

[0019] The application provides a driving safety detection method and device, electronic equipment and a medium. The method comprises the following steps: in response to a starting signal of a vehicle, acquiring pressure data, gravity data and foot image data of a main driving area of the vehicle. The pressure data is obtained by a pressure sensor arranged at a pedal. The gravity data is obtained by a gravity sensor arranged on the ground of the main driving area of the vehicle. The foot image data is obtained by a camera arranged in the main driving area by shooting the area around the pedal. According to the pressure data, the pressure distribution borne by the pedal is identified. According to the gravity data, the weight borne on the ground of the main driving area is identified. According to the foot image data, the contour feature of the foot of the driver of the vehicle is identified. According to the pressure distribution, the weight and the contour feature, a driving safety warning is given to the vehicle. Through the application, the non-standard driving behavior of the driver is monitored and reminded, and the driving safety is improved.

[0020] In order to make the above objectives, characteristics and advantages of the application more apparent, clear and easy to understand, the following preferred embodiments are specifically described below with reference to the attached drawings. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some of the embodiments of the application, and therefore should not be considered as a limitation to the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0022] Figure 1 The flow chart of the driving safety detection method provided by the embodiments of the application; Figure 2

[0024] The flow chart of the driving safety warning provided by the embodiments of the application; Figure 3

[0025] The structural schematic diagram of the driving safety detection device provided by the embodiments of the application; Figure 4 The structural schematic diagram of the electronic equipment provided by the embodiments of the application.

[0026] DETAILED DESCRIPTION

[0027] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the following will be combined with the accompanying drawings in the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, every other embodiment obtained by a person skilled in the art without creative work belongs to the scope protected by the present application.

[0027] Firstly, the application scenarios applicable to the present application are introduced. The present application can be applied to safe driving of a vehicle.

[0028] It is found through research that the existing technology for detecting whether a driver wears high heels mainly relies on two pressure sensors to monitor the pressure distribution of the soles of the driver, so as to serve as a basis for judging whether the driver wears high heels, and to issue a reminder to the driver accordingly.

[0029] However, this method has certain limitations in actual application, because the data of only two pressure sensors can not comprehensively and accurately reflect the sole condition of the driver. Specifically, since the sole design of high heels is special, the pressure distribution thereof is significantly different from that of flat shoes. However, if the driver wears high heels with a hard sole or a special design, or the weight of the driver, the stepping intensity and other factors change, errors can be caused in the data collected by the two pressure sensors, and thus a judgment error can be caused.

[0030] Based on this, the embodiments of the present application provide a driving safety detection method and device, electronic equipment and medium, aiming to monitor and remind the non-standard driving behavior of a driver, so as to improve driving safety.

[0031] Please refer to Figure 1 , Figure 1 The flowchart of a driving safety detection method provided by the embodiments of the present application is shown in FIG. 1. As shown in FIG. 1, the driving safety detection method provided by the embodiments of the present application comprises the following steps. Figure 1

[0032] S101, in response to a starting signal of a vehicle, acquiring pressure data, gravity data and foot image data of a main driving area of the vehicle.

[0033] ​Here, the start signal refers to a signal emitted when the vehicle is switched from a stationary state to a starting state, which can be a vehicle ignition signal or a start signal, the pressure data is obtained by a pressure sensor arranged at the pedal, the gravity data is obtained by a gravity sensor arranged on the ground in the main driving area of the vehicle, and the foot image data is obtained by a camera arranged in the main driving area by shooting the area around the pedal.

[0034] Specifically, the pressure sensor includes a plurality of pressure sensors, which are distributed at the pedal, and the pressure data includes the pressure values borne by a plurality of force detection points on the pedal collected by the plurality of pressure sensors. The foot image data can be used to identify the shape features of the driver's feet, such as the height of the heel and the shape of the sole, and the gravity data can be used to identify the total weight borne on the ground in the main driving area.

[0035] S102, according to the pressure data, identifying the pressure distribution borne by the pedal, according to the gravity data, identifying the weight borne on the ground in the main driving area, and according to the foot image data, identifying the shape features of the driver's feet of the vehicle.

[0036] In a possible implementation of the present application, the pressure distribution borne by the pedal can be identified by the following method: for each force detection point, determining the pressure value borne by the force detection point; determining the maximum pressure value and the minimum pressure value in all the pressure values borne by the force detection points; and obtaining a pressure performance score according to the pressure values corresponding to all the force detection points, the maximum pressure value and the minimum pressure value, the pressure performance score representing the pressure distribution borne by the pedal.

[0037] Here, each pressure sensor is placed at a specific position on the pedal, which is a force detection point, and the pressure sensor can accurately measure and record the pressure value at the detection point. In order to obtain comprehensive pressure distribution information on the pedal, multiple sensors are distributed at different positions on the pedal, and the selection of these positions is usually based on the use habit and force analysis of the pedal to ensure that key force points can be captured. When the pedal is subjected to pressure, each sensor will independently collect the pressure value of the detection point where it is located, and these pressure values can be used to analyze the force condition of the pedal, such as calculating the total pressure, average pressure or pressure distribution, etc.

[0038] Specifically, the pressure distribution borne by the pedal can be calculated by the following formula.

[0039]

[0040] wherein, is the pressure value corresponding to the i-th force detection point, The value of is [0, 1], which represents the i-th force detection point, p iwherein e is a very small positive number to avoid the error of division by zero when the maximum pressure value is equal to the minimum pressure value.

[0041] By analyzing the pressure values of all force detection points, a pressure distribution of the pedal can be obtained, and a pressure performance score P can be calculated according to the pressure distribution, wherein the pressure performance score P is in the range of [0, 1].

[0042] In a possible implementation of the present application, the weight borne on the ground in the main driving area can be identified by: comparing the gravity data with a preset gravity threshold to determine whether the gravity data is less than the preset gravity threshold; if the gravity data is less than the preset gravity threshold, quantitatively processing the difference between the preset gravity threshold and the gravity data to obtain a gravity performance score, wherein the gravity performance score is in the range of [0, 1], and the gravity performance score represents the difference between the gravity data and the preset gravity threshold; and if the gravity data is not less than the preset gravity threshold, adjusting the dynamic weight value corresponding to the subsequent gravity performance score to weaken the influence of gravity on safety detection.

[0043] Here, the preset gravity threshold is a threshold value calculated according to the pre-acquired data, and is used to distinguish the difference in gravity borne on the ground when wearing high heels and when not wearing high heels. The gravity performance score is a gravity quantitative index, and is used to represent the difference between the real-time gravity data and the preset gravity threshold. The higher the score, the greater the difference.

[0044] Specifically, the preset gravity threshold is calculated by the following formula:

[0045] G t = βμ H + (1-β)μ N + γσ

[0046] wherein G t is the preset gravity threshold, β is a preset weight factor, μ H is an average value of a plurality of first synthesized acceleration amplitudes on the three axes of the gravity sensor when wearing high heels in the pre-acquired data, reflecting the gravity characteristics borne on the ground when wearing high heels, μ N is an average value of a plurality of second synthesized acceleration amplitudes on the three axes of the gravity sensor when not wearing high heels in the pre-acquired data, reflecting the gravity characteristics borne on the ground when not wearing high heels, σ is an average value of the standard deviation of the plurality of first synthesized acceleration amplitudes and the standard deviation of the plurality of second synthesized acceleration amplitudes, reflecting the dispersion degree of the gravity data when wearing high heels and when not wearing high heels, and γ is a preset positive scaling factor, used to adjust the influence degree of the standard deviation σ in the threshold calculation.

[0047] In a possible implementation of the present application, the shape feature of the driver's foot can be identified by the following method: the foot image data is preprocessed to extract the edge feature in the foot image data; the driver's foot shape is identified according to the edge feature, and the foot shape is compared with the pre-stored high-heeled shoe shape to obtain an image performance score, which represents the similarity between the driver's foot shape and the pre-stored high-heeled shoe shape.

[0048] In a possible implementation of the present application, the method for identifying the shape feature of the driver's foot by image processing technology is as follows:

[0049] First, a data set containing various types of high-heeled shoes (such as thin heels, thick heels, slope heels, etc.) is constructed. In order to ensure the diversity and representativeness of the data set, a sufficient number of images are collected for each category, and these images are labeled in detail, including the type, color, and brand of the high-heeled shoes, so as to facilitate subsequent data processing and analysis.

[0050] Next, the collected foot image data is preprocessed, which includes converting the image to a grayscale image or performing color correction to improve the efficiency of subsequent processing; cropping, scaling, and other operations are performed on the image to remove unnecessary background or adjust the image size, making it more suitable for feature extraction. In the feature extraction stage, an edge detection algorithm is used to extract the edge features of the high-heeled shoes, which can clearly outline the contour of the high-heeled shoes. At the same time, texture analysis algorithms (such as gray level co-occurrence matrix, local binary pattern, etc.) can be applied to extract the texture features of the high-heeled shoes, and shape analysis algorithms (such as Hough transform, contour detection, etc.) can be used to identify the shape features of the high-heeled shoes. These features together constitute the complete image representation of the high-heeled shoes.

[0051] At the same time, image processing techniques can be used to further improve image quality, which includes using image filtering techniques to remove image noise, applying image enhancement techniques to improve the visual effect of the image, and using image segmentation techniques to separate the high-heeled shoes from the background for more accurate feature extraction and recognition. In order to further improve the accuracy and efficiency of recognition, deep learning technology can be introduced, specifically, a convolutional neural network model is used to automatically recognize and classify high-heeled shoe images. By training the model to learn the feature representation of high-heeled shoes and performing performance evaluation on the test set, we obtain a deep learning result I, whose value range is [0, 1], representing the matching degree of the image and the high-heeled shoe features. Finally, the extracted foot shape features are compared with the pre-stored high-heeled shoe shape, and an image performance score is calculated according to their similarity. This score can intuitively reflect the similarity between the driver's foot shape and the pre-stored high-heeled shoe shape, so as to determine whether the driver is wearing high-heeled shoes.

[0052] S103, according to the pressure distribution, weight and shape characteristics, driving safety warning is carried out for the vehicle.

[0053] The specific process of driving safety warning for the vehicle is introduced below. Figure 2 The specific process of driving safety warning for the vehicle is introduced below.

[0054] Figure 2 The flowchart of driving safety warning provided by the embodiments of the present application.

[0055] S201, according to the obtained pressure performance score, gravity performance score, image performance score, dynamic weight value corresponding to the pressure performance score, dynamic weight value corresponding to the gravity performance score, and dynamic weight value corresponding to the image performance score, the probability value of the driver wearing high heels is determined.

[0056] The dynamic weight value corresponding to the pressure performance score, the dynamic weight value corresponding to the gravity performance score, and the dynamic weight value corresponding to the image performance score are calculated by the following formula respectively:

[0057]

[0058] Dynamic Weight i The dynamic weight value corresponding to the i-th coefficient type, the coefficient type including the pressure coefficient type, the gravity coefficient type and the image coefficient type, i is an index variable, used to respectively indicate the pressure coefficient type, the gravity coefficient type and the image coefficient type, s i The performance score of the i-th coefficient type, ∑ i∈{G,P,I} s i The sum of the performance scores of all coefficient types, G is the gravity performance score, P is the pressure performance score, I is the image performance score, ω i The preset static basic weight corresponding to the i-th coefficient type.

[0059] S202, if the probability value exceeds the warning threshold, the vehicle is prohibited to start, and driving safety warning is carried out on the display terminal of the vehicle.

[0060] Here, the warning threshold can be set in advance according to past experience, if it exceeds the warning threshold, a warning window will pop up on the main control screen of the vehicle, and the vehicle is prohibited to start.

[0061] Specifically, the probability value can be calculated by the following formula:

[0062] Score=DynamicWeight G *G+DynamicWeight P *P+DynamicWeight I *I

[0063] Here, Score is a probability value, DynamicWeight G is a dynamic weight value corresponding to the gravity performance score, DynamicWeight P is a dynamic weight value corresponding to the gravity performance score, Dynamic Weight I is a dynamic weight value corresponding to the image performance score.

[0064] Referring to Figure 3 , Figure 3 is a structural schematic diagram of a driving safety detection device provided by an embodiment of the present application. The driving safety detection device 300 includes:

[0065] An acquisition module 301 is configured to acquire pressure data, gravity data and foot image data of a main driving area of a vehicle in response to a start signal of the vehicle. The pressure data is obtained by a pressure sensor arranged at a pedal, the gravity data is obtained by a gravity sensor arranged on the ground of the main driving area of the vehicle, and the foot image data is obtained by a camera arranged in the main driving area by shooting the area around the pedal.

[0066] An identification module 302 is configured to identify a pressure distribution borne by the pedal according to the pressure data, identify a weight borne on the ground of the main driving area according to the gravity data, and identify an outline feature of a foot of a driver of the vehicle according to the foot image data.

[0067] A warning module 303 is configured to perform driving safety warning for the vehicle according to the pressure distribution, the weight and the outline feature.

[0068] Referring to Figure 4 , Figure 4 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. As shown in Figure 4 , the electronic device 400 includes a processor 410, a memory 420 and a bus 430.

[0069] The memory 420 stores machine readable instructions executable by the processor 410. When the electronic device 400 is running, the processor 410 and the memory 420 communicate through the bus 430. When the machine readable instructions are executed by the processor 410, the steps of the driving safety detection method in the method embodiment shown in Figure 1 and Figure 2 can be performed. The specific implementation manner can be referred to the method embodiment, which will not be described here.

[0070] The present application also provides a computer readable storage medium, which stores a computer program. When the computer program is run by a processor, the steps of the driving safety detection method in the method embodiment shown in the aboveFigure 1 and Figure 2 The steps of the driving safety detection method in the method embodiment are specifically implemented as described above, and will not be described here.

[0071] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, and will not be described here.

[0072] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division, and there can be another division manner in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some communication interfaces, devices or units, and can be electrical, mechanical or other forms.

[0073] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., they can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0074] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0075] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solutions of the present application or the part of the present application that essentially contributes to the prior art or the part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and various storage medium that can store program codes.

[0076] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present application, and are used to illustrate the technical solutions of the present application, but are not limitations thereof. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can make modifications or easily think of changes to the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some of the technical features within the technical scope disclosed by the present application. The modifications, changes or replacements do not cause the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A driving safety detection method, characterized in that, The method includes: In response to the vehicle's start signal, pressure data, gravity data, and foot image data of the driver's area of ​​the vehicle are acquired. The pressure data is obtained by a pressure sensor installed at the pedal, the gravity data is obtained by a gravity sensor installed on the ground in the driver's area of ​​the vehicle, and the foot image data is obtained by a camera installed in the driver's area by capturing images of the area around the pedal. Based on the pressure data, the pressure distribution on the pedal is identified; based on the gravity data, the weight on the ground in the driver's area is identified; based on the foot image data, the shape characteristics of the driver's feet are identified. Based on the pressure distribution, weight, and shape characteristics, a driving safety warning is issued for the vehicle. The weight borne on the ground in the driver's area is identified in the following way: The gravity data is compared with a preset gravity threshold to determine whether the gravity data is less than the preset gravity threshold. The gravity data indicates the weight of the driver's feet in the vehicle. If the gravity data is less than the preset gravity threshold, the difference between the preset gravity threshold and the gravity data is quantified to obtain a gravity performance score. The gravity performance score characterizes the degree of difference between the gravity data and the preset gravity threshold. The steps for providing a driving safety warning for the vehicle based on the pressure distribution, weight, and shape characteristics include: Based on the obtained pressure performance score, gravity performance score, image performance score, and the dynamic weight values ​​corresponding to the pressure performance score, gravity performance score, and image performance score, the probability value of the driver wearing high heels is determined. If the probability value exceeds the warning threshold, the vehicle is prohibited from starting, and a driving safety warning is issued on the vehicle's display terminal.

2. The method according to claim 1, characterized in that, The pressure sensor includes multiple pressure sensors distributed along the pedal. The pressure data includes pressure values ​​at multiple force detection points on the pedal, collected by the multiple pressure sensors. The pressure distribution on the pedal is identified using the following method: For each stress detection point, determine the pressure value experienced at that point; Determine the maximum and minimum pressure values ​​among all the pressure values ​​experienced by the stress detection points; Based on the pressure values ​​corresponding to all the force detection points, the maximum pressure value, and the minimum pressure value, a pressure performance score is obtained, which characterizes the pressure distribution borne by the pedal.

3. The method according to claim 1, characterized in that, The driver's foot shape features are identified by the following methods: The foot image data is preprocessed to extract edge features from the foot image data; The driver's foot shape is identified based on the edge features, and the foot shape is compared with a pre-stored high-heeled shoe shape to obtain an image performance score, which represents the degree of similarity between the driver's foot shape and the pre-stored high-heeled shoe shape.

4. The method according to claim 1, characterized in that, The dynamic weight values ​​corresponding to the pressure performance score, the gravity performance score, and the image performance score are calculated using the following formulas: Among them, Dynamic Weight i This represents the dynamic weight value corresponding to the i-th coefficient type. The coefficient types include pressure coefficient type, gravity coefficient type, and image coefficient type, where i is an index variable used to refer to the pressure coefficient type, gravity coefficient type, and image coefficient type, respectively. For the performance score of the i-th coefficient type, The sum of performance scores for all coefficient types, where G is the gravity performance score, P is the pressure performance score, and I is the image performance score. This is the preset static base weight corresponding to the i-th coefficient type.

5. The method according to claim 1, characterized in that, The preset gravity threshold is calculated using the following formula: Among them, G t β is the preset gravity threshold, and β is the preset weighting factor. The average value of multiple first composite acceleration amplitudes on the three axes of the gravity sensor when wearing high heels is collected in advance. The average value of multiple second composite acceleration amplitudes on the three axes of the gravity sensor when not wearing high heels is collected in advance, where γ is a preset positive scaling factor. It is the average of the standard deviations of the plurality of first composite acceleration amplitudes and the standard deviations of the plurality of second composite acceleration amplitudes.

6. A driving safety detection device, characterized in that, The device includes: The acquisition module is used to acquire pressure data, gravity data and foot image data of the driver's area in response to the vehicle's start signal. The pressure data is obtained by a pressure sensor installed at the pedal, the gravity data is obtained by a gravity sensor installed on the ground in the driver's area, and the foot image data is obtained by a camera installed in the driver's area by taking pictures of the area around the pedal. The recognition module is used to identify the pressure distribution borne by the pedal based on the pressure data, to identify the weight borne on the ground in the driver's area based on the gravity data, and to identify the shape characteristics of the driver's feet based on the foot image data. The warning module is used to provide driving safety warnings for the vehicle based on the pressure distribution, the weight, and the shape characteristics. The identification module is further configured to compare the gravity data with a preset gravity threshold to determine whether the gravity data is less than the preset gravity threshold, wherein the gravity data indicates the weight data of the driver's feet in the vehicle; if the gravity data is less than the preset gravity threshold, the difference between the preset gravity threshold and the gravity data is quantified to obtain a gravity performance score, wherein the gravity performance score characterizes the degree of difference between the gravity data and the preset gravity threshold; The warning module is also used to determine the probability value of the driver wearing high heels based on the obtained pressure performance score, gravity performance score, image performance score, and the dynamic weight value corresponding to the pressure performance score, the dynamic weight value corresponding to the gravity performance score, and the dynamic weight value corresponding to the image performance score; if the probability value exceeds the warning threshold, the vehicle is prohibited from starting, and a driving safety warning is issued on the vehicle's display terminal.

7. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is in operation, the processor communicates with the memory via the bus, and the processor executes the machine-readable instructions to perform the steps of the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the method as described in any one of claims 1 to 5.

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