On-demand lighting sensing control method and system for highway tunnels based on the Internet of Things

Abstract

The present invention discloses a method and system for sensing and controlling on-demand lighting in highway tunnels based on the Internet of Things, which relates to intelligent control technology for highway tunnel lighting. The system includes an Internet of Things platform constructed by a sensing layer, a network layer, a management layer, and an application layer; wherein, the highway tunnel is divided into at least three tunnel sections from the entrance to the exit, namely, the entrance section, the middle section, and the exit section, each tunnel section is provided with a set of lighting control systems, and each tunnel section is divided into a plurality of monitoring sections arranged in sequence. The method comprises: the sensing layer collects data and sends it to the management sublayer via the network layer; the management sublayer determines whether there are vehicles in all monitoring sections of the corresponding tunnel section, and if there are vehicles, calculates the number of lamps turned on and the illumination of the lamps to be turned on; the management main layer generates control instructions and sends them to the lighting control system of the management sublayer to control the lamps to turn on according to the calculated illumination and time. The present invention can realize remote sensing and control, ensure the sight safety of tunnel driving, and reduce lighting costs.

Description

Technical Field

[0001] The present invention relates to intelligent control technology for highway tunnel lighting, and in particular to an on-demand lighting sensing control method and system for highway tunnels based on the Internet of Things. Background Art

[0002] With the rapid development of the highway industry, the number and mileage of highway tunnels are increasing, and the operating costs of highway tunnels are increasing. Tunnel lighting costs have always been the largest expense in tunnel operations. In order to ensure the safety of highway tunnel driving, the operating unit generally keeps the tunnel lighting fixtures on 24 hours a day from the opening of the highway (over-lighting). At the same time, for highway tunnels with small traffic volume and large seasonal influences, the traffic volume is small most of the year, and the tunnel is in a long-term no-car lighting state (ineffective lighting), resulting in a large amount of electricity being wasted, causing the highway tunnel operation to be "unaffordable". Therefore, some highway tunnel operating units have made misunderstandings on the concept of lighting energy saving, that is, using the strategy of controlling the switching of some lamps by timing loops to achieve the purpose of saving electricity costs. However, simply controlling the switching of some lamps by timing will cause uneven road brightness in the tunnel, "zebra pattern", "flickering" and substandard brightness, which brings serious safety hazards to vehicles driving in the tunnel.

[0003] The issue of balancing energy saving and safety in lighting systems has become a heavy burden, management difficulty and pain point for tunnel operation and management units. On the premise of ensuring driving safety, how to optimize the intelligent dimming mode of lighting systems with different tunnel lengths and different traffic volumes to achieve energy saving and consumption reduction, promote the transformation of existing lighting modes to intelligent and digital lighting applications, improve tunnel driving safety, and reduce highway operating costs is particularly urgent. Summary of the invention

[0004] The purpose of the present invention is to solve the problem that the existing highway tunnel lighting system cannot achieve both energy saving and safety. It provides a highway tunnel on-demand lighting sensing and control method and system based on the Internet of Things. When applied, the method and system can realize remote sensing and control of tunnel lighting control nodes at any position and designated area, and make the dimming range of the lighting fixtures in the tunnel always locked to a certain redundant lighting parking sight distance in front of the vehicle to ensure the safety of the tunnel driving line of sight, while ensuring the safe passage of vehicles, it can reduce the lighting cost.

[0005] The purpose of the present invention is mainly achieved through the following technical solutions: The on-demand lighting sensing control method for highway tunnels based on the Internet of Things is implemented based on an Internet of Things platform constructed based on a perception layer, a network layer, a management layer and an application layer; wherein, the highway tunnel is divided into at least three tunnel sections from the entrance to the exit, namely, the entrance section, the middle section and the exit section, each tunnel section is equipped with a lighting control system, and each tunnel section is divided into a plurality of monitoring sections arranged in sequence; the number of the perception layers is the same as the number of the highway tunnel sections, and each perception layer obtains the collected data of a tunnel section and sends it to the network layer, and receives the instructions sent by the management layer to control the opening and closing and illumination of the lamps in its lighting control system; the management layer includes a management main layer and management sublayers with the same number of highway tunnel sections, each management sublayer obtains the collected data of a perception layer through the network layer and sends it to the management main layer after processing, the management main layer obtains the data sent by all management sublayers at a set time interval and sends it to the application layer after processing for users to view and apply, and the management main layer also generates control instructions and sends them to the perception layer through the management sublayer and the network layer in turn to the lighting control system; The method comprises the following steps: Step S1: The perception layer obtains the vehicle presence data, ambient light perception data, and vehicle speed data, vehicle length data, and vehicle position data of all monitoring sections in the corresponding tunnel section at a set time interval, and sends them to the network layer, which is then transmitted to the management sublayer corresponding to the perception layer. Step S2: The management sublayer determines whether there are vehicles in all monitoring sections of the corresponding tunnel section according to the data it obtains. If there are vehicles, the lamp opening position and quantity are calculated according to the vehicle speed data, vehicle length data, vehicle position data and the lamp spacing of the corresponding tunnel section, and the illumination of the lamp to be turned on is calculated according to the ambient light perception data and the vehicle speed data, and then the calculated lamp opening position and quantity and lamp opening illumination data are sent to the management main layer; Step S3: After the management main layer obtains the data sent by the management sublayer at the set time interval, it calculates whether the number of lamps in the lighting control system in the perception layer corresponding to each management sublayer located in the vehicle's forward direction within the set time threshold meets the demand; if so, a control instruction is generated and sent to the lighting control system of the corresponding management sublayer to control the lamps to turn on according to the calculated illumination and time; if not, it is determined whether the lighting control system corresponding to the management sublayer is located in the tunnel exit section; if it is the exit section, a control instruction is directly generated and sent to the lighting control system corresponding to the management sublayer to control the lamps to turn on according to the calculated illumination and time; otherwise, a control instruction is generated and sent to the lighting control system corresponding to the management sublayer and the lighting control system corresponding to the management sublayer adjacent to the management sublayer in the tunnel exit direction to control the lamps to turn on according to the calculated illumination and time.

[0006] In the specific implementation of the present invention, the tunnel is divided into multiple tunnel sections. The data collected by the perception layer deployed in each tunnel section is independently controlled and processed by a management sublayer, and then uniformly coordinated and managed by the management main layer, which can improve data processing efficiency and accuracy.

[0007] Furthermore, the calculation of the number of lamps turned on in step S2 includes calculating the number of lamps that need to be activated synchronously when a single vehicle passes, and the calculation formula is: ;

[0008] in, N is the number of lamps to be activated, D is the stopping sight distance, L veh is the vehicle length, d lamp is the distance between lamps, The symbol for rounding up; Stopping sight distance D The calculation formula is: ;

[0009] in, v is the vehicle speed, t r The driver's reaction time, g is the acceleration due to gravity, f is the friction coefficient between tire and road, i is the longitudinal slope of the road, S 0 is the set safety margin.

[0010] Furthermore, the calculation formula for calculating the illumination of the lamp to be turned on according to the ambient light perception data and the vehicle speed data in step S2 is: ;

[0011] in, is the illumination of the lamp to be turned on, is the target illumination, is the measured ambient light perception data; where the target illumination The calculation method is: ;

[0012] in, E base is the basic illumination, k is the dynamic compensation coefficient, v crit is the critical speed threshold, e is the base of natural logarithms.

[0013] Furthermore, when the length of the highway tunnel is greater than a set length threshold, a transition section is provided between the entrance section and the middle section, and between the middle section and the exit section; the illumination of the lamps in the entrance section and the exit section of the highway tunnel when turned on is greater than the illumination of the lamps in the middle section, the illumination of the transition section between the entrance section and the middle section decreases from the tunnel entrance to the exit, and the illumination of the transition section between the middle section and the exit section increases from the tunnel entrance to the exit; the illumination adjustment is achieved by setting a basic illumination.

[0014] Furthermore, the management main layer determines whether there are multiple vehicles that need to turn on the same lamp at the same time based on the data it obtains. If there are lamps to be turned on, the illumination is: ;

[0015] in, is the final output illuminance when the lamp is turned on. Calculate the illumination of the lamps that need to be turned on for each vehicle independently. α is the attenuation factor.

[0016] Furthermore, the sensing layer in the first monitoring section from the entrance to the exit direction of the highway tunnel entrance section monitors whether there is a vehicle, and the device for monitoring the vehicle speed data, vehicle length data, and vehicle position data when a vehicle exists is arranged at a set distance from the highway tunnel entrance.

[0017] Furthermore, in step S3, when the lighting control system controls the lamps to turn on according to the calculated illumination and time, the calculated number of lamps that need to be turned on simultaneously are turned on synchronously, and the turn-on time intervals of the remaining lamps that need to be turned on are calculated based on the lamp spacing divided by the vehicle speed.

[0018] Furthermore, the control instructions generated by the management main layer are also used to control the on-time of the lamps in the lighting control system. When a single vehicle passes, the on-time t on The calculation formula is: ;

[0019] in, L lamp is the effective lighting length of the lamp, S buffer is the set buffer distance, v is the vehicle speed, t safe is the set safety redundancy time, t delay The system response delay is set; When multiple vehicles are following each other, the lights will remain on based on the nearest vehicle behind until the last vehicle passes the calculated stay-on time.

[0020] Furthermore, the vehicle presence data detection in the perception layer is realized by a geomagnetic sensor, the ambient light perception data detection is realized by a light sensor, and the vehicle speed data, vehicle length data and vehicle position data detection is realized by a millimeter wave radar sensor.

[0021] The system for realizing the above-mentioned on-demand lighting sensing control method for highway tunnels based on the Internet of Things comprises an Internet of Things platform constructed by a sensing layer, a network layer, a management layer and an application layer; wherein, the highway tunnel is divided into at least three tunnel sections, namely, an entrance section, an intermediate section and an exit section, from the entrance to the exit, each tunnel section is provided with a set of lighting control systems, and each tunnel section is divided into a plurality of monitoring sections arranged in sequence; the number of the sensing layers is the same as the number of the highway tunnel sections, and each sensing layer obtains the collected data of a tunnel section and sends it to the network layer, and receives the instructions sent by the management layer to control the opening and closing and illumination of the lamps in its lighting control system; the management layer comprises a management main layer and management sublayers, the number of which is the same as the number of the highway tunnel sections, each management sublayer obtains the collected data of a sensing layer through the network layer and sends it to the management main layer after processing, the management main layer obtains the data sent by all the management sublayers at a set time interval and sends it to the application layer after processing for users to view and apply, and the management main layer also generates control instructions and sends them to the lighting control system of the sensing layer through the management sublayer and the network layer in sequence; The perception layer is used to obtain the vehicle presence data, ambient light perception data, and vehicle speed data, vehicle length data, and vehicle position data of all monitoring sections in the corresponding tunnel section at set time intervals, and send them to the network layer, which is then transmitted to the management sublayer corresponding to the perception layer by the network layer; The management sublayer is used to determine whether there are vehicles in all monitoring sections of the corresponding tunnel section based on the data it obtains. If there are vehicles, the lamp opening position and number are calculated based on the vehicle speed data, vehicle length data, vehicle position data and the lamp spacing of the corresponding tunnel section, and the illumination of the lamps to be turned on is calculated based on the ambient light perception data and vehicle speed data, and then the calculated lamp opening position and number and lamp opening illumination data are sent to the management main layer; The management main layer is used to obtain the data sent by the management sublayer at the set time interval, and then calculate whether the number of lamps in the lighting control system of the perception layer corresponding to each management sublayer located in the vehicle's forward direction within the set time threshold meets the demand. If so, a control instruction is generated and sent to the lighting control system of the corresponding management sublayer to control the lamps to turn on according to the calculated illumination and time. If not, it is determined whether the lighting control system corresponding to the management sublayer is located in the tunnel exit section. If it is the exit section, a control instruction is directly generated and sent to the lighting control system corresponding to the management sublayer to control the lamps to turn on according to the calculated illumination and time. Otherwise, a control instruction is generated and sent to the lighting control system corresponding to the management sublayer and the lighting control system corresponding to the management sublayer adjacent to the management sublayer in the tunnel exit direction to control the lamps to turn on according to the calculated illumination and time.

[0022] In summary, compared with the prior art, the present invention has the following advantages: (1) The present invention can realize remote sensing and control of tunnel lighting control nodes in a specified area, so that the dimming range of the lighting fixtures in the tunnel is always locked to a certain redundant lighting parking sight distance in front of the vehicle, so as to ensure the safety of tunnel driving vision.

[0023] (2) The present invention can effectively reduce the "white hole" and "black hole" effects, reduce the accident rate, and enhance the driving comfort in the tunnel.

[0024] (3) The present invention can achieve an accompanying on-demand lighting effect of "lights on when a car approaches, lights off when a car leaves, and lights follow the car" based on real-time traffic information.

[0025] (4) The present invention applies the Internet of Things vehicle-based dimming technology to dynamically dim the lighting facilities in the tunnel to achieve a lighting effect of "lights on when a vehicle comes, lights off when a vehicle leaves, and lights follow the vehicle", thereby realizing on-demand lighting in highway tunnels. With a small vehicle flow, it can achieve energy savings of about 50%, and with a large vehicle flow, it can achieve energy savings of more than 30%. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings: Figure 1 A schematic diagram of the system structure of a specific embodiment of the present invention; Figure 2 The figure is a flow chart of a lighting sensing control method according to a specific embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0028] Example: like Figure 1As shown, the on-demand lighting sensing control system for highway tunnels based on the Internet of Things includes an Internet of Things platform constructed by a sensing layer, a network layer, a management layer and an application layer; wherein, the highway tunnel is divided into at least three tunnel sections from the entrance to the exit, namely, the entrance section, the middle section and the exit section, each tunnel section is equipped with a lighting control system, and each tunnel section is divided into a plurality of monitoring sections arranged in sequence. In this embodiment, the number of sensing layers is the same as the number of sections of the highway tunnel, and each sensing layer obtains the collected data of a tunnel section and sends it to the network layer. The sensing layer is also used to receive instructions sent by the management layer to control the opening and closing and illumination of the lamps in its lighting control system. The management layer of this embodiment includes a management main layer and management sublayers with the same number of sections as the highway tunnel sections. Each management sublayer obtains the collected data of a sensing layer through the network layer and sends it to the management main layer after processing. The management main layer obtains the data sent by all management sublayers at a set time interval and sends it to the application layer after processing for users to view and apply. The management main layer also generates control instructions and sends them to the lighting control system of the sensing layer through the management sublayer and the network layer in sequence.

[0029] The perception layer in this embodiment serves as a data acquisition and control port. Vehicle presence data detection in the perception layer is achieved through geomagnetic sensors, ambient light perception data detection is achieved through light sensors, vehicle speed data, vehicle length data and vehicle position data detection are achieved through millimeter wave radar sensors. The lighting control system used in this embodiment is a part of the perception layer, which is implemented based on existing technologies and will not be repeated here.

[0030] The network layer of this embodiment is a data transmission device, the number of network layers is the same as the number of highway tunnel segments, and each network layer corresponds to a perception layer and a management sublayer to provide data interaction, so as to improve the data transmission efficiency between the perception layer and the management sublayer.

[0031] The improvement of tunnel energy saving is not only reflected in the continuous optimization of tunnel construction specifications, but also in the selection of tunnel lighting fixtures. LED lamps consume less power than other traditional lighting fixtures and reduce a large amount of carbon dioxide emissions. Therefore, this embodiment uses LED lamps as lighting fixtures.

[0032] The perception layer of this embodiment uses low-bandwidth, low-power Bluetooth MESH communication networking technology to collect and control information such as the lighting distance of the vehicle headlights, the lighting speed of the lamps, and the lighting duration of the lamps in real time, to achieve adaptive linkage dynamic dimming, and form an IoT collection and control solution to ensure safe operation. Under the premise of meeting the lighting design specifications, this embodiment performs the best dynamic adjustment of the lights in each lighting section of the tunnel, realizes dynamic control of the brightness of each lighting section of the tunnel, and can avoid insufficient brightness in the tunnel caused by light decay and dust of the lamps.

[0033] In this embodiment, the management sublayer and the management main layer hardware are implemented based on existing computer systems, and the application layer hardware is implemented based on communication terminal devices such as mobile phones, tablet computers, laptops, desktop computers, etc. The application layer of this embodiment provides users with a data processing and application platform, and the parameters of each device in the perception layer can also be configured and adjusted through the input of authorized application layer users.

[0034] like Figure 2As shown, the above-mentioned on-demand lighting sensing control system for highway tunnels based on the Internet of Things in this embodiment includes the following steps when applied: Step S1, the sensing layer obtains the vehicle presence data, ambient light sensing data, and vehicle speed data, vehicle length data, and vehicle position data of all monitoring sections in the corresponding tunnel section at a set time interval, and sends them to the network layer, and the network layer transmits them to the management sublayer corresponding to the sensing layer; Step S2, the management sublayer determines whether there are vehicles in all monitoring sections of the corresponding tunnel section based on the data it has obtained, and if there are vehicles, calculates the lamp opening position and number based on the vehicle speed data, vehicle length data, vehicle position data and the lamp spacing of the corresponding tunnel section, and calculates the illumination of the lamp to be turned on based on the ambient light sensing data and the vehicle speed data, and then sends the calculated lamp opening position and number and lamp opening illumination data to the network layer. Send to the main management layer; Step S3, after the main management layer obtains the data sent by the management sublayer at the set time interval, it calculates whether the number of lamps in the lighting control system in the perception layer corresponding to each management sublayer, which is located in the vehicle's forward direction, within the set time threshold, meets the demand. If it meets the demand, it generates a control instruction and sends it to the lighting control system of the corresponding management sublayer to control the lamps to turn on according to the calculated illumination and time. If it does not meet the demand, it determines whether the lighting control system corresponding to the management sublayer is located in the exit section of the tunnel. If it is the exit section, it directly generates a control instruction and sends it to the lighting control system corresponding to the management sublayer to control the lamps to turn on according to the calculated illumination and time. Otherwise, it generates a control instruction and sends it to the lighting control system corresponding to the management sublayer and the lighting control system corresponding to the management sublayer adjacent to the management sublayer in the tunnel exit direction to control the lamps to turn on according to the calculated illumination and time. Among them, the time interval for the perception layer to collect data in step S1 of this embodiment and the time interval for the management main layer to obtain the data sent by the management sublayer in step S3 are set to the same value, both of which are the set interval time for two data collections. In step S2 of this embodiment, the lamp opening position is calculated based on the vehicle position data and the set vehicle-lamp distance threshold, that is, in this embodiment, the first lamp in the vehicle's forward direction that is within the vehicle-lamp distance threshold is used as the starting lamp to be turned on; in step S2, the number of lamps to be turned on is calculated, including the number of lamps that need to be activated synchronously when a single vehicle passes, and the total number of lamps that need to be turned on within the interval between two data collections of the perception layer. The total number of lamps that need to be turned on is obtained by multiplying the vehicle speed by the interval between two data collections and then dividing by the lamp distance and rounding up. In the specific implementation of this embodiment, when the starting lamp is turned on, multiple lamps after the starting lamp are turned on at the same time so that the number of synchronously turned-on lamps matches the calculated number of lamps turned on at the same time. In step S3 of this embodiment, when the lighting control system controls the lamps to be turned on according to the calculated illumination and time, the calculated number of lamps that need to be turned on at the same time are turned on synchronously, and the time interval for turning on the remaining lamps that need to be turned on is calculated based on the lamp distance divided by the vehicle speed.When this embodiment is applied, if it is necessary to keep six lamps in the vehicle's forward direction and adjacent to the vehicle turned on, the delay time for turning on the seventh lamp adjacent to the vehicle's current position from the vehicle's current position to the tunnel exit direction is obtained by dividing the lamp spacing by the vehicle speed. If there is a vehicle in front of the current vehicle and the seventh lamp is turned on, the seventh lamp is controlled to remain on.

[0035] In this embodiment, the sensing layer in the first monitoring section from the entrance to the exit direction of the highway tunnel entrance section monitors whether there is a vehicle, and the device for monitoring the speed data, vehicle length data, and vehicle position data when a vehicle exists is arranged at a set distance from the highway tunnel entrance, wherein the set distance is usually set to 50 to 100 meters from the tunnel entrance.

[0036] In step S2 of this embodiment, the number of lamps that need to be activated synchronously when a single vehicle passes is calculated, and the calculation formula is: ;

[0037] in, N is the number of lamps to be activated, D is the stopping sight distance, L veh is the vehicle length, d lamp is the distance between lamps (set to 10m in this embodiment), The symbol for rounding up; Stopping sight distance D The calculation formula is: ;

[0038] in, v is the vehicle speed (m / s), t r The driver's reaction time, g is the acceleration due to gravity, f is the friction coefficient between tire and road, i is the longitudinal slope of the road (obtained from the measured data of each monitoring section of the tunnel, with positive values ​​for uphill and negative values ​​for downhill), S 0 is the set safety margin (≥20m). Among them, the American Association of State Highway and Transportation Officials (AASHTO) stipulates that t r = 2.5 seconds, this value covers 90% of the driver's reaction ability (including perception, judgment, and starting braking action). The Chinese standard ("Highway Tunnel Lighting Design Specifications" JTG / T D70 / 2-01) clearly requires the use of t r=2.5 seconds, which is consistent with the ISO 2575:2018 international standard. Therefore, the driver reaction time is set to 2.5 seconds when this embodiment is applied. The friction coefficient between tire and road surface is affected by road surface material, humidity, tire condition, etc. According to the standard test method (ASTM E1911), the value of dry asphalt road surface is 0.70-0.85, and the value of wet asphalt road surface is 0.40-0.60. When this embodiment is implemented, the friction coefficient between tire and road surface can be selected within the above range according to the road surface condition.

[0039] The stopping sight distance of this embodiment is the total distance required for the vehicle to stop completely from discovering danger. This embodiment dynamically adjusts the lighting range to ensure that the front lighting of the vehicle covers the entire braking area to avoid accidents caused by lighting blind spots. This embodiment calculates the number of lamps that need to be lit to ensure that the front lighting of the vehicle covers the entire vehicle body + the stopping sight distance, dynamically follows the vehicle position, and only lights up the necessary lamps, saving energy while ensuring safety.

[0040] In step S2 of this embodiment, the calculation formula for calculating the illumination of the lamp to be turned on according to the ambient light perception data and the vehicle speed data is: ;

[0041] in, is the illumination of the lamp to be turned on, is the target illumination, is the measured ambient light perception data; where the target illumination The calculation method is: ;

[0042] in, E base is the basic illumination, k is the dynamic compensation coefficient (the value range is 0.2-0.5), v crit is the critical speed threshold (set to 80km / h, i.e. 22.22m / s in this embodiment), e is the base of the natural logarithm. This embodiment dynamically increases the lighting brightness according to the vehicle speed to compensate for the driver's visual needs when driving at high speed: Low speed ( ): Brightness is close to the base value ( E base );high speed( v ≥ vcrit ): Brightness increases to This can avoid insufficient lighting in high-speed scenes or energy waste in low-speed scenes due to fixed brightness.

[0043] In this embodiment, when the length of the highway tunnel is greater than the set length threshold, a transition section is arranged between the entrance section and the middle section, and between the middle section and the exit section; the illumination of the lamps in the entrance section and the exit section of the highway tunnel when they are turned on is greater than the illumination of the lamps in the middle section, the illumination of the transition section between the entrance section and the middle section decreases from the tunnel entrance to the exit, and the illumination of the transition section between the middle section and the exit section increases from the tunnel entrance to the exit; the illumination adjustment is achieved by setting the basic illumination.

[0044] In this embodiment, the management main layer determines whether there are multiple vehicles that need to turn on the same lamp at the same time based on the data it obtains. If there are lamps to be turned on, the illumination is: ;

[0045] in, is the final output illuminance when the lamp is turned on. Calculate the illumination of the lamps that need to be turned on for each vehicle independently. n is the number of vehicles existing at the same time, α is the attenuation factor (in this embodiment, the value is 0.8-1.0, and the default value is 0.9). In this embodiment, when multiple vehicles meet, the highest brightness requirement is selected and appropriately attenuated to resolve conflicts: the maximum value is taken to ensure the safety requirements of all vehicles; the attenuation factor is used to prevent overexposure or light pollution of the lamp (such as 0.9, which means a 10% reduction in brightness). For example, two vehicles each require 120 lx and 100 lx , the final output is 120×0.9=108 lx .

[0046] In this embodiment, the control instructions generated by the management master layer are also used to control the on-time of the lamps in the lighting control system. When a single vehicle passes, the on-time t on The calculation formula is: ;

[0047] in, L lamp is the effective lighting length of the lamp (set to 10m in this embodiment), S buffer is the set buffer distance (set to 5m in this embodiment to prevent the rear of the vehicle from being at the edge of the lighting), v is the vehicle speed, t safe is the set safety redundancy time (set to 2-3 seconds in this embodiment), t delay is the set system response delay (set to 0.2 seconds in this embodiment); When multiple vehicles are following each other, the lamp is kept on with the nearest vehicle as the reference until the last vehicle passes the calculated on-time. In this way, when this embodiment is applied, it is ensured that when the lamp is turned off, the vehicle has left the lighting area of ​​the lamp, and the following vehicles will not be affected.

[0048] This invention uses the Zhougongling Tunnel of Jiangxi Tongwan Expressway as a scenario to explore the application of the refined on-demand lighting sensing control system in highway tunnels in energy conservation and emission reduction. The purpose is to fully apply the Internet of Things technology and promote the deep integration of new technologies such as big data, the Internet, artificial intelligence, blockchain, and supercomputing with the transportation industry. The invention adopts the Internet of Things on-vehicle dimming technology to tunnels, which is of great significance for the application and promotion of on-demand lighting technology in highway tunnels and energy conservation and emission reduction.

[0049] The granularity of the on-board lighting in the tunnel can be large or small, for example, the minimum adjustable granularity is 1 lamp, and the maximum adjustable granularity is the entire tunnel. When single-lamp dimming control is performed, the energy saving ratio is undoubtedly the highest, but the cost is also the highest. When on-board dimming control is performed for the entire tunnel, on-demand lighting cannot be achieved, and the longer the tunnel, the lower the energy saving ratio. Therefore, it is necessary to weigh the granularity of the segmented control of the on-board lighting and find a cost-effectiveness balance point, that is, to use the minimum investment to generate higher energy-saving benefits. This embodiment is based on the requirements of lighting specifications and performs segmented control to independently control each tunnel section, thereby reducing "ineffective lighting" and "excessive lighting" in the tunnel.

[0050] At present, the existing market of tunnel lighting is still dominated by the sequential + loop method. This method uses the closed loop lighting method at night, which will cause uneven brightness of the tunnel road surface and the "zebra crossing" phenomenon, greatly affecting the safety of tunnel driving. The present invention is compatible with the sequential lighting method currently used in tunnel lighting, and can add as few devices as possible to the existing stock market solution to upgrade the system solution, so as to create a comfortable driving experience and achieve both safety and energy saving.

[0051] In the description of the above embodiments, relational terms such as first, second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "comprises", or any other variants thereof herein are intended to cover non-exclusive inclusion, including not only those elements, but also other elements not explicitly listed, or also including elements inherent to such process, method, article, or device. Those skilled in the art can clearly understand that the technical solutions described in the embodiments disclosed herein can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention can essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a computer-readable storage medium, such as a random access memory (RAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a flash memory, a hard disk, a CD-ROM, a floppy disk, a cassette tape, a magnetic medium, an optical medium, and other computer-readable storage media, and includes a number of instructions for enabling a device (such as a mobile phone, a computer, a server, a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0052] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A road tunnel on-demand lighting sensing control method based on the Internet of Things, characterized in that: The Internet of Things platform is implemented based on the perception layer, network layer, management layer and application layer; wherein, the highway tunnel is divided into at least three tunnel sections from the entrance to the exit, namely the entrance section, the middle section and the exit section, each tunnel section is equipped with a lighting control system, and each tunnel section is divided into a plurality of monitoring sections arranged in sequence; the number of the perception layers is the same as the number of the highway tunnel sections, and each perception layer obtains the collected data of a tunnel section and sends it to the network layer, and receives the instructions sent by the management layer to control the opening and closing and illumination of the lamps in its lighting control system; the management layer includes a management main layer and management sublayers with the same number of highway tunnel sections, each management sublayer obtains the collected data of a perception layer through the network layer and sends it to the management main layer after processing, the management main layer obtains the data sent by all management sublayers at a set time interval and sends it to the application layer after processing for users to view and apply, and the management main layer also generates control instructions and sends them to the perception layer through the management sublayer and the network layer in sequence to the lighting control system; The method comprises the following steps: Step S1: The perception layer obtains the vehicle presence data, ambient light perception data, and vehicle speed data, vehicle length data, and vehicle position data of all monitoring sections in the corresponding tunnel section at a set time interval, and sends them to the network layer, which is then transmitted to the management sublayer corresponding to the perception layer. Step S2: The management sublayer determines whether there are vehicles in all monitoring sections of the corresponding tunnel section according to the data it obtains. If there are vehicles, the lamp opening position and quantity are calculated according to the vehicle speed data, vehicle length data, vehicle position data and the lamp spacing of the corresponding tunnel section, and the illumination of the lamp to be turned on is calculated according to the ambient light perception data and the vehicle speed data, and then the calculated lamp opening position and quantity and lamp opening illumination data are sent to the management main layer; Step S3: After the management main layer obtains the data sent by the management sublayer at the set time interval, it calculates whether the number of lamps in the lighting control system in the perception layer corresponding to each management sublayer located in the vehicle's forward direction within the set time threshold meets the demand; if so, a control instruction is generated and sent to the lighting control system of the corresponding management sublayer to control the lamps to turn on according to the calculated illumination and time; if not, it is determined whether the lighting control system corresponding to the management sublayer is located in the tunnel exit section; if it is the exit section, a control instruction is directly generated and sent to the lighting control system corresponding to the management sublayer to control the lamps to turn on according to the calculated illumination and time; otherwise, a control instruction is generated and sent to the lighting control system corresponding to the management sublayer and the lighting control system corresponding to the management sublayer adjacent to the management sublayer in the tunnel exit direction to control the lamps to turn on according to the calculated illumination and time.

2. The on-demand lighting sensing control method for highway tunnels based on the Internet of Things according to claim 1 is characterized in that: The calculation of the number of lights turned on in step S2 includes calculating the number of lights that need to be activated synchronously when a single vehicle passes, and the calculation formula is: ； in, N is the number of lamps to be activated, D is the stopping sight distance, L veh is the vehicle length, d lamp is the distance between lamps, The symbol for rounding up; Stopping sight distance D The calculation formula is: ； in, v is the vehicle speed, t r The driver's reaction time, g is the acceleration due to gravity, f is the friction coefficient between tire and road, i is the longitudinal slope of the road, S 0 is the set safety margin.

3. The on-demand lighting sensing control method for highway tunnels based on the Internet of Things according to claim 1 is characterized in that: The calculation formula for calculating the illumination of the lamp to be turned on according to the ambient light perception data and the vehicle speed data in step S2 is: ； in, is the illumination of the lamp to be turned on, is the target illumination, is the measured ambient light perception data; where the target illumination The calculation method is: ； in, E base is the basic illumination, k is the dynamic compensation coefficient, v crit is the critical speed threshold, e is the base of natural logarithms.

4. The on-demand lighting sensing control method for highway tunnels based on the Internet of Things according to claim 3 is characterized in that: When the length of the highway tunnel is greater than a set length threshold, a transition section is arranged between the entrance section and the middle section, and between the middle section and the exit section; the illumination of the lamps in the entrance section and the exit section of the highway tunnel when they are turned on is greater than the illumination of the lamps in the middle section, the illumination of the transition section between the entrance section and the middle section decreases from the tunnel entrance to the exit, and the illumination of the transition section between the middle section and the exit section increases from the tunnel entrance to the exit; the illumination adjustment is achieved by setting the basic illumination.

5. The on-demand lighting sensing control method for highway tunnels based on the Internet of Things according to claim 1 is characterized in that: The management main layer determines whether there are multiple vehicles that need to turn on the same lamp at the same time based on the data it obtains. If there are lamps to be turned on, the illumination is: ； in, is the final output illuminance when the lamp is turned on. Calculate the illumination of the lamps that need to be turned on for each vehicle independently. α is the attenuation factor.

6. The on-demand lighting sensing control method for highway tunnels based on the Internet of Things according to claim 1 is characterized in that: The sensing layer in the first monitoring section from the entrance to the exit of the highway tunnel entrance section monitors whether there is a vehicle, and the devices for monitoring the vehicle speed data, vehicle length data, and vehicle position data when a vehicle exists are arranged at a set distance from the highway tunnel entrance.

7. The on-demand lighting sensing control method for highway tunnels based on the Internet of Things according to claim 1 is characterized in that: When the lighting control system controls the lamps to turn on according to the calculated illumination and time in step S3, the calculated number of lamps that need to be turned on simultaneously are turned on synchronously, and the turn-on time intervals of the remaining lamps that need to be turned on are calculated based on the lamp spacing divided by the vehicle speed.

8. The on-demand lighting sensing control method for highway tunnels based on the Internet of Things according to claim 1 is characterized in that: The control instructions generated by the management main layer are also used to control the lighting control system to keep the lamps on for a certain period of time. t on The calculation formula is: ； in, L lamp is the effective lighting length of the lamp, S buffer is the set buffer distance, v is the vehicle speed, t safe is the set safety redundancy time, t delay The system response delay is set; When multiple vehicles are following each other, the lights will remain on based on the nearest vehicle behind until the last vehicle passes the calculated stay-on time.

9. The on-demand lighting sensing control method for highway tunnels based on the Internet of Things according to claim 1 is characterized in that: The vehicle presence data detection in the perception layer is realized by a geomagnetic sensor, the ambient light perception data detection is realized by a light sensor, and the vehicle speed data, vehicle length data and vehicle position data detection is realized by a millimeter wave radar sensor.

10. A system for implementing the on-demand lighting sensing control method for highway tunnels based on the Internet of Things as described in any one of claims 1 to 9, characterized in that: An Internet of Things platform comprising a perception layer, a network layer, a management layer and an application layer; wherein, from the entrance to the exit, a highway tunnel is divided into at least three tunnel sections, namely, an entrance section, an intermediate section and an exit section, each tunnel section is provided with a lighting control system, and each tunnel section is divided into a plurality of monitoring sections arranged in sequence; the number of the perception layers is the same as the number of the highway tunnel sections, and each perception layer obtains the collected data of a tunnel section and sends it to the network layer, and receives the instructions sent by the management layer to control the opening and closing and illumination of the lamps in its lighting control system; the management layer comprises a management main layer and management sublayers, the number of which is the same as the number of the highway tunnel sections, each management sublayer obtains the collected data of a perception layer through the network layer and sends it to the management main layer after processing, the management main layer obtains the data sent by all management sublayers at a set time interval and sends it to the application layer after processing for users to view and apply, and the management main layer also generates control instructions and sends them to the perception layer through the management sublayer and the network layer in sequence to the lighting control system; The perception layer is used to obtain the vehicle presence data, ambient light perception data, and vehicle speed data, vehicle length data, and vehicle position data of all monitoring sections in the corresponding tunnel section at set time intervals, and send them to the network layer, which is then transmitted to the management sublayer corresponding to the perception layer by the network layer; The management sublayer is used to determine whether there are vehicles in all monitoring sections of the corresponding tunnel section based on the data it obtains. If there are vehicles, the lamp opening position and number are calculated based on the vehicle speed data, vehicle length data, vehicle position data and the lamp spacing of the corresponding tunnel section, and the illumination of the lamps to be turned on is calculated based on the ambient light perception data and vehicle speed data, and then the calculated lamp opening position and number and lamp opening illumination data are sent to the management main layer; The management main layer is used to obtain the data sent by the management sublayer at the set time interval, and then calculate whether the number of lamps in the lighting control system of the perception layer corresponding to each management sublayer located in the vehicle's forward direction within the set time threshold meets the demand. If so, a control instruction is generated and sent to the lighting control system of the corresponding management sublayer to control the lamps to turn on according to the calculated illumination and time. If not, it is determined whether the lighting control system corresponding to the management sublayer is located in the tunnel exit section. If it is the exit section, a control instruction is directly generated and sent to the lighting control system corresponding to the management sublayer to control the lamps to turn on according to the calculated illumination and time. Otherwise, a control instruction is generated and sent to the lighting control system corresponding to the management sublayer and the lighting control system corresponding to the management sublayer adjacent to the management sublayer in the tunnel exit direction to control the lamps to turn on according to the calculated illumination and time.

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