Flood prevention and early warning method, system and computer equipment for sunken long-distance traffic tunnels

Abstract

The present invention discloses a flood prevention and early warning method, system and computer equipment for a sunken long-distance traffic tunnel, wherein the method comprises S1, retrieving the travel time required for a vehicle to travel from the traffic light at the intersection closest to the tunnel to the tunnel entrance; S2, reading the time series of accumulated water levels to form a short-term prediction model for accumulated water in the long-distance traffic tunnel based on rainfall; S3, calculating the accumulated water height when a vehicle passes through position m in the tunnel according to the prediction model; S4, calculating the danger point; S5, calculating H max With H 设 The comparison is then made to execute the warning decision information, with the output signal of the warning decision information being "1" or "0." This invention facilitates vehicles to take detours in advance by linking control with the traffic lights closest to the tunnel entrance. Furthermore, considering the time required to travel through long traffic tunnels, the warning decision is triggered when the warning water level is reached at the most dangerous point in the tunnel, reducing the risk of vehicle submersion.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation technology, and in particular to a flood prevention and early warning method, system and computer equipment for a sunken long-distance traffic tunnel. Background Art

[0002] As global temperatures rise, extreme weather events become more frequent, and urban flooding is becoming increasingly common. Sunken traffic tunnels are particularly prone to urban flooding. When water accumulates in vehicles, it can easily prevent occupants from escaping in time, leading to fatalities.

[0003] There are currently two main methods of warning for sunken traffic tunnels. One is to set up a yellow water warning line before vehicles enter the tunnel (the height should be such that the lowest point submerges the exhaust pipe of a car). The second is to use an automated water level monitoring system, set up LED screens and broadcasts at the tunnel entrance to provide real-time water level warnings to prevent vehicles from entering the tunnel.

[0004] Although both of the above methods can solve the problem of early warning of water accumulation in sunken tunnels caused by low-intensity rainfall, the following problems still remain unresolved:

[0005] 1. Failure to reserve sufficient length or consider appropriate locations for vehicle detours. Existing flood prevention warning information for sunken tunnels, whether it is LED traffic warning lights, ground cordons, or voice broadcasts, is mostly located near the tunnel entrance. This makes it difficult for vehicles to detour when the tunnel is flooded and impassable, leading to dangerous situations such as submerging vehicles as the water level continues to rise;

[0006] 2. The time required for long-distance tunnel traversal is not taken into account. Existing traffic tunnels, especially long, sunken traffic tunnels, require a certain amount of time to pass through. When a vehicle enters the tunnel, the water level may not reach the warning level. However, during the long tunnel traversal, the water level may suddenly rise to the warning level, which may cause the vehicle to stall in the long tunnel. Summary of the Invention

[0007] The present invention provides a flood prevention and warning method, system and computer equipment for a sunken long-distance traffic tunnel that helps to improve the flood prevention safety of vehicles, and can solve at least one of the above-mentioned technical problems.

[0008] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0009] The flood prevention and early warning method for a sunken long-distance traffic tunnel includes the following steps:

[0010] S1, retrieve the time required for the vehicle to travel from the traffic light at the intersection closest to the tunnel to the tunnel entrance, record it as T0;

[0011] S2. Based on the T0 value and the reading of the water level time series, a short-term prediction model for water accumulation in long-distance traffic tunnels based on rainfall is formed;

[0012] S3. Based on the short-term prediction model for water accumulation in long-distance traffic tunnels, calculate the water accumulation height when a vehicle passes through point m in the tunnel, denoted as h. m，T ;

[0013] S4. Calculate the dangerous point H according to the water level at point m in S3. max =max(h m，T );

[0014] S5, H max With H 设 Compare to execute the early warning decision information, the output signal of the early warning decision information is "1" or "0", when H max ≥H 设 , output "1", when H max <H 设 , output "0".

[0015] Furthermore, in S2, the steps for building the short-term prediction model for water accumulation in long-distance traffic tunnels are as follows:

[0016] S21. Model selection: The autoregressive distributed lag model is used, which is as follows:

[0017]

[0018] in:

[0019] Y t is the accumulated water level at time t;

[0020] ε t is an independent and identically distributed error term;

[0021] β0, β i 、 is the estimated parameter;

[0022] p and q represent the hysteresis lengths of ponding water level and rainfall, respectively;

[0023] s represents the number of variables, which is 2 in this model, representing the rainfall on both sides of the long-distance traffic tunnel;

[0024] j = 1, 2, ...;

[0025] k = 1, 2, ...;

[0026] S22. Difference processing: Before modeling, the stationarity of the water level time series needs to be judged. The water level time series is judged through the trend chart. If it is judged to be a non-stationary series, a difference operation is required. The difference of formula (1) is converted to:

[0027]

[0028] The definition of the parameters in the formula is consistent with that in the above formula (1). After the conversion is completed, the sequence stationarity judgment is performed again;

[0029] S23, determining the lag length: If the accumulated water level time series is determined to be a stationary series in S23, the lag length needs to be determined. To predict the accumulated water levels corresponding to different positions of subsequent vehicles in the tunnel, the lag length is taken as the time required for the vehicle to depart from the traffic light at the intersection and reach the current corresponding position;

[0030] Specifically, a long-distance sunken traffic tunnel with a total length of l is divided into n equal parts. The tunnel entrance is set as the starting point of the horizontal coordinate and the starting point of the vertical coordinate is the surface elevation of the low-lying area. The ground elevation coordinate of point m is expressed as h m is the height difference between point m and the low-lying ground where the water level sensing component is located, m∈[0,n]. The average speed of vehicles passing through the tunnel is v, so the time required for vehicles to travel from the traffic light at the intersection to point m is T. m :

[0031]

[0032] S24. Model solution:

[0033]

[0034] Transform the above formula (4) into matrix form:

[0035] AX=Y (5)

[0036] In the above formula (5), the matrix A is 1, and The matrix formed is the matrix X with parameters β0, β i and Observation value ΔY n Column is Y;

[0037] The least squares method is used to solve the above formula (5):

[0038] X=(A T A) -1 A T Y (6)

[0039] After using historical data to obtain the parameter matrix X of equation (6), the predicted value of the water level difference ΔY can be obtained by substituting the previous data into equation (2). t , and then according to the following formula (7):

[0040] Y t =Y t-1 +ΔY t (7)

[0041] The predicted value for one period of time is calculated and used as the historical data of the subsequent time series to realize the water level prediction function.

[0042] Furthermore, in S3, the water level h when the vehicle passes through point m in the sunken long-distance traffic tunnel is m，T for:

[0043]

[0044] Furthermore, in said S4, H 设 The setting basis is the distance from the exhaust port of the car to the ground.

[0045] A flood prevention and warning system for a sunken long-distance traffic tunnel, applicable to the flood prevention and warning method for a sunken long-distance traffic tunnel, comprising a water condition monitoring module, a data transmission module, a warning decision module, and a warning execution module;

[0046] The water situation monitoring module includes a water accumulation monitoring unit and a rainfall monitoring unit. The water accumulation monitoring unit is used to monitor the water level information of the low-lying areas in the tunnel in real time. The rainfall monitoring unit is used to monitor the rainfall information of the tunnel environment in real time. The data transmission module is connected between the water situation monitoring module and the early warning decision module to establish data or signal transmission. The early warning decision module has a built-in algorithm unit containing the flood prevention and early warning method of the sunken long-distance traffic tunnel, which is used to analyze and process data or signals and form early warning decision information. The early warning execution module is connected to the early warning decision module to receive and execute the early warning decision information to perform flood prevention early warnings and confirm that vehicles detour in an orderly manner.

[0047] Furthermore, the water accumulation monitoring unit is arranged in a low-lying area in a sunken long-distance traffic tunnel, and includes at least a video sensing component, a water level sensing component and a power supply management component. The water level sensing component and the video sensing component are both connected to the data transmission module. The water level sensing component is used to sense water accumulation in the low-lying areas of the tunnel, and send the water accumulation situation to the data transmission module in real time. The video sensing component is used to take pictures and record to verify whether there is water accumulation, and send the verification situation to the data transmission module in real time. The power supply management component is connected to the video sensing component and the water level sensing component for safe power supply.

[0048] Furthermore, the early warning decision module includes at least a server, a cloud platform and a display device. The server is connected to the cloud platform through a dedicated network, and is used to process and execute the flood prevention and early warning method for sunken long-distance traffic tunnels. The cloud platform is used to observe and review the accumulated water level information collected by the water level sensing component. The display device is connected to the hard disk recorder via VGA, and is used to view the accumulated water level information collected by the video sensing component.

[0049] Furthermore, the warning execution module responds in real time after receiving the warning decision information output by the warning decision module, and the relevant response units are divided into three levels of warning according to the distance from the entrance of the sunken long-distance traffic tunnel, namely the first warning unit, the second warning unit and the third warning unit.

[0050] Furthermore, the first warning unit is a traffic light, which is set at a crossroad or T-junction near a tunnel entrance and includes at least a communication module, a control module, and a power module;

[0051] The communication module is connected to the early warning decision module and is used to receive decision instructions from the cloud platform. The control module is connected to the communication module and has two built-in traffic light control rules. The first set of traffic light control rules is normal traffic rules, and the red, yellow and green changes are changed according to fixed durations and frequencies. The second set of traffic light control rules is water accumulation warning rules, which keep detours and red lights on. The power module is used to safely power the first early warning unit;

[0052] After receiving the instruction from the cloud platform, the communication module drives the control module to respond in real time. When the output signal of the warning decision information is "0", the traffic light is controlled by the first set of traffic light control rules. When the output signal of the warning decision information is "1", the traffic light is controlled by the second set of traffic light control rules.

[0053] The second warning unit is a display screen installed above the tunnel entrance, establishing a communication connection with the cloud platform and responding to instructions. When the output signal of the warning decision information is "0", a sign indicating normal passage is displayed; when the output signal of the warning decision information is "1", a sign indicating no passage is displayed;

[0054] The third early warning unit uses a speaker, which is installed on the side wall inside the tunnel. It establishes a communication connection with the cloud platform and responds to instructions. When the output signal of the early warning decision information is "0", the broadcast is not triggered. When the output signal of the early warning decision information is "1", the broadcast is triggered to warn to leave.

[0055] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above-mentioned flood prevention and early warning method for a sunken long-distance traffic tunnel.

[0056] The beneficial effects of the present invention are embodied in:

[0057] 1. This invention proposes a flood prevention and warning method for sunken long-distance traffic tunnels. On the one hand, by linking control with the traffic lights closest to the tunnel entrance, vehicles can be detoured in advance to prevent them from being submerged. On the other hand, considering the time required to travel in a long-distance traffic tunnel, a warning decision is triggered when the warning water level is reached at the most dangerous point in the tunnel, thereby ensuring the safe exit of vehicles from the tunnel to the greatest extent possible and reducing the risk of vehicles being submerged.

[0058] 2. The present invention proposes a flood prevention and warning system for sunken long-distance traffic tunnels, which automatically monitors and collects the water level in the tunnel through a water situation monitoring module, and transmits the water level information in real time to the warning decision module through a data transmission module. The warning decision module analyzes the current water accumulation status in the tunnel according to an algorithm unit with a built-in flood prevention and warning method for sunken long-distance traffic tunnels, and provides it for remote monitoring and review, and obtains warning decision information at the same time. The warning execution module responds in real time according to the warning decision information. The relevant response units are divided into three levels of warning units according to the distance from the entrance of the sunken long-distance traffic tunnel, so as to improve the safety awareness and warning intensity of the safe evacuation of vehicles in the long-distance traffic tunnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The drawings described herein are used to provide further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute improper limitations on the present application.

[0060] Figure 1 This is a warning diagram of the yellow water accumulation warning line currently set up in the sunken traffic tunnel.

[0061] Figure 2 This is a schematic diagram of the automated water level monitoring system currently installed in sunken traffic tunnels.

[0062] Figure 3 It is a flow chart of a flood prevention and early warning method for a sunken long-distance traffic tunnel according to an embodiment of the present invention.

[0063] Figure 4 It is a schematic diagram of the process of building a short-term prediction model for water accumulation in a long-distance traffic tunnel according to an embodiment of the present invention.

[0064] Figure 5 It is a structural block diagram of a flood prevention and warning system for a sunken long-distance traffic tunnel according to an embodiment of the present invention.

[0065] Figure 6 This is a simulation diagram of the minute rainfall and the change of the lowest water level in an extreme rainfall case.

[0066] Figure 7 This is a simulation chart comparing the predicted value of waterlogging depth in rainfall data with the actual value in a certain extreme rainfall case.

[0067] Figure 8 It is a structural block diagram of a computer device according to an embodiment of the present invention.

[0068] The components in the accompanying drawings are marked as follows: 1. Water situation monitoring module; 2. Data transmission module; 3. Early warning decision module; 4. Early warning execution module; 5. Water accumulation monitoring unit; 6. Rainfall monitoring unit; 7. Server; 8. Cloud platform; 9. Display device; 10. First early warning unit; 11. Second early warning unit; 12. Third early warning unit. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. In the absence of conflict, the embodiments in this application and the features in the embodiments can be combined with each other. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0070] It should be noted that the "tunnel" appearing in the claims and description of this application refers to a sunken long-distance traffic tunnel. In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the meaning of "and / or" appearing throughout the text includes three parallel schemes. Taking "A and / or B" as an example, it includes scheme A, or scheme B, or schemes in which A and B are satisfied at the same time. In addition, "multiple" refers to more than two.

[0071] See also Figure 3 The embodiment of the present invention provides a flood prevention and warning method for a sunken long-distance traffic tunnel, comprising the following steps:

[0072] S1, retrieve the time required for the vehicle to travel from the traffic light at the intersection closest to the tunnel to the tunnel entrance, record it as T0;

[0073] S2. Based on the T0 value and the reading of the water level time series, a short-term prediction model for water accumulation in long-distance traffic tunnels based on rainfall is formed;

[0074] S3. Based on the short-term prediction model for water accumulation in long-distance traffic tunnels, calculate the water accumulation height when a vehicle passes through point m in the tunnel, denoted as h. m，T ;

[0075] S4. Calculate the dangerous point H according to the water level at point m in S3. max =max(h m，T );

[0076] S5, H max With H 设 Compare to execute the early warning decision information, the output signal of the early warning decision information is "1" or "0", when H max ≥H 设 , output "1", when H max <H 设 , output "0".

[0077] See also Figure 4 In this embodiment, in S2, the steps for building the short-term prediction model for water accumulation in long-distance traffic tunnels are as follows:

[0078] S21. Model selection: The autoregressive distributed lag model is used, which is as follows:

[0079]

[0080] Since rain gauges are installed at the front and rear entrances of the tunnel for real-time water level observation, rainfall forms water accumulation in the long-distance tunnel during the runoff generation and convergence process, which has obvious hysteresis. Therefore, the autoregressive distributed lag model is proposed in this application.

[0081] in:

[0082] Y t is the accumulated water level at time t;

[0083] ε t is an independent and identically distributed error term;

[0084] β0, β i 、 is the estimated parameter;

[0085] p and q represent the hysteresis lengths of ponding water level and rainfall, respectively;

[0086] s represents the number of variables, which is 2 in this model, representing the rainfall on both sides of the long-distance traffic tunnel;

[0087] j = 1, 2, ...;

[0088] k = 1, 2, ...;

[0089] S22. Difference processing: Before modeling, the stationarity of the water level time series needs to be judged. The water level time series is judged through the trend chart. If it is judged to be a non-stationary series, a difference operation is required. The difference of formula (1) is converted to:

[0090]

[0091] The definition of the parameters in the formula is consistent with that in the above formula (1). After the conversion is completed, the sequence stationarity judgment is performed again;

[0092] S23, determining the lag length: If the accumulated water level time series is determined to be a stationary series in S23, the lag length needs to be determined. To predict the accumulated water levels corresponding to different positions of subsequent vehicles in the tunnel, the lag length is taken as the time required for the vehicle to depart from the traffic light at the intersection and reach the current corresponding position;

[0093] Specifically, a long-distance sunken traffic tunnel with a total length of l is divided into n equal parts. The tunnel entrance is set as the starting point of the horizontal coordinate and the starting point of the vertical coordinate is the surface elevation of the low-lying area. The ground elevation coordinate of point m is expressed as h m is the height difference between point m and the low-lying ground where the water level sensing component is located, m∈[0,n]. The average speed of vehicles passing through the tunnel is v, so the time required for vehicles to travel from the traffic light at the intersection to point m is T. m :

[0094]

[0095] S24. Model solution:

[0096]

[0097] Transform the above formula (4) into matrix form:

[0098]

[0099] In the above formula (5), the matrix A is 1, and The matrix formed is the matrix X with parameters β0, β i and Observation value ΔY n Column is Y;

[0100] The least squares method is used to solve the above formula (5):

[0101] X=(A T A) -1A T Y (6)

[0102] After using historical data to obtain the parameter matrix X of equation (6), the predicted value of the water level difference ΔY can be obtained by substituting the previous data into equation (2). t , and then according to the following formula (7):

[0103] Y t =Y t-1 +ΔY t (7)

[0104] The predicted value for one period of time is calculated and used as the historical data of the subsequent time series to realize the water level prediction function.

[0105] In this embodiment, in S3, the water level h when the vehicle passes through point m in the sunken long-distance traffic tunnel is m，T for:

[0106]

[0107] In this embodiment, in S4, H 设 The setting basis is the distance from the exhaust port of the car to the ground, which is generally about 27cm.

[0108] See also Figure 5 , the embodiment of the present invention further provides a flood prevention and warning system for a sunken long-distance traffic tunnel, which is applicable to the flood prevention and warning method for a sunken long-distance traffic tunnel, and includes a water condition monitoring module 1, a data transmission module 2, a warning decision module 3 and a warning execution module 4;

[0109] The water situation monitoring module 1 includes a water accumulation monitoring unit 5 and a rainfall monitoring unit 6. The water accumulation monitoring unit 5 is used to monitor the water level information of the low-lying areas in the tunnel in real time. The rainfall monitoring unit 6 is used to monitor the rainfall information of the tunnel environment in real time. The data transmission module 2 is connected between the water situation monitoring module 1 and the early warning decision module 3, and is used to establish data or signal transmission. The early warning decision module 3 has a built-in algorithm unit containing the flood prevention and early warning method of the sunken long-distance traffic tunnel, which is used to analyze and process data or signals and form early warning decision information. The early warning execution module 4 is connected to the early warning decision module 3, and is used to receive and execute the early warning decision information to perform flood prevention early warnings and confirm that vehicles detour in an orderly manner.

[0110] In this application, considering the problem of signal difference in wireless transmission information in sunken long-distance traffic tunnels, the data transmission module 2 uses wired RS485 to transmit to the tunnel exit in the tunnel, and then converts it into 5G wireless transmission to the early warning decision module 3 through an RS485 to 5G converter.

[0111] See also Figure 5 In this embodiment, the water accumulation monitoring unit 5 is arranged in a low-lying area in a sunken long-distance traffic tunnel, and includes at least a video sensing component, a water level sensing component and a power supply management component. The water level sensing component and the video sensing component are both connected to the data transmission module 2. The water level sensing component is used to sense the water accumulation in the low-lying area of ​​the tunnel, and send the water accumulation situation to the data transmission module 2 in real time. The video sensing component is used to take pictures and record to verify whether there is water accumulation, and send the verification situation to the data transmission module 2 in real time. The power supply management component is connected to the video sensing component and the water level sensing component for safe power supply. The power supply management component is connected to an external power supply and can convert the 220V voltage into 24V voltage.

[0112] See also Figure 5 In this embodiment, the warning decision module 3 includes at least a server 7, a cloud platform 8, and a display device 9. The server 7 is connected to the cloud platform 8 via a dedicated network to process and execute the flood prevention and warning method for sunken long-distance traffic tunnels. The cloud platform 8 is used to observe and verify the accumulated water level information collected by the water level sensing component. The display device 9 is connected to a hard disk recorder via a VGA (Video Graphics Array) to view the accumulated water level information collected by the video sensing component. Users can observe tunnel accumulated water level data through a web platform on a remote network platform, such as a PC or mobile device, and can also verify it by viewing real-time on-site video.

[0113] See also Figure 5 In this embodiment, the warning execution module 4 responds in real time after receiving the warning decision information output by the warning decision module 3. The relevant response units are divided into three levels of warning according to the distance from the entrance of the sunken long-distance traffic tunnel, namely the first warning unit 10, the second warning unit 11 and the third warning unit 12.

[0114] See also Figure 5 In this embodiment, the first warning unit 10 uses a traffic light, which is set at a crossroad or T-junction near the tunnel entrance and includes at least a communication module, a control module and a power module;

[0115] The communication module can adopt 5G communication mode and be connected to the early warning decision module 3 to receive decision instructions from the cloud platform 8. The control module is connected to the communication module and has two sets of traffic light control rules built in. The first set of traffic light control rules is normal traffic rules, and the red, yellow and green changes are changed according to fixed duration and frequency. The second set of traffic light control rules is water accumulation warning rules, which keep detours and red lights on. The power module can adopt an external power supply mode to safely power the first early warning unit;

[0116] After receiving the instruction from the cloud platform 8, the communication module drives the control module to respond in real time. When the output signal of the warning decision information is "0", the traffic light is controlled by the first set of traffic light control rules. When the output signal of the warning decision information is "1", the traffic light is controlled by the second set of traffic light control rules.

[0117] The second warning unit 11 uses a display screen, such as an LED display screen, which is installed above the tunnel entrance, establishes a communication connection with the cloud platform 8 and responds to instructions. Specifically, the communication connection method can be connected to a router via a shielded network cable. When the output signal of the warning decision information is "0", a normal passage slogan, such as "Tunnel is free of water, normal passage" is displayed; when the output signal of the warning decision information is "1", a prohibition slogan, such as "Tunnel is at risk of flooding, prohibited passage" is displayed. The specific content of the slogan is not specifically limited in this application;

[0118] The third early warning unit 12 uses a speaker, such as a horn, which is installed on the inner side wall of the tunnel, establishes a communication connection with the cloud platform 8 and responds to instructions. Specifically, the communication leveling method can be selected to connect to the power amplifier through an audio cable and connect to the router through a shielded network cable. When the output signal of the early warning decision information is "0", the broadcast is not triggered. When the output signal of the early warning decision information is "1", the broadcast is triggered to warn to leave, such as "There is a risk of flooding in the tunnel, please leave quickly." The specific broadcast content is not specially limited in this application.

[0119] Below, this application will compare and analyze the method of the present invention with the traditional method in combination with simulation scenarios:

[0120] like Figure 6 As shown in the figure, taking an extreme rainfall event as an example, based on its minute rainfall and the changes in the lowest water level, it can be seen that the initial water discharge rate is greater than the water inflow rate, and the water level remains at 0 mm. Later, as the rainfall gradually increases and runoff gradually forms, the water inflow rate is greater than the drainage rate, and the water level gradually rises. Subsequently, the rainfall decreases, the drainage rate is greater than the water accumulation rate, and the water level begins to gradually decrease until it returns to 0 mm.

[0121] In this case, assume that a sunken long-distance traffic tunnel is approximately 3630 meters long, and the nearest road intersection is 364 meters from the tunnel entrance. 60 seconds before the start of rainfall, a car will enter the tunnel from the nearest intersection every 10 seconds. The speed limit inside the tunnel is 50 km / h. The center elevation difference along the tunnel is shown in Table 1 below:

[0122] Table 1. Center height difference of points along the line in a sunken long-distance traffic tunnel

[0123]

[0124]

[0125] According to this application early warning method, the lag time is calculated as shown in Table 2 below:

[0126] Table 2. Lag period length of internal points in a sunken long-distance traffic tunnel

[0127]

[0128] like Figure 7 As shown in FIG, based on the comparison between the predicted value of the water depth based on rainfall data and the actual value, it can be seen that the mean relative error (MRE) is 5.3%, which can be used in actual prediction.

[0129] In this extreme rainfall scenario, the traditional method and the method of the present invention were used to simulate vehicle stalling and detour respectively:

[0130] According to the traditional method: starting at the 65th minute, the water level at the most dangerous point exceeds 27cm, and vehicles are prohibited from entering the tunnel to prevent flooding. At this time, there are 27 vehicles in the tunnel, 18 of which are at risk of stalling. At the intersection between the tunnel and the tunnel entrance, there are 3 vehicles entering the tunnel. Closing the tunnel at this time does not facilitate detours.

[0131] According to the method of the present invention: at the 59th minute, according to the rainfall waterlogging simulation model, when the lag period is 4 minutes, vehicles passing through the adjacent road will enter the danger point at the 63rd minute and there is a risk of stalling. At this time, the traffic light is adjusted in time and a detour instruction is issued. At the 63rd minute, there are 9 vehicles in the tunnel, of which 0 vehicles are at risk of stalling, 0 vehicles have entered the tunnel between the adjacent tunnel intersection and the tunnel entrance, and the number of vehicles that have detoured in advance is 21;

[0132] Comparison shows that the method of the present invention can help more vehicles to detour in advance and has a better safety warning effect compared with the traditional method.

[0133] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the above-mentioned flood prevention and warning method for a sunken long-distance traffic tunnel.

[0134] See also Figure 8 An embodiment of the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above-mentioned flood prevention and warning method for a sunken long-distance traffic tunnel.

[0135] An embodiment of the present invention further provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute the steps of the above-mentioned flood prevention and early warning method for a sunken long-distance traffic tunnel.

[0136] It is understandable that the system, device and storage medium provided in the embodiments of the present invention correspond to the method provided in the embodiments of the present invention. The explanation, examples and beneficial effects of the relevant contents can refer to the corresponding parts of the above-mentioned sunken long-distance traffic tunnel flood prevention and warning method.

[0137] It should be noted that those skilled in the art will understand that all or part of the steps implemented in the embodiments of the present invention can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using hardware, it can be implemented in whole or in part in the form of purchased standard parts or modified parts. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiments of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)).

[0138] In summary, the present invention proposes a flood prevention and warning method for sunken long-distance traffic tunnels. On the one hand, through the linkage control with the traffic light closest to the tunnel entrance, it is convenient for vehicles to detour in advance to prevent vehicles from being submerged. On the other hand, considering the time required for driving in a long-distance traffic tunnel, the warning decision is triggered after the warning water level is reached at the most dangerous point in the tunnel, so as to maximize the protection of vehicles from the tunnel. Safe driving and reducing the risk of vehicles being submerged.

[0139] Furthermore, the present invention also proposes a flood prevention and warning system for a sunken long-distance traffic tunnel, which automatically monitors and collects the water level in the tunnel through a water condition monitoring module, and transmits the water level information in real time to a warning decision module through a data transmission module. The warning decision module analyzes the current water accumulation status in the tunnel according to an algorithm unit with a built-in flood prevention and warning method for a sunken long-distance traffic tunnel, and provides it for remote monitoring and review, and obtains warning decision information at the same time. The warning execution module responds in real time according to the warning decision information, and the relevant response units are divided into three levels of warning units according to the distance from the entrance of the sunken long-distance traffic tunnel, so as to improve the safety awareness and warning intensity of the safe evacuation of vehicles in the long-distance traffic tunnel.

[0140] It should be understood that the examples and implementation methods described herein are for illustrative purposes only and are not intended to limit the present invention. Those skilled in the art may make various modifications or changes based on them. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A flood prevention and early warning method for a sunken long-distance traffic tunnel, characterized in that: The following steps are involved: S1, retrieve the time required for the vehicle to travel from the traffic light at the intersection closest to the tunnel to the tunnel entrance, record it as T0; S2. Based on the T0 value and the reading of the water level time series, a short-term prediction model for water accumulation in long-distance traffic tunnels based on rainfall is formed; S3. Based on the short-term prediction model for water accumulation in long-distance traffic tunnels, calculate the water accumulation height when a vehicle passes through point m in the tunnel, denoted as h. m，T ; S4. Calculate the dangerous point H according to the water level at point m in S3. max =max(h m，T ); S5, H max With H 设 Compare to execute the early warning decision information, the output signal of the early warning decision information is "1" or "0", when H max ≥H 设 , output "1", when H max <H 设 , output "0"; In S2, the steps for building the short-term prediction model for water accumulation in long-distance traffic tunnels are as follows: S21. Model selection: The autoregressive distributed lag model is used, which is as follows: in: is the accumulated water level at time t; is an independent and identically distributed error term; 、 、 is the estimated parameter; 、 denote the hysteresis lengths of ponding water level and rainfall respectively; s represents the number of variables, which is 2 in this model, representing the rainfall on both sides of the long-distance traffic tunnel; j=1、2，…； k=1、2，…； S22. Difference processing: Before modeling, the stationarity of the water level time series needs to be judged. The water level time series is judged through the trend chart. If it is judged to be a non-stationary series, a difference operation is required. The difference of formula (1) is converted to: The definition of the parameters in the formula is consistent with that in the above formula (1). After the conversion is completed, the sequence stationarity judgment is performed again; S23. Determine the lag length: If the accumulated water level time series is determined to be a stationary series in S22, then determine the lag length. To predict the accumulated water levels corresponding to different positions of subsequent vehicles in the tunnel, the lag length is taken as the time required for the vehicle to depart from the traffic light at the intersection and reach the current corresponding position. Specifically, a long-distance sunken traffic tunnel with a total length of l is divided into n equal parts. The tunnel entrance is set as the starting point of the horizontal coordinate, and the starting point of the vertical coordinate is the surface elevation of the low-lying area. The ground elevation coordinate of point m is expressed as ( ), is the height difference between point m and the low-lying ground where the water level sensing component is located, m∈[0,n]. The average speed of vehicles passing through the tunnel is v, so the time required for vehicles to travel from the traffic light at the intersection to point m is T. m : ； S24. Model solution: Transform the above formula (4) into matrix form: In the above formula (5), the matrix A is 、 and ( ), then the matrix X is the parameter 、 and , observed values Column is Y; The least squares method is used to solve the above formula (5): After using historical data to obtain the parameter matrix X of the above formula (6), the predicted value of the water level difference can be obtained by substituting the previous data into formula (2): , and then according to the following formula (7): The predicted value for one period of time is calculated and used as the historical data of the subsequent time series to realize the water level prediction function.

2. The flood prevention and early warning method for a sunken long-distance traffic tunnel according to claim 1, characterized in that: In S3, the water level h when the vehicle passes through point m in the sunken long-distance traffic tunnel m，T for: 。 3. The flood prevention and early warning method for a sunken long-distance traffic tunnel according to claim 1, characterized in that: In the S4, H 设 The setting basis is the distance from the exhaust port of the car to the ground.

4. A flood prevention and warning system for a sunken long-distance traffic tunnel, applicable to the flood prevention and warning method for a sunken long-distance traffic tunnel as claimed in any one of claims 1 to 3, characterized in that: It includes a water situation monitoring module (1), a data transmission module (2), an early warning decision module (3) and an early warning execution module (4); The water situation monitoring module (1) includes a water accumulation monitoring unit (5) and a rainfall monitoring unit (6). The water accumulation monitoring unit (5) is used to monitor the water level information of the low-lying areas in the tunnel in real time. The rainfall monitoring unit (6) is used to monitor the rainfall information of the environment in which the tunnel is located in real time. The data transmission module (2) is connected between the water situation monitoring module (1) and the early warning decision module (3) and is used to establish data or signal transmission. The early warning decision module (3) is equipped with an algorithm unit containing the flood prevention and early warning method of the sunken long-distance traffic tunnel, which is used to analyze and process data or signals and form early warning decision information. The early warning execution module (4) is connected to the early warning decision module (3) and is used to receive and execute the early warning decision information to perform flood prevention and early warning and confirm that vehicles are detoured in an orderly manner.

5. The flood prevention and warning system for a sunken long-distance traffic tunnel according to claim 4, characterized in that: The water accumulation monitoring unit (5) is arranged in a low-lying area in a sunken long-distance traffic tunnel, and comprises at least a video sensing component, a water level sensing component and a power supply management component. The water level sensing component and the video sensing component are both connected to the data transmission module (2). The water level sensing component is used to sense water accumulation in the low-lying area of ​​the tunnel and send the water accumulation situation to the data transmission module (2) in real time. The video sensing component is used to take pictures and record to verify whether there is water accumulation, and send the verification situation to the data transmission module (2) in real time. The power supply management component is connected to the video sensing component and the water level sensing component for safe power supply.

6. The flood prevention and warning system for a sunken long-distance traffic tunnel according to claim 5, characterized in that: The early warning decision module (3) at least includes a server (7), a cloud platform (8) and a display device (9), wherein the server (7) is connected to the cloud platform (8) via a dedicated network and is used to process and execute the flood prevention early warning method for a sunken long-distance traffic tunnel, the cloud platform (8) is used to observe and review the accumulated water level information collected by the water level sensing component, and the display device (9) is connected to a hard disk recorder via a VGA and is used to view the accumulated water level information collected by the video sensing component.

7. The flood prevention and warning system for a sunken long-distance traffic tunnel according to claim 6, characterized in that: The warning execution module (4) responds in real time after receiving the warning decision information output by the warning decision module (3). The relevant response units are divided into three levels of warning according to the distance from the entrance of the sunken long-distance traffic tunnel, namely the first warning unit (10), the second warning unit (11) and the third warning unit (12).

8. The flood prevention and warning system for a sunken long-distance traffic tunnel according to claim 7, characterized in that: The first warning unit (10) is a traffic light, which is set at a crossroad or T-junction near a tunnel entrance and includes at least a communication module, a control module, and a power supply module; The communication module is connected to the early warning decision module (3) and is used to receive decision instructions from the cloud platform (8). The control module is connected to the communication module and has two sets of built-in traffic light control rules. The first set of traffic light control rules is a normal traffic rule, in which the red, yellow, and green lights change according to a fixed duration and frequency. The second set of traffic light control rules is a water accumulation early warning rule, in which detours are maintained and the red light is always on. The power module is used to safely power the first early warning unit. After receiving the instruction from the cloud platform (8), the communication module drives the control module to respond in real time. When the output signal of the warning decision information is "0", the traffic light is controlled by the first set of traffic light control rules. When the output signal of the warning decision information is "1", the traffic light is controlled by the second set of traffic light control rules. The second warning unit (11) uses a display screen, which is installed above the tunnel entrance, establishes a communication connection with the cloud platform (8) and responds to instructions. When the output signal of the warning decision information is "0", a slogan for normal passage is displayed, and when the output signal of the warning decision information is "1", a slogan for prohibiting passage is displayed; The third warning unit (12) is a loudspeaker installed on the inner side wall of the tunnel, establishing a communication connection with the cloud platform (8) and responding to instructions. When the output signal of the warning decision information is "0", the broadcast is not triggered. When the output signal of the warning decision information is "1", the broadcast is triggered to warn to leave.

9. A computer device, characterized in that: It includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the flood prevention and warning method for a sunken long-distance traffic tunnel as described in any one of claims 1 to 3.

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