Large-scale subway group escape system based on panic emotion infection

Abstract

The invention discloses a large-scale subway group escape system based on panic emotion infection, and relates to the technical field of escape systems.The large-scale subway group escape system based on panic emotion infection comprises the steps that 1, a crowd evacuation scene is constructed according to subway related information; step 2, initializing a crowd (Crowd); each individual in the crowd Crowd comprises personality characteristics phi, an initial emotion value e0 and an initial movement speed v0; 3, performing an emotion infection simulation algorithm; step 4: first; the range between the pedestrian carrying the luggage and the luggage is divided to be less than or equal to 0.5 m; carrying out related weighting and improvement on the evacuation speed and behavior of pedestrians according to the luggage volume and the luggage weight when the luggage volume and the luggage weight exceed the individual bearing capacity; a discarding behavior will occur; 5, calculating the crowd density rho of the walking area at the t + 1 moment according to the crowd movement information; the crowd evacuation behavior is updated; and step 6, realizing crowd evacuation visualization in a graphical mode.

Description

Technical Field

[0001] The present invention relates to the technical field of escape systems, and particularly to a large-scale subway group escape system based on panic emotion contagion. Background Art

[0002] With the acceleration of the urbanization process and the increase in the urban population scale, the subway has become the primary mode of travel for pedestrians. At the same time, road traffic congestion is becoming increasingly serious, the subway passenger flow is increasing day by day, and trampling incidents occur frequently. Therefore, it is crucial to simulate the crowd evacuation behavior in subway emergencies. Through computational and group simulation technologies, combined with group animation and visual analysis technologies, the evacuation behavior of the crowd can be further explored. This helps to quickly evacuate the crowd to a safe haven, reduce the occurrence of trampling accidents, and provide effective references for building planners. It has very important research significance in various fields such as urban public safety, virtual reality, and transportation.

[0003] Emotion is an internal factor affecting crowd evacuation. Emotion contagion is achieved by assigning different personality characteristics to individuals and applying different emotion contagion models. Its essence is the communication and transmission of emotions. In addition, emotion contagion has a great impact on an individual's emotions, behaviors, and decisions in specific situations. For example, during an emergency evacuation in a fire, emotion contagion will intensify panic and prompt individuals to take immediate action. In particular, negative emotions have a greater negative impact on crowd evacuation. The large-scale spread of panic emotions will lead to crowd congestion, pushing, and a significant increase in the incidence of trampling and other situations. However, most traditional crowd evacuation behaviors focus on path planning and collision avoidance, and it is difficult to visualize and simulate the movement of real-world crowds. Therefore, in the process of visualizing and simulating the movement of crowds facing subway safety, their inherent personalities and emotion contagion are also important factors that need to be considered.

[0004] Carry-on luggage hinders the flow of pedestrians to some extent. First, speed. Pedestrians carrying luggage or suitcases walk slower than normal pedestrians, whether on the platform, stairs, or slopes. Laxman et al. pointed out in 2010 that the walking speed of pedestrians carrying luggage decreased to about 85% of the normal level. Secondly, luggage occupies space, which may make the crowd evacuation more crowded and even cause blockages. Thirdly, Devroey et al. (2007) conducted research from a biomechanical perspective and found that carrying a load of 10% or more would cause significant changes in the body's physiological responses. Therefore, in-depth understanding of the impact of luggage on pedestrian evacuation helps to provide suggestions for the design of relevant pedestrian facilities and improve traffic efficiency.

[0005] In summary, we propose a visualization method for crowd evacuation based on panic emotions. Incorporate emotional contagion into the evacuation of people with and without luggage, and explore the evacuation behaviors of pedestrians with different personality traits when carrying or not carrying luggage during subway emergency evacuations. And the specific impact of panic emotion contagion on such behaviors. Summary of the Invention

[0006] The purpose of the present invention is to solve at least one of the technical problems existing in the prior art, and provide a large-scale subway group escape system based on panic emotion contagion, which can solve the above problems.

[0007] To achieve the above object, the present invention provides the following technical solutions: A large-scale subway group escape system based on panic emotion contagion, including the following specific steps. Step 1: Construct a crowd evacuation scenario according to subway-related information;

[0008] Step 2: Initialize the crowd Crowd; each individual in the crowd Crowd includes personality trait φ, initial emotion value e 0 and initial movement speed v 0 ;

[0009] Step 3: Emotion infection simulation algorithm;

[0010] Input the agents in the scenario;

[0011] Output the emotion intensity of the agent;

[0012] Step 1 For all agents, if the emotion intensity p of the agent < 1, find the neighbors around the agent;

[0013] Step 2 For the neighbors of the agent, if the emotion intensity of the agent is less than the emotion intensity of the neighbor, update the emotion intensity of the agent;

[0014] Step 3 For all agents in the scenario, if the emotion intensity p of the agent > 1, update the emotion intensity to 1;

[0015] Step 4 End;

[0016] In the emotion intensity update algorithm, consider two major factors, personality and distance, the emotion intensity at time t + 1

[0017]

[0018] Step 4: First; the range between the pedestrian carrying luggage and the luggage is divided into ≤ 0.5 m. Second; according to the luggage volume and luggage weight, the evacuation speed and behavior of the pedestrian are weighted and improved. When the luggage volume and weight exceed the personal bearing capacity; a discard behavior will occur;

[0019] Step 5: Calculate the crowd density ρ of the feasible walking area at time t+1 based on the crowd movement information; and update the crowd evacuation behavior.

[0020] In the said Step 4, based on the relevant information of the crowd density, individuals will have behaviors of discarding luggage or turning back to look for luggage. Specifically:

[0021] 4.1 According to the regulations of urban rail transit, the total weight that passengers can carry does not exceed 30 kg. Therefore, the weight of the luggage is 5 kg to 30 kg. When the luggage weight > 15 kg or the luggage volume is above medium-sized luggage, pedestrians will have the behavior of discarding.

[0022] 4.2 According to the relevant information of the crowd density, when the crowd density reaches medium level or above, the behavior of discarding will occur.

[0023] 4.3 Based on the combination of the weight and volume of the carried luggage and the crowd density information, when the pedestrian density is below medium level, the luggage weight < 15 kg, and the volume is small or medium-sized luggage, pedestrians will have the behavior of turning back. When any condition does not meet, the behavior of turning back will not occur. In addition, according to the situations in 4.1 and 4.2, when any one of the two conditions is satisfied, the behavior of discarding will occur.

[0024] Step 6: Realize the visualization of crowd evacuation in a graphical way.

[0025] Preferably, in the said Step 2, the personality characteristics of individual j are defined according to the OCEAN model as:

[0026] φ = [φ O , φ C , φ E , φ A , φ N

[0027] Where φ O is openness; φ C is conscientiousness; φ E is extraversion; φ A is agreeableness; φ N is neuroticism, and each dimension of the personality component follows a Gaussian distribution.

[0028] Preferably, in the said Step 3, p i (t) is the emotional intensity of agent i at time t;

[0029] G(i, j) represents the influence of personality on emotion:

[0030]

[0031] ​Preferably, in step 3, δ i is the reception ability of agent i, and the reception abilities of agents with different personalities are different.

[0032] Preferably, in step 3, ε j is the transmission ability of agent j; agent j is the agent among the neighbor agents with an emotional intensity p i < p j .

[0033] Preferably, in step 3, m is the number of agents among the neighbor agents with p i < p j ;

[0034] d ij represents the Euclidean distance between agent i and j;

[0035] d max represents the emotional infection radius (d max ∈[0,10]);

[0036] D(i, d) represents the influence of distance on emotion:

[0037]

[0038] Where:

[0039] ‖r i -r d ‖ represents the distance between agent i and the hazard source d;

[0040] R represents the radius of the agent itself (R ∈ (0, 0.5]).

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] 1. This large-scale subway group evacuation system based on panic emotion contagion is different from traditional crowd evacuation behaviors. The present invention effectively considers the internal trait during the crowd evacuation process, that is, emotion contagion. Traditional crowd evacuation visualization methods achieve crowd evacuation visualization by calculating the attraction, repulsion, etc. received by individuals. Such methods cannot truly reflect the movement changes of individuals when simulating crowd evacuation. Since individual evacuation is affected by psychological states, the present invention constructs individual emotion contagion behaviors to plan evacuation behaviors for individuals, making the crowd evacuation results more realistic.

[0043] 2. The large-scale subway crowd evacuation system based on panic emotion contagion. The present invention effectively considers the problem of pedestrians carrying luggage during evacuation in the real world. Traditional crowd evacuation methods do not consider the problem of pedestrians carrying items and only discuss the individual itself. However, in the real world, there are more pedestrians carrying items. Therefore, the present invention constructs a method for the evacuation behavior of relevant crowds, making it more realistic.

[0044] 3. The large-scale subway crowd evacuation system based on panic emotion contagion. The present invention ensures the efficiency of crowd evacuation. Traditional crowd evacuation behaviors do not consider whether there are behaviors of discarding or searching when carrying items, and such behaviors may affect the efficiency of crowd evacuation. On the basis of the original research, the present invention constructs relevant discarding and searching behaviors and formulates relevant plans according to crowd density and luggage-carrying situations, ensuring the efficiency of individual behaviors in crowd evacuation. In addition, the present invention also considers two emergency scenarios of fire and flood, more comprehensively improving the situation of crowd emergency evacuation. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The present invention will be further described below in conjunction with the drawings and embodiments:

[0046] Figure 1 It is the overall working flow chart of the method of the present invention;

[0047] Figure 2 It is the initial interface selection diagram of the method of the present invention;

[0048] Figure 3 It is the initial environmental scene diagram of the method of the present invention;

[0049] Figure 4 It is the schematic diagram of flood crowd initialization of the method of the present invention;

[0050] Figure 5 It is the schematic diagram of fire crowd initialization of the method of the present invention;

[0051] Figure 6 It is the schematic diagram of emotion contagion of the method of the present invention;

[0052] Figure 7 It is the schematic diagram of the crowd carrying luggage of the method of the present invention;

[0053] Figure 8 It is the schematic diagram of the crowd discarding luggage and turning back to search for luggage of the method of the present invention;

[0054] Figure 9 It is the schematic diagram of the end of crowd evacuation of the method of the present invention;

[0055] Figure 10 It is the schematic diagram of the panic degree of group escape of the method of the present invention

[0056] Figure 11 Schematic diagram of the number of people escaping in groups by the method of the present invention. Specific implementation manners

[0057] This part will describe in detail the specific embodiments of the present invention. The preferred embodiments of the present invention are shown in the drawings. The function of the drawings is to supplement the description in the text part of the specification, enabling people to intuitively and vividly understand each technical feature and the overall technical solution of the present invention. However, it should not be construed as a limitation on the protection scope of the present invention.

[0058] In the description of the present invention, it should be understood that for the orientation description, such as the orientation or positional relationship indicated by up, down, front, back, left, right, etc., is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation on the present invention.

[0059] In the description of the present invention, greater than, less than, exceeding, etc. are understood as not including the number itself, and above, below, within, etc. are understood as including the number itself. If there is a description of first and second, it is only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence relationship of the indicated technical features.

[0060] In the description of the present invention, unless otherwise clearly defined, words such as setting, installing, connecting, etc. should be understood in a broad sense. Those skilled in the art can reasonably determine the specific meanings of the above words in the present invention in combination with the specific content of the technical solution.

[0061] Please refer to Figures 1-11 , the present invention provides a technical solution: a large-scale subway crowd evacuation system based on panic emotion contagion, to solve the deficiencies of the existing crowd evacuation visualization methods, especially for the evacuation of people carrying luggage. The present invention provides an evacuation visualization method based on emotion contagion and people carrying luggage, considering the panic emotion contagion, crowd density, luggage weight and luggage volume during the crowd evacuation process, and conducting relevant quantification and analysis for these factors, making the effect more real and accurate, conforming to the real-world crowd evacuation situation, and providing an effective visualization tool for fields such as urban public safety, large building dormitories, and emergency drills;

[0062] The large-scale subway crowd evacuation system based on panic emotion contagion includes the following specific steps. Step 1: Construct a crowd evacuation scenario according to the relevant subway information;

[0063] Step 2: Initialize the crowd Crowd; each individual in the crowd Crowd includes personality trait φ, initial emotion value e 0 and initial movement speed v0 ; Among them, the personality characteristics of individual j are defined according to the OCEAN model as:

[0064] φ = [φ O , φ C , φ E , φ A , φ N

[0065] Among them, φ O is openness; φ C is conscientiousness; φ E is extraversion; φ A is agreeableness; φ N is neuroticism, and each dimension of the personality component follows a Gaussian distribution;

[0066] Step 3: Emotional contagion simulation algorithm;

[0067] Input the agents in the scenario;

[0068] Output the emotional intensity of the agents;

[0069] Step 1 For all agents, if the emotional intensity p of the agent < 1, find the neighbors around the agent;

[0070] Step 2 For the neighbors of the agent, if the emotional intensity of the agent is less than that of the neighbor, update the emotional intensity of the agent;

[0071] Step 3 For all agents in the scenario, if the emotional intensity p of the agent > 1, update the emotional intensity to 1;

[0072] Step 4 End;

[0073] In the emotional intensity update algorithm, consider two major factors of personality and distance. The emotional intensity at time t + 1

[0074]

[0075] Among them; p i (t) is the emotional intensity of agent i at time t;

[0076] G(i, j) represents the influence of personality on emotion:

[0077]

[0078] Among them:

[0079] δ i is the reception ability of agent i, and agents with different personalities have different reception abilities (as shown in the following table);​

[0080]

[0081] ε j is the sending ability of agent j; agent j is the agent with emotional intensity p among the neighbor agents i <p j whose occurrence ability is the same (emotional intensity is as shown in the following table)

[0082]

[0083] m is the number of p i <p j agents among the neighbor agents;

[0084] d ij represents the Euclidean distance between agent i and j;

[0085] d max represents the emotional infection radius (d max ∈[0,10]);

[0086] D(i, d) represents the influence of distance on emotion:

[0087]

[0088] where:

[0089] ‖r i -r d ‖ represents the distance between agent i and the hazard source d;

[0090] R represents the radius of the agent itself (R ∈ (0, 0.5]);

[0091] Step 4: First, the range between the pedestrian carrying luggage and the luggage is divided into ≤ 0.5 m. Second, the evacuation speed and behavior of the pedestrian are weighted and improved according to the luggage volume and weight. When the luggage volume and weight exceed the individual's bearing capacity, a discard behavior will occur;

[0092] Step 5: Calculate the crowd density ρ of the feasible walking area at time t + 1 according to the crowd movement information; and update the crowd evacuation behavior;

[0093] Furthermore, in the said Step 4, according to the relevant information based on the crowd density, individuals will have behaviors of discarding luggage or turning back to look for luggage; specifically:

[0094] 4.1 According to the "Rules for Taking Urban Rail Transit", the total weight that passengers can carry shall not exceed 30 kg. Therefore, the weight of the luggage is 5 kg to 30 kg. When the luggage weight > 15 kg or the luggage volume is above medium-sized luggage, pedestrians will discard it.

[0095] 4.2 According to the relevant information on crowd density, when the crowd density reaches medium level or above, there will be a discard behavior.

[0096] 4.3 Based on the weight and volume of the carried luggage, and combined with the crowd density information, when the pedestrian density is below medium level, the luggage weight < 15 kg, and the volume is small or medium-sized luggage, pedestrians will show a turning-back behavior. When any condition does not meet, there will be no turning-back behavior. In addition, according to the situations in 4.1 and 4.2, when any one of the two conditions is met, there will be a discard behavior.

[0097] Step 6: Realize the visualization of crowd evacuation in a graphical way.

[0098] Furthermore, to verify the effectiveness of the present invention, the present invention uses experiments to confirm the results:

[0099] In this experiment, the emergency scenario is specified as a subway station fire, the crowd density is set at a low density level, the initial infectors account for 10% of the group, and the people carrying luggage account for 10% of the group; the personality traits are evenly divided; small luggage accounts for 50%, medium-sized luggage accounts for 30%, and large luggage accounts for 10%; low-weight luggage accounts for 50%, medium-quality luggage accounts for 30%, and high-weight luggage accounts for 20%.

[0100] Randomly generate a random seed number and click start to conduct the experiment.

[0101] As shown in the Figure 10 schematic diagram of the panic degree of group evacuation, when, the average panic degree of the group increases to the maximum panic degree. In addition, Figure 11 The schematic diagram of the number of people escaping from the group shows that this time node is also the point where the number of people escaping increases the most (i.e., the slope is the largest), and the growth rate of the number of people escaping continuously increases when, and the growth rate decreases when.

[0102] Furthermore, different from the traditional crowd evacuation behavior, the present invention effectively considers the internal trait in the crowd evacuation process, that is, emotional contagion. The traditional crowd evacuation visualization method realizes crowd evacuation visualization by calculating the attraction, repulsion, etc. received by individuals. Such a method cannot truly reflect the movement changes of individuals when simulating crowd evacuation. Since individual evacuation is affected by the psychological state, the present invention constructs an individual emotional contagion behavior to plan evacuation behavior for individuals, making the crowd evacuation result more realistic.

[0103] Furthermore, the present invention effectively considers the problem of pedestrians carrying luggage during evacuation in the real world. Traditional crowd evacuation methods do not consider the problem of pedestrians carrying items and only discuss the individuals themselves. However, in the real world, there are more pedestrians carrying items. Therefore, the present invention constructs a method for crowd evacuation behavior, making it more realistic.

[0104] Furthermore, the present invention ensures the efficiency of crowd evacuation. Traditional crowd evacuation behaviors do not consider whether there are behaviors of discarding or searching when carrying items, and such behaviors may affect the crowd evacuation efficiency. On the basis of the original research, this study constructs relevant discarding and searching behaviors and formulates relevant plans according to the crowd density and the situation of carrying luggage, ensuring the efficiency of individual behaviors in crowd evacuation. In addition, the present invention also considers two emergency scenarios of fire and flood, more comprehensively improving the situation of crowd emergency evacuation.

[0105] Furthermore, the present invention designs a visualization method and system for the evacuation of people based on emotional contagion and people carrying luggage, considering two scenarios of fire and flood. First, use subway-related information to initialize the crowd evacuation scenario. Second, simulate the behavior of individuals carrying luggage for evacuation according to the volume and weight of the luggage carried by pedestrians in the real world; assign inherent personality traits to all individuals and update the emotions of individuals according to the development of emergency events and personality traits; construct a method for updating the speed of pedestrians based on emotional contagion, and improve the crowd evacuation behavior in combination with the crowd density situation in relevant areas and the portability of carrying luggage, improving the evacuation efficiency. This method makes the visualization effect of crowd evacuation more in line with the real situation and is expected to provide a flexible and controllable visualization tool for fields such as urban public safety, building planning, and emergency drills.

[0106] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge scope of those of ordinary skill in the art.

Claims

1. A large-scale subway group escape system based on panic contagion, characterized by: It includes the following specific steps: Step 1: construct a crowd evacuation scenario based on subway-related information; Step 2: Initialize the crowd; each individual in the crowd includes personality traits φ, initial emotion value e 0 and initial velocity v 0 ; Step 3: Emotional contagion simulation algorithm; Enter the agent in the scene; Output the agent's emotional intensity; Step 1: For all agents, if the agent's emotion intensity p < 1, find the neighbors around the agent; Step 2: For the agent's neighbors, if the agent's emotional intensity is less than that of its neighbors, update the agent's emotional intensity; Step 3: For all agents in the scene, if the agent's emotion intensity p>1, update the emotion intensity to 1; Step 4 ends; In the emotion intensity update algorithm, the emotion intensity at time t+1 is considered based on two factors: personality and distance. Step 4: First, the distance between the pedestrians carrying luggage and the luggage is divided into ≤0.5m. Secondly, the evacuation speed and behavior of pedestrians are weighted and improved according to the luggage volume and weight. When the luggage volume and weight exceed the individual's tolerance, the pedestrians will abandon the luggage. Step 5: Calculate the crowd density ρ in the walkable area at time t+1 based on the crowd movement information; and update the crowd evacuation behavior; In step 4, based on the relevant information based on the crowd density, individuals may abandon their luggage or return to look for their luggage. Specifically, 4.1 According to the rules of urban rail transit, the total weight that passengers can carry does not exceed 30kg. Therefore, the weight of luggage is: 5kg to 30kg. When the weight of luggage is greater than 15kg or the volume of luggage is larger than medium-sized luggage, pedestrians will abandon it; 4.2 According to the crowd density related information; when the crowd density reaches medium or above, the discard behavior will occur; 4.3 Based on the weight and volume of luggage carried and crowd density information; when the pedestrian density is below medium; When the luggage weight is less than 15kg and the volume is small or medium-sized, the pedestrian will turn back. If any of the conditions are not met, there will be no turning back. In addition, according to the situations in 4.1 and 4.2, the abandonment behavior will occur when any of the two conditions are met. Step 6: Visualize crowd evacuation in a graphical way.

2. The large-scale subway group escape system based on panic infection according to claim 1 is characterized by: In step 2, the personality characteristics of individual j are defined according to the OCEAN model as: φ=[φ O ,f C ,f E ,f A ,f N ] where φ O is openness; C Is a sense of responsibility; E is extroversion; φ A is affinity; N is neuroticism, and each dimension of the personality component follows a Gaussian distribution.

3. The large-scale subway group escape system based on panic infection according to claim 1 is characterized by: In step 3, p i (t) is the emotional intensity of agent i at time t; G(i,j) represents the influence of personality on emotions:

4. The large-scale subway group escape system based on panic contagion according to claim 1 is characterized by: In step 3, δ i is the receiving capability of agent i, and agents with different personalities have different receiving capabilities.

5. The large-scale subway group escape system based on panic contagion according to claim 1 is characterized by: In step 3, ε j is the sending capability of agent j; agent j is the emotion intensity p among neighboring agents i <p j agent, (whose ability to occur is consistent) (emotional intensity is shown in the following table).

6. The large-scale subway group escape system based on panic contagion according to claim 1 is characterized by: In step 3, m is the number of neighbor agents p i <p j Number of agents; d ij represents the Euclidean distance between agents i and j; d max represents the emotional contagion radius (d max ∈[0,10]); D(i,d) represents the effect of distance on emotion: in: ‖r i -r d ‖ represents the distance between agent i and hazard source d; R represents the radius of the agent itself (R∈(0,0.5]).

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