JP6679644B2 - Simulator, simulation method and action determination device - Google Patents

Description

  The present invention relates to a simulator that predicts a behavior of a crowd, a simulation method, and a behavior determination device that determines the behavior of an individual person who is one of the individuals that make up the crowd.

  In a public space where many people gather, it is necessary to investigate the mechanism of crowd behavior during a disaster in order to properly guide the crowd or to design a safe space so that the disaster will not expand or panic during a disaster. There is. Therefore, there is a method of using a simulator that simulates the behavior of a crowd.

  One of the explanations for the irrational behavior of the crowd in times of disaster is coherent behavior due to cognitive bias, and research has been conducted by approaching it as a leader-follower problem. The approach as a leader-follower problem is that, in a crowd consisting of a leader who decides his own behavior and a follower who decides his own behavior by the behavior of another person, as a result of the influence of individuals, irrational behavior as a crowd This is a modeling-based approach of taking.

  On the other hand, for example, a person who encounters a fire in a public space may participate in a fire extinguishing activity in addition to the evacuation. Generally, an individual constituting a crowd has a plurality of options for the purpose of action.

  For example, in the evacuation behavior prediction system described in Patent Document 1, the self-evacuation class for self-evacuation, self-evacuation disabled class, and facility managers and fire brigade It defined three types of human beings in the caregiver class to assist or rescue humans who could not do so, and predicted human behavior in the event of a fire.

JP, 2006-107231, A

However, in the prior art, the human type remained static during prediction. That is, in the prior art, it was necessary to arbitrarily set the purpose of the action of each individual in the crowd.
Therefore, it was difficult to predict the behavior selection of each individual in the crowd under unknown conditions, and to investigate the conditions under which each individual behavior selection occurred in the crowd.

  For example, in the prior art, the prediction does not include the action selection of each individual in the crowd, such as that a person in the self-evacuation class changes to a person in the caretaker class with the passage of time. From this, for example, when it is assumed that each individual evacuates or extinguishes when a fire occurs, in the conventional technique, the number of individuals extinguishing the fire is set to a certain number or more in order to obtain a simulation result of successful extinction. It is considered that it is necessary to make an arbitrary setting to set the action taken by the majority of individuals to evacuation in order to obtain a simulation result that fails to extinguish the fire.

The present invention has been made in view of the above problems, a simulator, a simulation method, and a behavior that can predict the behavior selection behavior in a crowd under unknown conditions and that can facilitate the investigation of the condition in which the behavior selection occurs in the crowd. An object is to provide a determining device.
In this specification, "crowd" means a group of people, and "crowd" means a group of social organisms including a person.

  In order to achieve such an object, the present invention is a simulator for predicting the behavior of a crowd in a predetermined space capable of achieving a plurality of goals, at least for each of a plurality of individuals constituting the crowd, An individual information storage unit that stores a behavior parameter including a selection purpose selected from the plurality of purposes, an attribute value indicating whether a leader or a follower, and a position in the space; Each time the stimulus value is set, a stimulus value setting unit that sequentially sets a stimulus value that represents the degree of the stimulus that triggers the action to achieve each, and the attribute value of the individual is a follower. A first winning probability for each of the purposes based on the stimulus value for each of the purposes, and a predetermined second value for the individual whose attribute value is a leader. A probability setting unit that sets a selection probability and a lottery with the first winning probability for each of the purposes for the individual for which the first winning probability is set, and change the attribute value of the winning individual to a leader A leader action determination unit that sets the selection purpose of the individual to a selected purpose, and an ambient individual information acquisition unit that extracts a surrounding individual whose position from the individual is within a predetermined distance for each individual, and The attribute value of the individual for which the second winning probability is set is changed to a follower at the second winning probability, and the attribute value is set to the surrounding individual of the individual for the selection purpose of the individual who is the follower. And a follower action determination unit that sets the selection purpose.

  In addition, the leader action determination unit, for the individual for which the first winning probability is set, the maximum first winning probability of the first winning probability for each of the purposes from the second largest first winning probability. Also, it is preferable to perform the lottery with the maximum first winning probability only when the value is higher than the predetermined value.

  Further, the individual information storage unit further stores a reaction threshold value for each of the purposes for each individual, and the probability setting unit, for each of the purposes for each individual, the higher the stimulus value, the higher the reaction It is preferable that the lower the threshold value, the higher the first winning probability is calculated.

  Further, it is preferable that the stimulus value setting unit lowers the stimulus value in accordance with the degree of achievement of one or more of the plurality of purposes.

  Further, it is preferable that the stimulus value setting unit sets the stimulus value for each individual.

  Further, in order to achieve such an object, the present invention is a simulation method for predicting a behavior of a crowd in a predetermined space capable of achieving a plurality of goals, wherein a computer includes a plurality of individuals constituting the crowd. For each of the plurality of purposes, at least a behavior parameter including a selected purpose selected from the plurality of purposes, an attribute value indicating whether a leader or a follower, and a position in the space are stored. A process of sequentially setting a stimulus value indicating the degree of stimulus that triggers the action to achieve each purpose, and each time the stimulus value is set, the attribute value of the individual is a follower A first winning probability is set for each object based on the stimulus value for each object, and the attribute value is a predetermined value for the individual who is the leader. (2) A process of setting a winning probability and a lottery with the first winning probability for each of the purposes is performed on the individual for which the first winning probability is set, and the attribute value of the winning individual is changed to a leader. Along with the process of setting the selection purpose of the individual as a winning target, the process of extracting the surrounding individuals whose position from the individual is within a predetermined distance for each individual, and the second winning probability is set. A process of changing the attribute value of an individual to a follower with the second winning probability and setting the selection purpose set in the surrounding individual of the individual to the selection purpose of the individual whose attribute value is a follower And a simulation method characterized by executing the following.

  Further, in order to achieve such an object, the present invention is a behavior determination device for determining the behavior of one's own individual, which is one of the individuals constituting a crowd in a predetermined space capable of achieving a plurality of objectives, For the own individual, at least an action parameter including a selected purpose selected from the plurality of purposes, an attribute value indicating whether it is a leader or a follower, and individual information that stores a position in the space. A storage unit, a stimulus value acquisition unit that acquires a stimulus value indicating a degree of a stimulus that triggers the action to achieve each of the plurality of purposes, and when the attribute value is a follower. Probability setting that sets a first winning probability for each of the purposes based on the stimulus value for each of the purposes, and sets a predetermined second winning probability when the attribute value is a leader And, when the first winning probability is set, a lottery is performed with the first winning probability for each of the purposes, the attribute value of the winning individual is changed to a leader, and the selection purpose of the individual is won. A leader action determination unit to be set for the purpose, a surrounding individual information acquisition unit for acquiring the actions of surrounding individuals within a predetermined distance from the position of the own individual among the individuals, and the second winning probability is set. And a follower action determining unit that changes the attribute value to a follower with the second winning probability and sets a purpose similar to the behavior of the surrounding individual to the selection purpose, and a behavior determining apparatus. To do.

  According to the present invention, even if the same setting is performed, the purpose of the action in individuals forming the crowd is probabilistically changed. This makes it possible to probabilistically predict the behavioral purpose selection in individuals constituting a crowd under unknown conditions, and facilitate the investigation of the conditions in which the behavioral objectives have been selected in the population constituting individuals.

It is a block diagram which shows the schematic structure of the simulator 1 which concerns on 1st embodiment. It is a functional block diagram of the simulator 1 which concerns on 1st embodiment. 3 schematically illustrates information stored in the environment information storage unit 41. 3 schematically illustrates the information stored in the individual information storage unit 42. 3 schematically illustrates the information stored in the individual information storage unit 42. It is an example of an intermediate prediction result. It is another example of an intermediate prediction result. 3 is a flowchart showing the operation of the simulator according to the first embodiment. It is a flow chart of action determination processing of a simulator concerning a first embodiment.

[First embodiment]
As a first embodiment according to the simulator of the present invention, a fire occurs in a room R having an exit to create a burning area, and a plurality of people (crowds) staying in the room R each have an evacuation action and a fire extinguishing action. An example of the simulator 1 that predicts how to select and execute any of the above is shown. In this example, it is assumed that the action is simplified, the evacuation action is performed by moving to the exit area A ₁ , and the fire extinguishing action is performed by moving to the combustion area A ₂ .
That is, in this embodiment, the space to be simulated (target space) is the room R, the individuals that make up the crowd are people, the event in the target space is a fire, and the purpose of the crowd or individuals is to evacuate. And the fire is extinguished, and the target space can achieve the purpose because of the areas A ₁ and A ₂ .
In addition, the exemplified simulator 1 includes an action determination device which is another aspect of the present invention, and the action determination device sequentially and randomly determines the action of each individual to predict the action of the crowd.

<Structure of Simulator 1>
FIG. 1 is a block diagram showing a schematic configuration of the simulator 1 according to the first embodiment.
The simulator 1 includes an operation input unit 2, a file input / output unit 3, a storage unit 4, a control unit 5, and a display unit 6. Of these, the file input / output unit 3, the storage unit 4, and the control unit 5 can be realized by a so-called computer, and the operation input unit 2 and the display unit 6 can be realized as peripheral devices of the computer.

  The operation input unit 2 is a user interface such as a keyboard and a mouse, and is operated by a user and used to input data. The operation input unit 2 is connected to the control unit 5, converts the user's operation into an operation signal, and outputs the operation signal to the control unit 5.

  The file input / output unit 3 is a DVD (Digital Versatile Disc) drive, a USB (Universa Serial Bus) interface, a network interface, etc., one of which is connected to an external device (not shown), a recording medium, a network, etc., and the other is a control unit. 5, the data is input to the control unit 5 as a file, and the data is output from the control unit 5 as a file.

  The storage unit 4 is a memory device such as a ROM (Read Only Memory) and a RAM (Random Access Memory), and stores various programs and various data. The storage unit 4 is connected to the control unit 5 and inputs / outputs these pieces of information from / to the control unit 5.

  The control unit 5 is configured by an arithmetic device such as a CPU (Central Processing Unit), a DSP (Digital Signal Processor), and an MCU (Micro Control Unit). The control unit 5 is connected to the storage unit 4 and operates as various processing units by reading and executing a program from the storage unit 4 to store and read various data in the storage unit 4. The control unit 5 is also connected to the operation input unit 2, the file input / output unit 3, and the display unit 6, and the user operates the operation input unit 2 to acquire the input data, and the file input / output unit 3 is operated. Data is externally acquired and output as a file, a simulation based on the obtained data is performed to predict the behavior of the crowd, and data of the prediction result is output as a file from the file input / output unit 3 and / or prediction The resulting data is imaged and displayed on the display unit 6.

  The display unit 6 is a display device such as a liquid crystal display or a CRT (Cathode Ray Tube) display, is connected to the control unit 5, and displays a prediction result by the control unit 5. The user visually recognizes the displayed prediction result and considers the behavior of the crowd.

<Function of Simulator 1>
FIG. 2 is a functional block diagram of the simulator 1 according to the first embodiment.

  The operation input unit 2 functions as a part of the condition setting unit 20 or the like. The file input / output unit 3 functions as a part of the condition setting unit 20 and a part of the prediction result output unit 57. The storage unit 4 functions as the repetition condition storage unit 40, the environment information storage unit 41, the individual information storage unit 42, and the like. The control unit 5 includes a risk value acquisition unit 50, a surrounding individual information acquisition unit 51, a stimulus value setting unit 52, a probability setting unit 53, a leader action determination unit 54, a follower action determination unit 55, an individual information update unit 56, and a prediction result output. It functions as a part of the unit 57 and the like.

  The condition setting unit 20 receives inputs of various conditions required for simulation, and stores the input conditions in the storage unit. The condition setting unit 20 is realized, for example, by the operation input unit 2 and the control unit 5 cooperating with each other, and the control unit 5 causes the storage unit 4 to store the value input by the user operating the operation input unit 2. . The condition setting unit 20 may include a file input / output unit 3 for inputting a file in which some or all of the conditions are written, and the control unit 5 sets the file designated by the user operating the operation input unit 2 as a file. The value obtained through the input / output unit 3 and written in the file is stored in the storage unit 4.

  The simulation is performed while advancing the virtual time within a predetermined range. Also, trials are repeated for virtual times within the same range. Although the conditions used in each trial are the same, the behavior of each individual at each virtual time of each trial is probabilistically determined, so that the simulation results between trials are rarely the same.

  The virtual time is a simulation of the passage of the actual time, but is advanced every time the simulator finishes the calculation for one hour, and is ticked faster than the passage of the actual time. For example, one virtual time is associated with an actual one second, and the virtual time is represented by an integer starting from 0 and incrementing by 1.

  In the simulation of this embodiment, assuming that the upper limit virtual time is T, the scheduled number of trials is M, and the virtual time is changed from 0 to (T-1), the trial of updating the environment and individual information for each virtual time is M. Repeated times.

  The repetition condition storage unit 40 stores the upper limit virtual time T and the scheduled trial count M. These values are set in advance by an input operation by the user using the condition setting unit 20.

  The environment information storage unit 41 stores information derived from the target space. Specifically, the environment information storage unit 41 stores a map of the target space including the exit area and a risk value indicating the magnitude of the risk occurring in the target space. The risk value is a function of virtual time. The map and the initial value of the risk value are preset by an input operation by the user using the condition setting unit 20. The risk values are sequentially added by the risk value acquisition unit 50.

  FIG. 3 schematically illustrates information stored in the environment information storage unit 41.

FIG. 3A shows a map 100 of the room R in a two-dimensional xy coordinate system. In the map 100, the floor surface of the room R is divided into 40 squares in the x direction and 40 squares in the y direction as movable areas of the individual, and a part of the block is the exit area A ₁ and another _{one of} the blocks. The area is a combustion area A ₂ . It is assumed that the center of the room R is the origin of the xy coordinate system and the x direction is north. In the environment information storage unit 41, a grid number in the x direction assigned to the center of gravity of each block, a grid number in the y direction, and a combination of codes for distinguishing the exit area A ₁ from the combustion area A ₂ and others are listed. Data is stored. The map 100 is a simple example for explaining the principle, but the target space may be a complicated space composed of a plurality of rooms and passages. In that case, the movable area has a complicated shape excluding areas such as walls and furniture.

  FIG. 3B schematically shows the risk value. The environment information storage unit 41 stores an initial value r (-1) and a series of risk values r (0), r (1), r (2), ..., R from virtual time 0 to (T-1). (T-1) is stored. In the present embodiment in which the event is a fire, the risk value is a value according to the scale of the fire.

  The individual information storage unit 42 stores at least an attribute value, a state value, and an action parameter for each of the plurality of individuals that form the crowd. The state value includes at least the position of the individual in the target space. Moreover, the action parameter includes at least the purpose of selection. Further, the individual information storage unit 42 may further store one or more of a reaction threshold value of each individual for each purpose, a cognitive threshold value of each individual, and a stimulation value for each individual for each purpose.

An identifier representing whether the individual is an evacuation leader, a fire extinguishing leader, or a follower is set in the attribute value. Leaders and followers are the roles of individuals in the crowd. Leaders decide their actions based on their will. A follower decides his / her behavior according to the behavior of another individual.
In the present invention, the attribute value is dynamically changed as the virtual time passes. However, the initial value of the attribute value is common in each trial. That is, the initial value of the attribute value is set by the input operation by the user using the condition setting unit 20, the initial value is set to the attribute value each time the trial is performed, and the attribute value is set to the leader action determination unit 54 and It is changed by the follower action determination unit 55 at any time.
Incidentally, in this embodiment, the initial value of the attribute value is a follower common to all individuals.

The state value represents the state of each individual at each virtual time of each trial. The state value is the position of the individual in the target space and is represented by a grid number.
The initial value of the state value is also common in each trial and is updated as the virtual time passes. That is, the initial value of the state value is set by the input operation by the user using the condition setting unit 20, the initial value is set to the state value for each trial, and the state value is set by the individual information updating unit 56 described later. Updated from time to time.
Incidentally, in the present embodiment, the initial value of the position of each individual is a value randomly set from the grid numbers in the movable area of the room R.
It should be noted that, in the present embodiment, the state value is only one element of the position, but in another embodiment, the state value may include a plurality of elements such as a value indicating the position and whether or not the fire extinguisher is held. Good.

The action parameter represents the action of each individual at each virtual time of each trial, and is a parameter that acts on the state value. The behavior parameter is basically the purpose of the behavior of each individual, the means of the behavior determined by the individual to achieve the purpose, and the state value per hour by the individual performing the means of the behavior. It is defined as the amount of change (state change amount).
For example, there are two purposes, evacuation and fire extinguishing, and an identifier representing a selected purpose selected from these plurality of purposes is stored as the purpose.
Further, for example, there are two types of means, that is, the movement to the exit area A ₁ and the movement to the combustion area A ₂ , and a code indicating the selected area is stored as the means. That is, when the former is selected, the code A ₁ is stored in the means, and when the latter is selected, the code A ₂ is stored in the means.
Further, for example, the state change amount is a movement amount in a grid unit, and a set of an increment value in the x direction and an increment value in the y direction of the grid number is stored as the state change amount. That is, in the target space represented by the map of FIG. 3 (A), for example, when moving one grid to the north (0, -1), when moving one grid to the northwest (-1, -1), ... And so on. If the movement amount of the individual whose virtual time t is (5, 10) at the number of trials m is (-1, -1), the position of virtual time (t + 1) at the number of trials m is (4, 9). ) Is updated.
Incidentally, the initial value of the selection purpose of each individual is not defined in the present embodiment, and the initial value of the movement amount of each individual is (0, 0). The behavior parameter is changed at any time by the leader behavior determination unit 54 and the follower behavior determination unit 55, which will be described later.

The reaction threshold and the cognitive threshold are parameters expressing the individuality of an individual, and are preset by an input operation by the user using the condition setting unit 20.
The reaction threshold of each individual for each purpose is a threshold for the stimulation value of the individual related to the purpose, and it is difficult to cause a reaction to take action by itself against the stimulation value related to the purpose, that is, to be changed to a leader. Represents a kusa. Individuals with higher response thresholds are less sensitive to stimuli, and individuals with lower response thresholds are more sensitive to stimuli. Therefore, an individual having a higher reaction threshold is less likely to be changed to a leader, and an individual having a lower reaction threshold is more likely to be changed to a leader.
The cognitive threshold for each individual represents the magnitude of the risk recognized by the individual. The higher the cognitive threshold, the more difficult it is for the stimulus value to increase in accordance with the increase in the risk value, and the lower the cognitive threshold, the easier the stimulus value increases. Therefore, an individual with a higher cognitive threshold is less likely to be changed to a leader, and an individual with a lower cognitive threshold is more likely to be changed to a leader.

The stimulus value is a value representing the degree of stimulus that triggers an action to achieve each purpose. For example, the stimulus value of the action for evacuation is set as a value that increases every moment according to the expansion of the scale of the fire and the broadcast that prompts the evacuation. In addition, for example, the stimulus value of the action for extinguishing the fire is set as a value that increases every moment according to the expansion of the scale of the fire. The stimulus value for each purpose for each individual is a stimulus value that the individual receives at each virtual time as an opportunity for action to achieve the target.
In this embodiment, the stimulus value is updated as the virtual time passes. However, the initial value of the stimulation value is common in each trial. That is, the initial value of the stimulation value is set by the input operation by the user using the condition setting unit 20, the initial value is set to the stimulation value each time the trial is performed, and the stimulation value is set by the stimulation value setting unit 52 described later. It is updated for each purpose, for each individual, and for each virtual time.
By the way, in this embodiment, the initial value s (−1) of the stimulation value is 0 in common for all individuals.

  4 and 5 schematically illustrate information stored in the individual information storage unit 42.

An individual ID for identifying the individual is given to each of the N individuals, and the individual ID and information about the individual are stored in association with each other.
The information 110 in FIG. 4 is the reaction thresholds θ _1,0 , θ _1,1 , for the evacuation stimulus values stored for each individual whose individual ID is 0, 1, ..., (N−1). , Θ _{1, N-1} , reaction thresholds θ _2,0 , θ _2,1 , ..., θ _{2, N-1} , and cognitive thresholds μ ₀ , μ ₁ , ..., μ _{N- 1} is illustrated.
FIG. 5 shows an example of the information 111 at the end of the simulation. As the information 111, the individual IDs at the virtual times 0, 1, 2, ..., (T-1) in the 1, 2, ..., Mth trials are 0, 1, ..., (N-1). ), The history of stimulus values, the history of attribute values, the history of state values, and the history of action parameters are stored. For example, in the information 111, the stimulus value at each virtual time relating to the evacuation given to the individual whose individual ID is 0 in the first trial is s _1,1,0 (0), s _1,1,0 ( 1), s _1,1,0 (2), ..., s _1,1,0 (T-1), the stimulus value at each virtual time relating to extinction given to the same individual in the same trial is s _{1,2. , 0} (0), s _1,2,0 (1), s _1,2,0 (2), ..., s _1,2,0 (T-1), and correspondingly, in the same trial. The attribute value of the same individual changes to follower, leader, leader, ..., Leader, and the selection purpose of the same individual changes to undetermined value, extinguishing, extinguishing, ..., Extinguishing in the same trial, and the selection area of the same individual in the same trial. Is an undetermined value, A ₂ , A ₂ , ..., A _2, and the movement amount of the same individual in the same trial is (0, 0), (Δx _1,0 (1), Δy _1,0 (1)) _, (Δx _{1,0 2), Δy 1,0 (2)} ), ..., (Δx 1,0 (T-1), and changes the _{Δy 1,0 (T-1))} , the grid of the individual positions at the same trial ( x _1,0 (0), y _1,0 (0), (x _1,0 (1), y _1,0 (1)), (x _1,0 (2), y _1,0 (2 )), ..., (x _1,0 (T-1), y _1,0 (T-1)) are stored.

The risk value acquisition unit 50 sequentially acquires the risk value indicating the magnitude of the risk occurring in the target space and outputs it to the stimulation value setting unit 52. Specifically, the risk value acquisition unit 50 receives a request from the stimulation value setting unit 52 each time the virtual time t advances, acquires the risk value r (t) at the virtual time t, and causes the stimulation value setting unit 52 to perform the acquisition. Output.
Specifically, the risk value acquisition unit 50 calculates the risk value r (t) at each virtual time t according to the following equation (1).

However, r (t-1) is a risk value set one time ago, and the risk value acquisition unit 50 acquires this from the environment information storage unit 41. Further, the risk value acquisition unit 50 stores the risk value acquired at the current time in the environment information storage unit 41 for the calculation after one time. γ is a scale factor related to the purpose of reducing the risk out of a plurality of purposes, and a value of 0 or more is preset in the scale factor γ. The purpose of reducing the risk in this embodiment is to extinguish fire. N _{ω = 2} is the number of individuals who are acting for the purpose of reducing the risk, and the risk value acquisition unit 50 refers to the individual information storage unit 42 and acquires N _{ω = 2} . π is a risk increase amount per one time, and a value larger than 0 is preset in the risk increase amount π. Further, max {·, 0} in the equation (1) represents that the value is limited to non-negative.
[Gamma] N [ _{omega] = 2} in Expression (1) is an estimated value of the degree of achievement of the purpose of reducing the risk, and the risk value is changed to be lower as the degree of achievement of the purpose of reducing the risk is higher. N _{ω = 2} is a value based on the action parameter, but it may be a value based on the information of the target space, such as using the small combustion area as the achievement level instead of N _{ω = 2} .
As described above, the risk value acquisition unit 50 changes the risk value to a low value in accordance with the degree of achievement of one or more of the plurality of purposes, thereby making the prediction including the purpose of reducing the risk more realistic. It makes it possible to be close to the world.

The surrounding individual information acquisition unit 51 acquires, for each individual, information about surrounding individuals existing within a predetermined distance from the position of the individual, and outputs the information to the stimulus value setting unit 52 and the follower action determination unit 55.
One of the pieces of information acquired by the surrounding individual information acquiring unit 51 is the number of surrounding individuals, and the surrounding individual information acquiring unit 51 determines the surroundings of the individual specified in response to the request specifying the individual ID from the stimulation value setting unit 52. Output the number of individuals. For example, the distance threshold T _D is set in advance to the radius of a circle that includes the neighboring 8 grids. The surrounding individual information acquisition unit 51 refers to the individual information storage unit 42, extracts an individual whose position within the radius T _D is set from the position of the specified individual as a surrounding individual, and extracts the number of surrounding individuals. Is counted and output. In addition, the surrounding individual information acquisition unit 51 is set as a selected purpose as a surrounding individual of the specified individual in response to a request specifying the individual ID and the purpose from the stimulus value setting unit 52. Output the number of surrounding individuals.
Further, another piece of information acquired by the surrounding individual information acquiring unit 51 is the behavior of the surrounding individual, and the surrounding individual information acquiring unit 51 specifies the individual designated by the follower action determining unit 55 in response to the request specifying the individual ID. Outputs the behavior of individuals around the. Specifically, the surrounding individual information acquisition unit 51 extracts the surrounding individual in the same manner as above and outputs the action parameter set for the extracted surrounding individual.

The stimulus value setting unit 52 sets a stimulus value for each individual for each purpose for each virtual time, and outputs the set stimulus value to the probability setting unit 53. Specifically, the stimulus value setting unit 52 calculates the stimulus value s _{ω, i} (t) of each individual i (individual whose individual ID is i) related to each purpose ω at each virtual time t using the following equation (2). ~ Set according to (5).

However, s _{ω, i} (t−1) is a stimulus value related to the purpose ω set one time before for the individual i, and the stimulus value setting unit 52 acquires this from the individual information storage unit 42. Further, the stimulus value setting unit 52 causes the individual information storage unit 42 to store the stimulus value set at the current time for setting after one time. δ _ω is the stimulus increase amount for the target ω per one time, and a value larger than 0 is preset for the stimulus increase amount δ _ω . α _ω is a scale factor for suppressing the stimulation related to the target ω, and a value of 0 or more is set in advance for the scale factor α _ω . Further, r (t) is the above-described risk value, and the stimulation value setting unit 52 acquires this from the risk value acquisition unit 50. g is a non-negative constant. μ _i is the cognitive threshold for the individual i among the cognitive thresholds described above, and the stimulation value setting unit 52 acquires this from the individual information storage unit 42. _ni is the number of individuals around the individual i, and the stimulation value setting unit 52 acquires this from the surrounding individual information acquisition unit 51. N _max is the maximum number of surrounding individuals, and a value of 1 or more is set in advance.
Further, max {·, 0} in the formula (2) and “if · 0 otherwise” in the formulas (3) and (5) respectively indicate that the values are restricted to non-negative values.

R _{p in the} equation (4) approaches 1 as the difference between the risk value r (t) and the cognitive threshold μ _i increases, and the stimulus value s _{ω, i} (t) in the equation (2) approaches 1 as R _p approaches. Greatly increase. That is, the smaller the cognitive threshold μ _{i, the} greater the difference from the risk value r (t) and the more likely the stimulation value s _{ω, i} (t) increases. This models the state of the real world in which the smaller the cognitive threshold, the more sensitive the risk is and the more likely a leader becomes.
In this way, the stimulus value setting unit 52 sets the stimulus value for each individual, and in particular, the greater the difference between the risk value r (t) and the cognitive threshold μ _i of the individual i, the more the individual information storage unit 42 stores. By making a large increase from the stored value s _{ω, i} (t−1) and setting the stimulation value s _{ω, i} (t), prediction closer to the real world is possible.

Further, F in Expression (5) approaches 0 as the number n _{i of} surrounding individuals increases, and the stimulation value s _i (t) in Expression (2) increases greatly as F approaches 0. That is, the stimulus value s _i (t) is likely to increase as the number of surrounding individuals increases. This is because the area where evacuation is less advanced promotes an increase in stimuli that trigger actions (the atmosphere in which evacuation is to be promoted), and the area where evacuation is advanced models the state of the real world where stimuli saturate. There is.
In this way, the stimulus value setting unit 52 sets the stimulus value for each individual, and in particular, the individual information storage unit 42 stores the individual having a larger number n _{i of} surrounding individuals extracted by the surrounding individual information acquisition unit 51. By greatly increasing the value s _{ω, i} (t−1) and setting the stimulus value s _{ω, i} (t), it is possible to make a prediction closer to the real world.

Here, the stimulus value setting unit 52 calculates F according to the following formula (6) instead of the formula (5) when calculating the stimulus value s _{2, i} (t) related to extinction (ω = 2). You can also

However, abs (•) represents an absolute value. Further, n _{ω = 2} is the number of surrounding individuals whose selection purpose is extinguishing, and the stimulation value setting unit 52 acquires this from the surrounding individual information acquisition unit 51. N _max is the maximum number of surrounding individuals, and a value of 1 or more is set in advance. ξ is the optimal number of individuals whose selection purpose is extinguishing among the number of surrounding individuals, and a value of 1 or more and N _max or less is set in advance.
The F of the equation (6) approaches 1 as n _{ω = 2} approaches ξ, and the stimulation value s _{ω, i} (t) of the equation (2) hardly increases as F approaches 1. That is, when n _{ω = 2} increases, the stimulation value s _{ω, i} (t) is suppressed, and the change of the target ω to the leader is suppressed. This has the effect of suppressing the number of individuals that select the purpose, which is known to be able to select only a small number of individuals from the crowd, and avoiding predictions that deviate from the real world.

  The control of the number of trials and the virtual time is performed by the stimulation value setting unit 52.

  Every time the stimulus value setting unit 52 sets the stimulus value, the probability setting unit 53 sets the first winning probability for each purpose based on the stimulus value for each purpose among the individuals whose attribute values are followers. Then, each of the first winning probabilities is output to the leader action determining unit 54, and the individual whose attribute value is the leader is set with the second winning probability determined for the selection purpose set for the individual. Each of the second winning probabilities is output to the follower action determination unit 55.

Specifically, the probability setting unit 53 reads from the individual information storage unit 42 the individual ID (i) of the individual whose attribute value is a follower and the reaction threshold θ _{ω, i} for each object ω of the individual, and the stimulus From the stimulus values input from the value setting unit 52, the stimulus value s _{ω, i} (t) for the individual i associated with each objective ω is specified, and the first winning probability P _{ω, i} of the individual i associated with the objective ω is specified. (X _{ω, i} = 0 → X _{ω, i} = 1) is set according to the following equation (7).

However, X _{ω, i} is a random variable corresponding to the attribute value of the individual i with respect to the target ω, X _{ω, i} = 1 is that the individual i is the leader with respect to the target ω, and X _{ω, i} = 0 is The individual i is a follower, and (X _{ω, i} = 0 → X _{ω, i} = 1) indicates that the individual i is changed from a follower to a leader associated with the purpose ω. That is, P _{ω, i} (X _{ω, i} = 0 → X _{ω, i} = 1) is the probability of changing the individual i from the follower to the leader associated with the purpose ω.

The first winning probability P _{ω, i} (X _{ω, i} = 0 → X _{ω, i} = 1) in Expression (7) is higher as the stimulation value s _{ω, i} (t) related to the target ω is higher, and the target ω. The lower the reaction threshold θ _{ω, i} related to, the higher the value. This modeled the state of the real world where the stronger the stimulus related to the purpose ω, the more likely it was to become the leader related to the target ω, and the more sensitive the reaction to the stimulus related to the purpose ω, the more likely it was to become the leader related to the purpose ω. There is.
As described above, the probability setting unit 53 has a higher first winning probability P _{ω, i} (X _ω ) as the plurality of stimulation values s _{ω, i} (t) is higher for each individual and is higher as the reaction threshold θ _{ω, i} is lower. _{, I} = 0 → X _{ω, i} = 1) is set.

In addition, the probability setting unit 53 specifies the individual ID (i) of the individual whose attribute value is the leader and the selection purpose ω from the individual information storage unit 42, and the second winning probability P related to the selection purpose ω of the individual i. _{ω, i} (X _{ω, i} = 1 → X _{ω, i} = 0) is set according to the following equation (8).

Since X _i is the same as that in the expression (7), P _{ω, i} (X _{ω, i} = 1 → X _{ω, i} = 0) is the probability of changing from the leader of the target ω to the follower. A value of 0 or more is set in advance in ε.

  Equations (7) and (8) are formulated according to the reaction threshold model, and the probability setting unit 53 is characterized by an original approach in which the reaction threshold model is applied to change between the leader and the follower.

  The leader action determination unit 54 performs a lottery with the first winning probability for each purpose for the individual for which the first winning probability is set by the probability setting unit 53, and changes the attribute value of the winning individual to the leader, Change the selection purpose of the winning individual to the winning purpose.

Specifically, the leader action determination unit 54 determines the first winning probability P _{ω, i} (X _{ω, i} = 0 → X _ω) for each of the plurality of objectives ω for the individual i for which the first winning probability is set. _{, I} = 1), and the individual information storage unit 42 stores that the attribute value X _{ω, i} related to the purpose ω of the individual (winning individual) _i is a leader when the lottery is won. Let
In the lottery, for example, the leader action determination unit 54 determines one random number in the range [0, 1], and the random number is P _{ω, i} (X _{ω, i} = 0 → X _{ω, i} = 1). If it is less than P, it is determined that it is won, and if it is P _{ω, i} (X _{ω, i} = 0 → X _{ω, i} = 1) or more, it is determined that it is a loss.

Here, in order to prevent a plurality of goals that cannot be simultaneously executed by individuals in the real world from being simultaneously selected, the leader action determination unit 54 sets the maximum first winning probability among the first winning probabilities for each of the plurality of objects that cannot be simultaneously executed. Only when the value is higher than the second highest winning probability by exceeding the threshold value Tp, the lottery is performed with the maximum first winning probability. That is, regarding the individual i, the leader action determination unit 54 sets j as the object having the largest first winning probability and k as the object having the second largest winning probability, and when the following expression (9) is satisfied, The lottery for the purpose j is performed.

It should be noted that the combination of objectives that cannot be executed simultaneously and the threshold value Tp are appropriately set in advance. In the present embodiment, evacuation and fire extinguishing are set as a combination of purposes that cannot be executed simultaneously.
By doing so, the leader action determination unit 54 eliminates the conflict of a plurality of purposes that cannot be simultaneously executed, and enables prediction that is more suitable for the real world.

In addition, the leader action determination unit 54 sets, as the action parameter of the individual whose attribute value is the leader, a value that brings the state value of the individual closer to the achievement of the selection purpose of the individual.
Specifically, the leader action determination unit 54 reads out the selection area and the position of the individual whose attribute value is the leader from the individual information storage unit 42, and stores the selection area and the position in the environment information storage unit 41 from each of the 8 neighborhood grids of the position. The distance to the selected area that is present is calculated, and the amount of movement from the position of the individual to the closest neighboring grid is determined.

  Then, the leader action determination unit 54 stores the determined selection purpose, selection area, and movement amount in the individual information storage unit 42 as the action parameter of the individual whose attribute value is the leader.

The follower action determination unit 55 changes the attribute value of the individual for which the second winning probability is set by the probability setting unit 53 to a follower with the probability, and sets the behavior parameter of the individual whose attribute value is the follower to the surroundings of the individual. Set a value similar to the behavior parameter of the individual.
Specifically, the follower action determination unit 55, for each individual ω for which the second winning probability is set, the second winning probability P _{ω, i} (X _{ω, i} = 1 → X _{ω, i).} = 0), the individual information storage unit 42 stores that the attribute value of the winning individual i is a follower when the lottery is won.
In the lottery, for example, the follower action determination unit 55 determines one random number in the range [0, 1], and the random number is P _{ω, i} (X _{ω, i} = 1 → X _{ω, i} = 0). winning if it is less than determines _{P ω, i (X ω,} i = 1 → X ω, i = 0) and the defeat equal to or greater than.
In addition, the follower action determination unit 55 causes the surrounding individual information acquisition unit 51 to acquire the action parameter of the individual surrounding the individual whose attribute value is the follower, and selects the winning individual with the largest selection purpose among the acquired action parameters. Decide on the purpose.
Further, the follower action determination unit 55 calculates the distance from each of the eight neighboring grids of the position of the individual whose attribute value is a follower to the selected area, and determines the amount of movement from the position of the individual to the closest neighboring grid. . Then, the follower action determination unit 55 stores the determined selection purpose, selection area, and movement amount in the individual information storage unit 42 as the action parameter of the individual whose attribute value is a follower.

The individual information updating unit 56 updates the state value of each individual with the action parameter of the individual.
In the present embodiment, the individual information updating unit 56 updates by adding the movement amount of the action parameter to the position of the state value. Specifically, the individual information updating unit 56 reads the position and the movement amount of each individual from the individual information storage unit 42, adds the read movement amount to the read position for each individual, and obtains the position after the addition. It is stored in the individual information storage unit 42.

  The prediction result output unit 57 outputs the prediction result which is the result of the simulation. The prediction result includes at least a part or all of the information stored in the individual information storage unit 42, and preferably further includes a part or all of the information stored in the environment information storage unit 41. Further, the prediction result output unit 57 statistically processes the information stored in the individual information storage unit 42, or the information and the information stored in the environment information storage unit 41, and uses the obtained statistical amount as the prediction result. You may output.

  The output timing of the prediction result may include the middle of the simulation in addition to the time when the simulation is finished. That is, part or all of the above information obtained up to the middle of the simulation may be output as the intermediate prediction result.

  In addition, the prediction result output unit 57 may output the prediction result as a data file, an image file, or an image, and may use one or more of these formats. You may output.

  Each of FIG. 6 and FIG. 7 is an example of an intermediate prediction result at a virtual time close to the upper limit virtual time at a certain number of trials. The prediction result output unit 57 generates an intermediate prediction result by superimposing and drawing a graphic representing an individual on the coordinates corresponding to the position of each individual on the image while imaging the map of the target space. To do.

Of these, the intermediate prediction result 110 illustrated in FIG. 6 is a prediction result in which a sufficient number of individuals select fire extinguishing (move to the combustion area A ₂ ) and the fire extinguishing succeeds. On the other hand, the intermediate prediction result 120 illustrated in FIG. 7 is a prediction result in which there are few individuals who have selected fire extinguishing and it is predicted that the fire extinguishing will fail. These prediction results are obtained from the same settings.

  If the prediction result by the simulator 1 is used, for example, an analysis that compares the position of the leader and its time transition in the trial illustrated in FIG. 6 and the trial illustrated in FIG. Is possible.

<Example of simulator 1 operation>
An operation example of the simulator 1 will be described with reference to the flowcharts of FIGS. 8 and 9.

  First, the condition setting unit 20 receives an input from the user and sets the conditions for simulation (step S1). That is, the simulation conditions obtained by the user manually inputting using the condition setting unit 20 and / or the user using the condition setting unit 20 to specify a file and the corresponding condition setting unit 20 are applicable. The condition setting unit 20 sets the simulation condition obtained by reading from the file in the iterative condition storage unit 40, the environment information storage unit 41, and the individual information storage unit 42.

  When the simulation condition is set, the stimulation value setting unit 52 initializes the number of trials to 1 (step S2), and sets the loop process of steps S2 to S12.

  Furthermore, in the loop processing of the number of trials, the stimulation value setting unit 52 initializes the virtual time to 0 (step S3), and sets the loop processing of steps S3 to S10.

  In the virtual time loop process, first, the action determination process is performed (step S4).

  The action determination process of step S4 will be described with reference to the flowchart of FIG.

  In the action determination process, first, the risk value is acquired. The stimulus value setting unit 52 requests the risk value acquisition unit 50 to specify a virtual time being set and requests the risk value to be acquired, and the risk value acquisition unit 50 updates the risk value accordingly and updates the stimulus value setting unit 52. Output to. That is, the risk value acquisition unit 50 refers to the individual information storage unit 42 to calculate the number of individuals whose latest (one time before) selection purpose is extinguishing as the extinction degree (step S401) and is designated. The risk value one hour before the specified time is read from the environment information storage unit 41, and these values are applied to the equation (1) to update the risk value (step S402).

Next, the stimulus value setting unit 52 refers to the individual information storage unit 42 to identify an individual whose position has not yet reached the exit area A ₁ , and sequentially sets the identified individual as a processing target (step S403), the loop process of steps S403 to S420 is set.

  In the individual loop processing, first, surrounding individuals are counted (step S404). That is, the stimulus value setting unit 52 specifies the individual ID of the processing target individual and requests the surrounding individual information acquisition unit 51 to acquire information about the surrounding individual, and the surrounding individual information acquisition unit 51 refers to the individual information storage unit 42. Then, the surrounding individuals of the designated individual are counted, and the counted number of surrounding individuals is output to the stimulus value setting unit 52.

  Next, the stimulus value for each purpose is updated (step S405). That is, the stimulus value setting unit 52 reads the stimulus value and the cognitive threshold of the individual to be processed one hour before from the individual information storage unit 42, the read stimulus value, the cognitive threshold, and the risk value acquired in step S402. Then, the number of surrounding individuals acquired in step S403 is applied to equations (2) to (6) to calculate a stimulus value, and the stimulus value is added to the individual information storage unit 42. For example, the stimulus value setting unit 52 performs updates related to two purposes of evacuation and fire extinguishing, updates related to evacuation are performed using Formulas (2) to (5), and updates related to extinguishment are performed using Formula (2) to. This is performed using (4) and equation (6).

  Subsequently, the probability setting unit 53 refers to the individual information storage unit 42 and confirms the attribute value of the individual to be processed (step S406).

  When the attribute value is a follower (YES in step S406), the probability setting unit 53 reads out the reaction threshold value and the latest stimulus value of the processing target individual from the individual information storage unit 42 for each of the plurality of purposes, and sets them. The first winning probability for each purpose is calculated by applying the formula (7) (step S407), and the groups of the object and the first winning probability are rearranged in ascending order of the first winning probability (step S408). Then, the leader action determination unit 54 compares the difference between the maximum first winning probability and the second largest first winning probability with a threshold value (step S409), and when the difference exceeds the threshold value (in step S409). (YES), and the lottery is performed with the maximum first winning probability (step S410). When it is won (YES in step S411), the attribute value of the individual to be processed in the individual information storage unit 42 is changed to the leader (step S412), and the object corresponding to the maximum first winning probability is the individual to be processed. To the selection purpose (step S412), and the process proceeds to step S417. If the difference is less than or equal to the threshold value (NO in step S409) or if the winning is not achieved (NO in step S411), it is determined that the attribute value of the processing target individual is not changed, and the process proceeds to step S419. To be

  On the other hand, when the attribute value is the leader (NO in step S406), the probability setting unit 53 sets the second winning probability corresponding to the selection purpose of the processing target individual based on the equation (8), and determines the follower action. The section 55 performs a lottery with the set second winning probability (step S414). If the player is elected (YES in step S415), the follower behavior determination unit 55 changes the attribute value of the processing target individual in the individual information storage unit 42 to a follower (step S416), and the process proceeds to step S419. If not won (NO in step S415), it is determined that the attribute value of the processing target individual is not changed, step S416 is omitted, and the process proceeds to step S417.

In step S <b> 417, the leader action determination unit 54 stores, in the individual information storage unit 42, the selection areas of the individual whose attribute value has been changed to the leader and the individual whose attribute value has not been changed from the leader. The area corresponding to the stored selection purpose of the individual is determined.
Then, the leader behavior determination unit 54 calculates the amount of movement of the position of the processing target individual to the neighboring grid closest to the selected area among the eight neighboring grids as the amount of movement of the individual (step S418).

On the other hand, in step S419, the follower action determination unit 55 makes the selection purpose of the individual whose attribute value is determined to be changed to the follower and the individuals whose attribute value is determined not to be changed from the follower to be similar to the surrounding individuals. To decide. The follower action determination unit 55 causes the surrounding individual information acquisition unit 51 to acquire the selection purpose of the individuals around the individual to be processed, and determines the selection purpose, which is the largest number, as the selection purpose of the individual to be processed. When the virtual time is 0 or close to 0, the selection purpose of many surrounding individuals may be undecided, but in that case, the selection purpose of the individual to be processed is also undecided.
Then, the leader action determining unit 54 determines the selection area of the individual to be processed as an area corresponding to the selection purpose of the individual (S420), and is closest to the selected area of the eight neighborhood grids of the position of the individual. The movement amount to the neighboring grid is calculated as the movement amount of the individual (step S421).

  In the following step S422, it is determined whether or not the individual loop processing has ended. The stimulus value setting unit 52 confirms whether or not all the individuals who have not reached the exit have been processed, and if not processed (NO in step S422), returns the process to step S403 and Continue the loop processing of.

  On the other hand, when all the individuals who have not reached the exit have been processed (YES in step S422), the leader behavior determining unit 54 and the follower behavior determining unit 55 cause the behavior of each individual stored in the individual information storage unit 42. The parameters are updated (step S423). That is, the leader action determination unit 54 stores the selection purpose determined in step S413, the selection area determined in step S417 and the movement amount determined in step S418 in the individual information storage unit 42, and the follower action determination unit 55 determines in step S419. The selected information, the selected area determined in step S420 and the movement amount determined in step S421 are stored in the individual information storage unit 42.

  When the action parameter is updated, the action determination process ends, the process proceeds to step S5 in FIG. 8, and the individual information updating unit 56 uses the movement amount of each individual updated in step S4 to position the individual. To update.

  In the subsequent step S6, the prediction result is output. The prediction result output unit 57 refers to the environment information storage unit 41 to draw a map of the room R, refers to the individual information storage unit 42 to draw the latest position of each individual on the map, and draws the result. Is displayed on the display unit 6 as an intermediate prediction result.

Then, the end of the virtual time loop process is determined. The stimulus value setting unit 52 increases the virtual time by 1 (step S7), and refers to the individual information storage unit 42 to check whether all the individuals have reached the exit (step S8). Furthermore, when there is an individual that has not reached the exit (NO in step S8), the stimulation value setting unit 52 confirms whether the increased virtual time is equal to or more than the upper limit virtual time (step S9).
If there is an individual that has not reached the exit and the virtual time is less than the upper limit virtual time (NO in step S9), the stimulation value setting unit 52 returns the processing to step S4 and continues the loop processing of the virtual time. .

  On the other hand, when all the individuals have reached the exit (YES in step S8) or when the virtual time is equal to or more than the upper limit virtual time (YES in step S9), it is determined whether or not the loop processing for the number of trials has ended. The stimulation value setting unit 52 increases the number of trials by 1 (step S10), and confirms whether or not the increased number of trials exceeds the scheduled number of trials (step S11). When the increased number of trials is equal to or less than the planned number of trials (NO in step S11), the stimulation value setting unit 52 returns the process to step S3 and continues the loop process of the number of trials.

  If the increased number of trials exceeds the scheduled number of trials (YES in step S11), the simulation ends and the prediction result is output. The prediction result output unit 57 writes all data in the individual information storage unit 42 and all data in the environment information storage unit 41 into a file, and outputs the file from the file input / output unit 3.

[Second embodiment]
In the first embodiment, the individual information storage unit 42, the surrounding individual information acquisition unit 51, the stimulus value setting unit 52, the probability setting unit 53, the leader action determination unit 54, the follower action determination unit 55, and the individual information update unit 56. An example of performing processing for a plurality of individuals has been shown. Instead of these, the simulator 1b in the second embodiment has an individual information storage unit 42b-i, which performs processing for one individual, a surrounding individual information acquisition unit 51b-i, a stimulus value setting unit 52b-i, The behavior determining apparatus 70b-i including the probability setting unit 53b-i, the leader behavior determining unit 54b-i, the follower behavior determining unit 55b-i, and the individual information updating unit 56b-i is provided by the number N of individuals. However, i = 0, 1, 2, ..., N-1.
That is, in each of the action determination devices 70b-i (where i = 0, 1, 2, ..., N-1) included in the simulator 1b, the storage unit 4 functions as a memory region in parallel or in a time-division manner, It is realized by the control unit 5 executing processes that operate in parallel or in a time-division manner.

  That is, each of the behavior determination devices 70b-i is a behavior determination device that determines the behavior of its own individual, which is one of the individuals constituting the crowd in the target space that can achieve a plurality of purposes. The individual information storage unit 42b-i that stores at least an action parameter including a selection purpose selected from the purposes, an attribute value indicating whether the user is a leader or a follower, and a position in the target space. For a plurality of purposes, a stimulus value acquisition unit 52b-i that acquires a stimulus value that indicates the degree of stimulus that triggers an action to achieve each of the purposes, and for each purpose when the attribute value is a follower. A probability setting unit 53b-i that sets a first winning probability for each purpose based on the stimulus value, and sets a predetermined second winning probability when the attribute value is a leader; When a selection probability is set, a leader action determination unit that performs a lottery with the first winning probability for each purpose, changes the attribute value of the winning individual to a leader and sets the selection purpose of the individual to the winning purpose 54b-i, a surrounding individual information acquisition unit 51b-i that acquires the behavior of surrounding individuals existing within a predetermined distance from the position of the own individual among the individuals, and an attribute value when the second winning probability is set. And a follower action determination unit 55b-i that sets a target similar to the action of the surrounding individuals to the selection purpose while changing to a follower with the second winning probability.

[Modifications of First and Second Embodiments]
In each of the above-described embodiments, an example in which the environment information storage unit 41 stores a two-dimensional space map is shown, but a three-dimensional map may be used. In that case, the state values and behavior parameters stored in the individual information storage units 42 and 42b-i are also three-dimensional information.

  In each of the above-described embodiments and the modifications thereof, a part of the simulation condition can be a value according to the situation of the real-time target space. For example, if the situation in the near future is predicted by a simulation in which the position of the actual person is set as the position of each individual, it becomes possible to accurately guide the crowd.

  Although the risk value acquisition unit 50 reads the risk value from the environment information storage unit 41 in each of the above-described embodiments and its modifications, in another embodiment, the risk value acquisition unit 50 includes a flame sensor and smoke. It may be configured by a function of a disaster sensor that measures a physical quantity of a real space related to a disaster such as a sensor and a control unit that processes a signal from the disaster sensor according to a program. In this case, the risk value acquisition unit 50 quantifies a signal indicating the presence or absence of a disaster and the degree of the disaster into a risk value according to a predetermined rule.

  In each of the above-described embodiments and its modified examples, the individual information updating units 56 and 56b-i each update the position of the individual without considering the size of the individual and eliminating the overlap. The position of the individual may be updated in consideration of the physical constraint of. In that case, for example, the individual information update units 56 and 56b-i respectively set the movement amounts determined by the leader action determination units 54 and 54b-i and the follower action determination units 55 and 55b-i, respectively, in the virtual space. Adjust the amount of movement to a position where individuals do not overlap each other and update. Alternatively, for example, the individual information updating units 56 and 56b-i move the individuals closer to the selection areas determined by the leader behavior determination units 54 and 54b-i and the follower behavior determination units 55 and 55b-i, respectively. The amount of movement, which is the amount of movement to a position where the individuals do not overlap in the virtual space, is calculated and updated.

[Third embodiment]
The autonomous mobile robot 8 according to the third embodiment includes an action determination device 70c that is an example of the action determination device of the present invention, and simulates one individual forming a crowd.

  The autonomous mobile robot 8 has an operation input unit 2c, a file input / output unit 3, a control unit 5, and an operation input unit 2c similar to the display unit 6 of the first embodiment, a file input / output unit 3c, a control unit 5c, and a display unit. 6c, a disaster sensor such as a flame sensor or a smoke sensor, a surrounding individual sensor such as a camera, a timekeeping unit that measures real time, and a movement control unit including a motor, wheels, positioning means, obstacle sensors, and the like. Prepare The disaster sensor, the surrounding individual sensor, and the movement control unit are each connected to the control unit 5c. It is desirable that the operation input unit 2c and the display unit 6c be removable.

  The autonomous mobile robot 8 includes the condition setting unit 20, the repetition condition storage unit 40, the environment information storage unit 41, the individual information storage unit 42, the risk value acquisition unit 50, the surrounding individual information acquisition unit 51, and the stimulation value of the first embodiment. Conditions for performing processing for one individual corresponding to each of the setting unit 52, the probability setting unit 53, the leader action determining unit 54, the follower action determining unit 55, the individual information updating unit 56, and the prediction result output unit 57. Setting unit 20c, repetition condition storage unit 40c, environment information storage unit 41c, individual information storage unit 42c, risk value acquisition unit 50c, surrounding individual information acquisition unit 51c, stimulus value setting unit 52c, probability setting unit 53c, leader action determination unit. 54c, a follower action determination unit 55c, an individual information update unit 56c, and a prediction result output unit 57c.

However, the risk value acquisition unit 50c acquires the risk value by quantifying the signal output by the disaster sensor according to a predetermined rule.
In addition, the surrounding individual information acquisition unit 51c analyzes the image output by the surrounding individual sensor, detects a robot and a person of the same type as the autonomous traveling robot 8 existing around the autonomous traveling robot 8 as surrounding individuals, and detects the detected surrounding individuals. The number and behavior of surrounding individuals are acquired by recognizing the number and behavior of.
Further, the real time is used instead of the virtual time in the first embodiment, and the stimulus value setting unit 52c controls the time of the simulation with reference to the real time output by the time counting unit. The number of trials is advanced for each instruction from the user through the operation input unit 2c, and the stimulation value setting unit 52c refers to the instruction signal from the operation input unit 2c to control the number of trials.
In addition, the individual information updating unit 56c rotates the motor in the direction indicated by the movement amount of the action parameter up to the distance indicated by the movement amount, drives the wheels connected to the motor, and moves the autonomous mobile robot 8. Let In addition, the individual information updating unit 56c analyzes a signal from an obstacle sensor that detects an obstacle around the autonomous mobile robot 8 to detect a distance and a direction to the obstacle, and detects the obstacle and the autonomous mobile robot 8. The rotation of the motor is suppressed so that the distance is not less than the predetermined distance. Further, the individual information updating unit 56c analyzes the signal output by the positioning means including the communication interface for communicating with the beacon system and the GPS system, detects the position of the autonomous mobile robot 8, and obtains the state value at the detected position. Update.

  Of these, the individual information storage unit 42c, the surrounding individual information acquisition unit 51c, the stimulus value setting unit 52c, the probability setting unit 53c, the leader action determination unit 54c, the follower action determination unit 55c, and the individual information update unit 56c are the action determination devices. Included in 70c.

  That is, the behavior determination device 70c is a behavior determination device that determines the behavior of the individual who is one of the individuals forming the crowd in the target space capable of achieving a plurality of purposes, and at least for the individual, An individual information storage unit 42c that stores a behavior parameter including a selected purpose selected from a plurality of purposes, an attribute value that indicates whether the user is a leader or a follower, and a position in the target space, and a plurality of purposes. The stimulus value acquisition unit 52c that acquires a stimulus value indicating the degree of stimulus that triggers an action to achieve each of the purposes, and for each purpose based on the stimulus value for each purpose when the attribute value is a follower. The first winning probability is set, and the first winning probability is set with the probability setting unit 53c that sets the second winning probability when the attribute value is the leader. In this case, a leader action determination unit 54c that performs a lottery with the first winning probability for each purpose, changes the attribute value of the winning individual to a leader, and sets the selection purpose of the individual to the winning purpose Of the surrounding individual information acquisition unit 51c that acquires the behavior of surrounding individuals existing within a predetermined distance from the position of the individual, and the attribute value to the follower with the second winning probability when the second winning probability is set. And a follower action determination unit 55c that changes and sets a purpose similar to the behavior of surrounding individuals as a selection purpose.

[Modifications common to the above embodiments]
In each of the above-described embodiments and its modifications, a room is illustrated as the target space, but the target space may be a concert hall, a station, or the like, and is not limited to indoors, but is also used for outdoor shopping malls, parks, towns, and the like. It may be a space, or a space that crosses indoors and outdoors such as at an event venue or school.

  In each of the above-described embodiments and its modifications, fire was illustrated as an event, but other disasters such as an earthquake, the appearance of a suspicious person, the occurrence of a sick person at an event site, the appearance of a celebrity, a call to the crowd, and question presentation. It can also be applied to events other than disasters such as.

  In each of the above-described embodiments and its modifications, evacuation and extinguishing were illustrated as the purpose of the action, but rescue action and field horse action against the occurrence of a sick person, field horse action against the appearance of a celebrity, response to a call and question presentation, etc. The purpose corresponding to can be set appropriately.

In each of the above-described embodiments and the modifications thereof, movement was illustrated as a means of action, but a shift to a leaning posture (evacuation under a sitting desk) as a means of evacuation against an earthquake, a response to a call or question presentation It is also possible to appropriately set means that does not involve movement according to the event and the purpose, such as raising hands and uttering as means of. It is also possible to set the movement to the exit and the transition to the bending posture as an option of the means, and to randomly select one of them.
It should be noted that in the above-described embodiment and its modifications, the means for one purpose is one, but it may be other than one if it is one or more.

  In each of the above-described embodiments and its modifications, a crowd of people is illustrated, but the invention can be applied to a crowd of other social organisms such as fish, birds, and ants. In addition, when the individual is other than a person, the target space and the event can be appropriately set according to the type of the individual.

According to the simulator 1, the simulator 1b and the action determination device 70b-i included in the simulator 1b, the autonomous mobile robot 8 and the action determination device 70c included in the autonomous mobile robot 8 described above, even if the same setting is performed. The selection purpose of each individual is changed stochastically, and different prediction results can be generated even if the same setting is made. Therefore, each of these can predict the behavior selection behavior of each individual in the crowd under unknown conditions, and if the prediction results obtained by each are used, it will be easy to identify the conditions under which the behavior selection occurred in the individuals that make up the community. it can.

1 ... Simulator 2 ... Operation input unit 20 ... Condition setting unit 3 ... File input / output unit 4 ... Storage unit 40 ... Repetition condition storage unit 41 ... Environmental information storage unit 42 ... Individual information storage unit 5 ... Control unit 50 ... Risk value acquisition unit 51 ... Surrounding individual information acquisition unit 52 ... Stimulation value setting unit 53 ... Probability setting unit 54 ... Reader Action determination unit 55 ... Follower action determination unit 56 ... Individual information update unit 57 ... Prediction result output unit 6 ... Display unit

Claims (7)

A simulator for predicting the behavior of a crowd in a predetermined space capable of achieving a plurality of purposes,
For each of the plurality of individuals forming the crowd, at least a behavioral parameter including a selection purpose selected from the plurality of purposes, an attribute value indicating whether a leader or a follower, and a position in the space are stored. An individual information storage unit,
For the plurality of purposes, a stimulus value setting unit that sequentially sets a stimulus value indicating the degree of stimulus that triggers the action to achieve each of the purposes,
Every time the stimulus value is set, among the individuals, the attribute value is a follower, the first winning probability for each of the goals based on the stimulus value for each of the goals is set, and the attribute value is A probability setting unit for setting a predetermined second winning probability for an individual who is a leader,
A lottery is performed on the individual for which the first winning probability is set at the first winning probability for each purpose, and the attribute value of the winning individual is changed to a leader and the selection purpose of the individual is won. Leader action decision unit to set the purpose,
A surrounding individual information acquisition unit that extracts, for each individual, a surrounding individual whose position from the individual is within a predetermined distance,
The attribute value of the individual for which the second winning probability is set is changed to a follower at the second winning probability, and the attribute value is set to the surrounding individuals of the individual for the selection purpose of the individual who is the follower. And a follower action determination unit that sets the selection purpose,
A simulator characterized by having.   The leader action determination unit, for the individual for which the first winning probability has been set, the predetermined first winning probability of the first winning probability for each of the purposes is greater than the second highest first winning probability. The simulator according to claim 1, wherein the lottery is performed with the maximum first winning probability only when the value is higher than the value. The individual information storage unit further stores a reaction threshold for each of the purposes for each individual,
The probability setting unit, for each of the purposes for each individual, calculates the first winning probability higher as the stimulus value is higher and higher as the reaction threshold is lower,
The simulator according to claim 1 or 2.   The simulator according to claim 3, wherein the stimulus value setting unit changes the stimulus value to a low value in accordance with the achievement level of one or more of the plurality of purposes.   The simulator according to claim 1, wherein the stimulation value setting unit sets the stimulation value for each individual. A simulation method for predicting the behavior of a crowd in a predetermined space capable of achieving a plurality of purposes,
On the computer,
For each of the plurality of individuals forming the crowd, at least a behavior parameter including a selection purpose selected from the plurality of purposes, an attribute value indicating whether a leader or a follower, and a position in the space are stored. ,
With respect to the plurality of purposes, a process of sequentially setting a stimulus value indicating the degree of stimulus that triggers the action to achieve each of the purposes,
Every time the stimulus value is set, among the individuals, the attribute value is a follower, the first winning probability for each of the goals based on the stimulus value for each of the goals is set, and the attribute value is A process of setting a predetermined second winning probability for an individual who is a leader,
A lottery is performed on the individual for which the first winning probability is set at the first winning probability for each purpose, and the attribute value of the winning individual is changed to a leader and the selection purpose of the individual is won. Process to set the purpose,
A process of extracting surrounding individuals whose position from the individual is within a predetermined distance for each individual;
The attribute value of the individual for which the second winning probability is set is changed to a follower at the second winning probability, and the attribute value is set to the surrounding individuals of the individual for the selection purpose of the individual who is the follower. And a process of setting the selection purpose,
A simulation method characterized by causing to execute. A behavior determination device for determining the behavior of one's own individual, which is one of the individuals forming a crowd in a predetermined space capable of achieving a plurality of purposes,
For the own individual, at least an action parameter including a selected purpose selected from the plurality of purposes, an attribute value indicating whether it is a leader or a follower, and individual information that stores a position in the space. Storage part,
For the plurality of purposes, a stimulus value acquisition unit that acquires a stimulus value that represents the degree of the stimulus that triggers the action to achieve each of the purposes,
When the attribute value is a follower, a first winning probability is set for each of the purposes based on the stimulus value for each of the purposes, and when the attribute value is a leader, a predetermined second winning probability is set. Department,
When the first winning probability is set, a lottery is performed with the first winning probability for each of the purposes, the attribute value of the winning individual is changed to a leader, and the selection purpose of the individual is selected as the winning purpose. A leader action decision section to set,
Among the individuals, a surrounding individual information acquisition unit that acquires the behavior of surrounding individuals existing at a predetermined distance or less from the position of the own individual,
A follower action determination unit that changes the attribute value to a follower at the second winning probability when the second winning probability is set and sets a purpose similar to the behavior of the surrounding individual to the selection purpose,
An action determination device comprising:

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