Tunnel light control system and control method based on active query mode of lighting lamp

Abstract

The application provides a tunnel light control system and control method based on an active query mode of a lighting lamp, an image processing module divides images in a field of view of a camera into not less than one grid along a tunnel direction, and determines whether there is a vehicle image in each grid in real time, obtains vehicle presence / absence query information with a grid address id number, stores the information, and sends the information by a first transceiving module; a data processing module of a lamp control unit continuously sends a vehicle-absence query instruction to a camera unit corresponding to adjacent related grids, and once there is no vehicle in all the related grids, a light control module is driven to turn off a local lighting lamp, otherwise, the lighting lamp is turned on. The application inquires in real time whether there is a vehicle in a field of view of a related camera by a lamp control unit, and then controls a local lighting lamp to be turned on or off, saves time delay caused by an intermediate link, meets lighting requirements of a high-speed vehicle, and has the characteristics of simple and reliable algorithm and low error rate.

Description

Technical Field

[0001] This invention belongs to the field of tunnel engineering technology and relates to a tunnel lighting control system and control method based on active querying of lighting lamps. Background Technology

[0002] In recent years, with increased national investment in infrastructure, the transportation industry has continued its rapid development. As of the end of 2021, there were 23,268 highway tunnels nationwide, with a total length of 24.6989 million meters. Among them, there were 1,599 extra-long tunnels with a total length of 7.1708 million meters, and 6,211 long tunnels with a total length of 10.8443 million meters. After tunnels are completed and put into operation, lighting electricity accounts for more than 70% of their operating costs. Currently, there is significant electricity waste in lighting. First, most tunnels use fixed-brightness all-weather lighting, meaning the lights remain on even when there are no vehicles passing through, resulting in substantial waste. Second, in actual tunnel engineering design, to ensure traffic safety, the design of tunnel lighting fixtures is generally based on the maximum external brightness and highest driving speed throughout the year. While traffic safety is considered, this greatly increases energy waste.

[0003] Chinese patent application number 201510192996.5, entitled "Method and Apparatus for Controlling Tunnel Lighting Conditions Using Infrared Camera Image Analysis," discloses a method and apparatus for controlling tunnel lighting conditions using infrared camera image analysis. It utilizes infrared cameras to obtain video information, processes the acquired video information to extract image feature information, and finally encodes this feature information as control parameters for adjusting the brightness of LED tunnel lights, achieving "lights on when a vehicle approaches, lights off when a vehicle passes," effectively saving energy while ensuring traffic safety within the tunnel. However, this method has drawbacks in application. It requires determining the number of vehicles approaching the detection point and their fastest speed, and encoding the three feature information points (node ​​number, number of vehicles, and speed) as control parameters for adjusting the brightness of the LED tunnel lights. Therefore, it suffers from complex algorithms, poor real-time performance, susceptibility to errors, and low reliability. Summary of the Invention

[0004] This invention proposes a tunnel lighting control system and method based on active querying of lighting lamps. Under the premise of meeting the requirements of current tunnel lighting specifications, the lighting control unit actively queries whether there are vehicles in the field of view of the associated camera, and directly controls the opening and closing of the lighting lamps within a certain distance in front of and behind the vehicle, realizing tunnel dimming of "lights on when a vehicle comes and lights off when a vehicle leaves".

[0005] The specific technical solution of the present invention is as follows:

[0006] A tunnel lighting control system based on an active query method for lighting lamps, wherein several lighting lamps are spaced apart in the tunnel, characterized in that: the control system includes a lighting control unit mounted on the lighting lamp and multiple camera units cascaded in the tunnel; the field of view of adjacent camera units seamlessly covers the entire tunnel surface;

[0007] Each camera unit includes a camera, an image processing module, and a first transceiver module. The image processing module divides the image within the camera's field of view into at least one grid along the tunnel direction, determines in real time whether there is a vehicle image in each grid, obtains the query information of whether there is a vehicle with the grid address ID number, stores it, and then sends it by the first transceiver module.

[0008] The lighting control unit includes a second transceiver module, a data processing module, and a lighting control module. The second transceiver module and the first transceiver module exchange and transmit data. The data processing module continuously sends a query command indicating no vehicles to the camera units corresponding to the adjacent associated grids. Once there are no vehicles in all associated grids, the lighting control module is driven to turn off the local lights; otherwise, the lights are turned on.

[0009] In the tunnel lighting control system based on the above-mentioned active query method of lighting lamps, the neighboring associated grid refers to the grid corresponding to 200m before and 100m after the grid where the local lighting lamp is located.

[0010] In the tunnel lighting control system based on the above-mentioned active query method of lighting lamps, the data processing module sends a query command for no vehicles every 0.5 to 2 seconds.

[0011] In the tunnel lighting control system based on the above-mentioned active query method of lighting lamps, the data processing module outputs a low level or a high level to the control port of the lighting lamp, so that the lighting lamp is turned off or on.

[0012] In the aforementioned tunnel lighting control system based on active query of lighting, the field of view of the camera unit is 200m, which is divided into two grids; the first camera unit is installed at a position where its field of view covers the section of road 200 meters before the tunnel entrance, and the last camera unit is installed at a position where its field of view covers the section of road 200 meters before the tunnel exit.

[0013] In the tunnel lighting control system based on the above-mentioned active query method of lighting lamps, each lighting lamp is equipped with a lighting control unit or lighting groups 100 meters apart share a lighting control unit.

[0014] In the tunnel lighting control system based on the above-mentioned active query method of lighting lamps, the first transceiver module and the second transceiver module use a LoRa IoT wireless communication module for data transmission.

[0015] In the aforementioned tunnel lighting control system based on the active query method of lighting lamps, the control system also includes a cloud server, which interacts and transmits data with the first transceiver module and the second transceiver module; the first transceiver module and the second transceiver module transmit wireless data with the cloud server 8 via a 4G or 5G network.

[0016] The tunnel lighting control method based on active querying of lighting lamps includes the following steps:

[0017] [1] The image processing module of each camera unit processes the images in the field of view in real time, determines whether there are vehicle images in all grids in the field of view, and combines the judgment results and grid address ID data into new information to be searched for whether there are vehicles and then stores it.

[0018] [2] The data processing module of the lighting control unit repeatedly sends the query command for no vehicles to the camera unit corresponding to the adjacent associated grid, obtains the query information in each associated grid, and makes a judgment; if there are no vehicles in all associated grids, the data processing module outputs a low level to the control port of the lighting lamp to turn off the lighting lamp; otherwise, as long as there is a vehicle in any grid, the data processing module outputs a high level to the control port of the lighting lamp to turn on the lighting lamp.

[0019] In the above-mentioned highway tunnel lighting control method based on active query of lighting, the step for the camera unit to determine whether there is a vehicle within the grid is as follows:

[0020] 【1】Hotspot area segmentation

[0021] The image processing module sets hotspot areas at the locations where vehicles appear within each grid and processes image data only within these hotspot areas;

[0022] [2] Bilateral filtering and background subtraction

[0023] After performing bilateral filtering on the image within the hotspot area at regular intervals, frame difference operation is performed between the image and the background image. Based on the preset variance threshold, a binary image is obtained. In the image, a value of 1 represents a part that is different from the background, and a value of 0 represents a part that is the same as the background.

[0024] [3] Corrosion expansion and contour detection

[0025] Following the erosion and dilation operations in conventional image processing, the number of pixels in the image region with a value of 0 after differential processing is filtered out, the image outline is drawn, and the sum of the number of pixels with an amplitude of 1 in the outline is counted. If the calculated value is greater than the preset number of pixels in the hot spot region and the threshold, it is determined that a vehicle has entered the hot spot region; otherwise, it is determined that no vehicle has entered the hot spot region.

[0026] The beneficial technical effects of this invention are as follows:

[0027] I. Based on the requirements of current tunnel lighting specifications, this invention proposes a method to control the lighting in the tunnel by keeping the area before and after a vehicle's location constantly lit while turning off the lights in the remaining areas to save energy. Multiple camera units are deployed within the tunnel, their fields of view seamlessly covering the entire tunnel surface. The lighting control unit queries the fields of view of the associated cameras in real time to check for vehicles, thereby controlling the local lighting to turn on or off. This eliminates the complex algorithms required by traditional tunnel energy-saving control, which need to calculate the number and speed of vehicles, thus saving time delays caused by intermediate steps. It meets the lighting requirements of high-speed vehicles and features a simple, reliable algorithm with a low error rate, achieving tunnel dimming with lights on when a vehicle approaches and off when a vehicle leaves. It is simple, reliable, and has good real-time performance.

[0028] Second, this invention divides the tunnel along its length into several grids according to the field of view of cascaded cameras. Each grid contains several lights, establishing a correspondence between the grid where the vehicle is located and the grids where the lights need to be switched on or off. The lighting control unit queries the cameras in real time to obtain information on whether there are vehicles in the associated grids, acquiring valid information including the grid ID number. Based on the principle of "lighting priority," it directly sends control commands to the lights in the grids that need to be controlled, eliminating the time delay caused by intermediate links, meeting the lighting requirements of high-speed vehicles, and featuring a simple and reliable algorithm with an extremely low error rate. At the same time, by using this method of dividing the lighting area according to grid segments, the streetlights in each grid can share a single lighting control unit, which saves on hardware costs for control, reduces the number of control commands sent and received and the probability of errors, simplifies data processing and computation, and improves system reliability.

[0029] Third, the camera unit of the present invention faces the road surface in the direction of oncoming vehicles. The field of view of the first camera covers the road section 200m in front of the tunnel, thereby controlling the lighting at the tunnel entrance. This replaces the traditional tunnel lighting control system that requires the installation of radar or on / off switches at the entrance to determine whether a vehicle is entering the tunnel. At the same time, it also eliminates the need to install cameras in a certain area at the exit of the tunnel, reducing hardware costs.

[0030] Fourth, the present invention uses a hotspot capture method to determine whether there is a vehicle in the grid. Hotspot areas where vehicles appear are marked in the aforementioned field of view grid. By statistically analyzing the proportion of gray values ​​in the dynamic image within the hotspot area that are greater than a set gray value threshold and the proportional coefficient, the dynamic changes that determine whether there is a vehicle can be obtained. This overcomes the recognition error caused by the reflection of vehicle lights from the walls around the tunnel and improves the accuracy. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the control circuit principle of an existing tunnel LED lighting group;

[0032] Figure 2This is a schematic diagram illustrating the composition principle of the control system for the automatic switching of tunnel lighting in this invention.

[0033] Figure 3 This is a schematic diagram illustrating the tunnel grid division and camera coverage principle of the present invention;

[0034] Figure 4 This is a schematic diagram illustrating the composition principle of the camera unit of the present invention;

[0035] Figure 5 This is a schematic diagram illustrating the composition principle of the lighting control unit of the present invention;

[0036] Figure 6 This is a schematic diagram of the lighting switch status of a single vehicle in scenario one according to the present invention;

[0037] Figure 7 This is a schematic diagram of the lighting switch status when a single vehicle is driving in scenario two according to the present invention;

[0038] Figure 8 This is a schematic diagram showing the lighting switch status of multiple vehicles in scenario three according to the present invention;

[0039] Figure 9 This is a schematic diagram illustrating the steps of the image processing module of the present invention to determine whether there is a vehicle within the grid.

[0040] Figure 10 This is a schematic diagram illustrating the steps in a specific embodiment of the present invention;

[0041] Reference numerals: 1-Tunnel; 2-Camera unit; 3-Lighting light; 4-Entrance; 5-Exit; 6-Vehicle; 7-Camera field of view; 8-Cloud server; 10-Grid; 11-Tunnel surface; 12-Off state; 13-On state; 21-Image sensor; 22-Supplemental light; 23-Infrared filter; 24-Image processing module; 25-Lens; 26-First transceiver module; 31-Power supply module; 32-LED light group; 33-Power supply port; 34-Control port; 35-Second transceiver module; 36-Data processing module; 37-Lighting control module; 61-Front vehicle; 62-Rear vehicle. Detailed Implementation

[0042] like Figure 1 and Figure 2 As shown, several lighting lamps 3 are installed at intervals inside tunnel 1. The lighting lamps 3 can be installed at the top or sides of tunnel 1. Typically, a group of lighting lamps is installed at equal intervals of 10-20m.

[0043] Current control circuits for tunnel lighting, such as Figure 1As shown in the figure, each LED lighting group 32 is powered by a commercially available standard power supply module 31. This module converts the AC input at the power supply port 33 into DC power and has a built-in overshoot protection circuit. The power supply module 31 is also equipped with a control port 34 for dimming control. A voltage of 0-12V is applied to the control port 34 to control the lighting brightness of the LEDs from dark to bright in stages.

[0044] To achieve the intelligent lighting effect of "lights on when a vehicle approaches, lights off when a vehicle leaves," this invention develops a control system for automatic switching of tunnel lighting. Traditional tunnel lighting control methods require identifying vehicle images and calculating vehicle speed and number to control the switching on and off of lights in the vehicle's driving area. This method suffers from drawbacks such as complex algorithms, poor real-time performance, susceptibility to errors, and low reliability. Based on in-depth research into tunnel specifications and multiple simulation tests of vehicles driving in tunnels, the inventors selected a system where lights remain on 200m in front of and 100m behind the vehicle (these distances can be adjusted according to different tunnels and lighting conditions). This avoids affecting the driver's vision, making them unaware of the energy-saving lighting control effect and believing they are driving in a well-lit tunnel. The specific idea is to abandon the traditional method that requires calculating vehicle speed and number, and instead adopt a simple and quick solution. Under conditions of maximum redundancy and ensuring sufficient lighting, the system controls the lights 200m in front of and 100m behind the vehicle to remain on based on the vehicle's position captured by a camera, thus making the driver unaware of the change in the tunnel lighting switch.

[0045] like Figure 2 and Figure 3 As shown, the control system for automatic switching of tunnel lighting of the present invention includes a cloud server 8, a lighting control unit set on each lighting lamp 3, and multiple camera units 2 cascaded in the tunnel 1. The camera units 2 face the road surface in the direction of oncoming vehicles and their field of view covers a 200-meter section of the road. The field of view of adjacent camera units 2 seamlessly covers the entire tunnel road surface.

[0046] like Figure 4As shown, the camera unit 2 includes a camera and a first transceiver module 26 for camera data transmission. Each camera includes a lens 25, an image sensor 21, and an internal image processing module 24. The camera is mounted on the arch of the tunnel, with the lens 25 facing the road surface area. Infrared supplementary lights 22 are installed around the camera lens, emitting invisible light with wavelengths of 850nm or 940nm, which will not affect the driver's driving. At the same time, an infrared filter 23 matching the wavelength of the infrared supplementary lights is installed in front of the lens, allowing only light of the matching wavelength to pass through for imaging, thereby filtering out background light and reducing interference from vehicle headlights, ensuring the reliability and stability of image acquisition. The image sensor 21 uses a 25fps, 8-megapixel CMOS camera, and the image processing module 24 uses a 64-bit ARM processor, which integrates a wireless LoRa IoT wireless communication module and a 4G / 5G module, serving as the first transceiver module 26.

[0047] The image processing module 24 divides the image of the tunnel surface 11 within the field of view 7 of the image sensor 21 into several grids 10 along the tunnel direction. Each grid corresponds to at least one lighting lamp 3, and each lighting lamp is equipped with a controller. Alternatively, all the lighting lamps in each grid can be grouped together and equipped with a controller. This can save on the hardware cost of control and reduce the number of control commands sent and received, thereby improving reliability.

[0048] like Figure 5 As shown, the lighting control unit includes a second transceiver module 35 and a lighting control module 37. The lighting control module includes an internal data processing module 36. The second transceiver module 35 adopts a LoRa IoT wireless communication module, etc. The data processing module 36 is composed of STM32xx microcontroller as the core device. The lighting control module 37 also includes an OP07 amplifier and peripheral circuits, which amplify the high and low levels output by the microcontroller to drive the LED lights.

[0049] The second transceiver module 26 of the lighting control unit exchanges data with the first transceiver module 26 of the adjacent camera unit 2. The cloud server 8 exchanges data with the first transceiver module 26 and the second transceiver module 35. The cloud server 8 is mainly used to back up the data between the first transceiver module 26 and the second transceiver module 35; both of them exchange data wirelessly with the cloud server 8 via a 4G / 5G network.

[0050] During implementation, the image processing module 24 of camera unit 2 determines in real time whether there is a vehicle image in each grid, obtains the query information of whether there is a vehicle with the grid address ID number, and stores it. According to the subsequent query process, it is sent by the first transceiver module 26. The real-time refresh frequency is usually 2-10Hz, that is, it can be refreshed once every 0.1s to 0.5s to obtain the vehicle information of each grid. The format of this information is grid ID + yes or no, where yes means there is a vehicle and no means there is no vehicle.

[0051] The data processing module 36 of the lighting control unit continuously and repeatedly sends a query command indicating no vehicles to the camera unit 2 corresponding to the adjacent associated grid. Once there are no vehicles in all associated grids, the lighting control module 37 is driven to turn off the local lighting 3; otherwise, the lighting 3 is turned on. Typically, a query command indicating no vehicles is sent every 0.5 to 2 seconds, continuously and without interruption. The data processing module 36 of the lighting control unit repeatedly sends the query command indicating no vehicles to the camera unit 2 corresponding to the adjacent associated grid, obtains the query information for each associated grid, and makes a judgment. If there are no vehicles in all associated grids, the data processing module 36 outputs a low level to the control port 34 of the lighting 3, causing the lighting to turn off; otherwise, if there is a vehicle in even one grid, the data processing module 36 outputs a high level to the control port 34 of the lighting 3, causing the lighting to turn on. The information is transmitted wirelessly between the second transceiver module 35 and the first transceiver module 26. The adjacent associated grid refers to the grids 200m before and 100m after the grid where the local lighting 3 is located. If there is a vehicle in one of the associated grids, the light controller turns on the lights in that grid; if there are no vehicles in any of the associated grids, the lights turn off. Figure 5 The output of the lighting control module 37 is directly connected to the control port 34 of the LED light group 32. By inputting a 0V or 12V voltage, the LED light group 32 can be turned on or off. The method for determining whether there is a vehicle within the camera's field of view grid in the tunnel is a conventional image processing method. It determines the presence of a vehicle within a specific area of ​​the field of view by comparing the image within the field of view with the background image.

[0052] like Figure 3 and Figure 6 As shown, m cascaded camera units divide the road surface image of the entire tunnel into m*n grids 10, with each grid 10 corresponding to at least one lighting lamp 3; the camera unit in each grid sends a light-on / off command to the lighting control unit of the lighting lamp 3 in the corresponding grid 100 meters behind and 200 meters before that grid, where the front and back direction is the same as the vehicle's driving direction.

[0053] Figure 6In this scenario, assuming each camera has a field of view of 200m along the tunnel's longitudinal direction, the camera area is divided into four grids, each representing 50m. In scenario one of the diagram, the lights in the grid containing vehicle 6, as well as the lights in the four grids before and the one grid after it, are on (13), while the remaining lights are off (12). If the distance between the light poles is 10-20 meters, then multiple sets of light poles within each grid will simultaneously turn on and off. It can be seen that when the vehicle travels to... Figure 7 In scenario two, the lights in the grid where vehicle 6 is located, as well as the lights in the four grids before it and the one grid after it, remain on (13), while the lights in the remaining grids remain off (12).

[0054] because Figure 6 and Figure 7 When only one vehicle is traveling in the tunnel, as long as the vehicle's lights are kept on within the grid 200m in front of the vehicle and 100m behind the vehicle, it will not affect the driver's vision, making the driver unaware of the energy-saving lighting effect and believing that they are driving in a well-lit tunnel.

[0055] exist Figure 8 In scenario three, when multiple vehicles are present, the distance between the front vehicle 61 and the rear vehicle 62 is less than 200m. At this time, the grid behind the front vehicle 61 that needs to turn off its lights is exactly at the intersection of the grid in front of the rear vehicle 62 that needs to turn on its lights. In this case, the solution adopted by the present invention is the principle of "lighting priority". The condition for turning off the lights in any grid is that no vehicles are detected in the area within 200m in front and 100m behind the corresponding grid. Otherwise, the lights are turned on.

[0056] like Figure 9 As shown, in order to accurately determine whether there are vehicles within the camera's field of view grid inside the tunnel, this invention proposes a scheme based on hotspot area image processing. The specific steps are as follows:

[0057] 【1】Hotspot area segmentation

[0058] The image processing module 24 divides the image within the field of view of the image sensor 21 into several grids along the tunnel direction. Within each grid, a hotspot region is set according to the location of the vehicle. Subsequent processing only involves image data within the hotspot region. This saves processing time and filters out tunnel edge images that are easily affected by lighting and where vehicles do not appear, thus improving accuracy. The hotspot region can be rectangular or other shapes.

[0059] [2] Bilateral filtering and background subtraction

[0060] The image within the hotspot area is subjected to bilateral filtering every 100ms, followed by frame differencing with the background image. A binary image is then obtained based on a preset variance threshold. In this image, a value of 1 represents a region different from the background, while a value of 0 represents a region identical to the background. Considering that the background image is constantly changing due to environmental influences, it is continuously updated, typically at a rate of 500 frames per second.

[0061] [3] Corrosion expansion and contour detection

[0062] Following the erosion and dilation operations in conventional image processing, the number of pixels in the image region with a value of 0 after differential processing is filtered out, the image outline is drawn, and the sum of the number of pixels with an amplitude of 1 in the outline is counted. If the calculated value is greater than the preset number of pixels in the hot spot region and the threshold, it is determined that a vehicle has entered the hot spot region; otherwise, it is determined that no vehicle has entered the hot spot region.

[0063] [4] Is there vehicle information available?

[0064] The image processing module 24 obtains and stores the information to be queried, which includes the grid address ID number, based on the change in the presence or absence of vehicles in each grid within the field of view. Then, according to the subsequent request query process, the first transceiver module 26 sends the information to the second transceiver module 26 of the lighting control unit that initiated the query.

[0065] This invention employs a hotspot capture method to determine whether a vehicle is present within a grid. Hotspot areas where vehicles appear are delineated within the aforementioned field of view grid. By statistically analyzing the percentage change and proportional coefficient of grayscale values ​​exceeding a set grayscale threshold in dynamic images within these hotspot areas, the dynamic changes indicating the presence or absence of vehicles are obtained. This overcomes the recognition errors caused by reflections from vehicle lights on the surrounding walls of tunnels and improves accuracy.

[0066] The following is an example:

[0067] like Figure 10 As shown, a tunnel is 600m long. Four camera units are installed between entrance 4 and exit 5: camera unit #1, camera unit #2, camera unit #3, and camera unit #4. The lighting fixtures are spaced 20m apart, arranged in groups of 100m each. Each group of lighting fixtures shares a single controller; that is, LED controllers are installed in sections C, D, E, F, G, and H of the tunnel. The camera's field of view is 200m, divided into two equal grids along the tunnel's length, each grid being 100m long. Five groups of lighting fixtures are located within each grid. Grids numbered A, B, C, D, E, F, G, H, J, and I are marked from the outside of entrance 4 to the outside of exit 5. All camera units are installed facing the tunnel entrance. Camera unit #1 is positioned over a 200m area outside entrance 4, while there is no corresponding camera unit in the final 200m area outside exit 5.

[0068] 1. The C-section lighting control module queries in real time whether there are vehicles in the A and B sections of camera unit #1 and the D section of camera unit #2. If there are vehicles in any of the areas, the lights in the C-section controller will be turned on. If there are no vehicles in any of the areas, the lights will be turned off.

[0069] 2. The D-section lighting control module queries in real time whether there are vehicles in the B-section area of ​​camera unit #1, the C-section area of ​​camera unit #2, and the E-section area of ​​camera unit #3. If there are vehicles in any of the areas, the lights in the D-section controller will be turned on. If there are no vehicles in any of the areas, the lights will be turned off.

[0070] 4. The E-segment lighting control module queries the C and D sections of camera unit #2 and the F section of camera unit #3 in real time to check if there are any vehicles. If there are vehicles in any of the areas, the lights in the E-segment controller will be turned on. If there are no vehicles in any of the areas, the lights will be turned off.

[0071] 5. The F-segment lighting control module queries in real time whether there are vehicles in the D-segment area of ​​camera unit #2, the E-segment area of ​​camera unit #3, and the G-segment area of ​​camera unit #4. If there are vehicles in any of the areas, the lights in the F-segment controller will be turned on. If there are no vehicles in any of the areas, the lights will be turned off.

[0072] 6. The G-segment lighting control module queries the E and F segments of camera unit #3 and the H segment of camera unit #4 in real time to check if there are any vehicles. If there are vehicles in any of the segments, the lights in the G-segment controller will be turned on. If there are no vehicles in any of the segments, the lights will be turned off.

[0073] 7. The H-segment lighting control module queries the F-segment area of ​​camera unit #3 and the G-segment area of ​​camera unit #4 in real time to check if there are any vehicles. If there are vehicles in either area, the lights in the H-segment controller will turn on. If there are no vehicles in any area, the lights will turn off.

[0074] This principle can be extended to calculations for scenarios involving multiple vehicles simultaneously within a tunnel. Furthermore, this method only requires dividing the entire tunnel into several grids, establishing a connection between the grid containing the vehicle and the grid requiring traffic light control, based on the convention of 200m in front of the vehicle and 100m behind it. It avoids complex calculations of vehicle numbers and speeds, thus featuring a simple and reliable process with very low error and reporting rates. In terms of signal processing, the camera unit has a built-in microcontroller-controlled image processing module, capable of determining the presence of vehicles within each grid area. It then wirelessly transmits the information to the nearest associated traffic light control unit requesting the query. Moreover, each traffic light control unit uses a cost-effective microcontroller, further reducing implementation costs.

[0075] The intelligent control technology of this invention achieves the intelligent tunnel lighting control effect of "lights on when a car approaches, lights off when a car leaves" under low traffic flow conditions. Under the condition of ensuring safe tunnel operation, the energy saving ratio is calculated to be 20-30% based on existing driving records.

Claims

1. A tunnel lighting control system based on an active query method for lighting lamps, wherein a plurality of lighting lamps (3) are spaced apart within the tunnel (1), characterized in that: The control system includes a lighting control unit installed on the lighting lamp (3) and multiple camera units (2) cascaded in the tunnel; the field of view of adjacent camera units (2) seamlessly covers the entire tunnel surface; Each camera unit (2) includes a camera, an image processing module (24) and a first transceiver module (26). The image processing module (24) divides the image in the field of view of the camera into at least one grid along the tunnel direction, determines in real time whether there is a vehicle image in each grid, obtains the query information of whether there is a vehicle with grid address ID number, stores it, and sends it by the first transceiver module (26). The lighting control unit includes a second transceiver module (35), a data processing module (36), and a lighting control module (37). The second transceiver module (35) and the first transceiver module (26) perform data interaction and transmission. The data processing module (36) continuously sends a query command indicating no vehicles to the camera unit (2) corresponding to the adjacent associated grid. Once there are no vehicles in all associated grids, the lighting control module (37) is driven to turn off the local lighting (3). Otherwise, the lighting (3) is turned on. The neighboring associated grid refers to the grids 200m before and 100m after the grid where the local lighting fixture is located; The field of view of the camera unit (2) is 200m and is divided into two grids; the first camera unit (2) is installed in a section of road 200 meters before the tunnel entrance, and the last camera unit (2) is installed in a section of road 200 meters before the tunnel exit. The first transceiver module (26) and the second transceiver module (35) use a Lora IoT wireless communication module to transmit data.

2. The tunnel lighting control system based on the active query method of lighting lamps according to claim 1, characterized in that: The data processing module (36) sends a query command for vehicles every 0.5 to 2 seconds.

3. The tunnel lighting control system based on the active query method of lighting lamps according to claim 1, characterized in that: The data processing module (36) outputs a low or high level to the control port (34) of the lighting lamp (3), causing the lighting lamp to turn off or on.

4. The tunnel lighting control system based on the active query method of lighting lamps according to claim 1, characterized in that: Each lighting fixture has its own lighting control unit, or lighting groups that are 100 meters apart can share a single lighting control unit.

5. The tunnel lighting control system based on the active query method of lighting lamps according to claim 1, characterized in that: The control system also includes a cloud server (8), which interacts and transmits data with the first transceiver module (26) and the second transceiver module (35); the first transceiver module (26) and the second transceiver module (35) transmit wireless data with the cloud server 8 through a 4G or 5G network.

6. A method for controlling tunnel lighting using the tunnel lighting control system based on the active query method of lighting lamps as described in any one of claims 1 to 5, characterized in that, Includes the following steps: [1] The image processing module (24) of each camera unit (2) processes the images in the field of view in real time, determines whether there are vehicle images in all grids in the field of view, and combines the judgment result and grid address id data into new information to be searched for whether there are vehicles and stores it. [2] The data processing module (36) of the lighting control unit repeatedly sends the query command for no vehicle to the camera unit (2) corresponding to the adjacent associated grid, obtains the query information in each associated grid, and makes a judgment; if there is no vehicle in all associated grids, the data processing module (36) outputs a low level to the control port (34) of the lighting lamp (3) to turn off the lighting lamp; otherwise, as long as there is a vehicle in one grid, the data processing module (36) outputs a high level to the control port (34) of the lighting lamp (3) to turn on the lighting lamp.

7. The tunnel lighting control method based on active querying of lighting lamps according to claim 6, characterized in that, The steps for camera unit (2) to determine whether there are vehicles within the grid are as follows: 【1】Hotspot area segmentation: The image processing module (24) sets hotspot areas at the locations where vehicles appear in each grid and processes only the image data within the hotspot areas; [2] Bilateral filtering and background subtraction After performing bilateral filtering on the image within the hotspot area at regular intervals, frame difference operation is performed between the image and the background image. Based on the preset variance threshold, a binary image is obtained. In the image, a value of 1 represents a part that is different from the background, and a value of 0 represents a part that is the same as the background. [3] Corrosion expansion and contour detection Following the erosion and dilation operations in conventional image processing, the number of pixels in the image region with a value of 0 after differential processing is filtered out, the image outline is drawn, and the sum of the number of pixels with an amplitude of 1 in the outline is counted. If the calculated value is greater than the preset number of pixels in the hot spot region and the threshold, it is determined that a vehicle has entered the hot spot region; otherwise, it is determined that no vehicle has entered the hot spot region.

Images