The present invention relates to an architectural model data assistance system and an architectural model data assistance method.
In planning and construction of high-rise buildings, information sharing among parties has been promoted by utilizing architectural model data called building information modeling (BIM) data or the like. The architectural model data is data including a plurality of architectural model parts, and the architectural model parts are data indicating building materials constituting a high-rise building, facilities such as elevators, and the like.
The information constituting the architectural model parts includes at least 2D or 3D shape data, and may further include any accompanying information such as specifications, model numbers, and manufacturers. The architectural model data also includes general BIM data.
Patent Literature 1 discloses a method and a device for performing evaluation using a simulation technique using architectural model data incorporating architectural model parts of an elevator as an input.
In addition, Patent Literature 2 discloses a device that reproduces detailed movements, determinations, and the like of a user at an elevator platform by a technique for simulating use of the elevator.
Patent Literature 1: JP 2014-10659 A
Patent Literature 2: WO 2017/199532 A
However, in the method of simulating a motion of a person using the system disclosed in Patent Literature 1, an action of waiting at a platform or an action of orderly boarding when a large number of people use an elevator is not considered.
In Patent Literature 2, in order to reproduce the orderly boarding action at the elevator, it is necessary to input data of the front-of-line position at the elevator platform.
That is, in the techniques described in Patent Literature 1 and Patent Literature 2, in an architectural model to which architectural model data is input, it is not considered to finely simulate the action of waiting at the platform or the action of orderly boarding when using the elevator without manually additionally inputting the front-of-line position or the like.
Therefore, an object of the present invention is to provide an architectural model data assistance system and an architectural model data assistance method capable of finely simulating an action of waiting at a platform or an action of orderly boarding by an elevator user without manually additionally inputting the front-of-line position or the like.
In order to solve the above problem, for example, the configuration described in the claims is adopted.
The present application includes a plurality of means for solving the above problem, and as an example thereof, the present invention includes a storage unit that stores architectural model data and simulation data, an architectural model data reading unit that reads the architectural model data stored in the storage unit, and a front-of-line position estimation unit that estimates a front-of-line position that is a position at which people who use the elevators start to line up at an elevator platform on the basis of the architectural model data read by the architectural model data reading unit.
According to the present invention, it is possible to realize a simulation in consideration of detailed movements of people at an elevator platform without manual data editing.
Problems, configurations, and effects other than those described above will be clarified by the description of embodiments described below.
Hereinafter, an architectural model data assistance system of the first embodiment example of the present invention (hereinafter, referred to as “the present example”) will be described with reference to
The architectural model data assistance system of the present example includes an arithmetic unit 100, a storage unit 110, an input unit 120, and a display unit 130 connected by a bus 150.
Note that each unit of the architectural model data assistance system may be connected by a network instead of being connected by the bus 150. The input unit 120 and the display unit 130 are additional configurations, and are not necessarily required for the architectural model data assistance system of the present example.
The storage unit 110 has a storage area for storing at least architectural model data 111 and simulation data 112, but may further have a storage area for storing simulation result data 113.
The arithmetic unit 100 includes at least an architectural model data reading unit 101, a front-of-line position estimation unit 102, and a simulation execution unit 103.
Note that the arithmetic unit 100 may be configured as a single arithmetic unit, but the arithmetic unit 100 may be configured to be distributed into a plurality of parts such that a part of the arithmetic unit 100 is provided in a server, which is not illustrated.
The configuration of the architectural model data assistance system of the present example has been described above.
The architectural model data reading unit 101 of the arithmetic unit 100 reads the architectural model data 111 from the storage unit 110. The architectural model data reading unit 101 recognizes the shape of the architectural model data on the basis of the read architectural model data 111, and converts the architectural model data into data of a format that can be executed by the simulation execution unit 103.
Here, converting into data of an executable format means converting the architectural model data 111 into, for example, elevator platform data. That is, in the conversion into the data of an executable format, the architectural model data reading unit 101 extracts the elevator platform data from the architectural model data 111. Then, the architectural model data reading unit 101 inputs the extracted elevator platform data to the front-of-line position estimation unit 102.
Note that, as the processing of extracting the elevator platform data, a method of cutting out a space within a certain distance from the door of an elevator as a platform is conceivable.
The front-of-line position estimation unit 102 estimates the front-of-line position on the basis of the input elevator platform data. The front-of-line position information estimated by the front-of-line position estimation unit 102 is input to the simulation execution unit 103. At this time, data obtained by converting the architectural model data 111 read by the architectural model data reading unit 101 into a simulation executable format is also input to the simulation execution unit 103.
The simulation execution unit 103 estimates detailed movements of people at the elevator platform and stores the simulation result in the simulation result data 113 of the storage unit 110. Note that the simulation result may be directly output and displayed on the display unit 130 without being stored in the storage unit 110.
Note that the simulation in the simulation execution unit 103 can be performed, for example, by using a known simulation technique disclosed in “Development of pedestrian flow simulator for smooth people movement in buildings” (FUJIWARA Masayasu, TORIYABE Satoru, and HATORI Takahiro) presented by the inventors in “The Proceedings of the Elevator, Escalator and Amusement Rides Conference” of The Japan Society of Mechanical Engineers held on Jan. 19, 2018.
As illustrated in
The CPU 201 reads, from the ROM 202, a program code of software for implementing the function of each unit of the architectural model data assistance system of the present example, and executes the program code. Variables and the like generated in the middle of arithmetic processing performed in the architectural model data assistance system of the present example are temporarily written in the RAM 203. The CPU 201 executes the program code recorded in the ROM 202, thereby implementing various functions of the architectural model data assistance system of the present example described above.
As the communication interface 205, for example, a network interface card (NIC) or the like is used. Although not illustrated in
The nonvolatile storage 204 includes nonvolatile memory such as a solid state drive (SSD), and stores and holds programs, data, and the like necessary for the operation of the CPU 201. In addition, the nonvolatile storage 204 constitutes the storage unit 110 in
Next, with reference to the flowchart of
First, an orientation “d” of the largest number of doors is selected among the orientations of the doors of elevators (step S301). For example, in the case of a general face-to-face arrangement in which six elevators are arranged to face each other, the orientations of the doors of the three elevators face the three elevators. In such a case, since the number of elevators facing each other is “3”, which is the maximum, one of the orientations in which the number is the maximum is selected and set to “d”.
To describe by using the specific example of
Next, scanning is performed with a direction rotated by 90 degrees and a direction rotated by −90 degrees with respect to the direction “d” of the orientation 431 of the doors of the elevators as the scanning direction. Then, a position where the distance to a doorway 400 is minimum is scanned regarding the direction rotated by 90 degrees from the direction “d” of the doors. In
As is clear from the graph 413, it is indicated that the point 433 at the end on the doorway 400 side is closest to the doorway. That is, the position 433 at the end on the doorway 400 side among the scanning positions indicated by the dotted line 432 is “p1”.
Next, scanning is performed along a dotted line 434 in the same direction as the direction 431 “d” of the doors from the position “p1” of the point 433, a point closest to the doorway 400 is calculated, and this point 435 is set as “p2” (step S303). Then, the distance to the doorway 400 is obtained at each position of the dotted line 434. The distance between each position of the dotted line 434 and the doorway 400 is indicated by a graph 423. In the graph 423, a vertical axis 421 indicates the scanning position, and a horizontal axis 422 indicates the distance from the doorway 400.
In the graph 423, a portion where the distance from the doorway 400 is minimum is indicated by a range 424 and a range 425, and cannot be uniquely specified. Therefore, the scanning position 435 corresponding to a barycentric position 426 of the plurality of positions where the distance from the doorway 400 is minimum is set as the point “p2” closest to the doorway 400.
Then, the position “p2” of the scanning position 435, which is the point closest to the doorway 400, is output as the front-of-line position (step S304). The front-of-line position estimation processing process using
Here, as illustrated in
First, in step S301 of
Then, in step S302 of
It can be seen from the graph 513 of
Next, in step S303 of
As can be seen from the graph 523, a portion where the distance from the doorway 500 is minimum is a range 524 and a range 525, and cannot be uniquely specified. Therefore, a scanning position 535 that is close to the doorway 500 and corresponds to a barycentric position 526 of the plurality of positions where the distance from the doorway 500 is minimum is set as “p2”.
Then, in step S304 of
Similarly to
First, in step S301 of
Next, in step S302 of
As can be seen from the graph 613, a portion where the distance from the doorway 600 is minimum is a range 614 and a range 615, and cannot be uniquely specified. Thus, a scanning position 633 corresponding to a position 616, which is the barycenter of the ranges 614 and 615 where the distance from the doorway 600 is minimum, is set as point “p1”.
Then, in step S303 of
As can be seen from
Then, in step S304 of
Next, an architectural model data assistance system of the second embodiment example of the present invention will be described with reference to
That is, the second embodiment example of the present invention is an embodiment example in which measurement data measured by the measurement unit 140 is used as an input of the front-of-line position estimation processing. Hereinafter, differences from the first embodiment example will be mainly described with reference to
Referring to
Similarly to the first embodiment example illustrated in
In addition, as in the first embodiment example, the arithmetic unit 100 includes an architectural model data reading unit 101, a front-of-line position estimation unit 102, and a simulation execution unit 103. The arithmetic unit 100 may be configured as a single arithmetic unit or may be configured to be distributed into a plurality of parts.
Note that an image sensor such as a camera, a depth sensor, an infrared sensor, or the like is used as the measurement unit 140.
First, the measurement unit 140 such as a camera or the like measures the staying time of people including an elevator user for each position of the elevator platform (step S801). Then, a position “p3” where the staying time of the people is long is calculated (step S802). Here, the position “p3” where the staying time is long refers to a place where the density of people is high at the elevator platform, and, for example, a space indicated by numeral 1010 in
Next,
In addition,
Here, the architectural model data 111 and elevator platform data included in the architectural model data 111 will be described. The architectural model data 111 includes elevator platform data. Here, the elevator platform data includes at least information regarding a floor 1100 of the elevator platform, information regarding elevators 1101, 1102, 1103, and 1104, and information of a doorway or a position 1110 connected to the doorway.
The information regarding the floor 1100 and the information regarding the elevators 1101, 1102, 1103, and 1104 have positions and shapes, and
The doorway of the architectural model data assistance system of the present invention includes not only a doorway of a building but also a doorway to a space owned by a tenant such as an office on each floor. The information of the doorway is included in the architectural model data 111. Then, the flow of people in the building may be estimated by recognizing a door or a tenant area included in the architectural model data 111, or may be designated manually. From this floor information, it is possible to recognize a passable space of the elevator platform.
First, the measurement unit 140 acquires the image data measured by the camera or the like as a measurement result (step S1201).
Then, the measurement unit 140 recognizes the position of people from each piece of image data acquired in step S1201 (step S1202). Here, in order to recognize the position of people from the image data, a widely known general image recognition method or a method such as machine learning is used.
Next, the position of people recognized from each piece of the image data is mapped on a plan view (step S1203). In order to perform mapping on the plan view, it is necessary to convert the position of people in the coordinate system of the image data into the coordinate system on the plan view.
Therefore, first, the distance to the position of the people recognized from the installation position of the measurement unit 140 is estimated according to the magnitude of the size of people recognized in the image. Then, conversion to the coordinate system on the plan view is performed using the estimated distance information, the position of the coordinate system of the image data, the coordinates and orientation of the installation position of the measurement unit 140, and the information of the angle of view of the measurement unit 140. Note that the coordinate system conversion method is not limited to the method described here. Other methods can also be used.
Next, the density of each position on the plan view is calculated on the basis of the positions of people on the plan view obtained from each piece of the image data (step S1204). The density of people on a plane refers to a value obtained by calculating a ratio of the number of pieces of data of existing people to the number of pieces of measured image data for each position to be measured. The result of calculating the density of people in step S1204 has already been described with reference to
Finally, the position having a high people density is calculated, and the position where the density is high and the distance to the elevator is short is output as the front-of-line position (step S1205). It is sufficient if the position having a high people density is determined on the basis of whether a preset threshold is exceeded. Note that a preset value may be used as the threshold, or the threshold may be dynamically changed according to the date and time or the time zone. In addition, the threshold can be changed depending on a position or a place. For example, it is also conceivable to change the threshold depending on the distance from a wall.
In addition, since it is not particularly necessary for the elevator users to line up during the time when the elevator platform is not crowded, it is not necessary to measure the front-of-line position. Therefore, the front-of-line position may be calculated only from a measurement result with a limited time zone such as the time zone at the time of going to work or leaving work and the time zone at lunch time. In addition, a certain threshold may be set for the density of people, and the front-of-line position may be estimated with respect to the measurement result for the time zone in which the density exceeds the threshold.
The front-of-line position estimation processing has been described above.
As described above, according to the present invention, in the architectural model data assistance system, it is possible to realize the architectural model data assistance system that estimates the front-of-line position by the measurement unit 140, uses the estimated front-of-line position and the architectural model data as inputs, and finely simulates the action of waiting at the platform or the action of orderly boarding when using the elevator in the input architectural model.
In addition, according to the present invention, in the architectural model data assistance system, it is possible to realize the architectural model data assistance system that uses the architectural model data as an input and finely simulates the action of waiting at the platform or the action of orderly boarding when using the elevator in the input architectural model without manually additionally inputting the front-of-line position or the like.
Note that the present invention is not limited to the above-described embodiments, and includes various modifications. The above-described embodiments have been described in order to describe the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to those including all the described configurations, and can be appropriately applied to other configurations.
In addition, some or all of the above-described configurations, functions, processing units, processing means, and the like may be realized by hardware, for example, by designing with an integrated circuit. In addition, each of the above-described configurations, functions, and the like may be realized by software by a processor interpreting and executing a program for realizing each function. Information such as a program, a table, and a file, and the like for realizing each function can be stored in a recording device such as memory, a hard disk, and a solid state drive (SSD), or a recording medium such as an IC card, an SD card, and a DVD, and the like.
In addition, in the drawings, control lines and information lines considered to be necessary for description are illustrated, and not all control lines and information lines of a product are necessarily illustrated. In practice, it may be considered that almost all the configurations are connected to each other.
100 Arithmetic unit
101 Architectural model data read unit
102 Front-of-line position estimation unit
103 Simulation execution unit
110 Storage unit
111 Architectural model data
112 Simulation data
113 Simulation result data
120 Input unit
130 Display unit
140 Measurement unit
Number | Date | Country | Kind |
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2019-235688 | Dec 2019 | JP | national |
Filing Document | Filing Date | Country | Kind |
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PCT/JP2020/041160 | 11/4/2020 | WO |