JP2000132783A - Traffic flow simulator, environment analysis system, traffic flow simulating method and storage medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a traffic flow simulator capable of appropriately simulating traffic flow of an area including a parking lot and a road environment related to it. SOLUTION: This traffic flow simulator is provided with a state quantity setting part 36 which divides an area being an analysis object, defines plural cells and also defines state quantity showing a cell category in respective defined cells, a module/cell managing part 32 and a simulation executing part 40 which, for each cell, refers to a local neighborhood system comprising other cells around the relevant cell, changes cell state quantity and carries out the traffic flow simulation of a road and its adjacent areas. State quantity showing a category shows at least the road, a vehicle and parking space respectively, and the simulation executing part 40 refers to attractiveness value being an index, with which the vehicle selects parking space, of a cell showing parking space among other cells constituting the local neighborhood system and decides a cell where the vehicle should moves.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a traffic flow simulator for simulating a road environment and its surrounding environment based on a traffic flow model, and more particularly to simulating a road environment including a parking lot. It relates to a traffic flow simulator.

[0002]

2. Description of the Related Art In recent years, traffic congestion due to an increase in traffic volume has become more severe, and it is urgently necessary to take measures to alleviate the traffic congestion. Traffic congestion often occurs due to factors such as the road environment such as road width, signal layout, and signal cycle, as well as the location of shops such as shopping centers located near the road and the location of the parking lot. For this reason, it is desired to execute a simulation considering not only the road environment but also the surrounding environment, and to take measures for realizing a smooth traffic flow.

[0003] When attention is paid to a parking lot in the surrounding environment, for example, Japanese Patent Application Laid-Open No. 8-77486 discloses a technique for simulating a traffic flow in the parking lot. In this technology, a parking lot is represented by a group of meshes of a certain size having attributes such as an entrance E, a parking space P, a passage L, and the like. The calculation is performed to express the operation of the vehicle on a layout. This makes it possible to see the movement of the vehicle in the parking lot by an image or the like.

[0004]

However, in the technology disclosed in the above publication, since only the inside of the parking lot is subjected to the simulation, the influence of the parking lot on the road facing the entrance of the parking lot, Conversely, it is not possible to know the effect on the parking lot from the road facing the entrance. The priority for selecting a parking space can be set in advance for each parking space, but this setting does not take into account the driver's field of view or the driver's tendency. In other words, the driver of the vehicle determines the field of view, the position of the parking space, the presence or absence of surrounding vehicles,
Many factors, such as accessibility to adjacent buildings, determine the space in which to park your vehicle.
Therefore, if the priorities are set in advance, a dynamic model of the vehicle in the parking lot cannot be created, so that there is a problem that the degree of freedom of the simulation is limited.

An object of the present invention is to provide a traffic flow simulator capable of appropriately simulating a traffic flow in an area including a parking lot and a road environment related thereto. A further object of the present invention is to provide a traffic flow simulator capable of appropriately simulating the flow of a vehicle in a parking lot in consideration of the tendency of a driver.

[0006]

SUMMARY OF THE INVENTION It is an object of the present invention to provide a cell defining means for dividing a region to be analyzed to define a plurality of cells, and for each of the defined cells, indicating a category of the cell. A category definition means for defining a state quantity;
For each of the cells, by referring to a local neighborhood consisting of other cells located in a predetermined range of the cell, and changing the state amount of the cell, a predetermined area adjacent to the road and the road is changed. A simulation means for executing a simulation of a traffic flow, wherein the state quantity indicating the category can at least indicate a road, a vehicle, and a parking space in a parking lot, respectively, Of the other cells constituting the local neighborhood system, of the cells indicating the parking space, the vehicle refers to an attractive value that is an index for selecting a parking space, and determines the cell to which the vehicle should move. Achieved by the featured traffic flow simulator. According to the present invention, an attractive value for selecting a parking space is provided, and a parking space where a vehicle should be parked is determined according to an attractive value of another cell constituting the local neighborhood system. Therefore, the movement of the vehicle in the parking lot can be made more realistic. Since the movement of the vehicle in the parking lot can be more appropriately simulated, it is possible to appropriately simulate the influence on the surrounding environment such as the road around the parking lot.

[0007] For example, the above-mentioned attractiveness values include the entrance of a building having a parking lot, the entrance of a parking lot, the presence or absence of a vehicle located in an adjacent parking space, the size of a vehicle located in an adjacent vehicle space, and It is preferable that a value corresponding to at least two or more of the positions of the building is represented by a sum of values weighted by weighting coefficients. With the corresponding value and the weighting coefficient, it is possible to set an attractive value in consideration of the driver's preference, and it is possible to execute a more realistic simulation. This attractive value may be determined according to the parking space, or the attractive value is:
A corresponding value determined corresponding to the parking space,
It may be determined by a weighting coefficient determined corresponding to the vehicle.

[0008] In a further preferred aspect of the present invention, another cell constituting the local neighborhood system is determined in advance corresponding to the cell. That is, by setting a local neighborhood system for each cell, the surrounding situation to be referred to can be changed according to the position of the cell. further,
It is more preferable that another cell constituting the local neighborhood system is determined in advance corresponding to the cell. For example, the driver mainly pays attention to the front while the vehicle is traveling, so that a more appropriate simulation can be performed by setting more cells located in the traveling direction of the vehicle as cells constituting the local neighborhood system. It is possible to execute. Alternatively, another cell constituting the local neighborhood system corresponds to a cell located in a predetermined range from a cell indicating a vehicle, and
The predetermined range may be defined as a state quantity.

In a further preferred aspect of the present invention, the field of view from the cell indicating the vehicle is further defined as a state quantity, and the cells constituting the local neighborhood system are viewed from the vehicle according to the field of view. The configuration is such that cells that cannot be obtained are removed, and the remaining cells are used as cells constituting a local neighborhood system. For example, in the case where the view is obstructed by a building or another vehicle, it is not possible to see anything behind the building or the other vehicle in the viewing direction.
This embodiment takes such a state into account, and thereby makes the movement of the vehicle more realistic.

In another embodiment of the present invention, a cell defining means for dividing a region to be analyzed to define a plurality of cells, and a state quantity indicating a category of the cell in each of the defined cells Category definition means for defining
For each of the cells, by referring to a local neighborhood consisting of other cells located in a predetermined range of the cell and changing the state amount of the cell, at least traffic in a predetermined area adjacent to the road A traffic flow simulator comprising a simulation means for executing a flow simulation, wherein the state quantity indicating the category can indicate a road, a vehicle, and a parking space in a parking lot, respectively, and the state quantity corresponding to the road. Of the cells having a state quantity corresponding to the road in at least three directions from the self, a state quantity indicating the ease of passage of the road is assigned, and the simulation means includes According to the state quantity indicating, calculate the probability indicating the traveling direction of the vehicle, according to the probability, determine the direction the vehicle should travel, It is configured to change the state amount indicating the category of the serial cell.

According to this embodiment, at a so-called intersection, the direction in which the vehicle should travel is determined stochastically in consideration of the ease of traffic of the vehicle. Therefore, it is possible to realize a simulation reflecting the driver's preference. The above-mentioned ease of passage is related to the road width, and it is preferable that the moving probability of the vehicle is determined based on the ratio of the road width. Note that the road means an area where vehicles can pass, and includes a public road, a private road, or a road where vehicles can pass in a parking lot.

In still another embodiment of the present invention, an environment analysis system includes a traffic flow simulator configured as described above, and parking lot data setting means for setting various data relating to a building and a parking space. The parking lot data setting means sets the size, shape and arrangement of the building, and also determines the area where the parking space can be arranged, whereby the state quantity indicating the category in the cell is defined. Further, the object of the present invention is also achieved by a simulation method including steps corresponding to various components of the traffic flow simulator, and a computer-readable storage medium storing a program including the steps.

In the present invention, for example, the cell definition means and the category definition means are mainly realized by the state quantity setting section and the module / cell management section shown in FIG. 2, and the simulation means is mainly shown in FIG. This is realized by the simulation execution unit.

[0014]

Embodiments of the present invention will be described below with reference to the accompanying drawings. FIG. 1 is a block diagram showing hardware for realizing a traffic flow simulator according to the first embodiment of the present invention, and FIG.
3 is a block diagram illustrating functions of a main part of the traffic flow simulator according to the first embodiment. As shown in FIG. 1, this traffic flow simulator includes a CPU 12, a memory 14, an external storage device 16, an interface (I
/ F) 18, a display device 20 such as a CRT, a mouse,
And an input device 22 such as a keyboard.
The CPU 12, the memory 14, and the I / F 18 are connected via a data bus 24. Also, the external storage device 1
6. The display device 20 and the input device 22 can be connected to the data bus 24 via the I / F 18, whereby the CPU
12, data can be exchanged. The memory 14 has a main memory for temporarily storing data under simulation and a running simulation program. Further, the external storage device 16 stores a program necessary for operating the traffic flow simulator according to the present embodiment.

The traffic flow simulator can be considered to have a function as shown in FIG. That is, the traffic flow simulator 10 includes a module / cell management unit 32 that manages cells and modules, which will be described later, a cell state amount storage unit 34 that stores a state amount for each cell, and a state that sets a state amount corresponding to a cell. A quantity setting unit 36, a simulation condition setting / storage unit 38 that sets simulation conditions and stores the conditions, a simulation execution unit 40 that executes a simulation based on predetermined simulation conditions, and stores the simulation results. Simulation result storage unit 4
2 is provided.

Next, the operation principle of the traffic flow simulator according to this embodiment, and the cells and modules will be described. This traffic flow simulator performs modeling using cellular automata (Cellular Automata; CA). That is, the analysis area is divided into partitioned areas called cells, discrete state quantities representing internal states on each cell are defined, and the state quantities are discrete-time-determined using local neighborhood rules that determine the interaction between neighboring cells. The transition is made along the course of.

In the present embodiment, a plane having a certain size (for example, 150 m × 150 m) is one unit to be analyzed, which is called a module, and the module is divided into a predetermined number (for example, 21 × 21) of cells. Divided. Roads, stop lines, cars, parking areas, and the like are defined as state quantities. FIG. 3 is a diagram illustrating an example of a module used in the present embodiment. FIG. 3 is a module showing a certain intersection, in which one grid represents one cell. Further, the pattern applied to the cell indicates the state quantity defined for the cell.

In FIG. 3, for example, a cell 301 indicates an area other than a road (for example, a building). Cell 3
02 indicates a road, and cell 303 indicates a stop line or signal. In the present embodiment, corresponding to each cell,
“Non-road area”, “No entry road”, “Right turn off entry road (see cells 304 and 305)”, “Road”,
"Stop line (signal)" and "car", "parking road",
Twelve state quantities indicating "parking lot entrance", "parking lot exit", "parking space", "shopping center entrance", and "shopping center (building)" are provided. That is, each of the cells is assigned one of the 12 numerical values (for example, 1 to 12) indicating the category of the cell.

The following describes these state quantities. (1) “Non-road area” is an area where vehicles cannot enter (including rivers, fields, residential areas, etc.)
Means Note that even if the area is not a road,
The building that owns the parking lot (the shopping center in the present embodiment) is given another state quantity as described later. (2) "No entry road" means oncoming lanes, one-way roads,
It means an area such as a pedestrian road where a certain vehicle cannot enter even if it is a road. (3) “Right-turn prohibited road” means an area where vehicles that have turned right cannot enter. (4) “Road” means a road other than the above (2) and (3). (5) "Stop line (signal)" indicates that a signal is present. When the state quantity indicating the cell category indicates a signal, a state quantity indicating the color of the signal (red, yellow, blue) and a display time (lighting time) of each color are further assigned. ing. (6) "Car" indicates that a car is located in that cell. When the state quantity indicating the cell category indicates a car, various state quantities such as a vehicle speed, a traveling direction of the vehicle, a driver's view, a vehicle size, and the like are assigned as described later. ing.

The following state variables are specific to the cells in the module containing the parking lot. FIG. 4 is a diagram illustrating an example of a module including a store and a parking lot owned by the store (hereinafter, referred to as a “store module”). In FIG. 4, cells 401 are, like those in FIG.
Indicates a "non-road area". Hereinafter, with reference to FIG.
A description will be given of the state quantity specific to the cell in the module including the parking lot. (7) “Road in parking lot” (cell 402) indicates a road in the parking lot. Neighboring system information to be described later is given to the state quantity of the road in the parking lot. (8) “Parking entrance” (cell 403) indicates the entrance of the parking lot, and access to the inside of the parking lot is possible from this position. This parking lot entrance is a cell (not shown) having the state quantity of the road in the same module or an adjacent module.
, So that the vehicle can enter the parking lot through the parking lot entrance. When the cell category indicates a parking lot entrance, a state quantity indicating a time required for a procedure at the parking lot entrance (for example, issuance of a parking ticket) is assigned. (9) The “parking lot exit” (cell 404) indicates the exit of the parking lot, from which the parking lot can access an external road. Like the parking entrance, the parking exit is adjacent to a cell (not shown) having a road state variable, through which vehicles can exit the parking lot. In addition, a state quantity indicating a time required for a procedure at a parking lot exit (for example, payment of a parking fee) is assigned to the state quantity. (10) “Parking space” (cell 405) indicates a space where a vehicle can be parked. The parking space includes an attractive value that is an index for the driver to select a parking space when the vehicle is parked (for example, that parking is easy, that the vehicle is adjacent to the entrance of the parking lot, that the entrance of the shopping center is Is adjacent to). (11) "Entrance to shopping center" (cell 406)
Indicates an entrance for accessing a shopping center (building). The position of the entrance of the shopping center is one of the factors for determining the attractiveness value. (12) “Shopping Center (Building)” (Cell 40
7) shows a building related to a parking lot. This is not necessarily a shopping center, but may be a facility having a parking lot (for example, a public hall, a convenience store, or an amusement facility).

The various state quantities provided corresponding to the cells will be further described. As shown in FIG. 5, in addition to the state quantity indicating the category corresponding to the cell position (x, y), various other state quantities are assigned according to the value of the state quantity indicating the category. I am getting it.
For example, corresponding to category (5) (ie, "stop line (signal)"), the state quantity indicating the color of the signal, and
A state quantity indicating the lighting time of each color signal is assigned.

For the category (6) "vehicle", six kinds of state quantities of a vehicle speed, a traveling direction, a right / left turn, a visual field, and a vehicle size are defined. These will be described below. Vehicle speed The vehicle speed is calculated per unit time during the simulation.
This is a state quantity indicating the number of cells in which the vehicle can travel. For example, if the state quantity is 1, the vehicle can travel in the traveling direction by one cell per unit time. Traveling direction The traveling direction is a state quantity indicating the traveling direction of the vehicle. Right / left turn In the state quantity indicating “right / left turn”, in addition to being able to indicate straight ahead, right turn, and left turn at the intersection located in front of the traveling direction of the road, a cell indicating the parking lot entrance adjacent to the cell indicating the road If there is, entry to the parking lot can be indicated. Field of View The field of view is a state quantity that indicates the driver's field of view. This varies depending on the situation around the vehicle. For example, the state quantity is changed by an object (building) that blocks the visual field. Vehicle size The state quantity indicating “vehicle size” includes at least the width of the vehicle. In addition, the length and height of the vehicle may be included. Among the above-mentioned state quantities, and, together with nearby system information corresponding to a parking lot road, a parking lot entrance and a parking lot exit to be described later, they are used to determine a range that the driver of the vehicle can see in the parking lot. Can be

Next, a description will be given of the neighboring system information, which is the state quantity provided in the cell arranged in the area corresponding to the parking lot. The neighboring system information specifies a candidate for determining a parking space to be parked when a vehicle is parked in a parking lot. For convenience of explanation, an explanation will be given using a part of the store module shown in FIG. In the store module shown in FIG.
03, neighborhood systems corresponding to the parking lot roads 604 and 605 are shown in FIGS. 6B to 6D, respectively. In addition,
6B to 6D, broken lines 601 and 602 are shown.
Correspond to the outer edges 601 and 602 of the module in FIG.

For example, in FIG. 6B, when the vehicle is located in the cell 603 and the vehicle has the traveling direction of the arrow, a predetermined number of The cell has been determined as a neighbor system. That is, information (for example, a cell number and a cell coordinate value) for specifying a plurality of cells shown in FIG. 6B is assigned to the cell 603 as the neighboring system information. Similarly, in FIGS. 6 (c) and 6 (d), a predetermined number of cells are determined as neighbors in the traveling direction and the left-right direction of the vehicle.

As described above, in the present embodiment, for each cell corresponding to the area in the parking lot, a predetermined range of cells is determined as a neighboring system for each traveling direction of the vehicle, and the cells in the predetermined range are specified. Is assigned as neighboring system information. This neighborhood information can be arbitrarily set by the operator. Further, as will be described in detail later, in the parking space, an attractive value serving as an index for the driver to select the parking space when the vehicle is parked is provided as a state quantity according to the surrounding situation. Therefore, in a simulation described below, a place to park is determined with reference to the attractiveness value in the cell determined as the neighboring system based on the neighboring system information.

In this embodiment, the parking lot entrance /
Distance to exit, distance to shopping center entrance, size of vehicle in cell adjacent to parking space, number of vehicles in cell adjacent to parking space (for example, parking on both sides, one side The attractiveness value is determined based on the location of the shopping center, etc.). More specifically, an attractive value is determined by determining an amount corresponding to the above condition and multiplying the amount by a coefficient. The amount and coefficient corresponding to the above conditions can be arbitrarily set by the operator, but in particular, the coefficient is determined by actually investigating the movement of the vehicle in the parking lot and based on the investigation result. A realistic simulation can be performed.

The operation of the simulator 10 configured as described above will be described below. FIG. 7 is a flowchart showing a process for setting simulation conditions.
As shown in FIG. 2, the operator first creates a module necessary to create a space to be simulated. More specifically, cells constituting a module include:
A state quantity indicating a predetermined category is given (step 70).
1, 702). The data provided from the input device 22 is
The state quantity setting unit 36 transmits the data including the information specifying the cell and the corresponding state quantity to the module / cell management unit 32 in response to this. The module / cell management unit 32 stores the given data in a predetermined area of the cell state quantity storage unit 34 (Step 703). For example, in a module as shown in FIG. 4, a state quantity indicating a category is assigned to each cell, and then the categories (7) to (10) (that is, “road in parking lot”, “parking lot entrance”, “ Neighboring system information is set for each of the cells to which the state quantities of “parking lot exit” and “parking space” are assigned. In the cell to which the category (8) is assigned, the entry procedure time is given, while in the cell to which the category (9) is assigned, the exit procedure time is given. Further, the module / cell management unit 32
A value (for example, an attractive value) obtained based on the set state quantity is calculated, and the obtained value is stored in a predetermined area of the cell state quantity storage unit 34 in association with the cell (step 70).
4).

The operator operates the input device 22 to input data relating to the temporal elements. The temporal element includes various information about the vehicle, in addition to the simulation time, each color of each traffic light. The information about the vehicle includes time intervals of vehicles entering the module, respective speeds of vehicles entering the module at this time interval,
It includes a traveling direction, a type such as a right / left turn (more specifically, a type of going straight, turning left / right or entering a parking lot), a field of view, and a vehicle size. Data on these temporal elements is given to the simulation condition setting / storage unit 38.

Simulation condition setting / storage section 38
When the data is received, the module / cell management unit 3 stores the data relating to the category initially set in the cell (for example, the time interval of each color of the traffic light).
2, and stored in the cell state quantity storage unit 34 in association with the related cell. The simulation condition setting / storage section 38 stores data other than the above in its own memory (not shown). In this way, it is possible to set a module to be a simulation space and conditions for executing the simulation.

Next, the processing mainly executed by the simulation execution section 40 will be described below. FIG. 8 is a flowchart illustrating the simulation processing according to the present embodiment. First, in response to the operator operating the input device 22 to instruct the start of the simulation, the simulation execution unit 40 is activated. The simulation executing unit 40 selects one of the modules arranged in the simulation space (Step 80).
1) Then, any cell in the selected module is selected (step 802). Next, referring to the state quantity indicating the category of the cell, if necessary, the corresponding local neighborhood is referred to (step 803). In the present embodiment, when the state quantity indicating the category of a cell is a vehicle, a local neighborhood is referred to. At the time of setting the module / cell, the cell to which the state quantity shown in the above (2) to (5) is given as a category with respect to the road,
When a vehicle is present, that is, for a cell that was initially in one of the categories (2) to (5) but subsequently becomes a category (6), The following cells are determined as the local neighborhood according to the traveling direction and the state quantity indicating the right / left turn (see FIG. 5).

For example, if the state quantity indicating the traveling direction of the vehicle indicates "straight ahead", the position of the cell in which the vehicle is located (ie, the cell of category (6)) is located ahead of the cell in the traveling direction. Are determined as local neighbors. Alternatively, when indicating "left turn" or "right turn", a predetermined number of cells located on the left side or right side of the traveling direction, respectively, are determined as local neighbors, in addition to the cells located on the front side in the traveling direction. Further, when a module / cell is set, if a vehicle exists in a cell to which a state quantity relating to the inside of a parking lot (that is, categories (7) to (10)) is given as a category, that is, initially, Cells that were in any of the categories (7) to (10) and later become the category (6) are determined based on the neighboring system information (see FIG. 5) as described above. Is determined as a local neighborhood.

Next, the simulation execution unit 40
The state quantity of the cell is changed with reference to the local neighborhood and the temporal element set in step 705. For example, the simulation execution unit 40 inputs a vehicle coming out of another adjacent module to a cell connected thereto, and sets a vehicle having a predetermined state quantity according to a time interval of inputting to the module. The module is put into a cell at a predetermined position on the outer edge of the module.

When the state quantity indicating the category of the cell is “stop line (signal)” (that is, category (5)), the simulation execution unit 40 refers to the simulation time and refers to the signal state. (See Fig. 5)
Is changed.

Next, the processing relating to a cell having a state quantity indicating a vehicle will be described below. For cells that were initially in one of categories (2) to (5) but subsequently become category (6), refer to the local neighborhood determined in step 803. ,
The state quantity of the cell is changed according to the state quantity indicating the vehicle speed, the traveling direction, and the right / left turn. For example, when the traveling direction of the vehicle is straight ahead, the category of the cell is indicated by referring to a cell near the local area and when the category of the predetermined cell is not (6) (that is, “vehicle”). The state quantity is the initial state (category (2)-
(5)), and the state quantity indicating the category of the cell ahead in the traveling direction by the number according to the vehicle speed is changed to “vehicle” (category (6)). For the cell whose category is changed to (6) "vehicle", the state quantities (vehicle speed, traveling direction, right / left turn, field of view, vehicle size) related to category (6) are also changed accompanying the latter change. You.

Even when the traveling direction of the vehicle is a left turn or a right turn, referring to the state quantity of a cell near the local area, if a predetermined condition is met, the state quantity indicating the category of the cell is changed. Early ones (Category (2)-(5)
), And the state quantity indicating the category of the cell on the left or right side of the cell is changed to “vehicle” (category (6)). A cell which initially has a state quantity of "stop line (signal)" (category (5)) and which currently has a state quantity of "vehicle" (category (6)) is a traffic light. The state quantity is controlled according to the state.

Next, initially, categories (7) to (1)
After that, the process of changing the state quantity for a cell which has been classified into the category (6), which is any one of the categories (0), will be described in more detail. FIG. 9 is a flowchart showing a process of changing the state quantity in the parking lot. FIG.
As shown in (1), the simulation execution unit 40 checks a cell that can be a neighboring system based on neighboring system information (see FIG. 5) corresponding to the cell. Next, a cell located behind an obstacle (for example, a vehicle) is found in consideration of the state quantity indicating the visual field (see FIG. 5) (step 901). In this embodiment, an obstacle may be a shopping center (category (12)) in addition to the vehicle.

For example, as shown in FIG. 10 (a), it is assumed that a vehicle is located in cell 603, and that the cells are located in cells 1001 and 1002 among the cells determined as the neighboring system. . In this case, cells that cannot be seen from the position of the cell 603 are found by the vehicles located in the cells 1001 and 1002 in consideration of the visual field related to the cell 603. For example, cells 1003, 100
4 denotes a vehicle located in the cell 1001 and a cell 603
It cannot be seen from the position. In this way, as shown in FIG. 10D, in the next step 902, a cell that needs to refer to its attractiveness value is determined. FIG.
0 (b) indicates cells 1001, 1002, 1005, 10
FIG. 10E illustrates a cell that cannot be seen from the position of the cell 604 by the vehicle located at 06.
FIG. 4 is a diagram showing a state in which such a cell is excluded from a neighboring system. Similarly, FIG. 10C shows cells 1002, 1
FIG. 10 is a diagram illustrating cells that cannot be seen from the position of the cell 605 by the vehicle located at 005 and 1006;
FIG. 10F is a diagram showing a state in which such a cell is excluded from the neighboring system.

When the cells to be excluded from the neighboring system are determined in this way, the attractive value of the cell of the category (10) (that is, “parking space”) among the remaining cells of the neighboring system is referred to. Then, the cell having the maximum value is specified (step 902). Next, the simulation executing unit 40 determines whether or not the maximum attractiveness value found in Step 902 is equal to or _larger than a predetermined threshold _Ath . In the present embodiment, the threshold value _Ath is set to a predetermined value. However, the threshold value _Ath may be arbitrarily set by the operator in step 704 in FIG. 7, or may be set to the category (6) ( That is, it may be defined as a state quantity of a cell of “vehicle”. In particular, in the latter case, the threshold value _Ath can be set for each vehicle. Step 903
If it is determined to be No, the simulation execution unit 40 changes the state quantity so that the vehicle moves along the traveling direction of the vehicle. This process is the same as the process of changing the state quantity of a cell when the vehicle corresponds to a state where the vehicle is located on a normal road.

On the other hand, at step 904,
s), the simulation execution unit 4
If 0, the target cell to which the cell having the state quantity indicating this vehicle should move is determined as the cell having the maximum attractive value (step 905). Therefore, the simulation execution unit 40
Changes the state quantity of the cell so that the vehicle moves toward the target cell (step 906). That is, a process of allocating the state quantity of the cell where the vehicle is located to a cell located on the way to the target cell is executed.

Initially, the state quantity corresponds to category (8) or (9) (ie, “parking lot entrance” or “parking lot exit”), which is currently the category (6) (ie, “vehicle parking lot”). )), The state quantity is controlled according to the entry procedure time or exit procedure time. That is, the state of the cell is maintained until the entry procedure time or the exit procedure time elapses. When the state quantity of a certain cell is changed in this way (step 804), the simulation execution unit 40 repeats the processing of steps 802 to 803 for all cells of a certain module (step 8).
05).

When the processing for all cells of a certain module is completed (Yes in step 805),
The simulation execution unit 40 transmits the state quantity of each cell to the module / cell management unit 32. In response to this, the module / cell management unit 32 stores the transmitted state quantity in the cell state storage unit 34 in association with each cell. On the other hand, the simulation execution unit 40 stores the state quantity of each cell in the simulation result storage unit 42 in association with the simulation time, and creates image data representing the state quantity indicating the category of each cell in color. This is output to the display device 20 (step 80).
6).

The simulation executing section 40 executes such processing for all modules (step 807). If the simulation time has not elapsed (No in step 808), the simulation time is incremented, and the process returns to step 801.
On the other hand, if the simulation time has elapsed (Yes in step 808), the process ends.

FIGS. 11 and 12 are examples of images representing simulations executed by the simulator 10 according to the present embodiment. The data for such images is
During the simulation, it is generated in step 806 by the simulation execution unit 40. FIG. 11 is an example of a simulation in the store module, and FIG.
It is an example of the simulation of the road condition of the periphery including the parking lot of FIG.

In the store module of FIG. 11, a large number of parking spaces (for example, reference numeral 1102) are arranged on one side of a building (shopping center) 1101. The vehicle arranged in the cell (for example, see reference numeral 1103) is moved so as to move the vehicle to the parking space having the maximum attractive value with reference to the attractive value of the parking space according to the flowchart shown in FIG. . FIG. 12 shows the store module shown in FIG.
It is a combination of various intersection modules with the form of a surrounding road. From FIG. 12, it is possible to understand what kind of traffic flow is occurring around the shopping center 1101.

As described above, in the present embodiment, a predetermined area including a road, a building, and the like is defined as an analysis space, and the analysis space is divided into a plurality of cells, and a state indicating a category in each of the cells is defined. We define quantities and create models for simulation. In the simulation process, the state quantity of each cell is changed while taking into account the state of peripheral cells constituting the local neighborhood. Furthermore, this state quantity includes information indicating various states in the parking lot (for example, a parking lot entrance / exit, a parking space, a shopping center entrance / exit, a shopping center) in addition to the road and the vehicle. Therefore, according to the present embodiment, it is possible to simulate the traffic flow in the area including the parking lot and the surrounding road environment without executing complicated processing.

In the above-described embodiment,
In the parking lot, an attractive value is assigned as a state quantity to the parking space, and a parking space to be parked is determined based on the attractive value. Therefore, it is possible to realize a more realistic simulation in consideration of the tendency of the driver.

Next, a second embodiment of the present invention will be described. In the first embodiment, the neighboring system information as shown in FIG. 6 is given to the cells arranged in the area corresponding to the inside of the parking lot. That is, in the first embodiment, the cells constituting the local neighborhood are determined in advance for each cell in the parking lot. On the other hand, in the second embodiment, a cell that defines an elliptical local neighborhood including a cell of a vehicle located in a parking lot is defined. Initially, a cell whose state quantity indicating a category indicates the inside of a parking lot (that is, category (7) “road in parking lot” to category (10) “parking space”) has a state quantity of a category ( 6)
(Ie, "vehicle"). At this time, as shown in FIG. 13A, cells included in the ellipse 1302 including the cell 1301 of the vehicle are determined as cells constituting the local neighborhood. The size and position of the ellipse can be set arbitrarily in accordance with the cell having the state quantity of the category (6). That is, the size and position of the cell constituting the local neighborhood can be defined for each vehicle. FIG. 14 is a diagram showing state quantities provided corresponding to cells in the second embodiment.
As shown in FIG. 14, in the second embodiment, in the case of category (6), neighboring system information (ellipse size, ellipse position) is assigned correspondingly.

As in the first embodiment, any one of the other cells constituting the local neighborhood system of a certain cell is
When an obstacle such as a vehicle is shown, a field of view that cannot be seen from the cell is determined in consideration of the field of view of the cell. For example, as shown in FIG.
When the cells 1303 and 1304 of the cells constituting the local neighborhood system of the cell 1301 indicate a vehicle, the cells 1303 and 1304 are located on the rear side in the viewing direction from the cell 1301 (for example, reference numeral 1305). , 1306) are removed from the cells constituting the local neighborhood system.

The thus constructed traffic flow simulator also operates in the same manner as in the first embodiment. That is, for setting the simulation conditions, the flowchart shown in FIG. 7 is executed, and in the simulation,
The flowcharts shown in FIGS. 8 and 9 are executed. In addition,
In this embodiment, when setting the state quantity of the cell indicating the vehicle in step 702, the neighboring system information is also set, and when setting the closing condition of the vehicle in step 705, for each vehicle to be inserted, Neighboring system information is set. According to the present embodiment, since the neighboring system information can be set as predetermined for each vehicle, it is possible to find a parking space where the vehicle should move using a local neighboring system unique to the vehicle. Become. Therefore, the tendency of the driver can be reflected in the simulation, and a more realistic simulation can be realized.

Next, a third embodiment of the present invention will be described. In the first embodiment and the second embodiment, an attractive value is calculated in advance for a cell of a parking space, and a cell of a vehicle examines the attractive value to find a cell having a maximum attractive value ( (See steps 902 to 905 in FIG. 9). On the other hand, in the third embodiment, a calculation formula for calculating the attractiveness value is provided for each vehicle, and the tendency of the driver can be more reflected in the simulation.

As described above, the attractiveness value is calculated based on the parking lot entrance /
Determine the distance corresponding to the distance to the exit, the distance to the entrance to the shopping center, the number of vehicles adjacent to the parking space, the position of the shopping center, etc., and determine the attractiveness value by multiplying this by a coefficient and adding it. Can be In other words, attraction value _{X, X = a 0 x 0 +} a 1 x 1 + ... + a n x n · · · · (1) that can be obtained by the equation. Here, x _i (i =
0, 1,..., N) are quantities corresponding to the conditions, a _i (i =
.., N) are the corresponding coefficients. In the third embodiment, the cell of a vehicle is unique coefficients a ₀ ~a _n is adapted to be assigned as the quantity of state (see FIG. 15).

The operation of the traffic flow simulator according to this embodiment will be described below. The processing for setting the simulation conditions is substantially the same as that shown in FIG. 7 except for the following points. That is, in the third embodiment, in step 704, the calculation of the attractiveness value is not performed. Further, with respect to the cell category (6) "vehicle", as the quantity of state, together with the coefficients a ₀ ~a _n for weighting attractive value calculation is set, for the vehicle to be introduced, the coefficients a ₀ ~a _n is set.

On the other hand, in the simulation, in the processing relating to the store module, the processing shown in FIG. 16 is executed. In FIG. 16, the same processes as those shown in FIG. 9 are denoted by the same reference numerals. As shown in FIG. 16, in this process, after determining the cells to be excluded from the vicinity, the remaining cells are assigned to the ones indicating the parking spaces, and the amounts x ₀ to x _n corresponding to the conditions are assigned. ,
by using the a ₀ ~a _n, it performs the calculation shown in equation (1),
The attractive value of each cell is calculated (step 1601). Next, among the obtained attractive values, the one with the largest value is determined (step 1602). Below, the maximum attractive value,
It is determined whether the threshold value _{A th} or more, to perform necessary processing (step 903～ step 906).

According to the present embodiment, a unique coefficient is assigned to each vehicle, and an attractive value is calculated based on this. Therefore, in some vehicles, the vicinity of the entrance to the shopping center is set as the largest factor for selecting a parking space, and in other vehicles, the presence or absence of an adjacent parking space is set as the largest factor for selection. , The preference for parking space selection can be set as desired. Therefore, a more realistic simulation can be realized in consideration of the tendency of the driver.

An environment analysis system can be constructed using the traffic flow simulation described in detail above. FIG. 17 is a block diagram showing a configuration of a main part of an environment analysis system for analyzing an influence on a surrounding area when a facility having a parking lot such as a shopping center is created. This environment analysis system can be realized with a hardware configuration as shown in FIG.
As shown in FIG. 17, this environment analysis system includes, in particular,
By changing the state quantity of the cell that owns the parking lot, it is possible to change the position of the shopping center, the position of the entrance and exit, the arrangement of the parking space, the position of the parking entrance and the like as desired.

The environment analysis system 50 includes, in particular, a store module setting unit 52 for changing a state quantity of a cell constituting a store module corresponding to a shopping center having a parking lot as desired. Have been. The store module setting unit 52 defines the area, shape, and position of the store as shown in FIG.
Based on the store area, shape, and position setting unit 62 that generates store data based on this, based on the generated store data, an area that can be allocated as a parking lot is determined, and a parking area calculation that generates parking lot data related thereto is determined. Part 64
And an entrance position setting unit 66 that generates store entrance data relating to the position of the entrance based on the store data, and various data (parking space related data) indicating the arrangement of the parking space based on the parking lot data. A parking space layout setting unit 68, a parking lot entrance setting unit 70 that generates parking lot entrance data at the position of the parking lot entrance based on the parking lot data, store data, parking lot data, parking space related data, parking lot It has a cell coordinate conversion unit 72 that receives the entrance data and outputs the coordinates of each cell in the store module and the corresponding category to the state quantity setting unit 36 (FIG. 17) based on the data.

By operating the input device 20, the operator can set a store, its entrance, a parking area, a layout of a parking space, a layout of a parking lot entrance, and the like as desired. At this time, it is preferable to display an image showing the structure of the store and the parking lot on the screen of the display device 22. When the structure of the store and the parking lot is determined by the store module setting unit 52 in this way, this is transmitted to the module / cell management unit 32 via the state amount setting unit 36.
Are stored in the cell state amount storage unit 34. In the environment analysis system configured as described above, the simulation itself operates similarly to the traffic flow simulator described in the first to third embodiments.

According to the environment analysis system of this embodiment, the simulation can be executed by appropriately changing the structures of the store and the parking lot.
By providing a store or a parking lot, it is possible to simulate the influence on the surrounding road environment, and it is possible to determine the arrangement of the store and the parking lot which is most preferable for the surrounding environment.

The present invention is not limited to the above embodiments, and various modifications are possible within the scope of the invention described in the claims, and these are also included in the scope of the present invention. Needless to say, this is done. For example, in the above-described embodiment, a store is used as a building, in particular, a shopping center is used. However, the present invention is not limited to this, and public facilities such as a public hall and a district center, a collection / delivery center where trucks enter and leave, and the like. It is apparent that the traffic flow simulator and the environment analysis system according to the present invention can be applied to the above.

In the above embodiment, a plane having a certain size is used as one unit to be analyzed, and this is called a module. However, the present invention is not limited to this. For example, a module that includes a long and narrow rectangle having a certain width indicating the form of a road or a combination of the rectangles, a plane indicating the form of the exit or entrance of the parking lot, a plane indicating the form of the entire parking lot, a plane indicating the form of the building, etc. , And
The module may be configured to be divided into one or more cells having a predetermined size. Even in this case, the analysis target can be defined by combining the modules.

In particular, in an environment analysis system using the traffic flow simulator, a building (shopping center), a parking lot, and an entrance are modularized, and the shape and arrangement thereof are changed as desired to execute a simulation. Accordingly, it is possible to more smoothly confirm the influence on the road environment and the like. Furthermore, in the third embodiment, the local neighborhood system as in the first embodiment is used. However, the present invention is not limited to this, and the local neighborhood system described in the second embodiment is used. May be adopted.

Further, in the third embodiment,
Coefficient a for determining force value₀~ A _nThe vehicle driver
May be set according to the age of the driver, the area where the driver is located, etc.
No. For example, based on statistically obtained data
Coefficient a for each vehicle₀~ A_nTo be determined
This makes it possible to realize this.

Further, in the above-described embodiment, in correspondence with the state quantity of vehicle (category 6), FIGS.
4 or a state quantity as shown in FIG. 15 is assigned, but the present invention is not limited to this. The amount may be assigned as an amount, and the simulation may be configured to examine how the amount of exhaust gas or noise changes due to the establishment of a store and a parking lot.

Of course, the state quantity indicating the residence time in the shopping center (building) may be set for each vehicle to be inserted, corresponding to the state quantity of the vehicle (category 6). The residence time can be calculated using statistics obtained based on the type, scale, and area of the building. Therefore, for example, the simulation condition setting / storage unit 38 shown in FIG. 2 allocates the statistically obtained residence time to the vehicle to be entered and executes the simulation, thereby realizing a more realistic simulation. Becomes possible. Alternatively, it goes without saying that the residence time may be individually set by the input device.

Since the residence time can be set as described above, it is possible to more accurately estimate the flow and the suspension of the vehicle in the parking lot. In addition, by changing the staying time, the vacant state in the parking lot can be changed, so that the influence on the traffic environment around the parking lot can be more accurately estimated.

There are other factors for selecting a parking space, such as the width of the road in the parking lot, the presence of obstacles such as pillars (especially in the case of an indoor parking lot), and the height of the ceiling. Therefore, the attractiveness value may be set in consideration of these factors. For example, consider a case where there is a road extending in one direction from an intersection in a parking lot and a road extending in another direction. In this case, assuming that a road extending in one direction is wider than a road extending in the other direction, the number of vehicles traveling along the road extending in one direction may be set to be larger. More specifically, the state quantity indicating the intersection in the parking lot (for example, category (13)) is stored in the cell of the intersection in the parking lot.
And a cell having the state quantity is assigned to each of the roads extending from the intersection with a state quantity serving as an index indicating the ease of vehicle passage. For example, this state quantity is
The width of each road connected to the intersection and the ratio to the standard width are shown (see FIG. 19).

An example of a simulation process using a cell having a state quantity as shown in FIG. 19 will be described below. FIG. 20 is a flowchart illustrating an example of a part of a simulation process in a parking lot. The process shown in FIG. 20 can be executed, for example, prior to the process shown in FIG. In this process, it is determined whether or not the category (13) corresponding to the cell (that is, the state quantity indicates “intersection in parking lot”) (step 2001).
When it is determined as Yes (Yes) in Step 2001, the simulation executing unit 40 calculates the moving probability of the vehicle based on the connected road width and the ratio of the road width (Step 2002). The state quantity of the cell is changed according to the moved probability (step 2003).
Thereby, when the vehicle is located in the cell, the traveling direction of the vehicle is determined according to the movement probability.

Note that the movement probability is not limited to one determined based on the road width. For example, it is obvious that the movement probability may be obtained based on the depth of the connected road, the presence or absence of an obstacle existing on the connected road, and the like. Alternatively, the movement probability itself may be defined as a state quantity and assigned as a state quantity corresponding to the category (13). In this case, the movement probability obtained statistically or input to the input device is set as the state quantity.

The presence or absence of obstacles such as road pillars, the width of the parking space, and the like may be set as a state quantity specific to the parking space. By doing so, a more realistic simulation is possible. For example, if the state quantity indicating the width of the parking space is set as a ratio A to the width of the standard parking space, an attractive value in consideration of the parking space can be obtained by multiplying the original attractive value by the ratio A. It becomes possible.

In the above-described embodiment, it goes without saying that a printer may be added to the traffic flow simulator or the environment analysis simulator so that simulation results and the like can be printed. Further, in the present specification, means does not necessarily mean physical means, but also includes a case where the function of each means is realized by software. Furthermore, the function of one means is
Realized by more than one physical means, or
The functions of two or more means may be realized by one physical means.

[0071]

According to the present invention, it is possible to provide a traffic flow simulator capable of appropriately simulating a traffic flow in an area including a parking lot and a road environment related thereto. Further, according to the present invention, it is possible to provide a traffic flow simulator capable of appropriately simulating the flow of a vehicle in a parking lot in consideration of the tendency of a driver.

[Brief description of the drawings]

FIG. 1 is a block diagram showing hardware for realizing a traffic flow simulator according to a first embodiment of the present invention.

FIG. 2 is a block diagram showing functions of main parts of the traffic flow simulator according to the first embodiment.

FIG. 3 is a diagram illustrating an example of a module used in the first embodiment;

FIG. 4 is a diagram illustrating an example of a store module used in the first embodiment.

FIG. 5 is a diagram for explaining various state quantities provided corresponding to cells in the first embodiment.

FIG. 6 is a diagram for explaining neighboring system information according to the first embodiment.

FIG. 7 is a flowchart illustrating a process for setting a simulation condition according to the first embodiment;

FIG. 8 is a flowchart illustrating a simulation process according to the first embodiment;

FIG. 9 is a flowchart illustrating a process of changing a state quantity in a parking lot according to the first embodiment;

FIG. 10 is a diagram for describing a local neighborhood system in consideration of a visual field in the first embodiment.

FIG. 11 is a diagram illustrating an example of a simulation in a store module.

FIG. 12 is a diagram showing an example of a simulation of a road condition around the parking lot shown in FIG. 11;

FIG. 13 is a diagram for explaining a local neighborhood system according to the second embodiment.

FIG. 14 is a diagram showing state quantities provided corresponding to cells in the second embodiment.

FIG. 15 is a diagram showing state quantities provided corresponding to cells in the third embodiment.

FIG. 16 is a flowchart illustrating a state amount changing process in a parking lot according to the third embodiment.

FIG. 17 is a decision block diagram showing a configuration of a main part of the environment analysis system according to the present invention.

FIG. 18 is a block diagram showing the configuration of a store module setting unit in FIG. 17 in more detail.

FIG. 19 is a diagram for explaining another example of various state quantities provided corresponding to cells.

FIG. 20 is a diagram illustrating another example of the processing executed by the simulation execution unit;

[Explanation of symbols]

 Reference Signs List 10 traffic flow simulator 12 CPU 14 memory 16 fixed storage device 18 interface 20 display device 22 input device 32 module / cell management unit 34 cell state amount storage unit 36 state amount setting unit 38 simulation condition setting / storage unit 40 simulation execution unit 42 simulation Result storage unit

Claims (17)

[Claims] 1. A cell defining means for dividing a region to be analyzed to define a plurality of cells; a category defining means for each of the defined cells defining a state quantity indicating a category of the cell; For each of the cells, by referring to a local neighborhood consisting of other cells located within a predetermined range of the cell and changing the state quantity of the cell, at least traffic in a predetermined area adjacent to the road A simulation means for performing a flow simulation, wherein the state quantity indicating the category can indicate at least a road, a vehicle, and a parking space in a parking lot, and the simulation means includes: Among other cells constituting the local neighborhood system, a cell indicating the parking space is an attractive indicator for the vehicle to select a parking space. Referring to value, traffic flow simulator, characterized by determining the vehicle cell to be moved. 2. A cell defining means for dividing a region to be analyzed to define a plurality of cells; a category defining means for each of the defined cells defining a state quantity indicating a category of the cell; For each of the cells, by referring to a local neighborhood consisting of other cells located in a predetermined range of the cell and changing the state amount of the cell, at least traffic in a predetermined area adjacent to the road A traffic flow simulator comprising simulation means for executing flow simulation, wherein the state quantity indicating the category can indicate a road, a vehicle, and a parking space in a parking lot, respectively, and corresponds to the road. A cell that indicates the ease of road traffic in a cell that has a state quantity corresponding to the road in at least three directions from among the cells that have the state quantity The simulation means calculates a movement probability indicating the traveling direction of the vehicle according to the state amount indicating the ease of passage, determines a direction in which the vehicle should travel according to the probability, A traffic flow simulator configured to change a state quantity indicating a cell category. 3. The method according to claim 1, wherein the simulation unit refers to an attractive value of a cell indicating the parking space among other cells constituting the local neighborhood system, the attractive value being an index for the vehicle to select a parking space. The traffic flow simulator according to claim 2, wherein a cell to be moved is determined. 4. The traffic flow simulator according to claim 2, wherein the state quantity indicating the ease of passage is related to a road width. 5. The traffic flow simulator according to claim 4, wherein the movement probability is determined based on a ratio of a road width. 6. The attractiveness value includes a doorway of a building having a parking lot, a doorway of a parking lot, presence or absence of a vehicle located in an adjacent parking space, a size of a vehicle located in an adjacent vehicle space, and The traffic according to any one of claims 1, 3 to 5, wherein a value corresponding to at least two or more of the positions of the building is represented by a sum of values weighted by weighting coefficients. Flow simulator. 7. The traffic flow simulator according to claim 6, wherein the attraction value is determined according to the parking space. 8. The vehicle according to claim 6, wherein the attraction value is determined by a corresponding value determined corresponding to the parking space and a weighting coefficient determined corresponding to the vehicle. The described traffic flow simulator. 9. The other cells constituting the local neighborhood system include:
The traffic flow simulator according to any one of claims 1 to 8, wherein the traffic flow simulator is determined in advance for each cell. 10. The traffic flow simulator according to claim 1, wherein another cell constituting the local neighborhood system is determined in advance corresponding to the cell. 11. The method according to claim 1, wherein another cell constituting the local neighborhood system corresponds to a cell located within a predetermined range from a cell indicating the vehicle, and the predetermined range is defined as a state quantity. The traffic flow simulator according to any one of claims 1 to 8, wherein 12. The traffic flow simulator according to claim 11, wherein the predetermined range substantially corresponds to an ellipse including the cell. 13. A field of view from a cell indicating a vehicle is defined as a state quantity, and a cell which cannot be seen from a vehicle among cells constituting the local neighborhood system is removed according to the field of view. The traffic flow simulator according to any one of claims 1 to 12, wherein the cells are configured to be cells constituting a local neighborhood system. 14. A state quantity indicating a residence time of a vehicle in a parking lot is defined corresponding to the state quantity corresponding to the vehicle, and the simulation means executes a simulation according to the residence time. The traffic flow simulator according to any one of claims 1 to 14, wherein the traffic flow simulator is configured. 15. An environment analysis system comprising: the traffic flow simulator according to claim 1; and parking data setting means for setting various data relating to a building and a parking space. The parking lot data setting means sets the size, shape and arrangement of the building, determines the area where the parking space can be arranged, and thereby defines the state quantity indicating the category in the cell. Characteristic environmental analysis system. 16. A step of dividing a region to be analyzed to define a plurality of cells, a step of defining, for each of the defined cells, a state quantity indicating a category of the cell, With reference to a local neighborhood system consisting of other cells located in a predetermined range of the cell,
Executing a simulation of a traffic flow in a predetermined area adjacent to the road by changing the state quantity of the cell, wherein the state quantity indicating the category is at least , A road, a vehicle, and a parking space in a parking lot, respectively, wherein the step of simulating selects a parking space by a vehicle in a cell indicating the parking space among other cells constituting the local neighborhood system. A method of simulating a traffic flow, characterized in that a cell to which a vehicle is to move is determined with reference to an attractive value serving as an index to be performed. 17. A step of dividing a region to be analyzed to define a plurality of cells, a step of defining a state quantity indicating a category of the cell in each of the defined cells, and a step of defining each of the cells With reference to a local neighborhood system consisting of other cells located in a predetermined range of the cell,
Executing a simulation of a traffic flow of a road and a predetermined area adjacent to the road by changing a state quantity of the cell; and a computer-readable storage storing a program for the simulation of the traffic flow. In the medium, the state quantity indicating the category can at least indicate a road, a vehicle and a parking space in a parking lot, and the step of the simulation includes, among other cells constituting the local neighborhood system, A computer-readable storage, wherein the cell indicating the parking space is configured to determine a cell to which the vehicle should move by referring to an attraction value which is an index by which the vehicle selects the parking space. Medium.