Intelligent vehicle early warning method and device, intelligent vehicle and computer readable medium

Abstract

The embodiment of the invention discloses an intelligent vehicle early warning method and device, an intelligent vehicle and a computer readable medium. A specific embodiment of the method comprises the following steps: acquiring reference time; the following early warning steps are executed: controlling a camera device to acquire a positioning code image sequence; the ultrasonic positioning device is controlled to collect the distance from a target point in the intelligent vehicle to the wall where the positioning code is pasted in the vertical line direction of the driving direction as the transverse distance; controlling a driving included angle detection device to detect an included angle between the driving direction of the intelligent vehicle and the wall surface pasted with the positioning code as a detection angle; performing identification processing on each positioning code image in the positioning code image sequence; error code detection processing is carried out on the identification code sequence; executing positioning code error early warning processing; generating intelligent vehicle positioning information and a safe spacing distance; after a second preset time period of the reference time, acquiring the system time again; and executing the early warning step again. According to the embodiment, the times of false alarm and missing alarm of the safety distance early warning of the intelligent vehicle are reduced.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to a smart car early warning method, a smart car, and a computer-readable medium. Background Art

[0002] With the development of autonomous driving and intelligent transportation, it is particularly important to locate and warn the safe distance of smart cars (e.g., automated vehicles, rail remote control vehicles) on preset driving tracks (e.g., guided vehicle driving tracks in underground lanes, logistics centers or warehouses). Smart car warning is a technology for locating and warning the safe distance of smart cars. At present, the method commonly used for locating and warning the safe distance of smart cars is to locate and warn the safe distance of smart cars through the GPRS system.

[0003] However, when the above method is used to perform driving positioning and safety distance warning for smart cars, the following technical problems often occur:

[0004] GPRS signals are wirelessly transmitted through base stations. The underground environment usually causes the signals to be severely attenuated by materials such as soil and concrete. When a smart car passes through an underground tunnel, the GPRS system is used to locate the smart car and provide a safety distance warning. Due to the environmental characteristics of the underground tunnel, the transmission of GPRS signals is blocked, resulting in poor positioning accuracy of the smart car in the underground tunnel. When there is a large deviation between the GPS positioning information of the smart car and the actual position, the distance between the smart car and the tunnel wall determined by the GPRS system may be less accurate, thereby increasing the number of false alarms and missed alarms of the smart car safety distance warning.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the invention

[0006] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0007] Some embodiments of the present disclosure propose a smart car early warning method, a device, a smart car and a computer-readable medium to solve one or more of the technical problems mentioned in the above background technology section.

[0008] In a first aspect, some embodiments of the present disclosure provide a smart car early warning method, the method comprising: in response to receiving vehicle startup information sent by a radio frequency transceiver module in the smart car, obtaining a system time as a reference time, wherein the smart car is equipped with a camera device, an ultrasonic positioning device and a driving angle detection device, and a positioning code is affixed to a wall on one side of the track on which the smart car travels; based on the reference time, performing the following early warning steps: within a first preset time period after the reference time, controlling the camera device to capture a positioning code image at a preset acquisition frequency to obtain a positioning code image sequence; determining a time point after the first preset time period of the reference time as a target time point; controlling the ultrasonic positioning device to capture, at the target time point, the distance between the target point in the smart car in the vertical direction of the driving direction and the wall on which the positioning code is affixed as a lateral distance distance; control the driving angle detection device to detect the angle between the driving direction of the smart car and the wall on which the positioning code is pasted as a detection angle at a target time point; perform recognition processing on each positioning code image in the positioning code image sequence to obtain a recognition code sequence; perform error detection processing on the recognition code sequence to obtain error detection information; in response to determining that the error detection information indicates that there is an error in the recognition code sequence, perform positioning code error warning processing based on the error detection information; in response to determining that the error detection information indicates that there is no error in the recognition code sequence, generate smart car positioning information and safe interval distance based on the recognition code sequence, lateral distance, and detection angle to perform safe distance warning processing; after a second preset time period of the reference time, obtain the system time again to update the reference time; and perform the above warning step again according to the updated reference time.

[0009] In a second aspect, some embodiments of the present disclosure provide a smart car, comprising: a camera device, an ultrasonic positioning device and a driving angle detection device; one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by one or more processors, the one or more processors implement the method described in any implementation method of the above-mentioned first aspect.

[0010] In a third aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the first aspect is implemented.

[0011] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: through the smart car early warning method of some embodiments of the present disclosure, the number of false alarms and missed alarms of the smart car safety distance early warning is reduced. Specifically, the reason for the increase in the number of false alarms and missed alarms of the smart car safety distance early warning is that the GPRS signal is wirelessly transmitted through the base station, and the underground environment usually causes the signal to be severely attenuated by materials such as soil and concrete. When the smart car passes through an underground tunnel, the GPRS system is used to locate the smart car and warn of the safety distance. Due to the environmental characteristics of the underground tunnel, the GPRS signal transmission is blocked, resulting in poor positioning accuracy of the smart car in the underground tunnel. When there is a large deviation between the GPS positioning information of the smart car and the actual position, the distance between the smart car and the tunnel wall determined by the GPRS system may be less accurate, thereby increasing the number of false alarms and missed alarms of the smart car safety distance early warning. Based on this, the smart car early warning method of some embodiments of the present disclosure, first, in response to receiving the vehicle startup information sent by the radio frequency transceiver module in the smart car, obtain the system time as the reference time, wherein the smart car is equipped with a camera device, an ultrasonic positioning device and a driving angle detection device, and the wall on one side of the track on which the smart car travels is pasted with a positioning code. Thus, the time when the smart car starts can be determined. Then, based on the reference time, the following early warning steps are performed: the first step, within the first preset time period after the reference time, control the camera device to capture the positioning code image at a preset acquisition frequency to obtain a positioning code image sequence. Thus, a positioning code image sequence for locating the smart car can be obtained. The second step, the time point after the first preset time period of the reference time is determined as the target time point. The third step, control the ultrasonic positioning device to collect the distance between the target point in the smart car in the vertical direction of the driving direction and the wall on which the positioning code is pasted at the target time point as the lateral distance. Thus, the lateral distance between the target point in the smart car in the vertical direction of the driving direction of the smart car and the wall on which the positioning code is pasted can be determined. The fourth step is to control the driving angle detection device to detect the angle between the driving direction of the smart car and the wall on which the positioning code is pasted at the target time point as the detection angle. Thus, the angle between the driving direction of the smart car and the wall on which the positioning code is pasted can be obtained. The fifth step is to identify and process each positioning code image in the positioning code image sequence to obtain an identification code sequence. Thus, the identification code sequence can be obtained by identifying the positioning code images in the positioning code image sequence. The sixth step is to perform error detection processing on the identification code sequence to obtain error detection information. Thus, the identification code sequence can be subjected to error detection processing. The seventh step is to perform positioning code error warning processing in response to determining that the error detection information indicates that there is an error in the identification code sequence, based on the error detection information, perform positioning code error warning processing. Thus, positioning code error warning processing is performed when an error occurs in the positioning code.In the eighth step, in response to determining that the error detection information indicates that there is no error in the identification code sequence, based on the identification code sequence, lateral distance, and detection angle, the smart car positioning information and safe interval distance are generated to perform safe distance warning processing. Thus, when the positioning code is normal, the position reference information between the actual reference object in the physical space and the smart car (i.e., the identification code sequence, lateral distance, the detection angle between the driving direction of the smart car and the wall on which the positioning code is pasted) can be used to generate the positioning information and safe interval distance of the smart car at the target time point without relying on external signals, and it is not affected by external signal interference, thereby improving the accuracy of the generation of the smart car positioning information and safe interval distance, and reducing the deviation between the smart car positioning information and the actual position. At the same time, the safe distance warning processing is performed under the condition of generating the positioning information and the safe interval distance. Thus, on the basis of reducing the misjudgment of the distance between the smart car and the lane wall, the accuracy of the safe distance warning is improved. In the ninth step, after the second preset time period of the reference time, the system time is obtained again to update the reference time. In the tenth step, the above-mentioned warning step is performed again according to the updated reference time. Also, before the smart car is processed for safety distance warning, the position reference information between the actual reference object in the physical space and the smart car (i.e., the identification code sequence, lateral distance, the detection angle between the driving direction of the smart car and the wall with the positioning code attached) is used to generate the positioning information and safety interval distance of the smart car at the target time point without relying on external signals, which reduces the probability of misjudgment of the distance between the smart car in the underground environment and the tunnel wall, and improves the accuracy of safety distance warning. In turn, the number of false alarms and missed alarms of the smart car safety distance warning is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0013] Figure 1 is a flow chart of some embodiments of the smart car early warning method according to the present disclosure;

[0014] Figure 2 is a schematic diagram of application scenarios of some embodiments of the smart car early warning method disclosed herein;

[0015] Figure 3 It is a schematic diagram of the structure of a smart car suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0016] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0017] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0018] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0019] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0020] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0021] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0022] Figure 1 The process 100 of some embodiments of the smart car early warning method according to the present disclosure is shown. The smart car early warning method includes the following steps:

[0023] Step 101, in response to receiving vehicle startup information sent by a radio frequency transceiver module in a smart car, obtaining system time as a reference time.

[0024] In some embodiments, the execution subject of the smart car early warning method (for example, a vehicle-mounted terminal loaded on the smart car) can obtain the system time as the reference time in response to the vehicle startup information sent by the radio frequency transceiver module in the smart car. Among them, the smart car is equipped with a camera, an ultrasonic positioning device and a driving angle detection device, and the wall on one side of the track on which the smart car is traveling is pasted with a positioning code. The smart car can be an automated car or a track remote control car traveling under a preset driving scene. The vehicle startup information can be a radio frequency signal characterizing the startup of the smart car. The camera can be a device for collecting an image of the positioning code on the wall on one side of the smart car (the left or right side of the car body), such as a camera, a camera, etc. The ultrasonic positioning device can be an ultrasonic rangefinder for collecting lateral distances. The lateral distance can be the distance between the point where the ultrasonic positioning device is installed on the smart car in the vertical direction of the driving direction of the smart car and the wall on which the positioning code is pasted. The driving angle detection device can be a multi-point laser displacement sensor for measuring the detection angle. The detection angle can be the angle between the driving direction of the smart car and the wall on which the positioning code is pasted. The camera device can be installed on the side of the smart car body near the positioning code, or can be installed in the preset area where the target point 202 in the smart car is located. The ultrasonic positioning device can be installed in the preset area where the target point 202 in the smart car is located. The driving angle detection device can be installed in the preset area where the target point 202 in the smart car is located. The positioning code can be a paper barcode representing the positioning code.

[0025] As an example, Figure 2 is a schematic diagram of application scenarios of some embodiments of the intelligent vehicle early warning method disclosed in the present invention, Figure 2 The smart car 203, the vehicle driving direction 201, the wall 204 with the positioning code pasted, the positioning code 205, the lateral distance d, the target point 202 in the smart car, the detection angle 206, and the detection angle 207 are displayed in the preset driving scene. The positioning code may be a paper barcode representing the positioning code. The positioning code may be a number representing the distance. As an example, the positioning code number may be a number between 0001 and 2500. The interval between each number may be a 1CM scale. For example, a positioning code numbered 1234 may represent a length of 12.34 meters. The positioning code may be pasted on a wall at a height of 15CM from the ground on one side of a driving lane or track. The target point in the smart car may be a point where an ultrasonic positioning device is installed. The detection angle It can be the angle between the driving direction of the smart car and the wall on which the positioning code is pasted.

[0026] Step 102: Based on the reference time, perform the following early warning steps:

[0027] Step 1021: within a first preset time period after a reference time, control the camera device to capture positioning code images at a preset acquisition frequency to obtain a positioning code image sequence.

[0028] In some embodiments, the execution subject may control the camera to capture the positioning code image at a preset acquisition frequency within a first preset time period after the reference time to obtain a positioning code image sequence. The preset acquisition frequency may be the frequency at which the camera captures the positioning code image, for example, the acquisition frequency may be 20 times per second. The positioning code image may be an image containing the positioning code.

[0029] Step 1022: determine a time point after a first preset time period of the reference time as a target time point.

[0030] In some embodiments, the execution entity may determine a time point after a first preset time period of the reference time as the target time point. As an example, the reference time may be 11:07 on February 28, 2024, the first preset time period may be from 11:07 on February 28, 2024 to 11:12 on February 28, 2024, and the target time point may be 11:12 on February 28, 2024.

[0031] Step 1023, controlling the ultrasonic positioning device to collect the distance between the target point in the smart car in the vertical direction of the driving direction and the wall surface on which the positioning code is pasted at the target time point as the lateral distance.

[0032] In some embodiments, the execution entity may control the ultrasonic positioning device to collect the distance between the target point in the smart car in the vertical direction of the driving direction and the wall on which the positioning code is pasted as the lateral distance at the target time point.

[0033] Step 1024, controlling the driving angle detection device to detect the angle between the driving direction of the smart car and the wall on which the positioning code is pasted at the target time point as the detection angle.

[0034] In some embodiments, the execution entity may control the driving angle detection device to detect the angle between the driving direction of the smart car and the wall on which the positioning code is pasted at a target time point as a detection angle.

[0035] Step 1025: perform recognition processing on each positioning code image in the positioning code image sequence to obtain a recognition code sequence.

[0036] In some embodiments, the execution subject may perform recognition processing on each positioning code image in the positioning code image sequence to obtain an recognition code sequence, wherein the positioning code in the positioning code sequence may be a positioning code.

[0037] In some optional implementations of some embodiments, the execution subject may perform recognition processing on each positioning code image in the positioning code image sequence through the following steps to obtain the recognition code sequence:

[0038] In the first step, for each positioning code image in the positioning code image sequence, the following recognition steps are performed:

[0039] The first sub-step is to perform positioning code extraction processing on the positioning code image to obtain a positioning code extraction image.

[0040] The second sub-step is to input the positioning code image into a pre-trained positioning code feature extraction model to obtain positioning code feature information corresponding to the positioning code image. The positioning code feature extraction model may be a convolutional neural network (CNN) model that takes the positioning code image as input and the positioning code feature information as output. The positioning code feature information may be a vector representing feature information of the extracted positioning code (such as information such as the width, spacing, shape and overall structure of the stripes).

[0041] The third sub-step is to obtain the coding number corresponding to the above-mentioned positioning code feature information from the preset database. In practice, first, the above-mentioned execution subject can determine the respective similarities (for example, cosine similarity) between the positioning code feature information and the respective pre-stored positioning code feature information pre-stored in the above-mentioned preset database as the respective similarities to be screened. Then, the above-mentioned execution subject can determine the similarity to be screened with the largest similarity value among the respective similarities to be screened as the target similarity. Finally, the above-mentioned execution subject can determine the positioning code number corresponding to the pre-stored positioning code feature information corresponding to the above-mentioned target similarity in the above-mentioned preset database as the coding number.

[0042] The fourth sub-step is to determine the above-mentioned coding number as the identification code.

[0043] In the second step, the identification codes are arranged according to the arrangement order of the positioning code images corresponding to the identification codes in the positioning code image sequence to obtain an identification code sequence.

[0044] In the process of adopting technical solutions to solve the problems mentioned in the background technology, the following problems are often accompanied:

[0045] In the process of identifying the positioning code image, in order to more accurately identify the positioning code, it is necessary to crop the positioning code image and extract the image of the positioning code in the positioning code image. The positioning code image is directly cropped to obtain the image of the positioning code in the positioning code image, and the noise of the cropped image where the positioning code is located is not removed. These noises will cause the edge and contour clarity of the positioning code in the cropped image to be low.

[0046] In the face of the above technical problems, the inventors decided to adopt the following solutions:

[0047] In some embodiments, the execution subject may perform positioning code extraction processing on the positioning code image to obtain a positioning code extraction image by the following steps:

[0048] In the first step, in response to determining that the number of color channels of each pixel in the above-mentioned positioning code extraction image is a first preset value, the above-mentioned positioning code extraction image is determined as a pre-processed image. The number of color channels can be a channel value for storing image color information. For example, the above-mentioned first preset value can be 1.

[0049] In the second step, in response to the number of color channels of each pixel in the positioning code extraction image being a second preset value, for each pixel in the positioning code extraction image, the following pixel processing steps are performed:

[0050] The first sub-step is to determine the three-primary color value information of the above pixel point. The above three-primary color value information may refer to the numerical information of the red, green and blue channels in the pixel point. For example, the three-primary color value information may be (64, 88, 125).

[0051] The second sub-step is to generate a color average value corresponding to the pixel point according to the three primary color value information. In practice, the execution subject may determine the average value of the values ​​included in the three primary color value information as the color average value.

[0052] The third sub-step is to determine the number of color channels of the above pixel point as the above first preset value.

[0053] The fourth sub-step is to determine the color average value as the color value of the pixel point.

[0054] In the third step, the positioning code extraction image obtained by processing each pixel of the positioning code extraction image through the above pixel processing step is determined as a pre-processed image.

[0055] The fourth step is to obtain a preset template image. The preset template image may be an image used as a reference or comparison when performing positioning code recognition processing. In practice, the execution subject may obtain the preset template image from a preset image library.

[0056] The fifth step is to perform positioning code recognition processing on the determined preprocessed image according to the preset template image to obtain the positioning code area information. In practice, the execution subject can match the area image with the highest similarity to the preset template image in the preprocessed image through template matching technology (for example, OpenCV template matching (cv2.matchTemplate) technology). Then, the execution subject can determine the position information of the area image in the preprocessed image as the positioning code area information. Among them, the area position information can be represented by the coordinates of a rectangular box. For example, the area position information can represent the area where the coordinates of the upper left corner are (x, y), the width is w and the height is h. The above x represents the coordinate value of the horizontal coordinate, the above y represents the coordinate value of the vertical coordinate, the above w can represent the value of the width of the rectangular box, and the above h can be the value of the height of the rectangular box.

[0057] In the sixth step, the determined pre-processed image is cropped according to the positioning code area information to obtain an initial positioning code image. In practice, the execution subject can call a cropping interface to retain the image of the area corresponding to the positioning code area information in the pre-processed image, and crop the image outside the area corresponding to the positioning code area information in the processed image to obtain the initial positioning code image. The cropping interface can be a function or method for cropping an image according to the cropping area information.

[0058] Step 7: edge enhancement processing is performed on the initial positioning code image to obtain an edge enhanced positioning code image. In practice, the execution subject may perform edge enhancement processing on the initial positioning code image by an edge enhancement algorithm to obtain an edge enhanced positioning code image. The edge enhanced positioning code image is an image in which the edge contour portion is more obvious after edge enhancement processing is performed on the initial positioning code image.

[0059] In the eighth step, for each edge-enhanced positioning code image pixel in the edge-enhanced positioning code image, perform the following filtering process:

[0060] Sub-step 1: align the center of the preset Gaussian filter convolution kernel with the pixel point of the edge enhancement positioning code image to obtain the aligned convolution window area. In practice, the execution subject may place the center of the preset Gaussian filter convolution kernel on the pixel point of the edge enhancement positioning code image, and determine the neighborhood area covered by the preset Gaussian filter convolution kernel on the pixel point of the edge enhancement positioning code image as the aligned convolution window area. As an example, the preset Gaussian filter convolution kernel may be Each edge-enhanced positioning code image pixel point in the edge-enhanced positioning code image can be The edge enhancement positioning code image pixel point may be an edge enhancement positioning code image pixel point whose pixel value corresponding to the second row and second column of the edge enhancement positioning code image pixel points is 1. The execution subject may set the center of the preset Gaussian filter convolution kernel (for example, ) is placed on the edge enhancement positioning code image pixel point with a pixel value of 1. The aligned convolution window area can be a 3×3 area centered on the edge enhancement positioning code image pixel point with a pixel value of 1 and including the edge enhancement positioning code image pixel point and 8 pixels around it.

[0061] Sub-step two, based on the above-mentioned aligned convolution window area, determine the neighborhood pixel point set corresponding to the above-mentioned edge enhancement positioning code image pixel point. The above-mentioned execution entity can determine the corresponding edge enhancement positioning code image pixel points in the aligned convolution window area as a neighborhood pixel point set. As an example, the above-mentioned neighborhood pixel point set can be {edge enhancement positioning code image pixel points with a pixel value of 0 in the first row and the first column, edge enhancement positioning code image pixel points with a pixel value of 0 in the first row and the second column, edge enhancement positioning code image pixel points with a pixel value of 0 in the first row and the third column, edge enhancement positioning code image pixel points with a pixel value of 0 in the second row and the first column, edge enhancement positioning code image pixel points with a pixel value of 1 in the second row and the second column, edge enhancement positioning code image pixel points with a pixel value of 2 in the second row and the third column, edge enhancement positioning code image pixel points with a pixel value of 0 in the third row and the first column, edge enhancement positioning code image pixel points with a pixel value of 0 in the third row and the second column, and edge enhancement positioning code image pixel points with a pixel value of 0 in the third row and the third column}.

[0062] Sub-step three, based on the above-mentioned neighborhood pixel point set and the above-mentioned preset Gaussian filter convolution kernel, generate a filter convolution value. In practice, first, the above-mentioned execution entity can determine the individual pixel values ​​corresponding to the neighborhood pixel point set as a neighborhood pixel value set. Then, the above-mentioned execution entity can perform a convolution operation on the above-mentioned preset Gaussian filter convolution kernel and the above-mentioned neighborhood pixel value set to obtain an initial filter convolution value. Then, the above-mentioned execution entity can perform an upward rounding operation on the above-mentioned initial filter convolution value to obtain a filter convolution value. As an example, the above-mentioned initial filter convolution value can be The above filter convolution value can be 1.

[0063] Sub-step four: updating the pixel values ​​of the edge-enhanced positioning code image pixels into filtered convolution values ​​to update the edge-enhanced positioning code image pixels.

[0064] In the ninth step, each edge-enhanced positioning code image pixel point of the edge-enhanced positioning code image is determined as the positioning code extraction image after the edge-enhanced positioning code image is subjected to the filtering process.

[0065] The above technical solution and its related contents, as an inventive point of the embodiment of the present disclosure, solve the technical problem of "low clarity of the edge and contour of the positioning code". The factors that lead to low clarity of the edge and contour of the positioning code are often as follows: directly cropping the positioning code image to obtain the image of the positioning code in the positioning code image, and not removing the noise of the cropped image where the positioning code is located. These noises will cause the edge and contour clarity of the positioning code in the cropped image to be low. If the above factors are solved, the effect of improving the clarity of the edge and contour of the positioning code can be achieved. In order to achieve this effect, first, in response to determining that the number of color channels of each pixel in the above positioning code extraction image is a first preset value, the above positioning code extraction image is determined as a preprocessed image. Then, in response to the number of color channels of each pixel in the above positioning code extraction image is a second preset value, for each pixel in the above positioning code extraction image, the following pixel processing steps are performed: the first sub-step, determining the three primary color value information of the above pixel. Thus, the three primary color value information of the pixel whose color channel number is the second preset data can be determined. The second sub-step, generating the color average value corresponding to the above pixel according to the above three primary color value information. Thus, the color average value for determining the color value of the pixel point can be obtained. In the third sub-step, the number of color channels of the above-mentioned pixel point is determined as the above-mentioned first preset value. Thus, the number of color channels of the pixel point can be changed. In the third sub-step, the above-mentioned color average value is determined as the color value of the above-mentioned pixel point. Afterwards, the positioning code extraction image processed by the above-mentioned pixel processing step for each pixel point of the positioning code extraction image is determined as the pre-processed image. Thus, the positioning code extraction image can be grayed through the above-mentioned steps to obtain the pre-processed image after graying. Then, the preset template image is obtained. Thus, the preset template image for performing positioning code recognition processing on the pre-processed image can be obtained. Then, according to the above-mentioned preset template image, the positioning code recognition processing is performed on the determined pre-processed image to obtain the positioning code area information. Thus, the positioning code area information of the positioning code in the pre-processed image can be determined. Then, according to the above-mentioned positioning code area information, the determined pre-processed image is cropped to obtain the initial positioning code image. Thus, the initial positioning code image where the positioning code is located can be obtained by cropping the pre-processed image. Next, edge enhancement processing is performed on the above-mentioned initial positioning code image to obtain an edge enhanced positioning code image. Thus, the edge details of the initial positioning code image can be made clearer by edge enhancement processing of the initial positioning code image. Next, for each edge enhanced positioning code image pixel point in the edge enhanced positioning code image, the following filtering processing is performed: Sub-step 1, aligning the center of the preset Gaussian filter convolution kernel with the above-mentioned edge enhanced positioning code image pixel point to obtain an aligned convolution window area. Thus, an aligned convolution window area for determining a neighborhood pixel point set can be obtained.Sub-step 2, based on the above-mentioned aligned convolution window area, determine the neighborhood pixel point set corresponding to the above-mentioned edge enhanced positioning code image pixel point. Thus, a neighborhood pixel point set for updating the edge enhanced positioning code image pixel point can be obtained. Afterwards, based on the above-mentioned neighborhood pixel point set and the above-mentioned preset Gaussian filter convolution kernel, a filter convolution value is generated. Next, the pixel value of the above-mentioned edge enhanced positioning code image pixel point is updated to a wave convolution value to update the edge enhanced positioning code image pixel point. Then, the edge enhanced positioning code image after the above-mentioned filtering processing of each edge enhanced positioning code image pixel point of the edge enhanced positioning code image is determined as a positioning code extraction image. Also because the initial positioning code image obtained by the cropping process is subjected to edge enhancement processing, the edge details of the initial positioning code image are clearer. Afterwards, the initial positioning code image with clearer edge details is filtered to obtain a positioning code extraction image with reduced noise, thereby improving the edge and contour clarity of the positioning code in the positioning code extraction image.

[0066] Step 1026: Perform error detection processing on the identification code sequence to obtain error detection information.

[0067] In some embodiments, the above-mentioned execution entity may perform error detection processing on the identification code sequence to obtain error detection information.

[0068] In some optional implementations of some embodiments, the execution subject may perform error detection processing on the identification code sequence through the following steps to obtain error detection information:

[0069] In the first step, each identification code corresponding to the first preset index information in the identification code sequence is determined as the first identification code sequence. The first preset index information may be index information indicating the position range of a specific character or field selected in the identification code sequence. For example, the first preset index information may be "the first to third positions in the identification code sequence".

[0070] The second step is to determine each identification code corresponding to the second preset index information in the identification code sequence as the second identification code sequence. For example, the second preset index information may be "the n-3th to the nth bit in the identification code sequence". The n may be the total number of identification codes in the identification code sequence.

[0071] The third step is to combine the first identification code sequence and the second identification code sequence to obtain a combined identification code sequence. In practice, the execution subject may concatenate the first identification code sequence and the second identification code sequence to obtain a combined identification code sequence.

[0072] The fourth step is to perform a monotonicity detection process on the above-mentioned combined sequence to obtain monotonicity detection information. In practice, the above-mentioned execution subject can perform a monotonicity detection process on the combined sequence by a linear scanning method to obtain monotonicity detection information. The above-mentioned monotonicity detection information can be one of the following: text information representing that the sequence is monotonically increasing, text information representing that the sequence is monotonically decreasing, and text information representing that the sequence is non-monotonic.

[0073] Step 5: In response to determining that the monotonicity detection information characterizing the sequence is monotonically increasing, the following increasing sequence error detection processing is performed:

[0074] The first sub-step is to determine the identification code sequence as an increasing sequence.

[0075] The second sub-step is to delete each identification code in the increasing sequence corresponding to the combined identification code sequence to update the increasing sequence.

[0076] The third sub-step is to perform the following first determination step for the first identification code in the updated incremental sequence:

[0077] The fourth sub-step is to compare the above identification code with each identification code in the above increasing sequence except the first identification code.

[0078] In a fifth sub-step, in response to determining that the above identification codes are all smaller than the above identification codes, executing the following steps:

[0079] Sub-step one: deleting the identification code from the ascending sequence to update the ascending sequence.

[0080] Sub-step two: in response to determining that the updated ascending sequence is not empty, executing the above-mentioned first determination step again according to the updated ascending sequence.

[0081] Sub-step three: in response to determining that the updated incremental sequence is empty, determining information indicating that there is no error in the identification code sequence as error detection information.

[0082] A sixth sub-step is, in response to determining that the identification code is greater than or equal to one of the identification codes, determining information indicating that errors exist in the identification code sequence as error detection information.

[0083] In the sixth step, in response to determining that the monotonicity detection information characterizing the sequence is monotonically decreasing, a decreasing sequence error detection process is performed on the identification code sequence to obtain error detection information.

[0084] In the seventh step, in response to determining that the monotonicity detection information indicates that the sequence is non-monotonic, information indicating that errors exist in the identification code sequence is determined as error detection information.

[0085] Step 1027: In response to determining that the error detection information indicates that the identification code sequence has errors, a positioning code error warning process is performed based on the error detection information.

[0086] In some embodiments, the execution subject may, in response to determining that the error detection information indicates that there is an error in the identification code sequence, perform positioning code error warning processing based on the error detection information.

[0087] In some optional implementations of some embodiments, the execution subject may perform positioning code error warning processing based on error code detection information through the following steps:

[0088] The first step is to save the positioning code image sequence corresponding to the error code detection information to a preset storage device, wherein the preset storage device is a preset database.

[0089] The second step is to send warning information indicating a positioning code error to each positioning code maintenance terminal. The positioning code maintenance terminal may be a terminal device (eg, a mobile phone) of a staff member who maintains the positioning code. The warning information may be a text message.

[0090] The third step is to send a warning message indicating a positioning code error to the intelligent vehicle driving control terminal. The intelligent vehicle driving control terminal may be a driving control system or module of the intelligent vehicle, such as a vehicle dynamic control system or an intelligent driving control system.

[0091] Step 1028, in response to determining that the error detection information indicates that there is no error in the identification code sequence, based on the identification code sequence, lateral distance, and detection angle, generate smart car positioning information and safe interval distance to perform safe distance warning processing.

[0092] In some embodiments, the above-mentioned execution entity can generate smart vehicle positioning information and safe interval distance based on the identification code sequence, lateral distance, and detection angle in response to determining that the error detection information represents that there are no errors in the identification code sequence, so as to perform safety distance warning processing.

[0093] In some optional implementations of some embodiments, the execution subject may generate smart car positioning information and safe interval distance based on the identification code sequence, lateral distance, and detection angle through the following steps to perform safe distance warning processing:

[0094] In the first step, the last identification code in the identification code sequence is determined as the target identification code.

[0095] The second step is to generate the smart car positioning information based on the lateral distance, the detection angle and the target identification code. In practice, the execution subject may query the distance value corresponding to the identification code from a preset database as the first value. Then, the execution subject may determine the product of the lateral distance and the sine value of the detection angle as the second value. Afterwards, the execution subject may determine the sum of the first value and the second value as the smart car positioning information.

[0096] The third step is to store the above smart car positioning information in a preset storage device.

[0097] The fourth step is to generate a safe interval distance based on the lateral distance and the detection angle. In practice, the execution entity may determine the safe interval distance as the product of the lateral distance and the cosine value of the detection angle.

[0098] Step 5: In response to determining that the safety interval distance is less than or equal to the preset safety distance, a warning message indicating that the safety distance is small is sent to the driving control terminal of the smart car. The warning message may be a text message.

[0099] Step 1029: After a second preset time period of the reference time, the system time is acquired again to update the reference time.

[0100] In some embodiments, the execution subject may obtain the system time again after a second preset time period of the reference time to update the reference time. In practice, the execution subject may determine the obtained system time as the reference time to update the reference time.

[0101] Step 10210, execute the early warning step again according to the updated reference time.

[0102] In some embodiments, the execution entity may execute the warning step again according to the updated reference time.

[0103] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: through the smart car early warning method of some embodiments of the present disclosure, the number of false alarms and missed alarms of the smart car safety distance early warning is reduced. Specifically, the reason for the increase in the number of false alarms and missed alarms of the smart car safety distance early warning is that the GPRS signal is wirelessly transmitted through the base station, and the underground environment usually causes the signal to be severely attenuated by materials such as soil and concrete. When the smart car passes through an underground tunnel, the GPRS system is used to locate the smart car and warn of the safety distance. Due to the environmental characteristics of the underground tunnel, the GPRS signal transmission is blocked, resulting in poor positioning accuracy of the smart car in the underground tunnel. When there is a large deviation between the GPS positioning information of the smart car and the actual position, the distance between the smart car and the tunnel wall determined by the GPRS system may be less accurate, thereby increasing the number of false alarms and missed alarms of the smart car safety distance early warning. Based on this, the smart car early warning method of some embodiments of the present disclosure, first, in response to receiving the vehicle startup information sent by the radio frequency transceiver module in the smart car, obtain the system time as the reference time, wherein the smart car is equipped with a camera device, an ultrasonic positioning device and a driving angle detection device, and the wall of the driving track of the smart car is pasted with a positioning code. Thus, the time when the smart car is started can be determined. Then, based on the reference time, the following early warning steps are performed: Then, within the first preset time period after the reference time, the camera device is controlled to capture the positioning code image at a preset acquisition frequency to obtain a positioning code image sequence. Thus, a positioning code image sequence for locating the smart car can be obtained. Afterwards, the time point after the first preset time period of the reference time is determined as the target time point. Then, the ultrasonic positioning device is controlled to collect the distance between the target point in the smart car in the vertical direction of the driving direction and the wall with the positioning code pasted at the target time point as the lateral distance. Thus, the lateral distance between the target point in the smart car in the vertical direction of the driving direction of the smart car and the wall with the positioning code pasted can be determined. Afterwards, the driving angle detection device is controlled to detect the angle between the driving direction of the smart car and the wall on which the positioning code is pasted at the target time point as the detection angle. Thus, the angle between the driving direction of the smart car and the wall on which the positioning code is pasted can be obtained. Next, each positioning code image in the positioning code image sequence is identified and processed to obtain an identification code sequence. Thus, the identification code sequence can be obtained by identifying the positioning code images in the positioning code image sequence. Then, the identification code sequence is processed for error detection to obtain error detection information. Thus, the identification code sequence can be processed for error detection. Afterwards, in response to determining that the error detection information indicates that there is an error in the identification code sequence, a positioning code error warning process is performed based on the error detection information. Thus, a positioning code error warning is performed when an error occurs in the positioning code.Then, in response to determining that the error detection information indicates that there is no error in the identification code sequence, based on the identification code sequence, the lateral distance, and the detection angle, the smart car positioning information and the safe interval distance are generated to perform the safety distance warning processing. Thus, when the positioning code is normal, the position reference information between the actual reference object in the physical space and the smart car (i.e., the identification code sequence, the lateral distance, the detection angle between the driving direction of the smart car and the wall on which the positioning code is pasted) can be used to generate the positioning information and the safe interval distance of the smart car at the target time point without relying on external signals, and it is not affected by external signal interference, thereby improving the accuracy of the generation of the smart car positioning information and the safe interval distance, and reducing the deviation between the smart car positioning information and the actual position. At the same time, the safety distance warning processing is performed under the condition of generating the positioning information and the safe interval distance. Thus, on the basis of reducing the misjudgment of the distance between the smart car and the lane wall, the accuracy of the safety distance warning is improved. After the second preset time period of the reference time, the system time is obtained again to update the reference time. According to the updated reference time, the above-mentioned warning step is performed again. Also, before the smart car is processed for safety distance warning, the position reference information between the actual reference object in the physical space and the smart car (i.e., the identification code sequence, lateral distance, the detection angle between the driving direction of the smart car and the wall on which the positioning code is pasted) is utilized to generate the positioning information and safety interval distance of the smart car at the target time point without relying on external signals, thereby reducing the misjudgment of the distance between the smart car and the alley wall, improving the accuracy of the safety distance warning, and reducing the number of false alarms and missed alarms of the smart car safety distance warning.

[0104] Reference below Figure 3 , which shows a structural schematic diagram of a smart car 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The smart car shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0105] like Figure 3 As shown, the smart car 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 to a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the smart car 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0106] Typically, the following devices may be connected to the I / O interface 305: input devices 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, a camera device, an ultrasonic positioning device, a driving angle detection device, etc.; output devices 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 308 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 309. The communication device 309 may allow the smart car 300 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The smart car 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0107] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the functions defined in the method of some embodiments of the present disclosure are executed.

[0108] It should be noted that the computer-readable medium recorded in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In some embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0109] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0110] The computer-readable medium may be included in the smart car; or it may exist independently and not be installed in the smart car. The computer-readable medium carries one or more programs. When one or more programs are executed by the smart car, the smart car: in response to receiving the vehicle startup information sent by the radio frequency transceiver module in the smart car, obtains the system time as the reference time, wherein the smart car is equipped with a camera device, an ultrasonic positioning device and a driving angle detection device, and the wall of the driving track of the smart car is affixed with a positioning code; based on the reference time, the following early warning steps are performed: within the first preset time period after the reference time, the camera device is controlled to capture the positioning code image at a preset acquisition frequency to obtain a positioning code image sequence; the time point after the first preset time period of the reference time is determined as the target time point; the ultrasonic positioning device is controlled to capture the distance between the target point in the smart car in the vertical direction of the driving direction and the wall on which the positioning code is affixed at the target time point. is the lateral distance; controlling the driving angle detection device to detect the angle between the driving direction of the smart car and the wall on which the positioning code is pasted as the detection angle at the target time point; performing recognition processing on each positioning code image in the positioning code image sequence to obtain an identification code sequence; performing error detection processing on the identification code sequence to obtain error detection information; in response to determining that the error detection information indicates that there is an error in the identification code sequence, performing positioning code error warning processing based on the error detection information; in response to determining that the error detection information indicates that there is no error in the identification code sequence, generating smart car positioning information and safe interval distance based on the identification code sequence, the lateral distance, and the detection angle to perform safe distance warning processing; after a second preset time period of the reference time, obtaining the system time again to update the reference time; and performing the above warning step again according to the updated reference time.

[0111] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0112] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0113] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0114] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of technical features, but should also cover other technical solutions formed by any combination of technical features or their equivalent features without departing from the inventive concept. For example, a technical solution formed by replacing the features with (but not limited to) the technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A smart car early warning method, comprising: In response to receiving vehicle startup information sent by a radio frequency transceiver module in a smart car, obtaining system time as a reference time, wherein the smart car is equipped with a camera device, an ultrasonic positioning device and a driving angle detection device, and a positioning code is attached to a wall on one side of the track on which the smart car travels; Based on the reference time, perform the following warning steps: In a first preset time period after the reference time, the camera device is controlled to capture positioning code images at a preset acquisition frequency to obtain a positioning code image sequence; Determine a time point after a first preset time period of the reference time as a target time point; Control the ultrasonic positioning device to collect the distance between the target point in the smart car in the vertical direction of the driving direction and the wall surface on which the positioning code is pasted as the lateral distance at the target time point; Controlling the driving angle detection device to detect the angle between the driving direction of the smart car and the wall on which the positioning code is pasted at the target time point as a detection angle; Performing recognition processing on each positioning code image in the positioning code image sequence to obtain an recognition code sequence; Performing error detection processing on the identification code sequence to obtain error detection information; In response to determining that the error detection information indicates that there is an error in the identification code sequence, performing positioning code error warning processing based on the error detection information; In response to determining that the error detection information indicates that the identification code sequence does not have an error, based on the identification code sequence, the lateral distance, and the detection angle, the smart vehicle positioning information and the safety interval distance are generated to perform a safety distance warning process; After a second preset time period of the reference time, obtaining the system time again to update the reference time; The early warning step is performed again according to the updated reference time.

2. The method according to claim 1, wherein: The performing of positioning code error warning processing based on the error code detection information includes: Saving the positioning code image sequence corresponding to the error code detection information to a preset storage device; Sending warning information indicating positioning code errors to each positioning code maintenance terminal; Send an early warning message indicating a positioning code error to the smart car driving control terminal.

3. The method according to claim 1, wherein: The method of generating smart car positioning information and safe interval distance based on the identification code sequence, lateral distance, and detection angle to perform safe distance warning processing includes: Determine the last identification code in the identification code sequence as the target identification code; Generate smart car positioning information based on lateral distance, detection angle and target identification code; Storing the smart car positioning information in a preset storage device; Based on the lateral distance and the detection angle, a safe separation distance is generated; In response to determining that the safety interval distance is less than or equal to the preset safety distance, a warning message indicating that the safety distance is small is sent to the driving control terminal of the smart car.

4. The method according to claim 1, wherein: The step of performing recognition processing on each positioning code image in the positioning code image sequence to obtain the recognition code sequence includes: For each positioning code image in the positioning code image sequence, the following recognition steps are performed: Performing positioning code extraction processing on the positioning code image to obtain a positioning code extraction image; Inputting the positioning code image into a pre-trained positioning code feature extraction model to obtain positioning code feature information corresponding to the positioning code image; Acquire a code number corresponding to the positioning code feature information from a preset database; Determine the coded number as an identification code; According to the determined arrangement order of the positioning code images corresponding to the identification codes in the positioning code image sequence, the identification codes are arranged to obtain an identification code sequence.

5. The method according to claim 1, wherein: The performing error detection processing on the identification code sequence to obtain error detection information includes: Determine each identification code in the identification code sequence corresponding to the first preset index information as a first identification code sequence; Determine each identification code in the identification code sequence corresponding to the second preset index information as a second identification code sequence; Combining the first identification code sequence and the second identification code sequence to obtain a combined identification code sequence; Performing monotonicity detection processing on the combined sequence to obtain monotonicity detection information; In response to determining that the monotonicity detection information represents that the sequence is monotonically increasing, performing the following increasing sequence error detection processing: Determining the identification code sequence as an increasing sequence; Deleting each identification code in the increasing sequence corresponding to the combined identification code sequence to update the increasing sequence; For the first identification code in the updated incremental sequence, the following first determination step is performed: comparing the identification code with each identification code in the increasing sequence except the first identification code; In response to determining that the identification codes are all smaller than the respective identification codes, performing the following steps: Deleting the identification code from the ascending sequence to update the ascending sequence; In response to determining that the updated ascending sequence is not empty, performing the first determination step again according to the updated ascending sequence; In response to determining that the updated incremental sequence is empty, determining information characterizing that there is no error in the identification code sequence as error detection information; In response to determining that the identification code is greater than or equal to one of the identification codes, determining information indicating that an error exists in the identification code sequence as error detection information; In response to determining that the monotonicity detection information characterizing the sequence is monotonically decreasing, performing decreasing sequence error detection processing on the identification code sequence to obtain error detection information; In response to determining that the monotonicity detection information indicates that the sequence is non-monotonic, information indicating that errors exist in the identification code sequence is determined as error detection information.

6. The method according to claim 5, wherein: The step of performing a decreasing sequence error detection process on the identification code sequence to obtain error detection information includes: Determining the identification code sequence as a decreasing sequence; Deleting each identification code corresponding to the combined identification code sequence in the decreasing sequence to update the decreasing sequence; For the first identification code in the updated decreasing sequence, the following second determination step is performed: comparing the first identification code with each identification code in the decreasing sequence except the first identification code; In response to determining that the first identification code is greater than each identification code, performing the following steps: The first identification code is deleted from the decreasing sequence to update the decreasing sequence; In response to determining that the updated decreasing sequence is not empty, performing the second determination step again according to the updated decreasing sequence; In response to determining that the updated decrement sequence is empty, determining information characterizing that there is no error in the identification code sequence as error detection information; In response to determining that the identification code is less than or equal to one of the identification codes, information indicating that errors exist in the identification code sequence is determined as error detection information.

7. A smart car, comprising: Camera device, ultrasonic positioning device and driving angle detection device; one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

8. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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