A truck collision warning control system for toll stations

Abstract

The present invention discloses a toll station truck collision warning control system; including a safety line, a video acquisition module, a carriage identification module, a data transmission module, an analysis module, a barrier control module, a voice prompt module and a display module; the safety line is arranged on the outside of the card issuing machine / payment machine at the toll station, and is arranged horizontally along the road, for warning the safety of the card issuing machine / payment machine. The toll station truck collision warning control system in the present invention can detect the position of the truck compartment, and can determine whether the position of the truck compartment exceeds the safety line, and when it exceeds the safety line, a voice prompt is given, and a warning screen is displayed on the screen to remind the driver to pay attention, until the driver adjusts the position of the compartment, the barrier is opened to allow the vehicle to pass, thereby avoiding the risk of collision and increasing the protection of the card issuing machine / payment machine.

Description

Technical Field

[0001] The invention belongs to the technical field of safety warning, and in particular relates to a truck collision warning control system at a toll station. Background Art

[0002] Toll booths are facilities used to collect tolls from passing vehicles. Toll booths must be set up on toll roads or toll interchanges. There are generally two types of toll booths: one is directly set up on the main line, also known as the roadblock type, which is mostly used at the start and end of the main line toll section; the other is set up on the interchange road or connecting line, which is generally used for the industrial interchange between the main line toll sections to control the toll of vehicles on the intersecting road entering and exiting the main line. Generally, a card issuing machine / payment machine is set up at the toll booth for calculation and payment.

[0003] Existing truck drivers often get close to the card issuing machine / payment machine when entering a toll station for the convenience of taking out / putting in the card. Since the truck body is wide or the loaded cargo is over-wide, the card issuing machine / payment machine may be scratched when the truck body passes through, thereby causing damage to the card issuing machine / payment machine. For this reason, we propose a toll station truck collision warning control system. Summary of the invention

[0004] The purpose of the present invention is to provide a toll station truck collision warning control system to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: A toll station truck collision warning control system, comprising a safety line, a video acquisition module, a carriage identification module, a data transmission module, an analysis module, a barrier machine control module, a voice prompt module and a display module;

[0006] The safety line is arranged outside the card issuing machine / payment machine at the toll station and is arranged horizontally along the road to warn about the safety of the card issuing machine / payment machine;

[0007] The video acquisition module is arranged on the side of the card issuing machine / payment machine, and is used to collect video data of the position of the safety line and detect the compartment of the truck;

[0008] The carriage identification module is in communication with the video acquisition module and is used to detect the position of the carriage in real time according to the video data and generate real-time data of the position of the carriage;

[0009] The data transmission module is communicatively connected to the carriage identification module and is used to transmit real-time data of the position of the carriage to the analysis module;

[0010] The analysis module is in communication with the data transmission module, and is used to receive the real-time data of the position of the carriage, and determine whether the position of the carriage exceeds the safety line according to the real-time data of the position of the carriage;

[0011] The barrier machine control module is in communication connection with the analysis module, and is used to control the barrier machine to open or close the barrier;

[0012] The voice prompt module is in communication with the analysis module and is used to give a voice prompt when the position of the carriage exceeds the safety line;

[0013] The display module is communicatively connected to the analysis module, and is used to display a warning screen when the position of the carriage exceeds the safety line to remind the driver to pay attention.

[0014] Preferably, the video acquisition module includes a detection camera and an image processing unit. The detection camera is installed on the side of the card issuing machine / payment machine and is used to collect video data of the security line position. The image processing unit is used to pre-process the image in the collected video data to obtain a de-fogged clear image.

[0015] Preferably, the method in which the image processing unit preprocesses the image in the video data comprises the following steps: for the video data affected by weather, for the fog image equation I(x)=J(x)t(x)+A(1-t(x)), a peak signal-to-noise ratio PSNR is introduced, and the optimal t(x) is obtained by finding the extreme value of the peak signal-to-noise ratio, wherein I(x) is the color value of the fog image, J(x) is the color value when there is no fog in the scene, A is the color value of the sky, A=max(max(dark_I)), wherein dark_I is the dark channel image, and t(x) is the transmittance distribution rate of the fog in the sky.

[0016] Preferably, the image processing unit obtains a defogged clear image by specifically comprising the following steps:

[0017] a. Read the video frame image f(x, y) in the video data;

[0018] b. The dark channel image is obtained by dark_I = min(fr(x, y), fg(x, y), fb(x, y)), where fr(x, y), fg(x, y) and fb(x, y) are the color values ​​of the three channels of the color image;

[0019] c. The image model after removing the weather effect is established as follows:

[0020]

[0021] d. Manually input or set the system to calculate the corresponding transmission distribution rate t(x); the range of w is 0-1, when w is 0-0.3, it is a rainy day, when w is 0-0.7, it is a foggy day, and when w is 0.7-1, it is a dusty day; from the shadow channel algorithm, we know that the range of the transmission distribution rate t(x) is: 0.1-0.3;

[0022] e. Calculate t(x)=1-w×(max(min(fr(x,y),fg(x,y),fb(x,y))));

[0023] f. According to the established image model after removing the weather effect, a set of images J(x) after eliminating the weather effect is calculated; the peak signal-to-noise ratio (PSNR) of the image after eliminating the weather effect and the original foggy image is calculated,

[0024] in, MSE is the mean square error and Where f(i, j) is the image affected by weather;

[0025] g. According to the given step size, increase w and repeat steps e to f to obtain the new image J(x) after eliminating the weather effect and the corresponding peak signal-to-noise ratio (PSNR) of the original foggy image;

[0026] h. If the signal-to-noise ratio increases by less than 0.01 or the signal-to-noise ratio decreases, proceed to step i, otherwise repeat g;

[0027] i. Output the current video frame image corresponding to the optimal w1 and t1(x) without the weather influence.

[0028] Preferably, the car identification module includes a receiving unit, a recognition model training unit and an output unit; the receiving unit is used to receive the video data; the recognition model training unit is used to construct an image recognition model based on RegNet, randomly divide the video data into a test set and a training set, and train and optimize the image recognition model until the image recognition model's recognition accuracy for the car reaches a preset threshold; the output unit is used to recognize the image in the video data based on the trained image recognition model, and output the recognition result of the position of the car.

[0029] Preferably, the data transmission module includes a data processing unit, and the data processing unit is used to perform noise reduction processing on the real-time data of the position of the carriage, and the steps of the noise reduction processing include:

[0030] Acquire real-time data of the position of the carriage, wherein the real-time data of the position of the carriage is a single variable time series signal;

[0031] Reconstructing the phase space in the embedding dimensional space based on the single variable time series signal to obtain the phase space matrix of the prime mover system;

[0032] performing singular value decomposition on the phase space matrix;

[0033] Calculate the effective reconstruction order of the phase space matrix and obtain the main singular value of the phase space matrix;

[0034] The main singular values ​​of the phase space matrix are used to reconstruct the signal to obtain a de-noised signal, thereby achieving de-noising processing of the real-time data of the position of the carriage.

[0035] Preferably, the signal reconstruction using the principal singular values ​​of the phase space matrix specifically includes: constructing a principal element matrix of the phase space matrix, calculating each principal component of the reconstructed signal; calculating the reconstructed signal based on the calculated principal components and the empirical orthogonal functions EOF corresponding to each principal component.

[0036] Preferably, the toll station truck collision warning control system also includes a protection module, which includes an anti-collision steel plate. The bottom end of the anti-collision steel plate is fixedly mounted on the ground, and the side of the anti-collision steel plate is in contact with the side of the card issuing machine / payment machine. The anti-collision steel plate is used to protect the card issuing machine / payment machine to prevent the card issuing machine / payment machine from being scratched.

[0037] Preferably, the toll station truck collision warning control system also includes an alarm module, and the alarm module includes an audible and visual alarm, and the audible and visual alarm is installed on the top of the barrier machine to generate audible and visual alarms to alert the driver.

[0038] Preferably, the toll station truck collision warning control system detects the truck compartment in the following steps:

[0039] S1. Collect video data of the safety line position and detect the truck compartment;

[0040] S2. Detecting the position of the carriage in real time according to the video data, generating real-time data of the position of the carriage;

[0041] S3 analyzes the real-time data of the position of the carriage, and determines whether the position of the carriage exceeds the safety line based on the real-time data of the position of the carriage, if not, enters S4, if so, enters S5;

[0042] S4. The barrier machine opens the barrier, lifts the pull rod to release, and ends the warning work;

[0043] S5. Give a voice prompt and display a warning screen to remind the driver to keep the barrier closed and adjust the position of the car. Repeat S1-S3 until the position of the car does not exceed the safety line.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] (1) The toll station truck collision warning control system of the present invention can detect the position of the truck compartment and determine whether the position of the truck compartment exceeds the safety line. When the position exceeds the safety line, a voice prompt is given and a warning screen is displayed on the screen to remind the driver to pay attention. The barrier machine will not open until the driver adjusts the compartment position, thereby avoiding the risk of collision and increasing the protection of the card issuing machine / payment machine.

[0046] (2) The video acquisition module in the present invention can process the video image to obtain a clear image without fogging, thereby improving the clarity of the video image and facilitating the compartment recognition module to identify the compartment position. In addition, the compartment recognition module in the present invention can identify the compartment position in the video image according to a preset image recognition model, thereby improving the accuracy of compartment recognition.

[0047] (3) The present invention provides a voice prompt module and a display module, which can provide voice prompts and display a warning screen at the same time to remind the driver to pay attention, thereby improving the warning effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a structural block diagram of the present invention;

[0049] Figure 2 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0050] 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.

[0051] See also Figure 1-Figure 2 ,The present invention provides a technical solution: a toll station truck collision warning control system, including a safety line, a video acquisition module, a carriage identification module, a data transmission module, an analysis module, a barrier machine control module, a voice prompt module and a display module;

[0052] The safety line is arranged outside the card issuing machine / payment machine at the toll station and is arranged horizontally along the road to warn about the safety of the card issuing machine / payment machine;

[0053] The video acquisition module is arranged on the side of the card issuing machine / payment machine, and is used to collect video data of the position of the safety line and detect the compartment of the truck;

[0054] The carriage identification module is in communication with the video acquisition module and is used to detect the position of the carriage in real time according to the video data and generate real-time data of the position of the carriage;

[0055] The data transmission module is communicatively connected to the carriage identification module and is used to transmit real-time data of the position of the carriage to the analysis module;

[0056] The analysis module is in communication with the data transmission module, and is used to receive the real-time data of the position of the carriage, and determine whether the position of the carriage exceeds the safety line according to the real-time data of the position of the carriage;

[0057] The barrier machine control module is in communication connection with the analysis module, and is used to control the barrier machine to open or close the barrier;

[0058] The voice prompt module is in communication with the analysis module and is used to give a voice prompt when the position of the carriage exceeds the safety line;

[0059] The display module is communicatively connected to the analysis module, and is used to display a warning screen when the position of the carriage exceeds the safety line to remind the driver to pay attention.

[0060] In this embodiment, preferably, the video acquisition module includes a detection camera and an image processing unit. The detection camera is installed on the side of the card issuing machine / payment machine and is used to collect video data of the security line position. The image processing unit is used to pre-process the image in the collected video data to obtain a de-fogged clear image.

[0061] In this embodiment, preferably, the method for preprocessing the image in the video data by the image processing unit includes the following steps: for the video data affected by weather, for the fog image equation I(x)=J(x)t(x)+A(1-t(x)), the peak signal-to-noise ratio PSNR is introduced, and the optimal t(x) is obtained by finding the extreme value of the peak signal-to-noise ratio, wherein I(x) is the color value of the fog image, J(x) is the color value when there is no fog in the scene, A is the sky color value, A=max(max(dark_I)), wherein dark_I is the dark channel image, and t(x) is the transmittance distribution rate of fog in the sky.

[0062] In this embodiment, preferably, the image processing unit obtains a clear image after defogging, specifically comprising the following steps:

[0063] a. Read the video frame image f(x, y) in the video data;

[0064] b. The dark channel image is obtained by dark_I = min(fr(x, y), fg(x, y), fb(x, y)), where fr(x, y), fg(x, y) and fb(x, y) are the color values ​​of the three channels of the color image;

[0065] c. The image model after removing the weather effect is established as follows:

[0066]

[0067] d. Manually input or set the system to calculate the corresponding transmission distribution rate t(x); the range of w is 0-1, when w is 0-0.3, it is a rainy day, when w is 0-0.7, it is a foggy day, and when w is 0.7-1, it is a dusty day; from the shadow channel algorithm, we know that the range of the transmission distribution rate t(x) is: 0.1-0.3;

[0068] e. Calculate t(x)=1-w×(max(min(fr(x,y),fg(x,y),fb(x,y))));

[0069] f. According to the established image model after removing the weather effect, a set of images J(x) after eliminating the weather effect is calculated; the peak signal-to-noise ratio (PSNR) of the image after eliminating the weather effect and the original foggy image is calculated,

[0070] in, MSE is the mean square error and Where f(i, j) is the image affected by weather;

[0071] g. According to the given step size, increase w and repeat steps e to f to obtain the new image J(x) after eliminating the weather effect and the corresponding peak signal-to-noise ratio (PSNR) of the original foggy image;

[0072] h. If the signal-to-noise ratio increases by less than 0.01 or the signal-to-noise ratio decreases, proceed to step i, otherwise repeat g;

[0073] i. Output the current video frame image corresponding to the optimal w1 and t1(x) without the weather influence.

[0074] In this embodiment, preferably, the car identification module includes a receiving unit, a recognition model training unit and an output unit; the receiving unit is used to receive the video data; the recognition model training unit is used to construct an image recognition model based on RegNet, randomly divide the video data into a test set and a training set, and train and optimize the image recognition model until the image recognition model's recognition accuracy for the car reaches a preset threshold; the output unit is used to recognize the image in the video data based on the trained image recognition model, and output the recognition result of the position of the car.

[0075] In this embodiment, preferably, the data transmission module includes a data processing unit, and the data processing unit is used to perform noise reduction processing on the real-time data of the position of the carriage, and the steps of the noise reduction processing include:

[0076] Acquire real-time data of the position of the carriage, wherein the real-time data of the position of the carriage is a single variable time series signal;

[0077] Reconstructing the phase space in the embedding dimensional space based on the single variable time series signal to obtain the phase space matrix of the prime mover system;

[0078] performing singular value decomposition on the phase space matrix;

[0079] Calculate the effective reconstruction order of the phase space matrix and obtain the main singular value of the phase space matrix;

[0080] The main singular values ​​of the phase space matrix are used to reconstruct the signal to obtain a de-noised signal, thereby achieving de-noising processing of the real-time data of the position of the carriage.

[0081] In this embodiment, preferably, the signal reconstruction using the principal singular values ​​of the phase space matrix specifically includes: constructing a principal element matrix of the phase space matrix, calculating each principal component of the reconstructed signal; calculating the reconstructed signal based on the calculated principal components and the empirical orthogonal functions EOF corresponding to each principal component.

[0082] In the present embodiment, preferably, the truck collision warning control system at the toll station also includes a protection module, the protection module includes an anti-collision steel plate, the bottom end of the anti-collision steel plate is fixedly mounted on the ground, and the side of the anti-collision steel plate is in contact with the side of the card issuing machine / payment machine, and the anti-collision steel plate is used to protect the card issuing machine / payment machine to prevent the card issuing machine / payment machine from being scratched.

[0083] In this embodiment, preferably, the toll station truck collision warning control system also includes an alarm module, and the alarm module includes an audible and visual alarm. The audible and visual alarm is installed on the top of the barrier machine to generate audible and visual alarms to alert the driver.

[0084] In this embodiment, preferably, the step of detecting the compartment of the truck by the toll station truck collision warning control system includes:

[0085] S1. Collect video data of the safety line position and detect the truck compartment;

[0086] S2. Detecting the position of the carriage in real time according to the video data, generating real-time data of the position of the carriage;

[0087] S3 analyzes the real-time data of the position of the carriage, and determines whether the position of the carriage exceeds the safety line based on the real-time data of the position of the carriage, if not, enters S4, if so, enters S5;

[0088] S4. The barrier machine opens the barrier, lifts the pull rod to release, and ends the warning work;

[0089] S5. Give a voice prompt and display a warning screen to remind the driver to keep the barrier closed and adjust the position of the car. Repeat S1-S3 until the position of the car does not exceed the safety line.

[0090] Principles and advantages of the present invention:

[0091] The toll station truck collision warning control system of the present invention can detect the position of the truck compartment and determine whether the position of the truck compartment exceeds the safety line. When exceeding the safety line, a voice prompt is given and a warning screen is displayed on the screen to remind the driver to pay attention. The barrier machine will not open until the driver adjusts the compartment position, thereby avoiding the risk of collision and increasing the protection of the card issuing machine / payment machine.

[0092] The video acquisition module in the present invention can process the video image to obtain a clear image without fogging, thereby improving the clarity of the video image, providing convenience for the carriage recognition module to identify the carriage position, and in conjunction with the carriage recognition module in the present invention, it can identify the carriage position in the video image according to a preset image recognition model, thereby improving the accuracy of carriage recognition;

[0093] The present invention provides a voice prompt module and a display module, so as to provide a voice prompt and display a warning screen at the same time, so as to remind the driver to pay attention, thereby improving the warning effect.

[0094] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A toll station truck collision warning control system, characterized in that: It includes a safety line, a video acquisition module, a carriage identification module, a data transmission module, an analysis module, a barrier control module, a voice prompt module and a display module; The safety line is arranged outside the card issuing machine / payment machine at the toll station and is arranged horizontally along the road to warn about the safety of the card issuing machine / payment machine; The video acquisition module is arranged on the side of the card issuing machine / payment machine, and is used to collect video data of the position of the safety line and detect the compartment of the truck; The carriage identification module is in communication with the video acquisition module and is used to detect the position of the carriage in real time according to the video data and generate real-time data of the position of the carriage; The data transmission module is communicatively connected to the carriage identification module and is used to transmit real-time data of the position of the carriage to the analysis module; The analysis module is in communication with the data transmission module, and is used to receive the real-time data of the position of the carriage, and determine whether the position of the carriage exceeds the safety line according to the real-time data of the position of the carriage; The barrier machine control module is in communication connection with the analysis module, and is used to control the barrier machine to open or close the barrier; The voice prompt module is in communication with the analysis module and is used to give a voice prompt when the position of the carriage exceeds the safety line; The display module is communicatively connected to the analysis module, and is used to display a warning screen when the position of the carriage exceeds the safety line to remind the driver to pay attention.

2. A toll station truck collision warning control system according to claim 1, characterized in that: The video acquisition module includes a detection camera and an image processing unit. The detection camera is installed on the side of the card issuing machine / payment machine and is used to collect video data of the security line position. The image processing unit is used to pre-process the image in the collected video data to obtain a clear de-fogged image.

3. A toll station truck collision warning control system according to claim 2, characterized in that: The method for preprocessing the image in the video data by the image processing unit comprises the following steps: for the video data affected by weather, for the fog image equation I(x)=J(x)t(x)+A(1-t(x)), introducing the peak signal-to-noise ratio PSNR, and obtaining the optimal t(x) by finding the extreme value of the peak signal-to-noise ratio, wherein I(x) is the color value of the fog image, J(x) is the color value when there is no fog in the scene, A is the sky color value, A=max(max(dark_I)), wherein dark_I is the dark channel image, and t(x) is the transmittance distribution rate of the fog in the sky.

4. A toll station truck collision warning control system according to claim 3, characterized in that: The image processing unit obtains a clear image after defogging, specifically comprising the following steps: a. Read the video frame image f(x, y) in the video data; b. The dark channel image is obtained by dark_I = min(fr(x, y), fg(x, y), fb(x, y)), where fr(x, y), fg(x, y) and fb(x, y) are the color values ​​of the three channels of the color image; c. The image model after removing the weather effect is established as follows: d. Manually input or set the system to calculate the corresponding transmission distribution rate t(x); the range of w is 0-1, when w is 0-0.3, it is a rainy day, when w is 0-0.7, it is a foggy day, and when w is 0.7-1, it is a dusty day; from the shadow channel algorithm, we know that the range of the transmission distribution rate t(x) is: 0.1-0.3; e. Calculate t(x)=1-w×(max(min(fr(x,y),fg(x,y),fb(x,y)))); f. According to the established image model after removing the weather effect, a set of images J(x) after eliminating the weather effect is calculated; the peak signal-to-noise ratio (PSNR) of the image after eliminating the weather effect and the original foggy image is calculated, in, MSE is the mean square error and Where f(i, j) is the image affected by weather; g. According to the given step size, increase w and repeat steps e to f to obtain the new image J(x) after eliminating the weather effect and the corresponding peak signal-to-noise ratio (PSNR) of the original foggy image; h. If the signal-to-noise ratio increases by less than 0.01 or the signal-to-noise ratio decreases, proceed to step i, otherwise repeat g; i. Output the current video frame image corresponding to the optimal w1 and t1(x) without the weather impact.

5. A toll station truck collision warning control system according to claim 1, characterized in that: The carriage recognition module includes a receiving unit, a recognition model training unit and an output unit; the receiving unit is used to receive the video data; The recognition model training unit is used to build an image recognition model based on RegNet, randomly divide the video data into a test set and a training set, and train and optimize the image recognition model until the recognition accuracy of the image recognition model for the carriage reaches a preset threshold; The output unit is used to recognize the image in the video data based on the trained image recognition model, and output the recognition result of the position of the carriage.

6. A toll station truck collision warning control system according to claim 1, characterized in that: The data transmission module includes a data processing unit, and the data processing unit is used to perform noise reduction processing on the real-time data of the position of the carriage, and the steps of the noise reduction processing include: Acquire real-time data of the position of the carriage, wherein the real-time data of the position of the carriage is a single variable time series signal; Reconstructing the phase space in the embedding dimensional space based on the single variable time series signal to obtain the phase space matrix of the prime mover system; performing singular value decomposition on the phase space matrix; Calculate the effective reconstruction order of the phase space matrix and obtain the main singular value of the phase space matrix; The main singular values ​​of the phase space matrix are used to reconstruct the signal to obtain a de-noised signal, thereby achieving de-noising processing of the real-time data of the position of the carriage.

7. A toll station truck collision warning control system according to claim 6, characterized in that: The signal reconstruction using the principal singular values ​​of the phase space matrix specifically includes: constructing a principal element matrix of the phase space matrix, calculating each principal component of the reconstructed signal; and calculating the reconstructed signal based on the calculated principal components and the empirical orthogonal functions EOF corresponding to each principal component.

8. The toll station truck collision warning control system according to claim 1, characterized in that: The toll station truck collision warning control system also includes a protection module, which includes an anti-collision steel plate. The bottom end of the anti-collision steel plate is fixedly mounted on the ground, and the side of the anti-collision steel plate is in contact with the side of the card issuing machine / payment machine. The anti-collision steel plate is used to protect the card issuing machine / payment machine to prevent the card issuing machine / payment machine from being scratched.

9. A toll station truck collision warning control system according to claim 1, characterized in that: The toll station truck collision warning control system also includes an alarm module, which includes an audible and visual alarm. The audible and visual alarm is installed on the top of the barrier machine and is used to generate audible and visual alarms to alert the driver.

10. The toll station truck collision warning control system according to claim 1, characterized in that: The toll station truck collision warning control system detects the truck compartment in the following steps: S1. Collect video data of the safety line position and detect the truck compartment; S2. Detecting the position of the carriage in real time according to the video data, generating real-time data of the position of the carriage; S3 analyzes the real-time data of the position of the carriage, and determines whether the position of the carriage exceeds the safety line based on the real-time data of the position of the carriage, if not, enters S4, if so, enters S5; S4. The barrier machine opens the barrier, lifts the pull rod to release, and ends the warning work; S5. Give a voice prompt and display a warning screen to remind the driver to keep the barrier closed and adjust the position of the car. Repeat S1-S3 until the position of the car does not exceed the safety line.

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