A simulation system and method for long-tunnel fire evacuation of mixed people and vehicles

Abstract

The application discloses a kind of long tunnel fire-oriented people-car hybrid evacuation simulation system and method, the system includes: scene and dangerous field coupling module, for building tunnel scene, import fire dangerous field;Early warning and vehicle shunt organization module, for fire information is abstracted as early warning signal along tunnel propagation;Behavior enhancement type pedestrian evacuation decision module, for coupling static field and fire field under the framework of cellular automaton calculation pedestrian transfer probability, and integrate the leader direction bias following based on fear value, fear propagation and competition mechanism;People-car collaborative constraint module, for processing people-car conflict in unified grid, when the grid that vehicle is scheduled to occupy and pedestrian current position or target position conflict, guide pedestrian to select the grid of transfer probability second high to avoid;Wherein, each module cooperates operation, makes fire dangerous field drive vehicle response, passenger release and pedestrian evacuation, forms continuous coupling simulation process.

Description

Technical Field

[0001] This invention relates to the field of fire safety evacuation simulation and emergency management technology, and in particular to a human-vehicle mixed evacuation simulation system and a human-vehicle mixed evacuation simulation method for fires in extra-long tunnels. Background Technology

[0002] Existing research on tunnel fires mainly focuses on two areas: fire environment simulation and pedestrian evacuation. The former emphasizes smoke diffusion, temperature distribution, and ventilation control, while the latter focuses on path selection and evacuation efficiency analysis for people in hazardous environments.

[0003] However, in highway tunnel fire scenarios, the fire environment is usually only weakly coupled with the evacuation process as an external input, and has not yet become a unified driving factor for exit availability, vehicle diversion, and the determination of pedestrian and occupant deaths. At the same time, vehicles are still simplified as static obstacles in most models, lacking the expression of the continuous chain of "fire warning - vehicle response - occupant release - pedestrian evacuation".

[0004] For tunnels with vehicular cross passages, especially (extra) long tunnels where regulations require both pedestrian and vehicular cross passages, the vehicular cross passages are not only geometrical ancillary facilities, but also crucial engineering units for vehicle diversion, alleviating parking congestion, and reducing pedestrian evacuation load under fire conditions. Existing models typically do not include vehicular cross passages as dynamic facilities with limited capacity and requiring organized release, making it difficult to reveal the impact of vehicle type combinations, lane competition, and cross passage organization on overall evacuation. Summary of the Invention

[0005] This invention aims to at least partially solve one of the technical problems in related technologies. Therefore, the first objective of this invention is to propose a simulation system for mixed pedestrian and vehicle evacuation in long tunnel fires, capable of uniformly representing the coupling relationship between the fire scene, vehicle behavior, pedestrian behavior, and cross passage organization and control, and can be used for evacuation assessment and organization optimization under tunnel fire conditions.

[0006] The second objective of this invention is to propose a simulation method for mixed evacuation of people and vehicles in fires in extra-long tunnels.

[0007] To achieve the above objectives, a first aspect of the present invention proposes a simulation system for mixed pedestrian and vehicle evacuation in fires in extra-long tunnels, comprising: The scene and hazard field coupling module is used to construct tunnel scenes, import fire hazard fields, and generate dynamic evacuation zones based on the location of the fire source and the availability of the vehicle cross passage. The early warning and vehicle diversion organization module is used to abstract fire information into early warning signals that propagate along the tunnel. Based on the propagation status of the early warning signals, it controls the vehicle diversion path, parking and disembarking, entrance sealing and vehicle cross passage opening, and triggers the release of occupants from parked vehicles to connect with the pedestrian evacuation process. The behavior-enhanced pedestrian evacuation decision module is used to calculate the pedestrian transfer probability by coupling static field and fire field under the framework of cellular automata, and integrates leader direction bias following, fear propagation and competition mechanism based on fear value; The vehicle-pedestrian coordination constraint module is used to handle vehicle-pedestrian conflicts in a unified grid. When the grid that a vehicle is scheduled to occupy conflicts with the current or target position of a pedestrian, it guides the pedestrian to choose the grid with the second highest probability of transfer to avoid the conflict. The modules work together to enable vehicle response, occupant release, and pedestrian evacuation in fire hazard areas, forming a continuous coupled simulation process.

[0008] In addition, the human-vehicle mixed evacuation simulation system for fires in extra-long tunnels according to the above embodiments of the present invention may also have the following additional technical features: According to one embodiment of the present invention, the early warning and vehicle diversion organization module abstracts the process of people and vehicles receiving fire information into the speed of early warning signal propagation, and triggers vehicle diversion and entrance control according to the propagation location of the early warning signal; when the early warning signal propagates to the location of the vehicle cross passage, it controls the upstream vehicles to switch to evacuation via the vehicle cross passage, and stops generating new vehicles when the signal propagates to the tunnel entrance.

[0009] According to one embodiment of the present invention, in the behavior-enhanced pedestrian evacuation decision module, the transition probability of a pedestrian within the Moore neighborhood is calculated by the following formula: In the formula, S ij It is a static field. F ij It was a fire scene. B ij For the direction offset term, k S and k F These represent the corresponding weights; The direction offset term is calculated using the following formula: , In the formula, v ij Let be the candidate movement direction vector. v L For the leader's direction vector, The angle between the candidate movement direction vector and the leader's direction vector.ω follow To follow the weight, e i For individuals i The leader is the one with the lowest fear value in the neighborhood.

[0010] According to one embodiment of the present invention, the static field is calculated as follows: In the formula, d min (i,j) represents the distance from the cell to the nearest reachable exit. d max For the whole audience d min The maximum value of (i,j); Fire scene calculations are performed using the following formula: , ; In the formula, k T Temperature weighting, k CO Weighted by CO concentration, k V For visibility weight; temp( i , j ) is the cell at the current time ( i , j The temperature at point ) is expressed in °C; CO( i , j ) is the cell at the current time ( i , j CO concentration at ) is expressed in ppm; vis( i , j ) is the cell at the current time ( i , j Visibility at () in meters; T 0 represents the initial ambient temperature; CO0 represents the maximum CO concentration permissible by the human body. V 0 represents the minimum visibility that should be guaranteed for tunnel escape.

[0011] According to one embodiment of the present invention, the vehicle-human cooperative constraint module first determines the target grid occupied by the vehicle in the next moment, and then performs pedestrian target selection. When the vehicle target grid conflicts with the pedestrian's current position or target position, the pedestrian selects the grid with the second highest transfer probability in the neighborhood to avoid it.

[0012] According to one embodiment of the present invention, considering the width of the cross passage and the differences in vehicle types, capacity constraints and release rules are set for the vehicle cross passage: only one large vehicle or two small vehicles are allowed to pass at each time step, and one large vehicle and one small vehicle are not allowed to pass at the same time; when the arrival combination is one large vehicle and one small vehicle, the large vehicle is given priority to pass, and when the arrival combination is two large vehicles, the vehicles in the left lane are given priority to pass.

[0013] According to one embodiment of the present invention, the dynamic evacuation zone divides the tunnel into a vehicle diversion zone, a parking and drop-off zone, a forced parking and gathering zone, and a normal departure zone based on the location of the fire source, the availability of the cross passage in front of the vehicle and its relative relationship with the fire source.

[0014] To achieve the above objectives, a second aspect of the present invention proposes a simulation method for mixed evacuation of people and vehicles in fires in extra-long tunnels. The method is based on the mixed evacuation simulation system for fires in extra-long tunnels described in any of the above embodiments, and includes the following steps: S1, construct the tunnel scene and set the location of the fire source, the layout of the cross passage and the initial traffic status; S2 generates a fire hazard field and maps it to an evacuation grid, thus coupling the fire field with the personnel and vehicle system. S3 updates vehicle diversion decisions, entrance control, and parking status based on fire early warning signal propagation; S4 triggers the release of occupants from parked vehicles and initiates the pedestrian evacuation process; S5 calculates pedestrian movement based on static field, fire field, directional offset and vehicle constraint rules; S6, organize vehicle evacuation according to the cross passage release rules; S7 outputs evacuation time, number of deaths, and traffic organization indicators.

[0015] Compared with the prior art, the present invention has the following beneficial effects: (1) The fire hazard field is transformed from an external boundary condition into a core driving variable in evacuation decision-making. Temperature, CO concentration and visibility directly affect exit availability, pedestrian movement and death determination, which improves the realism of fire-evacuation coupling.

[0016] (2) The continuous response chain of “fire warning - vehicle response - parking and getting off - pedestrian evacuation” is explicitly represented, which breaks through the limitations of existing models that only consider pedestrian evacuation or vehicle evacuation and realizes the simulation of the whole process of mixed evacuation of people and vehicles.

[0017] (3) Incorporating the cross passageway into the mixed evacuation system of people and vehicles as a dynamic facility with limited capacity and controlled by release rules can help analyze the impact of vehicle type combination, queue competition and release organization on evacuation efficiency.

[0018] (4) The direction bias algorithm of following the calmest local person is adopted instead of the traditional dynamic field conformity logic, so that the group conformity is a correction of the local direction rather than a forced adsorption of a certain position, reducing unreasonable long-term local aggregation in the narrow tunnel scenario, and is more suitable for stable evacuation modeling in the tunnel fire scenario.

[0019] (5) Applicable to the study of evacuation simulation, safety management and organization optimization in fire scenarios of tunnels with both vehicular and pedestrian cross passages.

[0020] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0021] Figure 1 This is a block diagram of a simulation system for mixed evacuation of people and vehicles in a fire in an extra-long tunnel, according to an embodiment of the present invention. Figure 2 This is a general framework diagram of a simulation system for mixed evacuation of people and vehicles in a fire in an extra-long tunnel according to an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the coupling relationship between the components of a simulation system for mixed pedestrian and vehicle evacuation in a fire in an extra-long tunnel according to an embodiment of the present invention. Figure 4 A flowchart illustrating scene initialization, early warning, and vehicle diversion organization according to an embodiment of the present invention; Figure 5 A flowchart of a behavior-enhanced pedestrian evacuation calculation according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the vehicle cross passage release management rules according to an embodiment of the present invention; Figure 7 This is a schematic diagram of dynamic evacuation zoning according to an embodiment of the present invention. Detailed Implementation

[0022] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0023] The following description, with reference to the accompanying drawings, describes the human-vehicle mixed evacuation simulation system and method for fires in extra-long tunnels, as proposed in the embodiments of the present invention.

[0024] like Figure 1As shown, the human-vehicle hybrid evacuation simulation system for fires in extra-long tunnels according to an embodiment of the present invention includes: a scene and hazard field coupling module 10, an early warning and vehicle diversion organization module 20, a behavior-enhanced pedestrian evacuation decision module 30, and a human-vehicle collaborative constraint module 40.

[0025] The system comprises several modules: a scenario and hazard field coupling module 10, which constructs the tunnel scenario, imports the fire hazard field, and generates dynamic evacuation zones based on the fire source location and the availability of vehicular cross passages; an early warning and vehicle diversion organization module 20, which abstracts fire information into early warning signals propagating along the tunnel, controls vehicle diversion paths, parking and passenger disembarkation, entrance closures, and vehicular cross passage opening based on the propagation status of the early warning signals, and triggers the release of occupants from parked vehicles to participate in the pedestrian evacuation process; a behavior-enhanced pedestrian evacuation decision module 30, which couples the static field and the fire field within a cellular automata framework to calculate pedestrian transfer probabilities and integrates leader directional bias following, fear propagation, and competition mechanisms based on fear values; and a human-vehicle collaborative constraint module 40, which handles human-vehicle conflicts in a unified grid. When a vehicle's intended grid conflicts with a pedestrian's current or target location, the module guides the pedestrian to choose the grid with the second-highest transfer probability for avoidance. All modules operate collaboratively, enabling the fire hazard field to drive vehicle responses, occupant releases, and pedestrian evacuations, forming a continuous coupled simulation process.

[0026] Specifically, the scenario and hazard field coupling module 10 first constructs a tunnel scenario and imports a fire hazard field composed of the spatiotemporal distribution of temperature, CO concentration, and visibility, mapping it to a unified evacuation grid. Simultaneously, based on the fire source location and the availability of the vehicular cross passage, it generates dynamic evacuation zones such as vehicle diversion zones, parking and passenger drop-off zones, forced parking aggregation zones, and normal departure zones, providing a unified spatial and hazard-driven foundation for subsequent modules. The early warning and vehicle diversion organization module 20 abstracts fire information into an early warning signal propagating upstream from the fire source. When this signal reaches the vehicular cross passage, it controls upstream vehicles to switch to evacuation via the cross passage; when it reaches the tunnel entrance, it stops generating new vehicles. Vehicles located in the vehicle diversion zone, upon receiving the fire signal, decide to evacuate via the cross passage. Simultaneously, it applies capacity constraints and release rules to the vehicular cross passage, allowing only one large vehicle or two small vehicles to pass at each time step, and implementing alternating compensation and priority release for different arrival combinations of large and small vehicles. Upon receiving a fire signal, vehicles entering the danger zone trigger a stopping and passenger disembarkation mechanism. The parked vehicles release their occupants and place them in nearby empty cells, thus converting the vehicle system's personnel load into a pedestrian evacuation process. The behavior-enhanced pedestrian evacuation decision module 30 receives the released pedestrians and, within a cellular automata framework, couples the static field and the fire field to calculate the transition probability of each candidate grid. The fire field acts as a suppression term, directly reducing the probability of the danger zone being selected. Simultaneously, this module integrates fear propagation and competition mechanisms, using the lowest fear value in the neighborhood as the leader. A fear-weighted directional bias term is used to correct the candidate grid scores, ensuring that conformity behavior follows the direction of locally calm individuals rather than attracting high-frequency positions, avoiding irrational gatherings in narrow tunnels. The vehicle-pedestrian coordination constraint module 40 coordinates the parallel movement of vehicles and pedestrians within a unified grid. It first determines the target grid to be occupied by the vehicle in the next moment, then calculates the pedestrian's target grid. If a conflict occurs, it guides pedestrians to choose the grid with the second-highest transition probability in the neighborhood for avoidance, achieving dynamic coordination of "people avoiding vehicles." Each module operates collaboratively with the fire hazard field as the unified driving force and the early warning signal as the time sequence, forming a complete continuous coupled simulation process of "fire early warning - vehicle response - occupant release - pedestrian evacuation".

[0027] Therefore, the vehicle-pedestrian hybrid evacuation simulation system for fires in extra-long tunnels, as described in this invention, transforms the fire hazard field from external boundary conditions into a core driving variable for evacuation decisions that runs through all modules, significantly improving the realism of the coupling between fire and evacuation. It explicitly expresses the complete response chain from vehicle receiving warning information, diversion or parking, personnel release to pedestrian evacuation, breaking through the limitations of existing models that only consider a single evacuation subject. By replacing the traditional dynamic field with directional offset following, it reduces repeated wandering and unreasonable gathering caused by the herd effect in narrow tunnels, improving simulation stability and exit guidance. The inclusion of vehicular cross passages as dynamic facilities with limited capacity and rule-based release in the simulation effectively reveals the impact of vehicle type combination, lane competition, and release organization on overall evacuation efficiency, providing reliable support for evacuation assessment, cross passage design, and emergency organization optimization under fire conditions in extra-long tunnels.

[0028] The following is combined with Figure 2The working process of this invention unfolds sequentially as follows: First, the scene and hazard field coupling module 10 performs scene initialization, constructs the tunnel geometric model, sets the fire source location and cross passage layout, configures the initial traffic state, and generates a fire hazard field containing the spatiotemporal distribution of temperature, CO concentration, and visibility. This hazard field is then mapped to a unified cellular automaton evacuation grid. Simultaneously, based on the fire source location, the availability of vehicular cross passages, and their relative relationship to the fire source, this module divides the tunnel into vehicle diversion zones, parking and pedestrian drop-off zones, forced parking aggregation zones, and normal departure zones, forming dynamic evacuation zones. This provides a unified spatial organization basis and hazard-driven data for subsequent modules. Afterward, the system enters the main loop, sequentially executing hazard field updates, early warning and vehicle diversion organization, pedestrian evacuation calculations, vehicle-pedestrian coordination constraints, and cross passage release management within each time step. In the early warning and vehicle diversion organization module 20, fire information is abstracted as an early warning signal propagating upstream along the tunnel from the fire source. The system monitors the position of the leading edge of the early warning signal in real time: when the early warning signal reaches the preset vehicle cross passage, it controls upstream vehicles to switch to the evacuation route via the vehicle cross passage; when the early warning signal reaches the tunnel entrance, it triggers the entrance closure mechanism and stops generating new vehicles. At the same time, for vehicles that have missed the cross passage when receiving the early warning signal and cannot be diverted via the cross passage, the module triggers their parking and passenger disembarkation mechanism, using the parked vehicle as the occupant release source, generating pedestrian individuals in the surrounding idle cells, and completing the load transfer from the vehicle system to the pedestrian system. After the occupants are released, the system enters the behavior-enhanced pedestrian evacuation decision module 30. Within a cellular automata framework, this module calculates the transition probability for each pedestrian's Moore neighborhood candidate grid. The transition probability is jointly determined by the static field, the fire field, and the directional bias term. The static field provides exit-oriented attraction based on exit distance. The fire field is a weighted composite of three hazardous products: temperature, CO concentration, and visibility, serving as a suppression term to reduce the probability of selecting a hazardous area. The directional bias term identifies the individual with the lowest fear value in the neighborhood as the leader, calculates the consistency between the candidate movement direction and the leader's direction, and weights it with individual fear values. This ensures that the group's conformity behavior manifests as following the direction of the locally calmer individual, avoiding the repeated wandering and localized "overheating" caused by traditional dynamic fields in narrow tunnels. After the pedestrian completes target selection, the system enters the human-vehicle cooperative constraint module 40. This module first determines the target grid to be occupied by the vehicle in the next moment within a unified grid, then checks each pedestrian's target grid against the vehicle's pre-occupied grid. If a conflict occurs, the module guides the pedestrian to select the grid with the second-highest transition probability within their neighborhood for avoidance, achieving dynamic coordination of "people avoiding vehicles." Finally, the system organizes vehicles to disperse through the cross passage according to the cross passage release management rules, and implements capacity constraints - only one large vehicle or two small vehicles are allowed to pass at each time step, and one large vehicle and one small vehicle are not allowed to pass at the same time. The system also implements an alternating compensation priority release strategy for different vehicle combinations.The system outputs an intermediate state at each time step, repeating the above process until all personnel have been evacuated or the termination condition is met, and finally outputs the evacuation time, number of deaths, and traffic organization indicators. The coupling relationship between the modules is as follows. Figure 3 As shown.

[0029] It should be noted that the mixed evacuation simulation system for fires in extra-long tunnels according to the embodiments of the present invention is applicable to tunnels with both vehicular and pedestrian cross passages, and is especially applicable to twin-tunnel separated (extra-long) highway tunnels that are required by regulations to have vehicular cross passages.

[0030] According to one embodiment of the present invention, the early warning and vehicle diversion organization module 20 abstracts the process of people and vehicles receiving fire information into the propagation speed of the early warning signal, and triggers vehicle diversion and entrance control according to the propagation location of the early warning signal; when the early warning signal propagates to the location of the vehicle cross passage, it controls upstream vehicles to switch to evacuation via the vehicle cross passage, and stops generating new vehicles when the signal propagates to the tunnel entrance. The scene initialization and early warning and vehicle diversion organization process is as follows: Figure 4 As shown.

[0031] According to one embodiment of the present invention, such as Figure 5 As shown, the behavior-enhanced pedestrian evacuation decision-making adopts a field cellular automata model. In the behavior-enhanced pedestrian evacuation decision-making module 30, the transition probability of a pedestrian in the Moore neighborhood is calculated by the following formula: In the formula, S ij It is a static field. F ij It was a fire scene. B ij For the direction offset term, k S and k F These represent the corresponding weights; The static field is calculated using the following formula: In the formula, d min (i,j) represents the distance from the cell to the nearest reachable exit. d max For the whole audience d min The maximum value of (i,j); Fire scene calculations are performed using the following formula: , ; In the formula, k T Temperature weighting,k CO Weighted by CO concentration, k V For visibility weight; temp( i , j ) is the cell at the current time ( i , j The temperature at point ) is expressed in °C; CO( i , j ) is the cell at the current time ( i , j CO concentration at ) is expressed in ppm; vis( i , j ) is the cell at the current time ( i , j Visibility at () in meters; T 0 represents the initial ambient temperature; CO0 represents the maximum CO concentration permissible by the human body. V 0 represents the minimum visibility that should be guaranteed for tunnel escape.

[0032] Traditional field-based cellular automata evacuation methods often use dynamic fields to characterize the herd effect of following previous paths, but this system does not incorporate this into the movement probability calculation. The reason is that (extra-long) tunnels have a narrow geometry and significant longitudinal evacuation characteristics. If a traditional dynamic field is directly used, areas frequently traversed by pedestrians are easily reinforced, attracting pedestrians to a certain location and causing them to linger repeatedly, weakening exit guidance and creating a local "overheating" phenomenon. Therefore, this system rewrites the herd behavior as a directional bias: pedestrian i identifies the person with the lowest fear value in their neighborhood as the "leader" and extracts their relative direction vector. v L For any candidate cell, the corresponding candidate movement direction is denoted as . v ij The direction offset term is calculated using the following formula: , In the formula, v ij Let be the candidate movement direction vector. v L For the leader's direction vector, The angle between the candidate movement direction vector and the leader's direction vector. ω follow To follow the weight, e i For individuals i The leader is the one with the lowest fear value in the neighborhood.

[0033] Therefore, the more consistent the candidate's direction is with the leader's direction and the more panicked the individual, the greater the directional reward the candidate cell receives. This treatment makes group conformity manifest as a correction of local directions rather than a forced attraction to a particular location, making it more suitable for stable evacuation modeling in tunnel fire scenarios.

[0034] The vehicle-pedestrian interaction coordination module first determines the target grid that the vehicle will occupy in the next moment, and then calculates the target grid for the pedestrian. If the grid that the vehicle is about to occupy conflicts with the grid that the pedestrian is currently occupying or the target grid, the pedestrian will choose the suboptimal grid according to the principle of avoiding vehicles.

[0035] According to one embodiment of the present invention, the vehicle-human cooperative constraint module 40 first determines the target grid occupied by the vehicle in the next moment, and then performs pedestrian target selection. When the vehicle target grid conflicts with the current position or target position of the pedestrian, the pedestrian selects the grid with the second highest transfer probability in the neighborhood to avoid it.

[0036] According to one embodiment of the present invention, the cross passage for vehicles is provided with capacity constraints and release rules: only one large vehicle or two small vehicles are allowed to pass at each time step, and one large vehicle and one small vehicle are not allowed to pass at the same time; when the arrival combination is one large vehicle and one small vehicle, the large vehicle is given priority to pass, and when the arrival combination is two large vehicles, the vehicles in the left lane are given priority to pass.

[0037] Specifically, such as Figure 6 As shown, the vehicle-pedestrian coordination constraint module 40 sets capacity constraints and release rules for the entrance of the vehicle cross passage. Only one large vehicle or two small vehicles are allowed to pass through each time step; simultaneous passage of one large vehicle and one small vehicle is not permitted. When the arrival combination is one large vehicle and one small vehicle, the large vehicle is released first to reduce the risk of congestion caused by its delay; in the next time step, the small vehicle in the other lane is released first to avoid long-term occupation of the cross passage by one lane. When the arrival combination is two large vehicles, the large vehicle in the left lane is released first; in the next time step, the large vehicle in the right lane is released first to alleviate partial congestion.

[0038] According to one embodiment of the present invention, such as Figure 7 As shown, the dynamic evacuation zoning divides the tunnel into vehicle diversion zones, parking and passenger drop-off zones, forced parking and gathering zones, and normal departure zones based on the location of the fire source, the availability of the cross passage in front of the vehicle, and their relative relationship with the fire source. This provides a unified spatial organization basis for vehicle decision-making, passenger release, and pedestrian evacuation.

[0039] Corresponding to the above embodiments, the present invention also provides a simulation method for mixed evacuation of people and vehicles in fires in extra-long tunnels.

[0040] The present invention provides a simulation method for mixed evacuation of people and vehicles in fires in extra-long tunnels. The method is based on the simulation system for mixed evacuation of people and vehicles in fires in extra-long tunnels described in any of the above embodiments, and includes the following steps: S1, construct the tunnel scene and set the location of the fire source, the layout of the cross passage and the initial traffic status; S2 generates a fire hazard field and maps it to an evacuation grid, thus coupling the fire field with the personnel and vehicle system. S3 updates vehicle diversion decisions, entrance control, and parking status based on fire early warning signal propagation; S4 triggers the release of occupants from parked vehicles and initiates the pedestrian evacuation process; S5 calculates pedestrian movement based on static field, fire field, directional offset and vehicle constraint rules; S6, organize vehicle evacuation according to the cross passage release rules; S7 outputs evacuation time, number of deaths, and traffic organization indicators.

[0041] It should be noted that for details not disclosed in the simulation method for mixed evacuation of people and vehicles in fires in extra-long tunnels according to the embodiments of the present invention, please refer to the details disclosed in the simulation system for mixed evacuation of people and vehicles in fires in extra-long tunnels according to the embodiments of the present invention, which will not be repeated here.

[0042] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0043] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0044] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0045] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A simulation system for mixed evacuation of people and vehicles in fires in extra-long tunnels, characterized in that, include: The scene and hazard field coupling module is used to construct tunnel scenes, import fire hazard fields, and generate dynamic evacuation zones based on the location of the fire source and the availability of the vehicle cross passage. The early warning and vehicle diversion organization module is used to abstract fire information into early warning signals that propagate along the tunnel. Based on the propagation status of the early warning signals, it controls the vehicle diversion path, parking and disembarking, entrance sealing and vehicle cross passage opening, and triggers the release of occupants from parked vehicles to connect with the pedestrian evacuation process. The behavior-enhanced pedestrian evacuation decision module is used to calculate the pedestrian transfer probability by coupling static field and fire field under the framework of cellular automata, and integrates leader direction bias following, fear propagation and competition mechanism based on fear value; The vehicle-pedestrian coordination constraint module is used to handle vehicle-pedestrian conflicts in a unified grid. When the grid that a vehicle is scheduled to occupy conflicts with the current or target position of a pedestrian, it guides the pedestrian to choose the grid with the second highest probability of transfer to avoid the conflict. The modules work together to enable vehicle response, occupant release, and pedestrian evacuation in fire hazard areas, forming a continuous coupled simulation process.

2. The simulation system for mixed evacuation of people and vehicles in extra-long tunnel fires according to claim 1, characterized in that, The warning and vehicle diversion organization module abstracts the process of people and vehicles receiving fire information into the speed of warning signal propagation, and triggers vehicle diversion and entrance control according to the location of the warning signal propagation. When the warning signal propagates to the location of the vehicle cross passage, it controls the upstream vehicles to switch to evacuation via the vehicle cross passage, and stops generating new vehicles when it propagates to the tunnel entrance.

3. The simulation system for mixed evacuation of people and vehicles in extra-long tunnel fires according to claim 1, characterized in that, In the behavior-enhanced pedestrian evacuation decision module, the transition probability of a pedestrian within the Moore neighborhood is calculated using the following formula: In the formula, S ij It is a static field. F ij It was a fire scene. B ij For the direction offset term, k S and k F These represent the corresponding weights; The directional offset term is calculated using the following formula: ， In the formula, v ij Let be the candidate movement direction vector. v L For the leader's direction vector, The angle between the candidate movement direction vector and the leader's direction vector. ω follow To follow the weight, e i For individuals i The fear value is the value of the leader, who is the one with the lowest fear value in the neighborhood.

4. The simulation system for mixed evacuation of people and vehicles in extra-long tunnel fires according to claim 3, characterized in that, The static field is calculated using the following formula: In the formula, d min (i,j) represents the distance from the cell to the nearest reachable exit. d max For the whole audience d min The maximum value of (i,j); The fire scene is calculated using the following formula: ， ； In the formula, k T Temperature weighting, k CO Weighted by CO concentration, k V For visibility weight; temp( i , j ) is the cell at the current time ( i , j The temperature at () is expressed in °C. CO( i , j ) is the cell at the current time ( i , j CO concentration at ) is expressed in ppm; vis( i , j ) is the cell at the current time ( i , j Visibility at () in meters; T 0 represents the initial ambient temperature; CO0 represents the maximum CO concentration permissible by the human body. V 0 represents the minimum visibility that should be guaranteed for tunnel escape.

5. The simulation system for mixed evacuation of people and vehicles in extra-long tunnel fires according to claim 1, characterized in that, The vehicle-human cooperative constraint module first determines the target grid to be occupied by the vehicle in the next moment, and then selects the pedestrian target. When the vehicle target grid conflicts with the pedestrian's current position or target position, the pedestrian selects the grid with the second highest transfer probability in the neighborhood to avoid it.

6. The simulation system for mixed evacuation of people and vehicles in extra-long tunnel fires according to claim 1, characterized in that, The cross passage for vehicles is subject to capacity constraints and release rules: only one large vehicle or two small vehicles are allowed to pass at each time step, and one large vehicle and one small vehicle are not allowed to pass at the same time; when the arrival combination is one large vehicle and one small vehicle, the large vehicle is given priority to pass, and when the arrival combination is two large vehicles, the vehicles in the left lane are given priority to pass.

7. The simulation system for mixed evacuation of people and vehicles in extra-long tunnel fires according to claim 1, characterized in that, The dynamic evacuation zone is divided into a vehicle diversion zone, a parking and drop-off zone, a forced parking and gathering zone, and a normal departure zone based on the location of the fire source, the availability of the cross passage in front of the vehicles, and their relative relationship with the fire source.

8. A simulation method for mixed evacuation of people and vehicles in fires in extra-long tunnels, characterized in that, The method, based on the human-vehicle mixed evacuation simulation system for fires in extra-long tunnels as described in any one of claims 1-7, includes the following steps: S1, construct the tunnel scene and set the location of the fire source, the layout of the cross passage and the initial traffic status; S2 generates a fire hazard field and maps it to an evacuation grid, thus coupling the fire field with the personnel and vehicle system. S3 updates vehicle diversion decisions, entrance control, and parking status based on fire early warning signal propagation; S4 triggers the release of occupants from parked vehicles and initiates the pedestrian evacuation process; S5 calculates pedestrian movement based on static field, fire field, directional offset and vehicle constraint rules; S6, organize vehicle evacuation according to the cross passage release rules; S7 outputs evacuation time, number of deaths, and traffic organization indicators.

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