A method for designing an OCC-based driving assistance information delivery system

Abstract

The application belongs to the technical field of optical communication and intelligent transportation, and particularly relates to a driving assistance information transmission system design method based on OCC; comprising six steps of encoding modulation, target identification, target tracking, region extraction, dynamic decoding and distance measurement and positioning; Manchester coding and self-defined coding are combined in the dynamic communication process to rearrange the data frame content, improve the system transmission information quantity, and transmit vehicle speed, steering and braking information; through an improved monocular imaging algorithm, a positioning method based on a fitting calibration method and a target image pixel deviation ratio is obtained, measurement error is reduced, and the distance and direction between vehicles are measured and calculated.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of optical communication and intelligent transportation, and particularly relates to a driving assistance information transmission system design method based on OCC. BACKGROUND

[0002] Ensuring driving safety is one of the important topics in the field of automatic driving of vehicles. As an important part of the automatic driving perception module, the vehicle-mounted camera can capture image information in front and rear of the vehicle for the purpose of environment perception and safety warning. The optical camera communication (OCC) technology further realizes information interaction between vehicles on the basis of the original function of the camera, can transmit rich driving assistance information, and effectively improves the safety and reliability of vehicle driving.

[0003] The light emitting diode (LED) array of the sending end of the OCC system can be integrated on the tail light of the front vehicle, the signal is mapped to the LED array through the modulation of the single-chip microcomputer and the driving amplification circuit, and the information is transmitted outward through a specific flashing mode. The camera of the receiving end is erected on the rear vehicle, the image of the target LED of the front vehicle is captured, and the signal is demodulated through an image processing algorithm to complete the information transmission process. The OCC technology takes optical signal as the carrier, has the advantages of no spectrum certification, no electromagnetic radiation, green environmental protection, etc., and can effectively make up for the problem of insufficient frequency band resources of wireless radio frequency communication.

[0004] The communication rate of the OCC technology depends on the number of LED lights, the modulation frequency of the single-chip microcomputer and the frame frequency of the camera. Due to the limitations of device size and cost, the way of improving the communication rate by improving the hardware performance has limitations, so it is necessary to improve the coding method to transmit more information under the limited communication rate, which is conducive to further improving the applicability of the OCC technology. There are problems such as large error and complex calculation method in distance measurement and positioning through monocular imaging principle of the camera. For the existing OCC system, a positioning method based on fitting calibration method and target image pixel deviation ratio is researched, which can accurately measure the distance and direction information between vehicles and effectively reduce the measurement error. SUMMARY

[0005] In order to overcome the above problems, the application provides a driving assistance information transmission system design method based on OCC. By adopting the combination of Manchester coding and self-defined coding in the dynamic communication process, the data frame content is rearranged, the information amount of the system is improved, and the vehicle speed, steering, braking and other information are transmitted. Through the improved monocular imaging algorithm, a positioning method based on fitting calibration method and target image pixel deviation ratio is obtained, the measurement error is reduced, and the distance and direction between vehicles are measured.

[0006] An OCC-based driving assistance information transmission system design method, including six steps of encoding modulation, target recognition, target tracking, region extraction, dynamic decoding and ranging positioning, the specific contents are as follows:

[0007] Step one, through the combination of Manchester coding and self-defined coding, the data frame content of the front vehicle driving information is arranged, and then the code elements are modulated by binary on-off keying and mapped to the LED array to continuously flash and transmit information to the outside; The specific steps are as follows:

[0008] (1) Redefine the data frame format transmitted by the sending end, including frame header, interval, data part, identification part and frame tail; The frame header is used to identify the beginning of the data frame, which is composed of four consecutive 1s; The interval part is 0, which is used to separate the frame header and the data part; The identification part includes sequence number and check bit, wherein the sequence number is used to identify the actual order of the frame, and special data frames are marked; The check bit adopts the form of even check, that is, when the total number of data part plus 1 in the check bit is even, the format of the data frame is correct; The frame tail is delimited by 0, which is used to separate the identification frame and the frame header part;

[0009] (2) The data part contains speed, steering and braking information, referring to the normal and legal driving speed of vehicles on the road, the speed integer bit interval is set to 0-255 in the form of 8-bit binary coding based on Manchester coding; The speed decimal part adopts 3-bit binary self-defined coding; Steering and braking information also adopts 3-bit binary self-defined coding, wherein 011, 101, 010 and 011 correspond to "straight, right turn, left turn and parking stop" and "parking stop, acceleration, braking and idling" information respectively, avoiding the occurrence of more than four consecutive 0 or 1 in the code element;

[0010] (2) The information coded in step (1) is modulated into the LED array in the form of OOK, and then the code element information is transmitted to the outside in the form of bright and dark flashing of each LED in the LED array;

[0011] Step two, the target recognition is to obtain the accurate position of the LED array by using the different characteristics of the LED array and the surrounding image, and the 808nm waveband optical filter is configured in front of the camera lens on the rear vehicle, and then the imaging position of the LED array on the front vehicle is detected by extracting the brightness information of the target LED array region, The specific content is as follows:

[0012] (1) The original gray-scale image containing the target LED array on the front vehicle is captured by the camera on the rear vehicle, and the gray-scale image is binarized by setting a threshold, as follows:

[0013]

[0014] Wherein a is the actual pixel value of any single pixel point on the image before the binarization operation, A is the pixel value after the threshold determination binarization, when a is greater than the threshold 105, the pixel value of the pixel point is assigned to 255; when a is less than the threshold 105, the pixel value of the pixel point is assigned to 0, and then a binary image represented as a two-dimensional logical matrix of MxN is obtained; the binary image is then dilated, eroded and closed to obtain the contour of the target LED array region;

[0015] (2) On the basis of the contour of the target LED array region obtained in step (1), draw the rectangular contour of the target LED array region; establish a coordinate system with the top left corner of the entire image as the coordinate origin, the upper boundary of the entire image as the x-axis and the left boundary as the y-axis, determine the coordinates D(x min , y min ) of the top left corner and the coordinates E(x max , y max ) of the bottom right corner of the rectangular contour of the target LED array; since the LED array used on the preceding vehicle is a square array, the rectangular contour is screened according to the aspect ratio characteristics of the LED array, as shown in the following formula:

[0016]

[0017] Wherein h is the vertical length of the target LED array region, and w is the horizontal length of the target LED array region; the required target LED array region is determined after screening; the maximum horizontal coordinate x max , the minimum horizontal coordinate x min , the maximum vertical coordinate y max , and the minimum vertical coordinate y min of the target LED array region are determined;

[0018] (3) The target region obtained in step (2) is expanded outward by 50 pixel values on each of the four sides to obtain an adjusted target region, and the top left corner coordinate of the region is D'(x min -50, y min -50), and the bottom right corner coordinate is E'(x max +50, y max +50);

[0019] Step three, continuously track the target region in the moving state, and the target region described below is the target region adjusted in step two; the specific content is as follows:

[0020] The target region coordinate information D' and E' are transmitted to the tracking algorithm, and the difference between the object trajectory in the forward and backward directions is measured, and the tracking reliability is ensured by minimizing the deviation, as shown in the following formula:

[0021] f =∑ (i，j) (I1(i, j) - I2(x + i, y + j)) 2

[0022] Where I1(i, j) is the position coordinate of a pixel point on the target region at t0, I2(x + i, y + j) is the position coordinate of the same pixel point after moving on the target region at t0 + 1, f is the sum of the forward and backward coordinate deviation values, and the smaller the f value, the better the consistency of the target moving trajectory, and the reliable trajectory is selected in the image, and the tracking coordinate information D' and E' are output in real time, and the target region is continuously tracked;

[0023] Step four, the dynamic target region continuously tracked is extracted, realizing the change from dynamic to pseudo-static of the target region;

[0024] Step five, the symbol information transmitted by the extracted target region in the moving state is captured and decoded by the rear camera, and the speed, steering and braking information of the front vehicle are obtained; The specific content is as follows:

[0025] The image information of the target region is demodulated by the direction projection method at the receiving end, and the positions of the LEDs are determined through the target region coordinate and the number and arrangement information of the LEDs, wherein the center coordinates of the imaging light spots of the positioning LEDs (i.e. the LEDs located at the four corners of the LED array) at the upper left corner, the lower left corner, the upper right corner and the lower right corner are (x min , y min ), (x min , y max ), (x max , y min ) and (x max , y max ), respectively. According to the center coordinates of the imaging light spots of the four positioning LEDs, the center coordinates (x LED，i , y LED，j ) information of the i-th row and j-th column LED in the LED array in the image is estimated, and the calculation is shown in the following formula:

[0026]

[0027] The value of k depends on the number of lamps in each row or column of the LED array, and the symbol state transmitted by the LED is determined by threshold discrimination, as shown in the following formula:

[0028]

[0029] If S ij = 1, the LED at i row j column in the LED array is in the on state, and the carried signal is decoded as 1; if S ij = 0, the LED at i row j column in the LED array is in the off state, and the carried signal is decoded as 0; by implementing the above decoding method, the 0, 1 symbol information carried by the target LED array image is demodulated, and then corresponding decoding is performed in combination with the Manchester coding and self-defined coding rules in step one; the vehicle speed, steering and braking information transmitted by the preceding vehicle are acquired;

[0030] Step six, by improving the camera monocular imaging method, a positioning method based on fitting calibration and target image pixel deviation ratio is adopted to measure the distance and direction between vehicles; the specific steps are as follows:

[0031] (1) The fitting calibration method is used to measure the vertical distance d between the sending end LED array and the receiving end camera. The receiving end camera is aligned with the sending end target LED array, and the target LED array image at different distances is photographed at 5-meter sampling interval in the distance interval of 10 to 80 meters, which is used for data formula fitting. After the image is processed by steps two to four, the target area is extracted, the number of pixels of the extracted target area in the vertical direction at different distances is calculated, and the corresponding distance information is fitted to obtain the calculation formula of the vertical distance d:

[0032] d = 1995.6 x x -0.949

[0033] Where x is the number of pixels of the extracted target LED array area in the vertical direction, which is calculated by the following formula:

[0034] x = y max -y min

[0035] (2) The actual distance s between the sending end LED array and the receiving end camera is calculated as follows:

[0036]

[0037]

[0038] Where, m is the maximum distance from the center of the camera object plane to the edge of the field of view, α is the camera field of view angle;

[0039] (3) further calculate the deviation direction and angle of the target LED array of the sending end relative to the center of the camera view field of the receiving end by calculating the difference between the center coordinates (x', y') of the target LED array and the center coordinates of the camera view field, wherein:

[0040]

[0041] If the horizontal coordinate x' of the center of the target LED array is greater than the horizontal coordinate of the center of the view field, it indicates that the front target LED array deviates to the right; if the horizontal coordinate x' of the center of the target LED array is less than the horizontal coordinate of the center of the view field, it indicates that the front target LED array deviates to the left; if the horizontal coordinate x' of the center of the target LED array is equal to the horizontal coordinate of the center of the view field, it indicates that the front target LED array is in the center position, so as to judge the deviation direction of the target LED array of the sending end relative to the center of the camera view field of the receiving end;

[0042] The deviation angle θ of the center of the LED array of the sending end relative to the center of the camera view field is calculated according to the following formula:

[0043]

[0044] The actual distance and specific position information between the vehicles are obtained.

[0045] The signal sending end on the front vehicle in the step one adopts an LED array with a wavelength of 808nm.

[0046] In the step (2), on the basis of the contour of the target LED array region obtained in the step (1), the cv2.findContours statement in the OpenCV software is called to draw the rectangular contour of the target LED array region.

[0047] In the step (3), the target region obtained in the step (2) is expanded by 50 pixel values outwardly on the four sides respectively by calling the cv2.rectangle statement in the OpenCV software, and the adjusted target region is obtained.

[0048] The beneficial effects of the present application are:

[0049] 1. The method disclosed in the present application can be used to construct a driving assistance information transmission system, and real-time transmission of vehicle speed, steering, braking, distance, position information can realize information interaction between vehicles, and improve the safety and reliability of vehicle driving.

[0050] 2. The encoding mode combining Manchester encoding and self-defined encoding in the method disclosed in the present application rearranges the data frame content, and improves the amount of system transmission information under limited communication rate.

[0051] 3. The positioning method based on the fitting calibration method and the target image pixel deviation ratio in the method has lower calculation complexity and higher measurement accuracy compared with a traditional positioning method. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art according to the contents of the embodiments of the present application and the drawings without creative labor.

[0053] Figure 1 The schematic diagram of the communication scene between vehicles for the OCC driving assistance information transmission system based on the present application.

[0054] Figure 2 The technical roadmap of the present application.

[0055] Figure 3 The schematic diagram of the data frame format of the present application.

[0056] Figure 4 The schematic diagram of the self-defined coding of the present application.

[0057] Figure 5 The schematic diagram of the profile of the target LED array obtained after the expansion corrosion operation of the present application.

[0058] Figure 6 The schematic diagram of the coordinate system establishment of the present application.

[0059] Figure 7 The schematic diagram of the target LED array region identified by the present application.

[0060] Figure 8 The schematic diagram of the target LED array region extended by the present application.

[0061] Figure 9 The schematic diagram of the target LED array region tracked by the present application.

[0062] Figure 10 The schematic diagram of the region extraction experimental results of the present application.

[0063] Figure 11 The schematic diagram of the interval 20m sampling partial image for data fitting of the present application.

[0064] Figure 12 The schematic diagram of the interval 40m sampling partial image for data fitting of the present application.

[0065] Figure 13The schematic diagram of the interval 60m sampling partial image for data fitting of the present application.

[0066] Figure 14 The schematic diagram of the interval 80m sampling partial image for data fitting of the present application.

[0067] Figure 15 The schematic diagram of the actual distance calculation based on the target image pixel deviation ratio of the present application.

[0068] Figure 16 The schematic diagram of the target deviation direction and angle calculation of the present application. DETAILED DESCRIPTION

[0069] The present application will be further described below in conjunction with the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application. In addition, it should be noted that, for the convenience of description, only the parts related to the present application are shown in the drawings, but not all the structures.

[0070] The present application provides a driving assistance information transmission system design method based on OCC. In order to make the technical solutions and characteristics of the present application more clear, the present application will be described in detail below in conjunction with the accompanying drawings.

[0071] Figure 1 The schematic diagram of the communication scene of the driving assistance information transmission system based on OCC between vehicles, vehicle A and vehicle B are respectively the sending end and receiving end of the OCC system. The sending end LED array can be integrated in the tail light of vehicle A. Vehicle A maps the speed, steering (left turn, right turn, straight ahead and parking stop), braking (acceleration, deceleration, idling and parking stop) information of its own driving onto the LED array after encoding and modulation, and transmits the information to the outside in the form of light signal through the continuous flashing of each LED; the receiving end camera is erected on the top of vehicle B and keeps the camera field of view facing forward. The camera on vehicle B takes a picture of the LED array on vehicle A in the field of view, obtains the target LED image, and demodulates the "0, 1" code information transmitted by the decoding method. At the same time, vehicle B measures the distance and direction information between the two vehicles by using the improved monocular imaging method, so as to form rich driving assistance information. The method flow realized by the present application is shown in Figure 2 The method flow realized by the present application is shown in

[0072] Step one, the signal sending end on the front vehicle uses LED array with wavelength of 808 nm, arranges the data frame content of the front vehicle driving information by combining Manchester coding and self-defined coding, improves the information transmission efficiency, then maps the code element to the LED array by binary on-off keying (OOK: On-Off Keying) modulation, constantly flashes to transmit information outward, and the specific steps are as follows:

[0073] (1) Redefine the data frame format transmitted by the sending end, as shown in the following formula (1), including frame header, interval, data part, identification part and frame tail; wherein the frame header is used to identify the beginning of the data frame, which is composed of four consecutive 1s and is easy to detect; the interval part is 0, which is used to separate the frame header and the data part; the identification part includes sequence number and check bit, wherein the sequence number is used to identify the actual order of the frame, so that the receiver can reorder the information, and mark the special data frame for identification; the check bit adopts even check, that is, when the total number of 1s in the data part plus the check bit is even, the format of the data frame is correct; the frame tail is delimited by 0, which is used to separate the identification frame and the frame header part; Figure 3

[0074] (2) The data part contains speed, steering and braking information, based on the normal and legal driving speed of the vehicle on the reference road, the speed integer bit interval is set to 0-255 in the form of 8-bit binary coding based on Manchester coding; the speed decimal bit adopts 3-bit binary self-defined coding, wherein 011, 101, 010 and 011 correspond to “0, 0.25, 0.5 and 0.75 km / h” respectively; the estimation interval of the decimal bit in such estimation mode is 0.25, that is, the maximum error does not exceed 0.125 km / h, which will not affect the driving safety; the steering and braking information also adopts 3-bit binary self-defined coding, wherein 011, 101, 010 and 011 correspond to “straight, right turn, left turn, parking stop” and “parking stop, acceleration, braking, idling” information respectively, and the corresponding relationship is shown in the following formula (2), which avoids the occurrence of more than four consecutive 0s or 1s in the code element. The combination of Manchester coding and self-defined coding makes the change of LED light and dark state more balanced, which will not affect the original function of the vehicle light, and it is easy to detect the data frame header to keep the information synchronization, which improves the information quantity by more than 2 times under the same rate condition. Figure 4

[0075] (3) The coded information in step (1) is mapped into the LED array in the form of OOK modulation, that is, the “1” code transmits high level to a single LED, which corresponds to the light-on state of the single LED; the “0” code transmits low level to a single LED, which corresponds to the light-off state of the single LED, then the code element information is transmitted to the outside world in the form of light-on and light-off flashing of each LED in the LED array.​​

[0076] Step two, the identification target is to use the LED array and the different characteristics of the surrounding image, get the accurate position of the LED array, configure the 808 nm waveband optical filter in front of the camera lens on the rear car, try to reduce the influence of other waveband light noise on the physical layer, and then detect the imaging position of the LED array on the front car by extracting the brightness information of the target LED array region. The specific content is as follows:

[0077] (1) Capture the original gray image containing the target LED array (i.e. the sending end target LED array) on the front car through the camera on the rear car (the image captured by the current test camera is a single channel gray image), and binarize the gray image by setting the threshold. After multiple experiments, the effect is better when the threshold is 105. The calculation method is as follows formula 1:

[0078]

[0079] Where a is the actual pixel value of any single pixel point (i.e. sampling point) on the image before binarization operation, and A is the pixel value after thresholding binarization. When a is greater than the threshold 105, the pixel value of the pixel point is assigned to 255; when a is less than the threshold 105, the pixel value of the pixel point is assigned to 0, and then a binary image represented by a two-dimensional logic matrix of MxN is obtained. Then perform closed operation of dilation and erosion on the binary image. This operation fills the small holes in the LED array and smooths the target region boundary. The calculation is as follows formula 2:

[0080]

[0081] Where is the dilation operation, is the erosion operation, B is the target LED array region of the original image, and C is the morphological operator. In this experimental system, the dilation coefficient is set to 20 and the erosion coefficient is set to 8. The dilation and erosion operators are both square matrix kernel form. The cv2.dilate and cv2.erode statements in OpenCV software are called to perform two closed operations respectively, and the contour of the target LED array region is obtained, as shown in the white area of Figure 5 ;

[0082] (2) Based on the contour of the target LED array region obtained in step (1), call the cv2.findContours statement in OpenCV software to draw the rectangular contour of the target LED array region. Take the top left corner of the camera captured image as the coordinate origin, and take the upper boundary of the whole image as the x axis and the left boundary as the y axis to establish a coordinate system, as shown in Figure 6 , determine the coordinates D(xmin , y min ) and the coordinate of the lower right corner vertex E(x max , y max ); since the LED array used on the front vehicle in the experiment is a 4*4 square array, the rectangular contour is screened according to the aspect ratio characteristics of the LED array, as shown in the following formula 3:

[0083]

[0084] where h is the vertical direction length of the target LED array region, and w is the horizontal direction length of the target LED array region; the target LED array region, i.e. the region of interest (ROI), required is determined through screening, as shown in the following formula 2: Figure 7 The maximum horizontal coordinate x max , the minimum horizontal coordinate x min , the maximum vertical coordinate y max , and the minimum vertical coordinate y min of the target LED array region are determined;

[0085] (3) The target region obtained by the recognition algorithm in step (2) is expanded outward by 50 pixel values on the four sides of the target region respectively (i.e. the four sides of the target region are translated outward by a distance of 50 pixel values) by calling the cv2.rectangle statement in the OpenCV software, to obtain an adjusted target region, the left upper corner vertex coordinate of which is D'(x min -50, y min -50), and the right lower corner vertex coordinate of which is E'(x max +50, y max +50), as shown in the following formula 3: Figure 8 This expansion allows the tracking algorithm to correct the slight deviation from the light source center and more accurately adapt to changes;

[0086] Step three, in order to continuously track the target region in the moving state, the target region described below is the target region adjusted in step two; the Median Flow-based machine learning algorithm is adopted in the present application, which has good tracking effect in the case of target deformation, interference and occlusion; the specific content is as follows:

[0087] The target region coordinate information D' and E are passed to the tracking algorithm, and after the initialization is completed, the tracking algorithm measures the difference between the forward and backward object trajectories at the same time, and adopts the minimum deviation method to ensure the tracking reliability, as shown in the following formula 4:

[0088] f = ∑ (i，j) (I1(i, j)-I2(x+i, y+j)) 2(4)

[0089] Wherein I1(i, j) is the position coordinate of a pixel point on the target area at t0, I2(x+i, y+j) is the position coordinate of the same pixel point after moving at t0+1, f is the sum of the front and rear coordinate deviation values, the smaller the f value, the better the consistency of the target trajectory, and the reliable trajectory is selected in the image, and the tracking coordinate information D' and E' and the algorithm overhead are output in real time, the target area is continuously tracked, and the tracking ROI is as shown in Figure 9

[0090] Step four, since the target LED array region obtained after step three tracking is dynamic, the position information of the moving target LED array region is changing all the time, the LED spatial position information in the moving process cannot be accurately positioned, and the decoding process cannot be completed, so it is necessary to extract the continuously tracked dynamic target region, and the OpenCV software is called region2 = region1[x min -90: x max +90, y min -90: y max +90] statement to extract a value slightly larger than the size of the target LED array region (in this experiment, the expanded pixel value is set to 90), realize the transition of the target region from dynamic to pseudo-static, extract the dynamic target region, and make the dynamic region pseudo-static; region extraction is the premise of realizing dynamic communication, and the effect after extraction is as shown in Figure 10

[0091] Step five, the identification target, tracking target, and region extraction process in the above steps are equivalent to establishing a communication link of free space optical communication, and on this basis, the dynamic communication process can be realized. The rear camera captures and decodes the symbol information transmitted by the extracted target region in the moving state, and obtains the speed, steering, and braking information of the front vehicle; the specific content is as follows:

[0092] The image information of the target region is demodulated by the direction projection method at the receiving end, the positions of the LEDs are determined through the target region coordinates and the number and arrangement information of the LEDs, wherein the center coordinates of the imaging spots of the positioning LEDs (i.e. the LEDs located at the four corners of the LED array) at the upper left corner, the lower left corner, the upper right corner, and the lower right corner of the array are (x min , y min ), (x min , y max ), (x max , y min ), and (x max , y max ​​), according to the center coordinates of the four positioning LED imaging spots, the center coordinates (x LED，i , y LED，j ) of the LED in the i-th row and the j-th column in the LED array in the image are estimated, and the information is calculated as shown in the following formula 5:

[0093]

[0094] The value of k depends on the number of lamps in each row or each column of the LED array (in this experiment, the value of k is 4), and then the threshold value is determined to determine the symbol state carried by the LED, as shown in the following formula 6:

[0095]

[0096] If S ij = 1, the LED in the i-th row and the j-th column of the LED array is in the on state, and the signal carried is decoded as 1; if S ij = 0, the LED in the i-th row and the j-th column of the LED array is in the off state, and the signal carried is decoded as 0; through the implementation of the above decoding method, the 0, 1 symbol information carried by the target LED array image is demodulated, and then combined with the Manchester coding and the self-defined coding rule in step one to perform corresponding decoding, and 001 respectively represent "0.75km / h" in the decimal place of the speed, "parking stop" in the steering information and "idling" in the braking information; the vehicle speed, steering and braking information transmitted by the preceding vehicle are acquired.

[0097] Step six, by improving the monocular imaging method of the camera, using the positioning method based on the fitting calibration method and the target image pixel deviation ratio, the distance and direction between vehicles are measured, and the measurement error is reduced; the specific steps are as follows:

[0098] (1) The OCC technology has certain requirements for the number, spacing and arrangement of the LED array lamps of the sending end, and the imaging size of the LED at the receiving end is relative, but the number of pixel points occupied by the imaging area is absolute. Based on the above points, the fitting calibration method is used to measure the vertical distance d between the sending end (i.e. the LED array on the preceding vehicle) and the receiving end (i.e. the camera on the following vehicle) (wherein the vertical distance d is the vertical distance between the plane where the rear end of the LED array is located and the plane where the front end of the camera is located);

[0099] The picture acquisition process for the calibration fitting method of measuring the vertical distance is as follows: the receiving end camera and the sending end target LED array are placed on the same straight line (i.e. the center of the field of view of the receiving end camera is aligned with the center point of the sending end target LED array, so that the line connecting the center of the field of view of the receiving end camera and the center point of the sending end target LED array is in the horizontal or vertical direction), and at 5-meter intervals, images of the target LED array at different distances are taken in the distance range of 10 to 80 meters for fitting of the data formula; some images are shown in Figure 11-14 , and after the captured images are processed through steps two to four, the target region is extracted, the number of pixels occupied by the extracted target LED array region in the vertical direction at different distances is calculated, and the corresponding distance information is fitted to obtain the calculation formula 7 of the vertical distance d:

[0100] d = 1995.6 x x -0.949 (7)

[0101] where x is the number of pixels occupied by the extracted target LED array region in the vertical direction, which is calculated by formula 8 as follows:

[0102] x = y max -y min (8)

[0103] Because the number of pixels occupied by the image in the vertical direction on the same horizontal line is the same, the d calculated by the above formula 7 is the vertical distance between the sending end LED array and the receiving end camera;

[0104] (2) The principle diagram for calculating the actual distance s between the sending end LED array and the receiving end camera (the actual distance s is the actual distance between the center of the field of view of the receiving end camera and the center point of the LED array) is shown in Figure 15 .

[0105]

[0106]

[0107] where m is the maximum distance from the center of the field of view of the camera object plane to the edge, α is the camera field of view angle;

[0108] The derivation process is as follows:

[0109] According to the vertical distance d obtained in (1), the maximum horizontal distance m (i.e. the maximum distance from the center of the field of view of the camera object plane to the edge m) in the field of view of the camera is calculated in combination with the camera field of view angle α, as formula 9:

[0110]

[0111] According to the target region coordinate information obtained by the tracking algorithm in step two, the center coordinate (x', y') of the target LED array imaging region is calculated as shown in the following formula 10:

[0112]

[0113] The absolute value of the difference between the horizontal center coordinate x' of the target LED array imaging region and the horizontal center coordinate of the camera field of view (1024 in this experiment) is obtained, and the pixel number a of the center coordinate of the target LED array imaging region deviating from the center of the camera field of view is obtained as shown in the following formula 11:

[0114] a = |x' - 1024| (11)

[0115] The resolution of the camera used in this experiment is 2048*2048, so the pixel number A (1024 in this experiment) of half of the field of view range is obtained, and the pixel deviation proportion q of the actual imaging position of the target LED array compared with the center position of the camera field of view is obtained as shown in the following formula 12:

[0116]

[0117] The actual deviation distance n of the actual position of the target LED array in the camera object plane compared with the center of the camera field of view is obtained, that is, the horizontal distance between the center point of the LED array and the center of the camera field of view on the object plane, which is calculated as shown in the following formula 13:

[0118]

[0119] Further, the actual distance s between the sending end LED array and the receiving end camera is calculated by the Pythagorean theorem as shown in the following formula 14:

[0120]

[0121] (3) Based on the calculation process in (2), the difference between the center coordinate (x', y') of the target LED array and the center coordinate of the camera field of view (the horizontal center coordinate of the field of view is 1024 in this experiment) is calculated as shown in formula 15, and the deviation direction and angle of the sending end target LED array relative to the center of the receiving end camera field of view are further calculated as shown in formula 16, where: Figure 16

[0122]

[0123]

[0124] ​If the horizontal coordinate x' of the center of the target LED array is greater than the horizontal coordinate 1024 of the center of the field of view, it indicates that the target LED array in front deviates to the right; if the horizontal coordinate x' of the center of the target LED array is less than the horizontal coordinate 1024 of the center of the field of view, it indicates that the target LED array in front deviates to the left; if the horizontal coordinate x' of the center of the target LED array is equal to the horizontal coordinate 1024 of the center of the field of view, it indicates that the target LED array in front is in the central position, so as to determine the deviation direction of the target LED array of the sending end compared with the center of the field of view of the camera of the receiving end (i.e. the deviation direction of the front vehicle compared with the rear vehicle);

[0125] The deviation angle θ of the center of the LED array of the sending end compared with the center of the field of view of the camera (i.e. the deviation angle of the front vehicle compared with the rear vehicle) is calculated by the vertical distance d between the target LED array of the sending end and the camera of the receiver and the deviation distance n of the target LED array compared with the center of the field of view of the camera in formula (2) again, and the calculation is as shown in the following formula 16:

[0126]

[0127] The actual distance and the specific position information between the vehicles are obtained through the above steps.

[0128] The preferred embodiments of the present application are described in detail above with reference to the accompanying drawings, but the protection scope of the present application is not limited to the specific details in the above embodiments. Any person skilled in the art within the technical concept range of the present application can make equivalent replacement or change according to the technical solution and the inventive concept of the present application within the technical range disclosed by the present application, and these simple modifications all belong to the protection scope of the present application.

Claims

1. A design method for a driver assistance information transmission system based on OCC, characterized in that... include: The process involves six steps: encoding and modulation, target identification, target tracking, region extraction, dynamic decoding, and ranging and localization. The specific details are as follows: Step 1: The data frame content of the vehicle's driving information is arranged by combining Manchester encoding and custom encoding. The code elements are then mapped onto the LED array through binary on / off keying modulation, and the information is continuously transmitted outward by flashing. The specific steps are as follows: (1) Redefine the data frame format transmitted by the sending end, including frame header, interval, data part, identifier part and frame trailer; the frame header is used to identify the beginning of the data frame and consists of four consecutive 1s; the interval part is 0 and is used to separate the frame header and the data part; the identifier part includes sequence number and check bit, where the sequence number is used to identify the actual order of the frames and to mark special data frames; the check bit adopts even parity, that is, when the total number of 1s in the data part plus the check bit is even, the data frame format is correct; the frame trailer is delimited by 0 and is used to separate the identifier frame and the frame header part. (2) The data section includes speed, steering and braking information. Referring to the normal legal driving speed of vehicles on the road, an 8-bit binary encoding based on Manchester encoding is adopted, and the integer part of the speed is set to 0-255; the decimal part of the speed is encoded using a 3-bit binary custom encoding; the steering and braking information are also encoded using a 3-bit binary custom encoding, where 011, 101, 010 and 011 correspond to "straight, right turn, left turn, park and stop" and "park and stop, accelerate, brake, idle speed" respectively, to avoid the code element having more than 4 consecutive 0s or consecutive 1s; (3) The information encoded in step (1) is mapped onto the LED array in the form of OOK modulation, and then the code information is transmitted to the outside world in the form of each LED in the LED array turning on and off and flashing. Step two, target identification, involves using the different features of the LED array compared to the surrounding image to obtain the accurate location of the LED array. An 808nm optical filter is placed in front of the camera lens on the rear vehicle. Then, by extracting the brightness information of the target LED array area, the imaging position of the LED array on the front vehicle is detected. The specific details are as follows: (1) Capture the original grayscale image containing the target LED array on the front vehicle using the camera on the rear vehicle, and binarize the grayscale image by setting a threshold, as shown in the following formula: Where 'a' is the actual pixel value of any single pixel in the image before binarization, and A is the pixel value after binarization by thresholding. When 'a' is greater than the threshold of 105, the pixel value of that pixel is assigned the value of 255; when 'a' is less than the threshold of 105, the pixel value of that pixel is assigned the value of 0, thus obtaining a binary image represented as an M×N two-dimensional logical matrix; then, the binary image is subjected to dilation and erosion closing operations to obtain the contour of the target LED array region. (2) Based on the outline of the target LED array region obtained in step (1), draw the rectangular outline of the target LED array region; establish a coordinate system with the upper left corner vertex of the entire image captured by the camera as the origin, the upper boundary of the entire image as the x-axis and the left boundary as the y-axis, and determine the coordinates D(x) of the upper left corner vertex of the rectangular outline of the target LED array. min y min ) and the coordinates E(x) of the lower right vertex max y max Since the LED array used on the preceding vehicle is a square array, the rectangular outline is selected based on the aspect ratio characteristics of the LED array, as shown in the following formula: Where h is the vertical length of the target LED array region and w is the horizontal length of the target LED array region; the required target LED array region is determined through screening. Determine the maximum x-coordinate of the target LED array region. max Minimum x-coordinate min , the maximum value of the ordinate y max and the minimum value of the ordinate y min ; (3) For the target area obtained in step (2), extend each of the four sides of the target area outward by 50 pixels to obtain the adjusted target area. The coordinates of the top left vertex of this area are D′(x min -50, y min -50), the coordinates of the lower right vertex are E′(x max +50, y max +50); Step 3: Continuously track the target area while it is moving. The target areas described below are the ones adjusted in Step 2. Details are as follows: The target area coordinates D′ and E′ are passed to the tracking algorithm. Simultaneously, the difference between the tracked object's trajectory in the forward and backward directions is measured. The tracking reliability is ensured by minimizing the deviation, as shown in the following formula: f=∑ (i，j) (I1(i,j)-I2(x+i,y+j)) 2 Where I1(i, j) is the position coordinate of a pixel in the target region at time t0, and I2(x+i, y+j) is the position coordinate of a pixel in the target region at time t0. o +1 time, the position coordinates of the same pixel in the target area after the movement, f is the sum of the coordinate deviations before and after, the smaller the value of f, the better the consistency of the target movement trajectory, and a reliable trajectory is selected in the image, and the tracking coordinate information D′ and E′ is output in real time to continuously track the target area; Step four: Extract the continuously tracked dynamic target region to transform the target region from dynamic to pseudo-static. Step 5: The rear vehicle's camera captures and decodes the symbolic information transmitted from the moving target area to obtain the speed, steering, and braking information of the preceding vehicle. The specific details are as follows: At the receiving end, the image information of the target area is demodulated using the directional projection method. The position of each LED is determined by the target area coordinates and the number and arrangement information of the LEDs. Specifically, the center coordinates of the imaging spots of the positioning LEDs at the top left, bottom left, top right, and bottom right corners of the array (i.e., the LEDs located at the four corners of the LED array) are (x...). min y min ), (x min y max ), (x max y min ) and (x max y max Based on the center coordinates of the four positioning LED imaging spots, estimate the center coordinates (x, y) of the LED in the i-th row and j-th column of the LED array in the image. LED，i y LED，j The information is calculated using the following formula: The value of k depends on the number of LEDs in each row or column of the LED array. The state of the transmitted symbols of the LEDs is then determined by a threshold, as shown in the following formula: If S ij =1, then the LED at row i and column j in the LED array is lit, and the signal it carries is decoded as 1; if S ij =0, then the LED in row i and column j of the LED array is in an off state, and the signal it carries is decoded as 0; through the above decoding method, the 0 and 1 symbol information transmitted by the target LED array image is demodulated, and then the corresponding decoding is performed by combining the Manchester encoding and custom encoding rules in step one. Acquire vehicle speed, steering and braking information transmitted by the vehicle in front; Step six: By improving the monocular imaging method of the camera, a positioning method based on fitting calibration and target image pixel deviation ratio is adopted to calculate the distance and orientation between vehicles; the specific steps are as follows: (1) The vertical distance d between the transmitting LED array and the receiving camera is measured using a fitting calibration method. The receiving camera is aligned with the transmitting target LED array. Images of the target LED array at different distances are taken at sampling intervals of 5 meters, ranging from 10 to 80 meters. These images are used to fit the data formula. The captured images are then processed through steps two to four to obtain the extracted target area. The number of pixels in the vertical direction of the extracted target area at different distances is calculated and fitted with the corresponding distance information to obtain the formula for calculating the vertical distance d. d=1995.6×x -0.949 Where x is the number of pixels in the vertical direction of the extracted target LED array region, which is calculated by the following formula; x | y max -and min (2) Calculate the actual distance s between the transmitting LED array and the receiving camera using the following formula: Where m is the maximum distance from the center of the camera's field of view to the edge. α is the camera's field of view angle; (3) By calculating the difference between the center coordinates (x′, y′) of the target LED array and the center coordinates of the camera's field of view, the deviation direction and angle of the target LED array at the transmitting end relative to the center of the camera's field of view are further calculated, where: If the x-coordinate of the target LED array center is greater than the x-coordinate of the field of view center, it means that the target LED array in front is biased to the right; if the x-coordinate of the target LED array center is less than the x-coordinate of the field of view center, it means that the target LED array in front is biased to the left; if the x-coordinate of the target LED array center is equal to the x-coordinate of the field of view center, it means that the target LED array in front is in the center position. This can be used to determine the direction of deviation of the target LED array at the transmitting end relative to the center of the field of view of the receiving end camera. Then calculate the deviation angle θ between the center point of the transmitting LED array and the center of the camera's field of view using the following formula: The above provides information on the actual distance and specific location between the vehicles.

2. The design method of a driving assistance information transmission system based on OCC according to claim 1, characterized in that... In step one, the signal transmitting end on the front vehicle uses an LED array with a wavelength of 808nm.

3. The design method of a driving assistance information transmission system based on OCC according to claim 1, characterized in that... In step two (2), based on the outline of the target LED array region obtained in step (1), the cv2.findContours statement in OpenCV software is called to draw the rectangular outline of the target LED array region.

4. The design method of a driving assistance information transmission system based on OCC according to claim 1, characterized in that... In step two (3), the target region obtained in step (2) is extended outward by 50 pixels on each of the four sides by calling the cv2.rectangle statement in the OpenCV software to obtain the adjusted target region.

Images