Tunnel traffic control method and system for multi-mode traffic variable analysis

Abstract

The invention discloses a tunnel traffic control method and system for multi-mode traffic variable analysis, and relates to the field of general control or regulation systems, and the method comprises the steps: obtaining vehicle operation state information and pollutant concentration distribution data, determining a pollutant generation region based on a vehicle state, and calculating a concentration gradient value and a diffusion rate value. And analyzing the concentration change trend according to the spatial-temporal distribution relationship, and dividing a vertical control region. And setting initial operation parameters of the jet fan in a preset adjustment range and a step length according to the pollutant distribution characteristics of each area. And monitoring area concentration distribution in real time, when a target area exceeds the standard, dynamically adjusting fan parameters of the area and an adjacent area to preset values, and setting illumination parameters of illumination equipment in the vertical control area according to pollutant concentration distribution characteristics. By implementing the method, the accuracy of tunnel partition environment parameter adjustment can be improved.

Description

Technical Field

[0001] This application relates to the field of general control or regulation systems, and particularly to a tunnel traffic control method and system for multi-modal traffic variable analysis. Background Art

[0002] With the rapid development of urban traffic infrastructure, tunnels have become important facilities for alleviating urban traffic congestion. The air quality inside tunnels directly affects driving safety and personnel health, and high concentrations of pollutants can affect the lighting visibility inside the tunnels. Therefore, an effective tunnel traffic control system needs to be established to manage and regulate the air quality inside the tunnels.

[0003] Current tunnel traffic control systems mainly adjust the environmental parameters inside the tunnels by setting environmental monitoring devices and control devices inside the tunnels. These systems adopt fixed control strategies and adjust the operating parameters of various devices at preset time intervals according to indicators such as traffic flow and pollutant concentration inside the tunnels to maintain the environmental quality inside the tunnels.

[0004] In practical applications, due to the obvious spatial differences in the distribution of pollutant concentrations inside the tunnels and the dynamic change characteristics affected by various factors such as vehicle flow and wind speed, fixed control strategies are difficult to accurately reflect the environmental control requirements of different regions, which may lead to over-control or under-control in some regions, resulting in energy waste or local pollutant accumulation. Summary of the Invention

[0005] This application provides a tunnel traffic control method and system for multi-modal traffic variable analysis, which is used to improve the accuracy of adjusting the environmental parameters of tunnel partitions.

[0006] In a first aspect, the present application provides a tunnel traffic control method for multi-modal traffic variable analysis, which is applied to a tunnel traffic control system. The method includes: obtaining vehicle operation state information and pollutant concentration distribution data in the tunnel space, where the vehicle operation state information includes vehicle type, quantity, vehicle speed, and vehicle distribution position; determining the spatial generation area of pollutants based on the vehicle operation state information, and calculating the concentration gradient value between adjacent heights and the diffusion rate value within a continuous time period according to the pollutant concentration data; determining the pollutant concentration change trend within each height range based on the spatio-temporal distribution relationship of the pollutant spatial generation area, concentration gradient value, and diffusion rate value, and dividing the tunnel space into multiple vertical control areas; setting the operation parameters of the jet fans in each area according to the pollutant distribution characteristics of the vertical control area, and setting the initial operation parameters of the jet fans in each area according to the deviation between the pollutant concentration and the preset threshold, based on the preset jet angle adjustment range and adjustment step, and the jet speed adjustment range and adjustment step; real-time monitoring the pollutant concentration distribution characteristics in each vertical control area, and when it is detected that the concentration in the target area exceeds the preset concentration threshold, adjusting the operation parameters of the jet fans in the target area and the adjacent areas to the preset operation parameters in the adjustment range of the jet angle and speed of the jet fans, and setting the lighting parameters of the lighting equipment in the vertical control area according to the pollutant concentration distribution characteristics.

[0007] In the above embodiment, the spatial generation area of pollutants is determined based on the vehicle operation state information, and the vertical control areas are divided by combining the spatio-temporal distribution relationship of the concentration gradient value and the diffusion rate value, so that the spatial distribution characteristics of pollutants are accurately characterized. The operation parameters of various control devices are dynamically set according to the characteristics of the vertical control area, and the environmental parameters of the relevant areas are adjusted in real time when it is detected that the target area exceeds the standard, realizing the precise matching of regional environmental control, avoiding the problems of excessive or insufficient regional control, ensuring the tunnel environmental quality and saving energy consumption.

[0008] In some embodiments in combination with some embodiments of the first aspect, the step of determining the pollutant concentration change trend in each height range and dividing the tunnel space into multiple vertical control regions according to the spatio-temporal distribution relationship of the pollutant spatial generation region, the concentration gradient value, and the diffusion rate value specifically includes: obtaining the pollutant concentration data at different heights within the pollutant spatial generation region, and performing coupled calculation on the concentration gradient value between adjacent heights and the diffusion rate value corresponding to the height to obtain the pollutant diffusion characteristic value; dividing the tunnel space into multiple temporary control regions according to the pollutant diffusion characteristic value, continuously collecting the pollutant concentration data within the temporary control regions, and when the difference between the pollutant diffusion characteristic values of adjacent temporary control regions is less than the preset difference, merging the adjacent temporary control regions into vertical control regions; when the fluctuation range of the pollutant diffusion characteristic value within the temporary control region is greater than the preset fluctuation threshold, dividing the temporary control region into multiple vertical control regions; and determining the boundary position of the vertical control region according to the pollutant concentration change trend between the vertical control regions.

[0009] In the above embodiments, the concentration gradient value between adjacent heights and the diffusion rate value are coupled and calculated to obtain the diffusion characteristic value, and the temporary control regions are divided accordingly. By continuously monitoring the concentration data within the region, the region division is dynamically adjusted. When the characteristics of adjacent regions are similar, they are merged. When the fluctuation within the region is large, it is subdivided. Finally, the boundary position is determined according to the concentration change trend, establishing a set of adaptive vertical zoning methods, which improves the accuracy and flexibility of space pollution control.

[0010] In some embodiments in combination with some embodiments of the first aspect, the step of, when detecting that the concentration of the target region exceeds the preset concentration threshold, adjusting the operating parameters of the jet fans in the target region and the adjacent regions to the preset operating parameters within the adjustment range of the jet angle and speed of the jet fans specifically includes: obtaining the pollutant concentration data of multiple monitoring points within each vertical control region, calculating the deviation degree between the pollutant concentration of each monitoring point and the preset concentration threshold, and determining the vertical control region with the largest deviation degree as the target region; determining the dominant propagation direction of the abnormal pollutant concentration according to the spatial distribution positions and the pollutant concentration data of the monitoring points within the target region; based on the dominant propagation direction, dividing the jet fans within the target region into a main control fan group and a collaborative fan group, and adjusting the jet angle and jet speed of the main control fan group; when the pollutant concentration decline rate of the target region is less than the preset decline rate, adjusting the operating parameters of the collaborative fan group; and determining the region directly adjacent to the pollutant propagation path according to the dominant propagation direction, and adjusting the operating parameters of the jet fans directly opposite to the main control fan group within the directly adjacent region.

[0011] In the above embodiment, the target area is determined based on the deviation degree of the monitoring point, the dominant propagation direction of the pollutants is analyzed, and the jet fans in the target area are divided into two fan groups: the main control group and the coordinated group. The parameters of the main control group are adjusted according to the propagation direction, and the coordinated group is started when necessary, and the fans in the adjacent areas are adjusted in a linked manner, forming a multi-level, coordinated jet fan control system, which enhances the ability to quickly remove pollutants in local areas.

[0012] In combination with some embodiments of the first aspect, in some embodiments, during real-time monitoring of the pollutant concentration distribution characteristics in each vertical control area, when it is detected that the concentration in the target area exceeds a preset concentration threshold, within the adjustment range of the jet angle and speed of the jet fan, the operating parameters of the jet fans in the target area and the adjacent area are adjusted to the preset operating parameters according to the set step length, and the method further includes: acquiring tunnel wall laser ranging sensor data, calculating the position deviation between the tunnel wall and the reference axis, and determining the curve area according to the position deviation; collecting vehicle speed data in the curve area, and dividing the curve area into a deceleration sub-area, a uniform speed sub-area and an acceleration sub-area according to the vehicle speed data; detecting the number of braking times of the vehicle in the deceleration sub-area, and adjusting the air supply frequency of the jet fan according to the number of braking times; acquiring the average vehicle speed of the inner lane and the outer lane in the curve area, calculating the average vehicle speed difference between the inner and outer lanes, and when the average vehicle speed difference is greater than the first preset threshold, setting the air supply interval time of the inner jet fan to the first preset time; In the above embodiment, the laser ranging data of the tunnel wall is obtained to determine the curve area, and the deceleration, uniform speed and acceleration sub-areas are divided according to the vehicle speed data, and the air supply frequency of the jet fan is adjusted based on the number of braking times. When the speed difference between the inner and outer lanes of the curve is large, the air supply time of the inner jet fan is dynamically adjusted, and a differentiated ventilation control strategy for the curve area is established, which effectively eliminates the local pollutant accumulation phenomenon caused by the change in vehicle speed in the curve area.

[0013] In combination with some embodiments of the first aspect, in some embodiments, after obtaining the average vehicle speeds of the inner lane and the outer lane in the curve area, calculating the average vehicle speed difference between the inner and outer lanes, and when the average vehicle speed difference is greater than a first preset threshold, setting the air supply interval time of the inner jet fan to the first preset time, the method also includes: when the average vehicle speed difference is less than the first preset threshold, setting the air supply interval time of the inner jet fan to a second preset time, and the first preset time is less than the second preset time.

[0014] In the above embodiments, when the difference in average vehicle speeds between the inner and outer lanes is less than a preset threshold, the air supply interval time of the inner jet fan is extended to a second preset time, so that the air supply frequency is adaptively adjusted according to the change in the vehicle speed difference. The switching between the two preset times of long and short establishes a dynamic response mechanism for the ventilation intensity in the inner area, reducing the equipment operation load while ensuring the ventilation effect and optimizing the energy utilization efficiency.

[0015] Combined with some embodiments of the first aspect, in some embodiments, when the distribution characteristics of pollutant concentrations in each vertical control area are monitored in real time, and when it is detected that the concentration in the target area exceeds the preset concentration threshold, after the step of adjusting the operating parameters of the jet fans in the target area and the adjacent areas to the preset operating parameters within the adjustment range of the jet angle and speed of the jet fans, the method further includes: collecting air quality data, light intensity data, and wind speed data in each vertical control area; calculating the deviation value between the air quality data and the historical data in the same period; when the deviation value is greater than the first preset deviation threshold, obtaining the wind speed change trend and air flow direction data of the target area; performing correlation calculation on the wind speed change trend and air flow direction data and the pollutant concentration change trend to determine the pollutant diffusion path; dividing a plurality of monitoring points in the vertical control area based on the pollutant diffusion path, and collecting the pollutant concentration data of the monitoring points; generating ventilation control parameters according to the pollutant space generation area, concentration gradient value, diffusion rate value, and pollutant concentration data of the monitoring points; generating lighting control parameters according to the light intensity data and pollutant concentration data; adjusting the opening number of the ventilation openings based on the ventilation control parameters, and adjusting the luminous power of the lighting equipment based on the lighting control parameters.

[0016] In the above embodiments, environmental parameters such as air quality, light intensity, and wind speed are collected, the deviation of historical data in the same period is analyzed, and the pollutant diffusion path is determined. Based on the diffusion path, a monitoring point network is arranged, ventilation and lighting control parameters are generated, precise adjustment of the number of ventilation openings and lighting power is realized, a linkage mechanism between environmental parameters and equipment control is constructed, and the overall efficiency of tunnel environment regulation is improved.

[0017] In combination with some embodiments of the first aspect, in some embodiments, after the step of real-time monitoring of the pollutant concentration distribution characteristics in each vertical control area, when it is detected that the concentration in the target area exceeds a preset concentration threshold, within the adjustment range of the jet angle and speed of the jet fan, adjusting the operating parameters of the jet fans in the target area and the adjacent area to the preset operating parameters according to the set step length, the method also includes: collecting environmental parameters of each vertical control area, the environmental parameters including light intensity, pollutant concentration and vehicle density; determining the operating condition type of each vertical control area according to the environmental parameters; obtaining the initial value of the control parameter of the jet fan based on the operating condition type; collecting the pollutant diffusion rate and vehicle speed data of the pollutant space generation area, and correcting the initial value of the control parameter according to the pollutant diffusion rate, concentration gradient value and vehicle speed data to obtain the corrected value of the control parameter of the jet fan; when the light intensity in the target area is lower than the first preset light threshold, increasing the luminous power of the lighting equipment according to the control parameter correction value, and adjusting the speed limit value of the vertical control area; when the vehicle density in the target area is greater than the preset density threshold, adjusting the air supply volume of the jet fan in the vertical control area based on the control parameter correction value.

[0018] In the above embodiment, environmental parameters are collected to determine the type of working condition, and the initial value of the control parameter is obtained based on the working condition type. The correction value of the control parameter of the jet fan is obtained by correcting it through the pollutant diffusion rate and vehicle speed data. When the light intensity is lower than the threshold, the lighting power and speed limit value are adjusted in conjunction, and when the vehicle density exceeds the standard, the air supply of the jet fan is adjusted, forming a set of adaptive control strategies based on multi-working condition analysis, realizing the coordinated optimization of tunnel environmental parameters and traffic control.

[0019] In a second aspect, an embodiment of the present application provides a tunnel traffic control system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the tunnel traffic control system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0020] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions. When the computer program product is run on a tunnel traffic control system, the tunnel traffic control system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions. When the instructions are executed on a tunnel traffic control system, the tunnel traffic control system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0022] It can be understood that the tunnel traffic control system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. This application determines the spatial generation area of ​​pollutants based on vehicle operation status information, and divides the vertical control area based on the spatiotemporal distribution relationship of concentration gradient values ​​and diffusion rate values, so that the spatial distribution characteristics of pollutants can be accurately characterized. The operating parameters of various control devices are dynamically set according to the characteristics of the vertical control area, and the environmental parameters of the relevant area are adjusted in real time when the target area is detected to exceed the standard, so as to achieve accurate matching of regional environmental control, avoid the problem of excessive or insufficient regional control, and ensure the quality of tunnel environment while saving energy consumption.

[0024] 2. This application calculates the diffusion characteristic value by coupling the concentration gradient value between adjacent heights with the diffusion rate value, and divides the temporary control area accordingly. By continuously monitoring the concentration data in the area, the regional division is dynamically adjusted. When the characteristics of adjacent areas are similar, they are merged, and when the fluctuations in the area are large, they are subdivided. Finally, the boundary position is determined according to the concentration change trend, and a set of adaptive vertical partitioning methods is established to improve the accuracy and flexibility of spatial pollution control.

[0025] 3. This application determines the target area based on the degree of deviation of the monitoring point, analyzes the dominant propagation direction of pollutants, and divides the jet fans in the target area into two fan groups: main control and coordinated. The parameters of the main control fan group are adjusted according to the propagation direction, and the coordinated fan group is started when necessary, and the fans in adjacent areas are adjusted in a linked manner, forming a multi-level, coordinated jet fan control system, which enhances the ability to quickly remove pollutants in local areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a tunnel traffic control method for multimodal traffic variable analysis in an embodiment of the present application; Figure 2 is another flow chart of the tunnel traffic control method of multimodal traffic variable analysis in an embodiment of the present application; Figure 3 It is a schematic diagram of the structure of a physical device of a tunnel traffic control system in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application, the singular forms "a", "an", "the above", "the", and "this" are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations including one or more of the listed items.

[0028] Hereinafter, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as implying or suggesting relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0029] For ease of understanding, the application scenarios of the embodiments of the present application are introduced below.

[0030] A 5-kilometer-long two-way four-lane tunnel has been built in a certain city, and a longitudinal ventilation system and an array of jet fans are installed in the tunnel. During operation, it is found that the pollutant distribution in the tunnel shows obvious spatial inhomogeneity: the CO concentration in the middle section of the tunnel often exceeds the standard by more than 50%, while the concentration in the two end areas remains at a relatively low level; at the same time, the distribution of pollutant concentration also changes dynamically with the traffic flow. Especially during the morning and evening rush hours, the NO2 concentration in some areas will suddenly increase to three times the normal value. The traditional ventilation control system is difficult to cope with this complex pollutant distribution characteristic, resulting in local areas being in a state of exceeding the pollutant standard for a long time. In addition, due to the large difference in pollutant concentration at different heights in the tunnel, the sensor data at the ground position cannot accurately reflect the air quality status of the entire space. These problems seriously affect the driving safety and traffic efficiency in the tunnel, and an intelligent ventilation system that can accurately identify and control the spatial distribution of pollutants is needed.

[0031] The current tunnel adopts a ventilation control strategy based on fixed time intervals: a group of CO / NO2 sensors are installed every 200 meters in the tunnel. When any sensor detects that the pollutant concentration exceeds the threshold, all jet fans in the area are started, and the air supply automatically stops after 30 minutes. There are obvious problems with this control method: when the traffic volume is large, the pollutant generation rate far exceeds the preset ventilation capacity, resulting in the continuous expansion of the exceeded area; and when the traffic volume is small, excessive ventilation causes energy waste. At the same time, due to the lack of monitoring of the vertical distribution of pollutants, ground-mounted sensors cannot detect pollutant clusters accumulated in the high altitude in time, and the pollution range has expanded when they are discovered. In addition, the fixed ventilation parameter settings cannot adapt to the changes in ventilation demand in different areas and at different times, and sometimes cause local vortices, which in turn aggravate the accumulation of pollutants.

[0032] After adopting the control method of the present invention, the system first collects the vehicle operation status and pollutant distribution data in the tunnel in real time through a multi-level sensor network. Based on the vehicle type, quantity and distribution position, the spatial generation area of ​​pollutants is accurately calculated. By analyzing the concentration gradient and diffusion rate between adjacent heights, the tunnel space is divided into multiple vertical control areas, and each area is equipped with an independent jet fan unit. When it is detected that the pollutants in the target area exceed the standard, the system will identify the dominant propagation direction of the pollutants, and divide the jet fans in the area into a main control group and a collaborative group. By collaboratively adjusting the jet angle and speed, a directional airflow channel is formed to quickly evacuate pollutants. At the same time, the system will also predict the diffusion trend of pollutants, adjust the ventilation parameters of adjacent areas in advance, and effectively prevent the expansion of the pollution range. This precise control method based on multidimensional data analysis keeps the pollutant concentration in the tunnel within a reasonable range at all times, which not only ensures driving safety, but also achieves efficient use of energy.

[0033] For ease of understanding, the following describes the process of the method provided by this implementation in combination with the above scenario. Figure 1 , which is a flow chart of a tunnel traffic control method for multimodal traffic variable analysis in an embodiment of the present application.

[0034] S101. Obtain vehicle operation status information and pollutant concentration distribution data in a tunnel space, wherein the vehicle operation status information includes vehicle type, quantity, speed, and vehicle distribution location.

[0035] Among them, the vehicle operation state information refers to the data set describing the overall operation characteristics of vehicles in the tunnel, including vehicle type (indicating different types of motor vehicles with different emission standards), vehicle quantity (indicating the total number of vehicles passing through a specific section per unit time), vehicle speed (indicating the real-time driving speed of the vehicle), and vehicle distribution position (indicating the real-time coordinate position of the vehicle in the tunnel space). The pollutant concentration distribution data refers to the numerical information reflecting the pollutant content at each monitoring point in the tunnel space, which is used to characterize the distribution state of pollutants in the space).

[0036] Specifically, this step starts to execute when the tunnel traffic control system starts to run, and real-time data is collected through various sensor devices deployed in the tunnel. First, the vehicle detector is used to obtain the vehicle type and quantity information of the vehicles passing through the tunnel, the speed radar is used to collect the vehicle speed data, and the vehicle distribution position is determined through video image processing technology. At the same time, gas concentration sensors distributed at different positions and heights in the tunnel are used to collect pollutant concentration data, and all the data is uploaded to the control system in real time for processing and analysis).

[0037] In some embodiments, the vehicle operation state information and the pollutant concentration distribution data can be obtained in various ways: Optionally, a high-definition camera array is installed on the top of the tunnel, the vehicle type is identified through computer vision algorithms and its movement trajectory is tracked, the vehicle speed is calculated in combination with the data of the laser ranging sensor, and a group of pollutant concentration sensors are arranged every 50 meters longitudinally in the tunnel; Optionally, vehicle detection coils are laid on the tunnel pavement, the vehicle information is obtained in cooperation with the license plate recognition system, the vehicle speed is measured using ultrasonic sensors, and concentration detection devices are installed at the grid point positions every 10 meters transversely and every 100 meters longitudinally in the tunnel. It can be understood that other combinations of sensors can also be used to achieve data collection, which is not limited here).

[0038] S102. Determine the spatial generation area of pollutants according to the vehicle operation state information, and calculate the concentration gradient value between adjacent heights and the diffusion rate value within a continuous time period according to the pollutant concentration data).

[0039] Among them, the spatial generation area of pollutants refers to the main pollutant generation positions determined according to the vehicle emission characteristics. The concentration gradient value represents the degree of difference in pollutant concentration between two adjacent height measurement points, and the diffusion rate value is used to represent the diffusion change speed of pollutants within a continuous time period).

[0040] Specifically, this step is executed after obtaining the vehicle operation status information and pollutant concentration distribution data. First, according to the emission coefficients and real-time location distributions of vehicle types, combined with vehicle speed and quantity information, the pollutant generation intensity at each spatial location is calculated to determine the pollutant spatial generation area. Then, using the concentration data of measurement points at different heights, the concentration difference between adjacent measurement points is calculated and divided by the height interval to obtain the concentration gradient value, and the diffusion rate value is obtained by dividing the concentration change amount over consecutive time points by the time interval.

[0041] In some embodiments, the determination of pollutant spatial characteristics can be achieved in various ways: Optionally, a vehicle emission model is established, and parameters such as vehicle type, quantity, and vehicle speed are substituted into the model to calculate the pollutant generation intensity at each location, and the generation area is determined according to the intensity distribution. At the same time, a three-dimensional interpolation algorithm is used to calculate the concentration value at any height position and obtain the gradient and diffusion rate; Optionally, a machine learning model is trained based on historical data, the real-time vehicle operation status information is input to predict the pollutant generation area, and the concentration gradient and diffusion characteristics are calculated through spatio-temporal sequence analysis methods. It can be understood that other mathematical models or algorithms can also be used to determine the pollutant spatial characteristics, which are not limited here.

[0042] S103. According to the spatio-temporal distribution relationship of the pollutant spatial generation area, concentration gradient value, and diffusion rate value, determine the pollutant concentration change trend within each height range, and divide the tunnel space into multiple vertical control regions.

[0043] Among them, the spatio-temporal distribution relationship refers to the mutual correlation characteristics of the pollutant generation and diffusion processes in the spatial and temporal dimensions. The concentration change trend represents the change law and direction of pollutants within different height ranges. The vertical control region refers to a spatial range unit with similar pollutant distribution characteristics. The pollutant diffusion characteristic value is a comprehensive index that characterizes the pollutant diffusion ability and is obtained by coupling and calculating the concentration gradient value and diffusion rate value.

[0044] Specifically, this step is executed after obtaining the spatial distribution characteristics of pollutants. First, analyze the change law of the pollutant concentration at each measurement point over time, and combine the distribution characteristics of the pollutant spatial generation area to establish a spatio-temporal correlation model for pollutant diffusion. Then, based on this model, predict the pollutant concentration change trend within different height ranges, and merge the spatial regions with similar diffusion characteristics according to the similarity of the concentration change trend, and finally form several relatively independent vertical control regions.

[0045] In some embodiments, the vertical partitioning of the tunnel space can be achieved in various ways: Optionally, first calculate the time autocorrelation coefficient and the spatial cross-correlation coefficient of the pollutant concentration at each measurement point, then use the clustering analysis method to divide the measurement points with higher correlation into the same region, and finally further subdivide or merge the regions according to the fluctuation of the pollutant diffusion characteristic values within the region; Optionally, establish a spatio-temporal sequence prediction model based on deep learning, input historical monitoring data to train the model, use the trained model to predict the change trend of the pollutant concentration at each spatial position, divide the regions according to the similarity of the trends, and determine the final control region range through the boundary optimization algorithm. It can be understood that other data analysis or artificial intelligence methods can also be used to achieve the division of the vertical control region, which is not limited here.

[0046] In some embodiments, this step specifically includes the following steps: Obtain the pollutant concentration data at different heights within the pollutant spatial generation region, and perform a coupling calculation on the concentration gradient value between adjacent heights and the diffusion rate value at the corresponding height to obtain the pollutant diffusion characteristic value.

[0047] In this step, the pollutant spatial generation region refers to the spatial range where pollutants are mainly generated in the tunnel, usually including the vehicle exhaust emission region and the pollutant aggregation region. The pollutant concentration data refers to the content values of specific pollutants in the air collected at the monitoring points at different heights, and the unit is usually mg / m³. The concentration gradient value represents the degree of concentration difference between two adjacent height measurement points, and the calculation method is the concentration difference between two points divided by the height difference. The diffusion rate value reflects the diffusion change speed of pollutants in the vertical direction and is obtained through the change amount of the pollutant concentration at a certain height within a unit time. The pollutant diffusion characteristic value is obtained by performing a weighted sum of the concentration gradient value and the diffusion rate value, and is used to characterize the overall characteristics of pollutant diffusion in this region.

[0048] Divide the tunnel space into multiple temporary control regions according to the pollutant diffusion characteristic value, continuously collect the pollutant concentration data within the temporary control regions, and when the difference between the pollutant diffusion characteristic values of adjacent temporary control regions is less than the preset difference, merge the adjacent temporary control regions into a vertical control region.

[0049] In this step, specifically in implementation, first, a plurality of monitoring points at different heights are arranged in the pollutant generation area. For example, one monitoring point is arranged at 0.5 m, 1.5 m, 2.5 m, and 3.5 m above the ground respectively. The pollutant concentration data of each monitoring point is collected every 10 seconds. For two adjacent height points, calculate their concentration gradient values. For example, the gradient value between 1.5 m and 0.5 m is (C1.5 - C0.5) / 1, where C represents the concentration value at the corresponding height. At the same time, calculate the concentration change amount of each height point within three consecutive sampling periods to obtain the diffusion rate value. Multiply the concentration gradient value and the diffusion rate value by the weight coefficients (such as 0.6 and 0.4) respectively and then add them to obtain the diffusion characteristic value of this height interval. Repeat this calculation process for all adjacent height intervals to obtain the complete diffusion characteristic value distribution.

[0050] When the fluctuation range of the diffusion characteristic value of pollutants in the temporary control area is greater than the preset fluctuation threshold, divide the temporary control area into multiple vertical control areas; determine the boundary positions of the vertical control areas according to the pollutant concentration change trend between the vertical control areas.

[0051] In this step, according to the calculated diffusion characteristic values, initially divide the space into temporary control areas according to the preset threshold (such as the diffusion characteristic values differ by 0.5). Continuously collect the pollutant data in each temporary area and calculate the diffusion characteristic values. When it is found that the difference between the characteristic values of two adjacent temporary areas is less than the preset difference (such as 0.3), merge these two areas into one vertical control area. On the contrary, when the diffusion characteristic value in a certain temporary area fluctuates beyond the preset threshold (such as the standard deviation is greater than 0.8) within multiple consecutive sampling periods, further divide this area into multiple vertical control areas. Finally, determine the boundary of the final vertical control area by analyzing the change trend of the pollutant concentration between regions, such as the position of the concentration mutation point or the significant gradient change. After the boundary is determined, continuously monitor the diffusion characteristic values of each area during operation to maintain the dynamic adjustment ability of the area division.

[0052] S104. Set the operating parameters of the jet fans in each area according to the pollutant distribution characteristics of the vertical control area. According to the preset jet angle adjustment range and adjustment step, and the jet speed adjustment range and adjustment step, set the initial operating parameters of the jet fans in each area according to the deviation between the pollutant concentration and the preset threshold.

[0053] Among them, the pollutant distribution characteristic refers to the spatial distribution pattern and change characteristics of pollutants in each vertical control area. The operating parameters of the jet fans include two key control quantities, namely the jet angle and the jet speed. The preset adjustment range represents the maximum and minimum limits within which the parameters can be adjusted. The adjustment step is the minimum change amount for each adjustment. The preset threshold is used to represent the target control value of the pollutant concentration.

[0054] Specifically, this step is executed after the vertical control area is divided. First, analyze the spatial distribution characteristics of pollutants in each area, including the uniformity of concentration distribution, change periodicity, etc., and then determine the control strategy of the jet fan according to these characteristics. For the jet fan in each area, within the preset angle and speed adjustment range, according to the deviation between the pollutant concentration in this area and the preset threshold, calculate the initial values of the jet angle and speed according to the set adjustment step size, so as to achieve the accurate setting of the fan operation parameters.

[0055] In some embodiments, the setting of the jet fan operation parameters can be achieved in various ways: Optionally, first establish a relationship model between the pollutant concentration and the jet parameters, then calculate the target jet effect according to the deviation between the regional pollutant concentration and the preset threshold, and finally obtain the required jet angle and speed through model inversion, and gradually adjust them to the target value according to the adjustment step size; Optionally, establish a fuzzy rule base based on expert experience, use the pollutant concentration deviation as the input variable, obtain the adjustment amount of the jet angle and speed through fuzzy inference, and generate the final operation parameters according to the adjustment step size constraint. It can be understood that other control algorithms can also be used to optimize the setting of the jet fan operation parameters, which are not limited here.

[0056] S105. Real-time monitor the pollutant concentration distribution characteristics in each vertical control area. When it is detected that the concentration in the target area exceeds the preset concentration threshold, within the adjustment range of the jet angle and speed of the jet fan, adjust the operation parameters of the jet fans in the target area and the adjacent areas to the preset operation parameters according to the set step size, and set the lighting parameters of the lighting equipment in the vertical control area according to the pollutant concentration distribution characteristics.

[0057] Among them, the pollutant concentration distribution characteristics refer to the spatial distribution pattern and time variation law of the pollutant concentration in each vertical control area. The target area refers to the vertical control area that needs to be focused on controlling currently. The preset concentration threshold refers to the allowable upper limit value of the pollutant concentration. The preset operation parameters include the optimal working state parameter combination of the jet fan and the optimal lighting parameter combination of the lighting equipment in each vertical control area. The main control fan group refers to the set of jet fans that play a major role in controlling the pollutants in the target area. The coordinated fan group represents the set of other jet fans that cooperate with the main control fan group. The dominant propagation direction refers to the main diffusion direction of the pollutants in space.

[0058] Specifically, this step is continuously executed after the initial operating parameters of the jet fans and lighting equipment are set. The system collects pollutant concentration data in real time through a sensor network distributed in each vertical control area. When the pollutant concentration in a certain area is detected to exceed the preset threshold, that area is identified as the target area. Subsequently, the spatial distribution characteristics and propagation trends of pollutants in the target area are analyzed to determine the dominant propagation direction, and based on this, the jet fans in the target area are divided into a main control fan group and a collaborative fan group. According to the degree of pollutant exceeding the standard, the jet angle and speed of the main control fan group are gradually adjusted within the preset adjustment range. If the pollutant concentration decline rate does not meet the requirements, the collaborative fan group is started for collaborative control. At the same time, considering that pollutants may spread to adjacent areas, the system will also correspondingly adjust the operating parameters of the jet fans in adjacent areas. For the lighting control of the vertical control area, the system sets lighting parameters according to the pollutant concentration distribution characteristics of each area in accordance with the regional height gradient, realizing a vertical gradient of lighting intensity, so as to ensure the lighting requirements of different height areas and improve driving safety.

[0059] In some embodiments, the dynamic adjustment of environmental parameters can be achieved in various ways: Optionally, first establish a control model based on deep reinforcement learning, use the pollutant concentration in each vertical control area as the state input, and the regional environmental control parameters as the action output, and continuously optimize the control strategy through online learning to achieve precise control of pollutants and accurate adjustment of lighting; the model first evaluates the effects of various control actions in the current state, then selects the optimal action to execute, and finally updates the control strategy according to the execution effect, continuously cycling and optimizing; Optionally, construct an adaptive control system based on model prediction, predict the change trend of pollutant concentration through rolling horizon prediction, and optimize the operating parameters of various devices in real time. The system first establishes a prediction model based on historical data, then designs an optimal control sequence according to the prediction results, and finally continuously optimizes the control effect through feedback correction. It can be understood that other intelligent control methods can also be used to achieve real-time optimization of environmental parameters, which are not limited here.

[0060] In some embodiments, this step specifically includes the following steps: Obtain the pollutant concentration data of multiple monitoring points in each vertical control area, calculate the deviation degree between the pollutant concentration of each monitoring point and the preset concentration threshold, and determine the vertical control area with the largest deviation degree as the target area.

[0061] In this step, the vertical control area refers to the tunnel space management unit divided according to the pollutant distribution characteristics, and each unit has relatively independent pollutant control requirements. The monitoring point refers to the sensor node arranged in each area for collecting pollutant concentration data. The preset concentration threshold refers to the pollutant concentration limit set according to the air quality standard. The deviation degree represents the difference between the measured concentration value and the threshold, and is obtained by subtracting the threshold from the measured value and taking the absolute value. The target area refers to the vertical control area with the most serious pollutant exceeding standard degree and requiring priority treatment.

[0062] In specific implementation, in each vertical control area, monitoring points are set according to the grid layout in the height and horizontal directions. Nine monitoring points are arranged at different heights (such as 0.5m, 1.5m, 2.5m) and different horizontal positions (such as left, middle, right) in each area to form a 3×3 monitoring network. The system collects the pollutant concentration data of each monitoring point every 5 seconds, and compares the collected data with the preset concentration threshold (such as the CO concentration of 35mg / m³). The calculation method is: deviation value = |measured concentration value - preset threshold|. For each vertical control area, the maximum value of the deviation values of all monitoring points in the area is taken as the deviation degree of the area. By comparing the deviation degrees of all vertical control areas, the area with the largest deviation degree is determined as the target area.

[0063] According to the spatial distribution positions and pollutant concentration data of each monitoring point in the target area, determine the main propagation direction of abnormal pollutant concentration.

[0064] In this step, the main propagation direction refers to the main direction of pollutant diffusion in space, which is determined by analyzing the concentration distribution gradient. The spatial distribution position refers to the three-dimensional coordinate position of the monitoring point in the target area.

[0065] In specific implementation, first establish a three-dimensional coordinate system in the target area, record the position coordinates (x, y, z) and corresponding concentration values of each monitoring point. Calculate the concentration gradient vector between adjacent monitoring points. The direction of the gradient vector points to the point with a higher concentration value, and the magnitude is the concentration difference between the two points divided by the distance. Divide the target area into 8 direction sectors (north, northeast, east, southeast, south, southwest, west, northwest), and count the concentration gradient vectors in each sector. For each sector, calculate the composite vector of all gradient vectors in the area. Compare the magnitudes of the composite vectors of each sector, and the sector direction where the maximum composite vector is located is the main propagation direction.

[0066] Based on the main propagation direction, divide the jet fans in the target area into the main control fan group and the collaborative fan group, and adjust the jet angle and jet speed of the main control fan group.

[0067] In this step, the main control fan group refers to the set of jet fans that play a major role in pollutant control. The collaborative fan group refers to other jet fans that cooperate with the main control fan group. The jet angle refers to the angle between the air outlet direction of the fan and the horizontal plane. The jet velocity refers to the air flow velocity at the air outlet of the fan.

[0068] In specific implementation, according to the determined dominant propagation direction, calculate the angle between the position of each jet fan in the target area and the propagation direction. Classify the fans with an angle less than 30° into the main control fan group, and the remaining fans into the collaborative fan group. For the fans in the main control fan group, adjust the jet angle to be between 60° and 90° with the propagation direction to ensure that the jet direction can effectively block the pollutant propagation. At the same time, increase the jet velocity of the main control fan group to 80% of the rated value to enhance the air flow control intensity.

[0069] When the pollutant concentration decline rate in the target area is less than the preset decline rate, adjust the operating parameters of the collaborative fan group.

[0070] In this step, the pollutant concentration decline rate refers to the reduction amount of the pollutant concentration in the target area per unit time. The preset decline rate is the minimum concentration decline speed determined according to the control requirements.

[0071] In specific implementation, calculate the average concentration value of all monitoring points in the target area every 10 seconds, and calculate the concentration decline rate through two consecutive sampling data: decline rate = (previous average concentration - current average concentration) / sampling time interval. When the calculated decline rate is less than the preset value (such as 2 mg / m³ / min), activate the collaborative fan group. Adjust the jet angle of the collaborative fan group to form an angle of 60° - 120° with the main control fan group to construct an auxiliary air flow field. Set the jet velocity of the collaborative fan group to 60% of the rated value to assist the main control fan group in accelerating the pollutant diffusion.

[0072] Determine the area directly adjacent to the pollutant propagation path according to the dominant propagation direction, and adjust the operating parameters of the jet fans directly opposite to the main control fan group in the directly adjacent area.

[0073] In this step, the directly adjacent area refers to the vertical control area adjacent to the target area on the pollutant propagation path. The opposite jet fan refers to the fan in the adjacent area that is opposite to the jet direction of the main control fan group.

[0074] In specific implementation, based on the determined dominant propagation direction, adjacent regions intersecting the propagation path are identified. Among these regions, the fans opposite to the jet direction of the main control fan group are selected for adjustment. The jet angles of these fans are adjusted to be opposite to the jet direction of the main control fan group to form an opposing air flow and enhance the local ventilation effect. The jet speed of these fans is set to 70% of the rated value, and it cooperates with the main control fan group to form a closed control air flow field to enhance the diffusion effect of pollutants. Regularly monitor the change in pollutant concentration in the adjacent regions to ensure that pollutant accumulation in other regions will not be caused by enhanced local ventilation.

[0075] The following further and more specific process description of the method provided in this embodiment is given. Please refer to Figure 2 , which is another process schematic diagram of the tunnel traffic control method for multi-modal traffic variable analysis in the embodiment of the present application.

[0076] S201. Obtain the data of the laser ranging sensors on the tunnel wall, calculate the position deviation between the tunnel wall and the reference axis, and determine the curved section according to the position deviation.

[0077] Among them, the laser ranging sensor data represents the distance information of the tunnel wall obtained by the laser sensor, the reference axis refers to the central reference line determined during tunnel design, and the position deviation represents the vertical distance between the actual wall position and the reference axis.

[0078] A set of laser ranging sensors is arranged along the longitudinal direction of the tunnel wall every 10 meters, and each set contains 4 sensors distributed at different positions in the tunnel cross-section. The sensor emits a laser beam to irradiate the wall and receives the reflected signal, and the wall distance value is calculated by the time-of-flight method. The obtained distance data is compared with the tunnel reference axis, and the position deviation of each measurement point is calculated. When the position deviations of multiple consecutive measurement points show regular changes, it indicates that there is a curve in this section of the tunnel. Specifically, the start and end positions of the curve are determined by analyzing the change trend of the position deviation: when the position deviation starts to continuously increase and the change rate exceeds 0.05 m / m, it is determined as the starting point of the curve; when the position deviation tends to be stable or starts to decrease, it is determined as the ending point of the curve.

[0079] S202. Collect the vehicle speed data in the curved section, and divide the curved section into a deceleration sub-region, a constant-speed sub-region, and an acceleration sub-region according to the vehicle speed data.

[0080] Among them, the vehicle speed data represents the real-time driving speed of the vehicle in the curved section. The deceleration sub-region refers to the entrance section of the curve where the vehicle needs to reduce its speed, the constant-speed sub-region refers to the middle section of the curve where the vehicle maintains a stable speed, and the acceleration sub-region refers to the exit section of the curve where the vehicle can increase its speed.

[0081] Install multiple speed measurement devices in the determined bend area, including geomagnetic detectors and radar speedometers, to collect the speed data of passing vehicles in real time. By analyzing the change characteristics of the vehicle speed data, the bend area is divided into three sub-areas: when the vehicle speed decrease rate is greater than 0.5 m / s² and the duration exceeds 3 seconds, it is divided into a deceleration sub-area; when the vehicle speed change rate fluctuates within the range of ±0.2 m / s², it is divided into a constant speed sub-area; when the vehicle speed increase rate is greater than 0.3 m / s² and the duration exceeds 2 seconds, it is divided into an acceleration sub-area. The boundaries of each sub-area are determined by the mutation points of the vehicle speed change rate.

[0082] S203. Detect the braking times of vehicles in the deceleration sub-area, and adjust the air supply frequency of the jet fan according to the braking times.

[0083] Among them, the braking times refer to the cumulative number of times that vehicles take braking deceleration in the deceleration sub-area, and the air supply frequency refers to the working cycle of the jet fan, including the air supply duration and the interval time.

[0084] Install an infrared sensor and a pressure sensor in the deceleration sub-area to detect the lighting of the vehicle brake lights and the change of tire pressure, and count the braking times of vehicles per unit time. When the braking times detected within 5 minutes exceed the preset threshold (such as 20 times), extend the air supply duration of the jet fan from the standard 60 seconds to 90 seconds, shorten the air supply interval time from 120 seconds to 90 seconds, and increase the air supply frequency. When the braking times drop below the threshold, restore the standard air supply frequency. The adjustment of the air supply frequency is realized by a programmable controller to ensure enhanced ventilation when vehicles brake frequently.

[0085] S204. Obtain the average vehicle speeds of the inner lane and the outer lane in the bend area, calculate the difference in the average vehicle speeds of the inner and outer lanes. When the difference in the average vehicle speeds is greater than the first preset threshold, set the air supply interval time of the inner jet fan to the first preset time.

[0086] Among them, the inner lane refers to the lane adjacent to the inner wall surface of the tunnel, the outer lane refers to the lane close to the outer wall surface of the tunnel, the average vehicle speed represents the average value of the speeds of all vehicles passing through this lane within 5 minutes, the difference in the average vehicle speeds represents the absolute difference in the average vehicle speeds of the inner and outer lanes, the first preset threshold is 10 km / h, the first preset time is 60 seconds, the inner jet fan refers to the jet device installed on the inner wall surface of the tunnel for local ventilation, and the air supply interval time represents the time interval between two air supply operations.

[0087] Three sets of speed measurement devices are arranged on the inner and outer lanes in the curved section, including geomagnetic detectors and Doppler radar speedometers, to achieve dual speed detection. The geomagnetic detectors are buried under the road surface to obtain the vehicle speed by detecting the magnetic field changes when the vehicle passes through; the Doppler radar speedometers are installed on the top of the tunnel to measure the vehicle speed using the Doppler effect. Each speed measurement point records the vehicle speed value every 10 seconds and stores it in the data cache. When the data volume reaches 30, the outliers are removed and the average value is calculated. The average values of the three speed measurement points are averaged again to obtain the final average vehicle speed of the lane. The average speed difference is calculated by "average vehicle speed of the inner lane - average vehicle speed of the outer lane". When the difference is greater than 10 km / h, it indicates that the vehicle speed difference between the inner and outer lanes is relatively large, and the vehicle speed of the inner lane is significantly higher than that of the outer lane. In this case, the pollutant generation intensity and diffusion characteristics in the inner area change significantly. At this time, it is necessary to strengthen the ventilation control in the inner area, and adjust the air supply interval time of the inner jet fan from the default 120 seconds to 60 seconds, that is, double the air supply frequency. The adjustment of the air supply interval time is executed by a programmable controller. The controller receives the vehicle speed difference signal and immediately triggers the update of the timer parameter when detecting that the difference exceeds the threshold, ensuring that the ventilation control responds to the vehicle speed change in a timely manner.

[0088] S205. When the average speed difference is less than the first preset threshold, set the air supply interval time of the inner jet fan to the second preset time, where the first preset time is less than the second preset time.

[0089] Among them, the second preset time is 120 seconds, which is greater than the first preset time of 60 seconds, reflecting the differential setting of the jet fan operation parameters under different working conditions. The adjustment of the air supply interval time is dynamically controlled based on the change of the vehicle speed difference to meet the ventilation requirements under different working conditions.

[0090] This step forms a complete control logic closed-loop with step S204. Based on the real-time calculated average speed difference, when the difference is less than 10 km / h, it indicates that the vehicle speeds of the inner and outer lanes are relatively balanced, the pollutant generation rate in the inner area tends to be stable, and the local ventilation demand decreases. At this time, the air supply interval time of the inner jet fan is restored from 60 seconds to 120 seconds, appropriately reducing the air supply frequency to save energy. The specific implementation process is as follows: the control system continuously monitors the change trend of the vehicle speed difference. When it detects that the difference changes from greater than the threshold to less than the threshold and lasts for more than 1 minute, it sends an update instruction to the jet fan controller. After receiving the instruction, the controller waits for the current air supply cycle to complete, and then updates the timer parameter to 120 seconds. During this period, the system continues to monitor the vehicle speed difference. If the difference exceeds the threshold again, the current control process is immediately interrupted and the control strategy in step S204 is executed. The entire adjustment process realizes the smooth switching of the jet fan operation parameters, avoiding the impact on the system caused by frequent parameter changes.

[0091] S206. Collect the air quality data, light intensity data, and wind speed data within each vertical control area.

[0092] Among them, the air quality data includes the concentration values of pollutants such as CO, NO2, PM10, and PM2.5, which are detected using professional gas analyzers and particulate monitors. The light intensity data represents the illuminance value formed by the superposition of natural light and artificial light in the tunnel and is measured by a high-precision illuminometer. The wind speed data includes two parameters, the air flow velocity and direction, which are monitored in real time using an ultrasonic anemometer. The collection of these environmental parameters provides data support for subsequent ventilation control decisions.

[0093] Set up environmental monitoring stations in each vertical control area, equipped with a multi-parameter air quality analysis system, a distributed light monitoring network, and an intelligent wind speed monitoring device. The air quality analysis system includes an electrochemical sensor array for detecting the CO concentration (accuracy 0.1 ppm) and the NO2 concentration (accuracy 1 μg / m³); a laser scattering particulate monitor for measuring the PM10 and PM2.5 concentrations (accuracy 1 μg / m³). The light monitoring network consists of multiple high-precision illuminometers with a measurement range of 0 - 20000 lux and a resolution of 1 lux, forming an illuminance monitoring grid within the area. The ultrasonic anemometer uses a four-channel ultrasonic transducer with a measurement range of 0 - 30 m / s, an accuracy of 0.1 m / s, and outputs the wind direction angle (accuracy 1°) at the same time. All sensors use an industrial-grade 4 - 20 mA signal output and are connected to the data acquisition unit through the RS485 bus. The data acquisition unit executes a sampling frequency of 100 Hz, performs digital filtering, temperature compensation, and zero calibration on the raw data, and then outputs the processed environmental parameter data at a preset time interval (CO / NO2 every 30 seconds, PM every 1 minute, illuminance every 1 minute, wind speed every 10 seconds). After outlier detection and data smoothing processing, these data are integrated to form the environmental state data set of the area, which is used to support the formulation of subsequent ventilation control strategies.

[0094] S207. Calculate the deviation value between the air quality data and the historical data of the same period; when the deviation value is greater than the first preset deviation threshold, obtain the wind speed change trend and air flow direction data of the target area.

[0095] Among them, the historical data of the same period refers to the average value of the air quality data in the same time period within the past 30 days. The deviation value represents the degree of difference between the current air quality data and the historical data of the same period. The first preset deviation threshold is set to 20%. The wind speed change trend includes the change rate and direction of the wind speed over time, and the air flow direction data indicates the angular information of the air flow movement.

[0096] The specific implementation process of this step is as follows: First, retrieve the air quality data within the same time period (15 minutes before and after the same time point) in the past 30 days from the database, and calculate the historical average of pollutant concentrations such as CO and NO2. Compare the currently real-time monitored air quality data with the historical average, and calculate the deviation percentage through the formula "|(current value - historical average) / historical average|×100%". When the deviation value of any pollutant exceeds 20%, start the wind field monitoring program, call the ultrasonic anemometer array deployed in the target area (one measuring point every 10 meters), and collect the wind speed data for 5 consecutive minutes. Calculate the wind speed change rate by dividing the wind speed difference between adjacent time points by the time interval. When the wind speed change rates of more than 3 consecutive measuring points have the same sign, it is determined as the wind speed change trend. At the same time, record the air flow direction angle of each measuring point, and calculate the dominant air flow direction in the area through vector decomposition and synthesis.

[0097] S208. Correlate and calculate the wind speed change trend and air flow direction data with the pollutant concentration change trend to determine the pollutant diffusion path.

[0098] Among them, the correlation calculation refers to the process of correlation analysis based on multi-parameter time series data. The pollutant concentration change trend represents the change characteristics of pollutant concentration over time, and the pollutant diffusion path indicates the main propagation channels of pollutants in space.

[0099] This step realizes the correlation analysis between the wind field characteristics and pollutant distribution through the data fusion method. First, convert the wind speed data and air flow direction data into velocity vectors to establish a regional wind field model. Conduct time series analysis on the pollutant concentration data of each monitoring point, and calculate the concentration change rate and change direction. Align the wind field data and concentration data on the same time scale, and calculate the time lag relationship between them through cross-correlation analysis. The specific calculation method is as follows: Select a time window of 10 minutes and a step size of 30 seconds, calculate the correlation coefficient between the wind speed change and the concentration change, and the time difference corresponding to the maximum correlation coefficient is the pollutant response time. Combine the wind field vector and the pollutant concentration gradient, and use the trajectory tracking algorithm to reconstruct the movement path of the pollutant. By solving the pollutant mass transport equation, obtain the main diffusion channels of pollutants in space.

[0100] S209. Divide multiple monitoring points in the vertical control area based on the pollutant diffusion path, and collect the pollutant concentration data of the monitoring points.

[0101] Among them, the monitoring point refers to the pollutant concentration detection position with a specific spatial location arranged in the vertical control area, and the pollutant concentration data includes the real-time concentration values of various pollutants.

[0102] On the determined pollutant diffusion path, the grid division method is used to determine the positions of monitoring points. First, a main monitoring point is set every 5 meters on the main axis of the diffusion path, and auxiliary monitoring points are set at 2 meters and 4 meters on both sides of the main axis to form a monitoring grid. For the turning points and convergence points of the diffusion path, the monitoring point density is increased to an interval of 2.5 meters. Multi-parameter air quality sensors are installed at each monitoring point, including electrochemical gas sensors and light scattering particulate sensors. The sampling frequency of the sensors is set to 2 Hz, and the concentration data after digital filtering is output every 30 seconds. The data of all monitoring points are transmitted to the data acquisition center in real time through the bus network. After data verification and calibration, the pollutant concentration distribution map of this area is generated to evaluate the accuracy of the diffusion path and the pollutant transmission characteristics.

[0103] S210. Generate ventilation control parameters according to the pollutant spatial generation area, concentration gradient value, diffusion rate value, and pollutant concentration data of the monitoring points.

[0104] Among them, the concentration gradient value represents the change in pollutant concentration per unit distance, the diffusion rate value indicates the diffusion change speed of pollutants in space, and the ventilation control parameters include control quantities such as air supply speed, air supply angle, and ventilation opening degree. The generation of ventilation control parameters uses a multi-parameter optimization algorithm to convert the monitoring data into specific ventilation equipment control instructions.

[0105] The specific process of generating ventilation control parameters is as follows: First, the pollutant spatial generation area is divided into three levels according to the concentration level, corresponding to different basic ventilation requirements. Calculate the spatial concentration gradient according to the formula "concentration gradient value = |difference in concentrations of adjacent monitoring points| / distance between monitoring points", and calculate the pollutant diffusion speed through "diffusion rate value = (current concentration - initial concentration) / time interval". Combine the real-time concentration data of the monitoring points to establish a ventilation demand model. The specific calculation method is: when the concentration gradient value is greater than 0.1 mg / m³ / m, the air supply speed increases by 0.5 m / s on the basis value; when the diffusion rate value is greater than 0.05 mg / m³ / s, the adjustment range of the air supply angle increases by 5 degrees; when the concentration of the monitoring point exceeds 20% of the threshold, the corresponding ventilation opening degree increases by 25%. The optimal combination of ventilation control parameters is obtained through iterative calculation, including the air supply speed (range 0 - 15 m / s), air supply angle (range 0 - 60 degrees), and opening degree (range 30% - 100%) of each ventilation opening.

[0106] S211. Generate lighting control parameters according to the light intensity data and pollutant concentration data.

[0107] Among them, the light intensity data represents the real-time illumination level inside the tunnel, and the lighting control parameters include control variables such as the number of lamps turned on, the power adjustment ratio, and the lighting zone settings. The generation of lighting control parameters needs to comprehensively consider two factors: light and air quality to achieve intelligent adjustment of the lighting system.

[0108] The generation process of the lighting control parameters is as follows: Obtain the illuminance distribution data of each area of the tunnel through the illuminance sensor network and calculate the deviation from the standard illuminance. At the same time, evaluate the impact of air quality on visibility based on the pollutant concentration data. When the PM10 concentration exceeds 150 μg / m³, the illuminance compensation value increases by 10%. Combining these two parts of data, adopt a segmented control strategy: when the measured illuminance is lower than 30% of the standard value, the lamp power is adjusted to 100%; when the illuminance deviation is between 10% - 30%, the power adjustment ratio is 60% - 90%; when the illuminance is close to the standard value, the power is maintained at 50%. For areas where high-concentration pollutants are detected, the power difference between the lamps in two adjacent lighting zones does not exceed 20% to ensure a gradual change in illuminance. The finally output lighting control parameters include the number of lamps turned on, the power percentage, and the gradual change time for each zone.

[0109] S212. Adjust the number of ventilation openings based on the ventilation control parameters and adjust the luminous power of the lighting equipment based on the lighting control parameters.

[0110] Among them, the number of ventilation openings represents the number of ventilation equipment in the working state, and the luminous power indicates the actual output power level of the lighting equipment. This step converts the generated control parameters into equipment execution instructions to achieve coordinated control of the ventilation and lighting systems.

[0111] The execution process of the control parameters adopts a distributed control method: First, the ventilation control system receives the ventilation control parameters and distributes control instructions to each ventilation equipment through the fieldbus network. For areas that need to increase the ventilation volume, start the standby ventilation openings one by one according to the principle of proximity, with a start interval of 15 seconds for each ventilation opening to avoid air flow turbulence. When the number of ventilation openings increases to the specified value, then adjust the working state of each ventilation opening according to the calculated air supply parameters. At the same time, the lighting control system adjusts the output power of the LED lamps according to the lighting control parameters. The power adjustment adopts the PWM control method with an adjustment accuracy of 1%, and the power gradual change time between adjacent zones is set to 30 seconds. The system monitors the operating status of the equipment in real time. When a device failure is detected, it automatically switches to the standby device to ensure the continuous execution of the control strategy.

[0112] S213. Collect the environmental parameters of each vertical control area, and the environmental parameters include light intensity, pollutant concentration, and vehicle density.

[0113] Among them, the light intensity represents the illuminance value in the tunnel, with the unit of lux, and is measured by an illuminance sensor; the pollutant concentration includes the contents of CO (mg / m³), NO2 (μg / m³), and PM10 (μg / m³), and is determined by a gas analyzer and a particulate matter monitor; the vehicle density represents the number of vehicles per unit length, with the unit of vehicles per 100 meters, and is obtained through video analysis and geomagnetic detection.

[0114] The environmental parameter collection adopts a multi-level monitoring network: monitoring points are arranged in a grid of 10 meters × 10 meters in each vertical control area. The light intensity is collected using a high-precision digital illuminometer, with a measurement range of 0 - 20000 lux, a resolution of 1 lux, and a sampling frequency of 1 Hz. The pollutant concentration is monitored using an electrochemical sensor array and a laser scattering particulate matter detector. The measurement accuracy of the CO concentration is 0.1 mg / m³, the measurement accuracy of the NO2 concentration is 1 μg / m³, and the measurement accuracy of the PM10 concentration is 1 μg / m³, with a sampling frequency of 2 Hz. The vehicle density data is obtained through a vehicle detection system, which integrates a video image processing unit and a geomagnetic induction coil. The video processing unit outputs vehicle count and position data every 0.1 seconds, and the geomagnetic coil triggers a count every time a vehicle passes by. All sensor data is transmitted to the data acquisition server through an industrial Ethernet, and an environmental parameter dataset is generated after data filtering and calibration.

[0115] S214. Determine the operating condition type of each vertical control area according to the environmental parameters.

[0116] Among them, the operating condition type represents the classification of the operating state of the vertical control area, which is divided based on the combined characteristics of the environmental parameters, including four types: normal operating condition, mild pollution operating condition, moderate pollution operating condition, and severe pollution operating condition.

[0117] The determination of the operating condition type adopts a multi-parameter threshold judgment method: First, standardize each environmental parameter to eliminate the influence of dimensions. The light intensity is divided into three levels: high illuminance (>200 lux), medium illuminance (50 - 200 lux), and low illuminance (<50 lux); the pollutant concentration calculates the over-standard multiple according to the standard limits of CO, NO2, and PM10 respectively; the vehicle density is divided into three levels: sparse (<15 vehicles per 100 meters), medium (15 - 30 vehicles per 100 meters), and crowded (>30 vehicles per 100 meters). Classify the parameter combination through a decision tree algorithm: When all parameters are within the normal range, it is determined as a normal operating condition; when any pollutant concentration exceeds the standard by less than 0.5 times and other parameters are normal, it is determined as a mild pollution operating condition; when the pollutant concentration exceeds the standard by 0.5 - 1 times or the vehicle density is in a crowded state, it is determined as a moderate pollution operating condition; when the pollutant concentration exceeds the standard by more than 1 time and the vehicle density is crowded, it is determined as a severe pollution operating condition.

[0118] S215. Obtain the initial control parameters of the jet fan based on the working condition type; collect the pollutant diffusion rate and vehicle speed data in the pollutant generation area of the space, and correct the initial control parameters according to the pollutant diffusion rate, concentration gradient value and vehicle speed data to obtain the corrected control parameters of the jet fan.

[0119] Among them, the initial control parameters include the basic operating parameters of the jet fan, such as jet angle, jet speed and operating time; the corrected control parameters refer to the final operating parameters after being corrected by real-time data. The parameter correction process takes into account the influence of pollutant diffusion characteristics and traffic flow conditions.

[0120] The execution process of this step is as follows: First, retrieve the corresponding initial control parameters from the parameter library according to the working condition type. Under normal working conditions, the jet angle is 30 degrees and the jet speed is 10 m / s; under light pollution conditions, the angle increases to 40 degrees and the speed increases to 12 m / s; under moderate pollution conditions, the angle is 50 degrees and the speed is 15 m / s; under heavy pollution conditions, the angle reaches 60 degrees and the speed is increased to 18 m / s. Then, perform parameter correction: calculate the pollutant diffusion rate. When the diffusion rate is greater than 0.1 mg / m³ / s, the jet speed is increased by 2 m / s on the basis of the initial value; calculate the concentration gradient value between adjacent measurement points. When the gradient value is greater than 0.2 mg / m³ / m, the jet angle is increased by 5 degrees; collect the vehicle speed data. When the average vehicle speed is lower than 30 km / h, the jet speed is increased by 1 m / s again. Superimpose these correction amounts on the initial parameters to obtain the final corrected control parameters. If the corrected parameters exceed the equipment limit value, take the maximum allowable value of this type of equipment.

[0121] S216. When the light intensity in the target area is lower than the first preset light threshold, increase the luminous power of the lighting equipment according to the corrected control parameters and adjust the speed limit value in the vertical control area.

[0122] Among them, the first preset light threshold is set to 100 lux, which represents the minimum illuminance standard required for safe driving. The luminous power refers to the actual output power of the lighting equipment, expressed as a percentage of the rated power. The speed limit value refers to the maximum allowable speed of vehicles in the vertical control area, with the unit of km / h. The corrected control parameters incorporate the comprehensive influence of environmental parameters and ventilation parameters.

[0123] The execution of this step adopts a linkage control method: when the light sensor detects that the light intensity in the target area is lower than 100 lux, the lighting compensation control is activated. The lighting power adjustment adopts a hierarchical control strategy. When the light intensity is between 80 - 100 lux, the lighting power is adjusted to 70% of the rated power; when the light intensity is between 60 - 80 lux, the power is adjusted to 85%; when the light intensity is lower than 60 lux, the power is adjusted to 100%. At the same time, the speed limit value is adjusted based on the change of lighting conditions: when the lighting power is 70%, the speed limit value is reduced by 10 km / h; when the lighting power is 85%, the speed limit value is reduced by 20 km / h; when the lighting power reaches 100%, the speed limit value is reduced by 30 km / h. The adjustment of the speed limit value is displayed through a variable message sign and a voice reminder is issued through the broadcast system. The system detects the light intensity every 30 seconds. When the light intensity returns above the threshold and lasts for 3 minutes, the lighting power and the speed limit value gradually return to the normal level, and the time interval of the recovery process is set to 5 minutes to ensure a smooth transition.

[0124] S217. When the vehicle density in the target area is greater than the preset density threshold, the air volume of the jet fan in the vertical control area is adjusted based on the control parameter correction value.

[0125] Among them, the preset density threshold is 25 vehicles per 100 meters, which represents the traffic flow density standard for strengthening ventilation control. The air volume of the jet fan refers to the air volume output by the jet fan per unit time, with the unit of m³ / h. This step correlates the vehicle density with the ventilation control parameters to achieve dynamic adjustment of the ventilation capacity.

[0126] The control process of this step is as follows: The vehicle density in the target area is monitored in real time through the vehicle detection system. When the detected vehicle density exceeds 25 vehicles per 100 meters, the air volume of the jet fan is adjusted based on the control parameter correction value. The air volume adjustment adopts a proportional control method: when the vehicle density is between 25 - 30 vehicles per 100 meters, the air volume is increased by 20% on the basis of the basic value; when the density is between 30 - 35 vehicles per 100 meters, the air volume is increased by 35%; when the density exceeds 35 vehicles per 100 meters, the air volume is increased by 50%. During the adjustment process, the difference in the air volume of adjacent jet fans does not exceed 15% to avoid local air flow turbulence. The system also monitors the power consumption and vibration data of the fan. When the power consumption exceeds 90% of the rated value or the vibration amplitude exceeds 2 mm, the increase in the air volume of this fan shall not exceed 30%. For the continuous high-density state (exceeding 10 minutes), the system issues a traffic restriction reminder through the tunnel entrance information board and implements interval release measures if necessary to control the vehicle density below the threshold. When the vehicle density drops below the threshold and lasts for 5 minutes, the air volume of the jet fan gradually decreases to the basic operating state at a rate of 5% per minute.

[0127] In some embodiments, the following steps may further be included: Collect multi-dimensional environmental status data in the vertical control area, including pollutant concentration data, light intensity data, temperature and humidity data, and wind speed and direction data; obtain traffic flow data, vehicle speed data, and vehicle type distribution data using an image recognition device and a vehicle detector; input the multi-dimensional environmental status data and vehicle data into a data processing model to generate an environmental status evaluation result; Based on the environmental status evaluation result, extract environmental characteristic parameters and traffic flow characteristic parameters, and establish an environmental change trend prediction model; calculate the change trend of environmental parameters in the future period according to the prediction model, and generate a traffic control instruction when the prediction result exceeds the preset threshold range; Adjust traffic rule parameters according to the traffic control instruction, including: when the predicted rising rate of pollutant concentration exceeds the first threshold, reduce the maximum speed limit value by a preset percentage and increase the minimum vehicle distance requirement; when the predicted traffic flow density exceeds the second threshold, start a lane control strategy and adjust the signal timing plan; when multiple environmental parameters deteriorate simultaneously, implement time-division traffic control; Collect traffic flow parameters after traffic rule adjustment, and calculate evaluation indicators including traffic efficiency and pollutant diffusion rate; when the evaluation indicators meet the preset conditions, restore traffic rule parameters at a preset time interval; when a traffic accident or other abnormal situation is detected, start an emergency control plan to ensure the rapid opening of the rescue channel first.

[0128] The tunnel traffic control system in the embodiment of the present invention application will be described from the perspective of hardware processing. Please refer to Figure 3 which is a schematic structural diagram of an entity device of the tunnel traffic control system in the embodiment of the present application.

[0129] It should be noted that Figure 3 The structure of the tunnel traffic control system shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0130] As Figure 3 shown, the tunnel traffic control system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage section 308 into the random access memory (RAM) 303, such as executing the methods described in the above embodiments. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other through a bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0131] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD), an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. The drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is installed on the drive 310 as needed so that a computer program read from it can be installed into the storage section 308 as needed.

[0132] Specifically, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 309, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are executed.

[0133] It should be noted that specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0134] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. Among them, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the block may occur in a different order from that marked in the accompanying drawings.

[0135] Specifically, the tunnel traffic control system of this embodiment includes a processor and a memory. A computer program is stored on the memory. When the computer program is executed by the processor, it implements the tunnel traffic control method for multi-modal traffic variable analysis provided in the above embodiment.

[0136] On the other hand, the present invention also provides a computer-readable storage medium. This storage medium may be included in the tunnel traffic control system described in the above embodiment; or it may exist alone without being assembled into the tunnel traffic control system. The above storage medium carries one or more computer programs. When the above one or more computer programs are executed by a processor of the tunnel traffic control system, the tunnel traffic control system implements the tunnel traffic control method for multi-modal traffic variable analysis provided in the above embodiment.

[0137] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the various embodiments of the present application.

[0138] As used in the above embodiments, depending on the context, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if detecting (the stated condition or event)" may be interpreted to mean "if determining..." or "in response to determining..." or "when detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)".

[0139] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by relevant hardware instructed by a computer program. This program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. The aforementioned storage media include: various media that can store program codes, such as ROM, random access memory (RAM), magnetic disks, or optical discs.

Claims

1. A tunnel traffic control method for multi-modal traffic variable analysis, characterized in that, Applied to a tunnel traffic control system, the method includes: Obtain the vehicle operation status information and pollutant concentration distribution data in the tunnel space, where the vehicle operation status information includes vehicle type, quantity, vehicle speed, and vehicle distribution location; Determine the spatial generation area of pollutants according to the vehicle operation status information, and calculate the concentration gradient value between adjacent heights and the diffusion rate value within a continuous time period according to the pollutant concentration data; Determine the pollutant concentration change trend within each height range according to the spatio-temporal distribution relationship of the pollutant spatial generation area, the concentration gradient value, and the diffusion rate value, and divide the tunnel space into multiple vertical control regions; Set the operation parameters of the jet fans in each region according to the pollutant distribution characteristics of the vertical control region. According to the preset jet angle adjustment range and adjustment step, and the jet speed adjustment range and adjustment step, set the initial operation parameters of the jet fans in each region according to the deviation between the pollutant concentration and the preset threshold; Real-time monitor the pollutant concentration distribution characteristics in each vertical control region. When it is detected that the concentration in the target region exceeds the preset concentration threshold, within the adjustment range of the jet angle and speed of the jet fan, adjust the operation parameters of the jet fans in the target region and the adjacent regions to the preset operation parameters according to the set step, and set the lighting parameters of the lighting equipment in the vertical control region according to the pollutant concentration distribution characteristics.

2. The method according to claim 1, characterized in that, The step of determining the pollutant concentration change trend within each height range according to the spatio-temporal distribution relationship of the pollutant spatial generation area, the concentration gradient value, and the diffusion rate value, and dividing the tunnel space into multiple vertical control regions specifically includes: Obtain the pollutant concentration data at different heights within the pollutant spatial generation area, and perform a coupling calculation on the concentration gradient value between adjacent heights and the diffusion rate value corresponding to the height to obtain a pollutant diffusion characteristic value; Divide the tunnel space into multiple temporary control regions according to the pollutant diffusion characteristic value, continuously collect the pollutant concentration data within the temporary control regions, and when the difference between the pollutant diffusion characteristic values of adjacent temporary control regions is less than the preset difference, merge the adjacent temporary control regions into a vertical control region; When the fluctuation range of the pollutant diffusion characteristic value within the temporary control region is greater than the preset fluctuation threshold, divide the temporary control region into multiple vertical control regions; determine the boundary positions of the vertical control regions according to the pollutant concentration change trend between the vertical control regions.

3. The method according to claim 1, characterized in that The step of real-time monitoring the pollutant concentration distribution characteristics in each vertical control region. When it is detected that the concentration in the target region exceeds the preset concentration threshold, within the adjustment range of the jet angle and speed of the jet fan, adjust the operation parameters of the jet fans in the target region and the adjacent regions to the preset operation parameters according to the set step specifically includes: Obtain the pollutant concentration data of multiple monitoring points within each vertical control region, calculate the deviation degree between the pollutant concentration of each monitoring point and the preset concentration threshold, and determine the vertical control region with the largest deviation degree as the target region; Determine the dominant propagation direction of abnormal pollutant concentration based on the spatial distribution positions of the monitoring points in the target area and the pollutant concentration data; Based on the dominant propagation direction, divide the jet fans in the target area into a main control fan group and a collaborative fan group, and adjust the jet angle and jet speed of the main control fan group; When the pollutant concentration decline rate in the target area is less than the preset decline rate, adjust the operating parameters of the collaborative fan group; Determine the area directly adjacent to the pollutant propagation path according to the dominant propagation direction, and adjust the operating parameters of the jet fans directly opposite to the main control fan group in the directly adjacent area; 4. The method according to claim 1, wherein After the step of, in real-time, monitoring the pollutant concentration distribution characteristics in each vertical control area, when it is detected that the concentration in the target area exceeds the preset concentration threshold, within the adjustment range of the jet angle and speed of the jet fan, adjusting the operating parameters of the jet fans in the target area and the adjacent area to the preset operating parameters according to the set step size, the method further includes: Obtain the data of the laser ranging sensor on the tunnel wall surface, calculate the position deviation between the tunnel wall surface and the reference axis, and determine the curve area according to the position deviation; Collect the vehicle speed data in the curve area, and divide the curve area into a deceleration sub-area, a constant speed sub-area, and an acceleration sub-area according to the vehicle speed data; Detect the braking times of the vehicles in the deceleration sub-area, and adjust the air supply frequency of the jet fan according to the braking times; Obtain the average vehicle speeds of the inner lane and the outer lane in the curve area, calculate the difference in the average vehicle speeds of the inner and outer lanes, and when the difference in the average vehicle speeds is greater than the first preset threshold, set the air supply interval time of the inner jet fan to the first preset time; 5. The method according to claim 4, characterized in that, After the step of, obtaining the average vehicle speeds of the inner lane and the outer lane in the curve area, calculating the difference in the average vehicle speeds of the inner and outer lanes, and when the difference in the average vehicle speeds is greater than the first preset threshold, setting the air supply interval time of the inner jet fan to the first preset time, the method further includes: When the difference in the average vehicle speeds is less than the first preset threshold, set the air supply interval time of the inner jet fan to the second preset time, where the first preset time is less than the second preset time; 6. The method according to claim 1, wherein After the step of, in real-time, monitoring the pollutant concentration distribution characteristics in each vertical control area, when it is detected that the concentration in the target area exceeds the preset concentration threshold, within the adjustment range of the jet angle and speed of the jet fan, adjusting the operating parameters of the jet fans in the target area and the adjacent area to the preset operating parameters according to the set step size, the method further includes: Collect the air quality data, light intensity data, and wind speed data in each vertical control area; Calculate the deviation value between the air quality data and the historical data in the same period; when the deviation value is greater than the first preset deviation threshold, obtain the wind speed change trend and air flow direction data of the target area; Perform correlation calculation on the wind speed change trend and the air flow direction data and the pollutant concentration change trend to determine the pollutant diffusion path; Divide a plurality of monitoring points in the vertical control area based on the pollutant diffusion path, and collect the pollutant concentration data of the monitoring points; Generate ventilation control parameters according to the pollutant spatial generation area, the concentration gradient value, the diffusion rate value, and the pollutant concentration data of the monitoring points; Generate lighting control parameters according to the light intensity data and the pollutant concentration data; Adjust the opening number of the ventilation openings based on the ventilation control parameters, and adjust the luminous power of the lighting equipment based on the lighting control parameters.

7. The method according to claim 1, wherein After the step of monitoring the pollutant concentration distribution characteristics in each of the vertical control areas in real time, and when it is detected that the concentration of the target area exceeds the preset concentration threshold, within the adjustment range of the jet angle and speed of the jet fan, adjusting the operating parameters of the jet fans in the target area and the adjacent areas to the preset operating parameters in accordance with a set step size, the method further includes: Collect the environmental parameters of each of the vertical control areas, where the environmental parameters include light intensity, pollutant concentration, and vehicle density; Determine the working condition type of each of the vertical control areas according to the environmental parameters; Obtain the initial value of the control parameter of the jet fan based on the working condition type; collect the pollutant diffusion rate and vehicle speed data of the pollutant spatial generation area, and correct the initial value of the control parameter according to the pollutant diffusion rate, the concentration gradient value, and the vehicle speed data to obtain the corrected value of the control parameter of the jet fan; When the light intensity of the target area is lower than the first preset light threshold, increase the luminous power of the lighting equipment according to the corrected value of the control parameter, and adjust the speed limit value of the vertical control area; When the vehicle density of the target area is greater than the preset density threshold, adjust the air supply volume of the jet fan in the vertical control area based on the corrected value of the control parameter.

8. A tunnel traffic control system, characterized in that, The tunnel traffic control system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the tunnel traffic control system to execute the method according to any one of claims 1-7.

9. A computer-readable storage medium, comprising instructions, characterized in that, When the instruction runs on the tunnel traffic control system, enabling the tunnel traffic control system to execute the method according to any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product runs on the tunnel traffic control system, enabling the tunnel traffic control system to execute the method according to any one of claims 1-7.

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