Tunnel energy conservation and emission reduction control method and system

Abstract

The invention discloses a tunnel energy conservation and emission reduction control method and system, belongs to the technical field of tunnel energy conservation and emission reduction control, and aims at solving the problems that an existing tunnel energy conservation and emission reduction method is low in intelligence, factors influencing energy conservation and emission of a highway tunnel are not comprehensively analyzed, and the energy conservation and emission reduction efficiency is low. And the requirements of saving energy and reducing emission cannot be met under the condition that normal operation management of the tunnel is ensured. The method comprises the following steps: constructing a tunnel traffic and safety association model based on historical traffic data and historical safety data; constructing a tunnel traffic and emission correlation model based on the historical traffic data and the historical carbon emission data; constructing a tunnel traffic control model based on the tunnel traffic and safety association model and the tunnel traffic and emission association model; and inputting the tunnel real-time operation data into the tunnel traffic control model to obtain the current optimal vehicle speed in the target tunnel, and limiting the speed of a vehicle entering the target tunnel according to the current optimal vehicle speed.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel energy conservation and emission reduction control, and in particular to a tunnel energy conservation and emission reduction control method and system. Background Art

[0002] With the rapid development of highway construction, the construction of highway tunnels has also advanced by leaps and bounds. In recent years, long tunnels and extra-long tunnels have accounted for an increasing proportion of highway tunnels. With the completion and opening of these tunnels, the operation and management costs of the tunnels, especially the energy consumption costs of the tunnels, have become a huge expense. In addition, there are problems in the current tunnels, such as backward design, short life of lighting facilities, excessive lighting, excessive energy consumption, and inadequate environmental protection, which has resulted in a situation that is neither environmentally friendly nor emission-reducing.

[0003] For the above problems, the most commonly used solution is to replace the lighting, ventilation and other electrical facilities in the tunnel with electrical equipment with lower energy consumption, thereby reducing some energy consumption. However, this method is less intelligent and cannot completely solve the problem of high energy consumption in the tunnel. There are still many external factors in the tunnel that affect energy consumption and carbon emissions, resulting in unsatisfactory energy conservation and emission reduction effects in the tunnel. In addition, replacing more energy-efficient electrical equipment will also generate additional tunnel operating costs. It can be seen that the current tunnel energy conservation and emission reduction methods have not conducted a comprehensive analysis of the factors that affect the energy conservation and emissions of highway tunnels, and cannot meet the requirements of energy conservation and emission reduction while ensuring the normal operation and management of the tunnel. Summary of the invention

[0004] The embodiments of the present invention provide a tunnel energy conservation and emission reduction control method and system for solving the following technical problems: the current tunnel energy conservation and emission reduction methods are less intelligent, and no comprehensive analysis is conducted on the factors affecting the energy conservation and emission of highway tunnels, and it is impossible to achieve the requirements of saving energy and reducing emissions while ensuring the normal operation and management of the tunnel.

[0005] The embodiment of the present invention adopts the following technical solutions: On the one hand, an embodiment of the present invention provides a tunnel energy conservation and emission reduction control method, the method comprising: obtaining historical traffic data and corresponding historical safety data and historical carbon emission data in a target tunnel; Based on the historical traffic data and the historical safety data, construct a tunnel traffic and safety association model; Based on the historical traffic data and the historical carbon emission data, construct a tunnel traffic and emission correlation model; Constructing a tunnel traffic control model based on the tunnel traffic and safety association model and the tunnel traffic and emission association model; Acquire real-time operation data and real-time brightness data in the target tunnel; Inputting the real-time operation data into the tunnel traffic control model to obtain the current optimal vehicle speed in the target tunnel, and limiting the speed of vehicles entering the target tunnel according to the current optimal vehicle speed; According to the real-time brightness data, the number and brightness of the lighting lamps in the target tunnel are adjusted to perform energy-saving optimization control.

[0006] In a feasible implementation manner, obtaining historical traffic data and corresponding historical safety data and historical carbon emission data in the target tunnel specifically includes: Collect historical traffic data of the target tunnel within a preset period of time; wherein the historical traffic data at least includes: average traffic volume and average vehicle speed per unit time within the preset period of time; Collect historical safety data and historical carbon emission data per unit time within the same preset time period, and correspond the historical safety data and historical carbon emission data to the historical traffic data one by one according to the time axis; The historical safety data includes at least: the traffic accident rate per unit time within a preset period of time and the proportion of serious traffic accidents.

[0007] In a feasible implementation manner, based on the historical traffic data and the historical safety data, a tunnel traffic and safety association model is constructed, which specifically includes: Calculating the vehicle speed standard deviation and the vehicle speed difference between adjacent road sections according to the average vehicle speed in the historical traffic data; Determining a first correlation formula between the vehicle speed standard deviation and the traffic accident incidence rate according to a linear relationship between the vehicle speed standard deviation and the traffic accident incidence rate in the historical safety data; Calculating an accident risk factor based on the proportion of serious traffic accidents in the historical safety data; Determine a second correlation formula between the speed difference between adjacent road sections and the proportion of serious traffic accidents according to the linear relationship between the speed difference between adjacent road sections and the proportion of serious traffic accidents in the historical safety data; The tunnel traffic and safety association model is constructed according to the first association formula and the second association formula.

[0008] In a feasible implementation manner, the tunnel traffic and safety association model is constructed according to the first association formula and the second association formula, specifically including: According to the first correlation formula , and the second association formula , and obtain the tunnel traffic and safety association model ; Wherein, P is the traffic accident rate, is the standard deviation of vehicle speed; r is the proportion of serious traffic accidents, is the accumulated value of vehicle speed, is the speed difference between the adjacent road sections; S is the driving safety factor, and v is the vehicle driving speed.

[0009] In a feasible implementation manner, based on the historical traffic data and the historical carbon emission data, a tunnel traffic and emission correlation model is constructed, which specifically includes: Obtain CO2 baseline emissions from the historical carbon emissions data and the model coefficient of CO ; In the historical traffic data, obtain the vehicle density ; According to the CO benchmark emission, the CO vehicle model coefficient and the vehicle density, a tunnel traffic and emission correlation model is constructed: ; Wherein, T is the total CO emissions in the target tunnel, L is the length of the target tunnel, v is the vehicle speed, n is the total number of vehicle types passing through the target tunnel, and m represents the mth vehicle type.

[0010] In a feasible implementation manner, based on the tunnel traffic and safety association model and the tunnel traffic and emission association model, a tunnel traffic control model is constructed, which specifically includes: according to , determine the tunnel safety factor of the target tunnel ;in, is the frequency of accidents within a unit distance of the target tunnel, is the economic loss of a single accident, is the length of the target tunnel, is the unit distance; according to , determine the CO cost coefficient of the target tunnel ; Where z is the number of fans required, which is calculated by dividing the required air volume by the air volume provided by each fan; The electricity cost for the fan operation is is the CO concentration per unit distance; according to , establish a tunnel traffic control model with the minimum energy saving and emission reduction cost for the target tunnel; where M is the tunnel operation cost, is the tunnel traffic and safety association model, is, T is the tunnel traffic and emission correlation model.

[0011] In a feasible implementation manner, obtaining real-time operation data and real-time brightness data in the target tunnel specifically includes: Acquire real-time operation data in the target tunnel; wherein the real-time operation data at least includes: the length of the target tunnel, the electricity cost required by the fan, and the CO concentration per unit distance; The real-time brightness data in the target tunnel is acquired by a brightness sensor device, wherein the real-time brightness data at least includes: an actual light intensity value per unit distance.

[0012] In a feasible implementation manner, the real-time operation data is input into the tunnel traffic control model to obtain the current optimal vehicle speed in the target tunnel, and the speed of vehicles entering the target tunnel is limited by the current optimal vehicle speed, specifically including: Inputting the real-time operation data collected in the current unit time into the tunnel traffic control model, and solving the tunnel traffic control model to obtain the optimal vehicle speed and the optimal number of fan starts in the current unit time; Displaying the optimal vehicle speed at the entrance of a target tunnel to limit the speed of vehicles entering the target tunnel; After the current unit time ends, the next unit time is entered and data is re-entered for solving to update the optimal vehicle speed; According to the optimal number of fans to be started, a corresponding number of fans in the target tunnel are controlled to operate.

[0013] In a feasible implementation manner, according to the real-time brightness data, the number and brightness of the lighting lamps in the target tunnel are adjusted to perform energy-saving optimization control, specifically including: Extract the actual light intensity value from the real-time brightness data within each unit distance; If the actual light intensity value within the unit distance is less than the first preset threshold, two-thirds of the lighting lamps in the unit distance are controlled to turn on; If the actual light intensity value within the unit distance is greater than or equal to the first preset threshold value and less than the second preset threshold value, then control one-half of the lighting lamps in the unit distance to turn on; If the actual light intensity value within the unit distance is greater than or equal to the second preset threshold, one third of the lighting lamps in the unit distance are controlled to be turned on.

[0014] On the other hand, an embodiment of the present invention further provides a tunnel energy-saving and emission-reduction control system, the system comprising: A model building module is used to obtain historical traffic data and corresponding historical safety data and historical carbon emission data in the target tunnel; based on the historical traffic data and the historical safety data, a tunnel traffic and safety association model is constructed; based on the historical traffic data and the historical carbon emission data, a tunnel traffic and emission association model is constructed; based on the tunnel traffic and safety association model and the tunnel traffic and emission association model, a tunnel traffic control model is constructed; A data acquisition module, used to obtain real-time operation data and real-time brightness data in the target tunnel; The energy-saving control module is used to input the real-time operation data into the tunnel traffic control model to obtain the current optimal vehicle speed in the target tunnel, and limit the speed of vehicles entering the target tunnel according to the current optimal vehicle speed; and is used to adjust the number and brightness of the lighting lamps in the target tunnel according to the real-time brightness data to perform energy-saving optimization control.

[0015] Compared with the prior art, the tunnel energy conservation and emission reduction control method and system provided by the embodiment of the present invention has the following beneficial effects: The present invention constructs a tunnel traffic control model by analyzing the relationship between the traffic conditions in the tunnel and safety and carbon emissions. By calculating the optimal vehicle speed per unit time, the vehicle flow and speed in the tunnel are intelligently controlled to achieve energy-saving control and emission reduction control in the tunnel. It can reduce energy consumption and carbon emissions in the tunnel by controlling vehicle speed and lighting while ensuring that the tunnel operating costs do not increase. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings: Figure 1 A flow chart of a tunnel energy saving and emission reduction control method provided by an embodiment of the present invention; Figure 2 A schematic structural diagram of a tunnel energy-saving and emission-reduction control system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0018] The embodiment of the present invention provides a tunnel energy saving and emission reduction control method, such as Figure 1 As shown, the tunnel energy saving and emission reduction control method specifically includes steps S101-S107: S101. Acquire historical traffic data, corresponding historical safety data, and historical carbon emission data in a target tunnel.

[0019] Specifically, firstly, historical traffic data of the target tunnel within a preset time period is collected; wherein the historical traffic data at least includes: average vehicle flow and average vehicle speed per unit time within the preset time period.

[0020] Furthermore, historical safety data and historical carbon emission data per unit time within the same preset time period are collected, and the historical safety data and historical carbon emission data are respectively matched one by one with the historical traffic data according to the time axis.

[0021] Among them, the historical safety data includes at least: the traffic accident rate per unit time within a preset period of time and the proportion of serious traffic accidents.

[0022] S102. Construct a tunnel traffic and safety association model based on historical traffic data and historical safety data.

[0023] Specifically, the speed standard deviation and the speed difference between adjacent sections are calculated based on the average speed in the historical traffic data, and then the first correlation formula between the speed standard deviation and the traffic accident rate is determined based on the linear relationship between the speed standard deviation and the traffic accident rate in the historical safety data.

[0024] Furthermore, the accident risk coefficient is calculated based on the proportion of serious traffic accidents in the historical safety data. Then, based on the linear relationship between the speed difference between adjacent sections and the proportion of serious traffic accidents in the historical safety data, a second correlation formula between the speed difference between adjacent sections and the proportion of serious traffic accidents is determined.

[0025] As a feasible implementation method, the first correlation formula is: , where P is the traffic accident rate, is the standard deviation of vehicle speed; the second correlation formula is , where r is the proportion of serious traffic accidents, is the accumulated value of vehicle speed, is the speed difference between adjacent road sections; Further, according to the first association formula and the second association formula, a tunnel traffic and safety association model is constructed. Specifically: according to the first association formula , and the second association formula , we get the tunnel traffic and safety association model ; Among them, S is the driving safety factor and v is the vehicle speed.

[0026] S103. Based on historical traffic data and historical carbon emission data, a tunnel traffic and emission correlation model is constructed.

[0027] Specifically, obtain the CO benchmark emissions from historical carbon emissions data and the model coefficient of CO Then, in the historical traffic data, obtain the vehicle density .

[0028] Furthermore, based on the CO benchmark emission, CO vehicle model coefficient and vehicle density, a tunnel traffic and emission correlation model is constructed: ; Where T is the total CO emissions in the target tunnel, L is the length of the target tunnel, v is the vehicle speed, n is the total number of vehicle types passing through the target tunnel, and m represents the mth vehicle type.

[0029] S104. Construct a tunnel traffic control model based on the tunnel traffic and safety association model and the tunnel traffic and emission association model.

[0030] Specifically, according to , determine the tunnel safety factor of the target tunnel ;in, is the frequency of accidents within a unit distance of the target tunnel, is the economic loss of a single accident, is the length of the target tunnel, is the unit distance.

[0031] Further, according to , determine the CO cost coefficient of the target tunnel ; Where z is the number of fans required, which is calculated by dividing the required air volume by the air volume provided by each fan; The electricity cost for the fan operation is is the CO concentration per unit distance.

[0032] Further, according to , establish a tunnel traffic control model with the minimum energy saving and emission reduction cost for the target tunnel; where M is the tunnel operation cost, is the tunnel traffic and safety association model, is, T is the tunnel traffic and emission correlation model.

[0033] S105. Acquire real-time operation data and real-time brightness data in the target tunnel.

[0034] Specifically, the real-time operation data in the target tunnel is obtained through the data acquisition equipment, wherein the real-time operation data at least includes: the length of the target tunnel, the electricity cost required for the fan, and the CO concentration per unit distance. At the same time, the real-time brightness data in the target tunnel is obtained through the brightness sensor equipment, wherein the real-time brightness data at least includes: the actual light intensity value per unit distance.

[0035] S106: Input the real-time operation data into the tunnel traffic control model to obtain the current optimal vehicle speed in the target tunnel, and use the current optimal vehicle speed to limit the speed of vehicles entering the target tunnel.

[0036] Specifically, the real-time operation data collected within the current unit time is input into the tunnel traffic control model In the tunnel traffic control model, the optimal vehicle speed and the optimal number of fans to be started are solved when M takes the minimum value. Passing through the tunnel at this optimal speed can achieve the requirements of energy saving and emission reduction while ensuring the normal operation and management of the tunnel.

[0037] Furthermore, the optimal vehicle speed is displayed at the entrance of the target tunnel to limit the speed of vehicles entering the target tunnel, thereby ensuring that the vehicle speed in the tunnel is maintained at the lowest emission and highest safety state.

[0038] Furthermore, after the current unit time ends, the next unit time is entered and data is re-entered for solving to update the optimal vehicle speed, thus achieving real-time control of energy saving and emission reduction.

[0039] Furthermore, according to the optimal number of fans to be started, the operation of a corresponding number of fans in the target tunnel is controlled to save energy consumption of the fans in the tunnel.

[0040] S107. According to the real-time brightness data, the number and brightness of the lighting lamps in the target tunnel are adjusted to perform energy-saving optimization control.

[0041] Specifically, the actual light intensity value is extracted from the real-time brightness data within each unit distance. If the actual light intensity value within the unit distance is less than the first preset threshold, two-thirds of the lighting lamps in the unit distance are controlled to be turned on.

[0042] If the actual light intensity value within the unit distance is greater than or equal to the first preset threshold and less than the second preset threshold, half of the lighting lamps in the unit distance are controlled to be turned on.

[0043] If the actual light intensity value within the unit distance is greater than or equal to the second preset threshold, one third of the lighting lamps in the unit distance are controlled to be turned on.

[0044] By controlling the number of lighting lamps, the brightness in the tunnel can be adjusted in real time, the brightness of the tunnel can be maintained at a stable state, and the energy consumption of the lighting lamps can be saved.

[0045] In addition, the embodiment of the present invention also provides a tunnel energy saving and emission reduction control system, such as Figure 2 As shown, the tunnel energy saving and emission reduction control system 200 specifically includes: The model building module 210 is used to obtain historical traffic data and corresponding historical safety data and historical carbon emission data in the target tunnel; based on the historical traffic data and the historical safety data, build a tunnel traffic and safety association model; based on the historical traffic data and the historical carbon emission data, build a tunnel traffic and emission association model; based on the tunnel traffic and safety association model and the tunnel traffic and emission association model, build a tunnel traffic control model; A data acquisition module 220 is used to obtain real-time operation data and real-time brightness data in the target tunnel; The energy-saving control module 230 is used to input the real-time operation data into the tunnel traffic control model to obtain the current optimal vehicle speed in the target tunnel, and limit the speed of vehicles entering the target tunnel according to the current optimal vehicle speed; and is used to adjust the number and brightness of the lighting lamps in the target tunnel according to the real-time brightness data to perform energy-saving optimization control.

[0046] Each embodiment of the present invention is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0047] The above describes specific embodiments of the present invention. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0048] The above description is only an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the embodiments of the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention should be included in the protection scope of the present invention.

Claims

1. A tunnel energy saving and emission reduction control method, characterized in that: The method comprises: Obtain historical traffic data and corresponding historical safety data and historical carbon emission data in the target tunnel; Based on the historical traffic data and the historical safety data, construct a tunnel traffic and safety association model; Based on the historical traffic data and the historical carbon emission data, construct a tunnel traffic and emission correlation model; Constructing a tunnel traffic control model based on the tunnel traffic and safety association model and the tunnel traffic and emission association model; Acquire real-time operation data and real-time brightness data in the target tunnel; Inputting the real-time operation data into the tunnel traffic control model to obtain the current optimal vehicle speed in the target tunnel, and limiting the speed of vehicles entering the target tunnel according to the current optimal vehicle speed; According to the real-time brightness data, the number and brightness of the lighting lamps in the target tunnel are adjusted to perform energy-saving optimization control.

2. A tunnel energy saving and emission reduction control method according to claim 1, characterized in that: Obtain the historical traffic data and corresponding historical safety data and historical carbon emission data in the target tunnel, including: Collect historical traffic data of the target tunnel within a preset period of time; wherein the historical traffic data at least includes: average traffic volume and average vehicle speed per unit time within the preset period of time; Collect historical safety data and historical carbon emission data per unit time within the same preset time period, and correspond the historical safety data and historical carbon emission data to the historical traffic data one by one according to the time axis; The historical safety data includes at least: the traffic accident rate per unit time within a preset period of time and the proportion of serious traffic accidents.

3. A tunnel energy saving and emission reduction control method according to claim 1, characterized in that: Based on the historical traffic data and the historical safety data, a tunnel traffic and safety association model is constructed, specifically including: Calculating the vehicle speed standard deviation and the vehicle speed difference between adjacent road sections according to the average vehicle speed in the historical traffic data; Determining a first correlation formula between the vehicle speed standard deviation and the traffic accident incidence rate according to a linear relationship between the vehicle speed standard deviation and the traffic accident incidence rate in the historical safety data; Calculating an accident risk factor based on the proportion of serious traffic accidents in the historical safety data; Determine a second correlation formula between the speed difference between adjacent road sections and the proportion of serious traffic accidents according to the linear relationship between the speed difference between adjacent road sections and the proportion of serious traffic accidents in the historical safety data; The tunnel traffic and safety association model is constructed according to the first association formula and the second association formula.

4. A tunnel energy saving and emission reduction control method according to claim 3, characterized in that: According to the first association formula and the second association formula, the tunnel traffic and safety association model is constructed, specifically including: According to the first correlation formula , and the second association formula , and obtain the tunnel traffic and safety association model ; Wherein, P is the traffic accident rate, is the standard deviation of vehicle speed; r is the proportion of serious traffic accidents, is the accumulated value of vehicle speed, is the speed difference between the adjacent road sections; S is the driving safety factor, and v is the vehicle driving speed.

5. A tunnel energy saving and emission reduction control method according to claim 1, characterized in that: Based on the historical traffic data and the historical carbon emission data, a tunnel traffic and emission correlation model is constructed, specifically including: Obtain CO2 baseline emissions from the historical carbon emissions data and the model coefficient of CO ; In the historical traffic data, obtain the vehicle density ; According to the CO benchmark emission, the CO vehicle model coefficient and the vehicle density, a tunnel traffic and emission correlation model is constructed: ; Wherein, T is the total CO emissions in the target tunnel, L is the length of the target tunnel, v is the vehicle speed, n is the total number of vehicle types passing through the target tunnel, and m represents the mth vehicle type.

6. A tunnel energy saving and emission reduction control method according to claim 1, characterized in that: Based on the tunnel traffic and safety association model and the tunnel traffic and emission association model, a tunnel traffic control model is constructed, which specifically includes: according to , determine the tunnel safety factor of the target tunnel ;in, is the frequency of accidents within a unit distance of the target tunnel, is the economic loss of a single accident, is the length of the target tunnel, is the unit distance; according to , determine the CO cost coefficient of the target tunnel ; Where z is the number of fans required, which is calculated by dividing the required air volume by the air volume provided by each fan; The electricity cost for the fan operation is is the CO concentration per unit distance; according to , establish a tunnel traffic control model with the minimum energy saving and emission reduction cost for the target tunnel; where M is the tunnel operation cost, is the tunnel traffic and safety association model, is, T is the tunnel traffic and emission correlation model.

7. A tunnel energy saving and emission reduction control method according to claim 1, characterized in that: Acquiring real-time operation data and real-time brightness data in the target tunnel, specifically including: Acquire real-time operation data in the target tunnel; wherein the real-time operation data at least includes: the length of the target tunnel, the electricity cost required by the fan, and the CO concentration per unit distance; The real-time brightness data in the target tunnel is acquired by a brightness sensor device, wherein the real-time brightness data at least includes: an actual light intensity value per unit distance.

8. A tunnel energy saving and emission reduction control method according to claim 1, characterized in that: Inputting the real-time operation data into the tunnel traffic control model to obtain the current optimal vehicle speed in the target tunnel, and limiting the speed of vehicles entering the target tunnel according to the current optimal vehicle speed, specifically includes: Inputting the real-time operation data collected in the current unit time into the tunnel traffic control model, and solving the tunnel traffic control model to obtain the optimal vehicle speed and the optimal number of fan starts in the current unit time; Displaying the optimal vehicle speed at the entrance of a target tunnel to limit the speed of vehicles entering the target tunnel; After the current unit time ends, enter the next unit time and re-enter the data for solving to update the optimal vehicle speed; According to the optimal number of fans to be started, a corresponding number of fans in the target tunnel are controlled to operate.

9. A tunnel energy saving and emission reduction control method according to claim 1, characterized in that: According to the real-time brightness data, the number and brightness of the lighting lamps in the target tunnel are adjusted to perform energy-saving optimization control, specifically including: Extract the actual light intensity value from the real-time brightness data within each unit distance; If the actual light intensity value within the unit distance is less than the first preset threshold, two-thirds of the lights in the unit distance are controlled to turn on; If the actual light intensity value within the unit distance is greater than or equal to the first preset threshold value and less than the second preset threshold value, then control one-half of the lighting lamps in the unit distance to turn on; If the actual light intensity value within the unit distance is greater than or equal to the second preset threshold, one third of the lighting lamps in the unit distance are controlled to be turned on.

10. A tunnel energy saving and emission reduction control system, characterized in that: The system comprises: A model building module is used to obtain historical traffic data and corresponding historical safety data and historical carbon emission data in the target tunnel; based on the historical traffic data and the historical safety data, a tunnel traffic and safety association model is constructed; based on the historical traffic data and the historical carbon emission data, a tunnel traffic and emission association model is constructed; based on the tunnel traffic and safety association model and the tunnel traffic and emission association model, a tunnel traffic control model is constructed; A data acquisition module, used to obtain real-time operation data and real-time brightness data in the target tunnel; The energy-saving control module is used to input the real-time operation data into the tunnel traffic control model to obtain the current optimal vehicle speed in the target tunnel, and limit the speed of vehicles entering the target tunnel according to the current optimal vehicle speed; and is used to adjust the number and brightness of the lighting lamps in the target tunnel according to the real-time brightness data to perform energy-saving optimization control.

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