Optimization method for rescue and evacuation structure of super-long highway tunnel

Abstract

The present application relates to the technical field of rescue evacuation structure optimization of highway tunnel, and discloses a rescue evacuation structure optimization method for super-long highway tunnel. The present application obtains tunnel traffic flow data, simulates evacuation personnel load under fire congestion working condition, obtains preset evacuation speed of different crowds under the influence of fire smoke, establishes a computer simulation model containing different horizontal passage spacing and width parameters, and calculates the required safety evacuation time, solves the problem that the existing super-long highway tunnel horizontal passage design relies on engineering experience or static specification, lacks quantitative evaluation for specific traffic characteristics and personnel composition, and the design scheme may have insufficient safety redundancy or high civil cost, realizes scientific and refined optimization of tunnel horizontal passage spacing and width, and significantly improves the safety and reliability of personnel evacuation under emergency conditions such as fire.

Description

Technical Field

[0001] This invention relates to the field of optimization technology for rescue and evacuation structures in highway tunnels, and particularly to a method for optimizing the rescue and evacuation structure of ultra-long highway tunnels. Background Technology

[0002] For existing extra-long highway tunnels, especially three-lane tunnels with high traffic flow, the design of the spacing and width of their cross passages (such as pedestrian cross passages) mainly relies on engineering experience or static specifications. There is a lack of a technical solution that can dynamically and accurately combine the actual traffic flow, personnel composition and the necessary safe evacuation time in emergency situations such as fires to conduct quantitative assessment and optimization. This may result in the design scheme not meeting safety requirements or causing redundancy in civil engineering. Summary of the Invention

[0003] In order to overcome the problems in the existing design of rescue and evacuation structures for ultra-long highway tunnels, such as reliance on engineering experience or static specifications leading to design schemes that may not meet safety requirements or cause redundancy in civil engineering, this invention provides an optimization method for the rescue and evacuation structure of ultra-long highway tunnels.

[0004] This invention provides a method for optimizing the rescue and evacuation structure of ultra-long highway tunnels, comprising:

[0005] Obtain traffic flow prediction data for the target tunnel, and based on the traffic flow prediction data, simulate and determine the evacuation load of the target tunnel under fire congestion conditions. Obtain the preset evacuation speed of different categories of people under the influence of fire smoke; A computer simulation model of the target tunnel is established, in which different cross passage spacing parameters and cross passage width parameters are set; The evacuation load and the preset evacuation speed are input into the computer simulation model to simulate and calculate the necessary safe evacuation time for personnel under each cross passage spacing parameter and each cross passage width parameter. Based on the required safe evacuation time for personnel, the parameter combination that meets the preset safe evacuation conditions is selected from the different cross passage spacing parameters and cross passage width parameters, and is used as the optimization result of the rescue and evacuation structure of the target tunnel.

[0006] According to a specific implementation, the step of simulating and determining the evacuation load of the target tunnel under fire congestion conditions based on the traffic flow prediction data in the above optimization method specifically includes: Based on the traffic flow prediction data, determine the traffic volume and vehicle type ratio of the target tunnel in the predicted year; The traffic volume and vehicle type ratio are input into the traffic micro-simulation model to simulate a traffic congestion scenario that occurs on the upstream road section when a fire occurs, and the number of each type of vehicle within the predetermined congestion length is obtained. The evacuation load is calculated based on the number of vehicles of each type and the preset passenger capacity of each type of vehicle.

[0007] According to a specific implementation, the step of obtaining the preset evacuation speed of different categories of people under the influence of fire smoke in the above optimization method specifically includes: Organize personnel evacuation tests, simulating vehicle obstacles and fire smoke environments along the test route; The evacuation time and evacuation distance of multiple groups of subjects of different ages and genders during the experiment were obtained; Based on the evacuation time and evacuation distance, the average evacuation speeds of young men, middle-aged men, elderly men, young women, middle-aged women, and elderly women are calculated under conditions of no smoke and smoke, respectively, and these speeds are used as the preset evacuation speeds.

[0008] According to a specific implementation, in the above optimization method, the preset evacuation speeds for different categories of people under the influence of fire smoke specifically include: 2.35 m / s for young men, 2.20 m / s for middle-aged men, 1.54 m / s for elderly men, 1.94 m / s for young women, 1.58 m / s for middle-aged women, and 1.05 m / s for elderly women.

[0009] According to a specific implementation method, in the above optimization method, the computer simulation model also sets up a working condition in which a fire occurs in the pedestrian cross passage, rendering it unusable. The simulation calculations specify the required safe evacuation time for personnel under each cross-aisle spacing parameter and each cross-aisle width parameter, including: The simulation calculation shows the necessary safe evacuation time for people when the adjacent cross passage is doubled in size to accommodate the evacuation of people under the condition that the pedestrian cross passage is unusable.

[0010] According to a specific implementation method, in the above optimization method, the computer simulation model is an individual-based personnel evacuation simulation model, in which the physical dimensions, initial positions, and preset evacuation speeds of each evacuated individual are defined.

[0011] According to a specific implementation, in the above optimization method, the necessary safe evacuation time for personnel includes detection alarm time, evacuation preparation time, and evacuation time. The detection alarm time is set to 60 seconds, and the evacuation preparation time is set to 120 seconds. The evacuation time was calculated using the computer simulation model.

[0012] According to a specific implementation, the step of selecting a parameter combination that meets the preset safe evacuation conditions from the different cross passage spacing parameters and cross passage width parameters based on the required safe evacuation time for personnel specifically includes: Obtain the available safe evacuation time for personnel in a fire situation; The parameter combination in which the required safe evacuation time for personnel is less than the available safe evacuation time for personnel is taken as the candidate combination to satisfy the preset safe evacuation condition; Based on the candidate combinations, determine the upper limit of the horizontal channel spacing parameter and the lower limit of the horizontal channel width parameter.

[0013] According to a specific implementation, the step of determining the upper limit value of the horizontal channel spacing parameter and the lower limit value of the horizontal channel width parameter based on the candidate combinations in the above optimization method specifically includes: Under the condition that the required safe evacuation time for personnel meets the safety requirements, preferably, the cross passage spacing parameter is set between 250 meters and 350 meters, and the cross passage width parameter is set between 2.0 meters and 2.5 meters.

[0014] According to a specific implementation method, in the above optimization method, the target tunnel is a three-lane, high-traffic, extra-long highway tunnel; the rescue and evacuation structure is a pedestrian cross passage set between the tunnel's driving lanes to connect two adjacent chambers.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention addresses the problems of existing ultra-long highway tunnel cross passage designs relying on engineering experience or static specifications, lacking quantitative assessments tailored to specific traffic characteristics and personnel composition, leading to insufficient safety redundancy or excessive civil engineering costs. It achieves scientific and refined optimization of tunnel cross passage spacing and width, significantly improving the safety and reliability of personnel evacuation in emergency situations such as fires. This effectively reduces the risk of mass casualties and unnecessary civil engineering costs caused by poor evacuation, while also enhancing the engineering design rationality and overall operational safety of rescue and evacuation structures. Furthermore, it provides a quantifiable decision-making basis for the safety design of ultra-long tunnel groups. By acquiring tunnel traffic flow data and simulating evacuation loads under fire congestion conditions, obtaining preset evacuation speeds for different groups under fire smoke influence, and establishing a computer simulation model including different cross passage spacing and width parameters and calculating the necessary safe evacuation time, this invention solves these problems. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for optimizing the rescue and evacuation structure of an ultra-long highway tunnel, as provided in an embodiment of the present invention. Detailed Implementation

[0017] The present invention will now be described in further detail with reference to specific embodiments. However, this should not be construed as limiting the scope of the above-described subject matter of the present invention to the following embodiments; all technologies implemented based on the content of the present invention fall within the scope of the present invention.

[0018] Unless otherwise specified, in the description of specific embodiments of the present invention, "several", "more than", or "a number of" represent at least two. The number can be any number, such as two, three, four, five, six, seven, eight, or nine, and can even exceed nine.

[0019] In the description of this invention, ultra-long highway tunnels refer to mountain highway tunnels exceeding 10 kilometers in length, designed with two-way or one-way multi-lane (especially three-lane) configurations. These tunnels are characterized by high traffic volume, complex vehicle composition, and enclosed, long and narrow interior spaces. In the event of an emergency such as a fire within the tunnel, vehicles and personnel upstream of the accident point will face severe smoke threats and must evacuate to adjacent safe chambers within a limited time via cross passages (especially pedestrian cross passages) located between the main tunnels. The spacing and width of these cross passages directly determine the necessary safe evacuation time for personnel and are core civil engineering parameters for ensuring tunnel operational safety. The optimization method provided by this invention aims to replace traditional experience-based design based on static specifications. By establishing a quantitative evaluation system that integrates long-term tunnel traffic volume, actual personnel composition, and dynamic fire simulation, it achieves refined design of cross passage structural parameters.

[0020] It should be noted that the method disclosed in this invention can be executed using one or more electronic devices with data storage and computing capabilities (such as servers, personal computers, or cloud computing platforms). This electronic device includes at least one or more processors and a memory coupled to the processors. The memory stores computer program instructions, which, when executed by the processor, enable the device to perform the steps of this invention. Furthermore, the simulation software involved in this invention (such as PTV-VISSIM for traffic flow simulation, FDS for fire smoke simulation, and Pathfinder for personnel evacuation simulation) are all commercially available software or open-source tools known in the art. Their specific internal algorithms are not the focus of this invention; rather, this invention proposes how to combine these tools according to a specific logical flow for the optimization decision-making of tunnel cross passage parameters.

[0021] The following will use a specific optimization example of the Qinling Tiantaishan Tunnel, an ultra-long highway tunnel, to provide a detailed explanation of the technical solution of this invention. Those skilled in the art should understand that this example is only for explaining the invention and not for limiting the scope of protection of this invention.

[0022] Please refer to Figure 1 The diagram illustrates a flowchart of an optimization method for the rescue and evacuation structure of an ultra-long highway tunnel according to an embodiment of the present invention. The method includes: Step 1: Obtain traffic flow prediction data for the target tunnel, and based on the traffic flow prediction data, simulate and determine the evacuation load of the target tunnel under fire congestion conditions.

[0023] According to the optimization method of the present invention, it is first necessary to obtain traffic flow prediction data for the target tunnel. This data typically originates from the tunnel's engineering feasibility study report or preliminary design documents. For example, the processor obtains the predicted traffic volume for the Qinling Tiantaishan Tunnel in a long-term target year (e.g., 2041): an average daily traffic volume of 57,291 vehicles (pcu / d), and determines the proportion of each vehicle type, including passenger cars (28.55%), buses (7.29%), light trucks (5.03%), medium trucks (14.22%), heavy trucks (15.86%), and trailers (29.05%).

[0024] To simulate the most unfavorable fire congestion conditions, the processor, according to the Chinese "Detailed Design Specifications for Ventilation of Highway Tunnels" (JTGT / D702-02—2014), set the upstream congestion calculation length to 1000 meters. The processor input these parameters into a traffic micro-simulation model. In a specific example, this simulation model is the PTV-VISSIM software. The processor built a 1000-meter-long three-lane tunnel model in VISSIM, setting the parking distance between vehicles to 1.5 meters, and the normal driving speed and spacing to be set according to design specifications. By running this simulation model, the processor statistically determined the number of each type of vehicle within this 1000-meter section under severe congestion conditions. For example, after multiple simulations and averaging, the vehicle composition results are as follows: 90 passenger cars, 23 buses, 16 light trucks, 45 medium trucks, 50 large trucks, and 91 trailers, totaling 315 vehicles.

[0025] Subsequently, the processor calculates the total evacuation load for this congested road section based on the preset passenger capacity of each type of vehicle (e.g., 5 passengers for cars, 50 passengers for buses, and 4 passengers for various types of trucks). Based on this, the processor determined that the personnel load density within the 1000-meter-long congested section upstream of the fire was 2.408 people / meter. This load, dynamically calculated from specific traffic data, forms the basis for subsequent simulation evaluations and solves the technical problem of coarse personnel load values ​​that are out of sync with reality in traditional methods.

[0026] Step 2: Obtain the preset evacuation speed for different categories of people under the influence of fire smoke. To realistically simulate evacuation behavior, the processor needs to acquire the evacuation speeds of different types of people under the influence of fire smoke. This method obtains these parameters by conducting real-world evacuation experiments. For example, the processor controls a data acquisition device to perform the following operations: Evacuation routes were laid out at the test site (e.g., a standard stadium) according to the actual design parameters of the tunnel cross passage (e.g., 2.0 meters wide and 250 meters long), and various vehicle models were placed on the routes to create obstacles. At the same time, smoke bombs and other tools were used to simulate the low visibility environment caused by a fire (visibility controlled at 2-4 meters).

[0027] Multiple groups of participants of different ages and genders were recruited. Age categories were: 20-35 years old (youth), 35-55 years old (middle-aged), and 55 years and older (elderly). A total of 76 participants were recruited, covering six categories: young men, young women, middle-aged men, middle-aged women, elderly men, and elderly women.

[0028] The processor records the evacuation time of each subject from the starting point to the ending point (simulated cross passage entrance) using methods such as eye trackers, timers, or video analysis. Based on the evacuation path length and this time, the average evacuation speed of each person is calculated. The speeds of subjects in the same category are statistically averaged to obtain the preset evacuation speed for that category in smoke-free and smoky environments.

[0029] Through the above experiments, the processor obtained a set of specific preset evacuation speeds, which serve as the basis for subsequent simulations. For example, under conditions where fire smoke is present, the evacuation speeds are: 2.35 m / s for young men, 2.20 m / s for middle-aged men, 1.54 m / s for elderly men, 1.94 m / s for young women, 1.58 m / s for middle-aged women, and 1.05 m / s for elderly women. These data, based on actual measurements of the local population, are more accurate than directly referencing foreign standards or empirical values, providing reliable input for the precise calculation of evacuation time.

[0030] Step 3: Establish a computer simulation model of the target tunnel, in which different cross passage spacing parameters and cross passage width parameters are set. This is the core step of the invention. The processor needs to build a simulation model of personnel evacuation in the target tunnel and simulate the evacuation process by inputting different cross passage design parameters.

[0031] The processor first creates a three-dimensional geometric model of the Qinling Tiantaishan Tunnel in evacuation simulation software (such as Pathfinder). This model includes at least the geometry of the main tunnel, lane markings, vehicle obstacles (their location and number determined by the congested vehicle distribution identified in step 1), and pedestrian cross passages. These cross passages are crucial evacuation exits connecting the two main tunnels.

[0032] Optionally, the processor sets several parameter variables to be optimized in the model, including: Cross passage spacing parameters: For example, set to 150 meters, 200 meters, 250 meters, 300 meters, 350 meters, and 400 meters respectively.

[0033] Cross passage width parameters: For example, set them to 1.5 meters, 2.0 meters, 2.5 meters, 3.0 meters, and 3.5 meters respectively.

[0034] The processor loads the evacuation personnel calculated in step 1 (2408 people) and the preset evacuation speeds for each type of personnel determined in step 2 are loaded into the simulation model as input parameters. The processor defines the physical dimensions of each evacuee (such as shoulder width and height according to the "Chinese Adult Anthropometric Dimensions" standard), initial location (uniformly or randomly distributed within a 1000-meter congested road segment according to vehicle distribution), and the personnel category to which they belong in the model.

[0035] The processor initiates a simulation, modeling the entire process from the occurrence of a fire alarm and the start of personnel evacuation until everyone has entered the cross passage. According to the definition of this invention, the Required Safe Evacuation Time (RSET) comprises three parts: alarm detection time, evacuation preparation time, and evacuation time. Optionally, the processor sets the alarm detection time to a fixed value of 60 seconds (based on the reliable response time of the tunnel's automatic fire alarm system) and the evacuation preparation time to a fixed value of 120 seconds (based on the warning time of the tunnel's recorded broadcast system and the reaction time of personnel). The evacuation time (i.e., the sum of movement time and congestion time) is dynamically calculated using Pathfinder software.

[0036] For each combination of the parameters of the cross-passage spacing and width, the processor runs a complete simulation and records the total time when all personnel enter the cross-passage under this combination, that is, the RSET. For example, under the working condition where the cross-passage spacing is 250 meters and the width is 2.0 meters, the RSET obtained by the processor through simulation calculation may be between 400 and 500 seconds. Through simulation, the processor can find that as the width of the cross-passage increases, the RSET will decrease, but when the width increases to 2.5 meters, the decreasing trend of the RSET becomes gentle; and as the cross-passage spacing increases, the movement distance of the personnel at the farthest point increases, resulting in a significant increase in the RSET.

[0037] Step 4: Input the evacuation personnel load and the preset evacuation speed into the computer simulation model, and simulate and calculate the required safe evacuation time of personnel under each cross-passage spacing parameter and each cross-passage width parameter. After obtaining the RSET under different combinations of cross-passage parameters, the processor compares it with a preset safety threshold. This safety threshold is the available safe evacuation time of personnel (ASET).

[0038] In an example of the present invention, the ASET is obtained through an independent fire smoke simulation (such as using FDS software). The ASET is defined as when at a certain moment after the fire occurs, the smoke temperature at a height of 2.0 meters (human eye characteristic height) upstream of the tunnel exceeds 60 °C or the visibility is lower than 10 meters, it is considered that a dangerous state has been reached, and the time duration before this is the ASET. For example, for a fire scale of 30 MW, under the condition of a longitudinal ventilation speed of 2.0 m / s, the calculated ASET is about 900 seconds.

[0039] The processor compares the RSET obtained by simulation with the ASET. The preset safe evacuation condition is: RSET < ASET. Only the combination of cross-passage parameters that meets this condition is considered safe.

[0040] The processor screens all simulation combinations. For example, the simulation results show that when the cross-passage spacing is 400 meters, the RSET under the severe congestion working condition exceeds the ASET and does not meet the safety condition. On the contrary, when the spacing is 250 meters, the RSET is much smaller than the ASET and meets the safety condition.

[0041] Based on the screening results, the processor determines the optimal combination of transverse channel parameters. Optionally, on the premise of meeting safety conditions and taking into account the civil engineering cost, the processor will select a combination where the RSET is slightly less than the ASET and the spacing is the largest. For example, the processor finally outputs that the optimized transverse channel spacing is between 250 meters and 350 meters, and the width is between 2.0 meters and 2.5 meters. Specifically in this example, since when the width exceeds 2.5 meters, the marginal benefit of the contribution to the RSET decreases, and the increase in width will significantly increase the civil engineering work volume, the processor takes 2.5 meters as the recommended upper limit value of the transverse channel width; at the same time, considering the design specification requirements and the calculated RSET safety margin, the processor takes 350 meters as the recommended upper limit value of the transverse channel spacing.

[0042] Optionally, in one possible implementation, the method of the present invention also considers the most unfavorable working condition, that is, a fire exactly occurs at a certain pedestrian transverse channel, resulting in the inoperability of this transverse channel.

[0043] In this case, the processor sets a special scenario in the computer simulation model: designates a certain transverse channel (for example, the channel at the 250-meter spacing position) as the "blocked" or "disabled" state. At this time, the people within the 125 meters upstream and 125 meters downstream that should have been evacuated by this disabled transverse channel will be forced to flow to the adjacent upstream or downstream transverse channels. This means that the adjacent transverse channel needs to bear all the people in its own designed evacuation range (for example, 125 meters) plus the evacuation range of the disabled channel (125 meters), that is, the total evacuation range expands to 250 meters, and the number of people also doubles accordingly.

[0044] The processor implements this scenario in the simulation model and recalculates the required safe evacuation time of the people at the adjacent transverse channel. Through this simulation, it can be verified whether the evacuation capacity of the adjacent transverse channel can still meet the safety conditions (that is, RSET < ASET) under extremely unfavorable conditions. If it cannot be met, it is prompted that the designer needs to further shorten the spacing of the transverse channel or increase its width to provide a higher safety redundancy. This consideration of the most unfavorable working condition greatly improves the robustness of the rescue evacuation structure design during actual disasters.

[0045] Through the aforementioned series of steps, the optimization method provided by this invention transforms the traditional static, specification-based design process into a dynamic, simulation-based, and quantifiable iterative optimization process. It solves the technical problems of existing technologies, such as the lack of targeted verification of design parameters and the difficulty in scientifically measuring safety redundancy, resulting in significant technical effects: it not only provides accurate and reliable cross-passage civil structure design basis for ultra-long, three-lane tunnels with high traffic flow, such as those at Tiantaishan (e.g., providing scientific suggestions of "350-meter spacing and 2.5-meter width"), ensuring personnel safety in emergencies, but also effectively reduces civil engineering costs and construction difficulty by avoiding over-design (such as unnecessarily reducing spacing or increasing width), achieving a balance between safety and economy, and improving the operational safety and scientific design level of ultra-long highway tunnel groups in my country.

[0046] Specifically, this invention addresses the problems of existing ultra-long highway tunnel cross passage designs relying on engineering experience or static specifications, lacking quantitative assessments tailored to specific traffic characteristics and personnel composition, leading to insufficient safety redundancy or excessive civil engineering costs. It achieves scientific and refined optimization of tunnel cross passage spacing and width, significantly improving the safety and reliability of personnel evacuation in emergency situations such as fires. This effectively reduces the risk of mass casualties and unnecessary civil engineering costs caused by poor evacuation, while also enhancing the engineering design rationality and overall operational safety of rescue and evacuation structures. Furthermore, it provides a quantifiable decision-making basis for the safety design of ultra-long tunnel groups. This is achieved by acquiring tunnel traffic flow data and simulating evacuation loads under fire congestion conditions, obtaining preset evacuation speeds for different groups under fire smoke influence, and establishing computer simulation models containing different cross passage spacing and width parameters and calculating the necessary safe evacuation time.

[0047] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing the rescue and evacuation structure of ultra-long highway tunnels, characterized in that, include: Obtain traffic flow prediction data for the target tunnel, and based on the traffic flow prediction data, simulate and determine the evacuation load of the target tunnel under fire congestion conditions. Obtain the preset evacuation speed of different categories of people under the influence of fire smoke; A computer simulation model of the target tunnel is established, in which different cross passage spacing parameters and cross passage width parameters are set; The evacuation load and the preset evacuation speed are input into the computer simulation model to simulate and calculate the necessary safe evacuation time for personnel under each cross passage spacing parameter and each cross passage width parameter. Based on the required safe evacuation time for personnel, the parameter combination that meets the preset safe evacuation conditions is selected from the different cross passage spacing parameters and cross passage width parameters, and is used as the optimization result of the rescue and evacuation structure of the target tunnel.

2. The method for optimizing the rescue and evacuation structure of ultra-long highway tunnels according to claim 1, characterized in that, Based on the traffic flow prediction data, the steps for simulating and determining the evacuation load of the target tunnel under fire congestion conditions specifically include: Based on the traffic flow prediction data, determine the traffic volume and vehicle type ratio of the target tunnel in the predicted year; The traffic volume and vehicle type ratio are input into the traffic micro-simulation model to simulate a traffic congestion scenario that occurs on the upstream road section when a fire occurs, and the number of each type of vehicle within the predetermined congestion length is obtained. The evacuation load is calculated based on the number of vehicles of each type and the preset passenger capacity of each type of vehicle.

3. The method for optimizing the rescue and evacuation structure of ultra-long highway tunnels according to claim 1, characterized in that, The steps for obtaining the preset evacuation speeds for different categories of people under the influence of fire smoke include: Organize personnel evacuation tests, simulating vehicle obstacles and fire smoke environments along the test route; The evacuation time and evacuation distance of multiple groups of subjects of different ages and genders during the experiment were obtained; Based on the evacuation time and evacuation distance, the average evacuation speeds of young men, middle-aged men, elderly men, young women, middle-aged women, and elderly women are calculated under conditions of no smoke and smoke, respectively, and these speeds are used as the preset evacuation speeds.

4. The method for optimizing the rescue and evacuation structure of ultra-long highway tunnels according to claim 3, characterized in that, The preset evacuation speeds for different categories of people under the influence of fire smoke are as follows: 2.35 m / s for young men, 2.20 m / s for middle-aged men, 1.54 m / s for elderly men, 1.94 m / s for young women, 1.58 m / s for middle-aged women, and 1.05 m / s for elderly women.

5. The method for optimizing the rescue and evacuation structure of ultra-long highway tunnels according to claim 1, characterized in that, The computer simulation model also includes a scenario where a fire occurs in a pedestrian crossing, rendering it unusable. The simulation calculations specify the required safe evacuation time for personnel under each cross-aisle spacing parameter and each cross-aisle width parameter, including: The simulation calculation shows the necessary safe evacuation time for people when the adjacent cross passage is doubled in size to accommodate the evacuation of people under the condition that the pedestrian cross passage is unusable.

6. The method for optimizing the rescue and evacuation structure of ultra-long highway tunnels according to claim 1, characterized in that, The computer simulation model is an individual-based personnel evacuation simulation model, which defines the physical dimensions, initial position, and preset evacuation speed of each evacuated individual.

7. The method for optimizing the rescue and evacuation structure of ultra-long highway tunnels according to claim 1, characterized in that, The required safe evacuation time for personnel includes the detection and alarm time, evacuation preparation time, and evacuation time. The detection alarm time is set to 60 seconds, and the evacuation preparation time is set to 120 seconds. The evacuation time was obtained through simulation calculation using the computer simulation model.

8. The method for optimizing the rescue and evacuation structure of ultra-long highway tunnels according to claim 1, characterized in that, The step of selecting a parameter combination that meets the preset safe evacuation conditions from the different cross passage spacing and width parameters based on the required safe evacuation time for personnel specifically includes: Obtain the available safe evacuation time for personnel in a fire situation; The parameter combination in which the required safe evacuation time for personnel is less than the available safe evacuation time for personnel is taken as a candidate combination to satisfy the preset safe evacuation condition; Based on the candidate combinations, determine the upper limit of the horizontal channel spacing parameter and the lower limit of the horizontal channel width parameter.

9. The method for optimizing the rescue and evacuation structure of ultra-long highway tunnels according to claim 8, characterized in that, The step of determining the upper limit value of the horizontal channel spacing parameter and the lower limit value of the horizontal channel width parameter based on the candidate combinations specifically includes: Under the condition that the required safe evacuation time for personnel meets the safety requirements, preferably, the cross passage spacing parameter is set to between 250 meters and 350 meters, and the cross passage width parameter is set to between 2.0 meters and 2.5 meters.

10. The method for optimizing the rescue and evacuation structure of ultra-long highway tunnels according to any one of claims 1-9, characterized in that, The target tunnel is a three-lane, high-traffic, extra-long highway tunnel; the rescue and evacuation structure is a pedestrian cross passage located between the tunnel's driving lanes to connect two adjacent chambers.

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