Road variable information board control system with intelligent light sensation adjustment

Abstract

The invention relates to the technical field of information board control, and discloses an intelligent light sensation adjustment road variable information board control system, which comprises a data acquisition unit, a data processing unit, a brightness adjustment unit, a display optimization unit and a fault detection module, the brightness adjusting unit can adaptively adjust the brightness of the information board and the brightness of each light-emitting unit according to different illumination, and energy-saving and display effects are considered; the display optimization unit is used for processing the display content image to enhance the display definition under different illumination; on one hand, the fault detection module performs fault detection on the light sensor to guarantee reliable data acquisition; on the other hand, by comparing the similarity of the content image template and the displayed content image, the integrity of the display content is detected, and if an abnormality is found, an early warning signal is generated in time to ensure accurate transmission of traffic information; according to the invention, from illumination perception, brightness and contrast adjustment to fault detection, efficient and stable operation of the road variable information board is guaranteed in all directions.

Description

Technical Field

[0001] The invention relates to the technical field of information board control, and in particular to a road variable information board control system with intelligent light sensing adjustment. Background Art

[0002] In modern traffic management, road variable information boards play a vital role. They can promptly transmit various traffic information to drivers, such as road conditions, weather, accident warnings, etc., which is of great significance for ensuring road traffic safety and improving traffic operation efficiency.

[0003] However, existing variable road information boards face many challenges in practical applications. On the one hand, different lighting environments have a huge impact on the display effect of the information board. In low-light environments, such as at night or on cloudy days, if the brightness of the information board is too high, it will not only cause energy waste, but also may stimulate the driver's vision and affect driving safety; insufficient brightness will make the information difficult to see and unable to be effectively transmitted. In high-light environments, such as direct sunlight on sunny days, if the brightness of the information board is not enough, the content is easily covered by the strong light, which also affects the driver's acquisition of information. On the other hand, the contrast of the current information board display content lacks an adaptive adjustment mechanism under different lighting conditions. In low-light environments, if the contrast is not appropriately increased, the information will appear blurred; in high-light environments, if the contrast is not reduced, the image may have too bright or too dark areas, which is also not conducive to the driver to read the information clearly.

[0004] In addition, existing variable road signage systems also have deficiencies in detecting sensor failures and display content integrity. If the light sensor fails, the brightness and contrast of the signage system may not be adjusted based on accurate lighting data, which can seriously affect the display effect. The lack of detection of display content integrity means that when the display content of the signage system is partially missing or erroneous, it cannot be discovered and repaired in a timely manner, reducing the accuracy and reliability of traffic information transmission.

[0005] Therefore, there is an urgent need for a road variable information board control system that can intelligently adjust the light sensitivity to solve the above problems and improve the intelligence level of traffic management and the quality of traffic information services. Summary of the invention

[0006] The purpose of the present invention is to provide a road variable information board control system with intelligent light sensing adjustment, which solves the technical problems raised in the background technology.

[0007] The purpose of the present invention can be achieved through the following technical solutions: A road variable information sign control system with intelligent light sensing adjustment, comprising: The data collection unit is used to evenly distribute a plurality of light sensors on the surface of the variable information board on the road, and then divide the information board into a number of areas of equal area, and then install a light sensor at the center of each area, and the light sensor collects light intensity data in real time; The data processing unit is used to pre-process the light intensity data collected by the data collection unit, and determine the current light environment according to the pre-processing result; The brightness adjustment unit is used to adaptively adjust the brightness of the information board according to the current lighting environment; The display optimization unit is used to adaptively adjust the contrast of the content displayed on the information board according to the current lighting environment.

[0008] As a further solution of the present invention: wherein the information board is composed of m light-emitting units.

[0009] As a further solution of the present invention: the pretreatment method is as follows: The light intensity collected by each light sensor is marked as G i , i=1, 2, ... n, n represents the number of light sensors; pass: ; Calculate the average light intensity G0; Then the average light intensity G0 is compared with the preset light intensity threshold interval [Gy min ,Gy max ] to compare, and determine the current lighting environment based on the comparison result; Among them, Gy min <Gy max ; When G0<Gy min When , the current lighting environment is determined to be a low-light environment; WhenGy min ≤G0≤Gy max When , the current lighting environment is determined to be a normal lighting environment; When G0>Gy max When , the current lighting environment is determined to be a high lighting environment.

[0010] As a further solution of the present invention: the brightness adaptive adjustment method is as follows: Step U1, extract the initial brightness of the information board and mark it as L0, and extract the preset brightness adjustment coefficient and mark it as k; StepU2, extract the initial brightness of each light-emitting unit and mark it as LF0 j , j = 1, 2, ... m; If the current lighting environment is a low-light environment, the brightness adjustment value of each light-emitting unit of the information board is LFd. j =LF0 j ×(1+k); If the current lighting environment is a high-light environment, the brightness adjustment value of each light-emitting unit of the information board is (1-k); If the current lighting environment is normal, the current brightness adjustment value of the information board is: LFd j =LF0 j ; Step U3, extract the proportionality coefficient between the brightness of the light-emitting unit and the driving current, and mark it as g; StepU4, pass: D j =LFd j / g; Calculate the driving current D of each light-emitting unit j ; Step U5, based on the driving current D of each light-emitting unit j , adjust the brightness of each light-emitting unit.

[0011] As a further solution of the present invention: wherein the brightness of the light-emitting unit is proportional to the driving current.

[0012] As a further solution of the present invention: the contrast adaptive adjustment method is as follows: Step D1, obtain the content image displayed on the information board, then convert it into a grayscale image, and then obtain the grayscale value of each pixel on the gray image and mark it as H u , u=1, 2, ...e, e represents the total number of pixels in the gray image; Step D2, through: ; Calculate the average pixel value H0 of all pixels on the gray image; Step D3, extracting a preset contrast adjustment index and marking it as b0, and then determining a contrast adjustment coefficient b of the information board display content according to the current lighting environment; Step D4, through: ; Calculate the contrast adjustment value H1 for each pixel value u ; Step D5, adjusting the contrast of the displayed content according to the contrast adjustment value of each pixel value.

[0013] As a further solution of the present invention: the contrast adjustment coefficient is determined as follows: If the current lighting environment is a low-light environment, the contrast adjustment coefficient of the information board display content is: b=(1+b0); If the current lighting environment is a normal lighting environment, the contrast adjustment coefficient of the information board display content is: b=1; If the current lighting environment is a high-light environment, the contrast adjustment coefficient of the information board display content is: b= (1-b0).

[0014] As a further solution of the present invention: also include: The fault detection module is used to perform sensor fault detection on multiple light sensors set on the surface of the information board, and determine whether the sensor is faulty based on the detection results; it is also used to perform integrity detection on the display content of the information board, and determine whether the content is complete based on the detection results.

[0015] As a further solution of the present invention: the sensor fault detection method is as follows: Step G1. Obtain the light intensity data collected by the light sensor at multiple collection time nodes within the specified observation period, and mark each light intensity as G. i，f , f=1, 2, ... z, z represents the number of acquisition time nodes in the specified period; Step G2, first select a light sensor, then: ; Calculate the average value of the light intensity Gp of the light sensor at multiple acquisition time nodes during the observation period i ; Also through: ; Calculate the standard deviation Ga of the light intensity of each light sensor at multiple acquisition time nodes during the observation period i ; Step G3, then select a collection time node, and then: ; Calculate the average light intensity G0 of multiple light sensors at each acquisition time node during the observation period i ; Also through: ; Calculate the light intensity difference Gc corresponding to each light sensor at each acquisition time node during the observation period i,f ; Step G4, then calculate the standard deviation Ga of the light intensity of each light sensor at multiple acquisition time nodes. i Compare it with the corresponding preset standard deviation threshold Gay, and calculate the light intensity difference Gc corresponding to each light sensor at each acquisition time node i,fCompare with the corresponding preset intensity difference threshold Gcy; When Ga i ≥Gay and Gc i,f If at least one of the conditions in ≥Gcy is true, the corresponding light sensor is judged to be faulty; When Ga i ≥Gay and Gc i,f If all of ≥Gcy are not true, it is determined that the corresponding light sensor has no fault.

[0016] As a further solution of the present invention: the integrity detection method is as follows: Step W1, obtain the content image template and the displayed content image of the information board; The displayed content image refers to the image corresponding to the traffic information actually displayed on the current information board; the content image template is the image corresponding to the preset traffic information content; Step W2, adjusting the resolution of the content image template and the displayed content image to be consistent; Step W3, extract the grayscale value of each pixel on the content image template and the displayed content image, and separate them into E1 （x，y） and E2 （x，y） ; Wherein, x=1, 2, ... q1, y=1, 2, ... q2, q1 represents the number of columns of pixels corresponding to the content image template and the displayed content image, and q2 represents the number of rows of pixels corresponding to the content image template and the displayed content image; StepW4, through the mean square error algorithm: ; Calculate the MSE similarity between the content image template and the displayed content image; StepW5, compare the similarity MSE with the preset mean square error threshold MSEy: When MSE>MSEy, the display content is determined to be incomplete or erroneous, and a display content failure warning signal is generated; otherwise, no display content failure warning signal is generated.

[0017] Beneficial effects of the present invention: Accurate light perception and environmental judgment: The data collection unit can comprehensively and accurately collect light intensity data in real time by evenly distributing light sensors on the surface of the information board and installing sensors at the center of the divided area. The data processing unit calculates the average light intensity based on these data and compares it with the preset threshold range to accurately determine whether the current light environment is low light, normal light or high light, providing a reliable basis for subsequent adjustments.

[0018] Adaptive brightness adjustment: The brightness adjustment unit makes targeted adjustments to the overall brightness of the information board and the brightness of each light-emitting unit according to different lighting environments. The brightness is increased in low-light environments and reduced in high-light environments, which not only ensures that road users can clearly obtain information under various lighting conditions, but also effectively avoids energy waste or visual discomfort caused by excessive brightness, achieving a good balance between energy saving and display effects.

[0019] Adaptive optimization of display contrast: The display optimization unit converts the information board display content image into a grayscale image, calculates the average pixel value, determines the contrast adjustment coefficient based on different lighting environments, and adjusts the contrast of each pixel value, which significantly enhances the display clarity under different lighting conditions and ensures that the information is presented more clearly and easily readable.

[0020] Light sensor fault detection: The fault detection module conducts in-depth analysis of the light intensity data of multiple acquisition time nodes for light sensors within a specified observation period. By calculating the average value, standard deviation, and light intensity difference between different sensors and comparing them with the preset threshold, it can timely and accurately detect whether there is a sensor fault, thereby ensuring the reliability of the data collection link and maintaining the stable operation of the entire intelligent light adjustment system.

[0021] Display content integrity detection: The fault detection module further performs integrity detection on the information board display content. By obtaining the content image template and the displayed content image, unifying the resolution, and using the mean square error algorithm to calculate the similarity between the two, and comparing with the preset mean square error threshold, it can quickly determine whether the displayed content is complete or wrong. Once an abnormality is detected, a display content fault warning signal is generated in a timely manner, which helps to promptly discover and solve problems related to the display content and ensure accurate communication of traffic information. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The present invention will be further described below in conjunction with the accompanying drawings.

[0023] Figure 1 The present invention is a system block diagram of a road variable information board control system with intelligent light sensing adjustment.

[0024] Figure 2 The present invention is a module function diagram of a fault detection module in a road variable information board control system with intelligent light sensing adjustment. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] Embodiment 1 See also Figure 1 and Figure 2 As shown, the present invention is a road variable information sign control system with intelligent light sensing adjustment, comprising: The data collection unit is used to evenly distribute multiple light sensors on the surface of the variable information board on the road, and then divide the information board into several areas of equal area. Then a light sensor is installed at the center of each area. The light sensor collects light intensity data in real time, and the light intensity collected by each light sensor is marked as G i , i=1, 2, ... n, n represents the number of light sensors; The data processing unit is used to pre-process the light intensity data collected by the data collection unit. The pre-processing method is as follows: First pass: ; Calculate the average light intensity G0; Then the average light intensity G0 is compared with the preset light intensity threshold interval [Gy min ,Gy max ] to compare, and determine the current lighting environment based on the comparison result; Among them, Gy min <Gy max ; When G0<Gy min When , the current lighting environment is determined to be a low-light environment; WhenGy min ≤G0≤Gy max When , the current lighting environment is determined to be a normal lighting environment; When G0>Gy max When , the current lighting environment is determined to be a high lighting environment; The brightness adjustment unit is used to adaptively adjust the brightness of the information board according to the current lighting environment. The method is as follows: Step U1, extract the initial brightness of the information board and mark it as L0, and extract the preset brightness adjustment coefficient and mark it as k; StepU2. If the current lighting environment is a low-light environment, the current brightness adjustment value of the information board is: Ld=L0×(1+k); If the current lighting environment is a normal lighting environment, the current brightness adjustment value of the information board is: Ld=L0; If the current lighting environment is a high-light environment, the current brightness adjustment value of the information board is: Ld=L0×(1-k); The information board is composed of m light-emitting units, and the initial brightness of each light-emitting unit is extracted and marked as LF0. j , j = 1, 2, ... m; In low light conditions, the brightness adjustment value of each light emitting unit is LFd j =LF0 j ×(1+k); In a high light environment, the brightness adjustment value of each light emitting unit is LFd j =LF0 j × (1-k); Step U3, extract the proportionality coefficient between the brightness of the light-emitting unit and the driving current, and mark it as g; In this embodiment, the brightness of the light-emitting unit is proportional to the driving current; StepU4, pass: D j =LFd j / g; Calculate the driving current D of each light-emitting unit j ; The brightness of the light-emitting unit is adjusted by controlling the driving current; In this example: In low light conditions, the driving current of the relevant light-emitting unit is adjusted to D j =[LF0 j × (1+k)] / g; In a high light environment, the driving current of the relevant light-emitting unit is adjusted to D j =[LF0 j × (1-k)] / g; Step U5, based on the driving current D of each light-emitting unit j , adjust the brightness of each light-emitting unit.

[0027] In this embodiment, the data acquisition unit evenly distributes light sensors on the surface of the information board and installs them in the center of the partition, which can collect light intensity data in all directions and in real time, providing rich and accurate raw data for subsequent processing; the data processing unit calculates the average light intensity and compares it with the preset threshold interval to accurately divide the three lighting environments of low, normal and high, providing a reliable basis for brightness adjustment; the brightness adjustment unit makes targeted adjustments to the brightness of the entire information board and each light-emitting unit according to different lighting environments. Increasing the brightness in a low-light environment and reducing the brightness in a high-light environment not only ensures the visibility of information, but also avoids energy waste and visual discomfort, achieving a balance between energy saving and display effect.

[0028] Embodiment 2 See also Figure 1 and Figure 2 As shown, as the second embodiment of the present invention, when the present application is implemented, compared with the first embodiment, the technical solution of this embodiment is different from that of the first embodiment only in that the present embodiment further includes: The display optimization unit is used to adaptively adjust the contrast of the information board display content according to the current lighting environment. The contrast adaptive adjustment method is as follows: Step D1, obtain the content image displayed on the information board, then convert it into a grayscale image, and then obtain the grayscale value of each pixel on the gray image and mark it as H u , u=1, 2, ...e, e represents the total number of pixels in the gray image; Step D2, through: ; Calculate the average pixel value H0 of all pixels on the gray image; Step D3, extracting a preset contrast adjustment index and marking it as b0, and then determining a contrast adjustment coefficient b of the information board display content according to the current lighting environment; If the current lighting environment is a low-light environment, the contrast adjustment coefficient of the information board display content is: b=(1+b0); If the current lighting environment is a normal lighting environment, the contrast adjustment coefficient of the information board display content is: b=1; If the current lighting environment is a high-light environment, the contrast adjustment coefficient of the information board display content is: b = (1-b0); Step D4, through: ; Calculate the contrast adjustment value H1 for each pixel value u ; In this embodiment, the contrast adjustment value is used to enhance the display clarity under different lighting conditions; Step D5, adjusting the contrast of the displayed content according to the contrast adjustment value of each pixel value.

[0029] This embodiment adds a display optimization function based on the first embodiment; the display optimization unit adjusts the contrast of the information board display content through a series of calculations according to different lighting environments. The contrast is increased in low-light environments and reduced in high-light environments, thereby enhancing the clarity of the display content under different lighting conditions, allowing road users to obtain information more clearly.

[0030] Embodiment 3 See also Figure 1 and Figure 2 As shown, as the third embodiment of the present invention, when the present application is implemented, compared with the first and second embodiments, the technical solution of this embodiment is to combine the solutions of the first and second embodiments, and the difference between the technical solution of this embodiment and the first and second embodiments is that in this embodiment, it also includes: A fault detection module is used to detect sensor faults using multiple light sensors installed on the surface of the information board, and to determine whether the sensor is faulty based on the detection results; Sensor fault detection methods are as follows: Step G1. Obtain the light intensity data collected by the light sensor at multiple collection time nodes within the specified observation period, and mark each light intensity as G. i，f , f=1, 2, ... z, z represents the number of acquisition time nodes in the specified period; Step G2, first select a light sensor, then: ; Calculate the average value of the light intensity Gp of the light sensor at multiple acquisition time nodes during the observation period i ; Also through: ; Calculate the standard deviation Ga of the light intensity of each light sensor at multiple acquisition time nodes during the observation period i ; Step G3, then select a collection time node, and then: ; Calculate the average light intensity G0 of multiple light sensors at each acquisition time node during the observation period i ; Also through: ; Calculate the light intensity difference Gc corresponding to each light sensor at each acquisition time node during the observation period i,f ; Step G4, then calculate the standard deviation Ga of the light intensity of each light sensor at multiple acquisition time nodes. i Compare it with the corresponding preset standard deviation threshold Gay, and calculate the light intensity difference Gc corresponding to each light sensor at each acquisition time node i,f Compare with the corresponding preset intensity difference threshold Gcy; When Ga i ≥Gay and Gc i,f If at least one of the conditions in ≥Gcy is true, it is determined that the corresponding light sensor is faulty; When Ga i ≥Gay and Gc i,f If all of ≥Gcy are not true, it is determined that the corresponding light sensor has no fault.

[0031] Based on Embodiments 1 and 2, this embodiment adds a fault detection module; the fault detection module calculates and analyzes the light intensity data of the light sensor at multiple time nodes within a specified observation period, including the average value, standard deviation, light intensity difference, etc., and compares it with the preset threshold value. It can timely and accurately detect whether there is a fault in the sensor, thereby ensuring the reliability of the data collection link and ensuring the stable operation of the entire system.

[0032] Embodiment 4 See also Figure 1 and Figure 2 As shown, as the fourth embodiment of the present invention, when the present application is specifically implemented, compared with the first embodiment, the second embodiment and the third embodiment, the difference between the present embodiment and the first embodiment, the second embodiment and the third embodiment is that in the present embodiment, the fault detection module is also used for integrity detection of the display content of the information board, and whether the content is complete is determined according to the detection result; The integrity test method is as follows: Step W1, obtain the content image template and the displayed content image of the information board; In this embodiment, the displayed content image refers to the image corresponding to the traffic information actually displayed on the current information board; for example, the image formed by the speed limit sign, road condition prompts and other contents displayed on the information board; the content image template is the image corresponding to the pre-set and correct traffic information content; it is a reference standard used for comparison with the actual displayed content image to detect whether the displayed content is complete and accurate; for example, for a specific traffic instruction, there is a standard image template, which includes all elements and layouts such as text, graphics, colors, etc. that should be displayed; Step W2, adjusting the resolution of the content image template and the displayed content image to be consistent; Step W3, extract the grayscale value of each pixel on the content image template and the displayed content image, and separate them into E1 （x，y） and E2 （x，y） ; Wherein, x=1, 2, ... q1, y=1, 2, ... q2, x represents the horizontal coordinate of the pixel after the corresponding resolutions of the content image template and the displayed content image are adjusted to be consistent, y represents the vertical coordinate of the pixel after the corresponding resolutions of the content image template and the displayed content image are adjusted to be consistent, q1 represents the number of columns of pixels corresponding to the content image template and the displayed content image, and q2 represents the number of rows of pixels corresponding to the content image template and the displayed content image; StepW4, through the mean square error algorithm: ; Calculate the MSE similarity between the content image template and the displayed content image; StepW5, compare the similarity MSE with the preset mean square error threshold MSEy: When MSE>MSEy, the display content is determined to be incomplete or erroneous, and a display content failure warning signal is generated; otherwise, no display content failure warning signal is generated.

[0033] This embodiment further expands the function of the fault detection module on the basis of the first, second and third embodiments; the fault detection module obtains the content image template and the displayed content image, unifies the resolution, calculates the similarity between the two using the mean square error algorithm, and compares it with the preset mean square error threshold to quickly determine whether the displayed content is complete or wrong. Once an abnormality is found, an early warning signal is generated in time, which helps to timely discover and solve the display content problem and ensure the accurate transmission of traffic information.

[0034] Embodiment 5 See also Figure 1 and Figure 2 As shown, as the fifth embodiment of the present invention, when the present application is implemented specifically, compared with the first, second, third and fourth embodiments, the technical solution of this embodiment is to combine the solutions of the above-mentioned first, second, third and fourth embodiments for implementation.

[0035] This embodiment combines all the advantages of the previous four embodiments; it realizes accurate light data collection and light environment judgment, ensures adaptive adjustment of brightness, and improves display clarity; it can perform fault detection on light sensors to ensure reliable data collection; at the same time, it performs integrity detection on the display content, promptly discovers and warns of display content problems, and comprehensively guarantees the efficient and stable operation of the road variable information board, providing accurate and clear traffic information for road users.

[0036] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0037] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A road variable information sign control system with intelligent light sensing adjustment, characterized in that: include: The data collection unit is used to evenly distribute a plurality of light sensors on the surface of the variable information board on the road, and then divide the information board into a number of areas of equal area, and then install a light sensor at the center of each area, and the light sensor collects light intensity data in real time; The data processing unit is used to pre-process the light intensity data collected by the data collection unit, and determine the current light environment according to the pre-processing result; The brightness adjustment unit is used to adaptively adjust the brightness of the information board according to the current lighting environment; Display optimization unit, used to adaptively adjust the contrast of the information board display content according to the current lighting environment; A fault detection module is used to detect sensor faults using multiple light sensors installed on the surface of the information board, and to determine whether the sensor is faulty based on the detection results; It is also used to perform integrity checks on the displayed content of information boards, and to determine whether the content is complete based on the test results.

2. According to claim 1, a road variable information sign control system with intelligent light sensing adjustment is characterized in that: The preprocessing method is as follows: The light intensity collected by each light sensor is marked as G i , i=1, 2, ... n, n represents the number of light sensors; Calculate the light intensity marker G i The average value is recorded as the average light intensity G0; Then the average light intensity G0 is compared with the preset light intensity threshold interval [Gy min ,Gy max ] for comparison, and determine the current lighting environment based on the comparison results.

3. According to claim 2, a road variable information sign control system with intelligent light sensing adjustment is characterized in that: The lighting environment is determined as follows: Among them, Gy min <Gy max ; When G0<Gy min When , the current lighting environment is determined to be a low-light environment; WhenGy min ≤G0≤Gy max When , the current lighting environment is determined to be a normal lighting environment; When G0>Gy max When , the current lighting environment is determined to be a high lighting environment.

4. According to claim 3, a road variable information sign control system with intelligent light sensing adjustment is characterized in that: in, The information board consists of m light-emitting units.

5. The intelligent light-sensing-adjustable road variable information sign control system according to claim 4 is characterized in that: The brightness adaptive adjustment method is as follows: Step U1, extract the initial brightness of the information board and mark it as L0, and extract the preset brightness adjustment coefficient and mark it as k; StepU2, extract the initial brightness of each light-emitting unit and mark it as LF0 j , j = 1, 2, ... m; If the current lighting environment is a low-light environment, the brightness adjustment value of each light-emitting unit of the information board is LFd. j =LF0 j ×(1+k); If the current lighting environment is a high-light environment, the brightness adjustment value of each light-emitting unit of the information board is (1-k); If the current lighting environment is normal, the current brightness adjustment value of the information board is: LFd j =LF0 j ; Step U3, extract the proportionality coefficient between the brightness of the light-emitting unit and the driving current, and mark it as g; Step U4, calculate the driving current of each light-emitting unit by dividing the current brightness adjustment value of the information board by the proportional coefficient g between the brightness of the light-emitting unit and the driving current, and record it as D j ; Step U5, based on the driving current D of each light-emitting unit j , adjust the brightness of each light-emitting unit.

6. The intelligent light-sensing-adjustable road variable information sign control system according to claim 5 is characterized in that: in, The brightness of the light-emitting unit is proportional to the driving current.

7. The intelligent light-sensing-adjustable road variable information sign control system according to claim 3 is characterized in that: The contrast adaptive adjustment method is as follows: Step D1, obtain the content image displayed on the information board, then convert it into a grayscale image, and then obtain the grayscale value of each pixel on the gray image and mark it as H u , u=1, 2, ...e, e represents the total number of pixels in the gray image; Step D2, calculate the gray value H of each pixel on the gray image u The average value of is recorded as the average pixel value H0; Step D3, extracting a preset contrast adjustment index and marking it as b0, and then determining a contrast adjustment coefficient b of the information board display content according to the current lighting environment; Step D4, through: ; Calculate the contrast adjustment value H1 for each pixel value u ; Step D5, adjusting the contrast of the displayed content according to the contrast adjustment value of each pixel value.

8. The intelligent light-sensing-adjustable road variable information sign control system according to claim 7 is characterized in that: The contrast adjustment factor is determined as follows: If the current lighting environment is a low-light environment, the contrast adjustment coefficient of the information board display content is: b=(1+b0); If the current lighting environment is a normal lighting environment, the contrast adjustment coefficient of the information board display content is: b=1; If the current lighting environment is a high-light environment, the contrast adjustment coefficient of the information board display content is: b= (1-b0).

9. The intelligent light-sensing-adjustable road variable information sign control system according to claim 1 is characterized in that: Sensor fault detection methods are as follows: Step G1. Obtain the light intensity data collected by the light sensor at multiple collection time nodes within the specified observation period, and mark each light intensity as G. i，f , f=1, 2, ... z, z represents the number of acquisition time nodes in the specified period; Step G2: First, select a light sensor and calculate the average light intensity of the light sensor at multiple acquisition time nodes during the observation period, and record it as Gp i ; Gp-binding i , calculate the standard deviation of the light intensity of each light sensor at multiple acquisition time nodes during the observation period, and record it as Ga i ; Step G3, then select a collection time node, calculate the average value of the light intensity corresponding to multiple light sensors at each collection time node during the observation period, and record it as G0 i ; Also through: ; Calculate the light intensity difference Gc corresponding to each light sensor at each acquisition time node during the observation period i,f ; Step G4, then calculate the standard deviation Ga of the light intensity of each light sensor at multiple acquisition time nodes. i Compare it with the corresponding preset standard deviation threshold Gay, and calculate the light intensity difference Gc corresponding to each light sensor at each acquisition time node i,f Compare with the corresponding preset intensity difference threshold Gcy; When Ga i ≥Gay and Gc i,f If at least one of the conditions in ≥Gcy is true, it is determined that the corresponding light sensor is faulty; When Ga i ≥Gay and Gc i,f If all of ≥Gcy are not true, it is determined that the corresponding light sensor has no fault.

10. The intelligent light-sensing-adjustable road variable information sign control system according to claim 1, characterized in that: The integrity test method is as follows: Step W1, obtain the content image template and the displayed content image of the information board; The displayed content image refers to the image corresponding to the traffic information actually displayed on the current information board; the content image template is the image corresponding to the preset traffic information content; Step W2, adjusting the resolution of the content image template and the displayed content image to be consistent; Step W3, extract the grayscale value of each pixel on the content image template and the displayed content image, and separate them into E1 （x，y） and E2 （x，y） ; Wherein, x=1, 2, ... q1, y=1, 2, ... q2, q1 represents the number of columns of pixels corresponding to the content image template and the displayed content image, and q2 represents the number of rows of pixels corresponding to the content image template and the displayed content image; StepW4, through the mean square error algorithm: ; Calculate the MSE similarity between the content image template and the displayed content image; StepW5, compare the similarity MSE with the preset mean square error threshold MSEy: When MSE>MSEy, it is determined that the display content is incomplete or erroneous, and a display content failure warning signal is generated; otherwise, no display content failure warning signal is generated.

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