An evacuation simulation method based on a fire evacuation model that considers guiding factors.

Abstract

This invention discloses an evacuation simulation method based on a fire evacuation model that considers guiding factors. Based on a cellular automata model, it considers guiding factors and fire factors to construct a fire evacuation model that considers guiding factors (GF-CA), providing effective technical support and improvement suggestions for evacuation safety management.

Description

Technical Field

[0001] This invention relates to the field of fire evacuation modeling technology, and specifically to an evacuation simulation method based on a fire evacuation model that considers guiding factors. Background Technology

[0002] Fire evacuation models can effectively solve simulation problems such as complex structures and difficulties in fire evacuation drills. By simulating personnel evacuation, reasonable emergency evacuation optimization strategies can be proposed to reduce casualties and property losses. Current research shows that traditional fire evacuation models do not consider the influence of guiding factors on evacuees, and research on the safe evacuation of personnel at subway transfer stations is insufficient and lacks systematic coverage. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention aims to provide an evacuation simulation method based on a fire evacuation model that considers guiding factors.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] An evacuation simulation method based on a fire evacuation model that considers guiding factors, the specific process of which is as follows:

[0006] The building space is divided into a uniform grid, using a two-dimensional cellular space structure with a square grid. The neighbor type is Moore, and cells can move in eight directions. The boundaries are evacuation walls and safety exits. P... ij The probability that cell i moves from the center to position j is given by the static field strength S. ij and dynamic field strength D ij Decide;

[0007] Based on this, a fire evacuation model considering guiding factors is established as follows:

[0008]

[0009] Where N is the normalization factor for the probability, ensuring that ∑P ij =1,K S The weighting coefficient representing the static field strength reflects the intensity of the impact of the location of safety exits on personnel evacuation; K D The weighting coefficients representing the dynamic field strength reflect the intensity of the interaction between people; n ij and ξ ij Describe whether cell i is occupied by a wall or obstacle and whether it is occupied by a pedestrian at this moment; K F The weighting coefficient representing the fire intensity reflects the strength of the fire's impact on personnel evacuation; K G The weighting coefficient representing the guiding field strength reflects the intensity of the guiding effect on personnel evacuation; fire field strength F ijand the guiding field strength G ij The fire field strength F represents the factors influencing the probability of cell i choosing position j. ij The magnitude is mainly determined by the location of the fire; the guiding field strength G ij This was primarily achieved through quantitative analysis of signage guidance, broadcast guidance, and guide guidance;

[0010] By calculating the static field strength value S ij Dynamic field strength value D ij Fire field intensity value F ij Guiding field strength value G ij Substituting into formula (2), the selection probability P of the cell can be calculated. ij Thus, the evacuation path can be obtained after taking into account guiding factors.

[0011] Furthermore, set R f Let F be the fire limit range, and dis be the shortest distance from cell i to the boundary of the fire area. When the cell is within this range, F ij Greater than 0, otherwise F ij Equal to 0:

[0012]

[0013]

[0014] Where, d i,f d represents the distance from cell i to the edge of the fire; i,f With F ij They are inversely proportional; when d i,f The larger the value, the farther cell i is from the fire location, the smaller the fire's impact on it, the smaller the resulting fire field strength, and the greater the probability that cell i will choose location j.

[0015] Furthermore, the cell size is set to 0.4m × 0.4m.

[0016] Furthermore, n ij and ξ ij The following describes whether cell i is occupied by a wall or obstacle and whether it is occupied by a pedestrian at this moment:

[0017]

[0018]

[0019] Furthermore, K S K D K F K G The value range is [-1, 1], and K satisfies S +K D +KF +K G =1.

[0020] Furthermore, the process of quantitatively analyzing the guidance provided by directional signs is as follows:

[0021] The effectiveness of visual guidance sign B1 on evacuees is expressed as follows: It is mainly related to the field of vision of personnel (D1), the effective range of the location of the sign (D2), and the density of the number of signs (D3).

[0022]

[0023] in, Indicates the radius of a person's field of vision; Indicates the range coefficient of the indicator sign; Indicates the density coefficient of the indicator sign; This represents the distance between cell i and indicator B1; Indicates the direction of action of the indicator, and is a unit vector.

[0024] Furthermore, the process of quantitatively analyzing the broadcast guidance is as follows:

[0025] The strength of the effect of broadcast guidance B2 on evacuees is expressed as follows: It is mainly related to the subjective reaction characteristics of personnel (D4), the objective characteristics of the environment (D5), and the number of broadcasts (D6):

[0026]

[0027] in, Indicates the characteristic coefficient of subjective reaction of personnel; This indicates the interference factor of the voice alarm system, which is related to the number of broadcasts. Indicates the direction of the broadcast guidance; is a unit vector. The objective characteristics of the current environment are mainly related to visibility and the clarity of the alarm sound:

[0028]

[0029] This represents the visibility coefficient, which ranges from (0,1) and can be obtained using a normal distribution. The lower the visibility, the more effective the broadcast guidance will be for evacuees. The weighting of alarm sound information depends on the sound pressure level and reverberation time at that location.

[0030] Furthermore, the process of quantitative analysis of facilitator guidance is as follows:

[0031] The strength of the influence of guide B3 on evacuees is expressed as follows: It is mainly related to the strength of the guide's effect (D7), the range of the guide's effect (D8), and the number of guides (D9):

[0032]

[0033] This represents the coefficient of influence of the guide; This represents the coefficient indicating the scope of the guide's influence. This indicates the interference factor caused by the facilitator, which is affected by the number of facilitators. This represents the distance between cell i and guide B3; This indicates the direction of the guide's action and is a unit vector.

[0034] Furthermore, by quantitatively analyzing the guiding factors, including signage, broadcast guidance, and human guides, the strength of their influence on evacuees was determined. Final guiding effect strength The guiding field strength G is the guiding effect with the best effect among the three types of guiding effects. ij That is, the intensity of the guiding effect Size:

[0035]

[0036] The beneficial effects of this invention are as follows: Based on the cellular automata model, this invention considers guiding factors and fire factors to construct a fire evacuation model that considers guiding factors (GF-CA), providing effective technical support and improvement suggestions for evacuation safety management. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the probability of the movement direction of environmental area cells in the decision simulation method based on the fire evacuation (GA-CA) model considering guiding factors described in this invention.

[0038] Figure 2 This is a schematic diagram of the cell movement direction in the decision simulation method based on the fire evacuation-considering-guide-factors (GA-CA) model described in this invention.

[0039] Figure 3 This is a schematic diagram illustrating the role of the indicator sign in the decision-making simulation method based on the fire evacuation-considering-guide-factors (GA-CA) model described in this invention.

[0040] Figure 4 This is a schematic diagram illustrating the broadcast guidance role in the decision simulation method based on the fire evacuation-CA model considering guidance factors described in this invention.

[0041] Figure 5This is a schematic diagram of the role of the guide in the decision simulation method based on the fire evacuation-considering-factors (GA-CA) model described in this invention. Detailed Implementation

[0042] The present invention will be further described below with reference to the accompanying drawings. It should be noted that this embodiment is based on the present technical solution and provides detailed implementation methods and specific operation processes, but the protection scope of the present invention is not limited to this embodiment.

[0043] This embodiment provides an evacuation simulation method based on a fire evacuation model that considers guiding factors. Based on a cellular automata model, it constructs a fire evacuation model that considers guiding factors and fire factors.

[0044] Cellular automata (CA) is a microscopic model in which spatial interactions and temporal causality are localized grid dynamics.

[0045] In the method of this embodiment, such as Figure 1 As shown, the building space is divided into a uniform grid, and a two-dimensional cellular space structure with a square grid is selected. The cell size is set to 0.4m × 0.4m, and the most commonly used Moore type is selected as the neighbor type. The cells can move in eight directions. Figure 2 As shown, the boundaries are evacuation walls and safety exits.

[0046] Use P ij The probability that cell i (i.e., person) moves from the center to position j is given by the static field strength S. ij and dynamic field strength D ij Decide.

[0047] P ij =Nexp(K S S ij )exp(K D D ij (1-n) ij )ξ ij (1)

[0048] Where N is the normalization factor for the probability, ensuring that ∑P ij =1,K S The weighting coefficient representing the static field strength reflects the intensity of the impact of the location of safety exits on personnel evacuation; K D The weighting coefficients representing the dynamic field strength reflect the intensity of the interaction between people; n ij and ξ ij Describe whether cell i is occupied by a wall or obstacle and whether it is occupied by a pedestrian at this moment, respectively. The specific determination is as follows:

[0049]

[0050]

[0051] This embodiment studies the evacuation simulation of a subway transfer station under a fire scenario. Therefore, it considers the impact of fire factors on personnel evacuation, as well as guidance factors. Thus, based on the above model, the fire field intensity F is introduced. ij and guiding field strength G ij A fire evacuation model considering guiding factors (GF-CA) is proposed:

[0052]

[0053] Among them, K F The weighting coefficient representing the fire intensity reflects the strength of the fire's impact on personnel evacuation; K G The weighting coefficient representing the guiding field strength reflects the intensity of the guiding effect on personnel evacuation; K S K D K F K G These are the influence weight coefficients of each influencing factor, with values ​​ranging from [-1, 1], and satisfying K... S +K D +K F +K G =1.

[0054] Furthermore, the fire started from one point and spread, having a certain range of influence; therefore, R is set. f Let F be the fire limit range, and dis be the shortest distance from cell i to the boundary of the fire area. When the cell is within this range, F ij Greater than 0, otherwise F ij It equals 0.

[0055]

[0056] Fire field strength F ij and the guiding field strength G ij The fire field strength F represents the factors influencing the probability of cell i choosing position j. ij The size is mainly determined by the location of the fire:

[0057]

[0058] Where, d i,f d represents the distance from cell i to the edge of the fire. i,f With F ij They are inversely proportional; when d i,fThe larger the value, the farther cell i is from the fire location, the smaller the fire's impact on it, the smaller the resulting fire field strength, and the greater the probability that cell i will choose location j.

[0059] Guided field strength G ij This mainly includes quantitative analysis of specific indicators and parameters for guidance by signs, broadcasts, and guides.

[0060] (1) Guiding signs

[0061] This embodiment of the method studies the effectiveness of visual guidance sign B1 on evacuees. like Figure 3 As shown, it is mainly related to the field of vision of personnel (D1), the effective range of the location of the sign (D2), and the density of the number of signs (D3).

[0062]

[0063] in, Indicates the radius of a person's field of vision (m); Indicates the effective range coefficient (m) of the indicator sign; Indicates the density coefficient of the indicator sign; This represents the distance (m) between cell i and indicator B1; Indicates the direction of action of the indicator, and is a unit vector.

[0064] (2) Broadcast instructions

[0065] The impact of broadcast guidance B2 on evacuees like Figure 4 As shown, it is mainly related to the subjective reaction characteristics of personnel (D4), the objective characteristics of the environment (D5), and the number of broadcasts (D6).

[0066]

[0067] in, Indicates the characteristic coefficient of subjective reaction of personnel; This indicates the interference factor of the voice alarm system, which is related to the number of broadcasts. Indicates the direction of the broadcast guidance; is a unit vector. The objective characteristics of the current environment are mainly related to visibility and the clarity of the alarm sound:

[0068]

[0069] This represents the visibility coefficient, which ranges from (0,1) and can be obtained using a normal distribution. The lower the visibility, the more effective the broadcast guidance will be for evacuees. The weighting of alarm sound information depends on the sound pressure level and reverberation time at that location.

[0070] (3) Guided by the facilitator

[0071] The influence of guide B3 on evacuees like Figure 5 As shown, it is mainly related to the intensity of the guide's effect (D7), the range of the guide's effect (D8), and the number of guides (D9).

[0072]

[0073] This represents the influence intensity coefficient (N) of the facilitator. This represents the range coefficient (m) of the guide's influence. This indicates the interference factor caused by the facilitator, which is affected by the number of facilitators. This represents the distance (m) between cell i and guide B3; This indicates the direction of the guide's action and is a unit vector.

[0074] In summary, through the analysis and quantification of guiding factors such as signage, broadcast guidance, and human guides, the strength of their effects on evacuees can be determined. Final guiding effect strength The guiding field strength G is the guiding effect with the best effect among the three types of guiding effects. ij That is, the intensity of the guiding effect Size.

[0075]

[0076] In summary, based on the calculated static field strength value S ij Dynamic field strength value D ij Fire field intensity value F ij Guiding field strength value G ij Substituting into formula (2), calculate the cell selection probability P. ij Thus, the evacuation path can be obtained after taking into account guiding factors.

[0077] Example 2

[0078] This embodiment verifies the performance of the fire evacuation model obtained in Example 1 through experiments.

[0079] Evacuation efficiency is calculated using the Optimal Work Efficiency Statistics (OPS) method to measure the overall effectiveness of evacuation and the rationality of evacuation exit allocation. The value ranges from [0,1], with lower values ​​indicating higher escape efficiency.

[0080]

[0081] Where n represents the number of evacuation exits; TET represents the safe escape time (s) of the last person to escape during the evacuation; EET i Let TET represent the passage time (in seconds) of the last survivor to exit the i-th exit, and TET = max{EET} i}, i = 1, 2, ..., n.

[0082] Taking the Shenyang Qingnian Street subway transfer station as an example for verification, the optimal operational efficiency (OPS) values ​​for personnel evacuation before and after applying the improved fire evacuation model were 0.279 and 0.068, respectively. This shows that the evacuation efficiency is significantly improved after considering the guiding factors, proving the effectiveness of the improved fire evacuation model.

[0083] For those skilled in the art, various corresponding changes and modifications can be made based on the above technical solutions and concepts, and all such changes and modifications should be included within the protection scope of the claims of this invention.

Claims

1. An evacuation simulation method based on a fire evacuation model considering guiding factors, characterized in that, The specific process is as follows: The building space is divided into a uniform grid, using a two-dimensional cellular space structure with a square grid. The neighbor type is Moore, allowing cells to move in eight directions. The boundaries are evacuation walls and safety exits. P... ij The probability that cell i moves from the center to position j is given by the static field strength S. ij and dynamic field strength D ij Decide; Based on this, a fire evacuation model considering guiding factors is established as follows: Where N is the normalization factor for the probability, ensuring ΣP ij =1,K S The weighting coefficient representing the static field strength reflects the intensity of the impact of the location of safety exits on personnel evacuation; K D The weighting coefficients representing the dynamic field strength reflect the intensity of the interaction between people; n ij and ξ ij Describe whether cell i is occupied by a wall or obstacle and whether it is occupied by a pedestrian at this moment; K F The weighting coefficient representing the fire intensity reflects the strength of the fire's impact on personnel evacuation; K G The weighting coefficient representing the guiding field strength reflects the intensity of the guiding effect on personnel evacuation; fire field strength F ij and the guiding field strength G ij The fire field strength F represents the factors influencing the probability of cell i choosing position j. ij The magnitude is mainly determined by the location of the fire; the guiding field strength G ij This was primarily achieved through quantitative analysis of signage guidance, broadcast guidance, and guide guidance; Set R f Let F be the fire limit range, and dis be the shortest distance from cell i to the boundary of the fire area. When the cell is within this range, F ij Greater than 0, otherwise F ij Equal to 0: Where, d i,f d represents the distance from cell i to the edge of the fire; i,f With F ij They are inversely proportional; when d i,f The larger the value, the farther cell i is from the fire location, the smaller the fire's impact on it, the smaller the resulting fire field strength, and the greater the probability that cell i will choose location j. K S K D K F K G The value range is [-1, 1], and K satisfies S +K D +K F +K G =1; By calculating the static field strength value S ij Dynamic field strength value D ij Fire field intensity value F ij Guiding field strength value G ij Substituting into formula (2), calculate the cell selection probability P. ij Thus, the evacuation route after taking into account guiding factors is obtained.

2. The method according to claim 1, characterized in that, The cell size is set to 0.4m × 0.4m.

3. The method according to claim 1, characterized in that, n ij and ξ ij The following describes whether cell i is occupied by a wall or obstacle and whether it is occupied by a pedestrian at this moment:

4. The method according to claim 1, characterized in that, The process of quantitative analysis of directional signage guidance is as follows: The effectiveness of visual guidance sign B1 on evacuees is expressed as follows: It is mainly related to the field of vision of personnel (D1), the effective range of the location of the sign (D2), and the density of the number of signs (D3). in, Indicates the radius of a person's field of vision; Indicates the range coefficient of the indicator sign; Indicates the density coefficient of the indicator sign; This represents the distance between cell i and indicator B1; Indicates the direction of action of the indicator, and is a unit vector.

5. The method according to claim 1, characterized in that, The process of quantitatively analyzing broadcast guidance is as follows: The strength of the effect of broadcast guidance B2 on evacuees is expressed as follows: It is mainly related to the subjective reaction characteristics of personnel (D4), the objective characteristics of the environment (D5), and the number of broadcasts (D6): in, Indicates the characteristic coefficient of subjective reaction of personnel; This indicates the interference factor of the voice alarm system, which is related to the number of broadcasts. Indicates the direction of the broadcast guidance; is a unit vector. The objective characteristics of the current environment are mainly related to visibility and the clarity of the alarm sound: This represents the visibility coefficient, which ranges from (0,1) and can be obtained using a normal distribution. The lower the visibility, the more effective the broadcast guidance will be for evacuees. The weighting of alarm sound information depends on the sound pressure level and reverberation time at that location.

6. The method according to claim 1, characterized in that, The process of quantitative analysis of facilitator guidance is as follows: The strength of the influence of guide B3 on evacuees is expressed as follows: It is mainly related to the strength of the guide's effect (D7), the range of the guide's effect (D8), and the number of guides (D9): This represents the coefficient of influence of the guide; This represents the coefficient indicating the scope of the guide's influence. This indicates the interference factor caused by the facilitator, which is affected by the number of facilitators. This represents the distance between cell i and guide B3; This indicates the direction of the guide's action and is a unit vector.

7. The method according to any one of claims 1, 4-6, characterized in that, By quantitatively analyzing the guiding factors, including signage, broadcast guidance, and human guides, the strength of their effects on evacuees was obtained. Final guiding effect strength The guiding field strength G is the guiding effect with the best effect among the three types of guiding effects. ij That is, the intensity of the guiding effect Size:

Images