A simulation method for emotional contagion in sudden public events based on improved SIRS model

Abstract

The application discloses a simulation method for emotional contagion in a sudden public event based on an improved SIRS model, gives a function for quantifying the panic emotion of pedestrians, and gives a calculation method for related time-varying parameters of panic emotion contagion in a crowd based on the contagion mechanism of an infectious disease.The application comprises the following steps: a three-dimensional simulation modeling of a public place with a sudden accident is performed by using a computer simulation software; an emotion function for quantifying the risk perception of pedestrians is proposed, and the emotion values of the pedestrians to be evacuated are randomly set; the emotion states are divided according to the risk perception degrees of the pedestrians; the calculation method for related time-varying parameters of panic emotion contagion in a crowd is determined; an SIRS state transition relationship considering the risk perception and self-emotion regulation of the pedestrians is established; the evacuation speed of the pedestrians under the emotional contagion is determined, and simulation is performed; and the application can reflect the phenomenon that the pedestrians have panic emotions when a sudden event occurs and the panic emotions spread in a crowd, thereby providing decision support for preventing and managing the sudden event, especially simulating the crowd evacuation process after the event and formulating an evacuation scheme.

Description

Technical Field

[0001] This invention relates to the field of personnel evacuation in public safety, and to a simulation method for the emotional contagion of sudden public events based on an improved SIRS (susceptible-infected-recovered-susceptible) model. Background Technology

[0002] In recent years, with the continuous advancement of urbanization in China and the increase in indoor gathering places and activities, the difficulty of emergency evacuation management during emergencies has increased dramatically. During sudden incidents, pedestrians' perception of accident risks can easily lead to panic, anxiety, and other negative emotions, which can quickly spread to the crowd. Furthermore, in a state of high panic, pedestrians tend to act blindly, making it difficult to rationally choose escape routes, which can easily cause congestion, collisions, and stampedes during evacuation, resulting in serious loss of life and property. Therefore, it is necessary to conduct in-depth research on the process of emotional contagion during emergency evacuations and its influencing factors, understand the behavioral patterns of groups under the influence of panic, and take effective intervention strategies to control the spread of panic in a timely manner. This is crucial for improving evacuation efficiency, reducing evacuation time, and ensuring the safety of people's lives and property.

[0003] While some models of mass emotion contagion based on infectious disease mechanisms have emerged, some models classify population states based on disease transmission models (SIR and SIS), directly applying the transformation laws from infectious disease models to the study of emotion contagion in mass events. This approach fails to fully consider the theoretical mechanisms of mass emotion contagion under emergencies, and existing simulations also suffer from poor intuitiveness. A significant challenge lies in how to rationally apply infectious disease mechanisms to the study of mass emotion contagion under emergencies and, in conjunction with current crowd simulation technology, to create intuitive and visual modeling. Therefore, this invention, considering factors such as pedestrians' risk perception and self-emotional regulation, presents a method for calculating relevant time-varying parameters for determining the contagion of panic in crowds. This improves the SIRS emotion contagion model, establishes a corresponding mass emotion contagion model and simulation method, and provides decision support for the prevention and management of emergencies, especially for simulating crowd evacuation processes and formulating evacuation plans. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a simulation method for the contagion of emotions in public emergencies based on an improved SIRS model. This method fully reflects the phenomenon of panic among pedestrians during emergencies and its spread within the crowd, thereby achieving a realistic simulation of the pedestrian evacuation process and providing technical support for realizing a more complete evacuation scenario that considers public panic.

[0005] To achieve the aforementioned objectives, this invention provides a simulation method for the emotional contagion of public emergencies based on an improved SIRS model, comprising the following steps:

[0006] Step S1: Use computer simulation software to create a 3D simulation model of a public place where an emergency may occur.

[0007] The modeling process mainly includes three parts: scene modeling, setting the pedestrian evacuation logic diagram, and setting pedestrian parameters. Scene modeling involves setting the internal structure of the area to be evacuated, the location of the emergency, and the locations of entrances and exits. Pedestrian parameter settings include basic information such as pedestrian age, shoulder width, speed, and gender. All model parameter settings must be based on actual case information to ensure the realism of the simulation.

[0008] Step S2: Propose an emotion function to quantify pedestrian risk perception and randomly set the emotion values ​​of the pedestrians (agents) to be evacuated;

[0009] Faced with sudden external stimuli, individuals with different personality traits exhibit variations in the degree of emotional perception and expression. Therefore, this invention first studies the factors influencing pedestrian panic or behavior during sudden accidents in public areas, finding that pedestrian emergency evacuation emotions differ across age, gender, crowd size, disaster severity, and environmental conditions. To quantify pedestrian panic, this invention introduces an emotion function to characterize the impact of these factors on passenger panic. The formula for calculating the panic value of pedestrians to be evacuated is as follows:

[0010]

[0011] Where E represents the pedestrian's perceived emotional value in response to the emergency, and N represents the number of pedestrians in the area to be evacuated. M Let S represent the pedestrian evacuation area of ​​the total evacuation zone, S represent the disaster-affected area of ​​the public area (e.g., fire), and λ represent the scenario adjustment factor. ω1, ω2, ω3, and ω4 are the weights of the number of people, the degree of impact of the sudden disaster, the age of pedestrians, and gender, respectively. The four weights should be assigned according to the specific actual impact on the evacuation area, and ω1+ω2+ω3+ω4=1. F(g) represents the degree of influence of gender risk perception on panic. F(g) follows a normal function. Compared with men, women's emotions are more easily affected by sudden situations. Considering that in reality, some women may be more rational, or some men may be more emotional, the influence of gender perception on panic is set to follow a normal distribution, which is closer to reality.

[0012] Meanwhile, considering that different pedestrians may not show strong consistency due to differences in their own knowledge, education, and psychological levels, even if they are in the same panic level, there are still differences in their actual emotional values. Therefore, according to the principle of homogeneity, it is assumed that pedestrians of the same type should satisfy "symmetry" and "structural similarity". For convenience, the panic emotional value of the pedestrians to be evacuated is set as a variable subject to normal distribution, so as to set the emotional values of the agents in the simulation.

[0013] Step S3: Divide the emotional states according to the risk perception degree of pedestrians;

[0014] It is set that the total number of people in a public place is N, and then according to the pedestrians' perception of the risk of emotions, they are divided into 3 emotional states: namely, the susceptible state S (Susceptible, normal population), the infected state I (Infected, panicked population), and the immune state R (Recovery, including temporarily immune people who are in a non-panicked state in a short time and completely immune people who are always in a non-panicked state during the event, collectively referred to as immune population).

[0015] Step S4: Determine the calculation method of relevant time-varying parameters for the spread of the panic emotion of the crowd;

[0016] The original SIRS model of the spread of the crowd's emotions describes the phenomenon of emotional infection in the crowd by setting the differential forms of the respective emotional states of the pedestrians. However, due to the lack of analysis of the deep reasons for the spread of pedestrians' emotions, there will still be a certain gap between the simulation results and the actual situation. At the same time, in the original SIRS model, the transition of the emotional states of each group of people is controlled by a fixed forwarding rate, and the driving force of pedestrians' emotional perception is not incorporated into the model, while pedestrians' risk perception of emergencies has an obvious impact on the spread of panic emotions in the crowd. As an important factor promoting the spread of emotions in the crowd, pedestrians' emotional perception needs to be added to the model to correct the simulation results, so as to make the calculation results closer to the actual situation.

[0017] Therefore, the present invention first assumes that the crowd is in a relatively closed state, and the inflow and outflow of the population in the crowd are not considered. At the same time, it is set that β(t) is the emotional dynamic infection rate, a is the general infection factor, γ(t) is the emotional regulation factor, b is the general immune factor, D(t) is the immune loss rate, and c is the exhaustion factor. And 0 < β(t) < 1; 0 < γ(t) < 1; 0 < D(t) < 1. Secondly, the present invention gives the calculation method of the emotional infection rate β(t). This method recognizes that the phenomenon of the spread of emotions in the crowd will change with time, crowd density, and individual cognition. At the same time, it is recognized that an individual will infect his own emotional information to the surrounding individuals and at the same time receive the influence of the emotions of other individuals within the emotional perception radius of this individual. Thus, the emotional dynamic infection rate β(t) is obtained as

[0018]

[0019] Where β(t) represents the probability that a susceptible individual will be infected at time t due to contact with panicked individuals in their vicinity. ρ represents the population density per unit area. d ij Let E be the distance between pedestrian i and pedestrian j, and the emotional contagion process only exists when the distance between them is less than the perception radius R. j Let P be the emotion value of pedestrian j. The more panicked pedestrian j is, the greater the impact on other pedestrians. E This indicates an individual's extroversion; the more extroverted an individual is, the easier it is for them to express their emotions. Males take P. E =0.4, female P E Let the value be 0.6.

[0020] Secondly, besides being influenced by the surrounding pedestrians and their own perception of the sudden event, pedestrians also regulate their panic through their own judgment. Therefore, we introduce the concept of pedestrian judgment to quantify an individual's emotion regulation ability. Since emotion regulation involves adjusting emotions towards a calm state, we characterize the pedestrian's emotion regulation as the pedestrian emotion regulation factor γ(t), whose specific expression is as follows:

[0021]

[0022] Wherein, γ(t) is the emotion recovery rate, which is inversely proportional to the individual's emotion value. The stronger the emotion, the more obvious the weakening effect on emotion regulation. C is the emotion regulation coefficient.

[0023] Then, pedestrians may lose their immunity to panic again due to environmental factors or contact with others. Furthermore, the reasons for this loss of immunity are related to the crowd density of the surrounding environment, the number of panicked individuals nearby, and the individual's probability of developing immunity to panic. Therefore, an immunity loss rate D(t) is defined to characterize this phenomenon. Its calculation method is as follows:

[0024] D(t) = 1 - (1 - b) ρ .

[0025] Where D(t) is the immune loss rate, which represents the probability that an immune person loses their immune capacity against panic at time t due to contact with panicked individuals in the surrounding area.

[0026] Step S5: Establish a SIRS model that considers pedestrians' risk perception and self-emotional regulation.

[0027] By using pedestrian risk perception and self-emotion regulation as quantitative indicators, and dynamically adjusting the passenger's emotional contagion indicator, pedestrian emotional perception and self-emotion regulation are incorporated into the SIRS model. The improved model process is as follows:Figure 1 As shown. The dynamic equations of this model are expressed as follows:

[0028]

[0029] Step S6: Determine the evacuation speed of pedestrians under the influence of emotional contagion and conduct simulation.

[0030] The method for simulating the spread of emotions during public emergencies in this invention can fully reflect the phenomenon of panic among pedestrians during emergencies and its spread among the crowd, thereby achieving a realistic simulation of the pedestrian evacuation process. Attached Figure Description

[0031] Figure 1 This is a flowchart of the improved SIRS group sentiment contagion model.

[0032] Figure 2 It is a model of the school auditorium.

[0033] Figure 3 It is an improved SIRS emotion contagion model diagram.

[0034] Figure 4 This is the flowchart of the running program.

[0035] Figure 5 This is a pedestrian evacuation effect diagram that takes into account the contagion of emotions. Detailed Implementation

[0036] The technical solution will be further explained below with reference to the accompanying drawings.

[0037] like Figure 2 As shown in this implementation example, a university auditorium is used as an example to simulate the emergency evacuation process after a sudden incident occurs while students are attending an academic ceremony in the auditorium. A simulation method for simulating the emotional contagion of public emergencies based on an improved SIRS model includes the following steps:

[0038] Step S1: Use computer simulation software to create a 3D simulation model of a public place where an emergency may occur;

[0039] First, a simulation example is given, using a university auditorium as an example, to simulate the emergency evacuation process after a sudden incident occurs while students are attending an academic ceremony in the auditorium. The scenario is modeled using Anylogic simulation evacuation software, and the specific modeling process is as follows:

[0040] (1) Scene modeling. For example... Figure 2 As shown, the Anylogic simulation evacuation software was used to model the auditorium according to its specific dimensions and size. Simultaneously, tools from the pedestrian database were used to create obstacles (walls, seats, stage) and entrances / exits.

[0041] (2) Draw a pedestrian flow chart. Students will be randomly seated after entering the auditorium. If a sudden disaster occurs during the activity, an emergency evacuation will be initiated immediately. The evacuation process ends when the last pedestrian successfully reaches the exit. Based on the above logic, the flow chart is created using controls in the software. Figure 2 The pedestrian evacuation logic diagram.

[0042] (3) Pedestrian basic parameter settings

[0043] ① Pedestrian shoulder width setting. After consulting "Anthropometric Dimensions of Chinese Adults", it was found that the shoulder width of pedestrians is generally between (0.4m, 0.5m). Therefore, the pedestrian diameter was set to uniform(0.4, 0.5)m for example simulation.

[0044] ② Pedestrian evacuation setup. Students in the auditorium were arranged into nine zones, with a total evacuation target of 950 people. Subsequently, considering that the spread of panic could be influenced by individual characteristics such as age and gender, the population was divided into six categories based on gender and age: young men, young women, middle-aged men, middle-aged women, elderly men, and elderly women.

[0045] ③ Evacuation Speed ​​Setting. Based on literature review and field research, the following conclusions were drawn: The walking speed of pedestrians in a calm state when escaping a danger zone is approximately 0.6 m / s; the expected speed before panic is triggered is approximately 1 m / s; and the evacuation speed during a panic is no greater than 1.5 m / s, varying from person to person. Therefore, the expected pedestrian speed was set according to the speeds in Table 1.

[0046] Table 1. Pedestrian evacuation speed considering emotional contagion.

[0047]

[0048] Step S2: Calculate the emotion function of pedestrian risk perception. First, set the influence region of a sudden event (such as a fire) to 0.4. Furthermore, age follows an N(0.7, 0.04) distribution, and gender follows an N(0.5, 0.09) distribution. Substitute this into the equation... The different emotional values ​​of various groups of people are obtained and randomly distributed to pedestrians. It is important to note that different pedestrians will not exhibit strong uniformity due to differences in their understanding, education, and psychological state; even if they are at the same level of panic, their actual emotional values ​​will differ. Therefore, based on the principle of homogeneity, it is assumed that pedestrians of the same type should satisfy "symmetry" and "structural similarity." For convenience, the panic emotional values ​​of pedestrians to be evacuated are set as variables that follow a normal distribution, thus setting the emotional values ​​of the agent in the simulation.

[0049] Step S3: Pedestrians are categorized into three emotional states based on their risk perception level. In this part, the proposed emotion contagion model SIRS is built using the system dynamics library in Anylogic.

[0050] The improved SIRS emotion contagion model diagram is shown below. Figure 3 .

[0051] Step S4: Calculate the relevant time-varying parameters of the contagion of panic among the population.

[0052] Step S5: Combining the time-varying parameters related to the contagion of panic in the crowd calculated in Step S4, establish the state transition relationship of SIRS that considers pedestrians' risk perception and self-emotional regulation. See the flowchart for the running procedure. Figure 4 .

[0053] Step S6: Determine the evacuation speed of pedestrians under the influence of emotional contagion, and conduct an evacuation simulation for this case. See simulation results below. Figure 5 .

Claims

1. A simulation method for the contagion of emotions in sudden public events based on an improved SIRS model, characterized in that... Includes the following steps: Step S1: Use computer simulation software to create a 3D simulation model of a public place where an emergency may occur. The 3D simulation model consists of three parts: scene modeling, setting a pedestrian evacuation logic diagram, and setting pedestrian parameters. Scene modeling includes setting the internal structure of the area to be evacuated, the location of the emergency, and the location of entrances and exits. Pedestrian parameter settings include the age, shoulder width, speed, and gender of pedestrians. Step S2: Propose an emotion function to quantify pedestrian risk perception and randomly set the emotion value of the pedestrians to be evacuated; Step S2 includes: Individuals with different personality traits exhibit differences in the degree of emotional perception and expression when faced with sudden external stimuli; the formula for calculating the panic value of pedestrians to be evacuated is as follows: ； in, This represents the pedestrian's perceived emotional state in response to an unexpected situation. This indicates the number of pedestrians in the area to be evacuated. This indicates the pedestrian evacuation of the total evacuation area. Indicates the area affected by the disaster in public areas. Represented as a scene adjustment factor; , , and These are the weights for the number of people, the degree of impact of the sudden disaster, and the age and gender of pedestrians. The weights for these four factors should be assigned based on the specific actual impact on the evacuation area. ; This indicates the degree to which gender-based risk perception influences panic. It conforms to a normal function; Step S3: Classify emotional states according to pedestrians' risk perception levels; Pedestrians are classified into three emotional states based on their risk perception levels: Given a total population of N in a public place, pedestrians are classified into three emotional states based on their perception of risk: S (Susceptible), I (Infected), and R (Recovery). S represents Susceptible (normal population); I represents Infected (panicked population); R represents Recovery, including temporarily immune individuals who are not in a panicked state for a short period and completely immune individuals who remain in a non-panicked state throughout the event, collectively referred to as the immune population. Step S4: Determine the calculation method for relevant time-varying parameters related to the contagion of panic among the population; In step S4, a method for calculating the time-varying parameters related to the contagion of panic among two groups is given, as follows: First, assume the population is in a relatively closed state, and do not consider the inflow and outflow of people within the population, while setting it as follows: Emotional dynamic infection rate, where 'a' represents general infectious agents. be is a mood regulator, and be is a general immune factor. Let be the immune loss rate, and c be the exhaustion factor; and 0 < 1. <1;0< <1;0< <1; Secondly, the emotional contagion rate is given. The calculation method is used to derive the dynamic infection rate of emotions. for ; in, This represents the probability that a susceptible individual at time t will be infected through contact with panicked individuals in their vicinity. Indicates the population density of a unit area; Let be the distance between pedestrian i and pedestrian j, and only if the distance between them is less than the perception radius. Emotional contagion only occurs at certain times; Let j be the emotion value of pedestrian j. The more panicked the pedestrian j is, the greater the impact on other pedestrians. This indicates an individual's extroversion; if an individual is more extroverted, their emotions are more easily expressed. (Male is considered more likely to be an extrovert.) =0.4, female Set the value to 0.6; Secondly, the emotional regulation role of pedestrians is characterized as pedestrian emotional regulation factors. Its specific expression is as follows: ； in, The emotional recovery rate is inversely proportional to the individual's emotional value; the stronger the emotion, the more pronounced the weakening effect on emotional regulation. This is the emotion regulation coefficient; Then, pedestrians will lose their immunity to panic again due to factors such as the environment or contact with others; Set the immune loss rate To characterize the above phenomenon; its calculation method is as follows: ； in, The immune loss rate represents the probability that an immune person at time t will lose their immunity to panic due to contact with panicked individuals in the surrounding area. Step S5: Establish a state transition relationship for SIRS that takes into account pedestrians' risk perception and self-emotional regulation; Step S6: Determine the evacuation speed of pedestrians under the influence of emotional contagion and conduct simulation.

2. The simulation method for emotion contagion in public emergencies based on an improved SIRS model as described in claim 1, characterized in that: In step S5, an improved SIRS emotion contagion model is presented; the dynamic equation of this model is expressed as follows: 。

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