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Helbing proposed a model based on physics using a particle system and socio-psychological forces in order to describe human crowd behavior in panic situation, this is now called the Helbing Model. His work is based on how the average person would react in a certain situation. Although this is a good model, there are always different types of people present in the crowd and they each have their own individual characteristics as well as how they act in a group structure. For instance, one person may not react to a panic situation, while another may stops walking and interfere in the crowd dynamics as a whole. Furthermore, depending on the group structure, the individual action can change because the agent is part of a group, for example, returning to a dangerous place in order to rescue a member of that group. Helbing's model can be generalized incorporating individualism, as proposed by Braun, Musse, Oliveira and Bodmann.

Helbing proposed a model based on physics using a particle system and socio-psychological forces in order to describe human crowd behavior in panic situation, this is now called the Helbing Model. His work is based on how the average person would react in a certain situation. Although this is a good model, there are always different types of people present in the crowd and they each have their own individual characteristics as well as how they act in a group structure. For instance, one person may not react to a panic situation, while another may stops walking and interfere in the crowd dynamics as a whole. Furthermore, depending on the group structure, the individual action can change because the agent is part of a group, for example, returning to a dangerous place in order to rescue a member of that group. Helbing's model can be generalized incorporating individualism, as proposed by Braun, Musse, Oliveira and Bodmann.

Helbing 提出了一个基于物理学的模型，使用粒子系统和社会心理力量来描述人群在恐慌情况下的行为，这个模型现在被称为 Helbing 模型。他的工作基于普通人在特定情况下的反应。虽然这是一个很好的模式，但是在人群中总是有不同类型的人，他们每个人都有自己的个性以及他们在群体结构中的行为方式。例如，一个人可能不会对恐慌情况做出反应，而另一个人可能会停下脚步，干扰整个人群的动态。此外，取决于群体结构，个体行为可能会发生变化，因为主体是群体的一部分，例如，为了拯救该群体的一个成员而返回到一个危险的地方。海尔宾的模式可以是由布劳恩、缪斯、奥利维拉和博德曼提出的广义合并个人主义。

Helbing 提出了一个基于物理学的模型，使用粒子系统和社会心理力量来描述人群在恐慌情况下的行为，这个模型现在被称为'''Helbing 模型 Helbing Model''''。他的工作基于在特定情况普通人如何反应。虽然这是一个很好的模式，但是在人群中总是有不同类型的人，他们每个人都有自己的个人特点和在群体结构中的行为方式。例如，一个人可能不会对恐慌情境做出反应，而另一个人可能会停下脚步并干扰整个人群的运动。此外，依赖群体结构个体行为可能会发生变化，因为个体是群体的一部分。例如，为了拯救该群体的一个成员而返回到一个危险的地方。如Braun, Musse, Oliveira 和 Bodmann 提出的那样，Helbing 的模型可以概括为'''合并个人主义incorporating individualism'''。

In order to tackle this problem, individuality should be assigned to each agent, allowing to deal with different types of behaviors. Another aspect to tackle this problem is the possibility to group people, forming these group causes people to change their behavior as a function of part of the group structure. Each agent (individual) can be defined according to the following parameters:

In order to tackle this problem, individuality should be assigned to each agent, allowing to deal with different types of behaviors. Another aspect to tackle this problem is the possibility to group people, forming these group causes people to change their behavior as a function of part of the group structure. Each agent (individual) can be defined according to the following parameters:

为了解决这个问题，应该给每个代理分配个性，允许处理不同类型的行为。解决这个问题的另一个方面是把人们分组的可能性，形成这样的群体会使人们作为群体结构的一部分而改变他们的行为。每个代理(个体)可以根据以下参数定义:

每个主体(个体)可以根据以下参数定义:

  Id – Agent identifier

  Id – Agent identifier

# IdFamily – Identifier of the family. A family is a predefined group formed by agents who know each other

# IdFamily – Identifier of the family. A family is a predefined group formed by agents who know each other

  IdFamily – Identifier of the family. A family is a predefined group formed by agents who know each other

  IdFamily – Identifier of the family. A family is a predefined group formed by agents who know each other

# DE – Dependence level of the agent which mimics the need for help. Values [0,1]

# DE – Dependence level of the agent which mimics the need for help. Values [0,1]

  DE – Dependence level of the agent which mimics the need for help. Values [0,1]

  DE – Dependence level of the agent which mimics the need for help. Values [0,1]

De-代理的依赖级别，模拟对帮助的需求。值[0,1]

De：主体的'''依赖水平Dependence level'''，用来模拟主体对他人帮助的需求。取值范围：[0,1]

# AL – Altruism level representing the tendency to help other agents. Values [0,1]

# AL – Altruism level representing the tendency to help other agents. Values [0,1]

  AL – Altruism level representing the tendency to help other agents. Values [0,1]

  AL – Altruism level representing the tendency to help other agents. Values [0,1]

Al-利他主义水平代表了帮助他人的倾向。值[0,1]

AL：'''利他主义水平Altruism Level'''，代表了帮助他人的倾向。取值范围：[0,1]

# v_i – Speed of the agent

# v_i – Speed of the agent

  v_i – Speed of the agent

  v_i – Speed of the agent

To model the effect of the dependence parameter with individual agents, the equation is defined as:

To model the effect of the dependence parameter with individual agents, the equation is defined as:

为了用单个主体模拟相关参数的影响，方程定义为:

为了模拟单个主体的因变量参数的效应（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]） effect: 效应），方程定义为:

  <math>v_i = (1-DE)v_{max}</math>

  <math>v_i = (1-DE)v_{max}</math>

Math v i (1-DE) v { max } / math

<math>v_i = (1-DE)v_{max}</math>

When evaluating the speed of the agent, it is clear that if the value of the dependence factor, DE, is equal to one, then the person would be fully disabled making him unable to move. If the dependence factor is equal to zero, then the person is able to run at his max speed.

When evaluating the speed of the agent, it is clear that if the value of the dependence factor, DE, is equal to one, then the person would be fully disabled making him unable to move. If the dependence factor is equal to zero, then the person is able to run at his max speed.

在评估代理程序的速度时，很明显，如果依赖因子 DE 的值等于1，那么该代理程序员将完全丧失行动能力。如果依赖因子等于零，那么人就能够以他的最大速度跑步。

在评估主体的速度时，很明显，如果依赖因子 DE 的值等于1，则表示该主体完全丧失行动能力。如果依赖因子等于0，那么该主体能够以其最大速度运动。

Group formation is related to the Altruism force which is implemented as an interaction force between two or more agents who are part of the same family. Mathematically, it is described as the following:

Group formation is related to the Altruism force which is implemented as an interaction force between two or more agents who are part of the same family. Mathematically, it is described as the following:

群体形成与利他主义力量有关，利他主义力量是同一家庭中两个或两个以上成员之间的互动力量。从数学上来说，它被描述为:

群组的形成与利他主义力量有关。利他主义力量是同一家族中两个或两个以上成员之间的互动力量。从数学上来说，它被描述为:

  <math>F\overline{a}_i = K\sum \left ( AL_iDE_j \times \left | d_{ij}-d_{ip} \right | \times e_{ij} \right ) </math>

  <math>F\overline{a}_i = K\sum \left ( AL_iDE_j \times \left | d_{ij}-d_{ip} \right | \times e_{ij} \right ) </math>

(AL ide j 乘以左 | d { ij }-d { ip }右 | 乘以 e { ij }右) / math

<math>F\overline{a}_i = K\sum \left ( AL_iDE_j \times \left | d_{ij}-d_{ip} \right | \times e_{ij} \right ) </math>

where:

where:

在哪里:

其中:

: {{math|''d_ij''}} represents the distance between two agents with the origin at the position of the agent;

: {{math|''d_ij''}} represents the distance between two agents with the origin at the position of the agent;

   represents the distance between two agents with the origin at the position of the agent;

   represents the distance between two agents with the origin at the position of the agent;

表示两个代理之间的距离，原点位于代理的位置;

{{math|''d_ij''}}表示两个主体之间的距离，原点设在主体的位置;

: {{math|''d_ip''}} is the distance vector point from the agents to the door's position {{math|''p''}} of the simulation environment;

: {{math|''d_ip''}} is the distance vector point from the agents to the door's position {{math|''p''}} of the simulation environment;

   is the distance vector point from the agents to the door's position  of the simulation environment;

   is the distance vector point from the agents to the door's position  of the simulation environment;

是模拟环境中从代理到门的位置的距离矢量点;

{{math|''d_ip''}}是模拟环境中从主体到门的位置的距离矢量点;

: {{math|''K''}} is a constant;

: {{math|''K''}} is a constant;

   is a constant;

   is a constant;

是一个常数

{{math|''K''}}是一个常数

: {{math|''e_ij''}} is the unitary vector with the origin at position i.

: {{math|''e_ij''}} is the unitary vector with the origin at position i.

   is the unitary vector with the origin at position i.

   is the unitary vector with the origin at position i.

Consequently, the greater the parameter  of agent , the bigger will be  which points to the agent  and has the high level of . When both agents are close enough to each other, the one with high  (agent  in this example) adopts the value of agent  (<math>DE_j = DE_i</math>). This means that the evacuation ability of agent  is shared with agent  and both start moving together.

Consequently, the greater the parameter  of agent , the bigger will be  which points to the agent  and has the high level of . When both agents are close enough to each other, the one with high  (agent  in this example) adopts the value of agent  (<math>DE_j = DE_i</math>). This means that the evacuation ability of agent  is shared with agent  and both start moving together.

因此，智能体的参数越大，指向智能体的参数就越大，具有较高的智能体水平。当两个代理彼此足够接近时，具有较高值的代理(本例中的代理)采用代理的值(math DE j DE i / math)。这意味着主体的撤离能力是与主体共享的，两者一起开始移动。

因此，主体{{math|''i''}}的利他主义水平{{math|''AL_i''}}越高，指向主体{{math|''j''}}的{{math|''Fā_i''}}就越大，{{math|''j''}}也具有较高的依赖水平{{math|''DE_j''}}。当两个代理彼此足够接近时，具有较高以来水平的主体(本例中的主体{{math|''j''}})就采用主体{{math|''i''}}依赖水平(<math>DE_j = DE_i</math>)。这意味着主体{{math|''i''}}与主体{{math|''j''}}共享撤离能力，两者一起开始移动。

By using these applying these equations in model testing using a normally distributed population, the results are fairly similar to the Helbing Model.

By using these applying these equations in model testing using a normally distributed population, the results are fairly similar to the Helbing Model.

通过将这些方程应用于正态分布总体的模型试验，结果与 Helbing 模型非常相似。

通过将这些方程应用于模型试验并采取正态分布的总体，结果与 Helbing 模型非常相似。

The places where this would be helpful would be in an evacuation scenario. Take for example, an evacuation of a building in the case of a fire. Taking into account the characteristics of individual agents and their group performances, determining the outcome of how the crowd would exit the building is critically important in creating the layout of the building.

The places where this would be helpful would be in an evacuation scenario. Take for example, an evacuation of a building in the case of a fire. Taking into account the characteristics of individual agents and their group performances, determining the outcome of how the crowd would exit the building is critically important in creating the layout of the building.

 

 

=== Leader behavior during evacuation simulations ===

=== Leader behavior during evacuation simulations ===